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genetic correlation directory

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“Genetic Architecture of the White Matter Connectome of the Human Brain”, Sha et al 2022

“Genetic architecture of the white matter connectome of the human brain”⁠, Zhiqiang Sha, Dick Schijven, Simon E. Fisher, Clyde Francks (2022-05-11; ):

White matter tracts form the structural basis of large-scale functional networks in the human brain. We applied brain-wide tractography to diffusion images from 30,810 adult participants (UK Biobank), and found significant heritability for 90 regional connectivity measures and 851 tract-wise connectivity measures. Multivariate genome-wide association analyses identified 355 independently associated lead SNPs across the genome, of which 77% had not been previously associated with human brain metrics. Enrichment analyses implicated neurodevelopmental processes including neurogenesis, neural differentiation, neural migration, neural projection guidance, and axon development, as well as prenatal brain expression especially in stem cells, astrocytes, microglia and neurons. We used the multivariate association profiles of lead SNPs to identify 26 genomic loci implicated in structural connectivity between core regions of the left-hemisphere language network, and also identified 6 loci associated with hemispheric left-right asymmetry of structural connectivity. Polygenic scores for schizophrenia, bipolar disorder, autism spectrum disorder, attention-deficit hyperactivity disorder, left-handedness, Alzheimer’s disease, amyotrophic lateral sclerosis, and epilepsy showed significant multivariate associations with structural connectivity, each implicating distinct sets of brain regions with trait-relevant functional profiles. This large-scale mapping study revealed common genetic contributions to the structural connectome of the human brain in the general adult population, highlighting links with polygenic disposition to brain disorders and behavioural traits.

“MegaBayesianAlphabet: Mega-scale Bayesian Regression Methods for Genome-wide Prediction and Association Studies With Thousands of Traits”, Qu et al 2022

“MegaBayesianAlphabet: Mega-scale Bayesian Regression methods for genome-wide prediction and association studies with thousands of traits”⁠, Jiayi Qu, Daniel E. Runcie, Hao Cheng (2022-05-08; backlinks):

Large-scale phenotype data are expected to increase the accuracy of genome-wide prediction and the power of genome-wide association analyses. However, genomic analyses of high-dimensional, highly correlated data are challenging. We developed MegaBayesianAlphabet to simultaneously analyze genetic variants underlying thousands of traits using the flexible priors of the Bayesian Alphabet family. As a demonstration, we implemented the BayesC prior in the R package MegaLMM and applied it to both simulated and real data sets. Our analyses show that the resulting model MegaBayesC can effectively use high-dimensional phenotypic data to improve the accuracy of genetic value prediction, the reliability of marker discovery, and the accuracy of marker effect size estimation in genome-wide analyses.

“Amplification Is the Primary Mode of Gene-by-Sex Interaction in Complex Human Traits”, Zhu et al 2022

“Amplification is the Primary Mode of Gene-by-Sex Interaction in Complex Human Traits”⁠, Carrie Zhu, Matthew J. Ming, Jared M. Cole, Mark Kirkpatrick, Arbel Harpak (2022-05-08):

Sexual dimorphism is observed in many complex traits and diseases and is suspected to be in part due to widespread gene-by-sex interactions (GxSex). To date, empirical evidence for GxSex in GWAS data has been elusive. We hypothesized that GxSex may be pervasive but largely missed by current approaches if it acts primarily through sex differences in the magnitude of many genetic effects (“amplification”), regulated by a shared cue such as a sex hormone, rather than differences in the identity of causal variants or the direction of their effect. To test this hypothesis, we inferred the genetic covariance structure between males and females across 27 physiological traits in the UK Biobank⁠. We found amplification to be a pervasive mode of GxSex across traits. As one example, we estimate that 38% of variants have a greater effect on urate levels in females than males. For some traits, notably those related to body mass, testosterone levels are associated with the magnitude of genetic effects in both males and females, but the association is opposite in sign between the sexes. Finally, we developed a novel test of sexually-antagonistic viability selection linking GxSex signals to allele frequency divergence between adult males and females. Using independent allele frequency data, we find marginally-significant evidence for contemporary sexually-antagonistic selection on genetic variation associated with testosterone. In summary, our results suggest that the systematic amplification of genetic effects is a common mode of GxSex that may contribute to sexual dimorphism and fuel its evolution.

“Magical Thinking in Individuals With High Polygenic Risk for Schizophrenia but No Non-affective Psychoses—a General Population Study”, Saarinen et al 2022

“Magical thinking in individuals with high polygenic risk for schizophrenia but no non-affective psychoses—a general population study”⁠, Aino Saarinen, Leo-Pekka Lyytikäinen, Jarmo Hietala, Henrik Dobewall, Veikka Lavonius, Olli Raitakari et al (2022-05-03; ⁠, ):

A strong genetic background for psychoses is well-established. Most individuals with a high genetic risk for schizophrenia⁠, however, do not develop the disorder.

We investigated whether individuals, who have a high genetic risk for schizophrenia but no non-affective psychotic disorders, are predisposed to develop milder forms of deviant thinking in terms of magical thinking⁠.

Participants came from the population-based Young Finns Study (n = 1,292). The polygenic risk score for schizophrenia (PRS) was calculated on the basis of the most recent genome-wide association study (GWAS). Psychiatric diagnoses over the lifespan were collected up to 2017 from the registry of hospital care. Magical thinking was evaluated with the Spiritual Acceptance Scale (eg. beliefs in telepathy⁠, miracles⁠, mystical events, or sixth sense) of the Temperament and Character Inventory in 1997, 2001, and 2012 (participants were 20–50-year-olds).

We found that, among those who did not develop non-affective psychotic disorders, high PRS predicted higher magical thinking in adulthood (p = 0.001). Further, PRS predicted different developmental courses: a low PRS predicted a steady decrease in magical thinking from age 20 to 50 years, while in individuals with high PRS the decrease in magical thinking ceased in middle age so that their level of magical thinking remained higher than expected for that age. These findings remained when controlling for sex, childhood family environment, and adulthood socioeconomic factors.

In conclusion, if high PRS does not lead to a non-affective psychotic disorder, it predicts milder forms of deviant thinking such as elevated magical thinking in adulthood, especially in middle age. The finding enhances our understanding of different outcomes of high genetic psychosis risk.

…In Models 1, we found that high weighted PRS (b = 0.077, p = 0.001, see Table 2) and high unweighted PRS (b = 0.082, p = 0.001, see Table 3) had a positive main effect on magical thinking (ie. high weighted and unweighted PRS predicted higher curve of magical thinking in adulthood). The statistically-significant main effects of age and age-squared indicated that the curve of magical thinking over age was curvilinear.

“The Contribution of Mate-choice, Couple Convergence and Confounding to Assortative Mating”, Sjaarda & Kutalik 2022

“The contribution of mate-choice, couple convergence and confounding to assortative mating”⁠, Jennifer Sjaarda, Zoltán Kutalik (2022-04-22):

Increased phenotypic similarity between partners, termed assortative mating (AM), has been observed for many traits. However, it is currently unclear if these observations are due to mate choice for certain phenotypes, post-mating convergence, or a result of confounding factors such as shared environment or indirect assortment. To dissect these underlying phenomena, we applied Mendelian randomisation (MR) to 51,664 couples in the UK biobank to a panel of 118 phenotypes under AM. We found that 54% (64 of 118) of the tested traits had a causal relationship between partners, with female-to-male effects on average being larger. Forty traits, including systolic blood pressure, basal metabolic rate, weight and height, showed significantly larger phenotypic correlation than MR-estimates, suggesting the presence of confounders. Subsequent analyses revealed household income, overall health rating, education and tobacco smoking as major overall confounders, accounting for 29.8, 14.1, 11.6, and 4.78%, of cross-partner phenotypic correlations, respectively. We detected limited evidence for couple-correlation convergence (eg. increased similarity with respect to smoking and medication use), measured by stratifying couples by their time spent together. Finally, mediation analysis revealed that the vast majority (>77%) of causal associations between one trait of an individual and a different trait of their partner is indirect. For example, the causal effect of the BMI of an individual on the overall health rating of their partner is entirely acting through the BMI of their partner. In summary, this study revealed many novel causal effects within couples, shedding light on the impact of confounding on couple phenotypic similarity.

“Borderline Personality Disorder and the Big Five: Molecular Genetic Analyses Indicate Shared Genetic Architecture With Neuroticism and Openness”, Streit et al 2022

“Borderline Personality Disorder and the Big Five: molecular genetic analyses indicate shared genetic architecture with Neuroticism and Openness”⁠, Fabian Streit, Stephanie H. Witt, Swapnil Awasthi, Jerome C. Foo, Martin Jungkunz, Josef Frank, Lucía Colodro-Conde et al (2022-04-11; ⁠, ):

Both environmental (eg. interpersonal traumatization during childhood and adolescence) and genetic factors may contribute to the development of Borderline Personality Disorder (BPD). Twin studies assessing borderline personality symptoms/​features in the general population indicate that genetic factors underlying these symptoms/​features are shared in part with the personality traits of the five-factor Model (FFM) of personality—the “Big Five”.

In the present study, the genetic overlap of BPD with the Big Five—Openness to Experience⁠, conscientiousness⁠, Extraversion⁠, Agreeableness⁠, and Neuroticism—was assessed. linkage disequilibrium score regression was used to calculate genetic correlations between a genome-wide association study (GWAS) in central European populations on BPD (n = 2,543) and GWAS on the Big Five (n = 76,551–122,886, Neuroticism n = 90,278). polygenic scores (PGS) were calculated to test the association of the genetic disposition for the personality traits with BPD case-control status.

Statistically-significant positive genetic correlations of BPD were found with Neuroticism (rg = 0.34, p = 6.3×10−5) and Openness (rg = 0.24, p = 0.036), but not with the other personality traits (all |rg| < 0.14, all p > 0.30). A cluster and item-level analysis showed positive genetic correlations of BPD with the Neuroticism clusters “Depressed Affect” and “Worry”, and with a broad range of Neuroticism items (n = 348,219–376,352). PGS analyses confirmed the genetic correlations, and found an independent contribution of the personality traits to BPD risk.

The observed associations indicate a partially shared genetic background of BPD and the personality traits Neuroticism and Openness. Larger GWAS of BPD and the “Big Five” are needed to further explore the role of personality traits in the etiology of BPD.

“Genetic Variants Associated With Longitudinal Changes in Brain Structure across the Lifespan”, Brouwer et al 2022

2022-brouwer.pdf: “Genetic variants associated with longitudinal changes in brain structure across the lifespan”⁠, Rachel M. Brouwer, Marieke Klein, Katrina L. Grasby, Hugo G. Schnack, Neda Jahanshad, Jalmar Teeuw, Sophia I. Thomopoulos et al (2022-04-05; ⁠, ; similar):

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases.

In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan.

Longitudinal magnetic resonance imaging data from 15,640 individuals [in 40 cohorts] were used to compute rates of change for 15 brain structures.

The most robustly identified genes GPR139⁠, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia⁠, cognitive functioning, insomnia⁠, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes.

Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.

“Integrative Analysis of Metabolite GWAS Illuminates the Molecular Basis of Pleiotropy and Genetic Correlation”, Smith et al 2022

“Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation”⁠, Courtney J. Smith, Nasa Sinnott-Armstrong, Anna Cichońska, Heli Julkunen, Eric Fauman, Peter Würtz, Jonathan K. Pritchard et al (2022-04-04; similar):

Pleiotropy and genetic correlation are widespread features in GWAS, but they are often difficult to interpret at the molecular level.

Here, we perform GWAS of 16 metabolites clustered at the intersection of amino acid catabolism, glycolysis, and ketone body metabolism in a subset of UK Biobank. We utilize the well-documented biochemistry jointly impacting these metabolites to analyze pleiotropic effects in the context of their pathways.

Among the 213 lead GWAS hits, we find a strong enrichment for genes encoding pathway-relevant enzymes and transporters. We demonstrate that the effect directions of variants acting on biology between metabolite pairs often contrast with those of upstream or downstream variants as well as the polygenic background. Thus, we find that these outlier variants often reflect biology local to the traits.

Finally, we explore the implications for interpreting disease GWAS, underscoring the potential of unifying biochemistry with dense metabolomics data to understand the molecular basis of pleiotropy in complex traits and diseases.

“Cross-trait Assortative Mating Is Widespread and Inflates Genetic Correlation Estimates”, Border et al 2022

“Cross-trait assortative mating is widespread and inflates genetic correlation estimates”⁠, Richard Border, Georgios Athanasiadis, Alfonso Buil, Andrew Schork, Na Cai, Alexander Young, Thomas Werge et al (2022-03-23; similar):

The observation of genetic correlations between disparate traits has been interpreted as evidence of widespread pleiotropy, altered theories of human genetic architecture, and spurred considerable research activity across the natural and social sciences. Here, we introduce cross-trait assortative mating (xAM) as an alternative explanation for observed genetic correlations. We observe that xAM is common across a broad array of phenotypes and that phenotypic cross-mate correlation estimates are strongly associated with genetic correlation estimates (R2 = 76%). Then, we present theoretical and simulation-based results demonstrating that, under xAM, genetic correlation estimators yield significant estimates even for traits with entirely distinct genetic bases. We demonstrate that existing xAM plausibly accounts for substantial fractions of genetic correlation estimates in two large samples (n = 827,960). For example, previously reported genetic correlation estimates between many pairs of psychiatric disorders are fully consistent with xAM alone. Finally, we provide evidence for a history of xAM at the genetic level using a novel approach based on cross-trait even/​odd chromosome polygenic score correlations. Together, our results demonstrate that previous reports have likely overestimated the true genetic similarity between many phenotypes.

“Estimating Trans-ancestry Genetic Correlation With Unbalanced Data Resources”, Zhao et al 2022

“Estimating trans-ancestry genetic correlation with unbalanced data resources”⁠, Bingxin Zhao, Xiaochen Yang, Hongtu Zhu (2022-03-23; similar):

The aim of this paper is to propose a novel estimation method of using genetic-predicted observations to estimate trans-ancestry genetic correlations, which describes how genetic architecture of complex traits varies among populations, in genome-wide association studies (GWAS). Our new estimator corrects for prediction errors caused by high-dimensional weak GWAS signals, while addressing the heterogeneity of GWAS data across ethnicities, such as linkage disequilibrium (LD) differences, which can lead to biased findings in homogeneity-agnostic analyses. Moreover, our estimator only requires one population to have a large GWAS sample size, and the second population can only have a much smaller number of participants (for example, hundreds). It is designed to specifically address the unbalanced data resources such that the GWAS sample size for European populations is usually larger than that of non-European ancestry groups. Extensive simulations and real data analyses of 30 complex traits in the UK Biobank study show that our method is capable of providing reliable estimates of a wide range of complex traits. Our results provide deep insights into the transferability of population-specific genetic findings.

“Genetics, Leadership Position, and Well-being: An Investigation With a Large-scale GWAS”, Song et al 2022

“Genetics, leadership position, and well-being: An investigation with a large-scale GWAS”⁠, Zhaoli Song, Wen-Dong Li, Xuye Jin, Junbiao Ying, Xin Zhang, Ying Song, Hengtong Li, Qiao Fan (2022-03-14; ⁠, ; similar):

Our study presents the largest whole-genome investigation of leadership phenotypes to date.

We identified genome-wide statistically-significant loci for leadership phenotypes, which are overlapped with top hits for bipolar disorder, schizophrenia⁠, and intelligence.

Our study demonstrated the polygenic nature of leadership, the positive genetic correlations between leadership traits and a broad range of well-being indicators, and the unique association of leadership with well-being after accounting for genetic influences related to other socioeconomic status measures. Our findings offer insights into the biological underpinnings of leadership.


Twin studies document leadership role occupancy (eg. whether one holds formal supervisory or management positions) as a heritable trait. However, previous studies have been underpowered in identifying specific genes associated with this trait, which has limited our understanding of the genetic correlations between leadership and one’s well-being.

We conducted a genome-wide association study (GWAS) on individuals’ leadership phenotypes that were derived from supervisory/​managerial positions and demands among 248,640 individuals of European ancestry from the UK Biobank data…and replicated top variants in 3 independent samples [UKBB followup, Add Health Wave IV, WLS].

Among the 9 genome-wide statistically-significant loci, the identified top regions are pinpointed to previously reported GWAS loci for bipolar disorder (miR-2113/​POUSF2 and LINC01239) and schizophrenia loci (ZSWIM6). We found positive genetic correlations between leadership position and several positive well-being and health indicators, including high levels of subjective well-being, and low levels of anxiety and depression (|rg| > 0.2). Intriguingly, we observed positive genetic correlations between leadership position and some negative well-being indicators, including high levels of bipolar disorder and alcohol intake frequency. We also observed positive genetic correlations between leadership position and shortened longevity, cardiovascular diseases, and body mass index after partialling out the genetic variance attributed to either educational attainment or income. The positive genetic correlation between leadership and bipolar disorder seems potentially more pronounced for those holding senior leadership positions (rg: 0.10 to 0.24), partially due to shared genetic variants with educational attainment.

Our findings provide insights into the polygenic nature of leadership and shared genetic underpinnings between the leadership position and one’s health and well-being.

“GWAS on Birth Year Infant Mortality Rates Provides Evidence of Recent Natural Selection”, Wu et al 2022

“GWAS on birth year infant mortality rates provides evidence of recent natural selection”⁠, Yuchang Wu, Shiro Furuya, Zihang Wang, Jenna E. Nobles, Jason M. Fletcher, Qiongshi Lu (2022-03-13; ; similar):

Quantifying natural selection in human populations is a central topic in evolutionary biology and human genetics. Current studies to identify which single-nucleotide polymorphism has undergone selection suffer from limited sample sizes and large uncertainties in the timing of selection.

In this study, we advance the field by showing that a genome-wide association study (GWAS) on infant mortality rate can identify recent selection signals. Our study produces well-powered genome-wide maps for selection.

It replicates 2 selection signals that were detected in a previous study using ancient DNA, substantially improves the resolution on the timing of selection, and provides evidence for very recent selection during World War II. It also provides fundamental insights into how to interpret GWAS results.


Following more than a century of phenotypic measurement of natural selection processes, much recent work explores relationships between molecular genetic measurements and realized fitness in the next generation.

We take an innovative approach to the study of contemporary selective pressure by examining which genetic variants are “sustained” in populations as mortality exposure increases. Specifically, we deploy a so-called “regional GWAS” (genome-wide association study) that links the infant mortality rate (IMR) by place and year in the United Kingdom with common genetic variants among birth cohorts in the UK Biobank⁠. These cohorts (born between 1936 and 1970) saw a decline in IMR from above 65 to under 20 deaths per 1,000 live births, with substantial subnational variations and spikes alongside wartime exposures.

Our results show several genome-wide statistically-significant loci, including LCT and TLR10/​1/​6, related to area-level cohort IMR exposure during gestation and infancy. Genetic correlations are found across multiple domains, including fertility, cognition, health behaviors, and health outcomes, suggesting an important role for cohort selection in modern populations.

Genetic Correlation with 50 Complex Traits: We next examined genetic correlation (40) between birth year IMR and a set of 50 traits widely assessed as outcomes of selection processes (Figure 5 and Dataset S4).

Among known target traits of selection (10), we found a statistically-significant correlation with vitamin D but found null results on hair and skin color. Our results are consistent with other approaches showing correlations with genetics of fertility (age at first birth) but do not find effects for number of children ever born, age at menarche, or age at menopause. Recall that Sanjak et al 11 reported inconsistent findings between reproductive success and age at menarche (positive) and age at menopause (negative), which the authors label as “less explicable” than other results; as a comparison, we obtained null results for these 2 traits. Similar to earlier findings (6, 8), we show correlations with EA and cognition, but we extend this finding by showing these results are driven by the direct-EA component and not by the indirect-EA component mediated by family environment (ie. genetic nurture), using methods in Wu et al 41, suggesting that the selection pressure more directly applies to the child’s genetics on education rather than parental behavior that affects their children’s education. The difference in these findings suggest a broader need for caution when examining the genetic correlation findings, as we cannot decouple parental and child genetics in these results. We also find relationships with anthropometrics, like Sanjak et al 11, but substantially extend our domains of interest to show findings for cardiovascular disease, tobacco use, and a variety of mental health conditions. The null findings on birth weight are suggestive that studies linking birthweight to insults akin to those prevailing during the 1930s and 1940s in the United Kingdom are likely capturing the deleterious effects of the disease environment (and accompanying wartime conditions) during that time, versus the differential survival of pregnancies (42, 43).

“Multivariate Genetic Analysis of Personality and Cognitive Traits Reveals Abundant Pleiotropy and Improves Prediction”, Hindley et al 2022

“Multivariate genetic analysis of personality and cognitive traits reveals abundant pleiotropy and improves prediction”⁠, Guy Hindley, Alexey A. Shadrin, Dennis van der Meer, Nadine Parker, Weiqiu Cheng, Kevin S. O’Connell et al (2022-03-02; ⁠, ⁠, ; similar):

Personality and cognition are heritable mental traits, and their genetic determinants may be distributed across interconnected brain functions. However, previous studies have employed univariate approaches which reduce complex traits to summary measures.

We applied the “pleiotropy-informed” multivariate omnibus statistical test (MOSTest) to genome-wide association studies (GWAS) of 35 item and task-level measures of neuroticism and cognition from the UK Biobank (n = 336,993). We identified 431 significant genetic loci and found evidence of abundant pleiotropy across personality and cognitive domains. Functional characterisation implicated genes with significant tissue-specific expression in all tested brain tissues and enriched in brain-specific gene-sets.

We conditioned independent GWAS of the Big 5 personality traits and cognition on our multivariate findings, which boosted genetic discovery in other personality traits and improved polygenic prediction. These findings advance our understanding of the polygenic architecture of complex mental traits, indicating a prominence of pleiotropic genetic effects across higher-order domains of mental function.

“Sleep Duration and Brain Structure—phenotypic Associations and Genotypic Covariance”, Fjell et al 2022

“Sleep duration and brain structure—phenotypic associations and genotypic covariance”⁠, Anders Fjell, Oystein Sorensen, Yunpeng Wang, Inge K. Amlien, William Baare, David Bartres-Faz, Lars Bertram et al (2022-02-17; ⁠, ; similar):

The question of how much sleep is best for the brain attracts scientific and public interest, and there is concern that insufficient sleep leads to poorer brain health. However, it is unknown how much sleep is sufficient and how much is too much. We analyzed 51,295 brain magnetic resonance images from 47,039 participants, and calculated the self-reported sleep duration associated with the largest regional volumes and smallest ventricles relative to intracranial volume (ICV) and thickest cortex. 6.8 hours of sleep was associated with the most favorable brain outcome overall. Critical values, defined by 95% confidence intervals, were 5.7 and 7.9 hours. There was regional variation, with for instance the hippocampus showing largest volume at 6.3 hours. Moderately long sleep (> 8 hours) was more strongly associated with smaller relative volumes, thinner cortex and larger ventricles than even very short sleep (< 5 hours), but effect sizes were modest. People with larger ICV reported longer sleep (7.5 hours), so not correcting for ICV yielded longer durations associated with maximal volume. Controlling for socioeconomic status, body mass index and depression symptoms did not alter the associations. Genetic analyses showed that genes related to longer sleep in short sleepers were related to shorter sleep in long sleepers. This may indicate a genetically controlled homeostatic regulation of sleep duration. Mendelian randomization analyses did not suggest sleep duration to have a causal impact on brain structure in the analyzed datasets. The findings challenge the notion that habitual short sleep is negatively related to brain structure.

“Genome-wide Analyses of ADHD Identify 27 Risk Loci, Refine the Genetic Architecture and Implicate Several Cognitive Domains”, Demontis et al 2022

“Genome-wide analyses of ADHD identify 27 risk loci, refine the genetic architecture and implicate several cognitive domains”⁠, Ditte Demontis, Bragi Walters, Georgios Athanasiadis, Raymond Walters, Karen Therrien, Leila Farajzadeh et al (2022-02-16; ⁠, ; similar):

Attention deficit hyperactivity disorder (ADHD) is a prevalent childhood psychiatric disorder, with a major genetic component. Here we present a GWAS meta-analysis of ADHD comprising 38,691 individuals with ADHD and 186,843 controls. We identified 27 genome-wide statistically-significant loci, which is more than twice the number previously reported. Fine-mapping risk loci highlighted 76 potential risk genes enriched in genes expressed in brain, particularly the frontal cortex, and in early brain development. Overall, ADHD was associated with several brain specific neuronal sub-types and especially midbrain dopaminergic neurons. In a subsample of 17,896 exome-sequenced individuals, we identified increased load of rare protein-truncating variants in cases for a set of risk genes enriched with likely causal common variants, suggesting implication of SORCS3 in ADHD by both common and rare variants. We found ADHD to be highly polygenic, with around seven thousand variants explaining 90% of the SNP heritability. Bivariate Gaussian mixture modeling estimated that more than 90% of ADHD influencing variants are shared with other psychiatric disorders (autism, schizophrenia and depression) and phenotypes (eg. educational attainment) when both concordant and discordant variants are considered. Additionally, we demonstrated that common variant ADHD risk was associated with impaired complex cognition such as verbal reasoning and a range of executive functions including attention.

“A Comprehensive Map of Genetic Relationships among Diagnostic Categories Based on 48.6 Million Relative Pairs from the Danish Genealogy”, Athanasiadis et al 2022

“A comprehensive map of genetic relationships among diagnostic categories based on 48.6 million relative pairs from the Danish genealogy”⁠, Georgios Athanasiadis, Joeri J. Meijsen, Dorte Helenius, Andrew J. Schork, Andrés Ingason, Wesley K. Thompson et al (2022-02-08; ⁠, ; similar):

The ability to extract multigenerational family relationships from large-scale population cohorts provides a powerful means to understand the heritability of a wide range of diseases and their genetic relationships to each other. By showing how the heritability of broad diagnostic categories changes over time and how said categories are related on the genetic level, our analysis of the Danish genealogy and linked national patient registers illustrates the vast potential of this resource in current biomedical research.


For more than half a century, Denmark has maintained population-wide demographic, health care, and socioeconomic registers that provide detailed information on the interaction between all residents and the extensive national social services system.

We leverage this resource to reconstruct the genealogy of the entire nation based on all individuals legally residing in Denmark since 1968. We cross-reference 6,691,426 individuals with nationwide health care registers to estimate heritability and genetic correlations of 10 broad diagnostic categories involving all major organs and systems.

Heritability estimates for mental disorders were consistently the highest across demographic cohorts (average h2 = 0.406, 95% CI = [0.403, 0.408]), whereas estimates for cancers were the lowest (average h2 = 0.130, 95% CI = [0.125, 0.134]). The average genetic correlation of each of the 10 diagnostic categories with the other 9 was highest for gastrointestinal conditions (average rg = 0.567, 95% CI = [0.566, 0.567]) and lowest for urogenital conditions (average rg = 0.386, 95% CI = [0.385, 0.388]). Mental, pulmonary, gastrointestinal, and neurological conditions had similar genetic correlation profiles.

[Keywords: heritability, genetic correlation, human disease, register data, Denmark, population registry]

Figure 4: Genetic correlations of each of 10 broad diagnostic categories with the remaining 9 by demographic cohort. Only the 4 most data-rich cohorts—Silent Generation, Baby Boomers, Generation X, and Millennials—were considered. Estimates were based on averages from all available relative pairs within a radius of 3 meioses weighted by sampling variance. Blank cells correspond to correlations not statistically-significantly different from zero.

Genetic Correlations: To understand the mutual relationships between the 10 broad diagnostic categories (15), we estimated their genetic correlations (rg) by combining within-category and between-category estimates of the latent correlation into Falconer’s method (16). We considered all family relations within a radius of 3 meioses and restricted the analyses to the 4 most data-rich demographic cohorts mentioned in Genealogy Network Structure (Figure 4 and Dataset S1).

All rg except 2 were positive, and all of them except one were also statistically-significantly different from zero. Overall, rg were highly consistent between consecutive cohorts, thus further boosting confidence in the estimates (SI Appendix, Figure 7). This trend was more marked for certain diagnostic categories such as mental, pulmonary, and neurological than others. In all 10 diagnostic categories, younger cohorts showed lower rg than older generations, whereas the opposite trend was observed for heritability that consistently increased in younger cohorts (Figure 4 and SI Appendix, Dataset S1). The average rg of each of the 10 diagnostic categories with the other 9 categories was highest for gastrointestinal conditions (0.567; SE = 0.0005) and lowest for urogenital conditions (0.386; SE = 0.0008).

“Genome-wide Association Meta-analysis Identifies 29 New Acne Susceptibility Loci”, Mitchell et al 2022

“Genome-wide association meta-analysis identifies 29 new acne susceptibility loci”⁠, Brittany L. Mitchell, Jake R. Saklatvala, Nick Dand, Fiona A. Hagenbeek, Xin Li, Josine L. Min, Laurent Thomas et al (2022-02-07; ; similar):

Acne vulgaris is a highly heritable skin disorder that primarily impacts facial skin. Severely inflamed lesions may leave permanent scars that have been associated with long-term psychosocial consequences.

Here, we perform a GWAS meta-analysis comprising 20,165 individuals with acne from 9 independent European ancestry cohorts.

We identify 29 novel genome-wide statistically-significant loci and replicate 14 of the 17 previously identified risk loci, bringing the total number of reported acne risk loci to 46. Using fine-mapping and eQTL colocalisation approaches, we identify putative causal genes at several acne susceptibility loci that have previously been implicated in Mendelian hair and skin disorders, including pustular psoriasis⁠. We identify shared genetic aetiology between acne, hormone levels, hormone-sensitive cancers and psychiatric traits. Finally, we show that a polygenic risk score calculated from our results explains up to 5.6% of the variance in acne liability in an independent cohort.

Genetic correlations and causal relationships of acne with other traits: Assuming a population prevalence of 30% for acne, the genome-wide statistically-significant acne risk loci explain an estimated 6.01% of the variance in acne liability. However, estimation of heritability explained by all common SNPs⁠, i.e., the SNP-based heritability, indicates that 22.95% (s.e. = 0.02) of the variance in acne liability is explained by common genetic variation across the genome.

We utilised this extensive polygenicity to examine the genetic correlation and potential causal relationship between acne and a series of 935 human diseases and traits, finding 45 traits with statistically-significant genetic correlations (Supplementary Data 7). As has been previously observed, there is evidence of genetic correlation between acne and Crohn’s Disease (rg = 0.19, s.e. = 0.07) (Figure 2a). We also observe evidence of shared genetic architecture with disease traits that are phenotypically associated with acne; this includes breast cancer (rg = 0.16, s.e. = 0.05) and psychiatric disorders such as schizophrenia (rg = 0.18, s.e. = 0.06) and bipolar disorder (rg = 0.12, s.e. = 0.05). There is also evidence of asymmetry in the observed genetic correlation between acne and endogenous testosterone and bilirubin levels, breast cancer, joint pain and headaches (Figure 2b, Supplementary Data 7).

Figure 2: Genetic correlation and latent causal variable analysis between acne and other complex traits. All analyses were conducted using GWAS summary statistic data from 935 complex traits in the CTG-VL platform. (a) Black circles represent point estimates of LD score-based genetic correlations. Error bars indicate 95% confidence intervals. (b) Color bar indicates strength and direction of genetic correlation where red indicates a negative correlation and blue a positive correlation. Red line indicates statistical-significance threshold for multiple testing (FDR < 5%). CI: confidence intervals, GCP: Genetic causal proportion.

“Genetic Risk Factors Have a Substantial Impact on Healthy Life Years”, Jukarainen et al 2022

“Genetic risk factors have a substantial impact on healthy life years”⁠, Sakari Jukarainen, Tuomo Kiiskinen, Aki S. Havulinna, Juha Karjalainen, Mattia Cordioli, Joel T. Rämö et al (2022-01-28; ⁠, ; similar):

The impact of genetic variation on overall disease burden has not been comprehensively evaluated. Here we introduce an approach to estimate the effect of different types of genetic risk factors on disease burden quantified through disability-adjusted life years (DALYs, “lost healthy life years”). We use genetic information from 735,748 individuals with registry-based follow-up of up to 48 years. At the individual level, rare variants had higher effects on DALYs than common variants, while common variants were more relevant for population-level disease burden. Among common variants, rs3798220 (LPA) had the strongest effect, with 1.18 DALYs attributable to carrying 1 vs 0 copies of the minor allele. Belonging to top 10% vs bottom 90% of a polygenic score for multisite chronic pain had an effect of 3.63 DALYs. Carrying a deleterious rare variant in LDLR, MYBPC3, or BRCA1/​2 had an effect of around 4.1–13.1 DALYs. The population-level disease burden attributable to some common variants is comparable to the burden from modifiable risk factors such as high sodium intake and low physical activity. Genetic risk factors can explain a sizeable number of healthy life years lost both at the individual and population level, highlighting the importance of incorporating genetic information into public health efforts.

“Heritability of Justice Sensitivity”, Wang et al 2022

2022-wang.pdf: “Heritability of Justice Sensitivity”⁠, Yun Wang, Yu L. L. Luo, Michael Shengtao Wu, Yuan Zhou (2022-01-27; similar):

Justice is one of the fundamental principles in human evolution, and justice sensitivity from the pro-self (eg. as a victim) and the prosocial perspective (eg. as an observer, beneficiary, and perpetrator) matters in mental wellness and social interaction. However, the extent to which individual difference in justice sensitivity is influenced by genetic versus environmental factors remains unclear. Using a sample with 244 twin pairs, the present research attempts to determine the extent to which genetic factors play a role in the inter-individual difference of justice sensitivity as well as whether different facets of justice sensitivity, namely, pro-self and prosocial perspectives, share a common genetic basis. Results showed that (1) all facets of justice sensitivity were moderately heritable (21–33%) and that the non-shared environmental factors plus measurement error accounted for the rest of the variations (67–79%); (2) associations between the prosocial facets of justice sensitivity were driven by common genetic (rg = .50–.65) and non-shared environmental (plus measurement error; re = .24–.65) influences, whereas no significant genetic link was found between the pro-self and prosocial facets. The current findings provide novel evidence that sensitivity to injustice, especially to others’ suffering, is fundamentally grounded upon genetic origin, thereby shedding light on the nature and nurture aspects of justice behavior.

“Mendelian Randomization of Genetically Independent Aging Phenotypes Identifies LPA and VCAM1 As Biological Targets for Human Aging”, Timmers et al 2022

“Mendelian randomization of genetically independent aging phenotypes identifies LPA and VCAM1 as biological targets for human aging”⁠, Paul R. H. J. Timmers, Evgeny S. Tiys, Saori Sakaue, Masato Akiyama, Tuomo T. J. Kiiskinen, Wei Zhou et al (2022-01-20; ; similar):

Length and quality of life are important to us all, yet identification of promising drug targets for human aging using genetics has had limited success.

In the present study, we combine 6 European-ancestry genome-wide association studies of human aging traits—healthspan, father and mother lifespan, exceptional longevity, frailty index and self-rated health—in a principal component framework that maximizes their shared genetic architecture. The first principal component (aging-GIP1) captures both length of life and indices of mental and physical wellbeing.

We identify 27 genomic regions associated with aging-GIP1, and provide additional, independent evidence for an effect on human aging for loci near HTT and MAML3 using a study of Finnish and Japanese survival. Using proteome-wide, 2-sample, Mendelian randomization and colocalization, we provide robust evidence for a detrimental effect of blood levels of apolipoprotein(a) and vascular cell adhesion molecule 1 on aging-GIP1.

Together, our results demonstrate that combining multiple aging traits using genetic principal components enhances the power to detect biological targets for human aging.

“Increased Depressive and Anxiety Symptoms in Non-heterosexual Individuals: Moderation by Childhood Factors Using a Twin Design”, Oginni et al 2022

2022-oginni.pdf: “Increased depressive and anxiety symptoms in non-heterosexual individuals: Moderation by childhood factors using a twin design”⁠, Olakunle Ayokunmi Oginni, Katarina Alanko, Patrick Jern, Frühling Vesta Rijsdijk (2022-01-15; ; similar):

  • The phenotypic associations between sexual orientation and psychosocial distress (high depressive and anxiety symptoms) are not substantially moderated by recalled childhood factors increase (these include childhood gender nonconformity, early-life adversities and poor parent-child relationships).
  • Using the classical twin design, the genetic component of the relationship between sexual orientation and psychological distress increases as childhood gender nonconformity increases.
  • The individual-specific environmental influences on this relationship decrease and then increase as childhood gender nonconformity increases.
  • Genetic risk for psychological distress may manifest more readily among non-heterosexual adults who were gender-nonconforming during childhood; however, non-genetic (individual-specific) protective processes may partly mitigate this risk.

Background: Evidence indicates that minority stress does not sufficiently explain mental health disparities in non-heterosexual compared to heterosexual individuals. We investigated alternative mechanisms whereby childhood factors (childhood gender nonconformity, early-life adversities and parent-child interactions) moderate the relationships between sexual orientation and depressive and anxiety symptoms.

Methods: The sample comprised twin pairs from the Finnish Genetics of Sexuality and Aggression cohort (n = 3,166 individuals, mean age = 37.5 ± 2.93 years). Twin analyses using structural equation modelling was performed in OpenMx⁠. Specifically, we tested whether childhood factors differentially moderated the underlying genetic and environmental influences on the relationships between sexual orientation, and depressive and anxiety symptoms.

Results: The associations between non-heterosexuality, and depressive and anxiety symptoms (r = 0.09, 0.10 respectively) were statistically-significantly influenced by both genetic and environmental factors. The genetic influences explaining the relationships of sexual orientation with depressive and anxiety symptoms were maximal at high levels of childhood gender nonconformity (βA = 0.09 and 0.11 respectively) whereas the individual-specific environmental influences on these relationships were maximal at lower levels of childhood gender nonconformity (βE = −0.10).

Limitations: Childhood factors were assessed retrospectively in a cross-sectional design.

Conclusions: Childhood gender nonconformity is associated with increased genetic and decreased individual-specific environmental influences on mental health among non-heterosexual individuals. Childhood gender nonconformity may, thus, enhance genetic risk and non-genetic protective processes for depressive and anxiety symptoms among non-heterosexual individuals.

[Keywords: sexual orientation, depressive symptoms, anxiety symptoms, childhood stressors, behavior genetics]

“Multivariate Genome-wide Association Meta-analysis of over 1 Million Subjects Identifies Loci Underlying Multiple Substance Use Disorders”, Hatoum et al 2022

“Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders”⁠, Alexander S. Hatoum, Sarah M. C. Colbert, Emma C. Johnson, Spencer B. Huggett, Joseph D. Deak, Gita A. Pathak et al (2022-01-12; ; similar):

Genetic liability to substance use disorders can be parsed into loci conferring general and substance-specific addiction risk. We report a multivariate genome-wide association study that disaggregates general and substance-specific loci for problematic alcohol use, problematic tobacco use, and cannabis and opioid use disorders in a sample of 1,025,550 individuals of European and 92,630 individuals of African descent. Nineteen loci were genome-wide statistically-significant for the general addiction risk factor (addiction-rf), which showed high polygenicity. Across ancestries PDE4B was significant (among others), suggesting dopamine regulation as a cross-trait vulnerability. The addiction-rf polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions, and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis, 1 for opioids) included metabolic and receptor genes. These findings provide insight into the genetic architecture of general and substance-specific use disorder risk that may be leveraged as treatment targets.

“Associations of Parental and Perinatal Factors With Subsequent Risk of Stress-related Disorders: a Nationwide Cohort Study With Sibling Comparison”, Li et al 2022

“Associations of parental and perinatal factors with subsequent risk of stress-related disorders: a nationwide cohort study with sibling comparison”⁠, Yuchen Li, Arvid Sjölander, Huan Song, Sven Cnattingius, Fang Fang, Qian Yang, Lorena Fernández de la Cruz et al (2022; ; similar):

Little is known about the contribution of pregnancy-related parental and perinatal factors to the development of stress-related disorders. We aimed to investigate whether parental/​perinatal adversities entail higher risks of stress-related disorders in the offspring, later in life, by accounting for genetic and early environmental factors.

Based on the nationwide Swedish registers, we conducted a population-based cohort study of 3,435,747 singleton births (of which 2,554,235 were full siblings), born 1973–2008 and survived through the age of 5 years. Using both population-based and sibling-based designs, we employed Cox regression to assess the association between parental and perinatal factors with subsequent risk of stress-related disorders. We identified 55,511 individuals diagnosed with stress-related disorders in the population analysis and 37,433 in the sibling analysis.

In the population-based analysis we observed increased risks of stress-related disorders among offspring of maternal/​paternal age <25, single mothers, parity ≥4, mothers with BMI ≥ 25 or maternal smoking in early pregnancy, gestational diabetes, and offspring born moderately preterm (GA 32–36 weeks), or small-for-gestational-age.

These associations were statistically-significantly attenuated toward null in the sibling analysis. Cesarean-section was weakly associated with offspring stress-related disorders in population [hazard ratio (HR) 1.09, 95% confidence interval (CI) 1.06–1.12] and sibling analyses (HR 1.10, 95% CI 1.02–1.20).

Our findings suggest that most of the observed associations between parental and perinatal factors and risk of stress-related disorders in the population analysis are driven by shared familial environment or genetics, and underscore the importance of family designs in epidemiological studies on the etiology of psychiatric disorders.

“Shared Brain and Genetic Architectures between Mental Health and Physical Activity”, Zhang et al 2022

“Shared brain and genetic architectures between mental health and physical activity”⁠, Wei Zhang, Sarah E. Paul, Anderson Winkler, Ryan Bogdan, Janine D. Bijsterbosch (2022; ⁠, ; similar):

Physical activity is correlated with, and effectively treats various forms of psychopathology. However, whether biological correlates of physical activity and psychopathology are shared remains unclear.

Here, we examined the extent to which the neural and genetic architecture of physical activity and mental health are shared. Using data from the UK Biobank (n = 6,389), canonical correlation analysis was applied to estimate associations between the amplitude and connectivity strength of sub-networks of three major neurocognitive networks (default mode, DMN; salience, SN; central executive networks, CEN) with accelerometer-derived measures of physical activity and self-reported mental health. We estimated the genetic correlation between mental health and physical activity measures, as well as putative causal relationships by applying linkage disequilibrium score regression, genomic structural equational modeling, and latent causal variable analysis to genome-wide association summary statistics (GWAS n = 91,105–500,199).

Physical activity and mental health were associated with connectivity strength and amplitude of the DMN, SN, and CEN (all r ≥ 0.12, all p < 0.048). These neural correlates exhibited highly similar loading patterns across mental health and physical activity models even when accounting for their shared variance. This suggests a largely shared brain network architecture between mental health and physical activity. Mental health and physical activity were also genetically correlated (|rg| = 0.085–0.121), but we found no evidence for causal relationships between them.

Collectively, our findings provide empirical evidence that mental health and physical activity have shared brain and genetic architectures and suggest potential candidate sub-networks for future studies on brain mechanisms underlying beneficial effects of physical activity on mental health.

“Patient-Driven Findings of Genetic Associations for PANS and PANDAS”, Horvath & Keating 2021

2021-horvath.pdf: “Patient-Driven Findings of Genetic Associations for PANS and PANDAS”⁠, Robert Steve Horvath, Samuel Keating (2021-12-31; ⁠, ; similar):

Background: There are presently very few genetic studies for PANS (Pediatric Acute-Onset Neuropsychiatric Syndrome) or PANDAS (Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections). More work in genetic associations for PANS and PANDAS (P/​P) is needed to increase understanding of these debilitating childhood disorders that have a range of presentations.

Objective: This work represents a novel approach that aims to determine genetic associations between P/​P and other diseases, disorders and traits (hereafter referred to as phenotypes).

Methods: Consumer genetic data (23andMe⁠, AncestryDNA) for 155 patients with P/​P were obtained from consenting parents over a period from 2018 to 2020. An analysis plan for this work was registered at Open Science Framework⁠, additional genotypes imputed using Impute.me⁠, and polygenic risk scores for 1,702 phenotypes calculated for each of the 155 P/​P patients.

Results: One-sample t-tests performed across the 155 individual risk scores revealed that P/​P is statistically-significantly associated with 21 different groups of Single Nucleotide Polymorphisms (SNPs) that are in turn associated with 21 phenotypes. Some of the 21 phenotypes (see Table 3) are previously known to be related to or associated with P/​P: a group of SNPs associated with Tourette’s Syndrome⁠, and another group associated with autism spectrum disorder or Schizophrenia⁠, and a third associated with “feeling nervous” yielded t-tests with p-values of 1.2 × 10−5, 1.2 × 10−11 and 1.0 × 10−5 respectively for association with the P/​P data. This validated our analysis methodology. Our analysis also revealed novel genetic associations such as between P/​P and plasma anti-thyroglobulin levels (p = 1.3 × 10−7), between P/​P and triglycerides (p = 5.6 × 10−6), and between P/​P and Lewy body disease (p = 7.8 × 10−6), inviting further investigation into the underlying etiology of P/​P.

Conclusion: P/​P is associated with many phenotypes not previously recognized as being connected to P/​P. Further work on these connections can lead to better understanding of P/​P.

[Keywords: PANS genetic associations, PANS polygenic risk score, consumer genetics tests, imputation]

“Familial Clustering of Psychiatric Disorders and Low IQ”, Weiser et al 2021

2021-weiser.pdf: “Familial clustering of psychiatric disorders and low IQ”⁠, Mark Weiser, Or Frenkel, Daphna Fenchel, Dorit Tzur, Sven Sandin, Magdalena Janecka, Linda Levi, Michael Davidson et al (2021-12-16; ⁠, ; similar):

Background: Although the ICD and DSM differentiate between different psychiatric disorders, these often share symptoms, risk factors, and treatments. This was a population-based, case-control, sibling study examining familial clustering of all psychiatric disorders and low IQ, using data from the Israel Draft-Board Registry on all Jewish adolescents assessed between 1998 and 2014.

Methods: We identified all cases with autism spectrum disorder (ASD, n = 2128), severe intellectual disability (ID, n = 9572), attention-deficit hyperactive disorder (ADHD) (n = 3272), psychotic (n = 7902), mood (n = 9704), anxiety (n = 10 606), personality (n = 24 816), or substance/​alcohol abuse (n = 791) disorders, and low IQ (⩾2 SDs below the population mean, n = 31 186). Non-CNS control disorders were adolescents with Type-1 diabetes (n = 2427), hernia (n = 29 558) or hematological malignancies (n = 931). Each case was matched with 10 age-matched controls selected at random from the Draft-Board Registry, with replacement, and for each case and matched controls, we ascertained all full siblings. The main outcome measure was the relative recurrence risk (RRR) of the sibling of a case having the same (within-disorder RRR) or a different (across-disorder RRR) disorder.

Results: Within-disorder RRRs were increased for all diagnostic categories, ranging from 11.53 [95% confidence interval (CI): 9.23–14.40] for ASD to 2.93 (95% CI: 2.80–3.07) for personality disorders. The median across-disorder RRR between any pair of psychiatric disorders was 2.16 (95% CI: 1.45–2.43); the median RRR between low IQ and any psychiatric disorder was 1.37 (95% CI: 0.93–1.98). There was no consistent increase in across-disorder RRRs between the non-CNS disorders and psychiatric disorders and/​or low IQ.

Conclusion: These large population-based study findings suggest shared etiologies among most psychiatric disorders, and low IQ.

“A Polygenic Score for Educational Attainment Partially Predicts Voter Turnout”, Dawes et al 2021

“A polygenic score for educational attainment partially predicts voter turnout”⁠, Christopher T. Dawes, Aysu Okbay, Sven Oskarsson, Aldo Rustichini (2021-12-14; ⁠, ; similar):

The strong correlation between education and voting is among the most robust findings in social science. We show that genes associated with the propensity to acquire education are also associated with higher voter turnout. A within-family analysis suggests education-linked genes exert direct effects on voter turnout but also reveals evidence of genetic nurture in second-order elections. Our findings have important implications for the study of political inequality. Scholars have argued that parental education is the main driver of the reproduction of political inequality across generations. By separating the effect of genes from parental nurturing, our findings suggest that the roots of individual-level political inequality run deeper than family background.


Twin and adoption studies have shown that individual differences in political participation can be explained, in part, by genetic variation. However, these research designs cannot identify which genes are related to voting or the pathways through which they exert influence, and their conclusions rely on possibly restrictive assumptions.

In this study, we use 3 different US samples and a Swedish sample to test whether genes that have been identified as associated with educational attainment, one of the strongest correlates of political participation, predict self-reported and validated voter turnout.

We find that a polygenic score capturing individuals’ genetic propensity to acquire education is statistically-significantly related to turnout. The strongest associations we observe are in second-order midterm elections in the United States and European Parliament elections in Sweden, which tend to be viewed as less important by voters, parties, and the media and thus present a more information-poor electoral environment for citizens to navigate. A within-family analysis [n = 10,000 sibling pairs] suggests that individuals’ education-linked genes directly affect their voting behavior..after controlling for the EDU PGS, the effect of education shrinks by 8%–17%, signaling that genes associated with education partially confound the relationship between education and turnout…but, for second-order elections, it also reveals evidence of genetic nurture. Finally, a mediation analysis suggests that educational attainment and cognitive ability combine to account for between 41% and 63% of the relationship between the genetic propensity to acquire education and voter turnout.

[Keywords: education, voting, polygenic score, turnout, cognitive ability]

Figure 1 illustrates that the polygenic score’s explanatory power is on par with that of personal income, parental income, and parental education and accounts for about half as much variation as years of education…Another possible mediator is personality, given that the EA PGS is correlated with personality traits(34, 35), a growing literature has demonstrated personality traits to be important for turnout(36), and personality and turnout have been shown to be influenced by shared genetic factors(9, 10).

“Genetic Determinants of Liking and Intake of Coffee and Other Bitter Foods and Beverages”, Cornelis & Dam 2021

“Genetic determinants of liking and intake of coffee and other bitter foods and beverages”⁠, Marilyn C. Cornelis, Rob M. van Dam (2021-12-13; ; similar):

Coffee is a widely consumed beverage that is naturally bitter and contains caffeine⁠. Genome-wide association studies (GWAS) of coffee drinking have identified genetic variants involved in caffeine-related pathways but not in taste perception. The taste of coffee can be altered by addition of milk/​sweetener, which has not been accounted for in GWAS.

Using UK and US cohorts, we test the hypotheses that genetic variants related to taste are more strongly associated with consumption of black coffee than with consumption of coffee with milk or sweetener and that genetic variants related to caffeine pathways are not differentially associated with the type of coffee consumed independent of caffeine content.

Contrary to our hypotheses, genetically inferred caffeine sensitivity was more strongly associated with coffee taste preferences than with genetically inferred bitter taste perception. These findings extended to tea and dark chocolate.

Taste preferences and physiological caffeine effects intertwine in a way that is difficult to distinguish for individuals which may represent conditioned taste preferences.

“Genome-wide Association Study and Multi-trait Analysis of Opioid Use Disorder Identifies Novel Associations in 639,709 Individuals of European and African Ancestry.”, Deak et al 2021

“Genome-wide association study and multi-trait analysis of opioid use disorder identifies novel associations in 639,709 individuals of European and African ancestry.”⁠, Joseph D. Deak, Hang Zhou, Marco Galimberti, Daniel F. Levey, Frank Wendt, Sandra Sanchez-Roige, Alexander S. Hatoum et al (2021-12-05; ; similar):

Background: Despite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci.
Methods: We performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) ancestry, optimizing genetic informativeness by performing MTAG (Multi-trait analysis of GWAS) with genetically correlated substance use disorders (SUDs). Meta-analysis included seven cohorts: the Million Veteran Program (MVP), Psychiatric Genomics Consortium (PGC), iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total n = 639,709 (Ncases = 20,858) across ancestries. OUD cases were defined as having lifetime OUD diagnosis, and controls as anyone not known to meet OUD criteria. We estimated SNP-heritability (h2SNP) and genetic correlations (rg). Based on genetic correlation, we performed MTAG on OUD, alcohol use disorder (AUD), and cannabis use disorder (CanUD).
Results: The EUR meta-analysis identified three genome-wide statistically-significant (GWS; p≤5× 10−8) lead SNPs, one at FURIN (rs11372849; p = 9.54× 10−10) and two OPRM1 variants (rs1799971, p = 4.92× 10−09 ; rs79704991, p = 1.37× 10−08; r2 = 0.02). Rs1799971 (p = 4.91× 10−08) and another OPRM1 variant (rs9478500; p = 1.95× 10−8; r2 = 0.03) were identified in the cross-ancestry meta-analysis. Estimated h2SNP was 12.75%, with strong rg with CanUD (rg = 0.82; p = 1.14× 10−47) and AUD (rg = 0.77; p = 6.36× 10−78). The OUD-MTAG resulted in 18 GWS loci, all of which map to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes.
Conclusion: We identified multiple OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.

“Shared Components of Heritability across Genetically Correlated Traits”, Ballard & O’Connor 2021

“Shared components of heritability across genetically correlated traits”⁠, Jenna Lee Ballard, Luke Jen O’Connor (2021-11-30):

Most disease-associated genetic variants are pleiotropic, affecting multiple genetically correlated traits. Their pleiotropic associations can be mechanistically informative: if many variants have similar patterns of association, they may act via similar pleiotropic mechanisms, forming a shared component of heritability.

We developed Pleiotropic Decomposition Regression (PDR) to identify shared components and their underlying genetic variants. We validated PDR on simulated data and identified limitations of existing methods in recovering the true components.

We applied PDR to three clusters of 5–6 traits genetically correlated with coronary disease, asthma, and type II diabetes respectively, producing biologically interpretable components. For CAD, PDR identified components related to BMI, hypertension and cholesterol, and it clarified the relationship among these highly correlated risk factors. We assigned variants to components, calculated their posterior-mean effect sizes, and performed out-of-sample validation. Our posterior-mean effect sizes pool statistical power across traits and substantially boost the correlation (r2) between true and estimated effect sizes compared with the original summary statistics: by 94% and 70% for asthma and T2D out of sample, and by a predicted 300% for CAD.

“Dimensional Characterizations of Gender Diversity Are Associated With Higher Polygenic Propensity for Cognitive Performance in a Neurodiverse Sample”, Thomas et al 2021

“Dimensional characterizations of gender diversity are associated with higher polygenic propensity for cognitive performance in a neurodiverse sample”⁠, Taylor R. Thomas, Ashton J. Tener, Ji Seung Yang, John F. Strang, Jacob J. Michaelson (2021-11-24; ; similar):

Both sex and gender are characteristics that play a key role in risk and resilience in health and well-being. Current research lacks the ability to quantitatively describe gender and gender diversity, and is limited to endorsement of categorical gender identities, which are contextually and culturally dependent. A more objective, dimensional approach to characterizing gender diversity will enable researchers to advance the health of gender-diverse people by better understanding how genetic factors interact to determine health outcomes. To address this research gap, we leveraged the Gender Self-Report (GSR), a questionnaire that captures multiple dimensions of gender diversity. We then performed polygenic score associations with brain-related traits like cognitive performance, personality, and neuropsychiatric conditions. The GSR was completed by n = 818 independent adults with or without autism in the SPARK cohort, and GSR factor analysis identified two factors: Binary (divergence from gender presumed by designated sex to the opposite) and Nonbinary (divergence from male and female gender norms) Gender Diversity (BGD and NGD, respectively). We performed polygenic associations (controlling for age, sex, and autism diagnostic status) in a subset of n = 452 individuals and found higher polygenic propensity for cognitive performance was associated with greater BGD (B = 0.017, p = 0.049) and NGD (B = 0.036, p = 0.002), and higher polygenic propensity for educational attainment was also associated with greater NGD (B = 0.030, p = 0.015). We did not observe any statistically-significant associations with personality or neuropsychiatric polygenic scores in this sample. Overall, our results suggest cognitive processes and gender diversity share overlapping genetic factors, indicating the biological utility of the GSR while also underscoring the importance of quantitatively measuring gender diversity in health research contexts.

“Novel Disease Associations With Schizophrenia Genetic Risk Revealed in ~400,000 UK Biobank Participants”, Zhang et al 2021

2021-zhang.pdf: “Novel disease associations with schizophrenia genetic risk revealed in ~400,000 UK Biobank participants”⁠, Ruyue Zhang, Arvid Sjölander, Alexander Ploner, Donghao Lu, Cynthia M. Bulik, Sarah E. Bergen (2021-11-19; ; similar):

Schizophrenia is a serious mental disorder with considerable somatic and psychiatric morbidity. It is unclear whether comorbid health conditions predominantly arise due to shared genetic risk or consequent to having schizophrenia⁠.

To explore the contribution of genetic risk for schizophrenia, we analysed the effect of schizophrenia polygenic risk scores (PRS) on a broad range of health problems in 406 929 individuals with no schizophrenia diagnosis from the UK Biobank⁠. Diagnoses were derived from linked health data including primary care, hospital inpatient records, and registers with information on cancer and deaths. Schizophrenia PRS were generated and tested for associations with general health conditions, 16 ICD10 main chapters, and 603 diseases using linear and logistic regressions.

Higher schizophrenia PRS was statistically-significantly associated with poorer overall health ratings, more hospital inpatient diagnoses, and more unique illnesses. It was also statistically-significantly positively associated with 4 ICD10 chapters: mental disorders; respiratory diseases; digestive diseases; and pregnancy, childbirth and the puerperium⁠, but negatively associated with musculoskeletal disorders. 31 specific phenotypes were statistically-significantly associated with schizophrenia PRS, and the 19 novel findings include several musculoskeletal diseases, respiratory diseases, digestive diseases, varicose veins⁠, pituitary hyperfunction, and other peripheral nerve disorders. These findings extend knowledge of the pleiotropic effect of genetic risk for schizophrenia and offer insight into how some conditions often comorbid with schizophrenia arise.

Additional studies incorporating the genetic basis of hormone regulation and involvement of immune mechanisms in the pathophysiology of schizophrenia may further elucidate the biological mechanisms underlying schizophrenia and its comorbid conditions.

“Genome-wide Association Study of Cerebellar Volume”, Tissink et al 2021

“Genome-wide association study of cerebellar volume”⁠, Elleke Tissink, Siemon C. de Lange, Jeanne E. Savage, Douglas P. Wightman, Kristen Kelly, Mats Nagel et al (2021-11-04; ; similar):

Cerebellar volume is highly heritable and associated with neurodevelopmental and neurodegenerative disorders. Understanding the genetic architecture of cerebellar volume may improve our insight into these disorders. This study aims to investigate the convergence of cerebellar volume genetic associations in close detail. A genome-wide associations study for cerebellar volume was performed in a sample of 27,486 individuals from UK Biobank, resulting in 29 genome-wide statistically-significant loci and a SNP heritability of 39.82%. We pinpoint variants that have effects on amino acid sequence or cerebellar gene-expression. Additionally, 85 genome-wide statistically-significant genes were detected and tested for convergence onto biological pathways, cerebellar cell types or developmental stages. Local genetic correlations between cerebellar volume and neurodevelopmental and neurodegenerative disorders reveal shared loci with Parkinson’’s disease, Alzheimer’s disease and schizophrenia. These results provide insights into the heritable mechanisms that contribute to developing a brain structure important for cognitive functioning and mental health.

“Genome-wide Association Analyses of Individual Differences in Quantitatively Assessed Reading-related and Language-related Skills in up to 34,000 People”, Eising et al 2021

“Genome-wide association analyses of individual differences in quantitatively assessed reading-related and language-related skills in up to 34,000 people”⁠, Else Eising, Nazanin Mirza-Schreiber, Eveline L. de Zeeuw, Carol A. Wang, Dongnhu T. Truong, Andrea G. Allegrini et al (2021-11-04; ⁠, ; similar):

The use of spoken and written language is a capacity that is unique to humans. Individual differences in reading-related and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30–80%, depending on the trait. The relevant genetic architecture is complex, heterogeneous, and multifactorial, and yet to be investigated with well-powered studies.

Here, we present a multi-cohort genome-wide association study (GWAS) of 5 traits assessed individually using psychometric measures: word reading, non-word reading, spelling, phoneme awareness, and non-word repetition, with total sample sizes ranging from 13,633 to 33,959 participants aged 5–26 years (12,411 to 27,180 for those with European ancestry, defined by principal component analyses).

We identified a genome-wide statistically-significant association with word reading (rs11208009, p = 1.098 x 10–8) independent of known loci associated with intelligence or educational attainment. All five reading/​language-related traits had robust SNP-heritability estimates (0.13–0.26), and genetic correlations between them were modest to high. Using genomic structural equation modelling, we found evidence for a shared genetic factor explaining the majority of variation in word and non-word reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to non-word repetition, intelligence and educational attainment.

A multivariate GWAS was performed to jointly analyse word and non-word reading, spelling, and phoneme awareness, maximizing power for follow-up investigation. Genetic correlation analysis of multivariate GWAS results with neuroimaging traits identified association with cortical surface area of the banks of the left superior temporal sulcus, a brain region with known links to processing of spoken and written language.

Analysis of evolutionary annotations on the lineage that led to modern humans showed enriched heritability in regions depleted of Neanderthal variants.

Together, these results provide new avenues for deciphering the biological underpinnings of these uniquely human traits.

“General Dimensions of Human Brain Morphometry Inferred from Genome-wide Association Data”, Fürtjes et al 2021

“General dimensions of human brain morphometry inferred from genome-wide association data”⁠, Anna Elisabeth Fürtjes, Ryan Arathimos, Jonathan R. I. Coleman, James H. Cole, Simon R. Cox, Ian J. Deary et al (2021-10-25; ⁠, ⁠, ; backlinks; similar):

The human brain is organised into networks of interconnected regions that have highly correlated volumes. In this study, we aim to triangulate insights into brain organisation and its relationship with cognitive ability and ageing, by analysing genetic data.

We estimated general genetic dimensions of human brain morphometry within the whole brain, and 9 predefined canonical brain networks of interest. We did so based on principal components analysis (PCA) of genetic correlations among grey-matter volumes for 83 cortical and subcortical regions (nparticipants = 36,778).

We found that the corresponding general dimension of brain morphometry accounts for 40% of the genetic variance in the individual brain regions across the whole brain, and 47–65% within each network of interest. This genetic correlation structure of regional brain morphometry closely resembled the phenotypic correlation structure of the same regions. Applying a novel multivariate methodology for calculating SNP effects for each of the general dimensions identified, we find that general genetic dimensions of morphometry within networks are negatively associated with brain age (rg = −0.34) and profiles characteristic of age-related neurodegeneration, as indexed by cross-sectional age-volume correlations (r = −0.27). The same genetic dimensions were positively associated with a genetic general factor of cognitive ability (rg = 0.17–0.21 for different networks).

We have provided a statistical framework to index general dimensions of shared genetic morphometry that vary between brain networks, and report evidence for a shared biological basis underlying brain morphometry, cognitive ability, and brain ageing, that are underpinned by general genetic factors.

…This indicates that the genetic association between brain morphometry and cognitive ability was not driven by specific network configurations. Instead, dimensions of shared genetic morphometry in general indexed genetic variance relevant to larger brain volumes and a brain organisation that is advantageous for better cognitive performance. This was regardless of how many brain regions and from which regions the measure of shared genetic morphometry was extracted. This lack of differentiation between networks, in how strongly they correlate with cognitive ability, is in line with the suggestion that the total number of neurons in the mammalian cortex, which should at least partly correspond to its volume, is a major predictor of higher cognitive ability.37 These findings suggest that highly shared brain morphometry between regions, and its genetic analogue, indicate a generally bigger, and cognitively better-functioning brain.

“Genetic and Environmental Influences on Sleep-Wake Behaviours in Adolescence”, O''Callaghan et al 2021

“Genetic and Environmental Influences on Sleep-Wake Behaviours in Adolescence”⁠, Victoria S. O''Callaghan, Narelle K. Hansell, Wei Guo, Joanne S. Carpenter, Haochang Shou, Lachlan T. Strike et al (2021-10-22; ; similar):

Objectives: To investigate the influence of genetic and environmental factors on sleep-wake behaviours across adolescence.

Methods: 495 participants (aged 9 to 17; 55% females), including 93 monozygotic (MZ) and 117 dizygotic (DZ) twin pairs, and 75 unmatched twins, wore an accelerometry device and completed a sleep diary for 2 weeks.

Results: Individual differences in sleep onset, wake time, and sleep midpoint were influenced by both additive genetic (44–50% of total variance) and shared environmental (31–42%) factors, with a predominant genetic influence for sleep duration (62%) and restorative sleep (43%). When stratified into younger (aged 9–14) and older (aged 16–17) subsamples, genetic sources were more prominent in older adolescents. The moderate correlation between sleep duration and midpoint (rp = −0.43, rg = 0.54) was attributable to a common genetic source. Sleep-wake behaviours on school and non-school nights were correlated (rp = 0.44–0.72) and influenced by the same genetic and shared environmental factors. Genetic sources specific to night-type were also identified, for all behaviours except restorative sleep.

Conclusions: There were strong genetic influences on sleep-wake phenotypes, particularly on sleep timing, in adolescence. Moreover, there may be common genetic influences underlying both sleep and circadian rhythms. The differences in sleep-wake behaviours on school and non-school nights could be attributable to genetic factors involved in reactivity to environmental context.

[Keywords: sleep, adolescence, heritability, twins, genetics, actigraphy]

“Uncovering the Genetic Architecture of Broad Antisocial Behavior through a Genome-Wide Association Study Meta-analysis.”, Tielbeek et al 2021

“Uncovering the Genetic Architecture of Broad Antisocial Behavior through a Genome-Wide Association Study Meta-analysis.”⁠, Jorim J. Tielbeek, Emil Uffelmann, Benjamin S. Williams, Lucia Colodro-Conde, Eloi Gagnon, Travis T. Mallard et al (2021-10-20; ; similar):

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 25 discovery samples (n = 85,359) and five independent replication samples (n = 8,058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, p = 6.32 × 10−10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/​cJ mice) from controls (the BALB/​cByJ strain). The SNP-based heritability of ASB was 8.4% (s.e.= 1.2%). Polygenic-risk-score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial positive genetic correlations between ASB and depression (rg = 0.63), smoking (rg = 0.54) and insomnia (rg = 0.47) as well as negative correlations with indicators of life history (age at first birth (rg = −0.58), fathers age at death (rg = −0.54)) and years of schooling (rg = −0.46). Our findings provide a starting point towards identifying critical biosocial risk mechanisms for the development of ASB.

“Genetic Contribution to Concern for Nature and Pro-environmental Behavior”, Chang et al 2021

“Genetic Contribution to Concern for Nature and Pro-environmental Behavior”⁠, Chia-chen Chang, Thi Phuong Le Nghiem, Qiao Fan, Claudia L. Y. Tan, Rachel Rui Ying Oh, Brenda B. Lin et al (2021-10-20; ; similar):

Earth is undergoing a devastating extinction crisis caused by human impacts on nature, but only a fraction of society is strongly concerned and acting on the crisis. Understanding what determines people’s concern for nature, environmental movement activism, and personal conservation behavior is fundamental if sustainability is to be achieved. Despite its potential importance, the study of the genetic contribution to concern for nature and pro-environmental behaviors has been neglected.

Using a twin data set (n = 2312), we show moderate heritability (30%–40%) for concern for nature, environmental movement activism, and personal conservation behavior and high genetic correlations between them (0.6–0.7), suggesting a partially shared genetic basis.

Our results shed light on the individual variation in sustainable behaviors, highlighting the importance of understanding both the environmental and genetic components in the pursuit of sustainability.

“Rare Variant Aggregation in 148,508 Exomes Identifies Genes Associated With Proxy Alzheimer’s Disease”, Wightman et al 2021

“Rare Variant Aggregation in 148,508 Exomes Identifies Genes Associated with Proxy Alzheimer’s Disease”⁠, Douglas P. Wightman, Jeanne E. Savage, Christiaan A. de Leeuw, Iris E. Jansen, Danielle Posthuma (2021-10-18; ⁠, ; similar):

We generated a proxy Alzheimer’s disease phenotype for 148,508 individuals in the UK biobank in order to perform exome-wide rare variant aggregation analyses to identify genes associated with proxy Alzheimer’s disease. We identified four genes statistically-significantly associated with the proxy phenotype, three of which have been previously associated with clinically diagnosed Alzheimer’s disease (SORL1, TREM2, and TOMM40). We identified one gene (HEXA) which has not been previously associated with Alzheimer’s disease but is known to contribute to neurodegenerative disease. Here we show that proxy Alzheimer’s disease can capture some of the rare variant association signal for Alzheimer’s disease and can be used to highlight genes and variants of interest. The proxy phenotype allows for the utilisation of large genetic databases without clinically diagnosed Alzheimer’s disease patients to uncover variants and genes that contribute to Alzheimer’s disease.

“Genetic Map of Regional Sulcal Morphology in the Human Brain”, Sun et al 2021

“Genetic map of regional sulcal morphology in the human brain”⁠, Benjamin B. Sun, Stephanie J. Loomis, Fabrizio Pizzagalli, Natalia Shatokhina, Jodie N. Painter, Christopher N. Foley et al (2021-10-15; ; similar):

The human brain is a complex organ underlying many cognitive and physiological processes, affected by a wide range of diseases. Genetic associations with macroscopic brain structure are emerging, providing insights into genetic sources of brain variability and risk for functional impairments and disease. However, specific associations with measures of local brain folding, associated with both brain development and decline, remain under-explored. Here we carried out detailed large-scale genome-wide associations of regional brain cortical sulcal measures derived from magnetic resonance imaging data of 40,169 individuals in the UK Biobank. Combining both genotyping and whole-exome sequencing data (~12 million variants), we discovered 388 regional brain folding associations across 77 genetic loci at p < 5× 10−8, which replicated at p < 0.05. We found genes in associated loci to be independently enriched for expression in the cerebral cortex, neuronal development processes and differential regulation in early brain development. We integrated coding associations and brain eQTLs to refine genes for various loci and demonstrated shared signal in the pleiotropic KCNK2 locus with a cortex-specific KCNK2 eQTL. Genetic correlations with neuropsychiatric conditions highlighted emerging patterns across distinct sulcal parameters and related phenotypes. We provide an interactive 3D visualization of our summary associations, making complex association patterns easier to interpret, and emphasising the added resolution of regional brain analyses compared to global brain measures. Our results offer new insights into the genetic architecture underpinning brain folding and provide a resource to the wider scientific community for studies of pathways driving brain folding and their role in health and disease.

“Major Depressive Disorder and Lifestyle: Correlated Genetic Effects in Extended Twin Pedigrees”, Huider et al 2021

“Major Depressive Disorder and Lifestyle: Correlated Genetic Effects in Extended Twin Pedigrees”⁠, Floris Huider, Yuri Milaneschi, Matthijs D. van der Zee, Eco J. C. de Geus, Quinta Helmer, Brenda W. J. H. Penninx et al (2021-09-26; ; similar):

In recent years, evidence has accumulated with regard to the ubiquity of pleiotropy across the genome, and shared genetic etiology is thought to play a large role in the widespread comorbidity among psychiatric disorders and risk factors.

Recent methods investigate pleiotropy by estimating genetic correlation from genome-wide association summary statistics. More comprehensive estimates can be derived from the known relatedness between genetic relatives. Analysis of extended twin pedigree data allows for the estimation of genetic correlation for additive and non-additive genetic effects, as well as a shared household effect.

Here we conduct a series of bivariate genetic analyses in extended twin pedigree data on lifetime major depressive disorder (MDD) and 3 indicators of lifestyle, namely smoking behavior, physical inactivity, and obesity, decomposing phenotypic variance and covariance into genetic and environmental components. We analyze lifetime MDD and lifestyle data in a large multigenerational dataset of 19,496 individuals by variance component analysis in the ‘Mendel’ software.

We find genetic correlations for MDD and smoking behavior (rg = 0.249), physical inactivity (rg = 0.161), body-mass index (rg = 0.081), and obesity (rg = 0.155), which were primarily driven by additive genetic effects.

These outcomes provide evidence in favor of a shared genetic etiology between MDD and the lifestyle factors.

[Keywords: major depressive disorder, lifestyle, extended twin pedigree, variance decomposition, Mendel, genetic correlation, pleiotropy]

“Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors”, Mullins et al 2021

“Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors”⁠, Niamh Mullins, JooEun Kang, Adrian I. Campos, Jonathan R.I. Coleman, Alexis C. Edwards, Hanga Galfalvy et al (2021-09-08; ; similar):

Background: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders⁠.

Methods: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.

Results: 2 loci reached genome-wide statistical-significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program⁠. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlations with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status⁠, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with non-psychiatric traits remained largely unchanged.

Conclusions: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

[Keywords: genetic correlation, genome-wide association study, pleiotropy, polygenicity, suicide, suicide attempt]

“Robust Genetic Nurture Effects on Education: A Systematic Review and Meta-analysis Based on 38,654 Families across 8 Cohorts”, Wang et al 2021

2021-wang.pdf: “Robust genetic nurture effects on education: A systematic review and meta-analysis based on 38,654 families across 8 cohorts”⁠, Biyao Wang, Jessie R. Baldwin, Tabea Schoeler, Rosa Cheesman, Wikus Barkhuizen, Frank Dudbridge, David Bann et al (2021-09-02; similar):

Similarities between parents and offspring arise from nature and nurture. Beyond this simple dichotomy, recent genomic studies have uncovered “genetic nurture” effects, whereby parental genotypes influence offspring outcomes via environmental pathways rather than genetic transmission. Such genetic nurture effects also need to be accounted for to accurately estimate “direct” genetic effects (ie. genetic effects on a trait originating in the offspring).

Empirical studies have indicated that genetic nurture effects are particularly relevant to the intergenerational transmission of risk for child educational outcomes, which are, in turn, associated with major psychological and health milestones throughout the life course. These findings have yet to be systematically appraised across contexts. We conducted a systematic review and meta-analysis to quantify genetic nurture effects on educational outcomes.

A total of 12 studies comprising 38,654 distinct parent(s)-offspring pairs or trios from 8 cohorts reported 22 estimates of genetic nurture effects. Genetic nurture effects on offspring’s educational outcomes (βgenetic nurture = 0.08, 95% CI [0.07, 0.09]) were smaller than direct genetic effects (βdirect genetic = 0.17, 95% CI [0.13, 0.20]). Findings were largely consistent across studies. Genetic nurture effects originating from mothers and fathers were of similar magnitude, highlighting the need for a greater inclusion of fathers in educational research. Genetic nurture effects were largely explained by observed parental education and socioeconomic status, pointing to their role in environmental pathways shaping child educational outcomes.

Findings: provide consistent evidence that environmentally mediated parental genetic influences contribute to the intergenerational transmission of educational outcomes, in addition to effects due to genetic transmission.

[Keywords: educational attainment, educational achievement, genetic nurture, intergenerational transmission, meta-analysis]

“Polygenic Heterogeneity Across Obsessive-Compulsive Disorder Subgroups Defined by a Comorbid Diagnosis”, Strom et al 2021

“Polygenic Heterogeneity Across Obsessive-Compulsive Disorder Subgroups Defined by a Comorbid Diagnosis”⁠, Nora I. Strom, Jakob Grove, Sandra M. Meier, Marie Bækvad-Hansen, Judith Becker Nissen, Thomas Damm Als et al (2021-08-31; ; similar):

Among patients with obsessive-compulsive disorder (OCD), 65–85% manifest another psychiatric disorder concomitantly or at some other time point during their life. OCD is highly heritable, as are many of its comorbidities. A possible genetic heterogeneity of OCD in relation to its comorbid conditions, however, has not yet been exhaustively explored.

We used a framework of different approaches to study the genetic relationship of OCD with 3 commonly observed comorbidities, namely major depressive disorder (MDD), attention-deficit hyperactivity disorder (ADHD), and autism spectrum disorder (ASD).

First, using publicly available summary statistics from large-scale genome-wide association studies, we compared genetic correlation patterns for OCD, MDD, ADHD, and ASD with 861 somatic and mental health phenotypes. Secondly, we examined how polygenic risk scores (PRS) of 8 traits that showed heterogeneous correlation patterns with OCD, MDD, ADHD, and ASD partitioned across comorbid subgroups in OCD using independent unpublished data from the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH). The comorbid subgroups comprised of patients with only OCD (n = 366), OCD and MDD (n = 1,052), OCD and ADHD (n = 443), OCD and ASD (n = 388), and OCD with more than 1 comorbidity (n = 429).

We found that PRS of all traits but BMI were statistically-significantly associated with OCD across all subgroups (Neuroticism: p = 1.19 × 10−32, bipolar disorder: p = 7.51 × 10−8, anorexia nervosa: p = 3.52 × 10−20, age at first birth: p = 9.38 × 10−5, educational attainment: p = 1.56 × 10−4, OCD: p = 1.87 × 10−6, insomnia: p = 2.61 × 10−5, BMI: p = 0.15). For age at first birth, educational attainment, and insomnia PRS estimates statistically-significantly differed across comorbid subgroups (p = 2.29 × 10−4, p = 1.63 × 10−4, and p = 0.045, respectively). Especially for anorexia nervosa, age at first birth, educational attainment, insomnia, and neuroticism the correlation patterns that emerged from genetic correlation analysis of OCD, MDD, ADHD, and ASD were mirrored in the PRS associations with the respective comorbid OCD groups.

Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across OCD comorbid subgroups.

“Why Are Some People More Jealous Than Others? Genetic and Environmental Factors”, Kupfer et al 2021

“Why are some people more jealous than others? Genetic and environmental factors”⁠, Tom R. Kupfer, Morgan J. Sidari, Brendan P. Zietsch, Patrick Jern, Joshua M. Tybur, Laura W. Wesseldijk et al (2021-08-27; ; similar):

[see also “Individual Aesthetic Preferences for Faces Are Shaped Mostly by Environments, Not Genes”⁠, Germine et al 2015] Research on romantic jealousy has traditionally focused on sex differences.

We investigated why individuals vary in romantic jealousy, even within the sexes, using a genetically informed design of ~7,700 Finnish twins and their siblings. First, we estimated genetic, shared environmental and nonshared environmental influences on jealousy. Second, we examined relations between jealousy and several variables that have been hypothesized to relate to jealousy because they increase the risk (eg. mate-value discrepancy) or costs (eg. restricted sociosexuality) of infidelity.

Jealousy was 29% heritable, and non-shared environmental influences explained the remaining variance. The magnitude and sources of genetic influences did not differ between the sexes. Jealousy was associated with: having a lower mate value relative to one’s partner; having less trust in one’s current partner; having been cheated by a previous or current partner; and having more restricted sociosexual attitude and desire. Within monozygotic twin pairs, the twin with more restricted sociosexual desire and less trust in their partner than his or her co-twin experienced statistically-significantly more jealousy, showing that these associations were not merely due to the same genes or family environment giving rise to both sociosexual desire or trust and jealousy. The association between sociosexual attitude and jealousy was predominantly explained by genetic factors (74%), whereas all other associations with jealousy were mostly influenced by nonshared environmental (non-familial) factors (estimates >71%).

Overall, our findings provide some of the most robust support to date on the importance of variables predicted by mate-guarding accounts to explain why people vary in jealousy.

[Keywords: jealousy, twins, mate value discrepancy, trust, infidelity, sociosexuality, individual differences, genetics]

3.4. Do these factors still influence romantic jealousy when controlling for familial confounding? The follow-up discordant-twin analyses showed that, within monozygotic twins, the twin with a more restricted sociosexual desire experienced higher jealousy (β = −0.18, p < 0.001, n = 455), and the twin who rated their partner more trustworthy reported lower jealousy (β = −0.15, p < 0.01, n = 224 discordant twins) than his or her co-twin. The effects of sociosexual attitude (β = −0.09, p = 0.08; n = 455), having been cheated on in the past (β = 0.08, p = 0.08; n = 196), having been cheated on in the current relationship (β = 0.02, p = 0.79; n = 17), and mate value discrepancy (β = 0.04, p = 0.50, n = 228), were not statistically-significant when controlling for genetic and shared environmental confounding. However, the regression betas from the discordant-twin design analyses were similar in size to the betas from the regression analyses with the full sample that were reported in Table 4⁠. These co-twin control results should be interpreted in light of the far lower statistical power in these analyses compared to the regressions using the full sample.

The bivariate twin analyses showed that the majority of the association between jealousy and the predictors was influenced by nonshared environmental factors (all estimates above 71%) and not by familial factors, with the exception of the association between jealousy and sociosexual attitude, which was mostly explained by genetic factors (74%) (see right side of Table 3).

Discussion:…The finding that familial environmental influences did not influence jealousy has theoretical implications. According to influential accounts of attachment theory⁠, mental models of relationship expectations are transmitted from parents to children, through learning during infancy (Fonagy & Target 2005; Van IJzendoorn 1995; Verhage et al 2016; c.f., Barbaro et al 2017), and these mental models later determine emotion reactions, including jealousy, towards perceived relationship threats in adulthood (Mikulincer & Shaver 2005; Sharpsteen & Kirkpatrick 1997). Our finding that variation in jealousy is not influenced by familial environmental factors, which includes parenting, is inconsistent with these accounts. An implication is that research that seeks to understand variation in—and the development of—jealousy should attend more to genetic and nonshared environmental influences than to shared environmental factors such as parenting behavior. However, one caveat is that a limitation of twin studies is that they do not control for genetic and environmental interplay (for example, parental genes shaping the twin’s family environment) which can confound the estimate of the influence of the family environment (Keller et al 2010). Therefore, it is safest to say that we found no influence of the family environment ‘independent of genetic factors’ (Turkheimer et al 2005).

In contrast to attachment theory’s parental transmission account, mate-guarding perspectives hypothesize that jealousy should be primarily influenced by factors that increase the risk of infidelity by one’s mate (Buss 2013). These will often be socio-ecological variables (eg. the attractiveness of one’s mate, or the number of rivals in one’s environment) which presumably derive more from the nonshared environment than the shared environment. Our finding of a substantial nonshared environmental influence on variation in jealousy is therefore consistent with mate-guarding accounts (though not uniquely consistent with those accounts). Note, however, that the estimate of the nonshared environment also includes measurement error⁠.

“On the Genetic and Environmental Relationship Between Suicide Attempt and Death by Suicide”, Edwards et al 2021

2021-edwards.pdf: “On the Genetic and Environmental Relationship Between Suicide Attempt and Death by Suicide”⁠, Alexis C. Edwards, Henrik Ohlsson, Eve Mościcki, Casey Crump, Jan Sundquist, Paul Lichtenstein, Kenneth S. Kendler et al (2021-07-14; similar):

Objective: The authors examined the extent to which the genetic and environmental etiology of suicide attempt and suicide death is shared or unique.

Methods: The authors used Swedish national registry data for a large cohort of twins, full siblings, and half siblings (n = 1,314,990) born between 1960 and 1990 and followed through 2015. They conducted twin-family modeling of suicide attempt and suicide death to estimate heritability for each outcome, along with genetic and environmental correlations between them. They further assessed the relationship between suicide attempt by young people compared with adults.

Results: In bivariate models, suicide attempt and death were moderately heritable among both women (attempt: additive genetic variance component [A] = 0.52, 95% CI = 0.44, 0.56; death: A = 0.45, 95% CI = 0.39, 0.59) and men (attempt: A = 0.41, 95% CI = 0.38, 0.49; death: A = 0.44, 95% CI = 0.43, 0.44). The outcomes were substantially, but incompletely, genetically correlated (women: rA = 0.67, 95% CI = 0.55, 0.67; men: rA = 0.74, 95% CI = 0.63, 0.87). Environmental correlations were weaker (women: rE = 0.36, 95% CI = 0.29, 0.45; men: rE = 0.21, 95% CI = 0.19, 0.27). Heritability of suicide attempt was stronger among people ages 10–24 (A = 0.55–0.62) than among those age 25 and older (A = 0.36–0.38), and the genetic correlation between attempt during youth and during adulthood was stronger for women (rA = 0.79, 95% CI = 0.72, 0.79) than for men (rA = 0.39, 95% CI = 0.26, 0.47).

Conclusions: The genetic and environmental etiologies of suicide attempt and death are partially overlapping, exhibit modest sex differences, and shift across the life course. These differences must be considered when developing prevention efforts and risk prediction algorithms. Where feasible, suicide attempt and death should be considered separately rather than collapsed, including in the context of gene identification efforts.

“Early Life Antibiotic Exposure and the Subsequent Risk of Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder: A Systematic Review and Meta-Analysis”, Yu et al 2021

2021-yu.pdf: “Early Life Antibiotic Exposure and the Subsequent Risk of Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder: A Systematic Review and Meta-Analysis”⁠, Hai-ying Yu, Yuan-yue Zhou, Li-ya Pan, Xue Zhang, Hai-yin Jiang (2021-06-03; similar):

This study was conducted to assess this association between early life antibiotic exposure and the risk of autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) in later life.

The results showed that early life antibiotic exposure was associated with an increased risk of ASD (OR = 1.13, 95% confidence interval (CI): 1.07–1.21) or ADHD (OR = 1.18, 95% CI: 1.1–1.27). However, this association for ASD (OR = 1.04, 95% CI: 0.97–1.11) or ADHD (OR = 0.98, 95% CI: 0.94–1.02) disappeared when data from sibling-matched studies were pooled.

The statistically-significant association between early life antibiotic exposure and ASD or ADHD in later life can be partially explained by unmeasured genetic and familial confounding factors.

“Genetically Proxied Diurnal Preference, Sleep Timing, and Risk of Major Depressive Disorder”, Daghlas et al 2021

2021-daghlas.pdf: “Genetically Proxied Diurnal Preference, Sleep Timing, and Risk of Major Depressive Disorder”⁠, Iyas Daghlas, Jacqueline M. Lane, Richa Saxena, Céline Vetter (2021-05-26; ; backlinks; similar):

  • Question: Does a tendency toward sleeping and waking earlier have a potential causal role in reducing the risk of major depressive disorder?
  • Findings: This 2-sample Mendelian randomization analysis of data from nearly 840 000 adults of European ancestry found an association between earlier sleep timing patterns and lower risk of major depressive disorder.
  • Meaning: These data suggest that sleep timing patterns are a risk factor for major depressive disorder, and they should be examined further in randomized clinical trials of sleep interventions.
  • Importance: Morning diurnal preference is associated with reduced risk of major depressive disorder (MDD); however, causality in this association is uncertain.
  • Objective: To examine the association of genetically proxied morning diurnal preference with depression risk using Mendelian randomization.

Design, Setting, and Participants: This 2-sample Mendelian randomization study used summary-level genetic associations with diurnal preference and MDD. Up to 340 genetic loci associated with diurnal preference in a meta-analysis of the UK Biobank and 23andMe cohorts were considered as genetic proxies for diurnal preference. The effect size of these variants was scaled using genetic associations with accelerometer-based measurement of sleep midpoint. Genetic associations with MDD were obtained from a meta-analysis of genome-wide association studies data from the Psychiatric Genomics Consortium and UK Biobank. The inverse-variance weighted method was used to estimate the association of genetically proxied morning diurnal preference, corresponding to a 1-hour earlier sleep midpoint, with MDD risk.

Exposures: Morning diurnal preference scaled to a 1-hour earlier, objectively measured sleep midpoint.

Main Outcomes and Measures: Risk of MDD, including self-reported and clinically diagnosed cases, as ascertained in meta-analyses of genome-wide association studies.

Results: A total of 697 828 individuals (all of European ancestry) were in the UK Biobank and 23andMe cohorts; 85 502 in the UK Biobank had measurements of the sleep midpoint. A further 170 756 individuals with MDD and 329 443 control participants (all of European ancestry) were in the Psychiatric Genomics Consortium and UK Biobank data. Genetically proxied earlier diurnal preference was associated with a 23% lower risk of depression (odds ratio [OR] per 1-hour earlier sleep midpoint, 0.77 [95% CI, 0.63–0.94]; p = 0.01). This association was similar when restricting analysis to individuals with MDD as stringently defined by the Psychiatric Genomics Consortium (OR, 0.73 [95% CI, 0.54–1.00]; p = 0.05) but not statistically-significant when defined by hospital-based billing codes in the UK Biobank (OR, 0.64 [95% CI, 0.39–1.06]; p = 0.08). Sensitivity analyses examining potential bias due to pleiotropy or reverse causality showed similar findings (eg. intercept [SE], 0.00 [0.001]; p = 0.66 by Egger intercept test).

Conclusions and Relevance: The results of this Mendelian randomization study support a protective association of earlier diurnal preference with risk of MDD and provide estimates contextualized to an objective sleep timing measure. Further investigation in the form of randomized clinical trials may be warranted. [See also how sleep deprivation can temporarily relieve depression (Boland et al 2017)]

“Dissecting Polygenic Signals from Genome-wide Association Studies on Human Behaviour”, Abdellaoui & Verweij 2021

2021-abdellaoui.pdf: “Dissecting polygenic signals from genome-wide association studies on human behaviour”⁠, Abdel Abdellaoui, Karin J. H. Verweij (2021-05-13; similar):

Genome-wide association studies on human behavioural traits are producing large amounts of polygenic signals with substantial predictive power and potentially useful biological clues. Behavioural traits are more distal and are less directly under biological control compared with physical characteristics, which makes the associated genetic effects harder to interpret.

The results of genome-wide association studies for human behaviour are likely made up of a composite of signals from different sources. While sample sizes continue to increase, we outline additional steps that need to be taken to better delineate the origin of the increasingly stronger polygenic signals. In addition to genetic effects on the traits themselves, the major sources of polygenic signals are those that are associated with correlated traits, environmental effects and ascertainment bias.

Advances in statistical approaches that disentangle polygenic effects from different traits as well as extending data collection to families and social circles with better geographic coverage will probably contribute to filling the gap of knowledge between genetic effects and behavioural outcomes.

“The Relationship between Cannabis and Schizophrenia: a Genetically Informed Perspective”, Johnson et al 2021

2021-johnson.pdf: “The relationship between cannabis and schizophrenia: a genetically informed perspective”⁠, Emma C. Johnson, Alexander S. Hatoum, Joseph D. Deak, Renato Polimanti, Robin M. Murray, Howard J. Edenberg et al (2021-05-05; ⁠, ; similar):

Background and Aims: While epidemiological studies support a role for heavy, high-potency cannabis use on first-episode psychosis, genetic models of causation suggest reverse causal effects of schizophrenia on cannabis use liability. We estimated the genetic relationship between cannabis use disorder (CUD) and schizophrenia (SCZ) and tested whether liability for CUD is causally associated with increased liability to SCZ while adjusting for tobacco smoking.

Design: This study used summary statistics from published genome-wide association studies (GWAS). We used genomic structural equation modeling (GSEM)⁠, latent causal variable (LCV) analysis⁠, and multivariable Mendelian randomization to examine genetic relationships between CUD, cannabis ever-use, ever-smoked tobacco regularly, nicotine dependence and SCZ, and to test for a causal relationship between liability to CUD and liability to SCZ.

Setting: Genome-wide association studies were published previously as part of international consortia.

Participants: Sample sizes of the GWAS summary statistics used in this study ranged from 161 405 to 357 806 individuals of European ancestry.

Measurements: Genome-wide summary statistics for CUD and SCZ were the primary measurements, while summary statistics for cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence were included as additional variables in the genomic structural equation models and the multivariable Mendelian randomization analyses.

Findings: Genetic liability to CUD was statistically-significantly associated with SCZ [β = 0.29, 95% confidence interval (CI) = 0.11, 0.46, p = 0.001], even when accounting for cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence as simultaneous predictors. We found mixed evidence of a causal relationship, with the latent causal variable analysis finding no evidence of causality (genetic causality proportion = −0.08, 95% CI = −0.40, 0.23, p = 0.87) but the multivariable Mendelian randomization analyses suggesting a statistically-significant, risk-increasing effect of CUD on liability to SCZ (β = 0.10, 95% CI = 0.02, 0.18, p = 0.02), accounting for the additional risk factors (cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence).

Conclusions: Genetic liability for cannabis use disorder appears to be robustly associated with schizophrenia, above and beyond tobacco smoking and cannabis ever-use, with mixed evidence to support a causal relationship between cannabis use disorder and schizophrenia.

[Keywords: cannabis, genome-wide association study, genomic structural equation modeling, latent causal variable model, multivariable Mendelian randomization, schizophrenia, tobacco]

“Evidence for Specificity of Polygenic Contributions to Attainment in English, Maths and Science during Adolescence”, Donati et al 2021

“Evidence for specificity of polygenic contributions to attainment in English, maths and science during adolescence”⁠, Georgina Donati, Iroise Dumontheil, Oliver Pain, Kathryn Asbury, Emma L. Meaburn (2021-02-16; ; similar):

How well one does at school is predictive of a wide range of important cognitive, socioeconomic, and health outcomes. The last few years have shown marked advancement in our understanding of the genetic contributions to, and correlations with, academic attainment. However, there exists a gap in our understanding of the specificity of genetic associations with performance in academic subjects during adolescence, a critical developmental period.

To address this, the Avon Longitudinal Study of Parents and Children was used to conduct genome-wide association studies of standardised national English (n = 5,983), maths (n = 6,017) and science (n = 6,089) tests.

High SNP-based heritabilities (h[^2^~SNP~]{.supsub}) for all subjects were found (41–53%). Further, h[^2^~SNP~]{.supsub} for maths and science remained after removing shared variance between subjects or IQ (n = 3,197–5,895). One genome-wide statistically-significant single nucleotide polymorphism (rs952964, p = 4.86 × 10−8) and 4 gene-level associations with science attainment (MEF2C, BRINP1, S100A1 and S100A13) were identified. Rs952964 remained statistically-significant after removing the variance shared between academic subjects.

The findings highlight the benefits of using environmentally homogeneous samples for genetic analyses and indicate that finer-grained phenotyping will help build more specific biological models of variance in learning processes and abilities.

“Genetic and Environmental Architecture of Conscientiousness in Adolescence”, Takahashi et al 2021

“Genetic and environmental architecture of conscientiousness in adolescence”⁠, Yusuke Takahashi, Anqing Zheng, Shinji Yamagata, Juko Ando (2021-02-05; ; similar):

Using a genetically informative design (about 2,000 twin pairs), we investigated the phenotypic and genetic and environmental architecture of a broad construct of conscientiousness (including Conscientiousness per se, Effortful Control⁠, Self-Control [Brief Self-Control scale], and Grit).

These 4 different measures were substantially correlated; the coefficients ranged from 0.74 (0.72–0.76) to 0.79 (0.76–0.80). Univariate genetic analyses revealed that individual differences in conscientiousness measures were moderately attributable to additive genetic factors, to an extent ranging from 62 (58–65) to 64% (61–67%); we obtained no evidence that shared environmental influences were observed. Multivariate genetic analyses showed that for the 4 measures used to assess conscientiousness, genetic correlations were stronger than the corresponding non-shared environmental correlations, and that a latent common factor accounted for over 84% of the genetic variance.

Our findings suggest that individual differences in the 4 measures of conscientiousness are not distinguishable at both the phenotypic and behavioural genetic levels, and that the overlap was substantially attributable to genetic factors.

Figure 2: AE common pathway model for Conscientiousness-related measures with standardised estimates (and 95% confidence intervals) alongside bar charts for the percent variance explained.

“Why Is Personality Tied to Sleep Quality? A Biometric Analysis of Twins”, Krizan et al 2021

2021-krizan.pdf: “Why is personality tied to sleep quality? A biometric analysis of twins”⁠, Zlatan Krizan, Garrett Hisler, Robert F. Krueger, Matt McGue (2021-02-01; ; similar):

Highlights:

  • Examined genetic background and environmental experiences as reasons for ties between personality and sleep quality.
  • Among 734 twin-pairs genetic factors accounted for the majority of associations between sleep quality and traits.
  • Non-shared environmental experiences also contributed to linkages of sleep quality with some traits.
  • Genetic influences that tied traits to sleep quality were somewhat unique across traits.

Despite consistent links between personality traits and poor sleep, little is known about genetic and environmental influences that may produce them. This study examined how much genetic background and environmental experiences contributed to phenotypic linkages between personality and subjective sleep quality.

734 twin pairs from the Minnesota Study of Twin Aging and Development rated their sleep quality and provided personality reports. Bi-variate analyses revealed that genetic factors accounted for the majority of observed associations between subjective sleep quality and traits, but also that non-shared environmental experience played a role that varied across traits.

The findings strongly implicate genotype in tying subjective sleep quality to personality variation, alongside non-shared environmental influences, and suggest indicate influences unique to individual traits.

“Genome-wide Association Analyses of Post-traumatic Stress Disorder and Its Symptom Subdomains in the Million Veteran Program”, Stein et al 2021

2021-stein.pdf: “Genome-wide association analyses of post-traumatic stress disorder and its symptom subdomains in the Million Veteran Program”⁠, Murray B. Stein, Daniel F. Levey, Zhongshan Cheng, Frank R. Wendt, Kelly Harrington, Gita A. Pathak, Kelly Cho et al (2021-01-28; similar):

We conducted genome-wide association analyses of over 250,000 participants of European (EUR) and African (AFR) ancestry from the Million Veteran Program

Applying genome-wide multiple testing correction, we identified 3 statistically-significant loci in European case-control analyses and 15 loci in quantitative symptom analyses. Genomic structural equation modeling indicated tight coherence of a PTSD symptom factor that shares genetic variance with a distinct internalizing (mood-anxiety-neuroticism) factor. Partitioned heritability indicated enrichment in several cortical and subcortical regions, and imputed genetically regulated gene expression in these regions was used to identify potential drug repositioning candidates.

These results validate the biological coherence of the PTSD syndrome, inform its relationship to comorbid anxiety and depressive disorders and provide new considerations for treatment.

“A Co-Twin Control Study of the Association Between Bullying Victimization and Self-Harm and Suicide Attempt in Adolescence”, O’Reilly et al 2021

2021-oreilly.pdf: “A Co-Twin Control Study of the Association Between Bullying Victimization and Self-Harm and Suicide Attempt in Adolescence”⁠, Lauren M. O’Reilly, Erik Pettersson, Patrick D. Quinn, E. David Klonsky, Jessie R. Baldwin, Sebastian Lundström et al (2021-01-18; similar):

Purpose: The aim of the study was to investigate the magnitude of an independent association between bullying victimization and self-harm and suicide attempt in adolescence after adjusting for unmeasured and measured confounding factors.

Methods: Using the Child and Adolescent Twin Study in Sweden, we examined twins born between 1994 and 1999 (n = 13,852). Twins self-reported bullying victimization at age 15 years and self-harm and suicide attempt at age 18 years. We created a factor score of 13 bullying items, on which self-harm and suicide attempt items were regressed in three models: (1) among unrelated individuals; (2) among co-twins, in which a twin exposed to more bullying was compared with his/​her co-twin who was exposed to less; and (3) among co-twins while adjusting for indicators of childhood psychopathology.

Results: Among unrelated individuals, an one standard deviation increase in bullying victimization was associated with increased odds for self-harm (odds ratio [OR], 1.29 [95% confidence interval, 1.23–1.36]) and suicide attempt (OR, 1.68 [1.53–1.85]). Among co-twins, the odds attenuated for self-harm (OR, 1.19 [1.09–1.30]) and suicide attempt (OR, 1.39 [1.17–1.66]). Finally, when accounting for childhood psychopathology, there was a 14% (1.04–1.25) and 25% (1.03–1.52) relative increase in odds of self-harm and suicide attempt, respectively.

Conclusions: The results suggest that bullying victimization was uniquely associated with self-harm and suicide attempt over and above the confounding because of unmeasured and measured factors (ie. familial vulnerability and pre-existing psychopathy). However, magnitudes were small, suggesting that additional interventions and screenings are needed to address suicidality apart from bullying interventions.

[Keywords: bullying victimization, suicide attempt, self-harm, co-twin]

“Shared Heritability of Human Face and Brain Shape”, Naqvi et al 2021

“Shared heritability of human face and brain shape”⁠, Sahin Naqvi, Yoeri Sleyp, Hanne Hoskens, Karlijne Indencleef, Jeffrey P. Spence, Rose Bruffaerts, Ahmed Radwan et al (2021; ; similar):

Evidence from model organisms and clinical genetics suggests coordination between the developing brain and face, but the role of this link in common genetic variation remains unknown. We performed a multivariate genome-wide association study of cortical surface morphology in 19,644 individuals of European ancestry, identifying 472 genomic loci influencing brain shape, of which 76 are also linked to face shape. Shared loci include transcription factors involved in craniofacial development, as well as members of signaling pathways implicated in brain-face cross-talk. Brain shape heritability is equivalently enriched near regulatory regions active in either forebrain organoids or facial progenitors. However, we do not detect significant overlap between shared brain-face genome-wide association study signals and variants affecting behavioral-cognitive traits. These results suggest that early in embryogenesis, the face and brain mutually shape each other through both structural effects and paracrine signaling, but this interplay may not impact later brain development associated with cognitive function.

“Evidence for Shared Genetics between Physical Activity, Sedentary Behaviour and Adiposity-related Traits”, Schnurr et al 2020

2020-schnurr.pdf: “Evidence for shared genetics between physical activity, sedentary behaviour and adiposity-related traits”⁠, Theresia M. Schnurr, Bente M. Stallknecht, Thorkild I.A. Sørensen, Tuomas O. Kilpeläinen, Torben Hansen et al (2020-12-22; ; similar):

Observational, cross-sectional and longitudinal studies showed that physical activity and sedentary behaviour are associated with adiposity-related traits, apparently in a bidirectional manner. Physical activity is also suggested to suppress the genetic risk of adiposity.

Since phenotypic associations with genetic variants are not subject to reverse causation or confounding, they may be used as tools to shed light on cause and effect in this complex interdependency. We review the evidence for shared genetics of physical activity and adiposity-related traits and for gene-by-physical activity interactions on adiposity-related traits in human studies. We outline limitations, challenges and opportunities in studying and understanding of these relationships.

In summary, physical activity and sedentary behaviour are genetically correlated with body mass index and fat percentage but may not be correlated with lean body mass. Mendelian randomisation analyses show that physical activity and sedentary behaviour have bidirectional relationships with adiposity. Several studies suggest that physical activity suppresses genetic risk of adiposity. No studies have yet tested whether adiposity enhances genetic predisposition to sedentariness.

The complexity of the comprehensive causal model makes the assessment of the single or combined components challenging. Substantial progress in this field may need long-term intervention studies.

[Keywords: adiposity, genetic determinants, physical activity, sedentary behaviour]

“A Genetic Perspective on the Association between Exercise and Mental Health in the Era of Genome-wide Association Studies”, Geus 2020

“A genetic perspective on the association between exercise and mental health in the era of genome-wide association studies”⁠, Eco J. C. de Geus (2020-12-14; ; backlinks; similar):

  • Triangulation across the results from genetically informative designs supports the existence of causal effects of exercise on mental health as well as residual confounding by genetic factors that independently influence participation in regular exercise and mental health outcomes.
  • A model explaining the heritability of voluntary exercise behaviour in terms of genetic moderation of its positive mental health effects can explain how causal effects co-exist with genetic pleiotropy.
  • The model calls for further research with strategies that use genomic information to improve the success of interventions on regular exercise behaviour.

Regular exercise is associated with mental health throughout the life course but the chain-of-causality underlying this association remains contested. I review results from genetically informative designs that examine causality, including the discordant monozygotic twin design, multivariate genetic models, Mendelian Randomization⁠, and stratification on polygenic risk scores. Triangulation across the results from these and the standard designs for causal inference (RCT⁠, prospective studies) in the extant literature supports the existence of causal effects of exercise on mental health as well as residual confounding by genetic factors that independently influence participation in regular exercise and mental health outcomes. I present an update of our earlier model for the genetic determinants of voluntary exercise behaviour. The model allows causal effects of regular exercise on mental health to co-exist with genetic pleiotropy through differences in the genetic sensitivity to the mental health benefits of exercise. The model encourages research on strategies that use genomic information to improve the success of interventions on regular exercise behaviour.

[Keywords: twin study, Mendelian randomization, polygenic risk score, exercise psychology, personalized medicine]

Figure 3: Genetic correlation between exercise behaviour and mental health. Note: The higher order latent genetic factor in the oval on the left contains all sets of genetic variants that explain the heritability of regular voluntary exercise behaviour. The sets of variants that are relevant for the model (G1 through G8) are repeated in the figure close to the traits where they apply. By influencing the causal mechanisms through which exercise influences mental health, these genetic variants create a genetic correlation between exercise and mental health. This genetic pleiotropy is indicated by the large dashed arrows.

“Inclusion of Variants Discovered from Diverse Populations Improves Polygenic Risk Score Transferability”, Cavazos & Witte 2020

“Inclusion of variants discovered from diverse populations improves polygenic risk score transferability”⁠, Taylor B. Cavazos, John S. Witte (2020-12-01; ; backlinks; similar):

The majority of polygenic risk scores (PRSs) have been developed and optimized in individuals of European ancestry and may have limited generalizability across other ancestral populations. Understanding aspects of PRSs that contribute to this issue and determining solutions is complicated by disease-specific genetic architecture and limited knowledge of sharing of causal variants and effect sizes across populations.

Motivated by these challenges, we undertook a simulation study to assess the relationship between ancestry and the potential bias in PRSs developed in European ancestry populations. Our simulations show that the magnitude of this bias increases with increasing divergence from European ancestry, and this is attributed to population differences in linkage disequilibrium and allele frequencies of European-discovered variants, likely as a result of genetic drift⁠. Importantly, we find that including into the PRS variants discovered in African ancestry individuals has the potential to achieve unbiased estimates of genetic risk across global populations and admixed individuals.

We confirm our simulation findings in an analysis of hemoglobin A1c (HbA1c), asthma, and prostate cancer in the UK Biobank.

Given the demonstrated improvement in PRS prediction accuracy, recruiting larger diverse cohorts will be crucial—and potentially even necessary—for enabling accurate and equitable genetic risk prediction across populations.

[Keywords: polygenic risk scores, population genetics⁠, statistical genetics, local ancestry, GWAS]

“Integrating the Study of Personality and Psychopathology in the Context of Gene-environment Correlations across Development”, Perlstein & Waller 2020

2020-perlstein.pdf: “Integrating the study of personality and psychopathology in the context of gene-environment correlations across development”⁠, Samantha Perlstein, Rebecca Waller (2020-11-29; ⁠, ; similar):

Objective: A key principle of individual differences research is that biological and environmental factors jointly influence personality and psychopathology. Genes and environments interact to influence the emergence and stability of both normal and abnormal behavior (ie. genetic predisposition, X, is exacerbated or buffered under environmental conditions, Y, or vice versa), including by shaping the neural circuits underpinning behavior. The interplay of genes and environments is also reflected in various ways in which they are correlated (ie. rGE). That is, the same genetic factors that give rise to personality or psychopathology also shape that person’s environment.

Methods: In this review, we outline passive, evocative, and active rGE processes and review the findings of studies that have addressed rGE in relation to understanding individual differences in personality and psychopathology across development.

Results: Throughout, we evaluate the question of whether it is possible, not only to differentiate the person from their problems, but also to differentiate the person from their problems and their environment.

Conclusions: We provide recommendations for future research to model rGE and better inform our ability to study personality and psychopathology, while separating the influence of the environment.

“Genetic Predictors of Educational Attainment and Intelligence Test Performance Predict Voter Turnout”, Aarøe et al 2020

2020-aroe.pdf: “Genetic predictors of educational attainment and intelligence test performance predict voter turnout”⁠, Lene Aarøe, Vivek Appadurai, Kasper M. Hansen, Andrew J. Schork, Thomas Werge, Ole Mors, Anders D. Børglum et al (2020-11-09; similar):

Although the genetic influence on voter turnout is substantial (typically 40–50%), the underlying mechanisms remain unclear. Across the social sciences, research suggests that ‘resources for politics’ (as indexed notably by educational attainment and intelligence test performance) constitute a central cluster of factors that predict electoral participation. Educational attainment and intelligence test performance are heritable. This suggests that the genotypes that enhance these phenotypes could positively predict turnout. To test this, we conduct a genome-wide complex trait analysis of individual-level turnout. We use two samples from the Danish iPSYCH case-cohort study, including a nationally representative sample as well as a sample of individuals who are particularly vulnerable to political alienation due to psychiatric conditions (n = 13,884 and n = 33,062, respectively). Using validated individual-level turnout data from the administrative records at the polling station, genetic correlations and Mendelian randomization, we show that there is a substantial genetic overlap between voter turnout and both educational attainment and intelligence test performance.

“Use of Genetically Informed Methods to Clarify the Nature of the Association Between Cannabis Use and Risk for Schizophrenia”, Gillespie & Kendler 2020

2020-gillespie.pdf: “Use of Genetically Informed Methods to Clarify the Nature of the Association Between Cannabis Use and Risk for Schizophrenia”⁠, Nathan A. Gillespie, Kenneth S. Kendler (2020-11-04; ⁠, ; similar):

When evaluating efforts to reduce cannabis use as a means of preventing schizophrenia, the proportion of this association that is causal is critical. Given the high heritability of schizophrenia, we reviewed reports that relied on 4 genetic methods (Table) capable of addressing the nature of the cannabis-schizophrenia association. We evaluated 3 hypotheses: (1) it is entirely causal, (2) it is partly causal and partly confounded by genetic/​familial effects and/​or reverse causation, or (3) it is entirely noncausal. (We are unable to review the literature regarding short-term psychiatric effects of cannabis administration.)

Confounding here refers to genetic risks that increase the probability of both using/​misusing cannabis and schizophrenia, thereby explaining at least part of the association. In this example, reverse causality refers to a theoretical underlying mechanism in which schizophrenia liability or symptoms increase the risk of using cannabis. The first 2 methods are natural experiments, discordant relative design, and Mendelian randomization, that directly evaluate each hypothesis. The 2 other methods, linkage disequilibrium score regression (LDSR) and polygenic risks scores (PRSs), measure genetic associations, which, although less definitive, provide evidence of correlated genetic risks that undermine the plausibility of hypothesis 1.

…As summarized in the Table, when triangulating across 4 genetically informative methods, the findings, with considerable but not complete consistency, argue against hypothesis 1. Although the number of available studies is modest, there is relatively reliable evidence across multiple methods that the cannabis-schizophrenia association stems partly from shared familial/​genetic risk factors and/​or reverse causation. We also have good evidence against hypothesis 3, ie, familial/​genetic risk factors explaining all of the association. The 1 study that directly estimated the degree of familial confounding 4 suggests that it is substantial and accounts for more than half of the observed association. Results from LDSR and PRS methods suggest more modest degrees of confounding while raising the possibility of reverse causation. A prudent conclusion is that the observed cannabis-schizophrenia association in the general population may arise from some potential causal effect of cannabis on the risk of schizophrenia, while an appreciable proportion of the association is not causal. When based on associations observed in the population (ie. without control for confounders), claims made about the changes in risk for schizophrenia stemming from changing levels of cannabis use are very likely to be exaggerated and potentially substantially so.

“Multivariate Genomic Analysis of 1.5 Million People Identifies Genes Related to Addiction, Antisocial Behavior, and Health”, Linnér et al 2020

“Multivariate genomic analysis of 1.5 million people identifies genes related to addiction, antisocial behavior, and health”⁠, Richard Karlsson Linnér, Travis T. Mallard, Peter B. Barr, Sandra Sanchez-Roige, James W. Madole, Morgan N. Driver et al (2020-10-16; ; similar):

Behaviors and disorders related to self-regulation, such as substance use, antisocial conduct, and ADHD, are collectively referred to as externalizing and have a shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.5 million people, our approach is statistically more powerful than single-trait analyses and identifies more than 500 genetic loci. The identified loci were enriched for genes expressed in the brain and related to nervous system development. A polygenic score constructed from our results captures variation in a broad range of behavioral and medical outcomes that were not part of our genome-wide analyses, including traits that until now lacked well-performing polygenic scores, such as opioid use disorder, suicide, HIV infections, criminal convictions, and unemployment. Our findings are consistent with the idea that persistent difficulties in self-regulation can be conceptualized as a neurodevelopmental condition.

“Genetic Architecture of 11 Major Psychiatric Disorders at Biobehavioral, Functional Genomic, and Molecular Genetic Levels of Analysis”, Grotzinger et al 2020

“Genetic Architecture of 11 Major Psychiatric Disorders at Biobehavioral, Functional Genomic, and Molecular Genetic Levels of Analysis”⁠, Andrew D. Grotzinger, Travis T. Mallard, Wonuola A. Akingbuwa, Hill F. Ip, Mark J. Adams, Cathryn M. Lewis et al (2020-09-23; ):

We systematically interrogate the joint genetic architecture of 11 major psychiatric disorders at biobehavioral, functional genomic, and molecular genetic levels of analysis. We identify four broad factors (Neurodevelopmental, Compulsive, Psychotic, and Internalizing) that underlie genetic correlations among the disorders, and test whether these factors adequately explain their genetic correlations with biobehavioral traits. We introduce Stratified Genomic Structural Equation Modelling, which we use to identify gene sets and genomic regions that disproportionately contribute to pleiotropy, including protein-truncating variant intolerant genes expressed in excitatory and GABAergic brain cells that are enriched for pleiotropy between disorders with psychotic features. Multivariate association analyses detect a total of 152 (20 novel) independent loci which act on the four factors, and identify nine loci that act heterogeneously across disorders within a factor. Despite moderate to high genetic correlations across all 11 disorders, we find very little utility of, or evidence for, a single dimension of genetic risk across psychiatric disorders.

“The Intersection of Individual Differences, Personality Variation, & Military Service: A Twin Comparison Design”, Nedelec et al 2020

2020-nedelec.pdf: “The intersection of individual differences, personality variation, & military service: A twin comparison design”⁠, Joseph L. Nedelec, Brian B. Boutwell, Kalliopi Theocharidou (2020-09-22; ; similar):

In societies where military service is voluntary multiple factors are likely to affect the decision to enlist. Past research has produced evidence that a handful of personality and social factors seem to predict service in the military. However, recent quantitative genetic research has illustrated that enlistment in the military appears to be partially heritable and thus past research is potentially subject to genetic confounding. To assess the extent to which genetic confounding exists, the current study examined a wide range of individual-level factors using a subsample of twins (n = 1,232) from the restricted-use version of the National Longitudinal Study of Adolescent to Adult Health. The results of a series of longitudinal twin comparison models, which control for the latent sources of influence that cluster within families (ie. shared genetic and family factors), illustrated generally null findings. However, individuals with higher scores on measures of extraversion and the general factor of personality were more likely to enlist in the military, after correction for familial confounding. Nonetheless, the overall results suggest that familial confounding should be a methodological concern in this area of research, and future work is encouraged to employ genetically informed methodologies in assessments of predictors of military enlistment.

[Keywords: military enlistment, genetic confounding, twin comparison, Add Health]

“Genetic and Environmental Influences on Stressful Life Events and Their Associations With Executive Functions in Young Adulthood: A Longitudinal Twin Analysis”, Morrison et al 2020

2020-morrison.pdf: “Genetic and Environmental Influences on Stressful Life Events and their Associations with Executive Functions in Young Adulthood: A Longitudinal Twin Analysis”⁠, Claire L. Morrison, Soo Hyun Rhee, Harry R. Smolker, Robin P. Corley, John K. Hewitt, Naomi P. Friedman et al (2020-09-21; similar):

Although stress is frequently considered an environmental factor, dependent stressful life events (SLEs)—-stressors that result from one’s actions or behaviors—-may in fact be evoked by a genetic liability. It has been suggested that dependent SLEs may be partially caused by poor executive function (EFs), higher-level cognitive abilities that enable individuals to implement goal-directed behavior. We investigated the possibility of genetic and environmental overlap between SLEs and EFs in a longitudinal twin study. We found high genetic stability in the number of dependent SLEs from age 23 to age 29, suggesting that the number of dependent stressors show persistence across time due to their genetic etiology. In addition, there was a nominally statistically-significant negative genetic correlation between a Common EF latent factor and dependent SLEs at age 23. The genetic stability of dependent SLEs and association with Common EF provides insight into how some behaviors may lead to persistent stress.

[Keywords: dependent stress, independent stress, executive control, genetic correlation, behavior genetics, twins]

“Common Variants Contribute to Intrinsic Human Brain Functional Networks”, Zhao et al 2020

“Common variants contribute to intrinsic human brain functional networks”⁠, Bingxin Zhao, Tengfei Li, Stephen M. Smith, Di Xiong, Xifeng Wang, Yue Yang, Tianyou Luo, Ziliang Zhu et al (2020-09-17; ⁠, ⁠, ; similar):

The human brain remains active in the absence of explicit tasks and forms networks of correlated activity. Resting-state functional magnetic resonance imaging (rsfMRI) measures brain activity at rest, which has been linked with both cognitive and clinical outcomes. The genetic variants influencing human brain function are largely unknown.

Here we utilized rsfMRI from 44,190 individuals of multiple ancestries (37,339 in the UK Biobank) to discover and validate the common genetic variants influencing intrinsic brain activity.

We identified hundreds of novel genetic loci associated with intrinsic functional signatures (p < 2.8 × 10−11), including associations to the central executive, default mode, and salience networks involved in the triple network model of psychopathology. A number of intrinsic brain activity associated loci colocalized with brain disorder GWAS (eg. Alzheimer’s disease, Parkinson’s disease, schizophrenia) and cognition, such as 19q13.32, 17q21.31, and 2p16.1. Particularly, we detected a colocalization between one (rs429358) of the two variants in the APOE ε4 locus and function of the default mode, central executive, attention, and visual networks. Genetic correlation analysis demonstrated shared genetic influences between brain function and brain structure in the same regions. We also detected statistically-significant genetic correlations with 26 other complex traits, such as ADHD, major depressive disorder, schizophrenia, intelligence, education, sleep, subjective well-being⁠, and neuroticism.

Common variants associated with intrinsic brain activity were enriched within regulatory element in brain tissues.

““Reports of My Death Were Greatly Exaggerated”: Behavior Genetics in the Postgenomic Era”, Harden 2020

2021-harden.pdf: ““Reports of My Death Were Greatly Exaggerated”: Behavior Genetics in the Postgenomic Era”⁠, K. Paige Harden (2020-09-08; similar):

Behavior genetics studies how genetic differences among people contribute to differences in their psychology and behavior. Here, I describe how the conclusions and methods of behavior genetics have evolved in the postgenomic era in which the human genome can be directly measured. First, I revisit the first law of behavioral genetics stating that everything is heritable, and I describe results from large-scale meta-analyses of twin data and new methods for estimating heritability using measured DNA. Second, I describe new methods in statistical genetics, including genome-wide association studies and polygenic score analyses. Third, I describe the next generation of work on gene × environment interaction, with a particular focus on how genetic influences vary across sociopolitical contexts and exogenous environments. Genomic technology has ushered in a golden age of new tools to address enduring questions about how genes and environments combine to create unique human lives.

“An Exposure-Wide and Mendelian Randomization Approach to Identifying Modifiable Factors for the Prevention of Depression”, Choi et al 2020

2020-choi.pdf: “An Exposure-Wide and Mendelian Randomization Approach to Identifying Modifiable Factors for the Prevention of Depression”⁠, Karmel W. Choi, Murray B. Stein, Kristen M. Nishimi, Tian Ge, Jonathan R. I. Coleman, Chia-Yen Chen, Andrew Ratanatharathorn et al (2020-08-14; ⁠, ; similar):

Objective:: Efforts to prevent depression, the leading cause of disability worldwide, have focused on a limited number of candidate factors. Using phenotypic and genomic data from over 100,000 UK Biobank participants, the authors sought to systematically screen and validate a wide range of potential modifiable factors for depression.

Methods:: Baseline data were extracted for 106 modifiable factors, including lifestyle (eg. exercise, sleep, media, diet), social (eg. support, engagement), and environmental (eg. green space, pollution) variables. Incident depression was defined as minimal depressive symptoms at baseline and clinically-significant depression at follow-up. At-risk individuals for incident depression were identified by polygenic risk scores or by reported traumatic life events. An exposure-wide association scan was conducted to identify factors associated with incident depression in the full sample and among at-risk individuals. Two-sample Mendelian randomization was then used to validate potentially causal relationships between identified factors and depression.

Results:: Numerous factors across social, sleep, media, dietary, and exercise-related domains were prospectively associated with depression, even among at-risk individuals. However, only a subset of factors was supported by Mendelian randomization evidence, including confiding in others (odds ratio = 0.76, 95% CI = 0.67, 0.86), television watching time (odds ratio = 1.09, 95% CI = 1.05–1.13), and daytime napping (odds ratio = 1.34, 95% CI = 1.17–1.53).

Conclusions:: Using a two-stage approach, this study validates several actionable targets for preventing depression. It also demonstrates that not all factors associated with depression in observational research may translate into robust targets for prevention. A large-scale exposure-wide approach combined with genetically informed methods for causal inference may help prioritize strategies for multimodal prevention in psychiatry.

“Molecular Genetics, Risk Aversion, Return Perceptions, and Stock Market Participation”, Sias et al 2020-page-2

2020-sias.pdf#page=2: “Molecular Genetics, Risk Aversion, Return Perceptions, and Stock Market Participation”⁠, Richard Sias, Laura Starks, Harry J. Turtle (2020-08-01; ⁠, ⁠, ⁠, ; similar):

We show that molecular variation in DNA related to cognition, personality, health, and body shape, predicts an individual’s equity market participation and risk aversion⁠.

Moreover, the molecular genetic endowments predict individuals’ return perceptions, most of which we find to be strikingly biased.

The genetic endowments also strongly associate with many of the investor characteristics (eg. trust, sociability, wealth) shown to explain heterogeneity in equity market participation.

Our analysis helps elucidate why financial choices are heritable and how genetic endowments can help explain the links between financial choices, risk aversion, beliefs, and other variables known to explain stock market participation.

…Using a large panel data set from the Health and Retirement Study that includes financial, psychosocial, demographic, and genetic data for 5,130 individuals across time, we examine the role of specific genetic endowments in financial decisions. We focus on 8 genetic endowments related to cognition (Educational Attainment and General Cognition), personality (Neuroticism and Depressive Symptoms), health (Myocardial Infarctions and Coronary Artery Disease) and body type (Height and BMI) and examine how these endowments help shape observed heterogeneity in financial decisions.

…Consistent with our hypotheses, individuals with higher genetic endowments associated with Educational Attainment, General Cognition, and Height are more likely to invest in equity markets (and in addition invest a larger fraction of their wealth in risky assets) while individuals with higher genetic scores associated with Neuroticism⁠, Depressive Symptoms, Myocardial Infarction, Coronary Artery Disease, and BMI exhibit lower equity market participation. Moreover, the effect sizes are substantial—a one standard deviation higher genetic endowment for Neuroticism predicts a 3.7% lower probability of holding any equity…we find that most of the 8 genetic endowments continue to predict equity market participation choices on their own. For example, after controlling for risk aversion and beliefs, a person with an one standard deviation larger genetic endowment for Neuroticism is still 2.8% less likely to hold any equity (as compared to 3.7% before controlling for risk aversion and beliefs).

“High-definition Likelihood Inference of Genetic Correlations across Human Complex Traits”, Ning 2020

2020-ning.pdf: “High-definition likelihood inference of genetic correlations across human complex traits”⁠, Zheng Ning (2020-06-29; similar):

Genetic correlation is a central parameter for understanding shared genetic architecture between complex traits. By using summary statistics from genome-wide association studies (GWAS), linkage disequilibrium score regression (LDSC) was developed for unbiased estimation of genetic correlations. Although easy to use, LDSC only partially utilizes LD information. By fully accounting for LD across the genome, we develop a high-definition likelihood (HDL) method to improve precision in genetic correlation estimation. Compared to LDSC, HDL reduces the variance of genetic correlation estimates by about 60%, equivalent to a 2.5× increase in sample size. We apply HDL and LDSC to estimate 435 genetic correlations among 30 behavioral and disease-related phenotypes measured in the UK Biobank (UKBB). In addition to 154 statistically-significant genetic correlations observed for both methods, HDL identified another 57 statistically-significant genetic correlations, compared to only another 2 statistically-significant genetic correlations identified by LDSC. HDL brings more power to genomic analyses and better reveals the underlying connections across human complex traits.

“Specific Antisocial and Borderline Personality Disorder Criteria and General Substance Use: A Twin Study”, Rosenström et al 2020

2020-rosenstrom.pdf: “Specific Antisocial and Borderline Personality Disorder Criteria and General Substance Use: A Twin Study”⁠, Tom Rosenström, Fartein Ask Torvik, Eivind Ystrom, Steven H. Aggen, Nathan A. Gillespie, Robert F. Krueger et al (2020-06-25; ⁠, ; similar):

Antisocial (ASPD) and borderline (BPD) personality disorders (PDs) are associated with increased risk for substance use. They are “specific” risk factors among PDs in that they withstand adjusting for the other PDs, whereas the reverse does not hold. Specificity is a classic sign of causation. This empirical work addresses 3 further problems that can undermine causal inferences in personality and substance-use research: hierarchical nature of etiologic factors in psychiatry, imperfectly operationalized PD criteria, and possible genetic or environmental confounding, as seen in lack of “etiologic continuity.” We used exploratory structural equation bifactor modeling and biometric models to mitigate these problems. The participants were Norwegian adult twins of ages 19–36 years (n = 2,801). Criteria for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM–5), PDs were assessed using a structured interview. General substance-use risk was indicated by World Health Organization Composite International Diagnostic Interviewed alcohol use disorder and illicit drug use, and by self-reported regular smoking. A general risk factor for all criteria of both ASPD and BPD was the strongest individual correlate of general substance use and showed etiologic continuity, though just 3 specific PD criteria could predict substance use to the same extent. The findings indicate that a broad latent factor for both ASPD and BPD may be a specific and a genetically and environmentally unconfounded risk factor for substance use. Substance-use treatment research might benefit from attending to transdiagnostic models of ASPD, BPD, and related behavioral disinhibition.

“Does Listening to Music Increase Your Ability to Discriminate Musical Sounds?”, Wesseldijk et al 2020

2020-wesseldijk.pdf: “Does listening to music increase your ability to discriminate musical sounds?”⁠, Laura W. Wesseldijk, Fredrik Ullén, Miriam A. Mosing (2020-06-15; ):

Music listening plays an important role in the daily lives of many. It remains unclear what explains variation in how much time people spend listening to music and whether music listening improves musical auditory discrimination skills.

In 10,780 Swedish twin individuals, data were available on hours of music listening, musical engagement and musical auditory discrimination.

Genetic and shared environmental factors together explain half of the variation in music listening in both sexes. Hours of music listening was positively associated with musical auditory discrimination in both sexes and this effect was independent of whether individuals played a musical instrument. However, the effect disappeared when applying a co-twin control analysis to control for genetic and shared environmental confounding⁠.

These findings suggest that music listening may not causally improve musical auditory discrimination skills, but rather that the association is likely due to shared familial factors.

[Keywords: music listening, musical auditory discrimination, genetics, shared environment, twins]

“Genetic Associations Between Executive Functions and a General Factor of Psychopathology”, Harden et al 2020

2019-harden.pdf: “Genetic Associations Between Executive Functions and a General Factor of Psychopathology”⁠, K. Paige Harden, Laura E. Engelhardt, Frank D. Mann, Megan W. Patterson, Andrew D. Grotzinger, Stephanie L. Savicki et al (2020-06-01; similar):

Objective: Symptoms of psychopathology covary across diagnostic boundaries, and a family history of elevated symptoms for a single psychiatric disorder places an individual at heightened risk for a broad range of other psychiatric disorders. Both twin-based and genome-wide molecular methods indicate a strong genetic basis for the familial aggregation of psychiatric disease. This has led researchers to prioritize the search for highly heritable childhood risk factors for transdiagnostic psychopathology. Cognitive abilities that involve the selective control and regulation of attention, known as executive functions (EFs), are a promising set of risk factors.

Method: In a population-based sample of child and adolescent twins (n = 1,913, mean age = 13.1 years), we examined genetic overlap between both EFs and general intelligence (g) and a transdiagnostic dimension of vulnerability to psychopathology, comprising symptoms of anxiety, depression, neuroticism, aggression, conduct disorder, oppositional defiant disorder, hyperactivity, and inattention. Psychopathology symptoms in children were rated by children and their parents.

Results: Latent factors representing general EF and g were highly heritable (h2 = 86%–92%), and genetic influences on both sets of cognitive abilities were robustly correlated with transdiagnostic genetic influences on psychopathology symptoms (genetic r values ranged from −0.20 to −0.38).

Conclusion: General EF and g robustly index genetic risk for transdiagnostic symptoms of psychopathology in childhood. Delineating the developmental and neurobiological mechanisms underlying observed associations between cognitive abilities and psychopathology remains a priority for ongoing research.

[Keywords: genetics, psychiatric comorbidity, executive functions]

“Genome-wide Meta-analysis of Problematic Alcohol Use in 435,563 Individuals Yields Insights into Biology and Relationships With Other Traits”, Zhou et al 2020

2020-zhou.pdf: “Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits”⁠, Hang Zhou, Julia M. Sealock, Sandra Sanchez-Roige, Toni-Kim Clarke, Daniel F. Levey, Zhongshan Cheng et al (2020-05-25; similar):

Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is not fully understood.

We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits.

Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance.

In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits.

“Genetic and Environmental Influences on the Developmental Trajectory of Callous-unemotional Traits from Childhood to Adolescence”, Takahashi et al 2020

2020-takahashi.pdf: “Genetic and environmental influences on the developmental trajectory of callous-unemotional traits from childhood to adolescence”⁠, Yusuke Takahashi, Christopher R. Pease, Jean-Baptiste Pingault, Essi Viding (2020-05-17; similar):

Background: This study examined the genetic and environmental influences underlying baseline level and developmental course of callous-unemotional (CU) traits across childhood and adolescence.

Methods: The data on 8,958 twin pairs (3,108 MZ twin pairs and 5,850 DZ twin pairs) from the Twins Early Development Study were analysed. CU traits were assessed at ages 7, 9, 12 and 16 by mothers and analysed using a biometric latent growth model.

Results: Individual differences in the baseline level of CU traits were highly heritable (76.5%), while the heritability of the developmental course of CU traits was moderate (43.6%). The genetic influences on baseline level and developmental course of CU traits were mostly non-overlapping. Nonshared environment made a modest contribution to the baseline level of CU traits (21.7%). Nonshared environmental influences on the developmental course of CU traits were moderate (43.2%), with nearly half of them being the same as those influencing the baseline level and just over half being specific. Shared environmental effects did not contribute to systematic change across childhood and adolescence but were rather age-specific.

Conclusions: Our findings demonstrate that rather than only being conceptualized as factors of stability, genes also play a dynamic role in explaining systematic change in CU traits. Genetic effects for the initial risk and subsequent development of CU traits are not the same. In addition to genetic factors, nonshared environmental influences play an important role in explaining why some children will increase or maintain their CU traits over time, whereas other will desist. New genetic and environmental influences with age suggest that repeated, age-tailored interventions may be required throughout development to make a lasting difference in the presentation of CU traits and associated outcomes.

“Conditional GWAS Analysis to Identify Disorder-specific SNPs for Psychiatric Disorders”, Byrne et al 2020

2020-bryne.pdf: “Conditional GWAS analysis to identify disorder-specific SNPs for psychiatric disorders”⁠, Enda M. Byrne, Zhihong Zhu, Ting Qi, Nathan G. Skene, Julien Bryois, Antonio F. Pardinas, Eli Stahl, Jordan W. Smoller et al (2020-05-12; ; similar):

Substantial genetic liability is shared across psychiatric disorders but less is known about risk variants that are specific to a given disorder. We used multi-trait conditional and joint analysis (mtCOJO) to adjust GWAS summary statistics of one disorder for the effects of genetically correlated traits to identify putative disorder-specific SNP associations. We applied mtCOJO to summary statistics for five psychiatric disorders from the Psychiatric Genomics Consortium—schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit hyperactivity disorder (ADHD) and autism (AUT). Most genome-wide statistically-significant variants for these disorders had evidence of pleiotropy (ie. impact on multiple psychiatric disorders) and hence have reduced mtCOJO conditional effect sizes. However, subsets of genome-wide statistically-significant variants had larger conditional effect sizes consistent with disorder-specific effects: 15 of 130 genome-wide statistically-significant variants for schizophrenia, 5 of 40 for major depression, 3 of 11 for ADHD and 1 of 2 for autism. We show that decreased expression of VPS29 in the brain may increase risk to SCZ only and increased expression of CSE1L is associated with SCZ and MD, but not with BIP. Likewise, decreased expression of PCDHA7 in the brain is linked to increased risk of MD but decreased risk of SCZ and BIP.

“Co-aggregation and Heritability of Organ-specific Autoimmunity: a Population-based Twin Study”, Skov et al 2020

2020-skov.pdf: “Co-aggregation and heritability of organ-specific autoimmunity: a population-based twin study”⁠, Jakob Skov, Daniel Eriksson, Ralf Kuja-Halkola, Jonas Höijer, Soffia Gudbjörnsdottir, Ann-Marie Svensson et al (2020-05-01; similar):

Objective: Co-aggregation of autoimmune diseases is common, suggesting partly shared etiologies. Genetic factors are believed to be important, but objective measures of environmental vs heritable influences on co-aggregation are absent. With a novel approach to twin studies, we aimed at estimating heritability and genetic overlap in seven organ-specific autoimmune diseases.

Design: Prospective twin cohort study.

Methods: We used a cohort of 110 814 twins to examine co-aggregation and heritability of Hashimoto’s thyroiditis, atrophic gastritis, celiac disease, Graves’ disease, type 1 diabetes, vitiligo and Addison’s disease. Hazard ratios (HR) were calculated for twins developing the same or different disease as compared to their co-twin. The differences between monozygotic and dizygotic twin pairs were used to estimate the genetic influence on co-aggregation. Heritability for individual disorders was calculated using structural equational modeling adjusting for censoring and truncation of data.

Results: Co-aggregation was more pronounced in monozygotic twins (median HR: 3.2, range: 2.2–9.2) than in dizygotic twins (median HR: 2.4, range: 1.1–10.0). Heritability was moderate for atrophic gastritis (0.38, 95% CI: 0.23–0.53) but high for all other diseases, ranging from 0.60 (95% CI: 0.49–0.71) for Graves’ disease to 0.97 (95% CI: 0.91–1.00) for Addison’s disease.

Conclusions: Overall, co-aggregation was more pronounced in monozygotic than in dizygotic twins, suggesting that disease overlap is largely attributable to genetic factors. Co-aggregation was common, and twins faced up to a 10-fold risk of developing diseases not present in their co-twin. Our results validate and refine previous heritability estimates based on smaller twin cohorts.

“Need to Account for Familial Confounding in Systematic Review and Meta-analysis of Prenatal Tobacco Smoke Exposure and Schizophrenia”, Quinn et al 2020

2020-quinn.pdf: “Need to Account for Familial Confounding in Systematic Review and Meta-analysis of Prenatal Tobacco Smoke Exposure and Schizophrenia”⁠, Patrick D. Quinn, Sandra M. Meier, Brian M. D’Onofrio (2020-04-02; ; similar):

In the context of continued uncertainty regarding the long-term mental health effects of prenatal exposure to maternal smoking during pregnancy, we read with great interest the recently published meta-analysis of smoking and schizophrenia by Hunter and colleagues. Although the meta-analysis found that “exposure to prenatal smoke increased the risk of schizophrenia by 29%” (p. 3), the authors noted that “familial confounding may explain some of the observed association” (p. 8). We agree with the importance of this alternative hypothesis. In fact, we were surprised that the review did not consider the results of sibling comparison studies that have directly addressed it, particularly given that the review had the opportunity to do so using data from articles included in the meta-analysis.

…The two studies of interest represented over 60% of the weighted sample. They yielded covariate-adjusted hazard ratios of 1.33 (95% confidence interval [CI], 1.23–1.45) and 1.13 (95% CI, 1.05–1.23). However, their sibling comparison results, which were excluded from the review, were weaker and not statistically-significant (hazard ratios, 1.21 [95% CI, 0.96–1.52] and 1.09 [0.84–1.42], respectively). These results suggest that familial confounding, rather than a true casual effect, explains much of the observed associations. The weaker associations from the sibling comparisons may thus dampen enthusiasm regarding a potentially meaningful role of exposure to maternal smoking during pregnancy in offspring schizophrenia. An approximately 10%–20% relative difference in rates of what is a rare outcome would suggest that modifying maternal smoking would have only a limited impact on the incidence of offspring schizophrenia.

“Genome-wide Association Study of Creativity Reveals Genetic Overlap With Psychiatric Disorders, Risk Tolerance, and Risky Behaviors”, Li et al 2020

2020-li.pdf: “Genome-wide Association Study of Creativity Reveals Genetic Overlap With Psychiatric Disorders, Risk Tolerance, and Risky Behaviors”⁠, Huijuan Li, Chuyi Zhang, Xin Cai, Lu Wang, Fang Luo, Yina Ma, Ming Li, Xiao Xiao (2020-03-05; ; similar):

Creativity represents one of the most important and partially heritable human characteristics, yet little is known about its genetic basis. Epidemiological studies reveal associations between creativity and psychiatric disorders as well as multiple personality and behavioral traits.

To test whether creativity and these disorders or traits share genetic basis, we performed genome-wide association studies (GWAS) followed by polygenic risk score (PRS) analyses. Two cohorts of Han Chinese subjects (4,834 individuals in total) aged 18–45 were recruited for creativity measurement using typical performance test. After exclusion of the outliers with statistically-significantly deviated creativity scores and low-quality genotyping results, 4,664 participants were proceeded for GWAS. We conducted PRS analyses using both the classical pruning and thresholding (P+T) method and the LDpred method. The extent of polygenic risk was estimated through linear regression adjusting for the top 3 genotyping principal components. R2 was used as a measurement of the explained variance.

PRS analyses demonstrated statistically-significantly positive genetic overlap, respectively, between creativity with schizophrenia (P+T method: R2(max) ~ 0.196%, p = 0.00245; LDpred method: R2(max) ~ 0.226%, p = 0.00114), depression (P+T method: R2(max) ~ 0.178%, p = 0.00389; LDpred method: R2(max) ~ 0.093%, p = 0.03675), general risk tolerance (P+T method: R2(max) ~ 0.177%, p = 0.00399; LDpred method: R2(max) ~ 0.305%, p = 0.00016), and risky behaviors (P+T method: R2(max) ~ 0.187%, p = 0.00307; LDpred method: R2(max) ~ 0.155%, p = 0.00715).

Our results suggest that human creativity is probably a polygenic trait affected by numerous variations with tiny effects. Genetic variations that predispose to psychiatric disorders and risky behaviors may underlie part of the genetic basis of creativity, confirming the epidemiological associations between creativity and these traits.

“Genetics of Schizophrenia in the South African Xhosa”, Gulsuner et al 2020

2020-gulsuner.pdf: “Genetics of schizophrenia in the South African Xhosa”⁠, S. Gulsuner, D. J. Stein, E. S. Susser, G. Sibeko, A. Pretorius, T. Walsh, L. Majara, M. M. Mndini, S. G. Mqulwana et al (2020-01-31; ; similar):

Africa, the ancestral home of all modern humans, is the most informative continent for understanding the human genome and its contribution to complex disease. To better understand the genetics of schizophrenia, we studied the illness in the Xhosa population of South Africa, recruiting 909 cases and 917 age-matched, gender-matched, and residence-matched controls. Individuals with schizophrenia were statistically-significantly more likely than controls to harbor private, severely damaging mutations in genes that are critical to synaptic function, including neural circuitry mediated by the neurotransmitters glutamine, γ-aminobutyric acid, and dopamine. Schizophrenia is genetically highly heterogeneous, involving severe ultra-rare mutations in genes that are critical to synaptic plasticity. The depth of genetic variation in Africa revealed this relationship with a moderate sample size and informed our understanding of the genetics of schizophrenia worldwide.

“Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders”, Consortium 2019

2019-pgc.pdf: “Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders”⁠, Cross-Disorder Group of the Psychiatric Genomics Consortium (2019-12-12; ; similar):

  • Three groups of highly genetically-related disorders among 8 psychiatric disorders
  • Identified 109 pleiotropic loci affecting more than one disorder
  • Pleiotropic genes show heightened expression beginning in 2nd prenatal trimester
  • Pleiotropic genes play prominent roles in neurodevelopmental processes

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/​hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

“Investigating the Causal Effect of Cannabis Use on Cognitive Function With a Quasi-experimental Co-twin Design”, Ross et al 2019

2019-ross.pdf: “Investigating the causal effect of cannabis use on cognitive function with a quasi-experimental co-twin design”⁠, J. Megan Ross, Jarrod M. Ellingson, Soo Hyun Rhee, John K. Hewitt, Robin P. Corley, Jeffrey M. Lessem et al (2019-11-02; )

“Contribution of Genetics to Visceral Adiposity and Its Relation to Cardiovascular and Metabolic Disease”, Karlsson et al 2019

2019-karlsson.pdf: “Contribution of genetics to visceral adiposity and its relation to cardiovascular and metabolic disease”⁠, Torgny Karlsson, Mathias Rask-Andersen, Gang Pan, Julia Höglund, Claes Wadelius, Weronica E. Ek, Åsa Johansson et al (2019-09-09)

“Assortative Mating and the Evolution of Desirability Covariation”, Conroy-Beam et al 2019

2019-conroybeam.pdf: “Assortative mating and the evolution of desirability covariation”⁠, Daniel Conroy-Beam, James R. Roney, Aaron W. Lukaszewski, David M. Buss, Kelly Asao, Agnieszka Sorokowska et al (2019-09-01; similar):

Mate choice lies close to differential reproduction, the engine of evolution. Patterns of mate choice consequently have power to direct the course of evolution.

Here we provide evidence suggesting one pattern of human mate choice—the tendency for mates to be similar in overall desirability—caused the evolution of a structure of correlations that we call the d factor.

We use agent-based models to demonstrate that assortative mating causes the evolution of a positive manifold of desirability, d, such that an individual who is desirable as a mate along any one dimension tends to be desirable across all other dimensions. Further, we use a large cross-cultural sample with n = 14,478 from 45 countries around the world to show that this d-factor emerges in human samples, is a cross-cultural universal, and is patterned in a way consistent with an evolutionary history of assortative mating.

Our results suggest that assortative mating can explain the evolution of a broad structure of human trait covariation.

[Keywords: assortative mating, trait covariation, agent-based modeling, cross-cultural studies]

“Predicting Musical Aptitude and Achievement: Practice, Teaching, and Intelligence”, Mosing et al 2019

“Predicting Musical Aptitude and Achievement: Practice, Teaching, and Intelligence”⁠, Miriam A. Mosing, David Z. Hambrick, Fredrik Ullén (2019-09; ⁠, ):

Studies of expertise have traditionally had a strong focus on the role of one single factor, i.e. long-term deliberate practice⁠, for expert performance. However, recent empirical and theoretical work strongly suggests that expertise is a function of many variables that may have practice-independent effects on performance, but also moderate the efficacy of practice itself.

Here we study such interaction effects in a large cohort (n > 4,500) of Swedish twins, using music as a model domain, and measured expert performance (musical auditory discrimination) as well as self-reported real-life achievement as indices of expertise. Specifically, we test 2 recently proposed hypotheses, i.e.  1. that the efficacy of practice increases if the individual also takes part in teacher-led lessons, and 2. that practice efficacy increases with higher intelligence.

The results did not support the first hypothesis. Both practice and frequency of music lessons had positive associations with the 2 measures of expertise but, contrary to predictions, the interaction between them was negative, i.e. the effect of each practiced hour decreased with more lessons. In contrast, the second hypothesis was supported by the data, i.e. we found a positive interaction between practice and intelligence, suggesting that higher cognitive ability is related to more efficient practice behaviors.

Together the results further support that domain-specific expertise is a complex outcome, which depends on an interplay of a variety of factors.

[Keywords: expertise, training, music, IQ, ability]

“Large-scale GWAS Reveals Insights into the Genetic Architecture of Same-sex Sexual Behavior”, Ganna et al 2019

“Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior”⁠, Andrea Ganna, Karin J. H. Verweij, Michel G. Nivard, Robert Maier, Robbee Wedow, Alexander S. Busch, Abdel Abdellaoui et al (2019-08-29; ⁠, ⁠, ⁠, ; similar):

Twin studies and other analyses of inheritance of sexual orientation in humans has indicated that same-sex sexual behavior has a genetic component. Previous searches for the specific genes involved have been underpowered and thus unable to detect genetic signals. Ganna et al 2019 perform a genome-wide association study on 493,001 participants from the United States, the United Kingdom, and Sweden to study genes associated with sexual orientation (see the Perspective by Mills). They find multiple loci implicated in same-sex sexual behavior indicating that, like other behavioral traits, nonheterosexual behavior is polygenic.

Introduction: Across human societies and in both sexes, some 2 to 10% of individuals report engaging in sex with same-sex partners, either exclusively or in addition to sex with opposite-sex partners. Twin and family studies have shown that same-sex sexual behavior is partly genetically influenced, but previous searches for the specific genes involved have been underpowered to detect effect sizes realistic for complex traits.

Rationale: For the first time, new large-scale datasets afford sufficient statistical power to identify genetic variants associated with same-sex sexual behavior (ever versus never had a same-sex partner), estimate the proportion of variation in the trait accounted for by all variants in aggregate, estimate the genetic correlation of same-sex sexual behavior with other traits, and probe the biology and complexity of the trait. To these ends, we performed genome-wide association discovery analyses on 477,522 individuals from the United Kingdom and United States, replication analyses in 15,142 individuals from the United States and Sweden, and follow-up analyses using different aspects of sexual preference.

Results: In the discovery samples (UK Biobank and 23andMe), 5 autosomal loci were statistically-significantly associated with same-sex sexual behavior. Follow-up of these loci suggested links to biological pathways that involve sex hormone regulation and olfaction. 3 of the loci were statistically-significant in a meta-analysis of smaller, independent replication samples. Although only a few loci passed the stringent statistical corrections for genome-wide multiple testing and were replicated in other samples, our analyses show that many loci underlie same-sex sexual behavior in both sexes. In aggregate, all tested genetic variants accounted for 8 to 25% of variation in male and female same-sex sexual behavior, and the genetic influences were positively but imperfectly correlated between the sexes [genetic correlation coefficient (rg)= 0.63; 95% confidence intervals, 0.48 to 0.78]. These aggregate genetic influences partly overlapped with those on a variety of other traits, including externalizing behaviors such as smoking, cannabis use, risk-taking, and the personality trait “openness to experience.” Additional analyses suggested that sexual behavior, attraction, identity, and fantasies are influenced by a similar set of genetic variants (rg > 0.83); however, the genetic effects that differentiate heterosexual from same-sex sexual behavior are not the same as those that differ among nonheterosexuals with lower versus higher proportions of same-sex partners, which suggests that there is no single continuum from opposite-sex to same-sex preference.

Conclusion: Same-sex sexual behavior is influenced by not one or a few genes but many. Overlap with genetic influences on other traits provides insights into the underlying biology of same-sex sexual behavior, and analysis of different aspects of sexual preference underscore its complexity and call into question the validity of bipolar continuum measures such as the Kinsey scale. Nevertheless, many uncertainties remain to be explored, including how sociocultural influences on sexual preference might interact with genetic influences. To help communicate our study to the broader public, we organized workshops in which representatives of the public, activists, and researchers discussed the rationale, results, and implications of our study.

“The Genetics of Human Fertility”, Kim & Lee 2019

2019-kim.pdf: “The genetics of human fertility”⁠, Yuri Kim, James J. Lee (2019-06-01; ⁠, ; similar):

Heritable variation in fitness—survival and reproduction—is the fuel of evolution by natural selection. Many human societies have dramatically reduced mortality before and during the prime reproductive years, making fertility a reasonably good proxy for the whole of fitness in much of our species. For this reason, empirical knowledge regarding the genetics of fertility must be an essential part of any framework for understanding past and ongoing trends in human adaptive evolution. Here we use R. A. Fisher’s analysis of human fertility as a starting point and find strong support from more recent research for his main contentions: fertility is a moderately heritable trait, where much of the genetic influences are shared with psychological characteristics.

“Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients across Four Healthcare Systems”, Zheutlin et al 2019

“Penetrance and pleiotropy of polygenic risk scores for schizophrenia in 106,160 patients across four healthcare systems”⁠, Amanda B. Zheutlin, Jessica Dennis, Richard Karlsson Linnér, Arden Moscati, Nicole Restrepo, Peter Straub et al (2019-03-23; ; similar):

Objective: Individuals at high risk for schizophrenia may benefit from early intervention but few validated risk predictors are available. Genetic profiling is one approach to risk stratification that has been extensively validated in research cohorts, but its utility in clinical settings remains largely unexplored. Moreover, the broad health consequences of a high genetic risk of schizophrenia are poorly understood, despite being relevant to treatment decisions.

Method: We used electronic health records for 106,160 patients from four healthcare systems to evaluate the penetrance and pleiotropy of genetic risk for schizophrenia. Polygenic risk scores (PRSs) for schizophrenia were calculated from summary statistics and tested for association with 1359 disease categories, including schizophrenia and psychosis, in phenome-wide association studies. Effects were combined through meta-analysis across sites.

Results: PRSs were robustly associated with schizophrenia (odds ratio per standard deviation increase in PRS = 1.55 [95% confidence interval (CI), 1.4–1.7], p = 4.48 x 10−16) and patients in the highest risk decile of the PRS distribution had up to 4.6× increased odds of schizophrenia compared to those in the bottom decile (95% CI, 2.9–7.3, p = 1.37 x 10−10). PRSs were also positively associated with a range of other phenotypes, including anxiety, mood, substance use, neurological, and personality disorders, as well as suicidal behavior, memory loss, and urinary syndromes; they were inversely related to obesity.

Conclusions: We demonstrate that an available measure of genetic risk for schizophrenia is robustly associated with schizophrenia in healthcare settings and has pleiotropic effects on related psychiatric disorders as well as other medical syndromes. Our results provide an initial indication of the opportunities and limitations that may arise with the future application of PRS testing in healthcare systems.

“New Evidence on the Link between Genes, Psychological Traits, and Political Engagement”, Weinschenk et al 2019

2019-weinschenk.pdf: “New evidence on the link between genes, psychological traits, and political engagement”⁠, Aaron C. Weinschenk, Christopher T. Dawes, Christian Kandler, Edward Bell, Rainer Riemann (2019; similar):

We investigate the link between genes, psychological traits, and political engagement using a new data set containing information on a large sample of young German twins. The TwinLife Study enables us to examine the predominant model of personality, the Big Five framework, as well as traits that fall outside the Big Five, such as cognitive ability, providing a more comprehensive understanding of the underpinnings of political engagement. Our results support previous work showing genetic overlap between some psychological traits and political engagement. More specifically, we find that cognitive ability and openness to experience are correlated with political engagement and that common genes can explain most of the relationship between these psychological traits and political engagement. Relationships between genes, psychological traits, and political engagement exist even at a fairly young age, which is an important finding given that previous work has relied heavily on older samples to study the link between genes, psychological traits, and political engagement.

“Genome-wide Association Study Identifies Eight Risk Loci and Implicates Metabo-psychiatric Origins for Anorexia Nervosa”, Watson et al 2019

2019-watson.pdf: “Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa”⁠, Hunna J. Watson, Zeynep Yilmaz, Laura M. Thornton, Christopher Hamp#x000FC;bel, Jonathan R. I. Coleman et al (2019-01-01)

“Genetic Correlations of Polygenic Disease Traits: from Theory to Practice”, Rheenen et al 2019

2019-vanrheenen.pdf: “Genetic correlations of polygenic disease traits: from theory to practice”⁠, Wouter Rheenen, Wouter J. Peyrot, Andrew J. Schork, S. Hong Lee, Naomi R. Wray (2019-01-01)

“Quantifying Between‐cohort and Between‐sex Genetic Heterogeneity in Major Depressive Disorder”, Trzaskowski et al 2019

2019-trzaskowski.pdf: “Quantifying between‐cohort and between‐sex genetic heterogeneity in major depressive disorder”⁠, Maciej Trzaskowski, Divya Mehta, Wouter J. Peyrot, David Hawkes, Daniel Davies, David M. Howard, Kathryn E. Kemper et al (2019-01-01)

“Identification of 28 New Susceptibility Loci for Type 2 Diabetes in the Japanese Population”, Suzuki et al 2019

2019-suzuki.pdf: “Identification of 28 new susceptibility loci for type 2 diabetes in the Japanese population”⁠, Ken Suzuki, Masato Akiyama, Kazuyoshi Ishigaki, Masahiro Kanai, Jun Hosoe, Nobuhiro Shojima, Atsushi Hozawa et al (2019-01-01; ; backlinks)

“Genome-wide Analysis Reveals Extensive Genetic Overlap between Schizophrenia, Bipolar Disorder, and Intelligence”, Smeland et al 2019

2019-smeland.pdf: “Genome-wide analysis reveals extensive genetic overlap between schizophrenia, bipolar disorder, and intelligence”⁠, Olav B. Smeland, Shahram Bahrami, Oleksandr Frei, Alexey Shadrin, Kevin O’Connell, Jeanne Savage, Kyoko Watanabe et al (2019-01-01; )

“Multi-Polygenic Score Approach to Identifying Individual Vulnerabilities Associated With the Risk of Exposure to Bullying”, Schoeler et al 2019

2019-schoeler.pdf: “Multi-Polygenic Score Approach to Identifying Individual Vulnerabilities Associated With the Risk of Exposure to Bullying”⁠, Tabea Schoeler, Shing Wan Choi, Frank Dudbridge, Jessie Baldwin, Lauren Duncan, Charlotte M. Cecil, Esther Walton et al (2019-01-01)

“Association Studies of up to 1.2 Million Individuals Yield New Insights into the Genetic Etiology of Tobacco and Alcohol Use”, Liu et al 2019

2019-liu.pdf: “Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use”⁠, Mengzhen Liu, Yu Jiang, Robbee Wedow, Yue Li, David M. Brazel, Fang Chen, Gargi Datta, Jose Davila-Velderrain et al (2019-01-01; ; backlinks)

“The Association Between Genetic Predisposition and Parental Socialization: An Examination of Gene-Environment Correlations Using an Adoption-Based Design”, Knoblach et al 2019

2019-knoblach.pdf: “The Association Between Genetic Predisposition and Parental Socialization: An Examination of Gene-Environment Correlations Using an Adoption-Based Design”⁠, Rachel A. Knoblach, Joseph A. Schwartz, Marianna McBride, Kevin M. Beaver (2019; ; similar):

An extensive body of research has examined the role that genetic influences play in the development of antisocial behavior. Even so, there remains much that is unknown regarding the intersections among antisocial behavior, environments, and genetic influences. The current study is designed to shed some light on this issue by examining whether gene-environment correlations are present in the lives of adopted adolescents. More specifically, this article seeks to contribute to scholarship efforts aimed at understanding whether biological parents’ antisocial behavioral phenotypes—behaviors often attributed to an increased likelihood of receiving a genetic propensity for antisocial behaviors—predict variation in environments that are experienced by their adopted-away offspring. To do so, the biological parents of adoptees were assessed and used to identify ways in which children elicit certain responses from their adoptive parents based, in part, on their genotype. Correlational analyses were calculated on a sample of adoptees (the final analytic sample ranged between n = 229 and n = 293) drawn from the National Longitudinal Study of Adolescent to Adult Health (Add Health). The results of the study revealed very little evidence of gene-environment correlations. The implications of these findings are considered.

“Unravelling the Interplay Between Genetic and Environmental Contributions in the Unfolding of Personality Differences from Early Adolescence to Young Adulthood”, Kandler et al 2019

2019-kandler.pdf: “Unravelling the Interplay Between Genetic and Environmental Contributions in the Unfolding of Personality Differences from Early Adolescence to Young Adulthood”⁠, Christian Kandler, Trine Waaktaar, René Mõttus, Rainer Riemann, Svenn Torgersen, Cornelia Wrzus (2019; similar):

In two studies, we examined the genetic and environmental sources of the unfolding of personality trait differences from childhood to emerging adulthood. Using self-reports from over 3000 representative German twin pairs of three birth cohorts, we could replicate previous findings on the primary role of genetic sources accounting for the unfolding of inter-individual differences in personality traits and stabilizing trait differences during adolescence. More specifically, the genetic variance increased between early (ages 10–12 years) and late (ages 16–18 years) adolescence and stabilized between late adolescence and young adulthood (ages 21–25 years). This trend could be confirmed in a second three-wave longitudinal study of adolescents’ personality self-reports and parent ratings from about 1400 Norwegian twin families (average ages between 15 and 20 years). Moreover, the longitudinal study provided evidence for increasing genetic differences being primarily due to accumulation of novel genetic influences instead of an amplification of initial genetic variation. This is in line with cumulative interaction effects between twins’ correlated genetic makeups and environmental circumstances shared by adolescent twins reared together. In other words, nature × nurture interactions rather than transactions can account for increases in genetic variance and thus personality variance during adolescence.

“Genetic and Environmental Variation in Political Orientation in Adolescence and Early Adulthood: A Nuclear Twin Family Analysis”, Hufer et al 2019

2019-hufer.pdf: “Genetic and environmental variation in political orientation in adolescence and early adulthood: A Nuclear Twin Family analysis”⁠, Anke Hufer, Anna Elena Kornadt, Christian Kandler, Rainer Riemann (2019-01-01)

“Genomics of Disease Risk in Globally Diverse Populations”, Gurdasani et al 2019

2019-gurdasani.pdf: “Genomics of disease risk in globally diverse populations”⁠, Deepti Gurdasani, Inamp#x000EA;s Barroso, Eleftheria Zeggini, Manjinder S. Sandhu (2019-01-01)

“Multivariate Genome-wide Analyses of the Well-being Spectrum”, Baselmans et al 2019

2019-baselmans.pdf: “Multivariate genome-wide analyses of the well-being spectrum”⁠, Bart M. L. Baselmans, Rick Jansen, Hill F. Ip, Jenny Dongen, Abdel Abdellaoui, Margot P. Weijer, Yanchun Bao et al (2019-01-01)

“Genetic Predisposition vs Individual-Specific Processes in the Association Between Psychotic-like Experiences and Cannabis Use”, Karcher et al 2019

“Genetic Predisposition vs Individual-Specific Processes in the Association Between Psychotic-like Experiences and Cannabis Use”⁠, Nicole R. Karcher, Deanna M. Barch, Catherine H. Demers, David A. A Baranger, Andrew C. Heath, Michael T. Lynskey et al (2019; ; backlinks; similar):

Importance: Previous research indicates that cannabis use is associated with psychotic-like experiences (PLEs). However, it is unclear whether this association results from predispositional (ie. shared genetic) factors or individual-specific factors (eg. causal processes, such as cannabis use leading to PLEs).

Objectives: To estimate genetic and environmental correlations between cannabis use and PLEs, and to examine PLEs in twin and nontwin sibling pairs discordant for exposure to cannabis use to disentangle predispositional from individual-specific effects.

Design, Setting, and Participants: In this cross-sectional analysis, diagnostic interviews and self-reported data were collected from 2 separate population-based samples of twin and nontwin sibling pairs. Data from the Human Connectome Project were collected between August 10, 2012, and September 29, 2015, and data from the Australian Twin Registry Cohort 3 (ATR3) were collected between August 1, 2005, and August 31, 2010. Data were analyzed between August 17, 2017, and July 6, 2018. The study included data from 1188 Human Connectome Project participants and 3486 ATR3 participants, totaling 4674 participants.

Main Outcomes and Measures: Three cannabis-involvement variables were examined: frequent use (ie. ≥100×), a DSM-IV lifetime cannabis use disorder diagnosis, and current cannabis use. Genetic and environmental correlations between cannabis involvement and PLEs were estimated. Generalized linear mixed models examined PLE differences in twin and nontwin sibling pairs discordant for cannabis use.

Results: Among the 4674 participants, the mean (SD) age was 30.5 (3.2) years, and 2923 (62.5%) were female. Data on race/​ethnicity were not included as a covariate owing to lack of variability within the ATR3 sample; among the 1188 participants in the Human Connectome Project, 875 (73.7%) were white. Psychotic-like experiences were associated with frequent cannabis use (β = 0.11; 95% CI, 0.08–0.14), cannabis use disorder (β = 0.13; 95% CI, 0.09–0.16), and current cannabis use (β = 0.07; 95% CI, 0.04–0.10) even after adjustment for covariates. Correlated genetic factors explained between 69.2% and 84.1% of this observed association. Within discordant pairs of twins/​siblings (N~pairs~, 308–324), Psychotic-like experiences were more common in cannabis-exposed individuals compared with their relative who used cannabis to a lesser degree (β ≥ .23, p < 0.05; eg, frequent and infrequent cannabis-using relatives significantly differed, z = -5.41; p < 0.001).

Conclusions and Relevance: Despite the strong contribution of shared genetic factors, frequent and problem cannabis use also appears to be associated with PLEs via person-specific pathways. This study’s findings suggest that policy discussions surrounding legalization should consider the influence of escalations in cannabis use on trait-like indices of vulnerability, such as PLEs, which could contribute to pervasive psychological and interpersonal burden.

“Life-course Socioeconomic Differences and Social Mobility in Preventable and Non-preventable Mortality: a Study of Swedish Twins”, Ericsson et al 2019

2019-ericsson.pdf: “Life-course socioeconomic differences and social mobility in preventable and non-preventable mortality: a study of Swedish twins”⁠, Malin Ericsson, Nancy L. Pedersen, Anna L. V Johansson, Stefan Fors, Anna K. Dahl Aslan (2019; similar):

Background: Despite advances in life expectancy, low socioeconomic status is associated with a shorter lifespan. This study was conducted to investigate socioeconomic differences in mortality by comparing preventable with non-preventable causes of death in 39 506 participants from the Swedish Twin Registry born before 1935.

Methods: Childhood social class, own education, own social class and social mobility were used as separate indicators of socioeconomic status. These data were linked to the Swedish Cause of Death Register. Cause of death was categorized as preventable or non-preventable mortality according to indicators presented in the Avoidable Mortality in the European Union (AMIEHS) atlas. Using Cox proportional hazard models, we tested the association between the socioeconomic measures and all-cause mortality, preventable mortality and non-preventable mortality. Additional co-twin control analyses indicated whether the associations reflected genetic confounding.

Results: The social gradient for mortality was most prominent for the adult socioeconomic measures. There was a social gradient in both preventable mortality and non-preventable mortality, but with an indication of a moderately stronger effect in preventable causes of death. In analyses of social mobility, those who experienced life-time low socioeconomic status (SES) or downward social mobility had an increased mortality risk compared with those with life-time high SES and upward social mobility. Adjustments for genetic confounding did not change the observed associations for education, social class or social mobility and mortality. In the co-twin control analyses of reared-apart twins, the association between childhood social class and mortality weakened, indicating possible genetic influences on this association.

Conclusions: Our results indicate that there is an association between low adult socioeconomic status and increased mortality independent of genetic endowment. Thus, we do not find support for indirect social selection as the basis for mortality inequalities in Sweden.

[Keywords: mortality, socioeconomic status, social mobility, social gradient, social selection, co-twin control]

Key Messages:

  • Mortality followed a social gradient with higher mortality for lower socioeconomic groups, independent of preventability, in a large Swedish twin study linked to register-based mortality data.
  • There was a similar gradient in both preventable and non-preventable mortality, with an indication of a moderately stronger effect in preventable causes of death, and the adult socioeconomic indicator was more important compared with the childhood measure.
  • The impact of socioeconomic factors was stronger in premature mortality (<70 years of age), but the social gradient was present also in late-life mortality.
  • Familial confounding could not explain the observed associations between adult socioeconomic circumstances and mortality inequalities, indicating that socioeconomic status in itself may have an effect on mortality.

“Estimating the Educational Consequences of Teenage Childbearing: Identification, Heterogeneous Effects and the Value of Biological Relationship Information”, Heiland et al 2018

2019-heiland.pdf: “Estimating the educational consequences of teenage childbearing: Identification, heterogeneous effects and the value of biological relationship information”⁠, Frank Heiland, Sanders Korenman, Rachel A. Smith (2018-12-28)

“The Stability of Educational Achievement across School Years Is Largely Explained by Genetic Factors”, Rimfeld et al 2018

“The stability of educational achievement across school years is largely explained by genetic factors”⁠, Kaili Rimfeld, Margherita Malanchini, Eva Krapohl, Laurie J. Hannigan, Philip S. Dale, Robert Plomin (2018-09-04; ; similar):

Little is known about the etiology of developmental change and continuity in educational achievement.

Here, we study achievement from primary school to the end of compulsory education for 6,000 twin pairs in the UK-representative Twins Early Development Study sample.

Results: showed that educational achievement is highly heritable across school years and across subjects studied at school (twin heritability ~60%; SNP heritability ~30%); achievement is highly stable (phenotypic correlations ~0.70 from ages 7 to 16). Twin analyses, applying simplex and common pathway models, showed that genetic factors accounted for most of this stability (70%), even after controlling for intelligence (60%). Shared environmental factors also contributed to the stability, while change was mostly accounted for by individual-specific environmental factors. polygenic scores⁠, derived from a genome-wide association analysis of adult years of education, also showed stable effects on school achievement.

We conclude that the remarkable stability of achievement is largely driven genetically even after accounting for intelligence.

“Exploring the Genetic Correlations of Antisocial Behavior and Life History Traits”, Tielbeek et al 2018

“Exploring the genetic correlations of antisocial behavior and life history traits”⁠, Jorim J. Tielbeek, J. C. Barnes, Arne Popma, Tinca J. C. Polderman, James J. Lee, John R. B. Perry, Danielle Posthuma et al (2018-08-23; ; similar):

Prior evolutionary theory provided reason to suspect that measures of development and reproduction would be correlated with antisocial behaviors in human and non-human species. Behavioral genetics has revealed that most quantitative traits are heritable, suggesting that these phenotypic correlations may share genetic etiologies. We use GWAS data to estimate the genetic correlations between various measures of reproductive development (n = 52,776–318,863) and antisocial behavior (n = 31,968). Our genetic correlation analyses demonstrate that alleles associated with higher reproductive output (number of children ever born, rg = 0.50, p = 0.0065) were positively correlated with alleles associated with antisocial behavior, whereas alleles associated with more delayed reproductive onset (age of first birth, rg = −0.64, p = 0.0008) were negatively associated with alleles linked to antisocial behavior. Ultimately, these findings coalesce with evolutionary theories suggesting that increased antisocial behaviors may partly represent a faster life history approach, which may be significantly calibrated by genes.

“Analysis of Shared Heritability in Common Disorders of the Brain”, Consortium 2018

“Analysis of shared heritability in common disorders of the brain”⁠, The Brainstorm Consortium (2018-06-22; ⁠, ; similar):

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified statistically-significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

“Common Disease Is More Complex Than Implied by the Core Gene Omnigenic Model”, Wray et al 2018

“Common Disease Is More Complex Than Implied by the Core Gene Omnigenic Model”⁠, Naomi R. Wray, Cisca Wijmenga, Patrick F. Sullivan, Jian Yang, Peter M. Visscher (2018-06-14; backlinks; similar):

The evidence that most adult-onset common diseases have a polygenic genetic architecture fully consistent with robust biological systems supported by multiple back-up mechanisms is now overwhelming. In this context, we consider the recent “omnigenic” or “core genes” model. A key assumption of the model is that there is a relatively small number of core genes relevant to any disease. While intuitively appealing, this model may underestimate the biological complexity of common disease, and therefore, the goal to discover core genes should not guide experimental design. We consider other implications of polygenicity, concluding that a focus on patient stratification is needed to achieve the goals of precision medicine.

…In conclusion, Boyle et al 2017 are congratulated for their synthesis of current data and for articulation of a biological framework that has prompted extensive constructive discussion. We agree that understanding the cell-specific role of disease-associated variants is a crucial step for advancing knowledge of common disease. However, whereas those authors extrapolate results of analyses of GWAS summary statistics to make fundamental assumptions that rare variants of large effect in a small number of genes play the most critical roles in clinical conditions that attract a common disease diagnosis, we believe it would be a major disservice to the field to allow these assumptions to guide the next steps of research. To assume that a limited number of core genes are key to our understanding of common disease may underestimate the true biological complexity, which is better represented by systems genetics and network approaches (Baliga et al 2017, Parikshak et al 2015). While Boyle et al advocate for WES studies, they did not discuss the sample sizes needed for such discovery. We believe that in the short term, large samples recorded for key measures of phenotypic heterogeneity and genome-wide SNP data are the best next steps for research using human DNA samples in moving forward our understanding of complex genetic diseases. Large numbers of samples, biobanked for cellular reprogramming, will position us well for the next generation of sequencing and other new technologies. High-throughput phenotyping to characterize cellular properties associated with disease-associated genomes may be the key to penetrate the polygenic complexity of common disease and provide the data needed for patient stratification, as well as to progress toward the goal of new drug treatments. These are research paths that need to advance in parallel to advance the promise of precision medicine.

“Sex Differences in the Big Five Model Personality Traits: A Behavior Genetics Exploration”, South et al 2018

2018-south.pdf: “Sex differences in the Big Five model personality traits: A behavior genetics exploration”⁠, Susan C. South, Amber M. Jarnecke, Colin E. Vize (2018-06-01; ; similar):

  • Mean level sex differences were found for Neuroticism, Agreeableness, and Conscientiousness (women higher on all).
  • No evidence of qualitative genetic differences between men and women on any of the Big Five traits.
  • No evidence of quantitative genetic or environmental differences between men and women on any of the Big Five traits.

The importance of genetic influences for the Five Factor/​Big Five Model (BFM) traits is well established. Relatively understudied, however, are the presence and magnitude of sex differences in genetic and environmental variance of these traits. The current study tested if men and women differ (1) qualitatively in the genetic mechanisms, or (2) quantitatively, on the genetic and environmental variance, contributing to BFM personality domains. Results from a nationally representative U.S. adult twin sample (n = 973 pairs) supported phenotypic (ie. mean level) sex differences in 3 of 5 personality traits (Neuroticism, Agreeableness, Conscientiousness) but did not support genetic or environmental sex differences in any trait.

[Keywords: personality, sex differences, behavior genetics, twin]

“Genetic Variants Associated With Subjective Well-being, Depressive Symptoms, and Neuroticism Identified through Genome-wide Analyses”, Okbay et al 2018

2016-okbay.pdf: “Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses”⁠, Aysu Okbay, Bart M. L. Baselmans, Jan-Emmanuel De Neve, Patrick Turley, Michel G. Nivard, Mark Alan Fontana et al (2018-04-26; ⁠, ; similar):

Major depressive disorder (MDD) [vs subjective well-being] is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide.

We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and statistically-significant loci.

The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology.

All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

“Improving Genetic Prediction by Leveraging Genetic Correlations among Human Diseases and Traits”, Maier et al 2018

“Improving genetic prediction by leveraging genetic correlations among human diseases and traits”⁠, Robert M. Maier, Zhihong Zhu, Sang Hong Lee, Maciej Trzaskowski, Douglas M. Ruderfer, Eli A. Stahl, Stephan Ripke et al (2018-03-07; ⁠, ; backlinks; similar):

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7% for height to 47% for type 2 diabetes⁠, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait.

“A Combined Analysis of Genetically Correlated Traits Identifies 187 Loci and a Role for Neurogenesis and Myelination in Intelligence”, Hill et al 2018

“A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence”⁠, William D. Hill, Robert E. Marioni, O. Maghzian, Stuart J. Ritchie, Sarah P. Hagenaars, A. M. McIntosh et al (2018-01-11; ⁠, ; backlinks; similar):

Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental health variables. Education is strongly genetically correlated with intelligence (rg = 0.70). We used these findings as foundations for our use of a novel approach—multi-trait analysis of genome-wide association studies (MTAG; Turley et al 2017)—to combine two large genome-wide association studies (GWASs) of education and intelligence, increasing statistical power and resulting in the largest GWAS of intelligence yet reported. Our study had four goals: first, to facilitate the discovery of new genetic loci associated with intelligence; second, to add to our understanding of the biology of intelligence differences; third, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predicts phenotypic intelligence in an independent sample.

By combining datasets using MTAG, our functional sample size increased from 199,242 participants to 248,482. We found 187 independent loci associated with intelligence, implicating 538 genes, using both SNP-based and gene-based GWAS. We found evidence that neurogenesis and myelination—as well as genes expressed in the synapse, and those involved in the regulation of the nervous system—may explain some of the biological differences in intelligence.

The results of our combined analysis demonstrated the same pattern of genetic correlations as those from previous GWASs of intelligence, providing support for the meta-analysis of these genetically-related phenotypes.

“Childhood Body Mass Index and Development of Eating Disorder Traits across Adolescence”, Wiklund et al 2018

2018-wiklund.pdf: “Childhood body mass index and development of eating disorder traits across adolescence”⁠, Camilla A. Wiklund, Ralf Kuja-Halkola, Laura M. Thornton, Katarina Bälter, Elisabeth Welch, Cynthia M. Bulik et al (2018-01-01)

“The Effect of Education on Political Knowledge: Evidence From Monozygotic Twins”, Weinschenk & Dawes 2018

2018-weinschenk.pdf: “The Effect of Education on Political Knowledge: Evidence From Monozygotic Twins”⁠, Aaron C. Weinschenk, Christopher T. Dawes (2018; similar):

Political scientists have long been interested in the determinants of political knowledge. In many studies, education is the strongest predictor of political knowledge. However, some studies have found that education has no effect on knowledge once confounding variables are taken into account. In addition, some recent work suggests that education remains the strongest predictor of knowledge even after accounting for confounders like personality traits and intelligence.

We provide new evidence on the effect of education on political knowledge by utilizing the co-twin control design. By looking at the relationship between education and knowledge within monozygotic twin pairs, we are able to circumvent sources of confounding of the relationship due to genetic factors and early-life family environment because monozygotic twins share both. We find that the relationship between education and political knowledge is highly confounded by genes and/​or familial environment. The results from a naive model that does not take into account unobserved family factors indicate that education has a positive and statistically-significant effect on political knowledge. However, in a twin fixed-effects model that accounts for confounding due to genetic factors and familial socialization, we find that the effect of education on political knowledge drops substantially and is not statistically-significant at conventional levels.

“Transancestral GWAS of Alcohol Dependence Reveals Common Genetic Underpinnings With Psychiatric Disorders”, Walters et al 2018

2018-walters.pdf: “Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders”⁠, Raymond K. Walters, Renato Polimanti, Emma C. Johnson, Jeanette N. McClintick, Mark J. Adams, Amy E. Adkins et al (2018-01-01; ; backlinks)

“Using Genetic Data to Strengthen Causal Inference in Observational Research”, Pingault et al 2018

2018-pingault.pdf: “Using genetic data to strengthen causal inference in observational research”⁠, Jean-Baptiste Pingault, Paul F. Oamp#x02019;Reilly, Tabea Schoeler, George B. Ploubidis, Framp#x000FC;hling Rijsdijk et al (2018-01-01)

“Genetic and Environmental Influences on Internalizing Psychopathology across Age and Pubertal Development”, Patterson et al 2018

2018-patterson.pdf: “Genetic and environmental influences on internalizing psychopathology across age and pubertal development”⁠, Megan W. Patterson, Frank D. Mann, Andrew D. Grotzinger, Jennifer L. Tackett, Elliot Tucker-Drob, K. Paige Harden et al (2018-01-01)

“Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood”, Ni et al 2018

2018-ni.pdf: “Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood”⁠, Guiyan Ni, Gerhard Moser, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Stephan Ripke et al (2018-01-01)

“Challenging Assumptions: A Genetically Sensitive Assessment of the Criminogenic Effect of Contact With the Criminal Justice System”, Nedelec & Silver 2018

2018-nedelec.pdf: “Challenging Assumptions: A Genetically Sensitive Assessment of the Criminogenic Effect of Contact With the Criminal Justice System”⁠, Joseph L. Nedelec, Ian A. Silver (2018; similar):

A key assumption underlying various components of criminological thought is the criminogenic effect of involvement with the criminal justice system. Prior assessments of this effect, however, have been mixed and all are subject to potential genetic confounding. In the current study, we employ twin difference scores using both monozygotic and dizygotic twins to isolate the effect of involvement with the criminal justice system on future criminal behavior. The findings illustrate null associations between a variety of interactions of the criminal justice system and subsequent criminal offending. The study illustrates the continued ineffectiveness of the standard social science methodological approach to assessing criminology’s main assumptions.

“'Same but Different': Associations between Multiple Aspects of Self-regulation, Cognition, and Academic Abilities”, Malanchini et al 2018

2018-malanchini.pdf: “'Same but different': Associations between multiple aspects of self-regulation, cognition, and academic abilities”⁠, Margherita Malanchini, Laura E. Engelhardt, Andrew D. Grotzinger, K. Paige Harden, Elliot M. Tucker-Drob et al (2018-01-01)

“A Behavioral Genetic Analysis of the Cooccurrence Between Psychopathic Personality Traits and Criminal Behavior”, Lewis et al 2018

2018-lewis.pdf: “A Behavioral Genetic Analysis of the Cooccurrence Between Psychopathic Personality Traits and Criminal Behavior”⁠, Richard H. Lewis, Eric J. Connolly, Danielle L. Boisvert, Brian B. Boutwell (2018; similar):

A developed line of research has found that psychopathic personality traits and criminal behavior are correlated with one another. Although there is little question about the association between psychopathic personality traits and criminal behavior, what remains less clear is whether psychopathic traits exert a direct effect on criminal behavior. An alternative possibility is that previously unmeasured genetic and shared environmental factors account for much of the association between the two.

Understanding the extent to which genetic and environmental factors influence the covariance between psychopathic personality traits and criminal behavior can further our understanding of individual differences in propensity to engage in antisocial behavior. The current study analyzes 872 twins (MZ twins = 352, DZ twins = 520) from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine the magnitude of genetic and environmental effects on the covariation between psychopathic personality and criminal behavior. Results from bivariate behavioral genetic analyses revealed that the correlation between psychopathic personality traits and criminal behavior was accounted for by common additive genetic (58%) and nonshared environmental (42%) influences. Fixed-effect linear regression models, however, suggested that psychopathic personality traits were not statistically-significantly associated with criminal behavior once common genetic and environmental influences were taken into account.

“Genetic and Environmental Influences on Verbal Fluency in Middle Age: A Longitudinal Twin Study”, Gustavson 2018

2018-gustavson.pdf: “Genetic and Environmental Influences on Verbal Fluency in Middle Age: A Longitudinal Twin Study”⁠, Daniel E. Gustavson (2018-01-01)

“Childhood Neurodevelopmental Disorders and Risk of Coercive Sexual Victimization in Childhood and Adolescence—a Population‐based Prospective Twin Study”, Gotby et al 2018

2018-gotby.pdf: “Childhood neurodevelopmental disorders and risk of coercive sexual victimization in childhood and adolescence—a population‐based prospective twin study”⁠, Vide Ohlsson Gotby, Paul Lichtenstein, Niklas Långström, Erik Pettersson (2018-01-01)

“Association Between Population Density and Genetic Risk for Schizophrenia”, Colodro-Conde et al 2018

2018-colodroconde.pdf: “Association Between Population Density and Genetic Risk for Schizophrenia”⁠, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, John B. Whitfield, Fabian Streit, Scott Gordon, Kathryn E. Kemper et al (2018-01-01; )

“Genetic and Environmental Overlap Between Substance Use and Delinquency in Adolescence”, Boisvert et al 2018

2018-boisvert.pdf: “Genetic and Environmental Overlap Between Substance Use and Delinquency in Adolescence”⁠, Danielle L. Boisvert, Eric J. Connolly, Jamie C. Vaske, Todd A. Armstrong, Brian B. Boutwell (2018; ; similar):

During adolescence, many teens begin to experiment with substances and engage in delinquent behavior. The current study seeks to examine whether and to what extent genetic and environmental factors contribute to the association between substance use (ie. marijuana and alcohol) and different forms of delinquent offending (ie. violent and nonviolent) across males and females. Analyses were based on same-sex twins (n = 1,072) from the sibling subsample of the National Longitudinal Study of Adolescent to Adult Health (Add Health). The results revealed moderate to large genetic overlap between substance use and delinquent behavior for males. Much of the covariation between alcohol use and offending behavior for females was attributable to common environmental factors, while common genetic factors explained a large portion of the overlap between marijuana use and offending in males and females. The implications of these findings for sex differences in prevention and intervention efforts are discussed from a biosocial perspective.

“Genetic and Environmental Associations Between Child Personality and Parenting”, Ayoub et al 2018

2018-ayoub.pdf: “Genetic and Environmental Associations Between Child Personality and Parenting”⁠, Mona Ayoub, Daniel A. Briley, Andrew Grotzinger, Megan W. Patterson, Laura E. Engelhardt, Jennifer L. Tackett et al (2018; similar):

Parenting is often conceptualized in terms of its effects on offspring. However, children may also play an active role in influencing the parenting they receive. Simple correlations between parenting and child outcomes may be due to parent-to-child causation, child-to-parent causation, or some combination of the two. We use a multirater, genetically informative, large sample (n = 1,411 twin sets) to gain traction on this issue as it relates to parental warmth and stress in the context of child Big Five personality. Considerable variance in parental warmth (27%) and stress (45%) was attributable to child genetic influences on parenting. Incorporating child Big Five personality into the model roughly explained half of this variance. This result is consistent with the hypothesis that parents mold their parenting in response to their child’s personality. Residual heritability of parenting is likely due to child characteristics beyond the Big Five.

“Polycystic Ovary Syndrome, Personality, and Depression: A Twin Study”, Cesta et al 2017

2017-cesta.pdf: “Polycystic ovary syndrome, personality, and depression: A twin study”⁠, Carolyn E. Cesta, Ralf Kuja-Halkola, Kelli Lehto, Anastasia N. Iliadou, Mikael Landén (2017-11-01; ; similar):

  • Women with PCOS had a 2-fold increase in odds for lifetime MDD.
  • Women with PCOS score higher on Neuroticism scale.
  • There are common genetic factors between neuroticism, PCOS, and MDD.
  • Neuroticism contributes to a portion of the comorbidity between PCOS and MDD.

Background: Women with polycystic ovary syndrome (PCOS) are at elevated risk for suffering from depression. Neuroticism is a personality trait that has been associated with an increased risk for developing major depressive disorder (MDD). The aim of the present study was to quantify and decompose the correlation between Neuroticism, PCOS, and MDD into shared and unique genetic and environmental etiologies, by using quantitative genetic methods.

Methods: In a cohort of 12,628 Swedish female twins born from 1959 to 1985, Neuroticism, PCOS identified by symptoms of hyperandrogenemia (ie. hirsutism) and oligoovulation and/​or anovulation⁠, and lifetime MDD status were determined through questionnaire responses. Structural equation modeling was used to study the genetic and environmental sources of the variation within, and covariation between Neuroticism, PCOS, and MDD.

Results: Female twins with PCOS (n = 752) had statistically-significantly higher levels of Neuroticism than women without PCOS, and a 2-fold increase in odds for a lifetime prevalence of MDD. The phenotypic correlation between PCOS and MDD was 0.19, with 63% of the correlation attributable to common genetic factors between the 2 traits. When taking into account Neuroticism, 41% was attributable to common genetic factors and 9% attributable to common environmental factors shared between all 3 traits, with the remainder attributable to components unique to PCOS and MDD.

Conclusion: There are common genetic factors between Neuroticism, PCOS, and MDD; however, Neuroticism shares ~half of the genetic and environmental components behind the phenotypic correlation between PCOS and MDD, providing some etiological evidence behind the comorbidity between PCOS and depression.

[Keywords: polycystic ovary syndrome, depression, personality, Neuroticism, twins, genetic correlation]

“Multi-trait Analysis of Genome-wide Association Summary Statistics Using MTAG”, Turley et al 2017

2018-turley.pdf: “Multi-trait analysis of genome-wide association summary statistics using MTAG”⁠, Patrick Turley, Raymond K. Walters, Omeed Maghzian, Aysu Okbay, James J. Lee, Mark Alan Fontana, Tuan Anh Nguyen-Viet et al (2017-10-23; backlinks; similar):

We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (Neff = 354,862), neuroticism (n = 168,105), and subjective well-being (n = 388,538).

As compared to the 32, 9, and 13 genome-wide statistically-significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by ~25%, matching theoretical expectations.

“Genome-wide Association Study of Social Relationship Satisfaction: Significant Loci and Correlations With Psychiatric Conditions”, Warrier et al 2017

“Genome-wide association study of social relationship satisfaction: significant loci and correlations with psychiatric conditions”⁠, Varun Warrier, the 23andMe Research Team, Thomas Bourgeron, Simon Baron-Cohen (2017-10-05; ⁠, ⁠, ; similar):

Dissatisfaction in social relationships is reported widely across many psychiatric conditions. We investigated the genetic architecture of family relationship satisfaction and friendship satisfaction in the UK Biobank. We leveraged the high genetic correlation between the two phenotypes (rg = 0.87±0.03; p < 2.2×10−16) to conduct multi-trait analysis of Genome Wide Association Study (GWAS) (Neffective family = 164,112; Neffective friendship = 158,116). We identified two genome-wide statistically-significant associations for both the phenotypes: rs1483617 on chromosome 3 and rs2189373 on chromosome 6, a region previously implicated in schizophrenia. eQTL and chromosome conformation capture in neural tissues prioritizes several genes including NLGN1. Gene-based association studies identified several significant genes, with highest expression in brain tissues. Genetic correlation analysis identified significant negative correlations for multiple psychiatric conditions including highly significant negative correlation with cross-psychiatric disorder GWAS, underscoring the central role of social relationship dissatisfaction in psychiatric diagnosis. The two phenotypes were enriched for genes that are loss of function intolerant. Both phenotypes had modest, significant additive SNP heritability of ~6%. Our results underscore the central role of social relationship satisfaction in mental health and identify genes and tissues associated with it.

“Identification of Genetic Loci Jointly Influencing Schizophrenia Risk and the Cognitive Traits of Verbal-Numerical Reasoning, Reaction Time, and General Cognitive Function”, Smeland et al 2017

2017-smeland.pdf: “Identification of Genetic Loci Jointly Influencing Schizophrenia Risk and the Cognitive Traits of Verbal-Numerical Reasoning, Reaction Time, and General Cognitive Function”⁠, Olav B. Smeland, Oleksandr Frei, Karolina Kauppi, W. David Hill, Wen Li, Yunpeng Wang, Florian Krull et al (2017-10-01; similar):

Question: What genetic loci jointly influence schizophrenia and cognitive function?

Findings: In this analysis of genome-wide association studies on schizophrenia and cognitive traits in more than 250,000 participants, 21 genomic regions were found to be shared between schizophrenia and cognitive traits.

Meaning: The findings provide new insights into the common genetic basis underlying schizophrenia and cognitive function, suggesting novel molecular genetic mechanisms.

Importance: Schizophrenia is associated with widespread cognitive impairments. Although cognitive deficits are one of the factors most strongly associated with functional outcome in schizophrenia, current treatment strategies largely fail to ameliorate these impairments. To develop more efficient treatment strategies in patients with schizophrenia, a better understanding of the pathogenesis of these cognitive deficits is needed. Accumulating evidence indicates that genetic risk of schizophrenia may contribute to cognitive dysfunction.


Objective: To identify genomic regions jointly influencing schizophrenia and the cognitive domains of reaction time and verbal-numerical reasoning, as well as general cognitive function, a phenotype that captures the shared variation in performance across cognitive domains.

Design, Setting, & Participants: Combining data from genome-wide association studies from multiple phenotypes using conditional false discovery rate analysis provides increased power to discover genetic variants and could elucidate shared molecular genetic mechanisms. Data from the following genome-wide association studies, published from July 24, 2014, to January 17, 2017, were combined: schizophrenia in the Psychiatric Genomics Consortium cohort (n = 79,757 [cases, 34,486; controls, 45,271]); verbal-numerical reasoning (n = 36,035) and reaction time (n = 111,483) in the UK Biobank cohort; and general cognitive function in CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) (n = 53,949) and COGENT (Cognitive Genomics Consortium) (n = 27,888).

Main Outcomes & Measures: Genetic loci identified by conditional false discovery rate analysis. Brain messenger RNA expression and brain expression quantitative trait locus functionality were determined.

Results: Among the participants in the genome-wide association studies, 21 loci jointly influencing schizophrenia and cognitive traits were identified: 2 loci shared between schizophrenia and verbal-numerical reasoning, 6 loci shared between schizophrenia and reaction time, and 14 loci shared between schizophrenia and general cognitive function. One locus was shared between schizophrenia and 2 cognitive traits and represented the strongest shared signal detected (nearest gene TCF20; chromosome 22q13.2), and was shared between schizophrenia (z-score, 5.01; p = 5.53 × 10−7), general cognitive function (z-score, −4.43; p = 9.42 × 10−6), and verbal-numerical reasoning (z-score, −5.43; p = 5.64 × 10−8). For 18 loci, schizophrenia risk alleles were associated with poorer cognitive performance. The implicated genes are expressed in the developmental and adult human brain. Replicable expression quantitative trait locus functionality was identified for 4 loci in the adult human brain.

Conclusions & Relevance: The discovered loci improve the understanding of the common genetic basis underlying schizophrenia and cognitive function, suggesting novel molecular genetic mechanisms.

“Genome-wide Association Study Identifies 112 New Loci for Body Mass Index in the Japanese Population”, Akiyama et al 2017

2017-akiyama.pdf: “Genome-wide association study identifies 112 new loci for body mass index in the Japanese population”⁠, Masato Akiyama, Yukinori Okada, Masahiro Kanai, Atsushi Takahashi, Yukihide Momozawa, Masashi Ikeda, Nakao Iwata et al (2017-09-11; ; backlinks; similar):

Obesity is a risk factor for a wide variety of health problems. In a genome-wide association study (GWAS) of body mass index (BMI) in Japanese people (n = 173,430), we found 85 loci statistically-significantly associated with obesity (p < 5.0 × 10−8), of which 51 were previously unknown. We conducted trans-ancestral meta-analyses by integrating these results with the results from a GWAS of Europeans and identified 61 additional new loci. In total, this study identifies 112 novel loci, doubling the number of previously known BMI-associated loci. By annotating associated variants with cell-type-specific regulatory marks, we found enrichment of variants in CD19+ cells. We also found statistically-significant genetic correlations between BMI and lymphocyte count (p = 6.46 × 10−5, rg = 0.18) and between BMI and multiple complex diseases. These findings provide genetic evidence that lymphocytes are relevant to body weight regulation and offer insights into the pathogenesis of obesity.

“Ninety-nine Independent Genetic Loci Influencing General Cognitive Function Include Genes Associated With Brain Health and Structure (n = 280,360)”, Davies et al 2017

“Ninety-nine independent genetic loci influencing general cognitive function include genes associated with brain health and structure (n = 280,360)”⁠, Gail Davies, Max Lam, Sarah E. Harris, Joey W. Trampush, Michelle Luciano, W. David Hill, Saskia P. Hagenaars et al (2017-08-18; ⁠, ; backlinks; similar):

General cognitive function is a prominent human trait associated with many important life outcomes1,2, including longevity3. The substantial heritability of general cognitive function is known to be polygenic, but it has had little explication in terms of the contributing genetic variants4,5,6. Here, we combined cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total n = 280,360; age range = 16 to 102). We found 9,714 genome-wide statistically-significant SNPs (P<5 x 10−8) in 99 independent loci. Most showed clear evidence of functional importance. Among many novel genes associated with general cognitive function were SGCZ, ATXN1, MAPT, AUTS2, and P2RY6. Within the novel genetic loci were variants associated with neurodegenerative disorders, neurodevelopmental disorders, physical and psychiatric illnesses, brain structure, and BMI. Gene-based analyses found 536 genes statistically-significantly associated with general cognitive function; many were highly expressed in the brain, and associated with neurogenesis and dendrite gene sets. Genetic association results predicted up to 4% of general cognitive function variance in independent samples. There was significant genetic overlap between general cognitive function and information processing speed, as well as many health variables including longevity.

“Genetic Correlations of Hip Dysplasia Scores for Golden Retrievers and Labrador Retrievers in France, Sweden and the UK”, Wang et al 2017

2017-wang.pdf: “Genetic correlations of hip dysplasia scores for Golden retrievers and Labrador retrievers in France, Sweden and the UK”⁠, S. Wang, G. Leroy, S. Malm, T. Lewis, Å. Viklund, E. Strandberg, W. F. Fikse (2017-08-01; ; similar):

  • Hip dysplasia (HD) genetic parameters were estimated for 2 dog breeds in France, Sweden and the UK.
  • Estimates of heritability ranged from 0.15 to 0.41, according to breed and country.
  • The power of estimation was highly associated with the connectedness between populations.
  • Genetic progress to reduce the prevalence of HD could be improved by selection across countries.
  • Estimated genetic correlations of HD scores demonstrated the feasibility of international evaluation.

In order to reduce the prevalence of inherited diseases in pedigree dogs, the feasibility of implementation of an international breeding program was investigated. One prerequisite is a strong genetic correlation between countries and our objective was to estimate this correlation for canine hip dysplasia (HD) across 3 countries to evaluate the feasibility of an international genetic evaluation. Data were provided by the Société Centrale Canine (SCC, France), Svenska Kennelklubben (SKK, Sweden) and The Kennel Club (KC, UK) on Golden retriever and Labrador retriever dogs. Trivariate analysis on the 3 different modes of scoring HD in France, Sweden and the UK was performed using a mixed linear animal model. Heritability, genetic correlation, number of common sires, genetic similarity, selection differentials and accuracy of selection were calculated.

The estimated heritabilities of Golden retrievers (Labrador retrievers) for HD scores were 0.28 (0.15), 0.28 (0.29) and 0.41 (0.34) in France, Sweden and the UK, respectively. The feasibility of performing a genetic evaluation of HD across countries was indicated by the favourable genetic correlations estimated between score modes (ranged from 0.48 to 0.99). The accuracy of selection for the most recent birth year cohorts of male dogs was not improved by international evaluation compared to national evaluation.

Improvement in genetic progress can however be achieved by selection across populations in different countries, particularly for small populations, which were indicated by the large difference between selection differentials based on the national and international evaluations.

[Keywords: best linear unbiased prediction (BLUP), dog, genetic correlation, hip dysplasia, international breeding program]

“GWAS Meta-analysis Reveals Novel Loci and Genetic Correlates for General Cognitive Function: a Report from the COGENT Consortium”, Trampush et al 2017

“GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium”⁠, J. W. Trampush, M. L. Z. Yang, J. Yu, E. Knowles, G. Davies, D. C. Liewald, J. M. Starr, S. Djurovic et al (2017-01-17; ⁠, ⁠, ; backlinks; similar):

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide statistical-significance level (p<5 × 10−8). Gene-based analysis identified an additional three Bonferroni-corrected statistically-significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e. = 0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional statistically-significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/​weight and smoking behavior, as well as a novel genetic association to the personality trait of Openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

“GW-SEM: A Statistical Package to Conduct Genome-Wide Structural Equation Modeling”, Verhulst 2017

2017-verhulst.pdf: “GW-SEM: A Statistical Package to Conduct Genome-Wide Structural Equation Modeling”⁠, Brad Verhulst (2017-01-01)

“Pleiotropic Genetic Effects Influencing Sleep and Neurological Disorders”, Veatch et al 2017

2017-veatch.pdf: “Pleiotropic genetic effects influencing sleep and neurological disorders”⁠, Olivia J. Veatch, Brendan T. Keenan, Philip R. Gehrman, Beth A. Malow, Allan I. Pack (2017-01-01)

“Hidden Heritability due to Heterogeneity across Seven Populations”, Tropf et al 2017

2017-tropf.pdf: “Hidden heritability due to heterogeneity across seven populations”⁠, Felix C. Tropf, S. Hong Lee, Renske M. Verweij, Gert Stulp, Peter J. van der Most, Ronald de Vlaming et al (2017-01-01)

“Psychiatric Genetics and the Structure of Psychopathology”, Smoller et al 2017

2017-smoller.pdf: “Psychiatric genetics and the structure of psychopathology”⁠, Jordan W. Smoller, Ole A. Andreassen, Howard J. Edenberg, Stephen V. Faraone, Stephen J. Glatt, Kenneth S. Kendler et al (2017-01-01)

“Prediction of Alcohol Use Disorder Using Personality Disorder Traits: a Twin Study”, Rosenström et al 2017

2017-rosenstrom.pdf: “Prediction of alcohol use disorder using personality disorder traits: a twin study”⁠, Tom Rosenström, Fartein Ask Torvik, Eivind Ystrom, Nikolai Olavi Czajkowski, Nathan A. Gillespie, Steven H. Aggen et al (2017-01-01)

“Genetic Evidence of Assortative Mating in Humans”, Robinson et al 2017

2017-robinson.pdf: “Genetic evidence of assortative mating in humans”⁠, Matthew R. Robinson, Aaron Kleinman, Mariaelisa Graff, Anna A. E. Vinkhuyzen, David Couper, Michael B. Miller et al (2017-01-01)

“Sensation Seeking and Impulsive Traits As Personality Endophenotypes for Antisocial Behavior: Evidence from Two Independent Samples”, Mann et al 2017

2017-mann.pdf: “Sensation seeking and impulsive traits as personality endophenotypes for antisocial behavior: Evidence from two independent samples”⁠, Frank D. Mann, Laura Engelhardt, Daniel A. Briley, Andrew D. Grotzinger, Megan W. Patterson, Jennifer L. Tackett et al (2017-01-01)

“Genome-wide Association Analysis Identifies 30 New Susceptibility Loci for Schizophrenia”, Li et al 2017

2017-li.pdf: “Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia”⁠, Zhiqiang Li, Jianhua Chen, Hao Yu, Lin He, Yifeng Xu, Dai Zhang, Qizhong Yi, Changgui Li, Xingwang Li et al (2017-01-01)

“High-Resolution Genetic Maps Identify Multiple Type 2 Diabetes Loci at Regulatory Hotspots in African Americans and Europeans”, Lau et al 2017

2017-lau.pdf: “High-Resolution Genetic Maps Identify Multiple Type 2 Diabetes Loci at Regulatory Hotspots in African Americans and Europeans”⁠, Winston Lau, Toby Andrew, Nikolas Maniatis (2017-01-01)

“Genetic Analysis in UK Biobank Links Insulin Resistance and Transendothelial Migration Pathways to Coronary Artery Disease”, Klarin et al 2017

2017-klarin.pdf: “Genetic analysis in UK Biobank links insulin resistance and transendothelial migration pathways to coronary artery disease”⁠, Derek Klarin, Qiuyu Martin Zhu, Connor A. Emdin, Mark Chaffin, Steven Horner, Brian J. McMillan, Alison Leed et al (2017-01-01)

“Identification of 153 New Loci Associated With Heel Bone Mineral Density and Functional Involvement of GPC6 in Osteoporosis”, Kemp et al 2017

2017-kemp.pdf: “Identification of 153 new loci associated with heel bone mineral density and functional involvement of GPC6 in osteoporosis”⁠, John P. Kemp, John A. Morris, Carolina Medina-Gomez, Vincenzo Forgetta, Nicole M. Warrington, Scott E. Youlten et al (2017-01-01)

“Genetic Contributors to Variation in Alcohol Consumption Vary by Race/ethnicity in a Large Multi-ethnic Genome-wide Association Study”, Jorgenson et al 2017

2017-jorgenson.pdf: “Genetic contributors to variation in alcohol consumption vary by race / ethnicity in a large multi-ethnic genome-wide association study”⁠, E Jorgenson, K. K Thai, T. J Hoffmann, L. C Sakoda, M. N Kvale, Y. Banda, C. Schaefer, N. Risch, J. Mertens et al (2017-01-01)

“Assessing Genetic and Environmental Influences on Epicardial and Abdominal Adipose Tissue Quantities: A Classical Twin Study”, Jermendy et al 2017

2017-jermendy.pdf: “Assessing genetic and environmental influences on epicardial and abdominal adipose tissue quantities: A classical twin study”⁠, A L. Jermendy, M. Kolossvary, Z. D Drobni, A. D Tarnoki, D. L Tarnoki, J. Karady, S. Voros, H. J Lamb et al (2017-01-01)

“Bayesian Analysis of Genetic Association across Tree-structured Routine Healthcare Data in the UK Biobank”, Cortes et al 2017

2017-cortes.pdf: “Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank”⁠, Adrian Cortes, Calliope A. Dendrou, Allan Motyer, Luke Jostins, Damjan Vukcevic, Alexander Dilthey, Peter Donnelly et al (2017-01-01)

“Leveraging Multi-Ethnic Evidence for Risk Assessment of Quantitative Traits in Minority Populations”, Coram et al 2017

2017-coram.pdf: “Leveraging Multi-Ethnic Evidence for Risk Assessment of Quantitative Traits in Minority Populations”⁠, Marc A. Coram, Huaying Fang, Sophie I. Candille, Themistocles L. Assimes, Hua Tang (2017-01-01)

“Genetic Correlation between Alcohol Preference and Conditioned Fear: Exploring a Functional Relationship”, Chester & Weera 2017

2017-chester.pdf: “Genetic correlation between alcohol preference and conditioned fear: Exploring a functional relationship”⁠, Julia A. Chester, Marcus M. Weera (2017-01-01)

“Genetic Correlations between Intraocular Pressure, Blood Pressure and Primary Open-angle Glaucoma: a Multi-cohort Analysis”, Aschard et al 2017

2017-aschard.pdf: “Genetic correlations between intraocular pressure, blood pressure and primary open-angle glaucoma: a multi-cohort analysis”⁠, Hugues Aschard, Jae H. Kang, Adriana I. Iglesias, Pirro Hysi, Jessica N. Cooke Bailey, Anthony P. Khawaja et al (2017-01-01)

“Association Between Schizophrenia-Related Polygenic Liability and the Occurrence and Level of Mood-Incongruent Psychotic Symptoms in Bipolar Disorder”, Association 2017

2017-allardyce.pdf: “Association Between Schizophrenia-Related Polygenic Liability and the Occurrence and Level of Mood-Incongruent Psychotic Symptoms in Bipolar Disorder”⁠, American Medical Association (2017-01-01)

“Genetic and Environmental Contributions to the Association Between Cannabis Use and Psychotic-Like Experiences in Young Adult Twins”, Nesvåg et al 2017

“Genetic and Environmental Contributions to the Association Between Cannabis Use and Psychotic-Like Experiences in Young Adult Twins”⁠, Ragnar Nesvåg, Ted Reichborn-Kjennerud, Nathan A. Gillespie, Gun Peggy Knudsen, Jørgen G. Bramness, Kenneth S. Kendler et al (2017; ; backlinks; similar):

To investigate contributions of genetic and environmental risk factors and possible direction of causation for the relationship between symptoms of cannabis use disorders (CUD) and psychotic-like experiences (PLEs), a population-based sample of 2793 young adult twins (63.5% female, mean [range] age 28.2 [19–36] y) were assessed for symptoms of CUD and PLEs using the Composite International Diagnostic Interview. Latent risk of having symptoms of CUD or PLEs was modeled using Item Response Theory. Co-twin control analysis was performed to investigate effect of familiar confounding for the association between symptoms of CUD and PLEs. Biometric twin models were fitted to estimate the heritability, genetic and environmental correlations, and direction for the association. Lifetime use of cannabis was reported by 10.4% of the twins, and prevalence of PLEs ranged from 0.1% to 2.2%. The incidence rate ratio of PLEs due to symptoms of CUD was 6.3 (95% CI, 3.9, 10.2) in the total sample and 3.5 (95% CI, 1.5, 8.2) within twin pairs. Heritability estimates for symptoms of CUD were 88% in men and women, and for PLEs 77% in men and 43% in women. The genetic and environmental correlations between symptoms of CUD and PLEs were 0.55 and 0.52, respectively. The model allowing symptoms of CUD to cause PLEs had a better fit than models specifying opposite or reciprocal directions of causation. The association between symptoms of CUD and PLEs is explained by shared genetic and environmental factors and direct effects from CUD to risk for PLEs.

“Single Nucleotide Polymorphism Heritability of a General Psychopathology Factor in Children”, Neumann et al 2016

2016-neumann.pdf: “Single Nucleotide Polymorphism Heritability of a General Psychopathology Factor in Children”⁠, Alexander Neumann, Irene Pappa, Benjamin B. Lahey, Frank C. Verhulst, Carolina Medina-Gomez, Vincent W. Jaddoe et al (2016-12-01; similar):

Objective: Co-occurrence of mental disorders is commonly observed, but the etiology underlying this observation is poorly understood. Studies in adolescents and adults have identified a general psychopathology factor associated with a high risk for different psychiatric disorders. We defined a multi-informant general psychopathology factor in school-aged children and estimated its single nucleotide polymorphism (SNP) heritability. The goal was to test the hypothesis that child behavioral and emotional problems are under the influence of highly pleiotropic common autosomal genetic variants that non-specifically increase the risk for different dimensions of psychopathology.

Method: Children from the Generation R cohort were repeatedly assessed between ages 6 to 8 years. Child behavior problems were reported by parents, teachers, and children. Confirmatory factor analysis estimated a general psychopathology factor across informants using various psychiatric problem scales. Validation of the general psychopathology factor was based on IQ and temperamental measures. Genome-wide complex trait analysis (GCTA) was used to estimate the SNP heritability (n = 2,115).

Results: The general psychopathology factor was associated with lower IQ, higher negative affectivity, and lower effortful control, but not with surgency. Importantly, the general psychopathology factor showed a statistically-significant SNP heritability of 38% (SE = 0.16, p = 0.008).

Conclusion: Common autosomal SNPs are pleiotropically associated with internalizing, externalizing, and other child behavior problems, and underlie a general psychopathology factor in childhood.

[Keywords: child behavior, psychopathology, comorbidity, genetic pleiotropy, SNP heritability]

“Genome-wide Analysis Identifies 12 Loci Influencing Human Reproductive Behavior”, Barban et al 2016

2016-barban.pdf: “Genome-wide analysis identifies 12 loci influencing human reproductive behavior”⁠, Nicola Barban, Rick Jansen, Ronald de Vlaming, Ahmad Vaez, Jornt J. Mandemakers, Felix C. Tropf, Xia Shen et al (2016-10-31; ; similar):

The genetic architecture of human reproductive behavior—age at first birth (AFB) and number of children ever born (NEB)—has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood.

We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are statistically-significantly associated with AFB and/​or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort.

These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.

“Partitioning Heritability Analysis Reveals a Shared Genetic Basis of Brain Anatomy and Schizophrenia”, Lee et al 2016

2016-lee.pdf: “Partitioning heritability analysis reveals a shared genetic basis of brain anatomy and schizophrenia”⁠, P. H. Lee, J. T. Baker, A. J. Holmes, N. Jahanshad, T. Ge, J-Y. Jung, Y. Cruz, D. S. Manoach, D. P. Hibar et al (2016-10-11; ; similar):

Schizophrenia is a devastating neurodevelopmental disorder with a complex genetic etiology. Widespread cortical gray matter loss has been observed in patients and prodromal samples. However, it remains unresolved whether schizophrenia-associated cortical structure variations arise due to disease etiology or secondary to the illness.

Here we address this question using a partitioning-based heritability analysis of genome-wide single-nucleotide polymorphism (SNP) and neuroimaging data from 1750 healthy individuals.

We find that schizophrenia-associated genetic variants explain a statistically-significantly enriched proportion of trait heritability in 8 brain phenotypes (false discovery rate = 10%). In particular, intracranial volume and left superior frontal gyrus thickness exhibit statistically-significant and robust associations with schizophrenia genetic risk under varying SNP selection conditions. Cross-disorder comparison suggests that the neuro-genetic architecture of schizophrenia-associated brain regions is, at least in part, shared with other psychiatric disorders.

Our study highlights key neuroanatomical correlates of schizophrenia genetic risk in the general population. These may provide fundamental insights into the complex pathophysiology of the illness, and a potential link to neurocognitive deficits shaping the disorder.

“Educational Attainment and Personality Are Genetically Intertwined”, Mõttus et al 2016

“Educational attainment and personality are genetically intertwined”⁠, René Mõttus, Anu Realo, Uku Vainik, Jüri Allik, Tõnu Esko (2016-09-28; ; similar):

It is possible that heritable variance in personality characteristics does not reflect (only) genetic and biological processes specific to personality per se. We tested the possibility that Five-Factor Model personality domains and facets, as rated by people themselves and their knowledgeable informants, reflect polygenic influences that have been previously associated with educational attainment. In a sample of over 3,000 adult Estonians, polygenic scores for educational attainment, based on small contributions from more than 150,000 genetic variants, were correlated with various personality traits, mostly from the Neuroticism and Openness domains. The correlations of personality characteristics with educational attainment-related polygenic influences reflected almost entirely their correlations with phenotypic educational attainment. Structural equation modeling of the associations between polygenic risk, personality (a weighed aggregate of education-related facets) and educational attainment lent relatively strongest support to the possibility of educational attainment mediating (explaining) some of the heritable variance in personality traits.

“Identification of 15 Genetic Loci Associated With Risk of Major Depression in Individuals of European Descent”, Hyde et al 2016

2016-hyde.pdf: “Identification of 15 genetic loci associated with risk of major depression in individuals of European descent”⁠, Craig L. Hyde, Michael W. Nagle, Chao Tian, Xing Chen, Sara A. Paciga, Jens R. Wendland, Joyce Y. Tung et al (2016-08-01; backlinks; similar):

Despite strong evidence supporting the heritability of major depressive disorder (MDD), previous genome-wide studies were unable to identify risk loci among individuals of European descent. We used self-report data from 75,607 individuals reporting clinical diagnosis of depression and 231,747 individuals reporting no history of depression through 23andMe and carried out meta-analysis of these results with published MDD genome-wide association study results. We identified five independent variants from four regions associated with self-report of clinical diagnosis or treatment for depression. Loci with a p value <1.0 × 10−5 in the meta-analysis were further analyzed in a replication data set (45,773 cases and 106,354 controls) from 23andMe. A total of 17 independent SNPs from 15 regions reached genome-wide statistical-significance after joint analysis over all three data sets. Some of these loci were also implicated in genome-wide association studies of related psychiatric traits. These studies provide evidence for large-scale consumer genomic data as a powerful and efficient complement to data collected from traditional means of ascertainment for neuropsychiatric disease genomics.

“The Genetics of Success: How Single-Nucleotide Polymorphisms Associated With Educational Attainment Relate to Life-Course Development”, Belsky et al 2016

2016-belsky.pdf: “The Genetics of Success: How Single-Nucleotide Polymorphisms Associated With Educational Attainment Relate to Life-Course Development”⁠, Daniel W. Belsky, Terrie E. Moffitt, David L. Corcoran, Benjamin Domingue, HonaLee Harrington, Sean Hogan et al (2016-06-01; ⁠, ⁠, ⁠, ⁠, ; backlinks; similar):

A previous genome-wide association study (GWAS) of more than 100,000 individuals identified molecular-genetic predictors of educational attainment.

We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the 4-decade Dunedin Study (N = 918). There were 5 main findings.

  1. polygenic scores predicted adult economic outcomes even after accounting for educational attainments.
  2. genes and environments were correlated: Children with higher polygenic scores were born into better-off homes.
  3. children’s polygenic scores predicted their adult outcomes even when analyses accounted for their social-class origins; social-mobility analysis showed that children with higher polygenic scores were more upwardly mobile than children with lower scores.
  4. polygenic scores predicted behavior across the life course, from early acquisition of speech and reading skills through geographic mobility and mate choice and on to financial planning for retirement.
  5. polygenic-score associations were mediated by psychological characteristics, including intelligence, self-control, and interpersonal skill. Effect sizes were small.

Factors connecting GWAS sequence with life outcomes may provide targets for interventions to promote population-wide positive development.

[Keywords: genetics, behavior genetics, intelligence, personality, adult development]

“Genetic Overlap between Schizophrenia and Developmental Psychopathology: a Longitudinal Approach Applied to Common Childhood Disorders between Age 7 and 15 Years”, Nivard et al 2016

“Genetic overlap between schizophrenia and developmental psychopathology: a longitudinal approach applied to common childhood disorders between age 7 and 15 years”⁠, Michel G. Nivard, Suzanne H. Gage, Jouke J. Hottenga, Catherina E. M. van Beijsterveldt, Abdel Abdellaoui et al (2016-05-11; ; similar):

Various non-psychotic psychiatric disorders in childhood and adolescence can precede the onset of schizophrenia, but the nature of this relationship remains unclear. We investigated to what extent the association between schizophrenia and psychiatric disorders in childhood is explained by shared genetic risk factors.

Polygenic risk scores (PRS), reflecting an individual’s genetic risk for schizophrenia, were constructed for participants in two birth cohorts (2,588 children from the Netherlands Twin Register (NTR) and 6,127 from the Avon Longitudinal Study of Parents And Children (ALSPAC)). The associations between schizophrenia PRS and measures of anxiety, depression, attention deficit hyperactivity disorder (ADHD), and oppositional defiant disorder/​conduct disorder (ODD/​CD) were estimated at age 7, 10, 12–13 and 15 years in the two cohorts. Results were then meta-analyzed, and age-effects and differences in the associations between disorders and PRS were formally tested in a meta-regression.

The schizophrenia PRS was associated with childhood and adolescent psychopathology Where the association was weaker for ODD/​CD at age 7. The associations increased with age this increase was steepest for ADHD and ODD/​CD. The results are consistent with a common genetic etiology of schizophrenia and developmental psychopathology as well as with a stronger shared genetic etiology between schizophrenia and adolescent onset psychopathology.

A multivariate meta-analysis of multiple and repeated observations enabled to optimally use the longitudinal data across diagnoses in order to provide knowledge on how childhood disorders develop into severe adult psychiatric disorders.

“Genome-wide Analyses of Empathy and Systemizing: Heritability and Correlates With Sex, Education, and Psychiatric Risk”, Warrier et al 2016

“Genome-wide analyses of empathy and systemizing: heritability and correlates with sex, education, and psychiatric risk”⁠, Varun Warrier, Roberto Toro, Bhismadev Chakrabarti, Nadia Litterman, David A. Hinds, Thomas Bourgeron et al (2016-04-29; ⁠, ; similar):

Empathy is the drive to identify the mental states of others and respond to these with an appropriate emotion. Systemizing is the drive to analyse or build lawful systems. Difficulties in empathy have been identified in different psychiatric conditions including autism and schizophrenia. In this study, we conducted genome-wide association studies of empathy and systemizing using the Empathy Quotient (EQ) (n = 46,861) and the Systemizing Quotient-Revised (SQ-R) (n = 51,564) in participants from 23andMe, Inc. We confirmed significant sex-differences in performance on both tasks, with a male advantage on the SQ-R and female advantage on the EQ. We found highly significant heritability explained by single nucleotide polymorphisms (SNPs) for both the traits (EQ: 0.11±0.014; p = 1.7 × 10−14 and SQ-R: 0.12±0.012; p = 1.2 × 10−20) and these were similar for males and females. However, genes with higher expression in the male brain appear to contribute to the male advantage for the SQ-R. Finally, we identified statistically-significant genetic correlations between high score for empathy and risk for schizophrenia (p = 2.5 × 10−5), and correlations between high score for systemizing and higher educational attainment (p = 5 × 10−4). These results shed light on the genetic contribution to individual differences in empathy and systemizing, two major cognitive functions of the human brain.

“Education and Social Trust: Testing a Causal Hypothesis Using the Discordant Twin Design”, Oskarsson et al 2016

2016-oskarsson.pdf: “Education and Social Trust: Testing a Causal Hypothesis Using the Discordant Twin Design”⁠, Sven Oskarsson, Peter Thisted Dinesen, Christopher T. Dawes, Magnus Johannesson, Patrik K. E. Magnusson et al (2016-04-27; ; similar):

One of the clearest results in previous studies on social trust is the robust positive relationship with educational attainment. The most common interpretation is that education has a causal effect on social trust. The theoretical argument and empirical results in this article suggest a different interpretation. We argue that common pre-adult factors such as cognitive abilities and personality traits rooted in genes and early-life family environment may confound the relationship between educational attainment and social trust. We provide new evidence on this question by utilizing the quasi-experiment of twinning. By looking at the relationship between education and social trust within monozygotic (MZ) twin pairs, we are able to avoid potential confounders rooted in genetic factors and common environmental influences because the monozygotic twins share both. The results suggest that when controlling for such familial factors the estimated effects of education on social trust are close to zero and far from reaching statistical-significance. Further analyses show that the relationship between education and social trust largely is driven by common genetic factors.

“Lifespan and Skeletal Muscle Properties: The Effects of Genetic Background, Physical Activity and Aging”, Karvinen 2016

2016-karvinen.pdf: “Lifespan and Skeletal Muscle Properties: The Effects of Genetic Background, Physical Activity and Aging”⁠, Sira Karvinen (2016-04-22; ; backlinks; similar):

Obesity and metabolic disorders have become a notable world-wide epidemic. The pathogenesis of metabolic diseases, such as metabolic syndrome and type 2 diabetes, has begun to negatively affect life expectancy of current generations. Low aerobic capacity has shown to be a strong predictor of mortality both in rodents and humans. Exercise is known to increase an individual’s aerobic capacity; interestingly, recent studies have suggested that genetic background may play a substantial role in the physical activity level of an individual. The purpose of this study was to investigate the role of genetic background and physical activity on skeletal muscle properties, metabolism and lifespan.

The study consisted of three parts:

  1. a cross-sectional voluntary running intervention in high-capacity runner (HCR) and low-capacity runner (LCR) rats,
  2. a longitudinal voluntary running intervention in HCR and LCR rats, and
  3. a long-term follow-up study with physical activity discordant human twins.

Our study showed that low intrinsic aerobic capacity is associated with fast muscular fatigue and slow metabolic recovery after maximal muscle contractions. At the whole-body level, low intrinsic aerobic capacity was linked to low body temperature, which may play a role in the onset of gaining extra weight and, thus, developing metabolic disorders. High intrinsic aerobic capacity in turn was associated with elevated SIRT3 protein level in skeletal muscle, which is possibly linked to increased lifespan. Nevertheless, vigorous physical activity commenced at adult age did not reduce mortality or increase lifespan in rodents. High long-term participation in vigorous leisure-time physical activity did predict statistically-significantly reduced mortality in dizygotic twins; however, there was no difference in the lifespan of monozygotic twins that are genetically identical. HCRs were more physically active both in control and voluntary running groups when compared to corresponding LCR groups. Also, the persistent discordances in participation of vigorous physical activity were statistically-significantly more common in dizygotic twin pairs than in monozygotic pairs stating that genes have an influence on the persistent voluntary participation in vigorous leisure-time physical activity.

Our results indicated that genetic predisposition plays a substantial role in exercise participation, hence, genetic pleiotropy may partly explain the associations observed previously between high physical activity and mortality.

  1. Torvinen et al 2012, “Rats bred for low aerobic capacity become promptly fatigued and have slow metabolic recovery after stimulated, maximal muscle contractions”
  2. Karvinen et al 2012, “Physical activity in adulthood: genes and mortality”
  3. Karvinen et al 2016, “Effects of intrinsic aerobic capacity, aging and voluntary running on skeletal muscle sirtuins and heat shock proteins”
  4. Karvinen et al 2016, “Voluntary running aids to maintain high body temperature in rats bred for high aerobic capacity”

“Physical and Neurobehavioral Determinants of Reproductive Onset and Success”, Day et al 2016

2016-day.pdf: “Physical and neurobehavioral determinants of reproductive onset and success”⁠, Felix R. Day, Hannes Helgason, Daniel I. Chasman, Lynda M. Rose, Po-Ru Loh, Robert A. Scott, Agnar Helgason et al (2016-04-18; backlinks; similar):

The ages of puberty, first sexual intercourse and first birth signify the onset of reproductive ability, behavior and success, respectively. In a genome-wide association study of 125,667 UK Biobank participants, we identify 38 loci associated (p < 5 × 10−8) with age at first sexual intercourse. These findings were taken forward in 241,910 men and women from Iceland and 20,187 women from the Women’s Genome Health Study. Several of the identified loci also exhibit associations (p < 5 × 10−8) with other reproductive and behavioral traits, including age at first birth (variants in or near ESR1 and RBM6-SEMA3F), number of children (CADM2 and ESR1), irritable temperament (MSRA) and risk-taking propensity (CADM2). Mendelian randomization analyses infer causal influences of earlier puberty timing on earlier first sexual intercourse, earlier first birth and lower educational attainment. In turn, likely causal consequences of earlier first sexual intercourse include reproductive, educational, psychiatric and cardiometabolic outcomes.

“Molecular Genetic Contributions to Self-rated Health”, Harris et al 2016

“Molecular genetic contributions to self-rated health”⁠, Sarah E. Harris, Saskia P. Hagenaars, Gail Davies, W. David Hill, David CM Liewald, Stuart J. Ritchie et al (2016-04-12; ⁠, ⁠, ; similar):

Background: Poorer self-rated health (SRH) predicts worse health outcomes, even when adjusted for objective measures of disease at time of rating. Twin studies indicate SRH has a heritability of up to 60% and that its genetic architecture may overlap with that of personality and cognition.

Methods: We carried out a genome-wide association study (GWAS) of SRH on 111 749 members of the UK Biobank sample. Univariate genome-wide complex trait analysis (GCTA)-GREML analyses were used to estimate the proportion of variance explained by all common autosomal SNPs for SRH. Linkage Disequilibrium (LD) score regression and polygenic risk scoring, two complementary methods, were used to investigate pleiotropy between SRH in UK Biobank and up to 21 health-related and personality and cognitive traits from published GWAS consortia.

Results: The GWAS identified 13 independent signals associated with SRH, including several in regions previously associated with diseases or disease-related traits. The strongest signal was on chromosome 2 (rs2360675, p = 1.77×10−10) close to KLF7, which has previously been associated with obesity and type 2 diabetes⁠. A second strong peak was identified on chromosome 6 in the major histocompatibility region (rs76380179, p = 6.15×10−10). The proportion of variance in SRH that was explained by all common genetic variants was 13%. Polygenic scores for the following traits and disorders were associated with SRH: cognitive ability, education, neuroticism, BMI, longevity, ADHD, major depressive disorder, schizophrenia, lung function, blood pressure, coronary artery disease, large vessel disease stroke, and type 2 diabetes.

Conclusion: Individual differences in how people respond to a single item on SRH are partly explained by their genetic propensity to many common psychiatric and physical disorders and psychological traits.

Key Messages

Genetic variants associated with common diseases and psychological traits are associated with self-rated health.

The SNP-based heritability of self-rated health is 0.13 (SE 0.006).

There is pleiotropy between self-rated health and psychiatric and physical diseases and psychological traits.

“Genome-wide Association Study of Cognitive Functions and Educational Attainment in UK Biobank (n = 112 151)”, Davies et al 2016

“Genome-wide association study of cognitive functions and educational attainment in UK Biobank (n = 112 151)”⁠, G. Davies, R. E. Marioni, D. C. Liewald, W. D. Hill, S. P. Hagenaars, S. E. Harris, S. J. Ritchie, M. Luciano et al (2016-04-05; ⁠, ⁠, ; backlinks; similar):

People’s differences in cognitive functions are partly heritable and are associated with important life outcomes. Previous genome-wide association (GWA) studies of cognitive functions have found evidence for polygenic effects yet, to date, there are few replicated genetic associations. Here we use data from the UK Biobank sample to investigate the genetic contributions to variation in tests of three cognitive functions and in educational attainment. GWA analyses were performed for verbal-numerical reasoning (n = 36 035), memory (n = 112 067), reaction time (n = 111 483) and for the attainment of a college or an university degree (n = 111 114). We report genome-wide statistically-significant single-nucleotide polymorphism (SNP)-based associations in 20 genomic regions, and statistically-significant gene-based findings in 46 regions. These include findings in the ATXN2, CYP2DG, APBA1 and CADM2 genes. We report replication of these hits in published GWA studies of cognitive function, educational attainment and childhood intelligence. There is also replication, in UK Biobank, of SNP hits reported previously in GWA studies of educational attainment and cognitive function. GCTA-GREML analyses, using common SNPs (minor allele frequency>0.01), indicated statistically-significant SNP-based heritabilities of 31% (s.e.m. = 1.8%) for verbal-numerical reasoning, 5% (s.e.m. = 0.6%) for memory, 11% (s.e.m. = 0.6%) for reaction time and 21% (s.e.m. = 0.6%) for educational attainment. Polygenic score analyses indicate that up to 5% of the variance in cognitive test scores can be predicted in an independent cohort. The genomic regions identified include several novel loci, some of which have been associated with intracranial volume, neurodegeneration, Alzheimer’s disease and schizophrenia.

“Genetic Contributions to Self-reported Tiredness”, Deary et al 2016

“Genetic contributions to self-reported tiredness”⁠, Vincent Deary, Saskia P. Hagenaars, Sarah E. Harris, W. David Hill, Gail Davies, David CM Liewald, International Consortium for Blood Pressure GWAS et al (2016-04-05; ; similar):

Self-reported tiredness and low energy, often called fatigue, is associated with poorer physical and mental health. Twin studies have indicated that this has a heritability between 6% and 50%. In the UK Biobank sample (n = 108 976) we carried out a genome-wide association study of responses to the question, “Over the last two weeks, how often have you felt tired or had little energy?” Univariate GCTA-GREML found that the proportion of variance explained by all common SNPs for this tiredness question was 8.4% (SE = 0.6%). GWAS identified one genome-wide statistically-significant hit (Affymetrix id 1:64178756_C_T; p = 1.36 x 10−11). LD score regression and polygenic profile analysis were used to test for pleiotropy between tiredness and up to 28 physical and mental health traits from GWAS consortia. Significant genetic correlations were identified between tiredness and BMI, HDL cholesterol, forced expiratory volume, grip strength, HbA1c, longevity, obesity, self-rated health, smoking status, triglycerides, type 2 diabetes⁠, waist-hip ratio, ADHD, bipolar disorder, major depressive disorder, neuroticism, schizophrenia, and verbal-numerical reasoning (absolute rg effect sizes between 0.11 and 0.78). Significant associations were identified between tiredness phenotypic scores and polygenic profile scores for BMI, HDL cholesterol, LDL cholesterol, coronary artery disease, HbA1c, height, obesity, smoking status, triglycerides, type 2 diabetes, and waist-hip ratio, childhood cognitive ability, neuroticism, bipolar disorder, major depressive disorder, and schizophrenia (standardised β’s between −0.016 and 0.03). These results suggest that tiredness is a partly-heritable, heterogeneous and complex phenomenon that is phenotypically and genetically associated with affective, cognitive, personality, and physiological processes.

“Hech, sirs! But I’m wabbit, I’m back frae the toon;

I ha’ena dune pechin’—jist let me sit doon.

From Glesca’

By William Dixon Cocker (1882-1970)

“Embryo Selection For Intelligence”, Branwen 2016

Embryo-selection: “Embryo Selection For Intelligence”⁠, Gwern Branwen (2016-01-22; ⁠, ⁠, ⁠, ⁠, ⁠, ⁠, ⁠, ; backlinks; similar):

A cost-benefit analysis of the marginal cost of IVF-based embryo selection for intelligence and other traits with 2016-2017 state-of-the-art

With genetic predictors of a phenotypic trait, it is possible to select embryos during an in vitro fertilization process to increase or decrease that trait. Extending the work of Shulman & Bostrom 2014⁠/​Hsu 2014⁠, I consider the case of human intelligence using SNP-based genetic prediction, finding:

  • a meta-analysis of GCTA results indicates that SNPs can explain >33% of variance in current intelligence scores, and >44% with better-quality phenotype testing
  • this sets an upper bound on the effectiveness of SNP-based selection: a gain of 9 IQ points when selecting the top embryo out of 10
  • the best 2016 polygenic score could achieve a gain of ~3 IQ points when selecting out of 10
  • the marginal cost of embryo selection (assuming IVF is already being done) is modest, at $1,822.7[^\$1,500.0^~2016~]{.supsub} + $243.0[^\$200.0^~2016~]{.supsub} per embryo, with the sequencing cost projected to drop rapidly
  • a model of the IVF process, incorporating number of extracted eggs, losses to abnormalities & vitrification & failed implantation & miscarriages from 2 real IVF patient populations, estimates feasible gains of 0.39 & 0.68 IQ points
  • embryo selection is currently unprofitable (mean: -$435.0[^\$358.0^~2016~]{.supsub}) in the USA under the lowest estimate of the value of an IQ point, but profitable under the highest (mean: $7,570.3[^\$6,230.0^~2016~]{.supsub}). The main constraints on selection profitability is the polygenic score; under the highest value, the NPV EVPI of a perfect SNP predictor is $29.2[^\$24.0^~2016~]{.supsub}b and the EVSI per education/​SNP sample is $86.3[^\$71.0^~2016~]{.supsub}k
  • under the worst-case estimate, selection can be made profitable with a better polygenic score, which would require n > 237,300 using education phenotype data (and much less using fluid intelligence measures)
  • selection can be made more effective by selecting on multiple phenotype traits: considering an example using 7 traits (IQ/​height/​BMI/​diabetes/​ADHD⁠/​bipolar/​schizophrenia), there is a factor gain over IQ alone; the outperformance of multiple selection remains after adjusting for genetic correlations & polygenic scores and using a broader set of 16 traits.

“Genetic Factor Common to Schizophrenia and HIV Infection Is Associated With Risky Sexual Behavior: Antagonistic vs. Synergistic Pleiotropic SNPs Enriched for Distinctly Different Biological Functions”, Wang et al 2016

2016-wang.pdf: “Genetic factor common to schizophrenia and HIV infection is associated with risky sexual behavior: antagonistic vs. synergistic pleiotropic SNPs enriched for distinctly different biological functions”⁠, Qian Wang, Renato Polimanti, Henry R. Kranzler, Lindsay A. Farrer, Hongyu Zhao, Joel Gelernter (2016-01-01)

“Not All Risks Are Created Equal: A Twin Study and Meta-analyses of Risk Taking across Seven Domains”, Wang et al 2016b

2016-wang-2.pdf: “Not all risks are created equal: A twin study and meta-analyses of risk taking across seven domains”⁠, Xiao-Tian Wang, Rui Zheng, Yan-Hua Xuan, Jie Chen, Shu Li (2016-01-01)

“Genetic Overlap between Attention-Deficit/Hyperactivity Disorder and Bipolar Disorder: Evidence from GWAS Meta-analysisMeta-analysis of ADHD and BPD GWAS”, Hulzen et al 2016

2016-vanhulzen.pdf: “Genetic overlap between Attention-Deficit / Hyperactivity Disorder and Bipolar Disorder: Evidence from GWAS meta-analysisMeta-analysis of ADHD and BPD GWAS”⁠, Kimm J. E. van Hulzen, Claus J. Scholz, Barbara Franke, Stephan Ripke, Marieke Klein, Andrew McQuillin et al (2016-01-01)

“Genome-wide Analysis of over 106 000 Individuals Identifies 9 Neuroticism-associated Loci”, Smith et al 2016

2016-smith.pdf: “Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci”⁠, D J. Smith, V. Escott-Price, G. Davies, M. E S. Bailey, L. Colodro-Conde, J. Ward, A. Vedernikov, R. Marioni et al (2016; ⁠, ; similar):

Neuroticism is a personality trait of fundamental importance for psychological well-being and public health. It is strongly associated with major depressive disorder (MDD) and several other psychiatric conditions. Although neuroticism is heritable, attempts to identify the alleles involved in previous studies have been limited by relatively small sample sizes. Here we report a combined meta-analysis of genome-wide association study (GWAS) of neuroticism that includes 91 370 participants from the UK Biobank cohort, 6659 participants from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and 8687 participants from a QIMR (Queensland Institute of Medical Research) Berghofer Medical Research Institute (QIMR) cohort. All participants were assessed using the same neuroticism instrument, the Eysenck Personality Questionnaire-Revised (EPQ-R-S) Short Form’s Neuroticism scale. We found a single-nucleotide polymorphism-based heritability estimate for neuroticism of ~15% (s.e. = 0.7%). Meta-analysis identified nine novel loci associated with neuroticism. The strongest evidence for association was at a locus on chromosome 8 (P = 1.5 × 10−15) spanning 4 Mb and containing at least 36 genes. Other associated loci included interesting candidate genes on chromosome 1 (GRIK3 (glutamate receptor ionotropic kainate 3)), chromosome 4 (KLHL2 (Kelch-like protein 2)), chromosome 17 (CRHR1 (corticotropin-releasing hormone receptor 1) and MAPT (microtubule-associated protein Tau)) and on chromosome 18 (CELF4 (CUGBP elav-like family member 4)). We found no evidence for genetic differences in the common allelic architecture of neuroticism by sex. By comparing our findings with those of the Psychiatric Genetics Consortia, we identified a strong genetic correlation between neuroticism and MDD and a less strong but statistically-significant genetic correlation with schizophrenia, although not with bipolar disorder. Polygenic risk scores derived from the primary UK Biobank sample captured ~1% of the variance in neuroticism in the GS:SFHS and QIMR samples, although most of the genome-wide statistically-significant alleles identified within a UK Biobank-only GWAS of neuroticism were not independently replicated within these cohorts. The identification of nine novel neuroticism-associated loci will drive forward future work on the neurobiology of neuroticism and related phenotypes.

“Alcohol Use Disorder and Divorce: Evidence for a Genetic Correlation in a Population-based Swedish Sample”, Salvatore et al 2016

2016-salvatore.pdf: “Alcohol use disorder and divorce: Evidence for a genetic correlation in a population-based Swedish sample”⁠, Jessica E. Salvatore, Sara Larsson Lönn, Jan Sundquist, Paul Lichtenstein, Kristina Sundquist, Kenneth S. Kendler et al (2016-01-01)

“Genetic Risk for Autism Spectrum Disorders and Neuropsychiatric Variation in the General Population”, Robinson et al 2016

2016-robinson.pdf: “Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population”⁠, Elise B. Robinson, Beate St Pourcain, Verneri Anttila, Jack A. Kosmicki, Brendan Bulik-Sullivan, Jakob Grove et al (2016-01-01)

“Schizophrenia Risk Alleles and Neurodevelopmental Outcomes in Childhood: a Population-based Cohort Study”, Riglin et al 2016

2016-riglin.pdf: “Schizophrenia risk alleles and neurodevelopmental outcomes in childhood: a population-based cohort study”⁠, Lucy Riglin, Stephan Collishaw, Alexander Richards, Ajay K. Thapar, Barbara Maughan, Michael C. O’Donovansych et al (2016-01-01; )

“Detection and Interpretation of Shared Genetic Influences on 42 Human Traits”, Berisa et al 2016

2016-pickrell.pdf: “Detection and interpretation of shared genetic influences on 42 human traits”⁠, Tomaz Berisa, Jimmy Z. Liu, Laure Ségurel, Joyce Y. Tung, David A. Hinds, Joseph K. Pickrell (2016-01-01)

“On the Relationship Between Domain-Specific Creative Achievement and Sexual Orientation in Swedish Twins”, Mosing et al 2016

2016-mosing.pdf: “On the Relationship Between Domain-Specific Creative Achievement and Sexual Orientation in Swedish Twins”⁠, Miriam A. Mosing, Karin J. H. Verweij, Christoph Abé, Örjan Manzano, Fredrik Ullén (2016-01-01)

“Genome-wide Associations for Birth Weight and Correlations With Adult Disease”, Horikoshi et al 2016

2016-horikoshi.pdf: “Genome-wide associations for birth weight and correlations with adult disease”⁠, Momoko Horikoshi, Robin N. Beaumont, Felix R. Day, Nicole M. Warrington, Marjolein N. Kooijman, Juan Fernandez-Tajes et al (2016-01-01)

“Genome-Wide Association Study of Loneliness Demonstrates a Role for Common Variation”, Gao et al 2016

2016-gao.pdf: “Genome-Wide Association Study of Loneliness Demonstrates a Role for Common Variation”⁠, Jianjun Gao, Lea K. Davis, Amy B. Hart, Sandra Sanchez-Roige, Lide Han, John T. Cacioppo, Abraham A. Palmer et al (2016-01-01)

“Predicting Cognitive Executive Functioning With Polygenic Risk Scores for Psychiatric Disorders”, Benca et al 2016

2016-benca.pdf: “Predicting Cognitive Executive Functioning with Polygenic Risk Scores for Psychiatric Disorders”⁠, Chelsie E. Benca, Jaime L. Derringer, Robin P. Corley, Susan E. Young, Matthew C. Keller, John K. Hewitt et al (2016-01-01)

“Novel Genetic Loci Underlying Human Intracranial Volume Identified through Genome-wide Association”, Adams et al 2016

2016-adams.pdf: “Novel genetic loci underlying human intracranial volume identified through genome-wide association”⁠, Hieab H. H Adams, Derrek P. Hibar, Vincent Chouraki, Jason L. Stein, Paul A. Nyquist, Miguel E. Rentería et al (2016-01-01)

“Top 10 Replicated Findings From Behavioral Genetics”, Plomin et al 2016-page-10

2016-plomin.pdf#page=10: “Top 10 Replicated Findings From Behavioral Genetics”⁠, Robert Plomin, John C. DeFries, Valerie S. Knopik, Jenae M. Neiderhiser (2016; ⁠, ⁠, ⁠, ; backlinks; similar):

Finding 7. Most measures of the “environment” show substantial genetic influence

Although it might seem a peculiar thing to do, measures of the environment widely used in psychological science—such as parenting, social support, and life events—can be treated as dependent measures in genetic analyses. If they are truly measures of the environment, they should not show genetic influence. To the contrary, in 1991, Plomin and Bergeman conducted a review of the first 18 studies in which environmental measures were used as dependent measures in genetically sensitive designs and found evidence for genetic influence for these measures of the environment. Substantial genetic influence was found for objective measures such as videotaped observations of parenting as well as self-report measures of parenting, social support, and life events. How can measures of the environment show genetic influence? The reason appears to be that such measures do not assess the environment independent of the person. As noted earlier, humans select, modify, and create environments correlated with their genetic behavioral propensities such as personality and psychopathology (McAdams, Gregory, & Eley, 2013). For example, in studies of twin children, parenting has been found to reflect genetic differences in children’s characteristics such as personality and psychopathology (Avinun & Knafo, 2014; Klahr & Burt, 2014; Plomin, 1994).

Since 1991, more than 150 articles have been published in which environmental measures were used in genetically sensitive designs; they have shown consistently that there is substantial genetic influence on environmental measures, extending the findings from family environments to neighborhood, school, and work environments. Kendler and Baker (2007) conducted a review of 55 independent genetic studies and found an average heritability of 0.27 across 35 diverse environmental measures (confidence intervals not available). Meta-analyses of parenting, the most frequently studied domain, have shown genetic influence that is driven by child characteristics (Avinun & Knafo, 2014) as well as by parent characteristics (Klahr & Burt, 2014). Some exceptions have emerged. Not surprisingly, when life events are separated into uncontrollable events (eg. death of a spouse) and controllable life events (eg. financial problems), the former show nonsignificant genetic influence. In an example of how all behavioral genetic results can differ in different cultures, Shikishima, Hiraishi, Yamagata, Neiderhiser, and Ando (2012) compared parenting in Japan and Sweden and found that parenting in Japan showed more genetic influence than in Sweden, consistent with the view that parenting is more child centered in Japan than in the West.

Researchers have begun to use GCTA to replicate these findings from twin studies. For example, GCTA has been used to show substantial genetic influence on stressful life events (Power et al 2013) and on variables often used as environmental measures in epidemiological studies such as years of schooling (C. A. Rietveld, Medland, et al 2013). Use of GCTA can also circumvent a limitation of twin studies of children. Such twin studies are limited to investigating within-family (twin-specific) experiences, whereas many important environmental factors such as socioeconomic status (SES) are the same for two children in a family. However, researchers can use GCTA to assess genetic influence on family environments such as SES that differ between families, not within families. GCTA has been used to show genetic influence on family SES (Trzaskowski et al 2014) and an index of social deprivation (Marioni et al 2014).

“The Biodemography of Fertility: A Review and Future Research Frontiers”, Mills & Tropf 2015

“The Biodemography of Fertility: A Review and Future Research Frontiers”⁠, Melinda C. Mills, Felix C. Tropf (2015-09-21; ⁠, ; backlinks; similar):

The social sciences have been reticent to integrate a biodemographic approach to the study of fertility choice and behaviour, resulting in theories and findings that are largely socially-deterministic. The aim of this paper is to first reflect on reasons for this lack of integration, provide a review of previous examinations, take stock of what we have learned until now and propose future research frontiers. We review the early foundations of proximate determinants followed by behavioural genetic (family and twin) studies that isolated the extent of genetic influence on fertility traits. We then discuss research that considers gene and environment interaction and the importance of cohort and country-specific estimates, followed by multivariate models that explore motivational precursors to fertility and education. The next section on molecular genetics reviews fertility-related candidate gene studies and their shortcomings and on-going work on genome wide association studies. Work in evolutionary anthropology and biology is then briefly examined, focusing on evidence for natural selection. Biological and genetic factors are relevant in explaining and predicting fertility traits, with socio-environmental factors and their interaction still key in understanding outcomes. Studying the interplay between genes and the environment, new data sources and integration of new methods will be central to understanding and predicting future fertility trends.

[Keywords: fertility, age at first birth, number of children ever born, genetics, behavioural genetics, molecular genetics, natural selection]

“Polygenic Risk Scores for Schizophrenia and Bipolar Disorder Predict Creativity”, Power et al 2015

2015-power.pdf: “Polygenic risk scores for schizophrenia and bipolar disorder predict creativity”⁠, Robert A. Power, Stacy Steinberg, Gyda Bjornsdottir, Cornelius A. Rietveld, Abdel Abdellaoui, Michel M. Nivard et al (2015-06-08; ; backlinks; similar):

We tested whether polygenic risk scores for schizophrenia and bipolar disorder would predict creativity. Higher scores were associated with artistic society membership or creative profession in both Icelandic (p = 5.2 × 10−6 and 3.8 × 10−6 for schizophrenia and bipolar disorder scores, respectively) and replication cohorts (p = 0.0021 and 0.00086). This could not be accounted for by increased relatedness between creative individuals and those with psychoses, indicating that creativity and psychosis share genetic roots.

“Mendelian Randomization With Invalid Instruments: Effect Estimation and Bias Detection through Egger Regression (MR-Egger)”, Bowden et al 2015

“Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression (MR-Egger)”⁠, Jack Bowden, George Davey Smith, Stephen Burgess (2015-06-06; ; backlinks; similar):

  • Mendelian randomization analyses using multiple genetic variants can be viewed as a meta-analysis of the causal estimates from each variant.
  • If the genetic variants have pleiotropic effects on the outcome, these causal estimates will be biased.
  • Funnel plots offer a simple way to detect directional pleiotropy; that is, whether causal estimates from weaker variants tend to be skewed in one direction.
  • Under a weaker set of assumptions than typically used in Mendelian randomization, an adaption of Egger regression (MR-Egger) can be used to detect and correct for the bias due to directional pleiotropy.

Background: The number of Mendelian randomization analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome-wide association studies, and the desire to obtain more precise estimates of causal effects. However, some genetic variants may not be valid instrumental variables, in particular due to them having more than one proximal phenotypic correlate (pleiotropy).

Methods: We view Mendelian randomization with multiple instruments as a meta-analysis, and show that bias caused by pleiotropy can be regarded as analogous to small study bias. Causal estimates using each instrument can be displayed visually by a funnel plot to assess potential asymmetry. Egger regression⁠, a tool to detect small study bias in meta-analysis, can be adapted to test for bias from pleiotropy, and the slope coefficient from Egger regression provides an estimate of the causal effect. Under the assumption that the association of each genetic variant with the exposure is independent of the pleiotropic effect of the variant (not via the exposure), Egger’s test gives a valid test of the null causal hypothesis and a consistent causal effect estimate even when all the genetic variants are invalid instrumental variables⁠.

Results: We illustrate the use of this approach by re-analysing 2 published Mendelian randomization studies of the causal effect of height on lung function, and the causal effect of blood pressure on coronary artery disease risk. The conservative nature of this approach is illustrated with these examples.

Conclusions: An adaption of Egger regression (which we call MR-Egger) can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations. The approach provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation.

[Keywords: Mendelian randomization⁠, invalid instruments, meta-analysis⁠, pleiotropy⁠, small study bias, MR-Egger test]

“Infertility Etiologies Are Genetically and Clinically Linked With Other Diseases in Single Meta-diseases”, Tarín et al 2015

“Infertility etiologies are genetically and clinically linked with other diseases in single meta-diseases”⁠, Juan J. Tarín, Miguel A. García-Pérez, Toshio Hamatani, Antonio Cano (2015-05-15; ; backlinks; similar):

The present review aims to ascertain whether different infertility etiologies share particular genes and/​or molecular pathways with other pathologies and are associated with distinct and particular risks of later-life morbidity and mortality. In order to reach this aim, we use two different sources of information: (1) a public web server named DiseaseConnect focused on the analysis of common genes and molecular mechanisms shared by diseases by integrating comprehensive omics and literature data; and (2) a literature search directed to find clinical comorbid relationships of infertility etiologies with only those diseases appearing after infertility is manifested. This literature search is performed because DiseaseConnect web server does not discriminate between pathologies emerging before, concomitantly or after infertility is manifested. Data show that different infertility etiologies not only share particular genes and/​or molecular pathways with other pathologies but they have distinct clinical relationships with other diseases appearing after infertility is manifested. In particular, (1) testicular and high-grade prostate cancer in male infertility; (2) non-fatal stroke and endometrial cancer, and likely non-fatal coronary heart disease and ovarian cancer in polycystic ovary syndrome; (3) osteoporosis, psychosexual dysfunction, mood disorders and dementia in premature ovarian failure; (4) breast and ovarian cancer in carriers of BRCA1/​2 mutations in diminished ovarian reserve; (5) clear cell and endometrioid histologic subtypes of invasive ovarian cancer, and likely low-grade serous invasive ovarian cancer, melanoma and non-Hodgkin lymphoma in endometriosis; and (6) endometrial and ovarian cancer in idiopathic infertility. The present data endorse the principle that the occurrence of a disease (in our case infertility) is non-random in the population and suggest that different infertility etiologies are genetically and clinically linked with other diseases in single meta-diseases. This finding opens new insights for clinicians and reproductive biologists to treat infertility problems using a phenomic approach instead of considering infertility as an isolated and exclusive disease of the reproductive system/​hypothalamic-pituitary-gonadal axis. In agreement with a previous validation analysis of the utility of DiseaseConnect web server, the present study does not show an univocal correspondence between common gene expression and clinical comorbid relationship. Further work is needed to untangle the potential genetic, epigenetic and phenotypic relationships that may be present among different infertility etiologies, morbid conditions and physical/​cognitive traits.

“Educational Attainment-related Loci Identified by GWAS Are Associated With Select Personality Traits and Mathematics and Language Abilities”, Zhu et al 2015

2015-zhu.pdf: “Educational attainment-related loci identified by GWAS are associated with select personality traits and mathematics and language abilities”⁠, Bi Zhu, Chuansheng Chen, Robert K. Moyzis, Qi Dong, Chongde Lin (2015; ; backlinks):

  • We genotyped 3 SNPs previously found to be related with educational attainment [in Rietveld et al 2013].
  • We investigated behavioral correlates of these genotypes in a Han Chinese sample.
  • Educationally advantaged allele associated with less fear of negative evaluation.
  • Educationally advantaged allele associated with higher mathematical ability.
  • Educationally advantaged allele associated with higher language ability.

A recent genome-wide association study of educational attainment identified 3 statistically-significant single nucleotide polymorphisms (SNPs) (rs9320913, rs11584700, and rs4851266).

In this study, we expanded this previous work by investigating behavioral correlates of these SNPs in a Han Chinese sample (rs9320913 was not available in our data and was thus replaced by rs12202969, which is in high linkage disequilibrium [i.e., correlations of alleles] with the former, r2 = 0.96 in Han Chinese population based on the 1000 Genomes Project).

Association analysis for individual SNPs showed statistically-significant associations between rs4851266 and a measure of language ability (Chinese word recognition), and between rs12202969 and a personality trait (fear of negative evaluation) and a measure of mathematical ability (number paired-associates learning). A polygenic score based on these 3 SNPs was also statistically-significantly associated with the measures of mathematical and language abilities. Specifically, educationally advantaged alleles identified in the previous study were associated with less fear of negative evaluation and higher mathematical and language abilities in the current study.

This exploratory study provides evidence of psychological mechanisms for the association between genes and educational attainment.

[Keywords: educational attainment, gene, math, language, personality]

“Common Psychiatric Disorders Share the Same Genetic Origin: a Multivariate Sibling Study of the Swedish Population”, Pettersson et al 2015

2015-pettersson.pdf: “Common psychiatric disorders share the same genetic origin: a multivariate sibling study of the Swedish population”⁠, E Pettersson, H. Larsson, P. Lichtenstein (2015-01-01; ⁠, )

“Did Sexual Selection Shape Human Music? Testing Predictions from the Sexual Selection Hypothesis of Music Evolution Using a Large Genetically Informative Sample of over 10,000 Twins”, Mosing et al 2015

“Did sexual selection shape human music? Testing predictions from the sexual selection hypothesis of music evolution using a large genetically informative sample of over 10,000 twins”⁠, Miriam A. Mosing, Karin J. H. Verweij, Guy Madison, Nancy L. Pedersen, Brendan P. Zietsch, Fredrik Ullén et al (2015; ⁠, ; backlinks; similar):

Although music is an universal feature of human culture, little is known about its origins and functions. A prominent theory of music evolution is the sexual selection hypothesis, which proposes that music evolved as a signal of genetic quality to potential mates. The sexual selection hypothesis offers several empirically testable predictions. First, musically skilled and active individuals should have greater mating success than less-skilled individuals. Second, if musical ability functions as an indicator of genetic quality, it is expected to be associated with other traits putatively related to genetic quality. Third, associations as per the first and second predictions are expected to be at least partly due to overlapping genetic influences. We tested these predictions in a large genetically informative sample of 10,975 Swedish twin individuals aged between 27 and 54 years (M = 40.1, SD = 7.7), using musical aptitude and music achievement as measures of musical ability. To assess mating success we examined number of sex-partners, age of first intercourse, sociosexuality, and number of offspring. General intelligence, simple reaction time, and height were used to investigate relationships with traits putatively related to genetic quality. Twin modeling showed moderate genetic influences on musical aptitude for both sexes (heritability estimates were 38% for males and 51% for females). Music achievement was also moderately influenced by genetic influences in males (heritability = 57%), but the genetic influences were low and nonsignificant for females (heritability = 9%). Contrary to predictions, the majority of phenotypic associations between musical ability and music achievement with mating success were nonsignificant or statistically-significant in the other direction, with those with greater musical ability scoring lower on the measures of mating success. Genetic correlations between these measures were also nonsignificant. Most correlations of musical aptitude and music achievement with genetic quality measures were statistically-significant, including correlations with general intelligence, simple reaction time, and, in females, height (but only for aptitude). However, only the correlation between musical aptitude and general intelligence in men was statistically-significantly driven by overlapping genetic influences. Our findings provide little support for a role of sexual selection in the evolution of musical ability. Alternative explanations and limitations are discussed.

“Pleiotropy across Academic Subjects at the End of Compulsory Education”, Rimfeld et al 2015

“Pleiotropy across academic subjects at the end of compulsory education”⁠, Kaili Rimfeld, Yulia Kovas, Philip S. Dale, Robert Plomin (2015; ; similar):

Research has shown that genes play an important role in educational achievement. A key question is the extent to which the same genes affect different academic subjects before and after controlling for general intelligence.

The present study investigated genetic and environmental influences on, and links between, the various subjects of the age-16 UK-wide standardized GCSE (General Certificate of Secondary Education) examination results for 12,632 twins.

Using the twin method that compares identical and non-identical twins, we found that all GCSE subjects were substantially heritable, and that various academic subjects correlated substantially both phenotypically and genetically, even after controlling for intelligence. Further evidence for pleiotropy in academic achievement was found using a method [GCTA] based directly on DNA from unrelated individuals.

We conclude that performance differences for all subjects are highly heritable at the end of compulsory education and that many of the same genes affect different subjects independent of intelligence.

“Common Genetic Variants Influence Human Subcortical Brain Structures”, Hibar et al 2015

“Common genetic variants influence human subcortical brain structures”⁠, Derrek P. Hibar, Jason L. Stein, Miguel E. Renteria, Alejandro Arias-Vasquez, Sylvane Desrivières, Neda Jahanshad et al (2015; ; similar):

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease.

To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts.

We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; p = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport.

Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

“Physical Attractiveness As a Phenotypic Marker of Health: an Assessment Using a Nationally Representative Sample of American Adults”, Nedelec & Beaver 2014

2014-nedelec.pdf: “Physical attractiveness as a phenotypic marker of health: an assessment using a nationally representative sample of American adults”⁠, Joseph L. Nedelec, Kevin M. Beaver (2014-11-01; ; similar):

Evolutionary explanations regarding the differential preference for particular traits hold that preferences arose due to traits’ association with increased potential for reproductive fitness. Assessments of physical attractiveness have been shown to be related to perceived and measured levels of health, an important fitness-related trait.

Despite the robust association between physical attractiveness and health observed in the extant literature, a number of theoretical and methodological concerns remain. Specifically, the research in this area possesses a lack of specificity in terms of measures of health, a reliance on artificial social interactions in assessing physical attractiveness, and a relatively infrequent use of non-student samples and leaves unaddressed the confounding effects of raters of attractiveness.

Using these concerns as a springboard, the current study employed data from the National Longitudinal Study for Adolescent Health (n ≈ 15,000; aged 25 to 34 years) to assess the relationship between physical attractiveness and various specific and overall measures of health. Logistic and OLS regression models illustrated a robust association between physical attractiveness and various measures of health, controlling for a variety of confounding factors.

In sum, the more attractive a respondent was rated, the less likely he or she was to report being diagnosed with a wide range of chronic diseases and neuropsychological disorders. Importantly, this finding was observed for both sexes. These analyses provide further support for physical attractiveness as a phenotypic marker of health.

The findings are discussed in reference to evolutionary theory, and the limitations of the study and future research suggestions are also addressed.

“Genomic Architecture of Human Neuroanatomical Diversity”, Toro et al 2014

2014-toro.pdf: “Genomic architecture of human neuroanatomical diversity”⁠, R. Toro, J-B. Poline, G. Huguet, E. Loth, V. Frouin, T. Banaschewski, G. J. Barker, A. Bokde, C. Büchel et al (2014-09-16; similar):

Human brain anatomy is strikingly diverse and highly inheritable: genetic factors may explain up to 80% of its variability. Prior studies have tried to detect genetic variants with a large effect on neuroanatomical diversity, but those currently identified account for <5% of the variance.

Here, based on our analyses of neuroimaging and whole-genome genotyping data from 1765 subjects, we show that up to 54% of this heritability is captured by large numbers of single-nucleotide polymorphisms of small-effect spread throughout the genome, especially within genes and close regulatory regions. The genetic bases of neuroanatomical diversity appear to be relatively independent of those of body size (height), but shared with those of verbal intelligence scores.

The study of this genomic architecture should help us better understand brain evolution and disease.

“Practice Does Not Make Perfect: No Causal Effect of Music Practice on Music Ability”, Mosing et al 2014

2014-mosing.pdf: “Practice Does Not Make Perfect: No Causal Effect of Music Practice on Music Ability”⁠, Miriam A. Mosing, Guy Madison, Nancy L. Pedersen, Ralf Kuja-Halkola, Fredrik Ullén (2014-07-30; ⁠, ; backlinks; similar):

The relative importance of nature and nurture for various forms of expertise has been intensely debated. Music proficiency is viewed as a general model for expertise, and associations between deliberate practice and music proficiency have been interpreted as supporting the prevailing idea that long-term deliberate practice inevitably results in increased music ability.

Here, we examined the associations (rs = 0.18–0.36) between music practice and music ability (rhythm, melody, and pitch discrimination) in 10,500 Swedish twins. We found that music practice was substantially heritable (40%–70%). Associations between music practice and music ability were predominantly genetic, and, contrary to the causal hypothesis, nonshared environmental influences did not contribute. There was no difference in ability within monozygotic twin pairs differing in their amount of practice, so that when genetic predisposition was controlled for, more practice was no longer associated with better music skills.

These findings suggest that music practice may not causally influence music ability and that genetic variation among individuals affects both ability and inclination to practice.

[Keywords: training, expertise, music ability, practice, heritability, twin, causality]

“Does Population Density and Neighborhood Deprivation Predict Schizophrenia? A Nationwide Swedish Family-Based Study of 2.4 Million Individuals”, Sariaslan et al 2014b

2014-sariaslan-2.pdf: “Does Population Density and Neighborhood Deprivation Predict Schizophrenia? A Nationwide Swedish Family-Based Study of 2.4 Million Individuals”⁠, Amir Sariaslan, Henrik Larsson, Brian D’Onofrio, Niklas Långström, Seena Fazel, Paul Lichtenstein (2014-07-22; ⁠, ; backlinks; similar):

People living in densely populated and socially disorganized areas have higher rates of psychiatric morbidity, but the potential causal status of such factors is uncertain.

We used nationwide Swedish longitudinal registry data to identify all children born 1967–1989 (n = 2,361,585), including separate datasets for all cousins (n = 1,715,059) and siblings (n = 1,667,894). The nature of the associations between population density and neighborhood deprivation and individual risk for a schizophrenia diagnosis was investigated while adjusting for unobserved familial risk factors (through cousin and sibling comparisons) and then compared with similar associations for depression. We generated familial pedigree structures using the Multi-Generation Registry and identified study participants with schizophrenia and depression using the National Patient Registry. Fixed-effects logistic regression models were used to study within-family estimates.

Population density, measured as ln(population size/​km2), at age 15 predicted subsequent schizophrenia in the population (OR = 1.10; 95% CI: 1.09; 1.11). Unobserved familial risk factors shared by cousins within extended families attenuated the association (1.06; 1.03; 1.10), and the link disappeared entirely within nuclear families (1.02; 0.97; 1.08). Similar results were found for neighborhood deprivation as predictor and for depression as outcome. Sensitivity tests demonstrated that timing and accumulation effects of the exposures (mean scores across birth, ages 1–5, 6–10, and 11–15 years) did not alter the findings.

Excess risks of psychiatric morbidity, particularly schizophrenia, in densely populated and socioeconomically deprived Swedish neighborhoods appear, therefore, to result primarily from unobserved familial selection factors. Previous studies may have overemphasized the etiological importance of these environmental factors.

“Behavior Genetic Research Methods: Testing Quasi-Causal Hypotheses Using Multivariate Twin Data”, Turkheimer & Harden 2014

2014-turkheimer.pdf: “Behavior Genetic Research Methods: Testing Quasi-Causal Hypotheses Using Multivariate Twin Data”⁠, Eric Turkheimer, K. Paige Harden (2014-01-01; ; backlinks)

“The High Heritability of Educational Achievement Reflects Many Genetically Influenced Traits, Not Just Intelligence”, Krapohl et al 2014

“The high heritability of educational achievement reflects many genetically influenced traits, not just intelligence”⁠, Eva Krapohl, Kaili Rimfeld, Nicholas G. Shakeshaft, Maciej Trzaskowski, Andrew McMillan, Jean-Baptiste Pingault et al (2014; ⁠, ; backlinks; similar):

Because educational achievement at the end of compulsory schooling represents a major tipping point in life, understanding its causes and correlates is important for individual children, their families, and society.

Here we identify the general ingredients of educational achievement using a multivariate design that goes beyond intelligence to consider a wide range of predictors, such as self-efficacy, personality, and behavior problems, to assess their independent and joint contributions to educational achievement. We use a genetically sensitive design to address the question of why educational achievement is so highly heritable. We focus on the results of a United Kingdom-wide examination, the General Certificate of Secondary Education (GCSE), which is administered at the end of compulsory education at age 16. GCSE scores were obtained for 13,306 twins at age 16, whom we also assessed contemporaneously on 83 scales that were condensed to 9 broad psychological domains, including intelligence, self-efficacy, personality, well-being, and behavior problems.

The mean of GCSE core subjects (English, mathematics, science) is more heritable (62%) than the 9 predictor domains (35–58%). Each of the domains correlates statistically-significantly with GCSE results, and these correlations are largely mediated genetically. The main finding is that, although intelligence accounts for more of the heritability of GCSE than any other single domain, the other domains collectively account for about as much GCSE heritability as intelligence. Together with intelligence, these domains account for 75% of the heritability of GCSE.

We conclude that the high heritability of educational achievement reflects many genetically influenced traits, not just intelligence.

“Parenting As a Reaction Evoked by Children’s Genotype: A Meta-Analysis of Children-as-Twins Studies”, Avinun & Knafo 2013

2013-avinun.pdf: “Parenting as a Reaction Evoked by Children’s Genotype: A Meta-Analysis of Children-as-Twins Studies”⁠, Reut Avinun, Ariel Knafo (2013-08-12; similar):

Parenting has been extensively studied but mostly as a causal factor influencing child outcomes. The aim of the current article is to examine the child’s side of the relationship by meta-analyzing studies which used quantitative genetic methods that provide leverage in understanding causality.

A meta-analysis of 32 children-as-twins studies of parenting revealed a heritability estimate of 23%, thus indicating that genetically influenced behaviors of the child affect and shape parental behavior. The shared-environment and nonshared-environmental estimates, which amounted to 43% and 34%, respectively, indicate not only substantial consistency in parental behavior but also differential treatment within the family. Assessment method, age, and parenting dimension were found to be statistically-significant moderators of these influences.

Our findings stress the importance of accounting for genotype-environment correlations in child-development studies and call into question previous research that interpreted correlational results in unidirectional terms with parenting as the sole causal factor.

[Keywords: genotype-environment correlation, evocative, parenting, child influences, twin studies]

“High Loading of Polygenic Risk for ADHD in Children With Comorbid Aggression”, Hamshere et al 2013

2013-hamshere.pdf: “High Loading of Polygenic Risk for ADHD in Children With Comorbid Aggression”⁠, Marian L. Hamshere, Kate Langley, Joanna Martin, Sharifah Shameem Agha, Evangelia Stergiakouli, Richard J. L. Anney et al (2013-08-01; backlinks; similar):

Objective: Although attention deficit hyperactivity disorder (ADHD) is highly heritable, genome-wide association studies (GWAS) have not yet identified any common genetic variants that contribute to risk. There is evidence that aggression or conduct disorder in children with ADHD indexes higher genetic loading and clinical severity. The authors examine whether common genetic variants considered en masse as polygenic scores for ADHD are especially enriched in children with comorbid conduct disorder.

Method: Polygenic scores derived from an ADHD GWAS meta-analysis were calculated in an independent ADHD sample (452 case subjects, 5,081 comparison subjects). Multivariate logistic regression analyses were employed to compare polygenic scores in the ADHD and comparison groups and test for higher scores in ADHD case subjects with comorbid conduct disorder relative to comparison subjects and relative to those without comorbid conduct disorder. Association with symptom scores was tested using linear regression.

Results: Polygenic risk for ADHD, derived from the meta-analysis, was higher in the independent ADHD group than in the comparison group. Polygenic score was statistically-significantly higher in ADHD case subjects with conduct disorder relative to ADHD case subjects without conduct disorder. ADHD polygenic score showed statistically-significant association with comorbid conduct disorder symptoms. This relationship was explained by the aggression items.

Conclusions: Common genetic variation is relevant to ADHD, especially in individuals with comorbid aggression. The findings suggest that the previously published ADHD GWAS meta-analysis contains weak but true associations with common variants, support for which falls below genome-wide statistical-significance levels. The findings also highlight the fact that aggression in ADHD indexes genetic as well as clinical severity.

“Polygenic Risk for Schizophrenia Is Associated With Cognitive Change Between Childhood and Old Age”, McIntosh et al 2013

2013-mcintosh.pdf: “Polygenic Risk for Schizophrenia Is Associated with Cognitive Change Between Childhood and Old Age”⁠, Andrew M. McIntosh, Alan Gow, Michelle Luciano, Gail Davies, David C. Liewald, Sarah E. Harris, Janie Corley et al (2013-05-15; ⁠, ; backlinks; similar):

Background: Genome-wide association studies (GWAS) have shown a polygenic component to the risk of schizophrenia. The disorder is associated with impairments in general cognitive ability that also have a substantial genetic contribution. No study has determined whether cognitive impairments can be attributed to schizophrenia’s polygenic architecture using data from GWAS.

Methods: Members of the Lothian Birth Cohort 1936 (LBC1936, n = 937) were assessed using the Moray House Test at age 11 and with the Moray House Test and a further cognitive battery at age 70. To create polygenic risk scores for schizophrenia, we obtained data from the latest GWAS of the Psychiatric GWAS Consortium on Schizophrenia. Schizophrenia polygenic risk profile scores were calculated using information from the Psychiatric GWAS Consortium on Schizophrenia GWAS.

Results: In LBC1936, polygenic risk for schizophrenia was negatively associated with IQ at age 70 but not at age 11. Greater polygenic risk for schizophrenia was associated with more relative decline in IQ between these ages. These findings were maintained when the results of LBC1936 were combined with that of the independent Lothian Birth Cohort 1921 (n = 517) in a meta-analysis.

Conclusions: Increased polygenic risk of schizophrenia is associated with lower cognitive ability at age 70 and greater relative decline in general cognitive ability between the ages of 11 and 70. Common genetic variants may underlie both cognitive aging and risk of schizophrenia.

[Keywords: Aging, cognition, dementia, schizophrenia]

“Examining the Role of Passive Gene-environment Correlation in Childhood Depression Using a Novel Genetically Sensitive Design”, Rice et al 2013

2013-rice.pdf: “Examining the role of passive gene-environment correlation in childhood depression using a novel genetically sensitive design”⁠, Frances Rice, Gema Lewis, Gordon T. Harold, Anita Thapar (2013-02-11; similar):

Parental depression is associated with disruptions in the parent-child relationship, exposure to stressful family life events, and offspring depressive symptoms. Evidence suggests that intergenerational transmission of depression involves environmental and inherited contributions. We sought to evaluate the role of passive gene-environment correlation (rGE) in relation to depression, family life events that were due to parental behavior, and parental positivity in a sample where children varied in genetic relatedness to their rearing parents.

Our study included 865 families with children born through assisted conception (444 related to both parents, 210 related to the mother only, 175 related to the father only, and 36 related to neither parent). Consistent with previous studies, the intergenerational transmission of depressive symptoms was largely due to environmental factors, although parent and child gender influenced results. Maternal and paternal depressive symptoms were associated with reduced positivity and increased parentally imposed life events regardless of parent-child relatedness.

Results of path analysis were consistent with passive rGE for both maternal and paternal positivity in that positivity partially mediated the link between maternal/​paternal depression and child depression only in genetically related parent-child pairs. Results also suggested passive rGE involving parentally imposed life events for mothers and fathers although passive rGE effects were smaller than for positivity.

“Identification of Risk Loci With Shared Effects on Five Major Psychiatric Disorders: a Genome-wide Analysis”

“Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis”⁠, (2013; ; backlinks; similar):

Background: Findings from family and twin studies suggest that genetic contributions to psychiatric disorders do not in all cases map to present diagnostic categories. We aimed to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics Consortium: autism spectrum disorder, attention deficit-hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia.

Methods: We analysed genome-wide single-nucleotide polymorphism (SNP) data for the five disorders in 33,332 cases and 27,888 controls of European ancestry. To characterise allelic effects on each disorder, we applied a multinomial logistic regression procedure with model selection to identify the best-fitting model of relations between genotype and phenotype. We examined cross-disorder effects of genome-wide statistically-significant loci previously identified for bipolar disorder and schizophrenia, and used polygenic risk-score analysis to examine such effects from a broader set of common variants. We undertook pathway analyses to establish the biological associations underlying genetic overlap for the five disorders. We used enrichment analysis of expression quantitative trait loci (eQTL) data to assess whether SNPs with cross-disorder association were enriched for regulatory SNPs in post-mortem brain-tissue samples.

Findings: SNPs at four loci surpassed the cutoff for genome-wide statistical-significance (p < 5×10−8) in the primary analysis: regions on chromosomes 3p21 and 10q24, and SNPs within two L-type voltage-gated calcium channel subunits, CACNA1C and CACNB2. Model selection analysis supported effects of these loci for several disorders. Loci previously associated with bipolar disorder or schizophrenia had variable diagnostic specificity. Polygenic risk scores showed cross-disorder associations, notably between adult-onset disorders. Pathway analysis supported a role for calcium channel signalling genes for all five disorders. Finally, SNPs with evidence of cross-disorder association were enriched for brain eQTL markers.

Interpretation: Our findings show that specific SNPs are associated with a range of psychiatric disorders of childhood onset or adult onset. In particular, variation in calcium-channel activity genes seems to have pleiotropic effects on psychopathology. These results provide evidence relevant to the goal of moving beyond descriptive syndromes in psychiatry, and towards a nosology informed by disease cause.

Funding: National Institute of Mental Health.

“The Prediction of School Achievement from a Behavior Genetic Perspective: Results from the German Twin Study on Cognitive Ability, Self-Reported Motivation, and School Achievement (CoSMoS)”, Gottschling et al 2012

2012-gottschling.pdf: “The prediction of school achievement from a behavior genetic perspective: Results from the German twin study on Cognitive Ability, Self-Reported Motivation, and School Achievement (CoSMoS)”⁠, Juliana Gottschling, Marion Spengler, Birgit Spinath, Frank M. Spinath (2012-01-01)

“Genetic Contributions to Stability and Change in Intelligence from Childhood to Old Age”, Deary et al 2012

2012-deary.pdf: “Genetic contributions to stability and change in intelligence from childhood to old age”⁠, Ian J. Deary, Jian Yang, Gail Davies, Sarah E. Harris, Albert Tenesa, David Liewald, Michelle Luciano et al (2012; ):

Understanding the determinants of healthy mental ageing is a priority for society today. So far, we know that intelligence differences show high stability from childhood to old age and there are estimantes of the genetic contribution to intelligence at different ages. However, attempts to discover whether genetic causes contribute to differences in cognitive ageing have been relatively uninformative.

Here we provide an estimate of the genetic and environmental contributions to stability and change in intelligence across most of the human lifetime. We used genome-wide single-nucleotide polymorphism (SNP) data from 1,940 unrelated individuals whose intelligence was measured in childhood (age 11 years) and again in old age (age 65, 70 or 79 years). We use a statistical method that allows genetic (co)vvarianceto be estimated from SNP data on unrelated individuals.

We estimate that causal genetic variants in linkage disequilibrium with common SNPs account for 0.24 of the variation in cognitive ability change from childhood to old age. Using bivariate analysis, we estimate a genetic correlation between intelligence at age 11 years and in old age of 0.62.

These estimates, derived from rarely available data on lifetime cognitive measures, warrant the search for genetic causes of cognitive stability and change.

“Shared Genetic Factors in the Co-occurrence of Symptoms of Depression and Cardiovascular Risk Factors”, López-León et al 2010

2010-lopezleon.pdf: “Shared genetic factors in the co-occurrence of symptoms of depression and cardiovascular risk factors”⁠, Sandra López-León, Yurii S. Aulchenko, Henning Tiemeier, Ben A. Oostra, Cornelia M. van Duijn, A. Cecile J. W. Janssens et al (2010-01-01)

“Causal Inference and Observational Research: The Utility of Twins”, McGue et al 2010

“Causal Inference and Observational Research: The Utility of Twins”⁠, Matt McGue, Merete Osler, Kaare Christensen (2010; ; backlinks; similar):

Valid causal inference is central to progress in theoretical and applied psychology. Although the randomized experiment is widely considered the gold standard for determining whether a given exposure increases the likelihood of some specified outcome, experiments are not always feasible and in some cases can result in biased estimates of causal effects. Alternatively, standard observational approaches are limited by the possibility of confounding, reverse causation⁠, and the nonrandom distribution of exposure (ie. selection).

We describe the counterfactual model of causation and apply it to the challenges of causal inference in observational research, with a particular focus on aging. We argue that the study of twin pairs discordant on exposure, and in particular discordant monozygotic twins, provides an useful analog to the idealized counterfactual design.

A review of discordant-twin studies in aging reveals that they are consistent with, but do not unambiguously establish, a causal effect of lifestyle factors on important late-life outcomes. Nonetheless, the existing studies are few in number and have clear limitations that have not always been considered in interpreting their results.

It is concluded that twin researchers could make greater use of the discordant-twin design as one approach to strengthen causal inferences in observational research.

“Stability, Change, and Heritability of Borderline Personality Disorder Traits from Adolescence to Adulthood: a Longitudinal Twin Study”, Bornovalova et al 2009

“Stability, change, and heritability of borderline personality disorder traits from adolescence to adulthood: a longitudinal twin study”⁠, Marina A. Bornovalova, Brian M. Hicks, William G. Iacono, Matt McGue (2009; ⁠, ; similar):

Although personality disorders are best understood in the context of lifetime development, there is a paucity of work examining their longitudinal trajectory. An understanding of the expected course and the genetic and environmental contributions to these disorders is necessary for a detailed understanding of risk processes that lead to their manifestation. The current study examined the longitudinal course and heritability of borderline personality disorder (BPD) over a period of 10 years starting in adolescence (age 14) and ending in adulthood (age 24). In doing so, we built on existing research by using a large community sample of adolescent female twins, a sensitive dimensional measure of BPD traits, an extended follow-up period, and a longitudinal twin design that allowed us to investigate the heritability of BPD traits at four discrete ages spanning mid-adolescence to early adulthood. Results indicated that mean-level BPD traits significantly decline from adolescence to adulthood, but rank order stability remained high. BPD traits were moderately heritable at all ages, with a slight trend for increased heritability from age 14 to age 24. A genetically informed latent growth curve model indicated that both the stability and change of BPD traits are highly influenced by genetic factors and modestly by nonshared environmental factors. Our results indicate that as is the case for other personality dimensions, trait BPD declines as individuals mature from adolescence to adulthood, and that this process is influenced in part by the same genetic factors that influence BPD trait stability.

“Individual Differences in Executive Functions Are Almost Entirely Genetic in Origin”, Friedman et al 2008

“Individual differences in executive functions are almost entirely genetic in origin”⁠, Naomi P. Friedman, Akira Miyake, Susan E. Young, John C. DeFries, Robin P. Corley, John K. Hewitt (2008; ; similar):

Recent psychological and neuropsychological research suggests that executive functions—the cognitive control processes that regulate thought and action—are multifaceted and that different types of executive functions are correlated but separable. The present multivariate twin study of 3 executive functions (inhibiting dominant responses, updating working memory representations, and shifting between task sets), measured as latent variables, examined why people vary in these executive control abilities and why these abilities are correlated but separable from a behavioral genetic perspective.

Results indicated that executive functions are correlated because they are influenced by a highly heritable (99%) common factor that goes beyond general intelligence or perceptual speed, and they are separable because of additional genetic influences unique to particular executive functions. This combination of general and specific genetic influences places executive functions among the most heritable psychological traits. These results highlight the potential of genetic approaches for uncovering the biological underpinnings of executive functions and suggest a need for examining multiple types of executive functions to distinguish different levels of genetic influences.

“Proceeding From Observed Correlation to Causal Inference: The Use of Natural Experiments”, Rutter 2007

“Proceeding From Observed Correlation to Causal Inference: The Use of Natural Experiments”⁠, Michael Rutter (2007; ⁠, ⁠, ⁠, ; backlinks; similar):

This article notes 5 reasons why a correlation between a risk (or protective) factor and some specified outcome might not reflect environmental causation. In keeping with numerous other writers, it is noted that a causal effect is usually composed of a constellation of components acting in concert. The study of causation, therefore, will necessarily be informative on only one or more subsets of such components. There is no such thing as a single basic necessary and sufficient cause. Attention is drawn to the need (albeit unobservable) to consider the counterfactual (ie. what would have happened if the individual had not had the supposed risk experience). 15 possible types of natural experiments that may be used to test causal inferences with respect to naturally occurring prior causes (rather than planned interventions) are described. These comprise 5 types of genetically sensitive designs intended to control for possible genetic mediation (as well as dealing with other issues), 6 uses of twin or adoptee strategies to deal with other issues such as selection bias or the contrasts between different environmental risks, 2 designs to deal with selection bias, regression discontinuity designs to take into account unmeasured confounders, and the study of contextual effects. It is concluded that, taken in conjunction, natural experiments can be very helpful in both strengthening and weakening causal inferences.

“Testing Hypotheses about the Relationship between Cannabis Use and Psychosis”, Degenhardt et al 2003

2002-degenhardt.pdf: “Testing hypotheses about the relationship between cannabis use and psychosis”⁠, Louisa Degenhardt, Wayne Hall, Michael Lynskey (2003-01-01; ⁠, ; backlinks)

“Chapter 21: Correlations Between Characters”, Lynch & Walsh 1998

1998-lynchwalsh-geneticsquantitativetraits-ch21-geneticcorrelations.pdf: “Chapter 21: Correlations Between Characters”⁠, Michael Lynch, Bruce Walsh (1998-01-01; backlinks)

“Heavy Consumption of Cigarettes, Alcohol and Coffee in Male Twins”, Swan et al 1997

1997-swan.pdf: “Heavy Consumption of Cigarettes, Alcohol and Coffee in Male Twins”⁠, Gary E. Swan, Dorit Carmelli, Lon R. Cardon (1997-01-01)

“Does Genetic Variance for Cognitive Abilities Account for Genetic Variance in Educational Achievement and Occupational Status? A Study of Twins Reared Apart and Twins Reared Together”, Lichtenstein & Pedersen 1997

1997-lichtenstein.pdf: “Does genetic variance for cognitive abilities account for genetic variance in educational achievement and occupational status? A study of twins reared apart and twins reared together”⁠, Paul Lichtenstein, Nancy L. Pedersen (1997; ⁠, ; similar):

Studies of brothers and twins have shown that about 50% of the variance in educational achievement and 40% of the variance in occupational status reflects between-family variance. About half of the between-family variance for educational achievement and even more for occupational status is due to genetic effects and the remainder is due to sharing the same environment.

With data on 35 pairs of male twins reared apart and 56 pairs reared together we investigated the extent to which genetic variance in SES can be attributed to genetic variance for cognitive abilities. For both educational achievement and occupational status there was statistically-significant genetic variance both in common with and independent of genetic variance for cognitive abilities.

Thus, there are genetic effects contributing to familial similarity for SES that are not the same as those of importance for cognitive abilities. Candidate traits that may account for this remaining genetic variance in SES are personality, interests, or talents not represented in standard cognitive tests.

“Genetic and Environmental Influences on the Covariation Between Hyperactivity and Conduct Disturbance in Juvenile Twins”

1996-silberg.pdf: “Genetic and Environmental Influences on the Covariation Between Hyperactivity and Conduct Disturbance in Juvenile Twins” (1996-01-01)

“Environmental Effects and Genetic Parameters for Measurements of Hunting Performance in the Finnish Spitz”, Karjalainen et al 1996

1996-karjalainen.pdf: “Environmental effects and genetic parameters for measurements of hunting performance in the Finnish Spitz”⁠, L. Karjalainen, M. Ojala, V. Vilva (1996-01-01; ; backlinks)

“A Twin Study of the Association of Post-traumatic Stress Disorder and Combat Exposure With Long-term Socioeconomic Status in Vietnam Veterans”, McCarren et al 1995

1995-mccarren.pdf: “A twin study of the association of post-traumatic stress disorder and combat exposure with long-term socioeconomic status in Vietnam veterans”⁠, Madeline McCarren, Gail R. Janes, Jack Goldberg, Seth A. Eisen, William R. True, William G. Henderson et al (1995; similar):

This study examines the association between post-traumatic stress disorder (PTSD) and combat exposure with the socioeconomic status of 2210 male monozygotic veteran twin pairs in 1987. In the unadjusted analysis on individuals, modest correlations indicated that those with PTSD were more likely to have been divorced, and less likely to be currently employed or to achieve high status in income, education or occupation. In the crude analysis of veterans not suffering from PTSD, there were small positive correlations between combat level experienced and the likelihood of ever being married, ever being divorced, and the number of years employed at the current job. However, when we examined identical twins discordant for PTSD, and adjusted for pre-military and military service factors, only unemployment remained statistically-significant. Likewise, in combat-discordant twins, no statistically-significant effects on the socioeconomic indicators were seen. We conclude that PTSD and combat experience in Southeast Asia have not had a major impact on the socioeconomic status of veterans.

“Chapter 3: Colorado Reading Project: An Update”, DeFries et al 1991

1991-defries.pdf: “Chapter 3: Colorado Reading Project: An Update”⁠, J. C. DeFries, R. K. Olson, B. F. Pennington, S. D. Smith (1991-01-01; backlinks)

“Relationship Between Blood Uric Acid Level and Personality Traits”, Ooki et al 1990

1990-ooki.pdf: “Relationship Between Blood Uric Acid Level and Personality Traits”⁠, S. Ooki, K. Yamada, A. Asaka (1990; ; similar):

The present study deals with the relationship between blood uric acid level and human behavior. Subjects were 37 MZ and 7 DZ twins aged from 18 to 45 years. In males, blood uric acid level increased with age, while it decreased with age in females. Blood uric acid level was corrected and standardized using regression lines separately for males and females. The distribution of standardized uric acid level corresponded well with the theoretical curve of normal distribution. The intraclass correlation coefficient for standardized uric acid level was r = 0.370 (p < 0.05) for the 37 MZ twins, but not statistically-significant for the 7 DZ twins. These findings suggest that blood uric acid level is genetically controlled. By the analysis of 12 personality traits in YG (Yatabe-Guilford) character test, it was revealed that “General activity” was more controlled by genetically than environmentally. In the evaluation of the correlation between standardized uric acid level and the YG 12 personality traits, statistically-significant correlation was observed in “Lack of agreeableness” and “Rhathymia”. Since these two personality traits include the factor of “activity”, it is concluded that the plasma uric acid level and activity in a broader sense are under genetic control. This conclusion is consistent with the generally accepted view that persons with high uric acid level are more active and energetic than those with low level.

“Genetic and Environmental Contributions to the Covariance between Occupational Status, Educational Attainment, and IQ: A Study of Twins”, Tambs et al 1989

1989-tambs.pdf: “Genetic and environmental contributions to the covariance between occupational status, educational attainment, and IQ: A study of twins”⁠, Kristian Tambs, Jon Martin Sundet, Per Magnus, Kåre Berg (1989-03; ; similar):

Scores of occupational status, educational attainment, and IQ were obtained for 507 monozygotic and 575 dizygotic male twin pairs born 1931–1935 and 1944–1960.

A multivariate genetic analysis with statistics from different cohorts showed heterogeneity between cohorts, and analyses were performed in 4 separate cohorts.

The only set of results which departed clearly from the rest was found for the group born 1931–1935, where the ratio of environmental to genetic effects exceeded those of the other groups. Typical heritability values in the 3 youngest groups (weighted means) were 0.43, 0.51, and 0.66 for occupation, education, and IQ, respectively. The values in the oldest group were 0.16, 0.10, and 0.37, but this sample is small and the estimates are unstable. Genetic variance influencing educational attainment also contributed ~1⁄4th of the genetic variance for occupational status and nearly half the genetic variance for IQ. The values for the between-families variances (reflecting family environment and assortative mating) varied from 2% to 35% in the 3 youngest groups but were higher for education (62%) and IQ (45%) in the oldest groups. All the between-families variance was common to all 3 variables. For educational attainment and IQ, the bulk of this between-families variance is probably genetic variance due to assortative mating. The common-factor environmental within-family variances were generally small, and the specific estimates seemed to contain mainly measurement error.

“Heritability Estimate for Temperament Scores in German Shepherd Dogs and Its Genetic Correlation With Hip Dysplasia”, Mackenzie et al 1985

1985-mackenzie.pdf: “Heritability estimate for temperament scores in German shepherd dogs and its genetic correlation with hip dysplasia”⁠, Stephen A. Mackenzie, Elizabeth A. B. Oltenacu, Eldin Leighton (1985-01-01; ⁠, ; backlinks)

“Genetics of Traits Which Determine the Suitability of Dogs As Guide-dogs for the Blind”, Goddard & Beilharz 1983

1983-goddard.pdf: “Genetics of traits which determine the suitability of dogs as guide-dogs for the blind”⁠, M. E. Goddard, R. G. Beilharz (1983-01-01; )

“Quantitative Genetics of Anthropometric Variation in the Solomon Islands”, Black 1982

1982-black.pdf: “Quantitative Genetics of Anthropometric Variation in the Solomon Islands”⁠, Stephen James Black (1982-10-21)

“Twin Research, Part A: Psychology and Methodology”, Nance et al 1978

1978-nance-twinresearchparta-psychologymethodology.pdf: “Twin Research, Part A: Psychology and Methodology”⁠, Walter E. Nance, Gordon Allen, Paolo Parisi (1978-01-01)

“Hereditary and Environmental Sources of Trait Variation and Covariation”, Breland 1972

1972-breland.pdf: “Hereditary and Environmental Sources of Trait Variation and Covariation”⁠, Nancy Schacht Breland (1972; ; similar):

The twin design for estimating proportions of hereditary and environmental sources of trait variation was presented and applied to a national sample of 806 twin sets who took the National Merit Scholarship Test in 1962. Parental report of differential treatment of their twins was used to test the assumption of equivalent within-family environments by zygosity.

A comparison of the sum of items reflecting differential treatment reported by the parents showed that identical twins are reported to be treated more alike than fraternal twins. Correlations of the treatment difference score with twin differences on the NMSQT and CPI scores showed a small but positive relationship between differential treatment and differences in measured achievement and personality. Within each actual zygosity group, the treatment difference scores of twins whose parents were correct about the zygosity diagnosis were compared to the scores of twins whose parents misdiagnosed them. These results indicated that parental behavior towards their twins is determined largely by the degree of genetic relatedness of their twins. However, the ordering of the treatment difference score means indicated that parental belief about zygosity also determined to some small degree their treatment of their twins. Within each zygosity group, the score differences on the NMSQT and CPI scales of twins correctly and incorrectly diagnosed by their parents were also compared, and the results showed that parental belief about zygosity has a small but consistent relationship to twin differences on measured achievement and personality.

This series of analyses indicated that the assumption of equal between-family environments by zygosity cannot be made, and that the environmental bias is greater for personality measures than for achievement measures. The assumption of equivalent between-family environments by zygosity was also tested, and it was concluded that this assumption does not introduce a serious bias in this sample.

Probable ranges of proportions of trait variance due to heredity, between-family and within-family environment were computed for each measure. Hereditary variation generally accounted for the majority of the variation in the NMSQT scales, and the between-family environmental component was generally larger that the within-family component. The heritability estimates of the CPI scales were quite varied, but in general the within-family environmental component was larger than the between-family component.

A multivariate method by which trait covariation can be partitioned into hereditary and environmental sources was presented and applied to the NMSQT scales. Matrices of cross twin correlations and correlations among twin differences were manipulated to produce hereditary and within and between-family environmental matrices.

The factor structures of these 3 component matrices were compared to the factor structure of the NMSQT. The verbal and math-science factor in the NMSQT were found in the hereditary and the within-family environmental matrices. Only a general factor was apparent in the between-family environmental matrix. This indicated that the 2 factors in the NMSQT are controlled by somewhat different hereditary mechanisms as well as different within-family environmental influences.

[Keywords: genetic correlation, environmental correlation, behavioral genetics, twin study, 1962 National Merit Scholarship sample, NMSQT, CPI, equal environment assumption, mistaken zygosity, personality, academic achievement, factor analysis⁠, thesis]

“1951 Rae: The Importance of Genetic Correlations in Selection”, RAE 1951

1951-rae.pdf: “1951 Rae: The Importance of Genetic Correlations in Selection”⁠, A. L. RAE (1951-01-01)

Miscellaneous