2021-edwards.pdf: “On the Genetic and Environmental Relationship Between Suicide Attempt and Death by Suicide”, (2021-07-14):
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.
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 ( ) 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 (OR = 1.18, 95% CI: 1.1–1.27). However, this association for ASD (OR = 1.04, 95% CI: 0.97–1.11) or (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 in later life can be partially explained by unmeasured genetic and familial confounding factors.
2021-daghlas.pdf: “Genetically Proxied Diurnal Preference, Sleep Timing, and Risk of Major Depressive Disorder”, (2021-05-26; ):
- 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 .
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)]
2021-johnson.pdf: “The relationship between cannabis and schizophrenia: a genetically informed perspective”, (2021-05-05):
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 ( ) and tested whether liability for CUD is causally associated with increased liability to while adjusting for tobacco smoking.
Design: This study used summary statistics from published genome-wide association studies (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 , and to test for a causal relationship between liability to CUD and liability to .). We used
Setting:were published previously as part of international consortia.
Participants: Sample sizes of thesummary 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 [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 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 (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 dependence).
Conclusions: Genetic liability for cannabis use disorder appears to be robustly associated with, 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,, genomic structural equation modeling, causal variable model, multivariable Mendelian randomization, , tobacco]
2021-krizan.pdf: “Why is personality tied to sleep quality? A biometric analysis of twins”, (2021-02-01):
- 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.
2021-stein.pdf: “Genome–wide association analyses of post–traumatic stress disorder and its symptom subdomains in the Million Veteran Program”, (2021-01-28):
We conducted EUR) and African (AFR) ancestry from the Million Veteran Program using electronic health record-validated post-traumatic stress disorder (PTSD) diagnosis and quantitative symptom phenotypes.of over 250,000 participants of European (
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 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.
2021-oreilly.pdf: “A Co-Twin Control Study of the Association Between Bullying Victimization and Self-Harm and Suicide Attempt in Adolescence”, (2021-01-18):
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 measuredfactors.
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, a 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 thebecause 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]
2020-schnurr.pdf: “Evidence for shared genetics between physical activity, sedentary behaviour and adiposity-related traits”, (2020-12-22; ):
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 , 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]
2020-perlstein.pdf: “Integrating the study of personality and psychopathology in the context of gene-environment correlations across development”, (2020-11-29):
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.
2020-aroe.pdf: “Genetic predictors of educational attainment and intelligence test performance predict voter turnout”, (2020-11-09; ):
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.
2020-gillespie.pdf: “Use of Genetically Informed Methods to Clarify the Nature of the Association Between Cannabis Use and Risk for Schizophrenia”, (2020-11-04):
When evaluating efforts to reduce cannabis use as a means of preventing, 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- association. We evaluated 3 hypotheses: (1) it is entirely causal, (2) it is partly causal and partly confounded by genetic/
familial effects and/ or, 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 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., thereby explaining at least part of the association. In this example, reverse causality refers to a theoretical underlying mechanism in which 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 (
…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-association stems partly from shared familial/
genetic risk factors and/ or. 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 LDSR and PRS methods suggest more modest degrees of while raising the possibility of . A prudent conclusion is that the observed cannabis- 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 stemming from changing levels of cannabis use are very likely to be exaggerated and potentially substantially so.4 suggests that it is substantial and accounts for more than half of the observed association. Results from
2020-nedelec.pdf: “The intersection of individual differences, personality variation, & military service: A twin comparison design”, (2020-09-22):
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. To assess the extent to which genetic 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 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 . Nonetheless, the overall results suggest that familial 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, twin comparison, Add Health]
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 between a Common EF 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,, behavior genetics, twins]
2020-choi.pdf: “An Exposure-Wide and Mendelian Randomization Approach to Identifying Modifiable Factors for the Prevention of Depression”, (2020-08-14):
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.
2020-ning.pdf: “High-definition likelihood inference of genetic correlations across human complex traits”, (2020-06-29):
Genetic correlation is a central parameter for understanding shared genetic architecture between complex traits. By using summary statistics from LDSC) was developed for unbiased estimation of . 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 , HDL reduces the variance of genetic correlation estimates by about 60%, equivalent to a 2.5-fold increase in sample size. We apply HDL and to estimate 435 genetic correlations among 30 behavioral and disease-related phenotypes measured in the UK Biobank (UKBB). In addition to 154 statistically-significant observed for both methods, HDL identified another 57 statistically-significant genetic correlations, compared to only another 2 statistically-significant identified by . HDL brings more power to genomic analyses and better reveals the underlying connections across human complex traits.( ), linkage disequilibrium score regression (
2020-rosenstrom.pdf: “Specific Antisocial and Borderline Personality Disorder Criteria and General Substance Use: A Twin Study”, (2020-06-25):
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 , 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 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.
2019-harden.pdf: “Genetic Associations Between Executive Functions and a General Factor of Psychopathology”, (2020-06-01):
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: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]
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 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.
2020-takahashi.pdf: “Genetic and environmental influences on the developmental trajectory of callous-unemotional traits from childhood to adolescence”, (2020-05-17):
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 biometricgrowth 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.
2020-bryne.pdf: “Conditional GWAS analysis to identify disorder-specific SNPs for psychiatric disorders”, (2020-05-12):
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 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 ( ), bipolar disorder (BIP), major depression (MD), attention-deficit hyperactivity disorder ( ) 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 , 5 of 40 for major depression, 3 of 11 for and 1 of 2 for autism. We show that decreased expression of VPS29 in the brain may increase risk to only and increased expression of CSE1L is associated with 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 and BIP.
2020-skov.pdf: “Co-aggregation and heritability of organ-specific autoimmunity: a population-based twin study”, (2020-05-01):
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.
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 andby Hunter and colleagues. Although the meta-analysis found that “exposure to prenatal smoke increased the risk of by 29%” (p. 3), the authors noted that “familial 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, 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 . 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.
2020-sakaue.pdf: “Trans-biobank analysis with 676,000 individuals elucidates the association of polygenic risk scores of complex traits with human lifespan”, Saori Sakaue, Masahiro Kanai, Juha Karjalainen, Masato Akiyama, Mitja Kurki, Nana Matoba, Atsushi Takahashi, Makoto Hirata, Michiaki Kubo, Koichi Matsuda, Yoshinori Murakami, Mark J. Daly, Yoichiro Kamatani, Yukinori Okada
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 () followed by polygenic risk score ( ) 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 . We conducted 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. analyses demonstrated statistically-significantly positive genetic overlap, respectively, between creativity with schizophrenia ((P+T) method: R2(max) ~ .196%, p = 0.00245; LDpred method: R2(max) ~ .226%, p = 0.00114), depression ((P+T) method: R2(max) ~ .178%, p = 0.00389; LDpred method: R2(max) ~ .093%, p = 0.03675), general risk tolerance ((P+T) method: R2(max) ~ .177%, p = 0.00399; LDpred method: R2(max) ~ .305%, p = 0.00016), and risky behaviors ((P+T) method: R2(max) ~ .187%, p = 0.00307; LDpred method: R2(max) ~ .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.
2020-gulsuner.pdf: “Genetics of schizophrenia in the South African Xhosa”, (2020-01-31):
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, 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. 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.
2019-pgc.pdf: “Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders”, (2019-12-12; ):
- 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,, 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.
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, Naomi P. Friedman
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
2019-kim.pdf: “The genetics of human fertility”, (2019-06-01):
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.
2019-wojcik.pdf: “Genetic analyses of diverse populations improves discovery for complex traits”, Genevieve L. Wojcik, Mariaelisa Graff, Katherine K. Nishimura, Ran Tao, Jeffrey Haessler, Christopher R. Gignoux, Heather M. Highland, Yesha M. Patel, Elena P. Sorokin, Christy L. Avery, Gillian M. Belbin, Stephanie A. Bien, Iona Cheng, Sinead Cullina, Chani J. Hodonsky, Yao Hu, Laura M. Huckins, Janina Jeff, Anne E. Justice, Jonathan M. Kocarnik, Unhee Lim, Bridget M. Lin, Yingchang Lu, Sarah C. Nelson, Sung-Shim L. Park, Hannah Poisner, Michael H. Preuss, Melissa A. Richard, Claudia Schurmann, Veronica W. Setiawan, Alexandra Sockell, Karan Vahi, Marie Verbanck, Abhishek Vishnu, Ryan W. Walker, Kristin L. Young, Niha Zubair, Victor Acuamp#x000F1;a-Alonso, Jose Luis Ambite, Kathleen C. Barnes, Eric Boerwinkle, Erwin P. Bottinger, Carlos D. Bustamante, Christian Caberto, Samuel Canizales-Quinteros, Matthew P. Conomos, Ewa Deelman, Ron Do, Kimberly Doheny, Lindsay Fernamp#x000E1;ndez-Rhodes, Myriam Fornage, Benyam Hailu, Gerardo Heiss, Brenna M. Henn, Lucia A. Hindorff, Rebecca D. Jackson, Cecelia A. Laurie, Cathy C. Laurie, Yuqing Li, Dan-Yu Lin, Andres Moreno-Estrada, Girish Nadkarni, Paul J. Norman, Loreall C. Pooler, Alexander P. Reiner, Jane Romm, Chiara Sabatti, Karla Sandoval, Xin Sheng, Eli A. Stahl, Daniel O. Stram, Timothy A. Thornton, Christina L. Wassel, Lynne R. Wilkens, Cheryl A. Winkler, Sachi Yoneyama, Steven Buyske, Christopher A. Haiman, Charles Kooperberg, Loic Marchand, Ruth J. F. Loos, Tara C. Matise, Kari E. North, Ulrike Peters, Eimear E. Kenny, Christopher S. Carlson ( )
2019-weinschenk.pdf: “New evidence on the link between genes, psychological traits, and political engagement”, (2019-01-01):
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.
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, Hamp#x000E9;lamp#x000E9;na A. Gaspar, Julien Bryois, Anke Hinney, Virpi M. Leppamp#x000E4;, Manuel Mattheisen, Sarah E. Medland, Stephan Ripke, Shuyang Yao, Paola Giusti-Rodramp#x000ED;guez, Ken B. Hanscombe, Kirstin L. Purves, Roger A. H. Adan, Lars Alfredsson, Tetsuya Ando, Ole A. Andreassen, Jessica H. Baker, Wade H. Berrettini, Ilka Boehm, Claudette Boni, Vesna Boraska Perica, Katharina Buehren, Rol, Burghardt, Matteo Cassina, Sven Cichon, Maurizio Clementi, Roger D. Cone, Philippe Courtet, Scott Crow, James J. Crowley, Unna N. Danner, Oliver S. P. Davis, Martina Zwaan, George Dedoussis, Daniela Degortes, Janiece E. DeSocio, Danielle M. Dick, Dimitris Dikeos, Christian Dina, Monika Dmitrzak-Weglarz, Elisa Docampo, Laramie E. Duncan, Karin Egberts, Stefan Ehrlich, Geamp#x000F2;rgia Escaramamp#x000ED;s, Tamp#x000F5;nu Esko, Xavier Estivill, Anne Farmer, Angela Favaro, Fernando Fernamp#x000E1;ndez-Aranda, Manfred M. Fichter, Krista Fischer, Manuel Famp#x000F6;cker, Lenka Foretova, Andreas J. Forstner, Monica Forzan, Christopher S. Franklin, Steven Gallinger, Ina Giegling, Johanna Giuranna, Fragiskos Gonidakis, Philip Gorwood, Monica Gratacos Mayora, Samp#x000E9;bastien Guillaume, Yiran Guo, Hakon Hakonarson, Konstantinos Hatzikotoulas, Joanna Hauser, Johannes Hebebrand, Sietske G. Helder, Stefan Herms, Beate Herpertz-Dahlmann, Wolfgang Herzog, Laura M. Huckins, James I. Hudson, Hartmut Imgart, Hidetoshi Inoko, Vladimir Janout, Susana Jimamp#x000E9;nez-Murcia, Antonio Juliamp#x000E0;, Gursharan Kalsi, Deborah Kaminskamp#x000E1;, Jaakko Kaprio, Leila Karhunen, Andreas Karwautz, Martien J. H. Kas, James L. Kennedy, Anna Keski-Rahkonen, Kirsty Kiezebrink, Youl-Ri Kim, Lars Klareskog, Kelly L. Klump, Gun Peggy S. Knudsen, Maria C. Via, Stephanie Hellard, Robert D. Levitan, Dong Li, Lisa Lilenfeld, Bochao Danae Lin, Jolanta Lissowska, Jurjen Luykx, Pierre J. Magistretti, Mario Maj, Katrin Mannik, Sara Marsal, Christian R. Marshall, Morten Mattingsdal, Sara McDevitt, Peter McGuffin, Andres Metspalu, Ingrid Meulenbelt, Nadia Micali, Karen Mitchell, Alessio Maria Monteleone, Palmiero Monteleone, Melissa A. Munn-Chernoff, Benedetta Nacmias, Marie Navratilova, Ioanna Ntalla, Julie K. Oamp#x02019;Toole, Roel A. Ophoff, Leonid Padyukov, Aarno Palotie, Jacques Pantel, Hana Papezova, Dalila Pinto, Raquel Rabionet, Anu Raevuori, Nicolas Ramoz, Ted Reichborn-Kjennerud, Valdo Ricca, Samuli Ripatti, Franziska Ritschel, Marion Roberts, Alessandro Rotondo, Dan Rujescu, Filip Rybakowski, Paolo Santonastaso, Andramp#x000E9, Scherag, Stephen W. Scherer, Ulrike Schmidt, Nicholas J. Schork, Alexandra Schosser, Jochen Seitz, Lenka Slachtova, P. Eline Slagboom, Margarita C. T. Slof-Op amp#x02018;t Landt, Agnieszka Slopien, Sandro Sorbi, Beata amp#x0015A;wiamp#x00105;tkowska, Jin P. Szatkiewicz, Ioanna Tachmazidou, Elena Tenconi, Alfonso Tortorella, Federica Tozzi, Janet Treasure, Artemis Tsitsika, Marta Tyszkiewicz-Nwafor, Konstantinos Tziouvas, Annemarie A. Elburg, Eric F. Furth, Gudrun Wagner, Esther Walton, Elisabeth Widen, Eleftheria Zeggini, Stephanie Zerwas, Stephan Zipfel, Andrew W. Bergen, Joseph M. Boden, Harry Brandt, Steven Crawford, Katherine A. Halmi, L. John Horwood, Craig Johnson, Allan S. Kaplan, Walter H. Kaye, James E. Mitchell, Catherine M. Olsen, John F. Pearson, Nancy L. Pedersen, Michael Strober, Thomas Werge, David C. Whiteman, D. Blake Woodside, Garret D. Stuber, Scott Gordon, Jakob Grove, Anjali K. Henders, Anders Juramp#x000E9;us, Katherine M. Kirk, Janne T. Larsen, Richard Parker, Liselotte Petersen, Jennifer Jordan, Martin Kennedy, Grant W. Montgomery, Tracey D. Wade, Andreas Birgegamp#x000E5;rd, Paul Lichtenstein, Claes Norring, Mikael Landamp#x000E9;n, Nicholas G. Martin, Preben Bo Mortensen, Patrick F. Sullivan, Gerome Breen, Cynthia M. Bulik
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-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, Julia Sidorenko, Robert Maier, Stephan Ripke, Manuel Mattheisen, Bernhard T. Baune, Hans J. Grabe, Andrew C. Heath, Lisa Jones, Ian Jones, Pamela A. F. Madden, Andrew M. McIntosh, Gerome Breen, Cathryn M. Lewis, Anders D. Børglum, Patrick F. Sullivan, Nicholas G. Martin, Kenneth S. Kendler, Douglas F. Levinson, Naomi R. Wray, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium
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, Aya Kadota, Kiyonori Kuriki, Mariko Naito, Kozo Tanno, Yasushi Ishigaki, Makoto Hirata, Koichi Matsuda, Nakao Iwata, Masashi Ikeda, Norie Sawada, Taiki Yamaji, Motoki Iwasaki, Shiro Ikegawa, Shiro Maeda, Yoshinori Murakami, Kenji Wakai, Shoichiro Tsugane, Makoto Sasaki, Masayuki Yamamoto, Yukinori Okada, Michiaki Kubo, Yoichiro Kamatani, Momoko Horikoshi, Toshimasa Yamauchi, Takashi Kadowaki ( )
2019-smeland.pdf: “Genome-wide analysis reveals extensive genetic overlap between , Olav B. Smeland, Shahram Bahrami, Oleksandr Frei, Alexey Shadrin, Kevin O’Connell, Jeanne Savage, Kyoko Watanabe, Florian Krull, Francesco Bettella, Nils Eiel Steen, Torill Ueland, Danielle Posthuma, Srdjan Djurovic, Anders M. Dale, Ole A. Andreassen ( , bipolar disorder, and intelligence” )
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, Essi Viding, Eamon McCrory, Jean-Baptiste Pingault
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, Daniel McGuire, Chao Tian, Xiaowei Zhan, Michelle Agee, Babak Alipanahi, Adam Auton, Robert K. Bell, Katarzyna Bryc, Sarah L. Elson, Pierre Fontanillas, Nicholas A. Furlotte, David A. Hinds, Bethann S. Hromatka, Karen E. Huber, Aaron Kleinman, Nadia K. Litterman, Matthew H. McIntyre, Joanna L. Mountain, Carrie A. M. Northover, J. Fah Sathirapongsasuti, Olga V. Sazonova, Janie F. Shelton, Suyash Shringarpure, Chao Tian, Joyce Y. Tung, Vladimir Vacic, Catherine H. Wilson, Steven J. Pitts, Amy Mitchell, Anne Heidi Skogholt, Bendik S. Winsvold, Bamp#x000F8;rge Sivertsen, Eystein Stordal, Gunnar Morken, Hamp#x000E5;vard Kallestad, Ingrid Heuch, John-Anker Zwart, Katrine Kveli Fjukstad, Linda M. Pedersen, Maiken Elvestad Gabrielsen, Marianne Bakke Johnsen, Marit Skrove, Marit Samp#x000E6;bamp#x000F8, Indredavik, Ole Kristian Drange, Ottar Bjerkeset, Sigrid Bamp#x000F8;rte, Synne amp#x000D8;ien Stensland, Hamp#x000E9;lamp#x000E8;ne Choquet, Anna R. Docherty, Jessica D. Faul, Johanna R. Foerster, Lars G. Fritsche, Maiken Elvestad Gabrielsen, Scott D. Gordon, Jeffrey Haessler, Jouke-Jan Hottenga, Hongyan Huang, Seon-Kyeong Jang, Philip R. Jansen, Yueh Ling, Reedik Mamp#x000E4;gi, Nana Matoba, George McMahon, Antonella Mulas, Valeria Orramp#x000F9;, Teemu Palviainen, Anita Pandit, Gunnar W. Reginsson, Anne Heidi Skogholt, Jennifer A. Smith, Amy E. Taylor, Constance Turman, Gonneke Willemsen, Hannah Young, Kendra A. Young, Gregory J. M. Zajac, Wei Zhao, Wei Zhou, Gyda Bjornsdottir, Jason D. Boardman, Michael Boehnke, Dorret I. Boomsma, Chu Chen, Francesco Cucca, Gareth E. Davies, Charles B. Eaton, Marissa A. Ehringer, Tamp#x000F5;nu Esko, Edoardo Fiorillo, Nathan A. Gillespie, Daniel F. Gudbjartsson, Toomas Haller, Kathleen Mullan Harris, Andrew C. Heath, John K. Hewitt, Ian B. Hickie, John E. Hokanson, Christian J. Hopfer, David J. Hunter, William G. Iacono, Eric O. Johnson, Yoichiro Kamatani, Sharon L. R. Kardia, Matthew C. Keller, Manolis Kellis, Charles Kooperberg, Peter Kraft, Kenneth S. Krauter, Markku Laakso, Penelope A. Lind, Anu Loukola, Sharon M. Lutz, Pamela A. F. Madden, Nicholas G. Martin, Matt McGue, Matthew B. McQueen, Sarah E. Medland, Andres Metspalu, Karen L. Mohlke, Jonas B. Nielsen, Yukinori Okada, Ulrike Peters, Tinca J. C. Polderman, Danielle Posthuma, Alexander P. Reiner, John P. Rice, Eric Rimm, Richard J. Rose, Valgerdur Runarsdottir, Michael C. Stallings, Alena Stanamp#x0010D;amp#x000E1;kovamp#x000E1;, Hreinn Stefansson, Khanh K. Thai, Hilary A. Tindle, Thorarinn Tyrfingsson, Tamara L. Wall, David R. Weir, Constance Weisner, John B. Whitfield, Bendik Slagsvold Winsvold, Jie Yin, Luisa Zuccolo, Laura J. Bierut, Kristian Hveem, James J. Lee, Marcus R. Munafamp#x000F2;, Nancy L. Saccone, Cristen J. Willer, Marilyn C. Cornelis, Sean P. David, David A. Hinds, Eric Jorgenson, Jaakko Kaprio, Jerry A. Stitzel, Kari Stefansson, Thorgeir E. Thorgeirsson, Gonamp#x000E7;alo Abecasis, Dajiang J. Liu, Scott Vrieze ( )
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.
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. © 2019 European Association of Personality Psychology
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-gurdasani.pdf: “Genomics of disease risk in globally diverse populations”, Deepti Gurdasani, Inamp#x000EA;s Barroso, Eleftheria Zeggini, Manjinder S. Sandhu
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, Melissa Smart, M. Kumari, Gonneke Willemsen, Jouke-Jan Hottenga, Dorret I. Boomsma, Eco J. C. Geus, Michel G. Nivard, Meike Bartels ( )
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 .
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 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]
- 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 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.
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-south.pdf: “Sex differences in the Big Five model personality traits: A behavior genetics exploration”, (2018-06-01):
- 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, ) but did not support genetic or environmental sex differences in any trait.
[Keywords: personality, sex differences, behavior genetics, twin]
2016-okbay.pdf: “Genetic variants associated with subjective well–being, depressive symptoms, and neuroticism identified through genome–wide analyses”, (2018-04-26; ):
Major depressive disorder (MDD) 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: lower educational attainment and higher body mass were putatively causal, whereas major depression and 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.
2018-wiklund.pdf: “Childhood , Camilla A. Wiklund, Ralf Kuja-Halkola, Laura M. Thornton, Katarina Bälter, Elisabeth Welch, Cynthia M. Bulik and development of eating disorder traits across adolescence”
2018-weinschenk.pdf: “The Effect of Education on Political Knowledge: Evidence From Monozygotic Twins”, (2018-01-01):
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 ofof 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 fordue 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.
2018-walters.pdf: “Transancestral , Raymond K. Walters, Renato Polimanti, Emma C. Johnson, Jeanette N. McClintick, Mark J. Adams, Amy E. Adkins, Fazil Aliev, Silviu-Alin Bacanu, Anthony Batzler, Sarah Bertelsen, Joanna M. Biernacka, Tim B. Bigdeli, Li-Shiun Chen, Toni-Kim Clarke, Yi-Ling Chou, Franziska Degenhardt, Anna R. Docherty, Alexis C. Edwards, Pierre Fontanillas, Jerome C. Foo, Louis Fox, Josef Frank, Ina Giegling, Scott Gordon, Laura M. Hack, Annette M. Hartmann, Sarah M. Hartz, Stefanie Heilmann-Heimbach, Stefan Herms, Colin Hodgkinson, Per Hoffmann, Jouke Hottenga, Martin A. Kennedy, Mervi Alanne-Kinnunen, Bettina Konte, Jari Lahti, Marius Lahti-Pulkkinen, Dongbing Lai, Lannie Ligthart, Anu Loukola, Brion S. Maher, Hamdi Mbarek, Andrew M. McIntosh, Matthew B. McQueen, Jacquelyn L. Meyers, Yuri Milaneschi, Teemu Palviainen, John F. Pearson, Roseann E. Peterson, Samuli Ripatti, Euijung Ryu, Nancy L. Saccone, Jessica E. Salvatore, Sandra Sanchez-Roige, Melanie Schwandt, Richard Sherva, Fabian Streit, Jana Strohmaier, Nathaniel Thomas, Jen-Chyong Wang, Bradley T. Webb, Robbee Wedow, Leah Wetherill, Amanda G. Wills, Michelle Agee, Babak Alipanahi, Adam Auton, Robert K. Bell, Katarzyna Bryc, Sarah L. Elson, Pierre Fontanillas, Nicholas A. Furlotte, David A. Hinds, Karen E. Huber, Aaron Kleinman, Nadia K. Litterman, Jennifer C. McCreight, Matthew H. McIntyre, Joanna L. Mountain, Elizabeth S. Noblin, Carrie A. M. Northover, Steven J. Pitts, J. Fah Sathirapongsasuti, Olga V. Sazonova, Janie F. Shelton, Suyash Shringarpure, Chao Tian, Joyce Y. Tung, Vladimir Vacic, Catherine H. Wilson, Jason D. Boardman, Danfeng Chen, Doo-Sup Choi, William E. Copeland, Robert C. Culverhouse, Norbert Dahmen, Louisa Degenhardt, Benjamin W. Domingue, Sarah L. Elson, Mark A. Frye, Wolfgang Gäbel, Caroline Hayward, Marcus Ising, Margaret Keyes, Falk Kiefer, John Kramer, Samuel Kuperman, Susanne Lucae, Michael T. Lynskey, Wolfgang Maier, Karl Mann, Satu Männistö, Bertram Müller-Myhsok, Alison D. Murray, John I. Nurnberger, Aarno Palotie, Ulrich Preuss, Katri Räikkönen, Maureen D. Reynolds, Monika Ridinger, Norbert Scherbaum, Marc A. Schuckit, Michael Soyka, Jens Treutlein, Stephanie Witt, Norbert Wodarz, Peter Zill, Daniel E. Adkins, Joseph M. Boden, Dorret I. Boomsma, Laura J. Bierut, Sandra A. Brown, Kathleen K. Bucholz, Sven Cichon, E. Jane Costello, Harriet Wit, Nancy Diazgranados, Danielle M. Dick, Johan G. Eriksson, Lindsay A. Farrer, Tatiana M. Foroud, Nathan A. Gillespie, Alison M. Goate, David Goldman, Richard A. Grucza, Dana B. Hancock, Kathleen Mullan Harris, Andrew C. Heath, Victor Hesselbrock, John K. Hewitt, Christian J. Hopfer, John Horwood, William Iacono, Eric O. Johnson, Jaakko A. Kaprio, Victor M. Karpyak, Kenneth S. Kendler, Henry R. Kranzler, Kenneth Krauter, Paul Lichtenstein, Penelope A. Lind, Matt McGue, James MacKillop, Pamela A. F. Madden, Hermine H. Maes, Patrik Magnusson, Nicholas G. Martin, Sarah E. Medland, Grant W. Montgomery, Elliot C. Nelson, Markus M. Nöthen, Abraham A. Palmer, Nancy L. Pedersen, Brenda W. J. H. Penninx, Bernice Porjesz, John P. Rice, Marcella Rietschel, Brien P. Riley, Richard Rose, Dan Rujescu, Pei-Hong Shen, Judy Silberg, Michael C. Stallings, Ralph E. Tarter, Michael M. Vanyukov, Scott Vrieze, Tamara L. Wall, John B. Whitfield, Hongyu Zhao, Benjamin M. Neale, Joel Gelernter, Howard J. Edenberg, Arpana Agrawal ( of alcohol dependence reveals common genetic underpinnings with psychiatric disorders” )
2018-verbanck.pdf: “Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases”, Marie Verbanck, Chia-Yen Chen, Benjamin Neale, Ron Do
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, Frank Dudbridge
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
2018-pasman.pdf: “GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal influence of schizophrenia”, Joamp#x000EB;lle A. Pasman ( )
2018-ni.pdf: “Estimation of , Guiyan Ni, Gerhard Moser, via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood” Working Group of the Psychiatric Genomics Consortium, Stephan Ripke, Benjamin M. Neale, Aiden Corvin, James T. R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau Jr., Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberly D. Chambert, Raymond C. K. Chan, Ronald Y. L. Chen, Eric Y. H. Chen, Wei Cheng, Eric F. C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, David Curtis, Michael Davidson, Kenneth L. Davis, Franziska Degenhardt, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Giulio Genovese, Lyudmila Georgieva, Ina Giegling, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Marian L. Hamshere, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Annette M. Hartmann, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, David M. Hougaard, Masashi Ikeda, Inge Joa, Antonio Juliá, René S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, James A. Knowles, Bettina Konte, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee Chee Keong, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lönnqvist, Milan Macek Jr., Patrik K. E. Magnusson, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsda, Robert W. McCarley, Colm McDonald, Andrew M. McIntosh, Sandra Meier, Carin J. Meijer, Bela Melegh, Ingrid Melle, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Lili Milani, Vihra Milanova, Younes Mokrab, Derek W. Morris, Ole Mors, Kieran C. Murphy, Robin M. Murray, Inez Myin-Germeys, Bertram Müller-Myhsok, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O’Callaghan, Colm O’Dushlaine, F. Anthony O’Neill, Sang-Yun Oh, Ann Olinc, Line Olsen, Jim Van Os, Christos Pantelis, George N. Papadimitriou, Sergi Papio, Elena Parkhomenko, Michele T. Pato, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietiläinenl, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Alan R. Sanders, Ulrich Schall, Christian R. Schubert, Thomas G. Schulze, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Jianxin Shi, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Jordan W. Smoller, Hon-Cheong So, Chris C. A. Spencer, Eli A. Stah, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T. Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Söderman, Srinivas Thirumalai, Draga Toncheva, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H. M. Wong, Brandon K. Wormley, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Kari Stefansson, Peter M. Visscher, Rolf Adolfsson, Ole A. Andreassen, Douglas H. R. Blackwood, Elvira Bramon, Joseph D. Buxbaum, Anders D. Børglum, Sven Cichon, Ariel Darvasi, Enrico Domenici, Hannelore Ehrenreich, Tõnu Esko, Pablo V. Gejman, Michael Gill, Hugh Gurling, Christina M. Hultman, Nakao Iwata, Assen V. Jablensky, Erik G. Jönsson, Kenneth S. Kendler, George Kirov, Jo Knight, Todd Lencz, Douglas F. Levinson, Qingqin S. Li, Jianjun Liu, Anil K. Malhotra, Steven A. McCarrol, Andrew McQuillin, Jennifer L. Moran, Preben B. Mortensen, Bryan J. Mowry, Markus M. Nöthen, Roel A. Ophoff, Michael J. Owen, Aarno Palotie, Carlos N. Pato, Tracey L. Petryshen, Danielle Posthuma, Marcella Rietsche, Brien P. Riley, Dan Rujescu, Pak C. Sham, Pamela Sklar, David St Clair, Daniel R. Weinberger, Jens R. Wendland, Thomas Werge, Mark J. Daly, Patrick F. Sullivan, Michael C. O’Donovan, Naomi R. Wray, S. Hong Lee, Psychosis Endophenotypes International Consortium, Wellcome Trust Consortium
2018-nedelec.pdf: “Challenging Assumptions: A Genetically Sensitive Assessment of the Criminogenic Effect of Contact With the Criminal Justice System”, (2018-01-01):
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.
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
2018-lewis.pdf: “A Behavioral Genetic Analysis of the Cooccurrence Between Psychopathic Personality Traits and Criminal Behavior”, (2018-01-01):
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 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 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 personality traits were not statistically-significantly associated with criminal behavior once common genetic and environmental influences were taken into account.
2018-khramtsova.pdf: “The role of sex in the genomics of human complex traits”, Ekaterina A. Khramtsova, Lea K. Davis, Barbara E. Stranger
2018-gustavson.pdf: “Genetic and Environmental Influences on Verbal Fluency in Middle Age: A Longitudinal Twin Study”, Daniel E. Gustavson
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-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, Loic Yengo, Zhili Zheng, Maciej Trzaskowski, Eveline L. de Zeeuw, Michel G. Nivard, Marjolijn Das, Rachel E. Neale, Stuart MacGregor, Catherine M. Olsen, David C. Whiteman, Dorret I. Boomsma, Jian Yang, Marcella Rietschel, John J. McGrath, Sarah E. Medland, Nicholas G. Martin ( )
2018-boisvert.pdf: “Genetic and Environmental Overlap Between Substance Use and Delinquency in Adolescence”, (2018-01-01):
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 (i.e., marijuana and alcohol) and different forms of delinquent offending (i.e., 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.
2018-ayoub.pdf: “Genetic and Environmental Associations Between Child Personality and Parenting”, (2018-01-01):
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 childpersonality 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 .
2017-cesta.pdf: “Polycystic ovary syndrome, personality, and depression: A twin study”, (2017-11-01):
- 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 approximately 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,]
2018-turley.pdf: “Multi-trait analysis of genome-wide association summary statistics using MTAG”, (2017-10-23; ):
We introduce multi-trait analysis of MTAG), a method for joint analysis of summary statistics from genome-wide association studies ( ) 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 (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 approximately 25%, matching theoretical expectations.(
2017-akiyama.pdf: “Genome-wide association study identifies 112 new loci for body mass index in the Japanese population”, (2017-09-11; ):
Obesity is a risk factor for a wide variety of health problems. In a 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.( ) of ( ) 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 of Europeans and identified 61 additional new loci. In total, this study identifies 112 novel loci, doubling the number of previously known -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 between and lymphocyte count (p = 6.46 × 10−5, rg = 0.18) and between
2017-wang.pdf: “Genetic correlations of hip dysplasia scores for Golden retrievers and Labrador retrievers in France, Sweden and the UK”, (2017-08-01):
- 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 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 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.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 (
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 favourableestimated 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]
2017-verhulst.pdf: “GW-, Brad Verhulst : A Statistical Package to Conduct Genome-Wide Structural Equation Modeling”
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-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, Andrew Bakshi, Daniel A. Briley, Charles Rahal, Robert Hellpap, Anastasia N. Iliadou, Tamp#x000F5;nu Esko, Andres Metspalu, Sarah E. Medland, Nicholas G. Martin, Nicola Barban, Harold Snieder, Matthew R. Robinson, Melinda C. Mills ( )
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
2017-smeland.pdf: “Identification of Genetic Loci Jointly Influencing , American Medical Association Risk and the Cognitive Traits of Verbal-Numerical Reasoning, Reaction Time, and General Cognitive Function”
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, Robert F. Krueger, Kenneth S. Kendler, Ted Reichborn-Kjennerud
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, Wouter J. Peyrot, Abdel Abdellaoui, Brendan P. Zietsch, Ilja M. Nolte, Jana V. van Vliet-Ostaptchouk, Harold Snieder, Sarah E. Medland, Nicholas G. Martin, Patrik K. E. Magnusson, William G. Iacono, Matt McGue, Kari E. North, Jian Yang, Peter M. Visscher ( )
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, Dixie B. Strathan, Andrew Heath, Michael Lynskey, Wendy Slutske, Nicholas G. Martin, Elliot M. Tucker-Drob, K. Paige Harden
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, Jiawei Shen, Zhijian Song, Weidong Ji, Meng Wang, Juan Zhou, Boyu Chen, Yahui Liu, Jiqiang Wang, Peng Wang, Ping Yang, Qingzhong Wang, Guoyin Feng, Benxiu Liu, Wensheng Sun, Baojie Li, Guang He, Weidong Li, Chunling Wan, Qi Xu, Wenjin Li, Zujia Wen, Ke Liu, Fang Huang, Jue Ji, Stephan Ripke, Weihua Yue, Patrick F. Sullivan, Michael C. O'Donovan, Yongyong Shi
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-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, Michael E. Weale, Chris C. A Spencer, François Aguet, Ayellet V. Segrè, Kristin G. Ardlie, Amit V. Khera, Virendar K. Kaushik, Pradeep Natarajan, Sekar Kathiresan
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, Jie Zheng, Celia L. Gregson, Elin Grundberg, Katerina Trajanoska, John G. Logan, Andrea S. Pollard, Penny C. Sparkes, Elena J. Ghirardello, Rebecca Allen, Victoria D. Leitch, Natalie C. Butterfield, Davide Komla-Ebri, Anne-Tounsia Adoum, Katharine F. Curry, Jacqueline K. White, Fiona Kussy, Keelin M. Greenlaw, Changjiang Xu, Nicholas C. Harvey, Cyrus Cooper, David J. Adams, Celia M. T Greenwood, Matthew T. Maurano, Stephen Kaptoge, Fernando Rivadeneira, Jonathan H. Tobias, Peter I. Croucher, Cheryl L. Ackert-Bicknell, J. H Duncan Bassett, Graham R. Williams, J. Brent Richards, David M. Evans
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, C. Weisner, H. Choquet
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, B. Merkely, G. Jermendy, P. Maurovich-Horvat
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, Stephen Leslie, Lars Fugger, Gil McVean
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-chester.pdf: “Genetic correlation between alcohol preference and conditioned fear: Exploring a functional relationship”, Julia A. Chester, Marcus M. Weera
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, R. R, Allingham, Allison Ashley-Koch, Richard K. Lee, Sayoko E. Moroi, Murray H. Brilliant, Gadi Wollstein, Joel S. Schuman, John H. Fingert, Donald L. Budenz, Tony Realini, Terry Gaasterland, William K. Scott, Kuldev Singh, Arthur J. Sit, Robert P. Igo Jr, Yeunjoo E. Song, Lisa Hark, Robert Ritch, Douglas J. Rhee, Vikas Gulati, Shane Haven, Douglas Vollrath, Donald J. Zack, Felipe Medeiros, Robert N. Weinreb, Ching-Yu Cheng, Daniel I. Chasman, William G. Christen, Margaret A. Pericak-Vance, Yutao Liu, Peter Kraft, Julia E. Richards, Bernard A. Rosner, Michael A. Hauser, Caroline C. W Klaver, Cornelia M. vanDuijn, Jonathan Haines, Janey L. Wiggs, Louis R. Pasquale
2017-allardyce.pdf: “Association Between , American Medical Association -Related Polygenic Liability and the Occurrence and Level of Mood-Incongruent Psychotic Symptoms in Bipolar Disorder”
2016-neumann.pdf: “Single Nucleotide Polymorphism Heritability of a General Psychopathology Factor in Children”, (2016-12-01):
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]
2016-barban.pdf: “Genome-wide analysis identifies 12 loci influencing human reproductive behavior”, (2016-10-31; ):
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-basedand 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.
2016-lee.pdf: “Partitioning heritability analysis reveals a shared genetic basis of brain anatomy and schizophrenia”, (2016-10-11):
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-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 SNP selection conditions. Cross-disorder comparison suggests that the neuro-genetic architecture of -associated brain regions is, at least in part, shared with other psychiatric disorders.-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 genetic risk under varying
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.
2016-hyde.pdf: “Identification of 15 genetic loci associated with risk of major depression in individuals of European descent”, (2016-08-01; ):
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.
2016-belsky.pdf: “The Genetics of Success: How Single-Nucleotide Polymorphisms Associated With Educational Attainment Relate to Life-Course Development”, (2016-06-01; ):
A previous( ) 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 thisusing the 4-decade Dunedin Study (N = 918). There were 5 main findings.
- polygenic scores predicted adult economic outcomes even after accounting for educational attainments.
- genes and environments were correlated: Children with higher polygenic scores were born into better-off homes.
- 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.
- 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.
- polygenic-score associations were mediated by psychological characteristics, including intelligence, self-control, and interpersonal skill. Effect sizes were small.
Factors connectingsequence with life outcomes may provide targets for interventions to promote population-wide positive development.
[Keywords: genetics, behavior genetics, intelligence, personality, adult development]
2016-oskarsson.pdf: “Education and Social Trust: Testing a Causal Hypothesis Using the Discordant Twin Design”, (2016-04-27):
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.
2016-karvinen.pdf: “Lifespan and Skeletal Muscle Properties: The Effects of Genetic Background, Physical Activity and Aging”, (2016-04-22; ):
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:
- a cross-sectional voluntary running intervention in high-capacity runner (HCR) and low-capacity runner (LCR) rats,
- a longitudinal voluntary running intervention in HCR and LCR rats, and
- 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.
- Torvinen et al 2012, “Rats bred for low aerobic capacity become promptly fatigued and have slow metabolic recovery after stimulated, maximal muscle contractions”
- Karvinen et al 2012, “Physical activity in adulthood: genes and mortality”
- Karvinen et al 2016, “Effects of intrinsic aerobic capacity, aging and voluntary running on skeletal muscle sirtuins and heat shock proteins”
- Karvinen et al 2016, “Voluntary running aids to maintain high body temperature in rats bred for high aerobic capacity”
2016-day.pdf: “Physical and neurobehavioral determinants of reproductive onset and success”, (2016-04-18; ):
The ages of puberty, first sexual intercourse and first birth signify the onset of reproductive ability, behavior and success, respectively. In a 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.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
2016-wang.pdf: “Genetic factor common to 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 and
2016-wang-2.pdf: “Not all risks are created equal: A twin study and meta-analyses of risk taking across seven domains”, X. T. (Xiao-Tian) Wang, Rui Zheng, Yan-Hua Xuan, Jie Chen, Shu Li
2016-vanhulzen.pdf: “Genetic overlap between Attention-Deficit /
Hyperactivity Disorder and Bipolar Disorder_ Evidence from BPD GWAS”meta-analysisMeta-analysis of and , Kimm J. E. van Hulzen, Claus J. Scholz, Barbara Franke, Stephan Ripke, Marieke Klein, Andrew McQuillin, Edmund J. Sonuga-Barke, John R. Kelsoe, Mikael Landén, Ole A. Andreassen, Klaus-Peter Lesch, Heike Weber, Stephen V. Faraone, Alejandro Arias-Vasquez, Andreas Reif
2016-smith.pdf: “Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci”, (2016-01-01; ):
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 ( ) 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 between neuroticism and MDD and a less strong but statistically-significant 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 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.
2016-salvatore.pdf: “Alcohol use disorder and divorce: Evidence for a , Jessica E. Salvatore, Sara Larsson Lönn, Jan Sundquist, Paul Lichtenstein, Kristina Sundquist, Kenneth S. Kendler in a population-based Swedish sample”
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, Julian Maller, Kaitlin E. Samocha, Stephan J. Sanders, Stephan Ripke, Joanna Martin, Mads V. Hollegaard, Thomas Werge, David M. Hougaard, Benjamin M. Neale, David M. Evans, David Skuse, Preben Bo Mortensen, Anders D. Børglum, Angelica Ronald, George Davey Smith, Mark J. Daly ( )
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 MRCGP, Barbara Maughan, Michael C. O'Donovansych, Anita Thaparsych ( )
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-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-kendall.pdf: “Cognitive Performance Among Carriers of Pathogenic Copy Number Variants_ Analysis of 152,000 UK Biobank Subjects”, Kimberley M. Kendall, Elliott Rees, Valentina Escott-Price, Mark Einon, Rhys Thomas, Jonathan Hewitt, Michael C. O’Donovan, Michael J. Owen, James T. R. Walters, George Kirov ( )
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, Bjarke Feenstra, Natalie R. van Zuydam, Kyle J. Gaulton, Niels Grarup, Jonathan P. Bradfield, David P. Strachan, Ruifang Li-Gao, Tarunveer S. Ahluwalia, Eskil Kreiner, Rico Rueedi, Leo-Pekka Lyytikäinen, Diana L. Cousminer, Ying Wu, Elisabeth Thiering, Carol A. Wang, Christian T. Have, Jouke-Jan Hottenga, Natalia Vilor-Tejedor, Peter K. Joshi, Eileen Tai Hui Boh, Ioanna Ntalla, Niina Pitkänen, Anubha Mahajan, Elisabeth M. van Leeuwen, Raimo Joro, Vasiliki Lagou, Michael Nodzenski, Louise A. Diver, Krina T. Zondervan, Mariona Bustamante, Pedro Marques-Vidal, Josep M. Mercader, Amanda J. Bennett, Nilufer Rahmioglu, Dale R. Nyholt, Ronald C. W. Ma, Claudia H. T. Tam, Wing Hung Tam, Santhi K. Ganesh, Frank J. A. van Rooij, Samuel E. Jones, Po-Ru Loh, Katherine S. Ruth, Marcus A. Tuke, Jessica Tyrrell, Andrew R. Wood, Hanieh Yaghootkar, Denise M. Scholtens, Lavinia Paternoster, Inga Prokopenko, Peter Kovacs, Mustafa Atalay, Sara M. Willems, Kalliope Panoutsopoulou, Xu Wang, Lisbeth Carstensen, Frank Geller, Katharina E. Schraut, Mario Murcia, Catharina E. M. van Beijsterveldt, Gonneke Willemsen, Emil V. R. Appel, Cilius E. Fonvig, Caecilie Trier, Carla M. T. Tiesler, Marie Standl, Zoltán Kutalik, Sílvia Bonàs-Guarch, David M. Hougaard, Friman Sánchez, David Torrents, Johannes Waage, Mads V. Hollegaard, Hugoline G. de Haan, Frits R. Rosendaal, Carolina Medina-Gomez, Susan M. Ring, Gibran Hemani, George McMahon, Neil R. Robertson, Christopher J. Groves, Claudia Langenberg, Jian’an Luan, Robert A. Scott, Jing Hua Zhao, Frank D. Mentch, Scott M. MacKenzie, Rebecca M. Reynolds, William L. Lowe, Anke Tönjes, Michael Stumvoll, Virpi Lindi, Timo A. Lakka, Cornelia M. van Duijn, Wiel, Kiess, Antje Körner, Thorkild I. A. Sørensen, Harri Niinikoski, Katja Pahkala, Olli T. Raitakari, Eleftheria Zeggini, George V. Dedoussis, Yik-Ying Teo, Seang-Mei Saw, Mads Melbye, Harry Campbell, James F. Wilson, Martine Vrijheid, Eco J. C. N. de Geus, Dorret I. Boomsma, Haja N. Kadarmideen, Jens-Christian Holm, Torben Hansen, Sylvain Sebert, Andrew T. Hattersley, Lawrence J. Beilin, John P. Newnham, Craig E. Pennell, Joachim Heinrich, Linda S. Adair, Judith B. Borja, Karen L. Mohlke, Johan G. Eriksson, Elisabeth Widén, Mika Kähönen, Jorma S. Viikari, Terho Lehtimäki, Peter Vollenweider, Klaus Bønnelykke, Hans Bisgaard, Dennis O. Mook-Kanamori, Albert Hofman, Fernando Rivadeneira, André G. Uitterlinden, Charlotta Pisinger, Oluf Pedersen, Christine Power, Elina Hyppönen, Nicholas J. Wareham, Hakon Hakonarson, Eleanor Davies, Brian R. Walker, Vincent W. V. Jaddoe, Marjo-Riitta Järvelin, Struan F. A. Grant, Allan A. Vaag, Debbie A. Lawlor, Timothy M. Frayling, George Davey Smith, Andrew P. Morris, Ken K. Ong, Janine F. Felix, Nicholas J. Timpson, John R. B. Perry, David M. Evans, Mark I. McCarthy, Rachel M. Freathy
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
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, Naomi P. Friedman
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, Stella Trompet, Alejandro Arias-Vasquez, Sudha Seshadri, Sylvane Desrivières, Ashley H. Beecham, Neda Jahanshad, Katharina Wittfeld, Sven J. Van der Lee, Lucija Abramovic, Saud Alhusaini, Najaf Amin, Micael Andersson, Konstantinos Arfanakis, Benjamin S. Aribisala, Nicola J. Armstrong, Lavinia Athanasiu, Tomas Axelsson, Alexa Beiser, Manon Bernard, Joshua C. Bis, Laura M. E Blanken, Susan H. Blanton, Marc M. Bohlken, Marco P. Boks, Janita Bralten, Adam M. Brickman, Owen Carmichael, M. Mallar Chakravarty, Ganesh Chauhan, Qiang Chen, Christopher R. K Ching, Gabriel Cuellar-Partida, Anouk Den Braber, Nhat Trung Doan, Stefan Ehrlich, Irina Filippi, Tian Ge, Sudheer Giddaluru, Aaron L. Goldman, Rebecca F. Gottesman, Corina U. Greven, Oliver Grimm, Michael E. Griswold, Tulio Guadalupe, Johanna Hass, Unn K. Haukvik, Saima Hilal, Edith Hofer, David Hoehn, Avram J. Holmes, Martine Hoogman, Deborah Janowitz, Tianye Jia, Dalia Kasperaviciute, Sungeun Kim, Marieke Klein, Bernd Kraemer, Phil H. Lee, Jiemin Liao, David C. M Liewald, Lorna M. Lopez, Michelle Luciano, Christine Macare, Andre Marquand, Mar Matarin, Karen A. Mather, Manuel Mattheisen, Bernard Mazoyer, David R. McKay, Rebekah McWhirter, Yuri Milaneschi, Nazanin Mirza-Schreiber, Ryan L. Muetzel, Susana Muñoz Maniega, Kwangsik Nho, Allison C. Nugent, Loes M. Olde Loohuis, Jaap Oosterlaan, Martina Papmeyer, Irene Pappa, Lukas Pirpamer, Sara Pudas, Benno Pütz, Kumar B. Rajan, Adaikalavan Ramasamy, Jennifer S. Richards, Shannon L. Risacher, Roberto Roiz-Santiañez, Nanda Rommelse, Emma J. Rose, Natalie A. Royle, Tatjana Rundek, Philipp G. Sämann, Claudia L. Satizabal, Lianne Schmaal, Andrew J. Schork, Li Shen, Jean Shin, Elena Shumskaya, Albert V. Smith, Emma Sprooten, Lachlan T. Strike, Alexander Teumer, Russell Thomson, Diana Tordesillas-Gutierrez, Roberto Toro, Daniah Trabzuni, Dhananjay Vaidya, Jeroen Van der Grond, Dennis Van der Meer, Marjolein M. J Van Donkelaar, Kristel R. Van Eijk, Theo G. M Van Erp, Daan Van Rooij, Esther Walton, Lars T. Westlye, Christopher D. Whelan, Beverly G. Windham, Anderson M. Winkler, Girma Woldehawariat, Christiane Wolf, Thomas Wolfers, Bing Xu, Lisa R. Yanek, Jingyun Yang, Alex Zijdenbos, Marcel P. Zwiers, Ingrid Agartz, Neelum T. Aggarwal, Laura Almasy, David Ames, Philippe Amouyel, Ole A. Andreassen, Sampath Arepalli, Amelia A. Assareh, Sandra Barral, Mark E. Bastin, Diane M. Becker, James T. Becker, David A. Bennett, John Blangero, Hans van Bokhoven, Dorret I. Boomsma, Henry Brodaty, Rachel M. Brouwer, Han G. Brunner, Randy L. Buckner, Jan K. Buitelaar, Kazima B. Bulayeva, Wiepke Cahn, Vince D. Calhoun, Dara M. Cannon, Gianpiero L. Cavalleri, Christopher Chen, Ching-Yu Cheng, Sven Cichon, Mark R. Cookson, Aiden Corvin, Benedicto Crespo-Facorro, Joanne E. Curran, Michael Czisch, Anders M. Dale, Gareth E. Davies, Eco J. C De Geus, Philip L. De Jager, Greig I. de Zubicaray, Norman Delanty, Chantal Depondt, Anita L. DeStefano, Allissa Dillman, Srdjan Djurovic, Gary Donohoe, Wayne C. Drevets, Ravi Duggirala, Thomas D. Dyer, Susanne Erk, Thomas Espeseth, Denis A. Evans, Iryna O. Fedko, Guillén Fernández, Luigi Ferrucci, Simon E. Fisher, Debra A. Fleischman, Ian Ford, Tatiana M. Foroud, Peter T. Fox, Clyde Francks, Masaki Fukunaga, J. Raphael Gibbs, David C. Glahn, Randy L. Gollub, Harald H. H Göring, Hans J. Grabe, Robert C. Green, Oliver Gruber, Vilmundur Gudnason, Sebastian Guelfi, Narelle K. Hansell, John Hardy, Catharina A. Hartman, Ryota Hashimoto, Katrin Hegenscheid, Andreas Heinz, Stephanie Le Hellard, Dena G. Hernandez, Dirk J. Heslenfeld, Beng-Choon Ho, Pieter J. Hoekstra, Wolfgang Hoffmann, Albert Hofman, Florian Holsboer, Georg Homuth, Norbert Hosten, Jouke-Jan Hottenga, Hilleke E. Hulshoff Pol, Masashi Ikeda, M. Kamran Ikram, Clifford R. Jack Jr, Mark Jenkinson, Robert Johnson, Erik G. Jönsson, J. Wouter Jukema, René S. Kahn, Ryota Kanai, Iwona Kloszewska, David S. Knopman, Peter Kochunov, John B. Kwok, Stephen M. Lawrie, Hervé Lemaître, Xinmin Liu, Dan L. Longo, W. T Longstreth Jr, Oscar L. Lopez, Simon Lovestone, Oliver Martinez, Jean-Luc Martinot, Venkata S. Mattay, Colm McDonald, Andrew M. McIntosh, Katie L. McMahon, Francis J. McMahon, Patrizia Mecocci, Ingrid Melle, Andreas Meyer-Lindenberg, Sebastian Mohnke, Grant W. Montgomery, Derek W. Morris, Thomas H. Mosley, Thomas W. Mühleisen, Bertram Müller-Myhsok, Michael A. Nalls, Matthias Nauck, Thomas E. Nichols, Wiro J. Niessen, Markus M. Nöthen, Lars Nyberg, Kazutaka Ohi, Rene L. Olvera, Roel A. Ophoff, Massimo Pandolfo, Tomas Paus, Zdenka Pausova, Brenda W. J H. Penninx, G. Bruce Pike, Steven G. Potkin, Bruce M. Psaty, Simone Reppermund, Marcella Rietschel, Joshua L. Roffman, Nina Romanczuk-Seiferth, Jerome I. Rotter, Mina Ryten, Ralph L. Sacco, Perminder S. Sachdev, Andrew J. Saykin, Reinhold Schmidt, Peter R. Schofield, Sigurdur Sigurdsson, Andy Simmons, Andrew Singleton, Sanjay M. Sisodiya, Colin Smith, Jordan W. Smoller, Hilkka Soininen, Velandai Srikanth, Vidar M. Steen, David J. Stott, Jessika E. Sussmann, Anbupalam Thalamuthu, Henning Tiemeier, Arthur W. Toga, Bryan J. Traynor, Juan Troncoso, Jessica A. Turner, Christophe Tzourio, Andre G. Uitterlinden, Maria C. Valdés Hernández, Marcel Van der Brug, Aad Van der Lugt, Nic J. A Van der Wee, Cornelia M. Van Duijn, Neeltje E. M Van Haren, Dennis Van ′t Ent, Marie-Jose Van Tol, Badri N. Vardarajan, Dick J. Veltman, Meike W. Vernooij, Henry Völzke, Henrik Walter, Joanna M. Wardlaw, Thomas H. Wassink, Michael E. Weale, Daniel R. Weinberger, Michael W. Weiner, Wei Wen, Eric Westman, Tonya White, Tien Y. Wong, Clinton B. Wright, H. Ronald Zielke, Alan B. Zonderman, Ian J. Deary, Charles DeCarli, Helena Schmidt, Nicholas G. Martin, Anton J. M De Craen, Margaret J. Wright, Lenore J. Launer, Gunter Schumann, Myriam Fornage, Barbara Franke, Stéphanie Debette, Sarah E. Medland, M. Arfan Ikram, Paul M. Thompson
2015-power.pdf: “Polygenic risk scores for schizophrenia and bipolar disorder predict creativity”, (2015-06-08; ):
We tested whether polygenic risk scores forand 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.
2015-zhu.pdf: “Educational attainment-related loci identified by , Bi Zhu, Chuansheng Chen, Robert K. Moyzis, Qi Dong, Chongde Lin ( are associated with select personality traits and mathematics and language abilities” )
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 ( )
2014-toro.pdf: “Genomic architecture of human neuroanatomical diversity”, (2014-09-16; ):
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.
2014-mosing.pdf: “Practice Does Not Make Perfect: No Causal Effect of Music Practice on Music Ability”, (2014-07-30; ):
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]
2014-sariaslan-2.pdf: “Does Population Density and Neighborhood Deprivation Predict Schizophrenia? A Nationwide Swedish Family-Based Study of 2.4 Million Individuals”, (2014-07-22; ):
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 = 2361585), including separate datasets for all cousins (n = 1 715 059) and siblings (n = 1667 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 withand 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 subsequentin 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.
2014-turkheimer.pdf: “Behavior Genetic Research Methods: Testing Quasi-Causal Hypotheses Using Multivariate Twin Data”, Eric Turkheimer, K. Paige Harden ( )
2013-avinun.pdf: “Parenting as a Reaction Evoked by Children’s Genotype: A Meta–Analysis of Children–as–Twins Studies”, (2013-08-12):
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]
2013-hamshere.pdf: “High Loading of Polygenic Risk for ADHD in Children With Comorbid Aggression”, (2013-08-01; ):
Objective: Although attention deficit hyperactivity disorder () is highly heritable, ( ) have not yet identified any common genetic variants that contribute to risk. There is evidence that aggression or conduct disorder in children with indexes higher genetic loading and clinical severity. The authors examine whether common genetic variants considered en masse as polygenic scores for are especially enriched in children with comorbid conduct disorder.
Method: Polygenic scores derived from an GWAS meta-analysis were calculated in an independent sample (452 case subjects, 5,081 comparison subjects). Multivariate logistic regression analyses were employed to compare polygenic scores in the 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 showed statistically-significant association with comorbid conduct disorder symptoms. This relationship was explained by the aggression items., derived from the meta-analysis, was higher in the independent group than in the comparison group. was statistically-significantly higher in case subjects with conduct disorder relative to case subjects without conduct disorder.
Conclusions: Common genetic variation is relevant to ADHD 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., especially in individuals with comorbid aggression. The findings suggest that the previously published
2013-mcintosh.pdf: “Polygenic Risk for Schizophrenia Is Associated with Cognitive Change Between Childhood and Old Age”, (2013-05-15; ):
Background:( ) have shown a polygenic component to the risk of . 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 .
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 , we obtained data from the latest of the Psychiatric GWAS Consortium on . polygenic risk profile scores were calculated using information from the Psychiatric GWAS Consortium on Schizophrenia .
Results: In LBC1936, polygenic risk for was negatively associated with IQ at age 70 but not at age 11. Greater polygenic risk for 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 ofis 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 .
[Keywords: Aging, cognition, dementia,]
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.
2013-parkes.pdf: “Genetic insights into common pathways and complex relationships among immune-mediated diseases”, Miles Parkes, Adrian Cortes, David A. van Heel, Matthew A. Brown
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-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, Lorna M. Lopez, Alan J. Gow, Janie Corley, Paul Redmond, Helen C. Fox, Suzanne J. Rowe, Paul Haggarty, Geraldine McNeill, Michael E. Goddard, David J. Porteous, Lawrence J. Whalley, John M. Starr, Peter M. Visscher ( )
2010-lopez-leon.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
2004-kendler.pdf: “FOCUS Spring 2004.qxd”, Owner
2002-degenhardt.pdf: “Testing hypotheses about the relationship between cannabis use and psychosis”, Louisa Degenhardt, Wayne Hall, Michael Lynskey ( )
1998-lynchwalsh-geneticsquantitativetraits-ch21-geneticcorrelations.pdf: “Chapter 21: Correlations Between Characters”, Michael Lynch, Bruce Walsh ( )
1997-swan.pdf: “Heavy Consumption of Cigarettes, Alcohol and Coffee in Male Twins”, Gary E. Swan, Dorit Carmelli, Lon R. Cardon
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”, (1997):
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.
1996-karjalainen.pdf: “Environmental effects and genetic parameters for measurements of hunting performance in the Finnish Spitz”, L. Karjalainen, M. Ojala, V. Vilva ( )
This study examines the association between post-traumatic stress disorder () 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 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 , 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 , 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 and combat experience in Southeast Asia have not had a major impact on the socioeconomic status of veterans.
1991-defries.pdf: “Chapter 3: Colorado Reading Project: An Update”, J. C. DeFries, R. K. Olson, B. F. Pennington, S. D. Smith ( )
1990-ooki.pdf: “Relationship Between Blood Uric Acid Level and Personality Traits”, (1990-01-01):
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.
1985-mackenzie.pdf: “Heritability estimate for temperament scores in German shepherd dogs and its , Stephen A. Mackenzie, Elizabeth A. B. Oltenacu, Eldin Leighton ( with hip dysplasia” )
1983-goddard.pdf: “Genetics of traits which determine the suitability of dogs as guide-dogs for the blind”, M. E. Goddard, R. G. Beilharz
1982-black.pdf: “Quantitative Genetics of Anthropometric Variation in the Solomon Islands”, Stephen James Black
1978-nance-twinresearchparta-psychologymethodology.pdf: “Twin Research, Part A: Psychology and Methodology”, Walter E. Nance, Gordon Allen, Paolo Parisi
1972-breland.pdf: “Hereditary and Environmental Sources of Trait Variation and Covariation”, (1972):
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: NMSQT, CPI, equal environment assumption, mistaken zygosity, personality, academic achievement, factor analysis, thesis], environmental correlation, behavioral genetics, twin study, 1962 National Merit Scholarship sample,
1951-rae.pdf: “1951 Rae: The Importance of , A. L. in Selection”RAE