Embryo-editing (Link Bibliography)

“Embryo-editing” links:

  1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4356746/bin/mp2014188x3.xlsx

  2. https://ipscell.com/2015/03/georgechurchinterview/

  3. ⁠, Kuna, Samuel T. Maislin, Greg Pack, Frances M. Staley, Bethany Hachadoorian, Robert Coccaro, Emil F. Pack, Allan I (2012):

    Study Objectives: To determine if the large and highly reproducible interindividual differences in rates of performance deficit accumulation during sleep deprivation, as determined by the number of lapses on a sustained reaction time test, the Psychomotor Vigilance Task (PVT), arise from a heritable trait.

    Design: Prospective, observational cohort study.

    Setting: Academic medical center.

    Participants: There were 59 monozygotic (mean age 29.2 ± 6.8 [SD] yr; 15 male and 44 female pairs) and 41 dizygotic (mean age 26.6 ± 7.6 yr; 15 male and 26 female pairs) same-sex twin pairs with a normal polysomnogram.

    Interventions: Thirty-eight hr of monitored, continuous sleep deprivation.

    Measurements and Results: Patients performed the 10-min PVT every 2 hr during the sleep deprivation protocol. The primary outcome was change from baseline in square root transformed total lapses (response time ≥ 500 ms) per trial. Patient-specific linear rates of performance deficit accumulation were separated from circadian effects using multiple linear regression. Using the classic approach to assess heritability, the intraclass correlation coefficients for accumulating deficits resulted in a broad sense heritability (h2) estimate of 0.834. The mean within-pair and among-pair heritability estimates determined by analysis of -based methods was 0.715. When variance components of mixed-effect were estimated by maximum likelihood estimation and used to determine the proportions of phenotypic variance explained by genetic and nongenetic factors, 51.1% (standard error = 8.4%, P < 0.0001) of twin variance was attributed to combined additive and dominance genetic effects.

    Conclusion: Genetic factors explain a large fraction of interindividual variance among rates of performance deficit accumulations on PVT during sleep deprivation.

  4. https://old.reddit.com/r/science/comments/3kj669/science_ama_series_im_yinghui_fu_i_study_the/cuy7fjh

  5. https://www.thecut.com/2015/03/what-its-like-to-need-hardly-any-sleep.html

  6. https://www.wsj.com/articles/SB10001424052748703712504576242701752957910

  7. https://www.bbc.com/future/story/20150706-the-woman-who-barely-sleeps

  8. https://www.npr.org/2011/04/16/135450214/eight-is-too-much-for-short-sleepers

  9. http://www.sciencesleep.org/ziliao/A%20sleep%20diary%20and%20questionnaire%20study%20of%20naturally%20short%20sleepers.pdf

  10. https://old.reddit.com/r/science/comments/3kj669/science_ama_series_im_yinghui_fu_i_study_the/cuy8cts

  11. https://www.newyorker.com/science/maria-konnikova/a-gene-makes-you-need-less-sleep

  12. ⁠, He, Ying Jones, Christopher R. Fujiki, Nobuhiro Xu, Ying Guo, Bin Holder, Jimmy L. Rossner, Moritz J. Nishino, Seiji Fu, Ying-Hui (2009):

    Sleep deprivation can impair human health and performance. Habitual total sleep time and homeostatic sleep response to sleep deprivation are quantitative traits in humans. Genetic loci for these traits have been identified in model organisms, but none of these potential animal models have a corresponding human genotype and phenotype.

    We have identified a mutation in a transcriptional repressor (hDEC2-P385R) that is associated with a human short sleep phenotype. Activity profiles and sleep recordings of transgenic mice carrying this mutation showed increased vigilance time and less sleep time than control mice in a zeitgeber time-dependent and sleep deprivation-dependent manner.

    These mice represent a model of human sleep homeostasis that provides an opportunity to probe the effect of sleep on human physical and mental health.

  13. ⁠, Pellegrino, Renata Kavakli, Ibrahim Halil Goel, Namni Cardinale, Christopher J. Dinges, David F. Kuna, Samuel T. Maislin, Greg Van Dongen, Hans P. A Tufik, Sergio Hogenesch, John B. Hakonarson, Hakon Pack, Allan I (2014):

    Study Objectives: Earlier work described a mutation in DEC2 also known as BHLHE41 (basic helix-loophelix family member e41) as causal in a family of short sleepers, who needed just 6 h sleep per night. We evaluated whether there were other variants of this gene in two well-phenotyped cohorts.

    Design: Sequencing of the BHLHE41 gene, electroencephalographic data, and delta power analysis and functional studies using cell-based luciferase.

    Results: We identified new variants of the BHLHE41 gene in two cohorts who had either acute sleep deprivation (n = 200) or chronic partial sleep deprivation (n = 217). One variant, Y362H, at another location in the same exon occurred in one twin in a dizygotic twin pair and was associated with reduced sleep duration, less recovery sleep following sleep deprivation, and fewer performance lapses during sleep deprivation than the homozygous twin. Both twins had almost identical amounts of non rapid eye movement (NREM) sleep. This variant reduced the ability of BHLHE41 to suppress CLOCK/​​​​BMAL1 and NPAS2/​​​​BMAL1 transactivation in vitro. Another variant in the same had no effect on sleep or response to sleep deprivation and no effect on CLOCK/​​​​BMAL1 transactivation. Random mutagenesis identified a number of other variants of BHLHE41 that affect its function.

    Conclusions: There are a number of mutations of BHLHE41. Mutations reduce total sleep while maintaining NREM sleep and provide resistance to the effects of sleep loss. Mutations that affect sleep also modify the normal inhibition of BHLHE41 of CLOCK/​​​​BMAL1 transactivation. Thus, clock mechanisms are likely involved in setting sleep length and the magnitude of sleep homeostasis.

    Citation: Pellegrino R, Kavakli IH, Goel N, Cardinale CJ, Dinges DF, Kuna ST, Maislin G, Van Dongen HP, Tufik S, Hogenesch JB, Hakonarson H, Pack AI. A novel BHLHE41 variant is associated with short sleep and resistance to sleep deprivation in humans. SLEEP 2014;37(8):1327-1336.

  14. https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?searchType=adhoc_search&type=rs&rs=rs4963956

  15. https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?searchType=adhoc_search&type=rs&rs=rs1480037

  16. https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?searchType=adhoc_search&type=rs&rs=rs4963955

  17. http://undark.org/article/the-death-of-a-study-national-childrens-study/

  18. http://www.cdc.gov/art/pdf/2013-report/art_2013_national_summary_report.pdf

  19. Pipeline

  20. https://science.sciencemag.org/content/337/6096/816.long

  21. ⁠, Jinek, Martin East, Alexandra Cheng, Aaron Lin, Steven Ma, Enbo Doudna, Jennifer (2013):

    Type II CRISPR immune systems in bacteria use a dual RNA-guided DNA endonuclease, Cas9, to cleave foreign DNA at specific sites. We show here that Cas9 assembles with hybrid guide RNAs in human cells and can induce the formation of double-strand DNA breaks (DSBs) at a site complementary to the guide RNA sequence in genomic DNA. This cleavage activity requires both Cas9 and the complementary binding of the guide RNA. Experiments using extracts from transfected cells show that RNA expression and/​​​​or assembly into Cas9 is the limiting factor for Cas9-mediated DNA cleavage. In addition, we find that extension of the RNA sequence at the 3’ end enhances DNA targeting activity in vivo. These results show that RNA-programmed genome editing is a facile strategy for introducing site-specific genetic changes in human cells.DOI:http:/​​​​/​​​​dx.doi.org/​​​​10.7554/​​​​eLife.00471.001.

  22. http://www.the-scientist.com/?articles.view/articleNo/41676/title/There-s-CRISPR-in-Your-Yogurt/

  23. http://www.independent.co.uk/news/science/crispr-gene-therapy-scientists-call-for-more-public-debate-around-breakthrough-technique-8927606.html

  24. https://www.nytimes.com/2014/07/17/science/a-call-to-fight-malaria-one-mosquito-at-a-time-by-altering-dna.html

  25. ⁠, Hwang, Woong Y. Fu, Yanfang Reyon, Deepak Maeder, Morgan L. Tsai, Shengdar Q. Sander, Jeffry D. Peterson, Randall T. Yeh, J-R Joanna Joung, J. Keith (2013):

    In bacteria, foreign nucleic acids are silenced by clustered, regularly interspaced, short palindromic repeats (CRISPR)–CRISPR-associated (Cas) systems. Bacterial type II CRISPR systems have been adapted to create guide RNAs that direct site-specific DNA cleavage by the Cas9 endonuclease in cultured cells. Here we show that the CRISPR-Cas system functions in vivo to induce targeted genetic modifications in zebrafish embryos with efficiencies similar to those obtained using zinc finger nucleases and transcription activator-like effector nucleases.

  26. https://www.nature.com/articles/522020a

  27. https://www.newscientist.com/article/2133095-boom-in-human-gene-editing-as-20-crispr-trials-gear-up/

  28. https://www.nature.com/articles/nature.2015.18448

  29. https://link.springer.com/article/10.1007/s11248-014-9832-x

  30. https://www.nature.com/articles/523013a

  31. 2017-midic.pdf

  32. https://academic.oup.com/jmcb/article/7/6/580/2459501?login=true

  33. ⁠, Wei Ni, Jun Qiao, Shengwei Hu, Xinxia Zhao, Misha Regouski, Min Yang, Irina A. Polejaeva, Chuangfu Chen (2014-08-10):

    The system has been adapted as an efficient genome editing tool in laboratory animals such as mice, rats, zebrafish and pigs. Here, we report that CRISPR/​​​​Cas9 mediated approach can efficiently induce monoallelic and biallelic gene knockout in goat primary fibroblasts. Four genes were disrupted simultaneously in goat fibroblasts by CRISPR/​​​​Cas9-mediated genome editing. The single-gene knockout fibroblasts were successfully used for somatic cell nuclear transfer (SCNT) and resulted in live-born goats harboring biallelic mutations. The CRISPR/​​​​Cas9 system represents a highly effective and facile platform for targeted editing of large animal genomes, which can be broadly applied to both biomedical and agricultural applications.

  34. https://www.nature.com/articles/srep13878

  35. ⁠, Liang, Puping Xu, Yanwen Zhang, Xiya Ding, Chenhui Huang, Rui Zhang, Zhen Lv, Jie Xie, Xiaowei Chen, Yuxi Li, Yujing Sun, Ying Bai, Yaofu Songyang, Zhou Ma, Wenbin Zhou, Canquan Huang, Junjiu (2015):

    Genome editing tools such as the clustered regularly interspaced short palindromic repeat (CRISPR)-associated system (Cas) have been widely used to modify genes in model systems including animal zygotes and human cells, and hold tremendous promise for both basic research and clinical applications. To date, a serious knowledge gap remains in our understanding of DNA repair mechanisms in human early embryos, and in the efficiency and potential off-target effects of using technologies such as CRISPR/​​​​Cas9 in human pre-implantation embryos. In this report, we used tripronuclear (3PN) zygotes to further investigate CRISPR/​​​​Cas9-mediated gene editing in human cells. We found that CRISPR/​​​​Cas9 could effectively cleave the endogenous β-globin gene (HBB). However, the efficiency of homologous recombination directed repair (HDR) of HBB was low and the edited embryos were mosaic. Off-target cleavage was also apparent in these 3PN zygotes as revealed by the T7E1 assay and whole-exome sequencing. Furthermore, the endogenous delta-globin gene (HBD), which is homologous to HBB, competed with exogenous donor oligos to act as the repair template, leading to untoward mutations. Our data also indicated that repair of the HBB locus in these embryos occurred preferentially through the non-crossover HDR pathway. Taken together, our work highlights the pressing need to further improve the fidelity and specificity of the CRISPR/​​​​Cas9 platform, a prerequisite for any clinical applications of CRSIPR/​​​​Cas9-mediated editing.

  36. https://www.nature.com/articles/520593a

  37. ⁠, Bakondi, Benjamin Lv, Wenjian Lu, Bin Jones, Melissa K. Tsai, Yuchun Kim, Kevin J. Levy, Rachelle Akhtar, Aslam Abbasi Breunig, Joshua J. Svendsen, Clive N. Wang, Shaomei (2016):

    Reliable genome editing via Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/​​​​Cas9 may provide a means to correct inherited diseases in patients. As proof of principle, we show that CRISPR/​​​​Cas9 can be used in vivo to selectively ablate the rhodopsin gene carrying the dominant S334ter mutation (Rho(S334)) in rats that model severe autosomal dominant retinitis pigmentosa. A single subretinal injection of guide RNA/​​​​Cas9 plasmid in combination with electroporation generated allele-specific disruption of Rho(S334), which prevented retinal degeneration and improved visual function.

  38. https://www.nature.com/articles/cr201757

  39. https://www.nature.com/articles/srep19969

  40. http://www.popsci.com/biotech-company-will-use-crispr-on-people-in-next-two-years

  41. ⁠, Long, Chengzu McAnally, John R. Shelton, John M. Mireault, Alex A. Bassel-Duby, Rhonda Olson, Eric N (2014):

    Duchenne muscular dystrophy (DMD) is an inherited X-linked disease caused by mutations in the gene encoding dystrophin, a protein required for muscle fiber integrity. DMD is characterized by progressive muscle weakness and a shortened life span, and there is no effective treatment. We used clustered regularly interspaced short palindromic repeat/​​​​Cas9 (CRISPR/​​​​Cas9)-mediated genome editing to correct the dystrophin gene (Dmd) mutation in the germ line of mdx mice, a model for DMD, and then monitored muscle structure and function. Genome editing produced genetically mosaic animals containing 2 to 100% correction of the Dmd gene. The degree of muscle phenotypic rescue in mosaic mice exceeded the efficiency of gene correction, likely reflecting an advantage of the corrected cells and their contribution to regenerating muscle. With the anticipated technological advances that will facilitate genome editing of postnatal somatic cells, this strategy may one day allow correction of disease-causing mutations in the muscle tissue of patients with DMD.

  42. ⁠, Yin, Hao Xue, Wen Chen, Sidi Bogorad, Roman L. Benedetti, Eric Grompe, Markus Koteliansky, Victor Sharp, Phillip A. Jacks, Tyler Anderson, Daniel G (2014):

    We demonstrate CRISPR-Cas9-mediated correction of a Fah mutation in hepatocytes in a mouse model of the human disease hereditary tyrosinemia. Delivery of components of the CRISPR-Cas9 system by hydrodynamic injection resulted in initial expression of the wild-type Fah protein in ~1/​​​​250 liver cells. Expansion of Fah-positive hepatocytes rescued the body weight loss phenotype. Our study indicates that CRISPR-Cas9-mediated genome editing is possible in adult animals and has potential for correction of human genetic diseases.

  43. 2016-yin.pdf: “Therapeutic genome editing by combined viral and non-viral delivery of CRISPR system components in vivo⁠, Hao Yin, Chun-Qing Song, Joseph R. Dorkin, Lihua J. Zhu, Yingxiang Li, Qiongqiong Wu, Angela Park, Junghoon Yang, Sneha Suresh, Aizhan Bizhanova, Ankit Gupta, Mehmet F. Bolukbasi, Stephen Walsh, Roman L. Bogorad, Guangping Gao, Zhiping Weng, Yizhou Dong, Victor Koteliansky, Scot A. Wolfe, Robert Langer, Wen Xue, Daniel G. Anderson

  44. https://www.sciencedirect.com/science/article/pii/S1934590913004621

  45. https://www.pennmedicine.org/news/news-releases/2016/november/scientists-use-crispr-for-first-time-to-correct-clotting-in-newborn-and-adult-mice

  46. 2017-yin.pdf: “In Vivo Excision of HIV-1 Provirus by saCas9 and Multiplex Single-Guide RNAs in Animal Models⁠, Chaoran Yin, Ting Zhang, Xiying Qu, Yonggang Zhang, Raj Putatunda, Xiao Xiao, Fang Li, Weidong Xiao, Huaqing Zhao, Shen Dai, Xuebin Qin, Xianming Mo, Won-Bin Young, Kamel Khalili, Wenhui Hu

  47. 2013-schwank.pdf: “Functional Repair of CFTR by CRISPR  /​ ​​ ​Cas9 in Intestinal Stem Cell Organoids of Cystic Fibrosis Patients”⁠, Gerald Schwank, Bon-Kyoung Koo, Valentina Sasselli, Johanna F. Dekkers, Inha Heo, Turan Demircan, Nobuo Sasaki, Sander Boymans, Edwin Cuppen, Cornelis K. van der Ent, Edward E. S. Nieuwenhuis, Jeffrey M. Beekman, Hans Clevers

  48. https://www.nature.com/articles/srep02510

  49. https://www.nature.com/articles/srep22555

  50. http://arep.med.harvard.edu/pdf/Yang_Science_2015.pdf

  51. 2017-niu.pdf: ⁠, Dong Niu, HongJiang Wei, Lin Lin, Haydy George, Tao Wang, IHsiu Lee, HongYe Zhao, Yong Wang, Yinan Kan, Ellen Shrock, Emal Lesha, Gang Wang, Yonglun Luo, Yubo Qing, Deling Jiao, Heng Zhao, Xiaoyang Zhou, Shouqi Wang, Hong Wei, Marc Gell, George M. Church, Luhan Yang (2017-08-10; genetics  /​ ​​ ​editing):

    Xenotransplantation is a promising strategy to alleviate the shortage of organs for human transplantation. In addition to the concern on pig-to-human immunological compatibility, the risk of cross-species transmission of porcine endogenous retroviruses (PERVs) has impeded the clinical application of this approach. Earlier, we demonstrated the feasibility of inactivating PERV activity in an immortalized pig cell line. Here, we confirmed that PERVs infect human cells, and observed the horizontal transfer of PERVs among human cells. Using CRISPR-Cas9, we inactivated all the PERVs in a porcine primary cell line and generated PERV-inactivated pigs via somatic cell nuclear transfer. Our study highlighted the value of PERV inactivation to prevent cross-species viral transmission and demonstrated the successful production of PERV-inactivated animals to address the safety concern in clinical xenotransplantation.

  52. ⁠, Cory J. Smith, Oscar Castanon, Khaled Said, Verena Volf, Parastoo Khoshakhlagh, Amanda Hornick, Raphael Ferreira, Chun-Ting Wu, Marc Güell, Shilpa Garg, Hannu Myllykallio, George M. Church (2019-03-15):

    To extend the frontier of genome editing and enable the radical redesign of mammalian genomes, we developed a set of dead-Cas9 base editor (dBEs) variants that allow editing at tens of thousands of loci per cell by overcoming the cell death associated with DNA double-strand breaks (DSBs) and single-strand breaks (SSBs). We used a set of gRNAs targeting repetitive elements—ranging in target copy number from about 31 to 124,000 per cell. dBEs enabled survival after large-scale base editing, allowing targeted mutations at up to ~13,200 and ~2610 loci in 293T and human induced pluripotent stem cells (hiPSCs), respectively, three orders of magnitude greater than previously recorded. These dBEs can overcome current on-target mutation and toxicity barriers that prevent cell survival after large-scale genome engineering.

    One Sentence Summary

    Base editing with reduced DNA nicking allows for the simultaneous editing of >10,000 loci in human cells.

  53. ⁠, Citorik, Robert J. Mimee, Mark Lu, Timothy K (2014):

    Current antibiotics tend to be broad spectrum, leading to indiscriminate killing of commensal bacteria and accelerated evolution of drug resistance. Here, we use CRISPR-Cas technology to create antimicrobials whose spectrum of activity is chosen by design. RNA-guided nucleases (RGNs) targeting specific DNA sequences are delivered efficiently to microbial populations using bacteriophage or bacteria carrying plasmids transmissible by conjugation. The DNA targets of RGNs can be undesirable genes or polymorphisms, including antibiotic resistance and virulence determinants in carbapenem-resistant Enterobacteriaceae and enterohemorrhagic Escherichia coli. Delivery of RGNs significantly improves survival in a Galleria mellonella infection model. We also show that RGNs enable modulation of complex bacterial populations by selective knockdown of targeted strains based on genetic signatures. RGNs constitute a class of highly discriminatory, customizable antimicrobials that enact selective pressure at the DNA level to reduce the prevalence of undesired genes, minimize off-target effects and enable programmable remodeling of ⁠.

  54. https://www.sciencedirect.com/science/article/pii/S0092867413004674

  55. http://library.ioz.ac.cn/bitstream/000000/10340/1/Simultaneous%20generation%20and%20germline%20transmiss.pdf

  56. https://www.nature.com/articles/nature.2015.17462

  57. https://www.nature.com/articles/srep05400

  58. ⁠, Mali, Prashant Yang, Luhan Esvelt, Kevin M. Aach, John Guell, Marc DiCarlo, James E. Norville, Julie E. Church, George M (2013):

    Bacteria and archaea have evolved adaptive immune defenses, termed clustered regularly interspaced short palindromic repeats (CRISPR)/​​​​CRISPR-associated (Cas) systems, that use short RNA to direct degradation of foreign nucleic acids. Here, we engineer the type II bacterial CRISPR system to function with custom guide RNA (gRNA) in human cells. For the endogenous AAVS1 locus, we obtained targeting rates of 10 to 25% in 293T cells, 13 to 8% in K562 cells, and 2 to 4% in induced pluripotent stem cells. We show that this process relies on CRISPR components; is sequence-specific; and, upon simultaneous introduction of multiple gRNAs, can effect multiplex editing of target loci. We also compute a genome-wide resource of ~190 K unique gRNAs targeting ~40.5% of human exons. Our results establish an RNA-guided editing tool for facile, robust, and multiplexable human genome engineering.

  59. ⁠, James E. DiCarlo, Alejandro Chavez, Sven L. Dietz, Kevin M. Esvelt, George M. Church (2015-03-19):

    Inheritance-biasing “gene drives” may be capable of spreading genomic alterations made in laboratory organisms through wild populations. We previously considered the potential for RNA-guided gene drives based on the versatile CRISPR/​​​​Cas9 genome editing system to serve as a general method of altering populations1. Here we report molecularly contained gene drive constructs in the yeast Saccharomyces cerevisiae that are typically copied at rates above 99% when mated to wild yeast. We successfully targeted both non-essential and essential genes, showed that the inheritance of an unrelated “cargo” gene could be biased by an adjacent drive, and constructed a drive capable of overwriting and reversing changes made by a previous drive. Our results demonstrate that RNA-guided gene drives are capable of efficiently biasing inheritance when mated to wild-type organisms over successive generations.

  60. ⁠, Gantz, Valentino M. Bier, Ethan (2015):

    An organism with a single recessive loss-of-function allele will typically have a wild-type phenotype, whereas individuals homozygous for two copies of the allele will display a mutant phenotype. We have developed a method called the mutagenic chain reaction (MCR), which is based on the CRISPR/​​​​Cas9 genome-editing system for generating autocatalytic mutations, to produce homozygous loss-of-function mutations. In ⁠, we found that MCR mutations efficiently spread from their chromosome of origin to the homologous chromosome, thereby converting heterozygous mutations to in the vast majority of somatic and germline cells. MCR technology should have broad applications in diverse organisms.

  61. https://www.pnas.org/content/112/49/E6736.full

  62. https://www.nature.com/articles/nbt.3439

  63. http://www.popsci.com/woolly-mammoth-dna-brought-life-elephant-cells

  64. 2016-whitworth.pdf: “Gene-edited pigs are protected from porcine reproductive and respiratory syndrome virus”⁠, Kristin M. Whitworth, Raymond R. R Rowland, Catherine L. Ewen, Benjamin R. Trible, Maureen A. Kerrigan, Ada G. Cino-Ozuna, Melissa S. Samuel, Jonathan E. Lightner, David G. McLaren, Alan J. Mileham, Kevin D. Wells, Randall S. Prather

  65. https://www.pnas.org/content/110/41/16526.full

  66. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1144-4

  67. https://www.nature.com/articles/cr2015130

  68. 2016-liu-2.pdf

  69. https://www.nature.com/articles/nature.2016.19754

  70. https://www.nature.com/news/welcome-to-the-crispr-zoo-1.19537

  71. http://www.pbs.org/wgbh/nova/next/nature/crispr-grapes/

  72. ⁠, Yanan Yue, Yinan Kan, Weihong Xu, Hong-Ye Zhao, Yixuan Zhou, Xiaobin Song, Jiajia Wu, Juan Xiong, Dharmendra Goswami, Meng Yang, Lydia Lamriben, Mengyuan Xu, Qi Zhang, Yu Luo, Jianxiong Guo, Shenyi Mao, Deling Jiao, Tien Dat Nguyen, Zhuo Li, Jacob V. Layer, Malin Li, Violette Paragas, Michele E. Youd, Zhongquan Sun, Yuan Ding, Weilin Wang, Hongwei Dou, Lingling Song, Xueqiong Wang, Lei Le, Xin Fang, Haydy George, Ranjith Anand, Shi Yun Wang, William F. Westlin, Marc Guell, James Markmann, Wenning Qin, Yangbin Gao, Hongjiang Wei, George M. Church, Luhan Yang (2019-12-19):

    Xenotransplantation, specifically the use of porcine organs for human transplantation, has long been sought after as an alternative for patients suffering from organ failure. However, clinical application of this approach has been impeded by two main hurdles: 1) risk of transmission of porcine endogenous retroviruses (PERVs) and 2) molecular incompatibilities between donor pigs and humans which culminate in rejection of the graft. We previously demonstrated that all 25 copies of the PERV elements in the pig genome could be inactivated and live pigs successfully generated. In this study, we improved the scale of porcine germline editing from targeting a single repetitive locus with CRISPR to engineering 18 different loci using multiple genome engineering methods. we engineered the pig genome at 42 alleles using CRISPR-Cas9 and transposon and produced PERVKO·3KO·9TG pigs which carry PERV inactivation, xeno-antigen KO and 9 effective human transgenes.. The engineered pigs exhibit normal physiology, fertility, and germline transmission of the edited alleles. In vitro assays demonstrated that these pigs gain significant resistance to human humoral and cell mediated damage, and coagulation dysregulations, similar to that of allotransplantation. Successful creation of PERVKO·3KO·9TG pigs represents a significant step forward towards safe and effective porcine xenotransplantation, which also represents a synthetic biology accomplishment of engineering novel functions in a living organism.

    One Sentence Summary

    Extensive genome engineering is applied to modify pigs for safe and immune compatible organs for human transplantation

  73. ⁠, Kelly Servick (Science) (2019-12-19):

    If any swine is fit to be an organ donor for people, then the dozens of pigs snuffling around Qihan Bio’s facility in Hangzhou, China, may be the best candidates so far. The Chinese company and its U.S. collaborators reported today that they have used the genome editor CRISPR to create the most extensively genetically engineered pigs to date—animals whose tissues, the researchers say, finally combine all the features necessary for a safe and successful transplant into humans. “This is the first prototype”, says Luhan Yang, a geneticist at Qihan Bio. In a preprint published today on bioRxiv, Qihan researchers and collaborators, including Cambridge, Massachusetts-based eGenesis—which Yang co-founded with Harvard University geneticist George Church—described the new generation of animals and various tests on their cells; the researchers have already begun to transplant the pigs’ organs into nonhuman primates, a key step toward human trials.

    …In the new study, the team for the first time combined these PERV “knockouts” with a suite of other changes to prevent immune rejection, for a record-setting 13 modified genes. In pig ear cells, they removed three genes coding for enzymes that help produce molecules on pig cells that provoke an immune response. They also inserted six genes that inhibit various aspects of the human immune response and three more that help regulate blood coagulation. The researchers then put the DNA-containing nuclei of these edited cells into eggs from pig ovaries collected at a slaughterhouse. These eggs developed into embryos that were implanted into surrogate mothers. Cells from the resulting piglets got another round of edits to remove the PERV sequences, after which their DNA went into another set of egg cells to create a new generation of pigs with all the desired edits. (In future, Yang says, the team will try to make all the modifications in a single generation.)

    The resulting pigs appeared healthy and fertile with functioning organs, the team reports today. And initial tests of their cells in lab dishes suggest their organs will be much less prone to immune rejection than those of unmodified pigs: The tendency of the pig cells to bind to certain human antibodies was reduced by 90%, and the modified cells better survived interactions with human immune cells. But a key test is still to come: Yang says her team has begun to transplant organs from the highly edited pigs into monkeys to gauge their safety and longevity.

    The combination of edits described in the new paper is “a technical feat”, says Marilia Cascalho, a transplant immunologist at the University of Michigan in Ann Arbor. “Whether it offers an advantage [over other engineered pig organs]… the jury is out on that”, she says…Yang says that Qihan plans to remain “laser-focused” on preclinical studies in 2020, but expects to be testing pig organs in humans within 5 years. Many in the field now feel an inevitable momentum around xenotransplantation: “There is so much need for organs”, Cascalho says. “I think it’s going to be a reality.”

  74. ⁠, Cornelius Rietveld (2015-01-08):

    This document provides further details about materials, methods and additional analyses to accompany the research report “Proxy-Phenotype Method Identifies Common Genetic Variants Associated with Cognitive Performance.”

  75. 2016-sekar.pdf: “Schizophrenia risk from complex variation of complement component 4”⁠, Aswin Sekar, Allison R. Bialas, Heather de Rivera, Avery Davis, Timothy R. Hammond, Nolan Kamitaki, Katherine Tooley, Jessy Presumey, Matthew Baum, Vanessa Van Doren, Giulio Genovese, Samuel A. Rose, Robert E. Handsaker, Mark J. Daly, Michael C. Carroll, Beth Stevens, Steven A. McCarroll

  76. https://www.nature.com/articles/nature13835

  77. https://journals.sagepub.com/doi/full/10.1177/2332858415599972

  78. 2015-zhu.pdf: “Educational attainment-related loci identified by GWAS are associated with select personality traits and mathematics and language abilities”⁠, Bi Zhu, Chuansheng Chen, Robert K. Moyzis, Qi Dong, Chongde Lin

  79. 2015-piffer.pdf: “A review of intelligence GWAS hits: Their relationship to country IQ and the issue of spatial autocorrelation”⁠, Davide Piffer

  80. 2010-winkler.pdf: “Admixture Mapping Comes of Age*”⁠, Cheryl A. Winkler, George W. Nelson, Michael W. Smith

  81. ⁠, Christopher S. Carlson, Tara C. Matise, Kari E. North, Christopher A. Haiman, Megan D. Fesinmeyer, Steven Buyske, Fredrick R. Schumacher, Ulrike Peters, Nora Franceschini, Marylyn D. Ritchie, David J. Duggan, Kylee L. Spencer, Logan Dumitrescu, Charles B. Eaton, Fridtjof Thomas, Alicia Young, Cara Carty, Gerardo Heiss, Loic Le Marchand, Dana C. Crawford, Lucia A. Hindorff, Charles L. Kooperberg (PAGE Consortium) (2013-08-08):

    The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS.

    In the present analysis of five common diseases and traits, including ⁠, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings.

    We demonstrate that, in all populations analyzed, a statistically-significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a effect in the opposite direction, after adjustment for multiple testing. However, 25% of tagSNPs identified in EA GWAS have statistically-significantly different in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes statistically-significantly to dilute effect sizes in this population.

    Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging.

    Author Summary: The number of known associations between human diseases and common genetic variants has grown dramatically in the past decade, most being identified in large-scale genetic studies of people of Western European origin. But because the frequencies of genetic variants can differ substantially between continental populations, it’s important to assess how well these associations can be extended to populations with different continental ancestry. Are the correlations between genetic variants, disease endpoints, and risk factors consistent enough for genetic risk models to be reliably applied across different ancestries? Here we describe a systematic analysis of disease outcome and risk-factor-associated variants (tagSNPs) identified in European populations, in which we test whether the effect size of a tagSNP is consistent across six populations with statistically-significant non-European ancestry. We demonstrate that although nearly all such tagSNPs have effects in the same direction across all ancestries (ie., variants associated with higher risk in Europeans will also be associated with higher risk in other populations), roughly a quarter of the variants tested have statistically-significantly different magnitude of effect (usually lower) in at least one non-European population. We therefore advise caution in the use of tagSNP-based genetic disease risk models in populations that have a different genetic ancestry from the population in which original associations were first made. We then show that this differential strength of association can be attributed to population-dependent variations in the correlation between tagSNPs and the variant that actually determines risk—the so-called functional variant. Risk models based on functional variants are therefore likely to be more robust than tagSNP-based models.

  82. ⁠, Kevin M. Waters, Daniel O. Stram, Mohamed T. Hassanein, Loïc Le Marchand, Lynne R. Wilkens, Gertraud Maskarinec, Kristine R. Monroe, Laurence N. Kolonel, David Altshuler, Brian E. Henderson, Christopher A. Haiman (2010-07-21):

    It has been recently hypothesized that many of the signals detected in genome-wide association studies (GWAS) to T2D and other diseases, despite being observed to common variants, might in fact result from causal mutations that are rare. One prediction of this hypothesis is that the allelic associations should be population-specific, as the causal mutations arose after the migrations that established different populations around the world. We selected 19 common variants found to be reproducibly associated to T2D risk in European populations and studied them in a large multiethnic study (6,142 cases and 7,403 controls) among men and women from 5 racial/​​​​ethnic groups (European Americans, African Americans, Latinos, Japanese Americans, and Native Hawaiians). In analysis pooled across ethnic groups, the allelic associations were in the same direction as the original report for all 19 variants, and 14 of the 19 were statistically-significantly associated with risk. In summing the number of risk alleles for each individual, the per-allele associations were highly statistically-significant (p < 10−4) and similar in all populations (odds ratios 1.09–1.12) except in Japanese Americans the estimated effect per allele was larger than in the other populations (1.20; p het = 3.8×10−4). We did not observe ethnic differences in the distribution of risk that would explain the increased prevalence of type 2 diabetes in these groups as compared to European Americans. The consistency of allelic associations in diverse racial/​​​​ethnic groups is not predicted under the hypothesis of Goldstein regarding “synthetic associations” of rare mutations in T2D.

    Author Summary:

    Single rare causal alleles and/​​​​or collections of multiple rare alleles have been suggested to create “synthetic associations” with common variants in genome-wide association studies (GWAS). This model predicts that associations with common variants will not be consistent across populations. In this study, we examined 19 T2D variants for association with T2D risk in 6,142 cases and 7,403 controls from five racial/​​​​ethnic populations in the Multiethnic Cohort (European Americans, African Americans, Latinos, Japanese Americans, and Native Hawaiians). In racial/​​​​ethnic pooled analysis, all 19 variants were associated with T2D risk in the same direction as previous reports in Europeans, and the sum total of risk variants was statistically-significantly associated with T2D risk in each racial/​​​​ethnic group. The consistent associations across populations do not support the Goldstein hypothesis that rare causal alleles underlie GWAS signals. We also did not find evidence that these markers underlie racial/​​​​ethnic disparities in T2D prevalence. Large-scale GWAS and sequencing studies in these populations are necessary in order to both improve the current set of markers at these risk loci and identify new risk variants for T2D that may be difficult, or impossible, to detect in European populations.

  83. ⁠, Torgerson, Dara G. Ampleford, Elizabeth J. Chiu, Grace Y. Gauderman, W. James Gignoux, Christopher R. Graves, Penelope E. Himes, Blanca E. Levin, Albert M. Mathias, Rasika A. Hancock, Dana B. Baurley, James W. Eng, Celeste Stern, Debra A. Celedón, Juan C. Rafaels, Nicholas Capurso, Daniel Conti, David V. Roth, Lindsey A. Soto-Quiros, Manuel Togias, Alkis Li, Xingnan Myers, Rachel A. Romieu, Isabelle Van Den Berg, David J. Hu, Donglei Hansel, Nadia N. Hernandez, Ryan D. Israel, Elliott Salam, Muhammad T. Galanter, Joshua Avila, Pedro C. Avila, Lydiana Rodriquez-Santana, Jose R. Chapela, Rocio Rodriguez-Cintron, William Diette, Gregory B. Adkinson, N. Franklin Abel, Rebekah A. Ross, Kevin D. Shi, Min Faruque, Mezbah U. Dunston, Georgia M. Watson, Harold R. Mantese, Vito J. Ezurum, Serpil C. Liang, Liming Ruczinski, Ingo Ford, Jean G. Huntsman, Scott Chung, Kian Fan Vora, Hita Li, Xia Calhoun, William J. Castro, Mario Sienra-Monge, Juan J. del Rio-Navarro, Blanca Deichmann, Klaus A. Heinzmann, Andrea Wenzel, Sally E. Busse, William W. Gern, James E. Lemanske, Robert F. Beaty, Terri H. Bleecker, Eugene R. Raby, Benjamin A. Meyers, Deborah A. London, Stephanie J. Gilliland, Frank D. Burchard, Esteban G. Martinez, Fernando D. Weiss, Scott T. Williams, L. Keoki Barnes, Kathleen C. Ober, Carole Nicolae, Dan L (2011):

    Asthma is a common disease with a complex risk architecture including both genetic and environmental factors. We performed a meta-analysis of North American genome-wide association studies of asthma in 5,416 individuals with asthma (cases) including individuals of European American, African American or African Caribbean, and Latino ancestry, with replication in an additional 12,649 individuals from the same ethnic groups. We identified five susceptibility loci. Four were at previously reported loci on 17q21, near IL1RL1, TSLP and IL33, but we report for the first time, to our knowledge, that these loci are associated with asthma risk in three ethnic groups. In addition, we identified a new asthma susceptibility locus at PYHIN1, with the association being specific to individuals of African descent (p = 3.9 × 10−9). These results suggest that some asthma susceptibility loci are robust to differences in ancestry when sufficiently large samples sizes are investigated, and that ancestry-specific associations also contribute to the complex genetic architecture of asthma.

  84. ⁠, Lingjun Zuo, Clarence K. Zhang, Fei Wang, Chiang-Shan R. Li, Hongyu Zhao, Lingeng Lu, Xiang-Yang Zhang, Lin Lu, Heping Zhang, Fengyu Zhang, John H. Krystal, Xingguang Luo (2011-10-01):

    Several genome-wide association studies (GWASs) reported tens of risk genes for alcohol dependence, but most of them have not been replicated or confirmed by functional studies. The present study used a GWAS to search for novel, functional and replicable risk gene regions for alcohol dependence. Associations of all top-ranked SNPs identified in a discovery sample of 681 African-American (AA) cases with alcohol dependence and 508 AA controls were retested in a primary replication sample of 1,409 European-American (EA) cases and 1,518 EA controls. The replicable associations were then subjected to secondary replication in a sample of 6,438 Australian family subjects. A functional expression quantitative trait locus (eQTL) analysis of these replicable risk SNPs was followed-up in order to explore their cis-acting regulatory effects on gene expression. We found that within a 90 Mb region around PHF3-PTP4A1 locus in AAs, a linkage disequilibrium (LD) block in PHF3-PTP4A1 formed the only peak associated with alcohol dependence at p < 10−4. Within this block, 30 SNPs associated with alcohol dependence in AAs (1.6×10−5p ≤ 0.050) were replicated in EAs (1.3×10−3p ≤ 0.038), and 18 of them were also replicated in Australians (1.8×10−3p ≤ 0.048). Most of these risk SNPs had strong cis-acting regulatory effects on PHF3-PTP4A1 expression across three HapMap samples. The distributions of −log(p) values for association and functional signals throughout this LD block were highly consistent across AAs, EAs, Australians and three HapMap samples. We conclude that the PHF3-PTP4A1 region appears to harbor a causal locus for alcohol dependence, and proteins encoded by PHF3 and/​​​​or PTP4A1 might play a functional role in the disorder.

  85. http://circgenetics.ahajournals.org/content/early/2011/08/10/CIRCGENETICS.111.959577.full.pdf

  86. ⁠, Nyholt, Dale R. Low, Siew-Kee Anderson, Carl A. Painter, Jodie N. Uno, Satoko Morris, Andrew P. MacGregor, Stuart Gordon, Scott D. Henders, Anjali K. Martin, Nicholas G. Attia, John Holliday, Elizabeth G. McEvoy, Mark Scott, Rodney J. Kennedy, Stephen H. Treloar, Susan A. Missmer, Stacey A. Adachi, Sosuke Tanaka, Kenichi Nakamura, Yusuke Zondervan, Krina T. Zembutsu, Hitoshi Montgomery, Grant W (2012):

    We conducted a genome-wide association of 4,604 endometriosis cases and 9,393 controls of Japanese and European ancestry. We show that rs12700667 on chromosome 7p15.2, previously found to associate with disease in Europeans, replicates in Japanese (p = 3.6 × 10−3), and we confirm association of rs7521902 at 1p36.12 near WNT4. In addition, we establish an association of rs13394619 in GREB1 at 2p25.1 with endometriosis and identify a newly associated locus at 12q22 near VEZT (rs10859871). Excluding cases of European ancestry of minimal or unknown severity, we identified additional previously unknown loci at 2p14 (rs4141819), 6p22.3 (rs7739264) and 9p21.3 (rs1537377). All seven effects were replicated in an independent cohort and associated at P <5 × 10−8 in a combined analysis. Finally, we found a significant overlap in polygenic risk for endometriosis between the genome-wide association cohorts of European and Japanese descent (p = 8.8 × 10−11), indicating that many weakly associated SNPs represent true endometriosis risk loci and that risk prediction and future targeted disease therapy may be transferred across these populations.

  87. ⁠, Fesinmeyer, Megan D. North, Kari E. Ritchie, Marylyn D. Lim, Unhee Franceschini, Nora Wilkens, Lynne R. Gross, Myron D. Bůžková, Petra Glenn, Kimberly Quibrera, P. Miguel Fernández-Rhodes, Lindsay Li, Qiong Fowke, Jay H. Li, Rongling Carlson, Christopher S. Prentice, Ross L. Kuller, Lewis H. Manson, Joann E. Matise, Tara C. Cole, Shelley A. Chen, Christina T. L Howard, Barbara V. Kolonel, Laurence N. Henderson, Brian E. Monroe, Kristine R. Crawford, Dana C. Hindorff, Lucia A. Buyske, Steven Haiman, Christopher A. Le Marchand, Loic Peters, Ulrike (2013):

    Objective: Several genome-wide association studies (GWAS) have demonstrated that common genetic variants contribute to obesity. However, studies of this complex trait have focused on ancestrally European populations, despite the high prevalence of obesity in some minority groups.

    Design and Methods: As part of the “Population Architecture using Genomics and Epidemiology (PAGE)” Consortium, we investigated the association between 13 GWAS-identified single-nucleotide polymorphisms (SNPs) and BMI and obesity in 69,775 subjects, including 6,149 American Indians, 15,415 African-Americans, 2,438 East Asians, 7,346 Hispanics, 604 Pacific Islanders, and 37,823 European Americans. For the BMI-increasing allele of each SNP, we calculated β coefficients using linear regression (for BMI) and risk estimates using logistic regression (for obesity defined as BMI ≥ 30) followed by fixed-effects meta-analysis to combine results across PAGE sites. Analyses stratified by racial/​​​​ethnic group assumed an additive genetic model and were adjusted for age, sex, and current smoking. We defined “replicating SNPs” (in European Americans) and “generalizing SNPs” (in other racial/​​​​ethnic groups) as those associated with an allele frequency-specific increase in BMI.

    Results: By this definition, we replicated 9⁄13 SNP associations (5 out of 8 loci) in European Americans. We also generalized 8⁄13 SNP associations (5⁄8 loci) in East Asians, 7⁄13 (5⁄8 loci) in African Americans, 6⁄13 (4⁄8 loci) in Hispanics, 5⁄8 in Pacific Islanders (5⁄8 loci), and 5⁄9 (4⁄8 loci) in American Indians.

    Conclusion: Linkage disequilibrium patterns suggest that tagSNPs selected for European Americans may not adequately tag causal variants in other ancestry groups. Accordingly, fine-mapping in large samples is needed to comprehensively explore these loci in diverse populations.

  88. https://www.sciencedirect.com/science/article/pii/S000292971300387X

  89. ⁠, Monda, Keri L. Chen, Gary K. Taylor, Kira C. Palmer, Cameron Edwards, Todd L. Lange, Leslie A. Ng, Maggie C. Y Adeyemo, Adebowale A. Allison, Matthew A. Bielak, Lawrence F. Chen, Guanjie Graff, Mariaelisa Irvin, Marguerite R. Rhie, Suhn K. Li, Guo Liu, Yongmei Liu, Youfang Lu, Yingchang Nalls, Michael A. Sun, Yan V. Wojczynski, Mary K. Yanek, Lisa R. Aldrich, Melinda C. Ademola, Adeyinka Amos, Christopher I. Bandera, Elisa V. Bock, Cathryn H. Britton, Angela Broeckel, Ulrich Cai, Quiyin Caporaso, Neil E. Carlson, Chris S. Carpten, John Casey, Graham Chen, Wei-Min Chen, Fang Chen, Yii-Der I. Chiang, Charleston W. K Coetzee, Gerhard A. Demerath, Ellen Deming-Halverson, Sandra L. Driver, Ryan W. Dubbert, Patricia Feitosa, Mary F. Feng, Ye Freedman, Barry I. Gillanders, Elizabeth M. Gottesman, Omri Guo, Xiuqing Haritunians, Talin Harris, Tamara Harris, Curtis C. Hennis, Anselm J. M Hernandez, Dena G. McNeill, Lorna H. Howard, Timothy D. Howard, Barbara V. Howard, Virginia J. Johnson, Karen C. Kang, Sun J. Keating, Brendan J. Kolb, Suzanne Kuller, Lewis H. Kutlar, Abdullah Langefeld, Carl D. Lettre, Guillaume Lohman, Kurt Lotay, Vaneet Lyon, Helen Manson, Joann E. Maixner, William Meng, Yan A. Monroe, Kristine R. Morhason-Bello, Imran Murphy, Adam B. Mychaleckyj, Josyf C. Nadukuru, Rajiv Nathanson, Katherine L. Nayak, Uma N'diaye, Amidou Nemesure, Barbara Wu, Suh-Yuh Leske, M. Cristina Neslund-Dudas, Christine Neuhouser, Marian Nyante, Sarah Ochs-Balcom, Heather Ogunniyi, Adesola Ogundiran, Temidayo O. Ojengbede, Oladosu Olopade, Olufunmilayo I. Palmer, Julie R. Ruiz-Narvaez, Edward A. Palmer, Nicholette D. Press, Michael F. Rampersaud, Evandine Rasmussen-Torvik, Laura J. Rodriguez-Gil, Jorge L. Salako, Babatunde Schadt, Eric E. Schwartz, Ann G. Shriner, Daniel A. Siscovick, David Smith, Shad B. Wassertheil-Smoller, Sylvia Speliotes, Elizabeth K. Spitz, Margaret R. Sucheston, Lara Taylor, Herman Tayo, Bamidele O. Tucker, Margaret A. Van Den Berg, David J. Edwards, Digna R. Velez Wang, Zhaoming Wiencke, John K. Winkler, Thomas W. Witte, John S. Wrensch, Margaret Wu, Xifeng Yang, James J. Levin, Albert M. Young, Taylor R. Zakai, Neil A. Cushman, Mary Zanetti, Krista A. Zhao, Jing Hua Zhao, Wei Zheng, Yonglan Zhou, Jie Ziegler, Regina G. Zmuda, Joseph M. Fernandes, Jyotika K. Gilkeson, Gary S. Kamen, Diane L. Hunt, Kelly J. Spruill, Ida J. Ambrosone, Christine B. Ambs, Stefan Arnett, Donna K. Atwood, Larry Becker, Diane M. Berndt, Sonja I. Bernstein, Leslie Blot, William J. Borecki, Ingrid B. Bottinger, Erwin P. Bowden, Donald W. Burke, Gregory Chanock, Stephen J. Cooper, Richard S. Ding, Jingzhong Duggan, David Evans, Michele K. Fox, Caroline Garvey, W. Timothy Bradfield, Jonathan P. Hakonarson, Hakon Grant, Struan F. A Hsing, Ann Chu, Lisa Hu, Jennifer J. Huo, Dezheng Ingles, Sue A. John, Esther M. Jordan, Joanne M. Kabagambe, Edmond K. Kardia, Sharon L. R Kittles, Rick A. Goodman, Phyllis J. Klein, Eric A. Kolonel, Laurence N. Le Marchand, Loic Liu, Simin McKnight, Barbara Millikan, Robert C. Mosley, Thomas H. Padhukasahasram, Badri Williams, L. Keoki Patel, Sanjay R. Peters, Ulrike Pettaway, Curtis A. Peyser, Patricia A. Psaty, Bruce M. Redline, Susan Rotimi, Charles N. Rybicki, Benjamin A. Sale, Michèle M. Schreiner, Pamela J. Signorello, Lisa B. Singleton, Andrew B. Stanford, Janet L. Strom, Sara S. Thun, Michael J. Vitolins, Mara Zheng, Wei Moore, Jason H. Williams, Scott M. Ketkar, Shamika Zhu, Xiaofeng Zonderman, Alan B. Kooperberg, Charles Papanicolaou, George J. Henderson, Brian E. Reiner, Alex P. Hirschhorn, Joel N. Loos, Ruth J. F North, Kari E. Haiman, Christopher A (2013):

    Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most statistically-significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, p = 3.4 × 10−11) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, p = 1.2 × 10−10). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, p = 6.9 × 10−8). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial p = 9.7 × 10−7), five of which reached genome-wide statistical-significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.

  90. http://iovs.arvojournals.org/article.aspx?articleid=2265959

  91. ⁠, Mahajan, Anubha Go, Min Jin Zhang, Weihua Below, Jennifer E. Gaulton, Kyle J. Ferreira, Teresa Horikoshi, Momoko Johnson, Andrew D. Ng, Maggie C. Y Prokopenko, Inga Saleheen, Danish Wang, Xu Zeggini, Eleftheria Abecasis, Goncalo R. Adair, Linda S. Almgren, Peter Atalay, Mustafa Aung, Tin Baldassarre, Damiano Balkau, Beverley Bao, Yuqian Barnett, Anthony H. Barroso, Ines Basit, Abdul Been, Latonya F. Beilby, John Bell, Graeme I. Benediktsson, Rafn Bergman, Richard N. Boehm, Bernhard O. Boerwinkle, Eric Bonnycastle, Lori L. Burtt, Noël Cai, Qiuyin Campbell, Harry Carey, Jason Cauchi, Stephane Caulfield, Mark Chan, Juliana C. N Chang, Li-Ching Chang, Tien-Jyun Chang, Yi-Cheng Charpentier, Guillaume Chen, Chien-Hsiun Chen, Han Chen, Yuan-Tsong Chia, Kee-Seng Chidambaram, Manickam Chines, Peter S. Cho, Nam H. Cho, Young Min Chuang, Lee-Ming Collins, Francis S. Cornelis, Marylin C. Couper, David J. Crenshaw, Andrew T. van Dam, Rob M. Danesh, John Das, Debashish de Faire, Ulf Dedoussis, George Deloukas, Panos Dimas, Antigone S. Dina, Christian Doney, Alex S. Donnelly, Peter J. Dorkhan, Mozhgan van Duijn, Cornelia Dupuis, Josée Edkins, Sarah Elliott, Paul Emilsson, Valur Erbel, Raimund Eriksson, Johan G. Escobedo, Jorge Esko, Tonu Eury, Elodie Florez, Jose C. Fontanillas, Pierre Forouhi, Nita G. Forsen, Tom Fox, Caroline Fraser, Ross M. Frayling, Timothy M. Froguel, Philippe Frossard, Philippe Gao, Yutang Gertow, Karl Gieger, Christian Gigante, Bruna Grallert, Harald Grant, George B. Grrop, Leif C. Groves, Chrisropher J. Grundberg, Elin Guiducci, Candace Hamsten, Anders Han, Bok-Ghee Hara, Kazuo Hassanali, Neelam Hattersley, Andrew T. Hayward, Caroline Hedman, Asa K. Herder, Christian Hofman, Albert Holmen, Oddgeir L. Hovingh, Kees Hreidarsson, Astradur B. Hu, Cheng Hu, Frank B. Hui, Jennie Humphries, Steve E. Hunt, Sarah E. Hunter, David J. Hveem, Kristian Hydrie, Zafar I. Ikegami, Hiroshi Illig, Thomas Ingelsson, Erik Islam, Muhammed Isomaa, Bo Jackson, Anne U. Jafar, Tazeen James, Alan Jia, Weiping Jöckel, Karl-Heinz Jonsson, Anna Jowett, Jeremy B. M Kadowaki, Takashi Kang, Hyun Min Kanoni, Stavroula Kao, Wen Hong L. Kathiresan, Sekar Kato, Norihiro Katulanda, Prasad Keinanen-Kiukaanniemi, Kirkka M. Kelly, Ann M. Khan, Hassan Khaw, Kay-Tee Khor, Chiea-Chuen Kim, Hyung-Lae Kim, Sangsoo Kim, Young Jin Kinnunen, Leena Klopp, Norman Kong, Augustine Korpi-Hyövälti, Eeva Kowlessur, Sudhir Kraft, Peter Kravic, Jasmina Kristensen, Malene M. Krithika, S. Kumar, Ashish Kumate, Jesus Kuusisto, Johanna Kwak, Soo Heon Laakso, Markku Lagou, Vasiliki Lakka, Timo A. Langenberg, Claudia Langford, Cordelia Lawrence, Robert Leander, Karin Lee, Jen-Mai Lee, Nanette R. Li, Man Li, Xinzhong Li, Yun Liang, Junbin Liju, Samuel Lim, Wei-Yen Lind, Lars Lindgren, Cecilia M. Lindholm, Eero Liu, Ching-Ti Liu, Jian Jun Lobbens, Stéphane Long, Jirong Loos, Ruth J. F Lu, Wei Luan, Jian'an Lyssenko, Valeriya Ma, Ronald C. W Maeda, Shiro Mägi, Reedik Männisto, Satu Matthews, David R. Meigs, James B. Melander, Olle Metspalu, Andres Meyer, Julia Mirza, Ghazala Mihailov, Evelin Moebus, Susanne Mohan, Viswanathan Mohlke, Karen L. Morris, Andrew D. Mühleisen, Thomas W. Müller-Nurasyid, Martina Musk, Bill Nakamura, Jiro Nakashima, Eitaro Navarro, Pau Ng, Peng-Keat Nica, Alexandra C. Nilsson, Peter M. Njølstad, Inger Nöthen, Markus M. Ohnaka, Keizo Ong, Twee Hee Owen, Katharine R. Palmer, Colin N. A Pankow, James S. Park, Kyong Soo Parkin, Melissa Pechlivanis, Sonali Pedersen, Nancy L. Peltonen, Leena Perry, John R. B Peters, Annette Pinidiyapathirage, Janini M. Platou, Carl G. Potter, Simon Price, Jackie F. Qi, Lu Radha, Venkatesan Rallidis, Loukianos Rasheed, Asif Rathman, Wolfgang Rauramaa, Rainer Raychaudhuri, Soumya Rayner, N. William Rees, Simon D. Rehnberg, Emil Ripatti, Samuli Robertson, Neil Roden, Michael Rossin, Elizabeth J. Rudan, Igor Rybin, Denis Saaristo, Timo E. Salomaa, Veikko Saltevo, Juha Samuel, Maria Sanghera, Dharambir K. Saramies, Jouko Scott, James Scott, Laura J. Scott, Robert A. Segrè, Ayellet V. Sehmi, Joban Sennblad, Bengt Shah, Nabi Shah, Sonia Shera, A. Samad Shu, Xiao Ou Shuldiner, Alan R. Sigurđsson, Gunnar Sijbrands, Eric Silveira, Angela Sim, Xueling Sivapalaratnam, Suthesh Small, Kerrin S. So, Wing Yee Stančáková, Alena Stefansson, Kari Steinbach, Gerald Steinthorsdottir, Valgerdur Stirrups, Kathleen Strawbridge, Rona J. Stringham, Heather M. Sun, Qi Suo, Chen Syvänen, Ann-Christine Takayanagi, Ryoichi Takeuchi, Fumihiko Tay, Wan Ting Teslovich, Tanya M. Thorand, Barbara Thorleifsson, Gudmar Thorsteinsdottir, Unnur Tikkanen, Emmi Trakalo, Joseph Tremoli, Elena Trip, Mieke D. Tsai, Fuu Jen Tuomi, Tiinamaija Tuomilehto, Jaakko Uitterlinden, Andre G. Valladares-Salgado, Adan Vedantam, Sailaja Veglia, Fabrizio Voight, Benjamin F. Wang, Congrong Wareham, Nicholas J. Wennauer, Roman Wickremasinghe, Ananda R. Wilsgaard, Tom Wilson, James F. Wiltshire, Steven Winckler, Wendy Wong, Tien Yin Wood, Andrew R. Wu, Jer-Yuarn Wu, Ying Yamamoto, Ken Yamauchi, Toshimasa Yang, Mingyu Yengo, Loic Yokota, Mitsuhiro Young, Robin Zabaneh, Delilah Zhang, Fan Zhang, Rong Zheng, Wei Zimmet, Paul Z. Altshuler, David Bowden, Donald W. Cho, Yoon Shin Cox, Nancy J. Cruz, Miguel Hanis, Craig L. Kooner, Jaspal Lee, Jong-Young Seielstad, Mark Teo, Yik Ying Boehnke, Michael Parra, Esteban J. Chambers, Jonh C. Tai, E. Shyong McCarthy, Mark I. Morris, Andrew P (2014):

    To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a statistically-significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

  92. https://www.nature.com/articles/ncomms7916

  93. ⁠, Locke, Adam E. Kahali, Bratati Berndt, Sonja I. Justice, Anne E. Pers, Tune H. Day, Felix R. Powell, Corey Vedantam, Sailaja Buchkovich, Martin L. Yang, Jian Croteau-Chonka, Damien C. Esko, Tonu Fall, Tove Ferreira, Teresa Gustafsson, Stefan Kutalik, Zoltán Luan, Jian'an Mägi, Reedik Randall, Joshua C. Winkler, Thomas W. Wood, Andrew R. Workalemahu, Tsegaselassie Faul, Jessica D. Smith, Jennifer A. Zhao, Jing Hua Zhao, Wei Chen, Jin Fehrmann, Rudolf Hedman, Åsa K. Karjalainen, Juha Schmidt, Ellen M. Absher, Devin Amin, Najaf Anderson, Denise Beekman, Marian Bolton, Jennifer L. Bragg-Gresham, Jennifer L. Buyske, Steven Demirkan, Ayse Deng, Guohong Ehret, Georg B. Feenstra, Bjarke Feitosa, Mary F. Fischer, Krista Goel, Anuj Gong, Jian Jackson, Anne U. Kanoni, Stavroula Kleber, Marcus E. Kristiansson, Kati Lim, Unhee Lotay, Vaneet Mangino, Massimo Leach, Irene Mateo Medina-Gomez, Carolina Medland, Sarah E. Nalls, Michael A. Palmer, Cameron D. Pasko, Dorota Pechlivanis, Sonali Peters, Marjolein J. Prokopenko, Inga Shungin, Dmitry Stančáková, Alena Strawbridge, Rona J. Sung, Yun Ju Tanaka, Toshiko Teumer, Alexander Trompet, Stella van der Laan, Sander W. van Setten, Jessica Van Vliet-Ostaptchouk, Jana V. Wang, Zhaoming Yengo, Loïc Zhang, Weihua Isaacs, Aaron Albrecht, Eva Ärnlöv, Johan Arscott, Gillian M. Attwood, Antony P. Bandinelli, Stefania Barrett, Amy Bas, Isabelita N. Bellis, Claire Bennett, Amanda J. Berne, Christian Blagieva, Roza Blüher, Matthias Böhringer, Stefan Bonnycastle, Lori L. Böttcher, Yvonne Boyd, Heather A. Bruinenberg, Marcel Caspersen, Ida H. Chen, Yii-Der Ida Clarke, Robert Daw, E. Warwick de Craen, Anton J. M Delgado, Graciela Dimitriou, Maria Doney, Alex S. F Eklund, Niina Estrada, Karol Eury, Elodie Folkersen, Lasse Fraser, Ross M. Garcia, Melissa E. Geller, Frank Giedraitis, Vilmantas Gigante, Bruna Go, Alan S. Golay, Alain Goodall, Alison H. Gordon, Scott D. Gorski, Mathias Grabe, Hans-Jörgen Grallert, Harald Grammer, Tanja B. Gräßler, Jürgen Grönberg, Henrik Groves, Christopher J. Gusto, Gaëlle Haessler, Jeffrey Hall, Per Haller, Toomas Hallmans, Goran Hartman, Catharina A. Hassinen, Maija Hayward, Caroline Heard-Costa, Nancy L. Helmer, Quinta Hengstenberg, Christian Holmen, Oddgeir Hottenga, Jouke-Jan James, Alan L. Jeff, Janina M. Johansson, Åsa Jolley, Jennifer Juliusdottir, Thorhildur Kinnunen, Leena Koenig, Wolfgang Koskenvuo, Markku Kratzer, Wolfgang Laitinen, Jaana Lamina, Claudia Leander, Karin Lee, Nanette R. Lichtner, Peter Lind, Lars Lindström, Jaana Lo, Ken Sin Lobbens, Stéphane Lorbeer, Roberto Lu, Yingchang Mach, François Magnusson, Patrik K. E Mahajan, Anubha McArdle, Wendy L. McLachlan, Stela Menni, Cristina Merger, Sigrun Mihailov, Evelin Milani, Lili Moayyeri, Alireza Monda, Keri L. Morken, Mario A. Mulas, Antonella Müller, Gabriele Müller-Nurasyid, Martina Musk, Arthur W. Nagaraja, Ramaiah Nöthen, Markus M. Nolte, Ilja M. Pilz, Stefan Rayner, Nigel W. Renstrom, Frida Rettig, Rainer Ried, Janina S. Ripke, Stephan Robertson, Neil R. Rose, Lynda M. Sanna, Serena Scharnagl, Hubert Scholtens, Salome Schumacher, Fredrick R. Scott, William R. Seufferlein, Thomas Shi, Jianxin Smith, Albert Vernon Smolonska, Joanna Stanton, Alice V. Steinthorsdottir, Valgerdur Stirrups, Kathleen Stringham, Heather M. Sundström, Johan Swertz, Morris A. Swift, Amy J. Syvänen, Ann-Christine Tan, Sian-Tsung Tayo, Bamidele O. Thorand, Barbara Thorleifsson, Gudmar Tyrer, Jonathan P. Uh, Hae-Won Vandenput, Liesbeth Verhulst, Frank C. Vermeulen, Sita H. Verweij, Niek Vonk, Judith M. Waite, Lindsay L. Warren, Helen R. Waterworth, Dawn Weedon, Michael N. Wilkens, Lynne R. Willenborg, Christina Wilsgaard, Tom Wojczynski, Mary K. Wong, Andrew Wright, Alan F. Zhang, Qunyuan Brennan, Eoin P. Choi, Murim Dastani, Zari Drong, Alexander W. Eriksson, Per Franco-Cereceda, Anders Gådin, Jesper R. Gharavi, Ali G. Goddard, Michael E. Handsaker, Robert E. Huang, Jinyan Karpe, Fredrik Kathiresan, Sekar Keildson, Sarah Kiryluk, Krzysztof Kubo, Michiaki Lee, Jong-Young Liang, Liming Lifton, Richard P. Ma, Baoshan McCarroll, Steven A. McKnight, Amy J. Min, Josine L. Moffatt, Miriam F. Montgomery, Grant W. Murabito, Joanne M. Nicholson, George Nyholt, Dale R. Okada, Yukinori Perry, John R. B Dorajoo, Rajkumar Reinmaa, Eva Salem, Rany M. Sandholm, Niina Scott, Robert A. Stolk, Lisette Takahashi, Atsushi Tanaka, Toshihiro van 't Hooft, Ferdin, M. Vinkhuyzen, Anna A. E Westra, Harm-Jan Zheng, Wei Zondervan, Krina T. Heath, Andrew C. Arveiler, Dominique Bakker, Stephan J. L Beilby, John Bergman, Richard N. Blangero, John Bovet, Pascal Campbell, Harry Caulfield, Mark J. Cesana, Giancarlo Chakravarti, Aravinda Chasman, Daniel I. Chines, Peter S. Collins, Francis S. Crawford, Dana C. Cupples, L. Adrienne Cusi, Daniele Danesh, John de Faire, Ulf den Ruijter, Hester M. Dominiczak, Anna F. Erbel, Raimund Erdmann, Jeanette Eriksson, Johan G. Farrall, Martin Felix, Stephan B. Ferrannini, Ele Ferrières, Jean Ford, Ian Forouhi, Nita G. Forrester, Terrence Franco, Oscar H. Gansevoort, Ron T. Gejman, Pablo V. Gieger, Christian Gottesman, Omri Gudnason, Vilmundur Gyllensten, Ulf Hall, Alistair S. Harris, Tamara B. Hattersley, Andrew T. Hicks, Andrew A. Hindorff, Lucia A. Hingorani, Aroon D. Hofman, Albert Homuth, Georg Hovingh, G. Kees Humphries, Steve E. Hunt, Steven C. Hyppönen, Elina Illig, Thomas Jacobs, Kevin B. Jarvelin, Marjo-Riitta Jöckel, Karl-Heinz Johansen, Berit Jousilahti, Pekka Jukema, J. Wouter Jula, Antti M. Kaprio, Jaakko Kastelein, John J. P Keinanen-Kiukaanniemi, Sirkka M. Kiemeney, Lambertus A. Knekt, Paul Kooner, Jaspal S. Kooperberg, Charles Kovacs, Peter Kraja, Aldi T. Kumari, M. Kuusisto, Johanna Lakka, Timo A. Langenberg, Claudia Marchand, Loic Le Lehtimäki, Terho Lyssenko, Valeriya Männistö, Satu Marette, André Matise, Tara C. McKenzie, Colin A. McKnight, Barbara Moll, Frans L. Morris, Andrew D. Morris, Andrew P. Murray, Jeffrey C. Nelis, Mari Ohlsson, Claes Oldehinkel, Albertine J. Ong, Ken K. Madden, Pamela A. F Pasterkamp, Gerard Peden, John F. Peters, Annette Postma, Dirkje S. Pramstaller, Peter P. Price, Jackie F. Qi, Lu Raitakari, Olli T. Rankinen, Tuomo Rao, D. C Rice, Treva K. Ridker, Paul M. Rioux, John D. Ritchie, Marylyn D. Rudan, Igor Salomaa, Veikko Samani, Nilesh J. Saramies, Jouko Sarzynski, Mark A. Schunkert, Heribert Schwarz, Peter E. H Sever, Peter Shuldiner, Alan R. Sinisalo, Juha Stolk, Ronald P. Strauch, Konstantin Tönjes, Anke Trégouët, David-Alexandre Tremblay, Angelo Tremoli, Elena Virtamo, Jarmo Vohl, Marie-Claude Völker, Uwe Waeber, Gérard Willemsen, Gonneke Witteman, Jacqueline C. Zillikens, M. Carola Adair, Linda S. Amouyel, Philippe Asselbergs, Folkert W. Assimes, Themistocles L. Bochud, Murielle Boehm, Bernhard O. Boerwinkle, Eric Bornstein, Stefan R. Bottinger, Erwin P. Bouchard, Claude Cauchi, Stéphane Chambers, John C. Chanock, Stephen J. Cooper, Richard S. de Bakker, Paul I. W Dedoussis, George Ferrucci, Luigi Franks, Paul W. Froguel, Philippe Groop, Leif C. Haiman, Christopher A. Hamsten, Anders Hui, Jennie Hunter, David J. Hveem, Kristian Kaplan, Robert C. Kivimaki, Mika Kuh, Diana Laakso, Markku Liu, Yongmei Martin, Nicholas G. März, Winfried Melbye, Mads Metspalu, Andres Moebus, Susanne Munroe, Patricia B. Njølstad, Inger Oostra, Ben A. Palmer, Colin N. A Pedersen, Nancy L. Perola, Markus Pérusse, Louis Peters, Ulrike Power, Chris Quertermous, Thomas Rauramaa, Rainer Rivadeneira, Fernando Saaristo, Timo E. Saleheen, Danish Sattar, Naveed Schadt, Eric E. Schlessinger, David Slagboom, P. Eline Snieder, Harold Spector, Tim D. Thorsteinsdottir, Unnur Stumvoll, Michael Tuomilehto, Jaakko Uitterlinden, André G. Uusitupa, Matti van der Harst, Pim Walker, Mark Wallaschofski, Henri Wareham, Nicholas J. Watkins, Hugh Weir, David R. Wichmann, H-Erich Wilson, James F. Zanen, Pieter Borecki, Ingrid B. Deloukas, Panos Fox, Caroline S. Heid, Iris M. O'Connell, Jeffrey R. Strachan, David P. Stefansson, Kari van Duijn, Cornelia M. Abecasis, Gonçalo R. Franke, Lude Frayling, Timothy M. McCarthy, Mark I. Visscher, Peter M. Scherag, André Willer, Cristen J. Boehnke, Michael Mohlke, Karen L. Lindgren, Cecilia M. Beckmann, Jacques S. Barroso, Inês North, Kari E. Ingelsson, Erik Hirschhorn, Joel N. Loos, Ruth J. F Speliotes, Elizabeth K (2015):

    Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10−8), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have statistically-significant effects on other metabolic phenotypes. The 97 loci account for ~2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/​​​​action, energy metabolism, lipid biology and adipogenesis.

  94. 2015-he.pdf

  95. https://www.sciencedirect.com/science/article/pii/S000292971300325X

  96. ⁠, (2014):

    Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide statistical-significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.

  97. 2018-zanetti.pdf

  98. ⁠, Brown, Brielin C. Ye, Chun Jimmie Price, Alkes L. Zaitlen, Noah (2016):

    The increasing number of genetic association studies conducted in multiple populations provides an unprecedented opportunity to study how the genetic architecture of complex phenotypes varies between populations, a problem important for both medical and population genetics. Here, we have developed a method for estimating the transethnic the correlation of causal-variant effect sizes at SNPs common in populations. This methods takes advantage of the entire spectrum of SNP associations and uses only summary-level data from genome-wide association studies. This avoids the computational costs and privacy concerns associated with genotype-level information while remaining scalable to hundreds of thousands of individuals and millions of SNPs. We applied our method to data on gene expression, rheumatoid arthritis, and type 2 diabetes and overwhelmingly found that the genetic correlation was statistically-significantly less than 1. Our method is implemented in a Python package called Popcorn.

  99. ⁠, Lencz, T. Knowles, E. Davies, G. Guha, S. Liewald, D. C Starr, J. M Djurovic, S. Melle, I. Sundet, K. Christoforou, A. Reinvang, I. Mukherjee, S. DeRosse, Pamela Lundervold, A. Steen, V. M John, M. Espeseth, T. Räikkönen, K. Widen, E. Palotie, A. Eriksson, J. G Giegling, I. Konte, B. Ikeda, M. Roussos, P. Giakoumaki, S. Burdick, K. E Payton, A. Ollier, W. Horan, M. Donohoe, G. Morris, D. Corvin, A. Gill, M. Pendleton, N. Iwata, N. Darvasi, A. Bitsios, P. Rujescu, D. Lahti, J. Hellard, S. L Keller, M. C Andreassen, O. A Deary, I. J Glahn, D. C Malhotra, A. K (2014):

    It has long been recognized that generalized deficits in cognitive ability represent a core component of schizophrenia (SCZ), evident before full illness onset and independent of medication. The possibility of genetic overlap between risk for SCZ and cognitive phenotypes has been suggested by the presence of cognitive deficits in first-degree relatives of patients with SCZ; however, until recently, molecular genetic approaches to test this overlap have been lacking. Within the last few years, large-scale genome-wide association studies (GWAS) of SCZ have demonstrated that a substantial proportion of the heritability of the disorder is explained by a polygenic component consisting of many common single-nucleotide polymorphisms (SNPs) of extremely small effect. Similar results have been reported in GWAS of general cognitive ability. The primary aim of the present study is to provide the first molecular genetic test of the classic endophenotype hypothesis, which states that alleles associated with reduced cognitive ability should also serve to increase risk for SCZ. We tested the endophenotype hypothesis by applying polygenic SNP scores derived from a large-scale cognitive GWAS meta-analysis (~5000 individuals from nine nonclinical cohorts comprising the Cognitive Genomics consorTium (COGENT)) to four SCZ case-control cohorts. As predicted, cases had significantly lower cognitive polygenic scores compared to controls. In parallel, polygenic risk scores for SCZ were associated with lower general cognitive ability. In addition, using our large cognitive meta-analytic data set, we identified nominally statistically-significant cognitive associations for several SNPs that have previously been robustly associated with SCZ susceptibility. Results provide molecular confirmation of the genetic overlap between SCZ and general cognitive ability, and may provide additional insight into pathophysiology of the disorder.

  100. 2018-tedja.pdf: “Genome-wide association meta-analysis highlights light-induced signaling as a driver for refractive error”⁠, Milly S. Tedja, Robert Wojciechowski, Pirro G. Hysi, Nicholas Eriksson, Nicholas A. Furlotte, Virginie J. M. Verhoeven, Adriana I. Iglesias, Magda A. Meester-Smoor, Stuart W. Tompson, Qiao Fan, Anthony P. Khawaja, Ching-Yu Cheng, Renamp#x000E9, Hamp#x000F6;hn, Kenji Yamashiro, Adam Wenocur, Clare Grazal, Toomas Haller, Andres Metspalu, Juho Wedenoja, Jost B. Jonas, Ya Xing Wang, Jing Xie, Paul Mitchell, Paul J. Foster, Barbara E. K. Klein, Ronald Klein, Andrew D. Paterson, S. Mohsen Hosseini, Rupal L. Shah, Cathy Williams, Yik Ying Teo, Yih Chung Tham, Preeti Gupta, Wanting Zhao, Yuan Shi, Woei-Yuh Saw, E-Shyong Tai, Xue Ling Sim, Jennifer E. Huffman, Ozren Polaamp#x00161;ek, Caroline Hayward, Goran Bencic, Igor Rudan, James F. Wilson, Tin Aung, Amutha B. Veluchamy, Kathryn P. Burdon, Harry Campbell, Li Jia Chen, Peng Chen, Wei Chen, Emily Chew, Margaret M. Deangelis, Xiaohu Ding, Angela Damp#x000F6;ring, David M. Evans, Sheng Feng, Brian Fleck, Rhys D. Fogarty, Jeremy R. Fondran, Maurizio Fossarello, Xiaobo Guo, Annet E. G. Haarman, Mingguang He, Laura D. Howe, Sarayut Janmahasatian, Vishal Jhanji, Mika Kamp#x000E4;hamp#x000F6;nen, Jaakko Kaprio, John P. Kemp, Kay-Tee Khaw, Chiea-Chuen Khor, Eva Krapohl, Jean-Franamp#x000E7;ois Korobelnik, Kris Lee, Shi-Ming Li, Yi Lu, Robert N. Luben, Kari-Matti Mamp#x000E4;kelamp#x000E4;, George McMahon, Akira Meguro, Evelin Mihailov, Masahiro Miyake, Nobuhisa Mizuki, Margaux Morrison, Vinay Nangia, Konrad Oexle, Songhomitra Panda-Jonas, Chi Pui Pang, Mario Pirastu, Robert Plomin, Taina Rantanen, Maria Schache, Ilkka Seppamp#x000E4;lamp#x000E4;, George D. Smith, Beate St Pourcain, Pancy O. Tam, J. Willem L. Tideman, Nicholas J. Timpson, Simona Vaccargiu, Zoran Vatavuk, Jie Jin Wang, Ningli Wang, Nick J. Wareham, Alan F. Wright, Liang Xu, Maurice K. H. Yap, Seyhan Yazar, Shea Ping Yip, Nagahisa Yoshimura, Alvin L. Young, Jing Hua Zhao, Xiangtian Zhou, Michelle Agee, Babak Alipanahi, Adam Auton, Robert K. Bell, Katarzyna Bryc, Sarah L. Elson, Pierre Fontanillas, David A. Hinds, Jennifer C. McCreight, Karen E. Huber, Aaron Kleinman, Nadia K. Litterman, 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, Vladimir Vacic, Catherine H. Wilson, Tariq M. Aslam, Sarah A. Barman, Jenny H. Barrett, Paul N. Bishop, Peter Blows, Catey Bunce, Roxana O. Carare, Usha Chakravarthy, Michelle Chan, Sharon Chua, David Crabb, Alexander Day, Parul Desai, Bal Dhillon, Andrew D. Dick, Cathy A. Egan, Sarah Ennis, Marcus Fruttiger, John Gallacher, David F. Garway-Heath, Jane Gibson, Dan M. Gore, Alison Hardcastle, Simon P. Harding, Ruth E. Hogg, Pearse A. Keane, Peng Tee Khaw, Gerassimos Lascaratos, Andrew Lotery, Phil J. Luthert, Tom J. MacGillivray, Sarah L. Mackie, Keith R. Martin, Michelle McGaughey, Bernadette McGuinness, Gareth J. McKay, Martin McKibbin, Danny Mitry, Tony Moore, James E. Morgan, Zaynah A. Muthy, Eoin Oamp#x02019;Sullivan, Chris Owen, Praveen J. Patel, Euan N. Paterson, Tunde Peto, Axel Petzold, Alicja R. Rudnicka, Jay E. Self, Sobha Sivaprasad, David H. W. Steel, Irene M. Stratton, Nicholas Strouthidis, Cathie L. M. Sudlow, Caroline Thaung, Dhanes Thomas, Emanuele Trucco, Adnan Tufail, Stephen A. Vernon, Ananth C. Viswanathan, Jayne V. Woodside, Max Yates, Jennifer L. Y. Yip, Yalin Zheng, Peter K. Joshi, Akitaka Tsujikawa, Fumihiko Matsuda, Kristina N. Whisenhunt, Tanja Zeller, Peter J. Spek, Roxanna Haak, Hanne Meijers-Heijboer, Elisabeth M. van Leeuwen, Sudha K. Iyengar, Jonathan H. Lass, Albert Hofman, Fernando Rivadeneira, Andramp#x000E9, G. Uitterlinden, Johannes R. Vingerling, Terho Lehtimamp#x000E4;ki, Olli T. Raitakari, Ginevra Biino, Maria Pina Concas, Tae-Hwi Schwantes-An, Robert P. Igo, Gabriel Cuellar-Partida, Nicholas G. Martin, Jamie E. Craig, Puya Gharahkhani, Katie M. Williams, Abhishek Nag, Jugnoo S. Rahi, Phillippa M. Cumberland, Camp#x000E9;cile Delcourt, Camp#x000E9;line Bellenguez, Janina S. Ried, Arthur A. Bergen, Thomas Meitinger, Christian Gieger, Tien Yin Wong, Alex W. Hewitt, David A. Mackey, Claire L. Simpson, Norbert Pfeiffer, Olavi Pamp#x000E4;rssinen, Paul N. Baird, Veronique Vitart, Najaf Amin, Cornelia M. Duijn, Joan E. Bailey-Wilson, Terri L. Young, Seang-Mei Saw, Dwight Stambolian, Stuart MacGregor, Jeremy A. Guggenheim, Joyce Y. Tung, Christopher J. Hammond, Caroline C. W. Klaver

  101. https://www.sciencedirect.com/science/article/pii/S0002929717301076

  102. ⁠, Aaron P. Ragsdale, Dominic Nelson, Simon Gravel, Jerome Kelleher (2020-06-05):

    Simulation plays a central role in population genomics studies. Recent years have seen rapid improvements in software efficiency that make it possible to simulate large genomic regions for many individuals sampled from large numbers of populations. As the complexity of the demographic models we study grows, however, there is an ever-increasing opportunity to introduce bugs in their implementation. Here we describe two errors made in defining models using the msprime coalescent simulator that have found their way into the published record. We discuss how these errors have affected downstream analyses and give recommendations for software developers and users to reduce the risk of such errors.

  103. https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-014-0091-5

  104. 2018-wray.pdf

  105. ⁠, 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, Chani J. Hodonsky, 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, Michael H. Preuss, Melissa A. Richard, Claudia Schurmann, Veronica W. Setiawan, Karan Vahi, Abhishek Vishnu, Marie Verbanck, Ryan Walker, Kristin L. Young, Niha Zubair, Jose Luis Ambite, Eric Boerwinkle, Erwin Bottinger, Carlos D. Bustamante, Christian Caberto, Matthew P. Conomos, Ewa Deelman, Ron Do, Kimberly Doheny, Lindsay Fernandez-Rhodes, Myriam Fornage, Gerardo Heiss, Lucia A. Hindorff, Rebecca D. Jackson, Regina James, Cecelia A. Laurie, Cathy C. Laurie, Yuqing Li, Dan-Yu Lin, Girish Nadkarni, Loreall C. Pooler, Alexander P. Reiner, Jane Romm, Chiara Sabati, Xin Sheng, Eli A. Stahl, Daniel O. Stram, Timothy A. Thornton, Christina L. Wassel, Lynne R. Wilkens, Sachi Yoneyama, Steven Buyske, Chris Haiman, Charles Kooperberg, Loic Le Marchand, Ruth JF Loos, Tara C. Matise, Kari E. North, Ulrike Peters, Eimear E. Kenny, Christopher S. Carlson (2017-09-15):

    Genome-wide association studies (GWAS) have laid the foundation for many downstream investigations, including the biology of complex traits, drug development, and clinical guidelines. However, the dominance of European-ancestry populations in GWAS creates a biased view of human variation and hinders the translation of genetic associations into clinical and public health applications. To demonstrate the benefit of studying underrepresented populations, the Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioral phenotypes in 49,839 non-European individuals. Using novel strategies for multi-ethnic analysis of admixed populations, we confirm 574 GWAS catalog variants across these traits, and find 28 novel loci and 42 residual signals in known loci. Our data show strong evidence of effect-size heterogeneity across ancestries for published GWAS associations, which substantially restricts genetically-guided precision medicine. We advocate for new, large genome-wide efforts in diverse populations to reduce health disparities.

  106. 2017-akiyama.pdf: ⁠, Masato Akiyama, Yukinori Okada, Masahiro Kanai, Atsushi Takahashi, Yukihide Momozawa, Masashi Ikeda, Nakao Iwata, Shiro Ikegawa, Makoto Hirata, Koichi Matsuda, Motoki Iwasaki, Taiki Yamaji, Norie Sawada, Tsuyoshi Hachiya, Kozo Tanno, Atsushi Shimizu, Atsushi Hozawa, Naoko Minegishi, Shoichiro Tsugane, Masayuki Yamamoto, Michiaki Kubo Yoichiro Kamatani (2017-09-11; genetics  /​ ​​ ​correlation):

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

  107. ⁠, Kelsey E. Grinde, Qibin Qi, Timothy A. Thornton, Simin Liu, Aladdin H. Shadyab, Kei Hang K. Chan, Alexander P. Reiner, Tamar Sofer (2018-01-04):

    Genetic risk scores (GRSs) are weighted sums of risk allele counts of single nucleotide polymorphisms (SNPs) associated with a disease or trait. Construction of GRSs is typically based on published results from Genome-Wide Association Studies (GWASs), the majority of which have been performed in large populations of European ancestry (EA) individuals. While many genotype-trait associations have been shown to generalize from EA populations to other populations, such as Hispanics/​​​​Latinos, the optimal choice of SNPs and weights for GRSs may differ between populations due to different linkage disequilibrium (LD) and allele frequency patterns. This is further complicated by the fact that different Hispanic/​​​​Latino populations may have different admixture patterns, so that LD and allele frequency patterns may not be the same among non-EA populations. Here, we compare various approaches for construction, using GWAS results from both large EA studies and a smaller study in Hispanics/​​​​Latinos, the Hispanic Community Health Study/​​​​Study of Latinos (HCHS/​​​​SOL, n = 12, 803). We consider multiple ways to select SNPs from association regions and to calculate the SNP weights. We study the performance of the resulting GRSs in an independent study of Hispanics/​​​​Latinos from the Woman Health Initiative (WHI, n = 3, 582). We support our investigation with simulation studies of potential genetic architectures in a single locus. We observed that selecting variants based on EA GWASs generally performs well, as long as SNP weights are calculated using Hispanics/​​​​Latinos GWASs, or using the meta-analysis of EA and Hispanics/​​​​Latinos GWASs. The optimal approach depends on the genetic architecture of the trait.

  108. ⁠, Lauren S. Mogil, Angela Andaleon, Alexa Badalamenti, Scott P. Dickinson, Xiuqing Guo, Jerome I. Rotter, W. Craig Johnson, Hae Kyung Im, Yongmei Liu, Heather E. Wheeler (2018-01-10):

    For many complex traits, gene regulation is likely to play a crucial mechanistic role. How the genetic architectures of complex traits vary between populations and subsequent effects on genetic prediction are not well understood, in part due to the historical paucity of GWAS in populations of non-European ancestry. We used data from the MESA (Multi-Ethnic Study of Atherosclerosis) cohort to characterize the genetic architecture of gene expression within and between diverse populations. Genotype and monocyte gene expression were available in individuals with African American (AFA, n = 233), Hispanic (HIS, n = 352), and European (CAU, n = 578) ancestry. We performed expression (eQTL) mapping in each population and show genetic correlation of gene expression depends on share ancestry proportions. Using elastic net modeling with cross validation to optimize genotypic predictors of gene expression in each population, we show the genetic architecture of gene expression is sparse across populations. We found the best predicted gene, HLA-DRB5, was the same across populations with R2 > 0.81 in each population. However, there were 1094 (11.3%) well predicted genes in AFA and 372 (3.8%) well predicted genes in HIS that were poorly predicted in CAU. Using genotype weights trained in MESA to predict gene expression in 1000 Genomes populations showed that a training set with ancestry similar to the test set is better at predicting gene expression in test populations, demonstrating an urgent need for diverse population sampling in genomics. Our predictive models in diverse cohorts are made publicly available for use in transcriptome mapping methods at http:/​​​​/​​​​predictdb.hakyimlab.org/​​​​.

    Author summary

    Most genome-wide association studies (GWAS) have been conducted in populations of European ancestry leading to a disparity in understanding the genetics of complex traits between populations. For many complex traits, gene regulation is likely to play a critical mechanistic role given the consistent enrichment of regulatory variants among trait-associated variants. However, it is still unknown how the effects of these key variants differ across populations. We used data from MESA to study the underlying genetic architecture of gene expression by optimizing gene expression prediction within and across diverse populations. The populations with genotype and gene expression data available are from individuals with African American (AFA, n = 233), Hispanic (HIS, n = 352), and European (CAU, n = 578) ancestry. After calculating the prediction performance, we found that there are many genes that were well predicted in AFA and HIS that were poorly predicted in CAU. We further showed that a training set with ancestry similar to the test set resulted in better gene expression predictions, demonstrating the need to incorporate diverse populations in genomic studies. Our gene expression prediction models are publicly available to facilitate future transcriptome mapping studies in diverse populations.

  109. ⁠, Liu, Jimmy Z. van Sommeren, Suzanne Huang, Hailiang Ng, Siew C. Alberts, Rudi Takahashi, Atsushi Ripke, Stephan Lee, James C. Jostins, Luke Shah, Tejas Abedian, Shifteh Cheon, Jae Hee Cho, Judy Dayani, Naser E. Franke, Lude Fuyuno, Yuta Hart, Ailsa Juyal, Ramesh C. Juyal, Garima Kim, Won Ho Morris, Andrew P. Poustchi, Hossein Newman, William G. Midha, Vandana Orchard, Timothy R. Vahedi, Homayon Sood, Ajit Sung, Joseph Y. Malekzadeh, Reza Westra, Harm-Jan Yamazaki, Keiko Yang, Suk-Kyun Barrett, Jeffrey C. Alizadeh, Behrooz Z. Parkes, Miles Bk, Thelma Daly, Mark J. Kubo, Michiaki Anderson, Carl A. Weersma, Rinse K (2015):

    Ulcerative colitis and Crohn’s disease are the two main forms of inflammatory bowel disease (IBD). Here we report the first trans-ancestry association study of IBD, with genome-wide or Immunochip genotype data from an extended cohort of 86,640 European individuals and Immunochip data from 9,846 individuals of East Asian, Indian or Iranian descent. We implicate 38 loci in IBD risk for the first time. For the majority of the IBD risk loci, the direction and magnitude of effect are consistent in European and non-European cohorts. Nevertheless, we observe genetic heterogeneity between divergent populations at several established risk loci driven by differences in allele frequency (NOD2) or effect size (TNFSF15 and ATG16L1) or a combination of these factors (IL23R and IRGM). Our results provide biological insights into the pathogenesis of IBD and demonstrate the usefulness of trans-ancestry association studies for mapping loci associated with complex diseases and understanding genetic architecture across diverse populations.

  110. ⁠, Ying Wang, Jing Guo, Guiyan Ni, Jian Yang, Peter M. Visscher, Loic Yengo (2020-01-15):

    Polygenic scores (PGS) have been widely used to predict complex traits and risk of diseases using variants identified from genome-wide association studies (GWASs). To date, most GWASs have been conducted in populations of European ancestry, which limits the use of GWAS-derived PGS in non-European populations. Here, we develop a new theory to predict the relative accuracy (RA, relative to the accuracy in populations of the same ancestry as the discovery population) of PGS across ancestries. We used simulations and real data from the to evaluate our results. We found across various simulation scenarios that the RA of PGS based on trait-associated SNPs can be predicted accurately from modelling linkage disequilibrium (LD), minor allele frequencies (MAF), cross-population correlations of SNP effect sizes and heritability. Altogether, we find that LD and MAF differences between ancestries explain alone up to ~70% of the loss of RA using European-based PGS in African ancestry for traits like body mass index and height. Our results suggest that causal variants underlying common genetic variation identified in European ancestry GWASs are mostly shared across continents.

  111. ⁠, Anna R. Docherty, Arden Moscati, Danielle Dick, Jeanne E. Savage, Jessica E. Salvatore, Megan Cooke, Fazil Aliev, Ashlee A. Moore, Alexis C. Edwards, Brien P. Riley, Daniel E. Adkins, Roseann Peterson, Bradley T. Webb, Silviu A. Bacanu, and Kenneth S. Kendler (2017-11-27):

    Background: Identifying genetic relationships between complex traits in emerging adulthood can provide useful etiological insights into risk for psychopathology. College-age individuals are under-represented in genomic analyses thus far, and the majority of work has focused on the clinical disorder or cognitive abilities rather than normal-range behavioral outcomes.

    Methods: This study examined a sample of emerging adults 18–22 years of age (n = 5947) to construct an atlas of polygenic risk for 33 traits predicting relevant phenotypic outcomes. 28 hypotheses were tested based on the previous literature on samples of European ancestry, and the availability of rich assessment data allowed for polygenic predictions across 55 psychological and medical phenotypes.

    Results: Polygenic risk for schizophrenia (SZ) in emerging adults predicted anxiety, depression, nicotine use, trauma, and family history of psychological disorders. Polygenic risk for neuroticism predicted anxiety, depression, phobia, panic, neuroticism, and was correlated with polygenic risk for cardiovascular disease.

    Conclusions: These results demonstrate the extensive impact of genetic risk for SZ, neuroticism, and major depression on a range of health outcomes in early adulthood. Minimal cross-ancestry replication of these phenomic patterns of polygenic influence underscores the need for more genome-wide association studies of non-European populations.

  112. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5971142/bin/NIHMS933200-supplement-SupplementA.pdf

  113. https://www.nature.com/articles/s41398-018-0236-1

  114. ⁠, Sulev Reisberg, Tatjana Iljasenko, Kristi Läll, Krista Fischer, Jaak Vilo (2017-05-25):

    Polygenic risk scores are gaining more and more attention for estimating genetic risks for liabilities, especially for noncommunicable diseases. They are now calculated using thousands of DNA markers. In this paper, we compare the score distributions of two previously published very large risk score models within different populations. We show that the risk score model together with its risk stratification thresholds, built upon the data of one population, cannot be applied to another population without taking into account the target population’s structure. We also show that if an individual is classified to the wrong population, his/​​​​her disease risk can be systematically incorrectly estimated.

  115. ⁠, LE Duncan, H. Shen, B. Gelaye, KJ Ressler, MW Feldman, RE Peterson, BW Domingue (2018-08-22):

    Studies of the relationship between genetic and phenotypic variation have historically been carried out on people of European ancestry. Efforts are underway to address this limitation, but until they succeed, the legacy of a Euro-centric bias in medical genetic studies will continue to hinder research, including the use of polygenic scores, which are individual-level metrics of genetic risk. Ongoing debate surrounds the generalizability of polygenic scores based on genome-wide association studies (GWAS) conducted in European ancestry samples, to non-European ancestry samples. We analyzed the first decade of polygenic scoring studies (2008-2017, inclusive), and found that 67% of studies included exclusively European ancestry participants and another 19% included only East Asian ancestry participants. Only 3.8% of studies were carried out on samples of African, Hispanic, or Indigenous peoples. We find that effect sizes for European ancestry-derived polygenic scores are only 36% as large in African ancestry samples, as in European ancestry samples (t=-10.056, df = 22, p = 5.5×10−10). Poorer performance was also observed in other non-European ancestry samples. Analysis of polygenic scores in the 1000Genomes samples revealed many strong correlations with global principal components, and relationships between height polygenic scores and height phenotypes that were highly variable depending on methodological choices in polygenic score construction. As polygenic score use increases in research, precision medicine, and direct-to-consumer testing, improved handling of linkage disequilibrium and variant frequencies (both of which currently reduce transferability of scores) across populations will improve polygenic score performance. These findings bolster the rationale for large-scale GWAS in diverse human populations.

    Significance Statement

    The modern genetics revolution enabled rough calculations of individuals’ genetic liability for many phenotypes, including height, weight, and schizophrenia. Increasingly, polygenic scores, which are individual-level metrics of genetic liability, are available via direct-to-consumer testing, and they are already widely used in research. The performance of these scores depends on the availability of very large genetic studies, and consequently it is problematic that people of European ancestry are vastly over-represented in these studies. We quantify the magnitude of this problem on the performance of polygenic scores in global samples and also show ancestry-related properties of polygenic scores. These findings set benchmarks for future progress, and they demonstrate the need for large-scale genetic studies in diverse human populations.

    Classification

    Biological Sciences—Genetics

  116. 2018-walters.pdf: “Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders”⁠, Raymond K. Walters, Renato Polimanti, Emma C. Johnson, Jeanette N. McClintick, Mark J. Adams, Amy E. Adkins, 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

  117. ⁠, Nikita Telkar, Theresa Reiker, Robin G. Walters, Kuang Lin, Deepti Gurdasani, Arthur Gilly, Lorraine Southam, Emmanouil Tsafantakis, Maria Karaleftheri, Janet Seeley, Anatoli Kamali, Gershim Asiki, Iona Y. Millwood, Huaidong Du, Yu Guo, Group Understanding Society Scientific Group, M. Kumari, George Dedoussis, Liming Li, Zhengming Chen, Manjinder S. Sandhu, Eleftheria Zeggini, Karoline Kuchenbaecker (2019-01-20):

    The under-representation of non-European samples in genome-wide association studies could ultimately restrict who benefits from medical advances through genomic science. Our aim was therefore to address the fundamental question whether causal variants for blood lipids are shared across populations.

    A polygenic score based on established LDL-cholesterol-associated loci from European discovery samples had consistent effects on serum levels in samples from the UK, Uganda and Greek population isolates (correlation coefficient r = 0.23 to 0.28 per LDL standard deviation, p < 1.9×10−14). Trans-ethnic genetic correlations between European ancestry, Chinese and Japanese cohorts did not differ statistically-significantly from 1 for HDL, LDL and triglycerides. In each study, >60% of major lipid loci displayed evidence of replication with one exception. There was evidence for an effect on serum levels in the Ugandan samples for only 10% of major triglyceride loci. The PRS was only weakly associated in this group (r = 0.06, SE = 0.013). We establish trans-ethnic colocalization as a method to distinguish shared from population-specific trait loci.

    Our results provide evidence for high levels of consistency of genetic associations for cholesterol biomarkers across populations. However, we also demonstrate that the degree of shared causal genetic architecture can be population-specific, trait-specific, and locus-specific. Efforts to implement genetic risk prediction in clinical settings should account for this.

  118. 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

  119. ⁠, Cassandra N. Spracklen, Momoko Horikoshi, Young Jin Kim, Kuang Lin, Fiona Bragg, Sanghoon Moon, Ken Suzuki, Claudia HT Tam, Yasuharu Tabara, Soo-Heon Kwak, Fumihiko Takeuchi, Jirong Long, Victor JY Lim, Jin-Fang Chai, Chien-Hsiun Chen, Masahiro Nakatochi, Jie Yao, Hyeok Sun Choi, Apoorva K. Iyengar, Hannah J. Perrin, Sarah M. Brotman, Martijn van de Bunt, Anna L. Gloyn, Jennifer E. Below, Michael Boehnke, Donald W. Bowden, John C. Chambers, Anubha Mahajan, Mark I. McCarthy, Maggie CY Ng, Lauren E. Petty, Weihua Zhang, Andrew P. Morris, Linda S. Adair, Zheng Bian, Juliana CN Chan, Li-Ching Chang, Miao-Li Chee, Yii-Der Ida Chen, Yuan-Tsong Chen, Zhengming Chen, Lee-Ming Chuang, Shufa Du, Penny Gordon-Larsen, Myron Gross, Xiuqing Guo, Yu Guo, Sohee Han, Annie-Green Howard, Wei Huang, Yi-Jen Hung, Mi Yeong Hwang, Chii-Min Hwu, Sahoko Ichihara, Masato Isono, Hye-Mi Jang, Guozhi Jiang, Jost B. Jonas, Yoichiro Kamatani, Tomohiro Katsuya, Takahisa Kawaguchi, Chiea-Chuen Khor, Katsuhiko Kohara, Myung-Shik Lee, Nannette R. Lee, Liming Li, Jianjun Liu, Andrea O. Luk, Jun Lv, Yukinori Okada, Mark A. Pereira, Charumathi Sabanayagam, Jinxiu Shi, Dong Mun Shin, Wing Yee So, Atsushi Takahashi, Brian Tomlinson, Fuu-Jen Tsai, Rob M. van Dam, Yong-Bing Xiang, Ken Yamamoto, Toshimasa Yamauchi, Kyungheon Yoon, Canqing Yu, Jian-Min Yuan, Liang Zhang, Wei Zheng, Michiya Igase, Yoon Shin Cho, Jerome I. Rotter, Ya-Xing Wang, Wayne HH Sheu, Mitsuhiro Yokota, Jer-Yuarn Wu, Ching-Yu Cheng, Tien-Yin Wong, Xiao-Ou Shu, Norihiro Kato, Kyong-Soo Park, E-Shyong Tai, Fumihiko Matsuda, Woon-Puay Koh, Ronald CW Ma, Shiro Maeda, Iona Y. Millwood, Juyoung Lee, Takashi Kadowaki, Robin G. Walters, Bong-Jo Kim, Karen L. Mohlke, Xueling Sim (2019-06-28):

    Meta-analyses of genome-wide association studies (GWAS) have identified >240 loci associated with type 2 diabetes (T2D), however most loci have been identified in analyses of European-ancestry individuals. To examine T2D risk in East Asian individuals, we meta-analyzed GWAS data in 77,418 cases and 356,122 controls. In the main analysis, we identified 298 distinct association signals at 178 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 56 loci newly implicated in T2D predisposition. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. New associations include signals in/​​​​near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect muscle and adipose differentiation. At another locus, eQTLs at two overlapping T2D signals act through two genes, NKX6-3 and ANK1, in different tissues. Association studies in diverse populations identify additional loci and elucidate disease genes, biology, and pathways.

    Type 2 diabetes (T2D) is a common metabolic disease primarily caused by insufficient insulin production and/​​​​or secretion by the pancreatic β cells and insulin resistance in peripheral tissues1. Most genetic loci associated with T2D have been identified in populations of European (EUR) ancestry, including a recent meta-analysis of genome-wide association studies (GWAS) of nearly 900,000 individuals of European ancestry that identified >240 loci influencing the risk of T2D2. Differences in allele frequency between ancestries affect the power to detect associations within a population, particularly among variants rare or monomorphic in one population but more frequent in another3,4. Although smaller than studies in European populations, a recent T2D meta-analysis in almost 200,000 Japanese individuals identified 28 additional loci4. The relative contributions of different pathways to the pathophysiology of T2D may also differ between ancestry groups. For example, in East Asian (EAS) populations, T2D prevalence is greater than in European populations among people of similar body mass index (BMI) or waist circumference5. We performed the largest meta-analysis of East Asian individuals to identify new genetic associations and provide insight into T2D pathogenesis.

  120. 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

  121. https://www.nature.com/articles/s41380-019-0517-y

  122. ⁠, Jing Guo, Andrew Bakshi, Ying Wang, Longda Jiang, Loic Yengo, Michael E. Goddard, Peter M. Visscher, Jian Yang (2019-11-14):

    Genome-wide association studies (GWAS) in samples of European ancestry have identified thousands of genetic variants associated with complex traits in humans. However, it remains largely unclear whether these associations can be used in non-European populations. Here, we seek to quantify the proportion of genetic variation for a complex trait shared between continental populations. We estimated the between-population correlation of genetic effects at all SNPs (rg) or genome-wide statistically-significant SNPs (rg(GWS)) for height and body mass index (BMI) in samples of European (EUR; n = 49,839) and African (AFR; n = 17,426) ancestry. The between EUR and AFR was 0.75 (s. e. = 0.035) for height and 0.68 (s. e. = 0.062) for BMI, and the corresponding was 0.82 (s. e. = 0.030) for height and 0.87 (s. e. = 0.064) for BMI, suggesting that a large proportion of GWAS findings discovered in Europeans are likely applicable to non-Europeans for height and BMI. There was no evidence that differs in SNP groups with different levels of between-population difference in allele frequency or linkage disequilibrium, which, however, can be due to the lack of power.

  123. ⁠, Satoshi Koyama, Kaoru Ito, Chikashi Terao, Masato Akiyama, Momoko Horikoshi, Yukihide Momozawa, Hiroshi Matsunaga, Hirotaka Ieki, Kouichi Ozaki, Yoshihiro Onouchi, Atsushi Takahashi, Seitaro Nomura, Hiroyuki Morita, Hiroshi Akazawa, Changhoon Kim, Jeong-sun Seo, Koichiro Higasa, Motoki Iwasaki, Taiki Yamaji, Norie Sawada, Shoichiro Tsugane, Teruhide Koyama, Hiroaki Ikezaki, Naoyuki Takashima, Keitaro Tanaka, Kokichi Arisawa, Kiyonori Kuriki, Mariko Naito, Kenji Wakai, Shinichiro Suna, Yasuhiko Sakata, Hiroshi Sato, Masatsugu Hori, Yasushi Sakata, Koichi Matsuda, Yoshinori Murakami, Hiroyuki Aburatani, Michiaki Kubo, Fumihiko Matsuda, Yoichiro Kamatani, Issei Komuro (2019-11-16):

    To elucidate the genetics of coronary artery disease (CAD) in the Japanese population, we conducted a large-scale genome-wide association study (GWAS) of 168,228 Japanese (25,892 cases and 142,336 controls) with genotype imputation using a newly developed reference panel of Japanese haplotypes including 1,782 CAD cases and 3,148 controls. We detected 9 novel disease-susceptibility loci and Japanese-specific rare variants contributing to disease severity and increased cardiovascular mortality. We then conducted a transethnic meta-analysis and discovered 37 additional novel loci. Using the result of the meta-analysis, we derived a polygenic risk score (PRS) for CAD, which outperformed those derived from either Japanese or European GWAS. The PRS prioritized risk factors among various clinical parameters and segregated individuals with increased risk of long-term cardiovascular mortality. Our data improves clinical characterization of CAD genetics and suggests the utility of transethnic meta-analysis for PRS derivation in non-European populations.

  124. ⁠, Kenneth Ekoru, Adebowale A. Adeyemo, Guanjie Chen, Ayo P. Doumatey, Jie Zhou, Amy R. Bentley, Daniel Shriner, Charles N. Rotimi (2020-05-25):

    There is growing support for the use of genetic risk scores (GRS) in routine clinical settings. Due to the limited diversity of current genomic discovery samples, there are concerns that the predictive power of GRS will be limited in non-European ancestry populations. Here, we evaluated the predictive utility of GRS for 12 cardiometabolic traits in sub-Saharan Africans (AF; n = 5200), African Americans (AA; n = 9139), and European Americans (EA; n = 9594). GRS were constructed as weighted sums of the number of risk alleles. Predictive utility was assessed using the additional phenotypic variance explained and increase in discriminatory ability over traditional risk factors (age, sex and BMI), with adjustment for ancestry-derived principal components. Across all traits, GRS showed upto a 5× and 20× greater predictive utility in EA relative to AA and AF, respectively. Predictive utility was most consistent for lipid traits, with percent increase in explained variation attributable to GRS ranging from 10.6% to 127.1% among EA, 26.6% to 65.8% among AA, and 2.4% to 37.5% among AF. These differences were recapitulated in the discriminatory power, whereby the predictive utility of GRS was 4× greater in EA relative to AA and up to 44× greater in EA relative to AF. Obesity and blood pressure traits showed a similar pattern of greater predictive utility among EA. This work demonstrates the poorer performance of GRS in AF and highlights the need to improve representation of multiethnic populations in genomic studies to ensure equitable clinical translation of GRS.

    Key Messages

    Genetic Risk Score (GRS) prediction is markedly poorer in sub-Saharan Africans compared with African Americans and European Americans

    To ensure equitable clinical translation of GRS, there is need need to improve representation of multiethnic populations in genomic studies

  125. http://infoproc.blogspot.com/2011/08/predictive-power-of-early-childhood-iq.html

  126. ⁠, Junpei Komiyama, Junya Honda, Hiroshi Nakagawa (2015-06-02):

    We discuss a multiple-play multi-armed bandit (MAB) problem in which several arms are selected at each round. Recently, Thompson sampling (TS), a randomized algorithm with a Bayesian spirit, has attracted much attention for its empirically excellent performance, and it is revealed to have an optimal regret bound in the standard single-play MAB problem. In this paper, we propose the multiple-play Thompson sampling (MP-TS) algorithm, an extension of TS to the multiple-play MAB problem, and discuss its regret analysis. We prove that MP-TS for binary rewards has the optimal regret upper bound that matches the regret lower bound provided by Anantharam et al 1987. Therefore, MP-TS is the first computationally efficient algorithm with optimal regret. A set of computer simulations was also conducted, which compared MP-TS with state-of-the-art algorithms. We also propose a modification of MP-TS, which is shown to have better empirical performance.

  127. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.831.5818&rep=rep1&type=pdf

  128. 2015-gianola.pdf: ⁠, Daniel Gianola, Guilherme J. M. Rosa (2014-11-03; genetics  /​ ​​ ​selection):

    Statistical methodology has played a key role in scientific animal breeding. Approximately one hundred years of statistical developments in animal breeding are reviewed. Some of the scientific foundations of the field are discussed, and many milestones are examined from historical and critical perspectives. The review concludes with a discussion of some future challenges and opportunities arising from the massive amount of data generated by livestock, plant, and human genome projects.

  129. https://www.nap.edu/read/24623/chapter/7

  130. ⁠, Biohackinfo News (2021-03-28):

    China’s new Criminal Code⁠, which came into effect four weeks ago on March 1st, has a new section dedicated to ‘illegal medical practices’, which makes it a punishable crime to create gene-edited babies, human clones and animal-human chimeras.

    The new section is an amendment to Article 336 of China’s Criminal Law, and officially outlaws “the implantation of genetically-edited or cloned human embryos into human or animal bodies, or the implantation of genetically edited or cloned animal embryos into human bodies”—with penalties ranging from fines to 7 years imprisonment.

    …Although Dr He had been sentenced for genetically modifying human embryos, China’s previous criminal code on ‘illegal medical practices’, under which he was sentenced, was extremely vague on the gene-editing of human embryos, and was mostly used to prosecute providers of dangerous medical procedures, and not researchers. The only official Chinese Government legal document that made a stipulation against genetically altering human embryos at the time of Dr He’s sentencing was a scientifically-outdated 2003 guideline by the Chinese Ministry of Health, which mostly addressed ethical issues on human embryonic stem cell research. And thus due to this legal vagueness on human gene-editing, legal experts in China found the court sentencing of Dr He to be very problematic…The new addition to the criminal code is meant to clear up these questions.

  131. 2015-henn.pdf: “Estimating the mutation load in human genomes”⁠, Brenna M. Henn, Laura R. Botigué, Carlos D. Bustamante, Andrew G. Clark, Simon Gravel

  132. 2014-simons.pdf: “The deleterious mutation load is insensitive to recent population history”⁠, Yuval B. Simons, Michael C. Turchin, Jonathan K. Pritchard, Guy Sella

  133. 2014-simons-supplementary.pdf

  134. 2012-fu.pdf: “Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants”⁠, Wenqing Fu, Timothy D. O’Connor, Goo Jun, Hyun Min Kang, Goncalo Abecasis, Suzanne M. Leal, Stacey Gabriel, David Altshuler, Jay Shendure, Deborah A. Nickerson, Michael J. Bamshad, NHLBI Exome Sequencing Project, Joshua M. Akey

  135. ⁠, Fu, Wenqing O'Connor, Timothy D. Jun, Goo Kang, Hyun Min Abecasis, Goncalo Leal, Suzanne M. Gabriel, Stacey Rieder, Mark J. Altshuler, David Shendure, Jay Nickerson, Deborah A. Bamshad, Michael J. Akey, Joshua M (2013):

    Establishing the age of each mutation segregating in contemporary human populations is important to fully understand our evolutionary history and will help to facilitate the development of new approaches for disease-gene discovery. Large-scale surveys of human genetic variation have reported signatures of recent explosive population growth, notable for an excess of rare genetic variants, suggesting that many mutations arose recently. To more quantitatively assess the distribution of mutation ages, we resequenced 15,336 genes in 6,515 individuals of European American and African American ancestry and inferred the age of 1,146,401 autosomal single nucleotide variants (SNVs). We estimate that approximately 73% of all protein-coding SNVs and approximately 86% of SNVs predicted to be deleterious arose in the past 5,000-10,000 years. The average age of deleterious SNVs varied significantly across molecular pathways, and disease genes contained a significantly higher proportion of recently arisen deleterious SNVs than other genes. Furthermore, European Americans had an excess of deleterious variants in essential and Mendelian disease genes compared to African Americans, consistent with weaker due to the Out-of-Africa dispersal. Our results better delimit the historical details of human protein-coding variation, show the profound effect of recent human history on the burden of deleterious SNVs segregating in contemporary populations, and provide important practical information that can be used to prioritize variants in disease-gene discovery.

  136. 2017-jonsson.pdf: “Parental influence on human germline de novo mutations in 1,548 trios from Iceland”⁠, Hákon Jónsson, Patrick Sulem, Birte Kehr, Snaedis Kristmundsdottir, Florian Zink, Eirikur Hjartarson, Marteinn T. Hardarson, Kristjan E. Hjorleifsson, Hannes P. Eggertsson, Sigurjon Axel Gudjonsson, Lucas D. Ward, Gudny A. Arnadottir, Einar A. Helgason, Hannes Helgason, Arnaldur Gylfason, Adalbjorg Jonasdottir, Aslaug Jonasdottir, Thorunn Rafnar, Mike Frigge, Simon N. Stacey, Olafur Th. Magnusson, Unnur Thorsteinsdottir, Gisli Masson, Augustine Kong, Bjarni V. Halldorsson, Agnar Helgason, Daniel F. Gudbjartsson, Kari Stefansson

  137. ⁠, Benedict Paten, Adam M. Novak, Jordan M. Eizenga, Garrison Erik (2017-03-14):

    The human reference genome is part of the foundation of modern human biology, and a monumental scientific achievement. However, because it excludes a great deal of common human variation, it introduces a pervasive reference bias into the field of human genomics. To reduce this bias, it makes sense to draw on representative collections of human genomes, brought together into reference cohorts. There are a number of techniques to represent and organize data gleaned from these cohorts, many using ideas implicitly or explicitly borrowed from graph based models. Here, we survey various projects underway to build and apply these graph based structures—which we collectively refer to as genome graphs—and discuss the improvements in read mapping, variant calling, and haplotype determination that genome graphs are expected to produce.

  138. https://www.nature.com/articles/nature15393

  139. ⁠, Chaisson, Mark J. P Huddleston, John Dennis, Megan Y. Sudmant, Peter H. Malig, Maika Hormozdiari, Fereydoun Antonacci, Francesca Surti, Urvashi Sandstrom, Richard Boitano, Matthew Landolin, Jane M. Stamatoyannopoulos, John A. Hunkapiller, Michael W. Korlach, Jonas Eichler, Evan E (2015):

    The human genome is arguably the most complete mammalian reference assembly, yet more than 160 euchromatic gaps remain and aspects of its structural variation remain poorly understood ten years after its completion. To identify missing sequence and genetic variation, here we sequence and analyse a haploid human genome (CHM1) using single-molecule, real-time DNA sequencing. We close or extend 55% of the remaining interstitial gaps in the human GRCh37 reference genome–78% of which carried long runs of degenerate short tandem repeats, often several kilobases in length, embedded within (G+C)-rich genomic regions. We resolve the complete sequence of 26,079 euchromatic structural variants at the base-pair level, including inversions, complex insertions and long tracts of tandem repeats. Most have not been previously reported, with the greatest increases in sensitivity occurring for events less than 5 kilobases in size. Compared to the human reference, we find a significant insertional bias (3:1) in regions corresponding to complex insertions and long short tandem repeats. Our results suggest a greater complexity of the human genome in the form of variation of longer and more complex repetitive DNA that can now be largely resolved with the application of this longer-read sequencing technology.

  140. https://www.nature.com/articles/nature20098

  141. 2017-gazal.pdf: ⁠, Steven Gazal, Hilary K. Finucane, Nicholas A. Furlotte, Po-Ru Loh, Pier Francesco Palamara, Xuanyao Liu, Armin Schoech, Brendan Bulik-Sullivan, Benjamin M. Neale, Alexander Gusev, Alkes L. Price (2017-09-11; genetics  /​ ​​ ​selection):

    Recent work has hinted at the linkage disequilibrium (LD)-dependent architecture of human complex traits, where SNPs with low levels of LD (LLD) have larger per-SNP heritability. Here we analyzed summary statistics from 56 complex traits (average n = 101,401) by extending stratified LD score regression to continuous annotations. We determined that SNPs with low LLD have statistically-significantly larger per-SNP heritability and that roughly half of this effect can be explained by functional annotations negatively correlated with LLD, such as DNase I hypersensitivity sites (DHSs). The remaining signal is largely driven by our finding that more recent common variants tend to have lower LLD and to explain more heritability (p = 2.38 × 10−104); the youngest 20% of common SNPs explain 3.9 times more heritability than the oldest 20%, consistent with the action of negative selection. We also inferred jointly statistically-significant effects of other LD-related annotations and confirmed via forward simulations that they jointly predict deleterious effects.

  142. ⁠, Armin P. Schoech, Daniel Jordan, Po-Ru Loh, Steven Gazal, Luke O’Connor, Daniel J. Balick, Pier F. Palamara, Hilary K. Finucane, Shamil R. Sunyaev, Alkes L. Price (2017-09-13):

    Understanding the role of rare variants is important in elucidating the genetic basis of human diseases and complex traits. It is widely believed that negative selection can cause rare variants to have larger per-allele effect sizes than common variants. Here, we develop a method to estimate the minor allele frequency (MAF) dependence of SNP effect sizes. We use a model in which per-allele effect sizes have variance proportional to [p(1−p)]α, where p is the MAF and negative values of α imply larger effect sizes for rare variants. We estimate α by maximizing its profile likelihood in a linear mixed model framework using imputed genotypes, including rare variants (MAF >0.07%). We applied this method to 25 UK Biobank diseases and complex traits (n = 113,851). All traits produced negative α estimates with 20 significantly negative, implying larger rare variant effect sizes. The inferred best-fit distribution of true α values across traits had mean −0.38 (s.e. 0.02) and standard deviation 0.08 (s.e. 0.03), with statistically-significant heterogeneity across traits (p = 0.0014). Despite larger rare variant effect sizes, we show that for most traits analyzed, rare variants (MAF <1%) explain less than 10% of total SNP-heritability. Using evolutionary modeling and forward simulations, we validated the α model of MAF-dependent trait effects and estimated the level of coupling between fitness effects and trait effects. Based on this analysis an average genome-wide negative selection coefficient on the order of 10−4 or stronger is necessary to explain the α values that we inferred.

  143. 2018-mahajan.pdf: “Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes”⁠, Anubha Mahajan, Jennifer Wessel, Sara M. Willems, Wei Zhao, Neil R. Robertson, Audrey Y. Chu, Wei Gan, Hidetoshi Kitajima, Daniel Taliun, N. William Rayner, Xiuqing Guo, Yingchang Lu, Man Li, Richard ⁠, Yao Hu, Shaofeng Huo, Kurt K. Lohman, Weihua Zhang, James P. Cook, Bram Peter Prins, Jason Flannick, Niels Grarup, Vassily Vladimirovich Trubetskoy, Jasmina Kravic, Young Jin Kim, Denis V. Rybin, Hanieh Yaghootkar, Martina Mamp#x000FC;ller-Nurasyid, Karina Meidtner, Ruifang Li-Gao, Tibor V. Varga, Jonathan Marten, Jin Li, Albert Vernon Smith, Ping An, Symen Ligthart, Stefan Gustafsson, Giovanni Malerba, Ayse Demirkan, Juan Fernandez Tajes, Valgerdur Steinthorsdottir, Matthias Wuttke, Camp#x000E9;cile Lecoeur, Michael Preuss, Lawrence F. Bielak, Marielisa Graff, Heather M. Highland, Anne E. Justice, Dajiang J. Liu, Eirini Marouli, Gina Marie Peloso, Helen R. Warren, Saima Afaq, Shoaib Afzal, Emma Ahlqvist, Peter Almgren, Najaf Amin, Lia B. Bang, Alain G. Bertoni, Cristina Bombieri, Jette Bork-Jensen, Ivan Brandslund, Jennifer A. Brody, Noamp#x000EB;l P. Burtt, Mickaamp#x000EB;l Canouil, Yii-Der Ida Chen, Yoon Shin Cho, Cramer Christensen, Sophie V. Eastwood, Kai-Uwe Eckardt, Krista Fischer, Giovanni Gambaro, Vilmantas Giedraitis, Megan L. Grove, Hugoline G. Haan, Sophie Hackinger, Yang Hai, Sohee Han, Anne Tybjamp#x000E6;rg-Hansen, Marie-France Hivert, Bo Isomaa, Susanne Jamp#x000E4;ger, Marit E. Jamp#x000F8;rgensen, Torben Jamp#x000F8;rgensen, Annemari Kamp#x000E4;ramp#x000E4;jamp#x000E4;mamp#x000E4;ki, Bong-Jo Kim, Sung Soo Kim, Heikki A. Koistinen, Peter Kovacs, Jennifer Kriebel, Florian Kronenberg, Kristi Lamp#x000E4;ll, Leslie A. Lange, Jung-Jin Lee, Benjamin Lehne, Huaixing Li, Keng-Hung Lin, Allan Linneberg, Ching-Ti Liu, Jun Liu, Marie Loh, Reedik Mamp#x000E4;gi, Vasiliki Mamakou, Roberta McKean-Cowdin, Girish Nadkarni, Matt Neville, Sune F. Nielsen, Ioanna Ntalla, Patricia A. Peyser, Wolfgang Rathmann, Kenneth Rice, Stephen S. Rich, Line Rode, Olov Rolandsson, Sebastian Schamp#x000F6;nherr, Elizabeth Selvin, Kerrin S. Small, Alena Stanamp#x0010D;amp#x000E1;kovamp#x000E1;, Praveen Surendran, Kent D. Taylor, Tanya M. Teslovich, Barbara Thorand, Gudmar Thorleifsson, Adrienne Tin, Anke Tamp#x000F6;njes, Anette Varbo, Daniel R. Witte, Andrew R. Wood, Pranav Yajnik, Jie Yao, Loamp#x000EF;c Yengo, Robin Young, Philippe Amouyel, Heiner Boeing, Eric Boerwinkle, Erwin P. Bottinger, Rajiv Chowdhury, Francis S. Collins, George Dedoussis, Abbas Dehghan, Panos Deloukas, Marco M. Ferrario, Jean Ferriamp#x000E8;res, Jose C. Florez, Philippe Frossard, Vilmundur Gudnason, Tamara B. Harris, Susan R. Heckbert, Joanna M. M. Howson, Martin Ingelsson, Sekar Kathiresan, Frank Kee, Johanna Kuusisto, Claudia Langenberg, Lenore J. Launer, Cecilia M. Lindgren, Satu Mamp#x000E4;nnistamp#x000F6;, Thomas Meitinger, Olle Melander, Karen L. Mohlke, Marie Moitry, Andrew D. Morris, Alison D. Murray, Renamp#x000E9;e Mutsert, Marju Orho-Melander, Katharine R. Owen, Markus Perola, Annette Peters, Michael A. Province, Asif Rasheed, Paul M. Ridker, Fernando Rivadineira, Frits R. Rosendaal, Anders H. Rosengren, Veikko Salomaa, Wayne H.-H. Sheu, Rob Sladek, Blair H. Smith, Konstantin Strauch, Andramp#x000E9, G. Uitterlinden, Rohit Varma, Cristen J. Willer, Matthias Blamp#x000FC;her, Adam S. Butterworth, John Campbell Chambers, Daniel I. Chasman, John Danesh, Cornelia Duijn, Josamp#x000E9;e Dupuis, Oscar H. Franco, Paul W. Franks, Philippe Froguel, Harald Grallert, Leif Groop, Bok-Ghee Han, Torben Hansen, Andrew T. Hattersley, Caroline Hayward, Erik Ingelsson, Sharon L. R. Kardia, Fredrik Karpe, Jaspal Singh Kooner, Anna Kamp#x000F6;ttgen, Kari Kuulasmaa, Markku Laakso, Xu Lin, Lars Lind, Yongmei Liu, Ruth J. F. Loos, Jonathan Marchini, Andres Metspalu, Dennis Mook-Kanamori, Bamp#x000F8;rge G. Nordestgaard, Colin N. A. Palmer, James S. Pankow, Oluf Pedersen, Bruce M. Psaty, Rainer Rauramaa, Naveed Sattar, Matthias B. Schulze, Nicole Soranzo, Timothy D. Spector, Kari Stefansson, Michael Stumvoll, Unnur Thorsteinsdottir, Tiinamaija Tuomi, Jaakko Tuomilehto, Nicholas J. Wareham, James G. Wilson, Eleftheria Zeggini, Robert A. Scott, Inamp#x000EA;s Barroso, Timothy M. Frayling, Mark O. Goodarzi, James B. Meigs, Michael Boehnke, Danish Saleheen, Andrew P. Morris, Jerome I. Rotter, Mark I. McCarthy