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1. Human genetic analyses of organelles highlight the nucleus in age-related trait heritability

Author: Rahul Gupta, Konrad J Karczewski, Daniel Howrigan, Benjamin M Neale, and Vamsi K Mootha
Subjects: aging, mitochondria, transcription factors, haplosufficiency, enrichment, constraint, Medicine, Science, Biology (General), QH301-705.5
Abstract: Most age-related human diseases are accompanied by a decline in cellular organelle integrity, including impaired lysosomal proteostasis and defective mitochondrial oxidative phosphorylation. An open question, however, is the degree to which inherited variation in or near genes encoding each organelle contributes to age-related disease pathogenesis. Here, we evaluate if genetic loci encoding organelle proteomes confer greater-than-expected age-related disease risk. As mitochondrial dysfunction is a ‘hallmark’ of aging, we begin by assessing nuclear and mitochondrial DNA loci near genes encoding the mitochondrial proteome and surprisingly observe a lack of enrichment across 24 age-related traits. Within nine other organelles, we find no enrichment with one exception: the nucleus, where enrichment emanates from nuclear transcription factors. In agreement, we find that genes encoding several organelles tend to be ‘haplosufficient,’ while we observe strong purifying selection against heterozygous protein-truncating variants impacting the nucleus. Our work identifies common variation near transcription factors as having outsize influence on age-related trait risk, motivating future efforts to determine if and how this inherited variation then contributes to observed age-related organelle deterioration.
Published: 2021
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2. Recent advances in understanding of attention deficit hyperactivity disorder (ADHD): how genetics are shaping our conceptualization of this disorder [version 2; peer review: 3 approved]

Author: Tetyana Zayats and Benjamin M Neale
Subjects: Medicine, Science
Abstract: Attention deficit hyperactivity disorder (ADHD) is a clinically defined disorder, and inattention and hyperactivity/impulsivity are its main symptom domains. The presentation, lifelong continuation and treatment response of ADHD symptoms, however, is highly heterogeneous. To better define, diagnose, treat and prevent ADHD, it is essential that we understand the biological processes underlying all of these elements. In this review, given the high heritability of ADHD, we discuss how and why genetics can foster such progress. We examine what genetics have taught us so far with regard to ADHD definition, classification, clinical presentation, diagnosis and treatment. Finally, we offer a prospect of what genetic studies on ADHD may bring in the future.
Published: 2020
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3. Correction: Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria.

Author: Felix Day, Tugce Karaderi, Michelle R Jones, Cindy Meun, Chunyan He, Alex Drong, Peter Kraft, Nan Lin, Hongyan Huang, Linda Broer, Reedik Magi, Richa Saxena, Triin Laisk, Margrit Urbanek, M Geoffrey Hayes, Gudmar Thorleifsson, Juan Fernandez-Tajes, Anubha Mahajan, Benjamin H Mullin, Bronwyn G A Stuckey, Timothy D Spector, Scott G Wilson, Mark O Goodarzi, Lea Davis, Barbara Obermayer-Pietsch, André G Uitterlinden, Verneri Anttila, Benjamin M Neale, Marjo-Riitta Jarvelin, Bart Fauser, Irina Kowalska, Jenny A Visser, Marianne Andersen, Ken Ong, Elisabet Stener-Victorin, David Ehrmann, Richard S Legro, Andres Salumets, Mark I McCarthy, Laure Morin-Papunen, Unnur Thorsteinsdottir, Kari Stefansson, andMe Research Team, Unnur Styrkarsdottir, John R B Perry, Andrea Dunaif, Joop Laven, Steve Franks, Cecilia M Lindgren, and Corrine K Welt
Subjects: Genetics, QH426-470
Abstract: [This corrects the article DOI: 10.1371/journal.pgen.1007813.].
Published: 2019
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4. Recent advances in understanding of attention deficit hyperactivity disorder (ADHD): how genetics are shaping our conceptualization of this disorder [version 1; peer review: 3 approved]

Author: Tetyana Zayats and Benjamin M Neale
Subjects: Medicine, Science
Abstract: Attention deficit hyperactivity disorder (ADHD) is a clinically defined disorder, and inattention and hyperactivity/impulsivity are its main symptom domains. The presentation, lifelong continuation and treatment response of ADHD symptoms, however, is highly heterogeneous. To better define, diagnose, treat and prevent ADHD, it is essential that we understand the biological processes underlying all of these elements. In this review, given the high heritability of ADHD, we discuss how and why genetics can foster such progress. We examine what genetics have taught us so far with regard to ADHD definition, classification, clinical presentation, diagnosis and treatment. Finally, we offer a prospect of what genetic studies on ADHD may bring in the future.
Published: 2019
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5. Correction: Insights into the genetic epidemiology of Crohn's and rare diseases in the Ashkenazi Jewish population.

Author: Manuel A Rivas, Brandon E Avila, Jukka Koskela, Hailiang Huang, Christine Stevens, Matti Pirinen, Talin Haritunians, Benjamin M Neale, Mitja Kurki, Andrea Ganna, Daniel Graham, Benjamin Glaser, Inga Peter, Gil Atzmon, Nir Barzilai, Adam P Levine, Elena Schiff, Nikolas Pontikos, Ben Weisburd, Monkol Lek, Konrad J Karczewski, Jonathan Bloom, Eric V Minikel, Britt-Sabina Petersen, Laurent Beaugerie, Philippe Seksik, Jacques Cosnes, Stefan Schreiber, Bernd Bokemeyer, Johannes Bethge, International IBD Genetics Consortium, NIDDK IBD Genetics Consortium, T2D-GENES Consortium, Graham Heap, Tariq Ahmad, Vincent Plagnol, Anthony W Segal, Stephan Targan, Dan Turner, Paivi Saavalainen, Martti Farkkila, Kimmo Kontula, Aarno Palotie, Steven R Brant, Richard H Duerr, Mark S Silverberg, John D Rioux, Rinse K Weersma, Andre Franke, Luke Jostins, Carl A Anderson, Jeffrey C Barrett, Daniel G MacArthur, Chaim Jalas, Harry Sokol, Ramnik J Xavier, Ann Pulver, Judy H Cho, Dermot P B McGovern, and Mark J Daly
Subjects: Genetics, QH426-470
Abstract: [This corrects the article DOI: 10.1371/journal.pgen.1007329.].
Published: 2019
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6. Genetic Overlap Between Alzheimer’s Disease and Bipolar Disorder Implicates the MARK2 and VAC14 Genes

Author: Ole Kristian Drange, Olav Bjerkehagen Smeland, Alexey A. Shadrin, Per Ivar Finseth, Aree Witoelar, Oleksandr Frei, Psychiatric Genomics Consortium Bipolar Disorder Working Group, Yunpeng Wang, Sahar Hassani, Srdjan Djurovic, Anders M. Dale, Ole A. Andreassen, Eli A Stahl, Gerome Breen, Andreas J Forstner, Andrew McQuillin, Stephan Ripke, Vassily Trubetskoy, Manuel Mattheisen, Jonathan R I Coleman, Heìleìna A Gaspar, Christiaan A de Leeuw, Stacy Steinberg, Jennifer M Whitehead Pavlides, Maciej Trzaskowski, Tune H Pers, Peter A Holmans, Liam Abbott, Esben Agerbo, Huda Akil, Diego Albani, Ney Alliey-Rodriguez, Thomas D Als, Adebayo Anjorin, Verneri Antilla, Swapnil Awasthi, Judith A Badner, Marie Bækvad-Hansen, Jack D Barchas, Nicholas Bass, Michael Bauer, Richard Belliveau, Sarah E Bergen, Carsten Bøcker Pedersen, Erlend Bøen, Marco Boks, James Boocock, Monika Budde, William Bunney, Margit Burmeister, Jonas Bybjerg-Grauholm, William Byerley, Miquel Casas, Felecia Cerrato, Pablo Cervantes, Kimberly Chambert, Alexander W Charney, Danfeng Chen, Claire Churchhouse, Toni-Kim Clarke, William Coryell, David W Craig, Cristiana Cruceanu, David Curtis, Piotr M Czerski, Anders M Dale, Simone de Jong, Franziska Degenhardt, Jurgen Del-Favero, J Raymond DePaulo, Amanda L Dobbyn, Ashley Dumont, Torbjørn Elvsåshagen, Valentina Escott-Price, Chun Chieh Fan, Sascha B Fischer, Matthew Flickinger, Tatiana M Foroud, Liz Forty, Josef Frank, Christine Fraser, Nelson B Freimer, Louise Friseìn, Katrin Gade, Diane Gage, Julie Garnham, Claudia Giambartolomei, Marianne Giørtz Pedersen, Jaqueline Goldstein, Scott D Gordon, Katherine Gordon-Smith, Elaine K Green, Melissa J Green, Tiffany A Greenwood, Jakob Grove, Weihua Guan, Joseì Guzman Parra, Marian L Hamshere, Martin Hautzinger, Urs Heilbronner, Stefan Herms, Maria Hipolito, Per Hoffmann, Dominic Holland, Laura Huckins, Steìphane Jamain, Jessica S Johnson, Anders Jureìus, Radhika Kandaswamy, Robert Karlsson, James L Kennedy, Sarah Kittel-Schneider, Sarah V Knott, James A Knowles, Manolis Kogevinas, Anna C Koller, Ralph Kupka, Catharina Lavebratt, Jacob Lawrence, William B Lawson, Markus Leber, Phil H Lee, Shawn E Levy, Jun Z Li, Chunyu Liu, Susanne Lucae, Anna Maaser, Donald J MacIntyre, Pamela B Mahon, Wolfgang Maier, Lina Martinsson, Steve McCarroll, Peter McGuffin, Melvin G McInnis, James D McKay, Helena Medeiros, Sarah E Medland, Fan Meng, Lili Milani, Grant W Montgomery, Derek W Morris, Thomas W Mühleisen, Niamh Mullins, Hoang Nguyen, Caroline M Nievergelt, Annelie Nordin Adolfsson, Evaristus A Nwulia, Claire O’Donovan, Loes M Olde Loohuis, Anil P S Ori, Lilijana Oruc, Urban Ösby, Roy H Perlis, Amy Perry, Andrea Pfennig, James B Potash, Shaun M Purcell, Eline J Regeer, Andreas Reif, Ceìline S Reinbold, John P Rice, Fabio Rivas, Margarita Rivera, Panos Roussos, Douglas M Ruderfer, Euijung Ryu, Cristina Saìnchez-Mora, Alan F Schatzberg, William A Scheftner, Nicholas J Schork, Cynthia Shannon Weickert, Tatyana Shehktman, Paul D Shilling, Engilbert Sigurdsson, Claire Slaney, Olav B Smeland, Janet L Sobell, Christine Søholm Hansen, Anne T Spijker, David St Clair, Michael Steffens, John S Strauss, Fabian Streit, Jana Strohmaier, Szabolcs Szelinger, Robert C Thompson, Thorgeir E Thorgeirsson, Jens Treutlein, Helmut Vedder, Weiqing Wang, Stanley J Watson, Thomas W Weickert, Stephanie H Witt, Simon Xi, Wei Xu, Allan H Young, Peter Zandi, Peng Zhang, Sebastian Zollner, Rolf Adolfsson, Ingrid Agartz, Martin Alda, Lena Backlund, Bernhard T Baune, Frank Bellivier, Wade H Berrettini, Joanna M Biernacka, Douglas H R Blackwood, Michael Boehnke, Anders D Børglum, Aiden Corvin, Nicholas Craddock, Mark J Daly, Udo Dannlowski, ToÞnu Esko, Bruno Etain, Mark Frye, Janice M Fullerton, Elliot S Gershon, Michael Gill, Fernando Goes, Maria Grigoroiu-Serbanescu, Joanna Hauser, David M Hougaard, Christina M Hultman, Ian Jones, Lisa A Jones, Reneì S Kahn, George Kirov, Mikael Landeìn, Marion Leboyer, Cathryn M Lewis, Qingqin S Li, Jolanta Lissowska, Nicholas G Martin, Fermin Mayoral, Susan L McElroy, Andrew M McIntosh, Francis J McMahon, Ingrid Melle, Andres Metspalu, Philip B Mitchell, Gunnar Morken, Ole Mors, Preben Bo Mortensen, Bertram Müller-Myhsok, Richard M Myers, Benjamin M Neale, Vishwajit Nimgaonkar, Merete Nordentoft, Markus M Nöthen, Michael C O’Donovan, Ketil J Oedegaard, Michael J Owen, Sara A Paciga, Carlos Pato, Michele T Pato, Danielle Posthuma, Josep Antoni Ramos-Quiroga, Marta Ribaseìs, Marcella Rietschel, Guy A Rouleau, Martin Schalling, Peter R Schofield, Thomas G Schulze, Alessandro Serretti, Jordan W Smoller, Hreinn Stefansson, Kari Stefansson, Eystein Stordal, Patrick F Sullivan, Gustavo Turecki, Arne E Vaaler, Eduard Vieta, John B Vincent, Thomas Werge, John I Nurnberger, Naomi R Wray, Arianna Di Florio, Howard J Edenberg, Sven Cichon, Roel A Ophoff, Laura J Scott, Ole A Andreassen, John Kelsoe, and Pamela Sklar
Subjects: Alzheimer’s disease, bipolar disorder, GWAS, pleiotropy, cognitive symptoms, affective symptoms, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Background: Alzheimer’s disease (AD) and bipolar disorder (BIP) are complex traits influenced by numerous common genetic variants, most of which remain to be detected. Clinical and epidemiological evidence suggest that AD and BIP are related. However, it is not established if this relation is of genetic origin. Here, we applied statistical methods based on the conditional false discovery rate (FDR) framework to detect genetic overlap between AD and BIP and utilized this overlap to increase the power to identify common genetic variants associated with either or both traits.Methods: We obtained genome wide association studies data from the International Genomics of Alzheimer’s Project part 1 (17,008 AD cases and 37,154 controls) and the Psychiatric Genetic Consortium Bipolar Disorder Working Group (20,352 BIP cases and 31,358 controls). We used conditional QQ-plots to assess overlap in common genetic variants between AD and BIP. We exploited the genetic overlap to re-rank test-statistics for AD and BIP and improve detection of genetic variants using the conditional FDR framework.Results: Conditional QQ-plots demonstrated a polygenic overlap between AD and BIP. Using conditional FDR, we identified one novel genomic locus associated with AD, and nine novel loci associated with BIP. Further, we identified two novel loci jointly associated with AD and BIP implicating the MARK2 gene (lead SNP rs10792421, conjunctional FDR = 0.030, same direction of effect) and the VAC14 gene (lead SNP rs11649476, conjunctional FDR = 0.022, opposite direction of effect).Conclusion: We found polygenic overlap between AD and BIP and identified novel loci for each trait and two jointly associated loci. Further studies should examine if the shared loci implicating the MARK2 and VAC14 genes could explain parts of the shared and distinct features of AD and BIP.
Published: 2019
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7. Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria.

Author: Felix Day, Tugce Karaderi, Michelle R Jones, Cindy Meun, Chunyan He, Alex Drong, Peter Kraft, Nan Lin, Hongyan Huang, Linda Broer, Reedik Magi, Richa Saxena, Triin Laisk, Margrit Urbanek, M Geoffrey Hayes, Gudmar Thorleifsson, Juan Fernandez-Tajes, Anubha Mahajan, Benjamin H Mullin, Bronwyn G A Stuckey, Timothy D Spector, Scott G Wilson, Mark O Goodarzi, Lea Davis, Barbara Obermayer-Pietsch, André G Uitterlinden, Verneri Anttila, Benjamin M Neale, Marjo-Riitta Jarvelin, Bart Fauser, Irina Kowalska, Jenny A Visser, Marianne Andersen, Ken Ong, Elisabet Stener-Victorin, David Ehrmann, Richard S Legro, Andres Salumets, Mark I McCarthy, Laure Morin-Papunen, Unnur Thorsteinsdottir, Kari Stefansson, andMe Research Team, Unnur Styrkarsdottir, John R B Perry, Andrea Dunaif, Joop Laven, Steve Franks, Cecilia M Lindgren, and Corrine K Welt
Subjects: Genetics, QH426-470
Abstract: Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health.
Published: 2018
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8. Insights into the genetic epidemiology of Crohn's and rare diseases in the Ashkenazi Jewish population.

Author: Manuel A Rivas, Brandon E Avila, Jukka Koskela, Hailiang Huang, Christine Stevens, Matti Pirinen, Talin Haritunians, Benjamin M Neale, Mitja Kurki, Andrea Ganna, Daniel Graham, Benjamin Glaser, Inga Peter, Gil Atzmon, Nir Barzilai, Adam P Levine, Elena Schiff, Nikolas Pontikos, Ben Weisburd, Monkol Lek, Konrad J Karczewski, Jonathan Bloom, Eric V Minikel, Britt-Sabina Petersen, Laurent Beaugerie, Philippe Seksik, Jacques Cosnes, Stefan Schreiber, Bernd Bokemeyer, Johannes Bethge, International IBD Genetics Consortium, NIDDK IBD Genetics Consortium, T2D-GENES Consortium, Graham Heap, Tariq Ahmad, Vincent Plagnol, Anthony W Segal, Stephan Targan, Dan Turner, Paivi Saavalainen, Martti Farkkila, Kimmo Kontula, Aarno Palotie, Steven R Brant, Richard H Duerr, Mark S Silverberg, John D Rioux, Rinse K Weersma, Andre Franke, Luke Jostins, Carl A Anderson, Jeffrey C Barrett, Daniel G MacArthur, Chaim Jalas, Harry Sokol, Ramnik J Xavier, Ann Pulver, Judy H Cho, Dermot P B McGovern, and Mark J Daly
Subjects: Genetics, QH426-470
Abstract: As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim (hosted in part at https://ibd.broadinstitute.org, also available in gnomAD at http://gnomad.broadinstitute.org). We estimate that 34% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 15-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect approximately 30 generations ago, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 148 AJ enriched protein-altering alleles that overlap with "pathogenic" ClinVar alleles (table available at https://github.com/macarthur-lab/clinvar/blob/master/output/clinvar.tsv), including those that account for 10-100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases, especially recessive conditions, including Gaucher disease (GBA, p.Asn409Ser, 8-fold enrichment); Canavan disease (ASPA, p.Glu285Ala, 12-fold enrichment); and Tay-Sachs disease (HEXA, c.1421+1G>C, 27-fold enrichment; p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohn's disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically attempt to evaluate whether strong acting rare alleles, particularly protein-truncating or otherwise large effect-size alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohn's disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are enriched in AJ (p < 0.005), including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population samples (0.97 s.d. higher, p
Published: 2018
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9. Correction: Phenome-wide heritability analysis of the UK Biobank.

Author: Tian Ge, Chia-Yen Chen, Benjamin M Neale, Mert R Sabuncu, and Jordan W Smoller
Subjects: Genetics, QH426-470
Abstract: [This corrects the article DOI: 10.1371/journal.pgen.1006711.].
Published: 2018
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10. Phenome-wide heritability analysis of the UK Biobank.

Author: Tian Ge, Chia-Yen Chen, Benjamin M Neale, Mert R Sabuncu, and Jordan W Smoller
Subjects: Genetics, QH426-470
Abstract: Heritability estimation provides important information about the relative contribution of genetic and environmental factors to phenotypic variation, and provides an upper bound for the utility of genetic risk prediction models. Recent technological and statistical advances have enabled the estimation of additive heritability attributable to common genetic variants (SNP heritability) across a broad phenotypic spectrum. Here, we present a computationally and memory efficient heritability estimation method that can handle large sample sizes, and report the SNP heritability for 551 complex traits derived from the interim data release (152,736 subjects) of the large-scale, population-based UK Biobank, comprising both quantitative phenotypes and disease codes. We demonstrate that common genetic variation contributes to a broad array of quantitative traits and human diseases in the UK population, and identify phenotypes whose heritability is moderated by age (e.g., a majority of physical measures including height and body mass index), sex (e.g., blood pressure related traits) and socioeconomic status (education). Our study represents the first comprehensive phenome-wide heritability analysis in the UK Biobank, and underscores the importance of considering population characteristics in interpreting heritability.
Published: 2017
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11. A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk

Author: Bradley Jermy, Kristi Läll, Brooke N. Wolford, Ying Wang, Kristina Zguro, Yipeng Cheng, Masahiro Kanai, Stavroula Kanoni, Zhiyu Yang, Tuomo Hartonen, Remo Monti, Julian Wanner, Omar Youssef, Estonian Biobank research team, FinnGen, Christoph Lippert, David van Heel, Yukinori Okada, Daniel L. McCartney, Caroline Hayward, Riccardo E. Marioni, Simone Furini, Alessandra Renieri, Alicia R. Martin, Benjamin M. Neale, Kristian Hveem, Reedik Mägi, Aarno Palotie, Henrike Heyne, Nina Mars, Andrea Ganna, and Samuli Ripatti
Subjects: Science
Abstract: Abstract Polygenic scores (PGSs) offer the ability to predict genetic risk for complex diseases across the life course; a key benefit over short-term prediction models. To produce risk estimates relevant to clinical and public health decision-making, it is important to account for varying effects due to age and sex. Here, we develop a novel framework to estimate country-, age-, and sex-specific estimates of cumulative incidence stratified by PGS for 18 high-burden diseases. We integrate PGS associations from seven studies in four countries (N = 1,197,129) with disease incidences from the Global Burden of Disease. PGS has a significant sex-specific effect for asthma, hip osteoarthritis, gout, coronary heart disease and type 2 diabetes (T2D), with all but T2D exhibiting a larger effect in men. PGS has a larger effect in younger individuals for 13 diseases, with effects decreasing linearly with age. We show for breast cancer that, relative to individuals in the bottom 20% of polygenic risk, the top 5% attain an absolute risk for screening eligibility 16.3 years earlier. Our framework increases the generalizability of results from biobank studies and the accuracy of absolute risk estimates by appropriately accounting for age- and sex-specific PGS effects. Our results highlight the potential of PGS as a screening tool which may assist in the early prevention of common diseases.
Published: 2024
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12. No evidence for association of autism with rare heterozygous point mutations in Contactin-Associated Protein-Like 2 (CNTNAP2), or in Other Contactin-Associated Proteins or Contactins.

Author: John D Murdoch, Abha R Gupta, Stephan J Sanders, Michael F Walker, John Keaney, Thomas V Fernandez, Michael T Murtha, Samuel Anyanwu, Gordon T Ober, Melanie J Raubeson, Nicholas M DiLullo, Natalie Villa, Zainabdul Waqar, Catherine Sullivan, Luis Gonzalez, A Jeremy Willsey, So-Yeon Choe, Benjamin M Neale, Mark J Daly, and Matthew W State
Subjects: Genetics, QH426-470
Abstract: Contactins and Contactin-Associated Proteins, and Contactin-Associated Protein-Like 2 (CNTNAP2) in particular, have been widely cited as autism risk genes based on findings from homozygosity mapping, molecular cytogenetics, copy number variation analyses, and both common and rare single nucleotide association studies. However, data specifically with regard to the contribution of heterozygous single nucleotide variants (SNVs) have been inconsistent. In an effort to clarify the role of rare point mutations in CNTNAP2 and related gene families, we have conducted targeted next-generation sequencing and evaluated existing sequence data in cohorts totaling 2704 cases and 2747 controls. We find no evidence for statistically significant association of rare heterozygous mutations in any of the CNTN or CNTNAP genes, including CNTNAP2, placing marked limits on the scale of their plausible contribution to risk.
Published: 2015
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13. Partitioning the heritability of Tourette syndrome and obsessive compulsive disorder reveals differences in genetic architecture.

Author: Lea K Davis, Dongmei Yu, Clare L Keenan, Eric R Gamazon, Anuar I Konkashbaev, Eske M Derks, Benjamin M Neale, Jian Yang, S Hong Lee, Patrick Evans, Cathy L Barr, Laura Bellodi, Fortu Benarroch, Gabriel Bedoya Berrio, Oscar J Bienvenu, Michael H Bloch, Rianne M Blom, Ruth D Bruun, Cathy L Budman, Beatriz Camarena, Desmond Campbell, Carolina Cappi, Julio C Cardona Silgado, Danielle C Cath, Maria C Cavallini, Denise A Chavira, Sylvain Chouinard, David V Conti, Edwin H Cook, Vladimir Coric, Bernadette A Cullen, Dieter Deforce, Richard Delorme, Yves Dion, Christopher K Edlund, Karin Egberts, Peter Falkai, Thomas V Fernandez, Patience J Gallagher, Helena Garrido, Daniel Geller, Simon L Girard, Hans J Grabe, Marco A Grados, Benjamin D Greenberg, Varda Gross-Tsur, Stephen Haddad, Gary A Heiman, Sian M J Hemmings, Ana G Hounie, Cornelia Illmann, Joseph Jankovic, Michael A Jenike, James L Kennedy, Robert A King, Barbara Kremeyer, Roger Kurlan, Nuria Lanzagorta, Marion Leboyer, James F Leckman, Leonhard Lennertz, Chunyu Liu, Christine Lochner, Thomas L Lowe, Fabio Macciardi, James T McCracken, Lauren M McGrath, Sandra C Mesa Restrepo, Rainald Moessner, Jubel Morgan, Heike Muller, Dennis L Murphy, Allan L Naarden, William Cornejo Ochoa, Roel A Ophoff, Lisa Osiecki, Andrew J Pakstis, Michele T Pato, Carlos N Pato, John Piacentini, Christopher Pittenger, Yehuda Pollak, Scott L Rauch, Tobias J Renner, Victor I Reus, Margaret A Richter, Mark A Riddle, Mary M Robertson, Roxana Romero, Maria C Rosàrio, David Rosenberg, Guy A Rouleau, Stephan Ruhrmann, Andres Ruiz-Linares, Aline S Sampaio, Jack Samuels, Paul Sandor, Brooke Sheppard, Harvey S Singer, Jan H Smit, Dan J Stein, E Strengman, Jay A Tischfield, Ana V Valencia Duarte, Homero Vallada, Filip Van Nieuwerburgh, Jeremy Veenstra-Vanderweele, Susanne Walitza, Ying Wang, Jens R Wendland, Herman G M Westenberg, Yin Yao Shugart, Euripedes C Miguel, William McMahon, Michael Wagner, Humberto Nicolini, Danielle Posthuma, Gregory L Hanna, Peter Heutink, Damiaan Denys, Paul D Arnold, Ben A Oostra, Gerald Nestadt, Nelson B Freimer, David L Pauls, Naomi R Wray, S Evelyn Stewart, Carol A Mathews, James A Knowles, Nancy J Cox, and Jeremiah M Scharf
Subjects: Genetics, QH426-470
Abstract: The direct estimation of heritability from genome-wide common variant data as implemented in the program Genome-wide Complex Trait Analysis (GCTA) has provided a means to quantify heritability attributable to all interrogated variants. We have quantified the variance in liability to disease explained by all SNPs for two phenotypically-related neurobehavioral disorders, obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS), using GCTA. Our analysis yielded a heritability point estimate of 0.58 (se = 0.09, p = 5.64e-12) for TS, and 0.37 (se = 0.07, p = 1.5e-07) for OCD. In addition, we conducted multiple genomic partitioning analyses to identify genomic elements that concentrate this heritability. We examined genomic architectures of TS and OCD by chromosome, MAF bin, and functional annotations. In addition, we assessed heritability for early onset and adult onset OCD. Among other notable results, we found that SNPs with a minor allele frequency of less than 5% accounted for 21% of the TS heritability and 0% of the OCD heritability. Additionally, we identified a significant contribution to TS and OCD heritability by variants significantly associated with gene expression in two regions of the brain (parietal cortex and cerebellum) for which we had available expression quantitative trait loci (eQTLs). Finally we analyzed the genetic correlation between TS and OCD, revealing a genetic correlation of 0.41 (se = 0.15, p = 0.002). These results are very close to previous heritability estimates for TS and OCD based on twin and family studies, suggesting that very little, if any, heritability is truly missing (i.e., unassayed) from TS and OCD GWAS studies of common variation. The results also indicate that there is some genetic overlap between these two phenotypically-related neuropsychiatric disorders, but suggest that the two disorders have distinct genetic architectures.
Published: 2013
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14. Analysis of rare, exonic variation amongst subjects with autism spectrum disorders and population controls.

Author: Li Liu, Aniko Sabo, Benjamin M Neale, Uma Nagaswamy, Christine Stevens, Elaine Lim, Corneliu A Bodea, Donna Muzny, Jeffrey G Reid, Eric Banks, Hillary Coon, Mark Depristo, Huyen Dinh, Tim Fennel, Jason Flannick, Stacey Gabriel, Kiran Garimella, Shannon Gross, Alicia Hawes, Lora Lewis, Vladimir Makarov, Jared Maguire, Irene Newsham, Ryan Poplin, Stephan Ripke, Khalid Shakir, Kaitlin E Samocha, Yuanqing Wu, Eric Boerwinkle, Joseph D Buxbaum, Edwin H Cook, Bernie Devlin, Gerard D Schellenberg, James S Sutcliffe, Mark J Daly, Richard A Gibbs, and Kathryn Roeder
Subjects: Genetics, QH426-470
Abstract: We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD.
Published: 2013
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15. Pervasive sharing of genetic effects in autoimmune disease.

Author: Chris Cotsapas, Benjamin F Voight, Elizabeth Rossin, Kasper Lage, Benjamin M Neale, Chris Wallace, Gonçalo R Abecasis, Jeffrey C Barrett, Timothy Behrens, Judy Cho, Philip L De Jager, James T Elder, Robert R Graham, Peter Gregersen, Lars Klareskog, Katherine A Siminovitch, David A van Heel, Cisca Wijmenga, Jane Worthington, John A Todd, David A Hafler, Stephen S Rich, Mark J Daly, and FOCiS Network of Consortia
Subjects: Genetics, QH426-470
Abstract: Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases-as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple-but not all-immune-mediated diseases (SNP-wise P(CPMA)
Published: 2011
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16. Testing for an unusual distribution of rare variants.

Author: Benjamin M Neale, Manuel A Rivas, Benjamin F Voight, David Altshuler, Bernie Devlin, Marju Orho-Melander, Sekar Kathiresan, Shaun M Purcell, Kathryn Roeder, and Mark J Daly
Subjects: Genetics, QH426-470
Abstract: Technological advances make it possible to use high-throughput sequencing as a primary discovery tool of medical genetics, specifically for assaying rare variation. Still this approach faces the analytic challenge that the influence of very rare variants can only be evaluated effectively as a group. A further complication is that any given rare variant could have no effect, could increase risk, or could be protective. We propose here the C-alpha test statistic as a novel approach for testing for the presence of this mixture of effects across a set of rare variants. Unlike existing burden tests, C-alpha, by testing the variance rather than the mean, maintains consistent power when the target set contains both risk and protective variants. Through simulations and analysis of case/control data, we demonstrate good power relative to existing methods that assess the burden of rare variants in individuals.
Published: 2011
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17. Genome-wide association studies in an isolated founder population from the Pacific Island of Kosrae.

Author: Jennifer K Lowe, Julian B Maller, Itsik Pe'er, Benjamin M Neale, Jacqueline Salit, Eimear E Kenny, Jessica L Shea, Ralph Burkhardt, J Gustav Smith, Weizhen Ji, Martha Noel, Jia Nee Foo, Maude L Blundell, Vita Skilling, Laura Garcia, Marcia L Sullivan, Heather E Lee, Anna Labek, Hope Ferdowsian, Steven B Auerbach, Richard P Lifton, Christopher Newton-Cheh, Jan L Breslow, Markus Stoffel, Mark J Daly, David M Altshuler, and Jeffrey M Friedman
Subjects: Genetics, QH426-470
Abstract: It has been argued that the limited genetic diversity and reduced allelic heterogeneity observed in isolated founder populations facilitates discovery of loci contributing to both Mendelian and complex disease. A strong founder effect, severe isolation, and substantial inbreeding have dramatically reduced genetic diversity in natives from the island of Kosrae, Federated States of Micronesia, who exhibit a high prevalence of obesity and other metabolic disorders. We hypothesized that genetic drift and possibly natural selection on Kosrae might have increased the frequency of previously rare genetic variants with relatively large effects, making these alleles readily detectable in genome-wide association analysis. However, mapping in large, inbred cohorts introduces analytic challenges, as extensive relatedness between subjects violates the assumptions of independence upon which traditional association test statistics are based. We performed genome-wide association analysis for 15 quantitative traits in 2,906 members of the Kosrae population, using novel approaches to manage the extreme relatedness in the sample. As positive controls, we observe association to known loci for plasma cholesterol, triglycerides, and C-reactive protein and to a compelling candidate loci for thyroid stimulating hormone and fasting plasma glucose. We show that our study is well powered to detect common alleles explaining >/=5% phenotypic variance. However, no such large effects were observed with genome-wide significance, arguing that even in such a severely inbred population, common alleles typically have modest effects. Finally, we show that a majority of common variants discovered in Caucasians have indistinguishable effect sizes on Kosrae, despite the major differences in population genetics and environment.
Published: 2009
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18. Multi-PGS enhances polygenic prediction by combining 937 polygenic scores

Author: Clara Albiñana, Zhihong Zhu, Andrew J. Schork, Andrés Ingason, Hugues Aschard, Isabell Brikell, Cynthia M. Bulik, Liselotte V. Petersen, Esben Agerbo, Jakob Grove, Merete Nordentoft, David M. Hougaard, Thomas Werge, Anders D. Børglum, Preben Bo Mortensen, John J. McGrath, Benjamin M. Neale, Florian Privé, and Bjarni J. Vilhjálmsson
Subjects: Science
Abstract: Abstract The predictive performance of polygenic scores (PGS) is largely dependent on the number of samples available to train the PGS. Increasing the sample size for a specific phenotype is expensive and takes time, but this sample size can be effectively increased by using genetically correlated phenotypes. We propose a framework to generate multi-PGS from thousands of publicly available genome-wide association studies (GWAS) with no need to individually select the most relevant ones. In this study, the multi-PGS framework increases prediction accuracy over single PGS for all included psychiatric disorders and other available outcomes, with prediction R 2 increases of up to 9-fold for attention-deficit/hyperactivity disorder compared to a single PGS. We also generate multi-PGS for phenotypes without an existing GWAS and for case-case predictions. We benchmark the multi-PGS framework against other methods and highlight its potential application to new emerging biobanks.
Published: 2023
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19. FAVOR: functional annotation of variants online resource and annotator for variation across the human genome.

Author: Hufeng Zhou, Theodore Arapoglou, Xihao Li, Zilin Li, Xiuwen Zheng 0001, Jill Moore, Abhijith Asok, Sushant Kumar, Elizabeth E. Blue, Steven Buyske, Nancy J. Cox, Adam Felsenfeld, Mark Gerstein, Eimear Kenny, Bingshan Li, Tara Cox Matise, Anthony Philippakis, Heidi L. Rehm, Heidi J. Sofia, Grace Snyder, Zhiping Weng, Benjamin M. Neale, Shamil R. Sunyaev, and Xihong Lin
Published: 2023
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20. Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia

Author: Yu-Han H. Hsu, Greta Pintacuda, Ruize Liu, Eugeniu Nacu, April Kim, Kalliopi Tsafou, Natalie Petrossian, William Crotty, Jung Min Suh, Jackson Riseman, Jacqueline M. Martin, Julia C. Biagini, Daya Mena, Joshua K.T. Ching, Edyta Malolepsza, Taibo Li, Tarjinder Singh, Tian Ge, Shawn B. Egri, Benjamin Tanenbaum, Caroline R. Stanclift, Annie M. Apffel, Steven A. Carr, Monica Schenone, Jake Jaffe, Nadine Fornelos, Hailiang Huang, Kevin C. Eggan, Kasper Lage, Stephan Ripke, Benjamin M. Neale, Aiden Corvin, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau, Jr., Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberley D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chan, Eric Y.H. Chen, Wei Cheng, Eric FC. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, David Curtis, Michael Davidson, Kenneth L. Davis, Franziska Degenhardt, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Giulio Genovese, Lyudmila Georgieva, Ina Giegling, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Marian L. Hamshere, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Annette M. Hartmann, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, David M. Hougaard, Masashi Ikeda, Inge Joa, Antonio Julià, René S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, James A. Knowles, Bettina Konte, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee, S. Hong Lee, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lönnqvist, Milan Macek, Patrik K.E. Magnusson, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Andrew M. McIntosh, Sandra Meier, Carin J. Meijer, Bela Melegh, Ingrid Melle, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Lili Milani, Vihra Milanova, Younes Mokrab, Derek W. Morris, Ole Mors, Kieran C. Murphy, Robin M. Murray, Inez Myin-Germeys, Bertram Müller-Myhsok, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O'Callaghan, Colm O'Dushlaine, F. Anthony O'Neill, Sang-Yun Oh, Ann Olincy, Line Olsen, Jim Van Os, Christos Pantelis, George N. Papadimitriou, Sergi Papiol, Elena Parkhomenko, Michele T. Pato, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietiläinen, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Alan R. Sanders, Ulrich Schall, Christian R. Schubert, Thomas G. Schulze, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Jianxin Shi, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Jordan W. Smoller, Hon-Cheong So, Chris C.A. Spencer, Eli A. Stahl, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Söderman, Srinivas Thirumalai, Draga Toncheva, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Naomi R. Wray, Kari Stefansson, Peter M. Visscher, Rolf Adolfsson, Ole A. Andreassen, Douglas H.R. Blackwood, Elvira Bramon, Joseph D. Buxbaum, Anders D. Børglum, Sven Cichon, Ariel Darvasi, Enrico Domenici, Hannelore Ehrenreich, Tõnu Esko, Pablo V. Gejman, Michael Gill, Hugh Gurling, Christina M. Hultman, Nakao Iwata, Assen V. Jablensky, Erik G. Jönsson, Kenneth S. Kendler, George Kirov, Jo Knight, Todd Lencz, Douglas F. Levinson, Qingqin S. Li, Jianjun Liu, Anil K. Malhotra, Steven A. McCarroll, Andrew McQuillin, Jennifer L. Moran, Preben B. Mortensen, Bryan J. Mowry, Markus M. Nöthen, Roel A. Ophoff, Michael J. Owen, Aarno Palotie, Carlos N. Pato, Tracey L. Petryshen, Danielle Posthuma, Marcella Rietschel, Brien P. Riley, Dan Rujescu, Pak C. Sham, Pamela Sklar, David St Clair, Daniel R. Weinberger, Jens R. Wendland, Thomas Werge, Mark J. Daly, Patrick F. Sullivan, Michael C. O'Donovan, Shengying Qin, Akira Sawa, Rene Kahn, Kyung Sue Hong, Wenzhao Shi, Ming Tsuang, Masanari Itokawa, Gang Feng, Stephen J. Glatt, Xiancang Ma, Jinsong Tang, Yunfeng Ruan, Feng Zhu, Yasue Horiuchi, Byung Dae Lee, Eun-Jeong Joo, Woojae Myung, Kyooseob Ha, Hong-Hee Won, Ji Hyung Baek, Young Chul Chung, Sung-Wan Kim, Agung Kusumawardhani, Wei J. Chen, Hai-Gwo Hwu, Akitoyo Hishimoto, Ikuo Otsuka, Ichiro Sora, Tomoko Toyota, Takeo Yoshikawa, Hiroshi Kunugi, Kotaro Hattori, Sayuri Ishiwata, Shusuke Numata, Tetsuro Ohmori, Makoto Arai, Yuji Ozeki, Kumiko Fujii, Se Joo Kim, Heon-Jeong Lee, Yong Min Ahn, Se Hyun Kim, Kazufumi Akiyama, Kazutaka Shimoda, and Makoto Kinoshita
Subjects: Molecular interaction, Developmental neuroscience, Cellular neuroscience, Proteomics, Science
Abstract: Summary: Genetics have nominated many schizophrenia risk genes and identified convergent signals between schizophrenia and neurodevelopmental disorders. However, functional interpretation of the nominated genes in the relevant brain cell types is often lacking. We executed interaction proteomics for six schizophrenia risk genes that have also been implicated in neurodevelopment in human induced cortical neurons. The resulting protein network is enriched for common variant risk of schizophrenia in Europeans and East Asians, is down-regulated in layer 5/6 cortical neurons of individuals affected by schizophrenia, and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in individuals with schizophrenia and bipolar disorder. Our findings showcase brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and its related disorders.
Published: 2023
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21. Ancestry: How researchers use it and what they mean by it

Author: Bege Dauda, Santiago J. Molina, Danielle S. Allen, Agustin Fuentes, Nayanika Ghosh, Madelyn Mauro, Benjamin M. Neale, Aaron Panofsky, Mashaal Sohail, Sarah R. Zhang, and Anna C. F. Lewis
Subjects: population descriptors, ancestry, genetic ancestry, race, ethnicity, population labeling, Genetics, QH426-470
Abstract: Background: Ancestry is often viewed as a more objective and less objectionable population descriptor than race or ethnicity. Perhaps reflecting this, usage of the term “ancestry” is rapidly growing in genetics research, with ancestry groups referenced in many situations. The appropriate usage of population descriptors in genetics research is an ongoing source of debate. Sound normative guidance should rest on an empirical understanding of current usage; in the case of ancestry, questions about how researchers use the concept, and what they mean by it, remain unanswered.Methods: Systematic literature analysis of 205 articles at least tangentially related to human health from diverse disciplines that use the concept of ancestry, and semi-structured interviews with 44 lead authors of some of those articles.Results: Ancestry is relied on to structure research questions and key methodological approaches. Yet researchers struggle to define it, and/or offer diverse definitions. For some ancestry is a genetic concept, but for many—including geneticists—ancestry is only tangentially related to genetics. For some interviewees, ancestry is explicitly equated to ethnicity; for others it is explicitly distanced from it. Ancestry is operationalized using multiple data types (including genetic variation and self-reported identities), though for a large fraction of articles (26%) it is impossible to tell which data types were used. Across the literature and interviews there is no consistent understanding of how ancestry relates to genetic concepts (including genetic ancestry and population structure), nor how these genetic concepts relate to each other. Beyond this conceptual confusion, practices related to summarizing patterns of genetic variation often rest on uninterrogated conventions. Continental labels are by far the most common type of label applied to ancestry groups. We observed many instances of slippage between reference to ancestry groups and racial groups.Conclusion: Ancestry is in practice a highly ambiguous concept, and far from an objective counterpart to race or ethnicity. It is not uniquely a “biological” construct, and it does not represent a “safe haven” for researchers seeking to avoid evoking race or ethnicity in their work. Distinguishing genetic ancestry from ancestry more broadly will be a necessary part of providing conceptual clarity.
Published: 2023
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22. Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

Author: Ying Wang, Shinichi Namba, Esteban Lopera, Sini Kerminen, Kristin Tsuo, Kristi Läll, Masahiro Kanai, Wei Zhou, Kuan-Han Wu, Marie-Julie Favé, Laxmi Bhatta, Philip Awadalla, Ben Brumpton, Patrick Deelen, Kristian Hveem, Valeria Lo Faro, Reedik Mägi, Yoshinori Murakami, Serena Sanna, Jordan W. Smoller, Jasmina Uzunovic, Brooke N. Wolford, Cristen Willer, Eric R. Gamazon, Nancy J. Cox, Ida Surakka, Yukinori Okada, Alicia R. Martin, Jibril Hirbo, Kuan-Han H. Wu, Humaira Rasheed, Jibril B. Hirbo, Arjun Bhattacharya, Huiling Zhao, Esteban A. Lopera-Maya, Sinéad B. Chapman, Juha Karjalainen, Mitja Kurki, Maasha Mutaamba, Juulia J. Partanen, Ben M. Brumpton, Sameer Chavan, Tzu-Ting Chen, Michelle Daya, Yi Ding, Yen-Chen A. Feng, Christopher R. Gignoux, Sarah E. Graham, Whitney E. Hornsby, Nathan Ingold, Ruth Johnson, Triin Laisk, Kuang Lin, Jun Lv, Iona Y. Millwood, Priit Palta, Anita Pandit, Michael H. Preuss, Unnur Thorsteinsdottir, Matthew Zawistowski, Xue Zhong, Archie Campbell, Kristy Crooks, Geertruida H. de Bock, Nicholas J. Douville, Sarah Finer, Lars G. Fritsche, Christopher J. Griffiths, Yu Guo, Karen A. Hunt, Takahiro Konuma, Riccardo E. Marioni, Jansonius Nomdo, Snehal Patil, Nicholas Rafaels, Anne Richmond, Jonathan A. Shortt, Peter Straub, Ran Tao, Brett Vanderwerff, Kathleen C. Barnes, Marike Boezen, Zhengming Chen, Chia-Yen Chen, Judy Cho, George Davey Smith, Hilary K. Finucane, Lude Franke, Andrea Ganna, Tom R. Gaunt, Tian Ge, Hailiang Huang, Jennifer Huffman, Jukka T. Koskela, Clara Lajonchere, Matthew H. Law, Liming Li, Cecilia M. Lindgren, Ruth J.F. Loos, Stuart MacGregor, Koichi Matsuda, Catherine M. Olsen, David J. Porteous, Jordan A. Shavit, Harold Snieder, Richard C. Trembath, Judith M. Vonk, David Whiteman, Stephen J. Wicks, Cisca Wijmenga, John Wright, Jie Zheng, Xiang Zhou, Michael Boehnke, Daniel H. Geschwind, Caroline Hayward, Eimear E. Kenny, Yen-Feng Lin, Hilary C. Martin, Sarah E. Medland, Aarno V. Palotie, Bogdan Pasaniuc, Kari Stefansson, David A. van Heel, Robin G. Walters, Sebastian Zöllner, Cristen J. Willer, Mark J. Daly, and Benjamin M. Neale
Subjects: Global-Biobank Meta-analysis Initiative, polygenic risk scores, multi-ancestry genetic prediction, accuracy heterogeneity, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract: Summary: Polygenic risk scores (PRSs) have been widely explored in precision medicine. However, few studies have thoroughly investigated their best practices in global populations across different diseases. We here utilized data from Global Biobank Meta-analysis Initiative (GBMI) to explore methodological considerations and PRS performance in 9 different biobanks for 14 disease endpoints. Specifically, we constructed PRSs using pruning and thresholding (P + T) and PRS-continuous shrinkage (CS). For both methods, using a European-based linkage disequilibrium (LD) reference panel resulted in comparable or higher prediction accuracy compared with several other non-European-based panels. PRS-CS overall outperformed the classic P + T method, especially for endpoints with higher SNP-based heritability. Notably, prediction accuracy is heterogeneous across endpoints, biobanks, and ancestries, especially for asthma, which has known variation in disease prevalence across populations. Overall, we provide lessons for PRS construction, evaluation, and interpretation using GBMI resources and highlight the importance of best practices for PRS in the biobank-scale genomics era.
Published: 2023
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23. RICOPILI: Rapid Imputation for COnsortias PIpeLIne.

Author: Max Lam, Swapnil Awasthi, Hunna J. Watson, Jackie Goldstein, Georgia Panagiotaropoulou, Vassily Trubetskoy, Robert Karlsson, Oleksander Frei, Chun-Chieh Fan, Ward De Witte, Nina R. Mota, Niamh Mullins, Kim Brügger, Sang Hong Lee, Naomi R. Wray, Nora Skarabis, Hailiang Huang, Benjamin M. Neale, Mark J. Daly, Manuel Mattheisen, Raymond Walters, and Stephan Ripke
Published: 2020
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24. A structural variation reference for medical and population genetics.

Author: Ryan L. Collins, Harrison Brand, Konrad J. Karczewski, Xuefang Zhao, Jessica Alföldi, Laurent C. Francioli, Amit V. Khera, Chelsea Lowther, Laura D. Gauthier, Harold Wang, Nicholas A. Watts, Matthew Solomonson, Alexander Baumann, Ruchi Munshi, Mark Walker, Christopher W. Whelan, Yongqing Huang, Ted Brookings, Ted Sharpe, Matthew R. Stone, Elise Valkanas, Jack Fu, Grace Tiao, Kristen M. Laricchia, Valentín Ruano-Rubio, Christine Stevens, Namrata Gupta, Caroline Cusick, Lauren Margolin, Irina M. Armean, Eric Banks, Louis Bergelson, Kristian Cibulskis, Kristen M. Connolly, Miguel Covarrubias, Beryl B. Cummings, Mark J. Daly, Stacey Donnelly, Yossi Farjoun, Steven Ferriera, Stacey Gabriel, Jeff Gentry, Thibault Jeandet, Diane Kaplan, Christopher Llanwarne, Eric V. Minikel, Benjamin M. Neale, Sam Novod, Anne H. O'Donnell-Luria, Nikelle Petrillo, Timothy Poterba, David Roazen, Andrea Saltzman, Kaitlin E. Samocha, Molly Schleicher, Cotton Seed, José Soto, Kathleen Tibbetts, Charlotte Tolonen, Christopher Vittal, Gordon Wade, Arcturus Wang, Qingbo Wang, James S. Ware, Ben Weisburd, Nicola Whiffin, Carlos A. Aguilar Salinas, Tariq Ahmad 0003, Christine M. Albert, Diego Ardissino, Gil Atzmon, John Barnard, Laurent Beaugerie, Emelia J. Benjamin, Michael Boehnke, Lori L. Bonnycastle, Erwin P. Bottinger, Donald W. Bowden, Matthew J. Bown, John C. Chambers, Juliana C. Chan, Daniel Chasman, Judy Cho, Mina K. Chung, Bruce Cohen, Adolfo Correa, Dana Dabelea, Dawood Darbar, Ravindranath Duggirala, Josée Dupuis, Patrick T. Ellinor, Roberto Elosua, Jeanette Erdmann, Tõnu Esko, Martti Färkkilä, Jose Florez, Andre Franke, Gad Getz, Benjamin Glaser, Stephen J. Glatt, David Goldstein, Clicerio Gonzalez, Leif Groop, Christopher A. Haiman, Craig Hanis, Matthew Harms, Mikko Hiltunen, Matti M. Holi, Christina M. Hultman, Mikko Kallela, Jaakko Kaprio, Sekar Kathiresan, Bong-Jo Kim, Young Jin Kim 0003, George Kirov, Jaspal Kooner, Seppo Koskinen, Harlan M. Krumholz, Subra Kugathasan, Soo Heon Kwak, Markku Laakso, Terho Lehtimäki, Ruth J. F. Loos, Steven A. Lubitz, Ronald C. W. Ma, Daniel G. MacArthur, Jaume Marrugat, Kari M. Mattila, Steven A. McCarroll, Mark I. McCarthy, Dermot McGovern, Ruth McPherson, James B. Meigs, Olle Melander, Andres Metspalu, Peter M. Nilsson, Michael C. O'Donovan, Dost öngür, Lorena Orozco, Michael J. Owen, Colin N. A. Palmer, Aarno Palotie, Kyong Soo Park, Carlos Pato, Ann E. Pulver, Nazneen Rahman, Anne M. Remes, John D. Rioux, Samuli Ripatti, Dan M. Roden, Danish Saleheen, Veikko Salomaa, Nilesh J. Samani, Jeremiah Scharf, Heribert Schunkert, Moore B. Shoemaker, Pamela Sklar, Hilkka Soininen, Harry Sokol, Tim Spector, Patrick F. Sullivan, Jaana Suvisaari, E. Shyong Tai, Yik Ying Teo, Tuomi Tiinamaija, Ming Tsuang, Dan Turner, Teresa Tusie-Luna, Erkki Vartiainen, Hugh Watkins, Rinse K. Weersma, Maija Wessman, James G. Wilson, Ramnik J. Xavier, Kent D. Taylor, Henry J. Lin, Stephen S. Rich, Wendy S. Post, Yii-Der Ida Chen, Jerome I. Rotter, Chad Nusbaum, Anthony A. Philippakis, Eric S. Lander, and Michael E. Talkowski
Published: 2020
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25. Genetic Risk Score for Intracranial Aneurysms: Prediction of Subarachnoid Hemorrhage and Role in Clinical Heterogeneity

Author: Mark K. Bakker, Jos P. Kanning, Gad Abraham, Amy E. Martinsen, Bendik S. Winsvold, John-Anker Zwart, Romain Bourcier, Tomonobu Sawada, Masaru Koido, Yoichiro Kamatani, Sandrine Morel, Philippe Amouyel, Stéphanie Debette, Philippe Bijlenga, Takiy Berrandou, Santhi K. Ganesh, Nabila Bouatia-Naji, Gregory Jones, Matthew Bown, Gabriel J.E. Rinkel, Jan H. Veldink, Ynte M. Ruigrok, Anne Hege Aamodt, Anne Heidi Skogholt, Ben M Brumpton, Cristen J Willer, Else C Sandset, Espen S Kristoffersen, Hanne Ellekjær, Ingrid Heuch, Jonas B Nielsen, Knut Hagen, Kristian Hveem, Lars G Fritsche, Laurent F Thomas, Linda M Pedersen, Maiken E Gabrielsen, Oddgeir L Holmen, Sigrid Børte, Wei Zhou, Shérine Abboud, Massimo Pandolfo, Vincent Thijs, Didier Leys, Marie Bodenant, Fabien Louillet, Emmanuel Touzé, Jean-Louis Mas, Yves Samson, Sara Leder, Anne Léger, Sandrine Deltour, Sophie Crozier, Isabelle Méresse, Sandrine Canaple, Olivier Godefroy, Maurice Giroud, Yannick Béjot, Pierre Decavel, Elizabeth Medeiros, Paola Montiel, Thierry Moulin, Fabrice Vuillier, Jean Dallongeville, Antti J Metso, Tiina Metso, Turgut Tatlisumak, Caspar Grond-Ginsbach, Christoph Lichy, Manja Kloss, Inge Werner, Marie-Luise Arnold, Michael Dos Santos, Armin Grau, Martin Dichgans, Constanze Thomas-Feles, Ralf Weber, Tobias Brandt, Alessandro Pezzini, Valeria De Giuli, Filomena Caria, Loris Poli, Alessandro Padovani, Anna Bersano, Silvia Lanfranconi, Simone Beretta, Carlo Ferrarese, Giacomo Giacolone, Stefano Paolucci, Philippe Lyrer, Stefan Engelter, Felix Fluri, Florian Hatz, Dominique Gisler, Leo Bonati, Henrik Gensicke, Margareth Amort, Hugh Markus, Jennifer Majersik, Bradford Worrall, Andrew Southerland, John Cole, Steven Kittner, Evangelos Evangelou, Helen R Warren, He Gao, Georgios Ntritsos, Niki Dimou, Tonu Esko, Reedik Mägi, Lili Milani, Peter Almgren, Thibaud Boutin, Jun Ding, Franco Giulianini, Elizabeth G Holliday, Anne U Jackson, Ruifang Li-Gao, Wei-Yu Lin, Jian’an Luan, Massimo Mangino, Christopher Oldmeadow, Bram Peter Prins, Yong Qian, Muralidharan Sargurupremraj, Nabi Shah, Praveen Surendran, Sébastien Thériault, Niek Verweij, Sara M Willems, Jing-Hua Zhao, John Connell, Renée de Mutsert, Alex SF Doney, Martin Farrall, Cristina Menni, Andrew D Morris, Raymond Noordam, Guillaume Paré, Neil R Poulter, Denis C Shields, Alice Stanton, Simon Thom, Gonçalo Abecasis, Najaf Amin, Dan E Arking, Kristin L Ayers, Caterina M Barbieri, Chiara Batini, Joshua C Bis, Tineka Blake, Murielle Bochud, Michael Boehnke, Eric Boerwinkle, Dorret I Boomsma, Erwin P Bottinger, Peter S Braund, Marco Brumat, Archie Campbell, Harry Campbell, Aravinda Chakravarti, John C Chambers, Ganesh Chauhan, Marina Ciullo, Massimiliano Cocca, Francis Collins, Heather J Cordell, Gail Davies, Martin H de Borst, Eco J de Geus, Ian J Deary, Joris Deelen, Fabiola Del Greco M, Cumhur Yusuf Demirkale, Marcus Dörr, Georg B Ehret, Roberto Elosua, Stefan Enroth, A Mesut Erzurumluoglu, Teresa Ferreira, Mattias Frånberg, Oscar H Franco, Ilaria Gandin, Paolo Gasparini, Vilmantas Giedraitis, Christian Gieger, Giorgia Girotto, Anuj Goel, Alan J Gow, Vilmundur Gudnason, Xiuqing Guo, Ulf Gyllensten, Anders Hamsten, Tamara B Harris, Sarah E Harris, Catharina A Hartman, Aki S Havulinna, Andrew A Hicks, Edith Hofer, Albert Hofman, Jouke-Jan Hottenga, Jennifer E Huffman, Shih-Jen Hwang, Erik Ingelsson, Alan James, Rick Jansen, Marjo-Riitta Jarvelin, Roby Joehanes, Åsa Johansson, Andrew D Johnson, Peter K Joshi, Pekka Jousilahti, J Wouter Jukema, Antti Jula, Mika Kähönen, Sekar Kathiresan, Bernard D Keavney, Kay-Tee Khaw, Paul Knekt, Joanne Knight, Ivana Kolcic, Jaspal S Kooner, Seppo Koskinen, Kati Kristiansson, Zoltan Kutalik, Maris Laan, Marty Larson, Lenore J Launer, Benjamin Lehne, Terho Lehtimäki, David CM Liewald, Li Lin, Lars Lind, Cecilia M Lindgren, YongMei Liu, Ruth JF Loos, Lorna M Lopez, Yingchang Lu, Leo-Pekka Lyytikäinen, Anubha Mahajan, Chrysovalanto Mamasoula, Jaume Marrugat, Jonathan Marten, Yuri Milaneschi, Anna Morgan, Andrew P Morris, Alanna C Morrison, Peter J Munson, Mike A Nalls, Priyanka Nandakumar, Christopher P Nelson, Teemu Niiranen, Ilja M Nolte, Teresa Nutile, Albertine J Oldehinkel, Ben A Oostra, Paul F O’Reilly, Elin Org, Sandosh Padmanabhan, Walter Palmas, Aarno Palotie, Alison Pattie, Brenda WJH Penninx, Markus Perola, Annette Peters, Ozren Polasek, Peter P Pramstaller, Quang Tri Nguyen, Olli T Raitakari, Rainer Rettig, Kenneth Rice, Paul M Ridker, Janina S Ried, Harriëtte Riese, Samuli Ripatti, Antonietta Robino, Lynda M Rose, Jerome I Rotter, Igor Rudan, Daniela Ruggiero, Yasaman Saba, Cinzia F Sala, Veikko Salomaa, Nilesh J Samani, Antti-Pekka Sarin, Reinhold Schmidt, Helena Schmidt, Nick Shrine, David Siscovick, Albert V Smith, Harold Snieder, Siim Sõber, Rossella Sorice, John M Starr, David J Stott, David P Strachan, Rona J Strawbridge, Johan Sundström, Morris A Swertz, Kent D Taylor, Alexander Teumer, Martin D Tobin, Maciej Tomaszewski, Daniela Toniolo, Michela Traglia, Stella Trompet, Jaakko Tuomilehto, Christophe Tzourio, André G Uitterlinden, Ahmad Vaez, Peter J van der Most, Cornelia M van Duijn, Germaine C Verwoert, Veronique Vitart, Uwe Völker, Peter Vollenweider, Dragana Vuckovic, Hugh Watkins, Sarah H Wild, Gonneke Willemsen, James F Wilson, Alan F Wright, Jie Yao, Tatijana Zemunik, Weihua Zhang, John R Attia, Adam S Butterworth, Daniel I Chasman, David Conen, Francesco Cucca, John Danesh, Caroline Hayward, Joanna MM Howson, Markku Laakso, Edward G Lakatta, Claudia Langenberg, Olle Melander, Dennis O Mook-Kanamori, Colin NA Palmer, Lorenz Risch, Robert A Scott, Rodney J Scott, Peter Sever, Tim D Spector, Pim van der Harst, Nicholas J Wareham, Eleftheria Zeggini, Daniel Levy, Patricia B Munroe, Christopher Newton-Cheh, Morris J Brown, Andres Metspalu, Bruce M. Psaty, Louise V Wain, Paul Elliott, Mark J Caulfield, Padhraig Gormley, Verneri Anttila, Priit Palta, Tune H Pers, Kai-How Farh, Ester Cuenca-Leon, Mikko Muona, Nicholas A Furlotte, Tobias Kurth, Andres Ingason, George McMahon, Lannie Ligthart, Gisela M Terwindt, Mikko Kallela, Tobias M Freilinger, Caroline Ran, Scott G Gordon, Anine H Stam, Stacy Steinberg, Guntram Borck, Markku Koiranen, Lydia Quaye, Hieab H H Adams, Juho Wedenoja, David A Hinds, Julie E Buring, Markus Schürks, Maria Gudlaug Hrafnsdottir, Hreinn Stefansson, Susan M Ring, Brenda W J H Penninx, Markus Färkkilä, Ville Artto, Mari Kaunisto, Salli Vepsäläinen, Rainer Malik, Andrew C Heath, Pamela A F Madden, Nicholas G Martin, Grant W Montgomery, Mitja I Kurki, Mart Kals, Kalle Pärn, Eija Hämäläinen, Hailiang Huang, Andrea E Byrnes, Lude Franke, Jie Huang, Evie Stergiakouli, Phil H Lee, Cynthia Sandor, Caleb Webber, Zameel Cader, Bertram Muller-Myhsok, Stefan Schreiber, Thomas Meitinger, Johan G Eriksson, Kauko Heikkilä, Elizabeth Loehrer, Andre G Uitterlinden, Lynn Cherkas, Audun Stubhaug, Christopher S Nielsen, Minna Männikkö, Evelin Mihailov, Hartmut Göbel, Ann-Louise Esserlind, Anne Francke Christensen, Thomas Folkmann Hansen, Thomas Werge, Jaakko Kaprio, Arpo J Aromaa, Olli Raitakari, M Arfan Ikram, Tim Spector, Marjo-Riitta Järvelin, Christian Kubisch, Michel D Ferrari, Andrea C Belin, Maija Wessman, Arn M J M van den Maagdenberg, George Davey Smith, Kari Stefansson, Nicholas Eriksson, Mark J Daly, Benjamin M Neale, Jes Olesen, Dale R Nyholt, Masato Akiyama, Varinder S. Alg, Joseph P. Broderick, Ben M. Brumpton, Jérôme Dauvillier, Hubert Desal, Christian Dina, Christoph M. Friedrich, Emília I. Gaál-Paavola, Jean-Christophe Gentric, Sven Hirsch, Isabel C. Hostettler, Henry Houlden, Juha E. Jääskeläinen, Marianne Bakke Johnsen, Liming Li, Kuang Lin, Antti Lindgren, Olivier Martin, Koichi Matsuda, Iona Y. Millwood, Olivier Naggara, Mika Niemelä, Joanna Pera, Richard Redon, Guy A. Rouleau, Marie Søfteland Sandvei, Sabine Schilling, Eimad Shotar, Agnieszka Slowik, Chikashi Terao, W. M. Monique Verschuren, Robin G. Walters, David J. Werring, Cristen J. Willer, Daniel Woo, Bradford B. Worrall, Sirui Zhou, Biological Psychology, Amsterdam Reproduction & Development, APH - Mental Health, APH - Methodology, AMS - Sports, AMS - Ageing & Vitality, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Systems Ecology, Sociology and Social Gerontology, Bakker, Mark K., Kanning, Jos P., Abraham, Gad, Martinsen, Amy E., Winsvold, Bendik S., Zwart, John-Anker, Bourcier, Romain, Sawada, Tomonobu, Koido, Masaru, Kamatani, Yoichiro, Morel, Sandrine, Amouyel, Philippe, Debette, Stéphanie, Bijlenga, Philippe, Berrandou, Takiy, Ganesh, Santhi K., Bouatia-Naji, Nabila, Jones, Gregory, Bown, Matthew, Rinkel, Gabriel J. E., Veldink, Jan H., Ruigrok, Ynte M., Girotto, G., All-In Stroke, Hunt, Group, Cadisp, Consortium for Blood Pressure, International, Headache Genetics Consortium, International, Stroke Genetics Consortium (ISGC) Intracranial Aneurysm Working Group, International, Utrecht University [Utrecht], Baker Heart and Diabetes Institute (AUSTRALIA), University of Melbourne, University of Oslo (UiO), Norwegian University of Science and Technology (NTNU), Oslo University Hospital [Oslo], Centre hospitalier universitaire de Nantes (CHU Nantes), unité de recherche de l'institut du thorax UMR1087 UMR6291 (ITX), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Nantes Université - UFR de Médecine et des Techniques Médicales (Nantes Univ - UFR MEDECINE), Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), The University of Tokyo (UTokyo), RIKEN Center for Integrative Medical Sciences [Yokohama] (RIKEN IMS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Hôpital Universitaire de Genève = University Hospitals of Geneva (HUG), Université de Genève = University of Geneva (UNIGE), Excellence Laboratory LabEx DISTALZ, Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Bordeaux [Bordeaux], Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), University of Michigan Medical School [Ann Arbor], University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, University of Otago [Dunedin, Nouvelle-Zélande], University of Leicester, Laboratoire de Neurosciences Fonctionnelles et Pathologies - UR UPJV 4559 (LNFP), Université de Picardie Jules Verne (UPJV), CHU Amiens-Picardie, HUNT All-In Stroke, CADISP group, International Consortium for Blood Pressure, International Headache Genetics Consortium, International Stroke Genetics Consortium (ISGC) Intracranial Aneurysm Working Group: Anne Hege Aamodt, Anne Heidi Skogholt, Ben M Brumpton, Cristen J Willer, Else C Sandset, Espen S Kristoffersen, Hanne Ellekjær, Ingrid Heuch, Jonas B Nielsen, Knut Hagen, Kristian Hveem, Lars G Fritsche, Laurent F Thomas, Linda M Pedersen, Maiken E Gabrielsen, Oddgeir L Holmen, Sigrid Børte, Wei Zhou, Shérine Abboud, Massimo Pandolfo, Vincent Thijs, Didier Leys, Marie Bodenant, Fabien Louillet, Emmanuel Touzé, Jean-Louis Mas, Yves Samson, Sara Leder, Anne Léger, Sandrine Deltour, Sophie Crozier, Isabelle Méresse, Sandrine Canaple, Olivier Godefroy, Maurice Giroud, Yannick Béjot, Pierre Decavel, Elizabeth Medeiros, Paola Montiel, Thierry Moulin, Fabrice Vuillier, Jean Dallongeville, Antti J Metso, Tiina Metso, Turgut Tatlisumak, Caspar Grond-Ginsbach, Christoph Lichy, Manja Kloss, Inge Werner, Marie-Luise Arnold, Michael Dos Santos, Armin Grau, Martin Dichgans, Constanze Thomas-Feles, Ralf Weber, Tobias Brandt, Alessandro Pezzini, Valeria De Giuli, Filomena Caria, Loris Poli, Alessandro Padovani, Anna Bersano, Silvia Lanfranconi, Simone Beretta, Carlo Ferrarese, Giacomo Giacolone, Stefano Paolucci, Philippe Lyrer, Stefan Engelter, Felix Fluri, Florian Hatz, Dominique Gisler, Leo Bonati, Henrik Gensicke, Margareth Amort, Hugh Markus, Jennifer Majersik, Bradford Worrall, Andrew Southerland, John Cole, Steven Kittner, Evangelos Evangelou, Helen R Warren, He Gao, Georgios Ntritsos, Niki Dimou, Tonu Esko, Reedik Mägi, Lili Milani, Peter Almgren, Thibaud Boutin, Jun Ding, Franco Giulianini, Elizabeth G Holliday, Anne U Jackson, Ruifang Li-Gao, Wei-Yu Lin, Jian'an Luan, Massimo Mangino, Christopher Oldmeadow, Bram Peter Prins, Yong Qian, Muralidharan Sargurupremraj, Nabi Shah, Praveen Surendran, Sébastien Thériault, Niek Verweij, Sara M Willems, Jing-Hua Zhao, John Connell, Renée de Mutsert, Alex Sf Doney, Martin Farrall, Cristina Menni, Andrew D Morris, Raymond Noordam, Guillaume Paré, Neil R Poulter, Denis C Shields, Alice Stanton, Simon Thom, Gonçalo Abecasis, Najaf Amin, Dan E Arking, Kristin L Ayers, Caterina M Barbieri, Chiara Batini, Joshua C Bis, Tineka Blake, Murielle Bochud, Michael Boehnke, Eric Boerwinkle, Dorret I Boomsma, Erwin P Bottinger, Peter S Braund, Marco Brumat, Archie Campbell, Harry Campbell, Aravinda Chakravarti, John C Chambers, Ganesh Chauhan, Marina Ciullo, Massimiliano Cocca, Francis Collins, Heather J Cordell, Gail Davies, Martin H de Borst, Eco J de Geus, Ian J Deary, Joris Deelen, Fabiola Del Greco M, Cumhur Yusuf Demirkale, Marcus Dörr, Georg B Ehret, Roberto Elosua, Stefan Enroth, A Mesut Erzurumluoglu, Teresa Ferreira, Mattias Frånberg, Oscar H Franco, Ilaria Gandin, Paolo Gasparini, Vilmantas Giedraitis, Christian Gieger, Giorgia Girotto, Anuj Goel, Alan J Gow, Vilmundur Gudnason, Xiuqing Guo, Ulf Gyllensten, Anders Hamsten, Tamara B Harris, Sarah E Harris, Catharina A Hartman, Aki S Havulinna, Andrew A Hicks, Edith Hofer, Albert Hofman, Jouke-Jan Hottenga, Jennifer E Huffman, Shih-Jen Hwang, Erik Ingelsson, Alan James, Rick Jansen, Marjo-Riitta Jarvelin, Roby Joehanes, Åsa Johansson, Andrew D Johnson, Peter K Joshi, Pekka Jousilahti, J Wouter Jukema, Antti Jula, Mika Kähönen, Sekar Kathiresan, Bernard D Keavney, Kay-Tee Khaw, Paul Knekt, Joanne Knight, Ivana Kolcic, Jaspal S Kooner, Seppo Koskinen, Kati Kristiansson, Zoltan Kutalik, Maris Laan, Marty Larson, Lenore J Launer, Benjamin Lehne, Terho Lehtimäki, David Cm Liewald, Li Lin, Lars Lind, Cecilia M Lindgren, YongMei Liu, Ruth Jf Loos, Lorna M Lopez, Yingchang Lu, Leo-Pekka Lyytikäinen, Anubha Mahajan, Chrysovalanto Mamasoula, Jaume Marrugat, Jonathan Marten, Yuri Milaneschi, Anna Morgan, Andrew P Morris, Alanna C Morrison, Peter J Munson, Mike A Nalls, Priyanka Nandakumar, Christopher P Nelson, Teemu Niiranen, Ilja M Nolte, Teresa Nutile, Albertine J Oldehinkel, Ben A Oostra, Paul F O'Reilly, Elin Org, Sandosh Padmanabhan, Walter Palmas, Aarno Palotie, Alison Pattie, Brenda Wjh Penninx, Markus Perola, Annette Peters, Ozren Polasek, Peter P Pramstaller, Quang Tri Nguyen, Olli T Raitakari, Rainer Rettig, Kenneth Rice, Paul M Ridker, Janina S Ried, Harriëtte Riese, Samuli Ripatti, Antonietta Robino, Lynda M Rose, Jerome I Rotter, Igor Rudan, Daniela Ruggiero, Yasaman Saba, Cinzia F Sala, Veikko Salomaa, Nilesh J Samani, Antti-Pekka Sarin, Reinhold Schmidt, Helena Schmidt, Nick Shrine, David Siscovick, Albert V Smith, Harold Snieder, Siim Sõber, Rossella Sorice, John M Starr, David J Stott, David P Strachan, Rona J Strawbridge, Johan Sundström, Morris A Swertz, Kent D Taylor, Alexander Teumer, Martin D Tobin, Maciej Tomaszewski, Daniela Toniolo, Michela Traglia, Stella Trompet, Jaakko Tuomilehto, Christophe Tzourio, André G Uitterlinden, Ahmad Vaez, Peter J van der Most, Cornelia M van Duijn, Germaine C Verwoert, Veronique Vitart, Uwe Völker, Peter Vollenweider, Dragana Vuckovic, Hugh Watkins, Sarah H Wild, Gonneke Willemsen, James F Wilson, Alan F Wright, Jie Yao, Tatijana Zemunik, Weihua Zhang, John R Attia, Adam S Butterworth, Daniel I Chasman, David Conen, Francesco Cucca, John Danesh, Caroline Hayward, Joanna Mm Howson, Markku Laakso, Edward G Lakatta, Claudia Langenberg, Olle Melander, Dennis O Mook-Kanamori, Colin Na Palmer, Lorenz Risch, Robert A Scott, Rodney J Scott, Peter Sever, Tim D Spector, Pim van der Harst, Nicholas J Wareham, Eleftheria Zeggini, Daniel Levy, Patricia B Munroe, Christopher Newton-Cheh, Morris J Brown, Andres Metspalu, Bruce M Psaty, Louise V Wain, Paul Elliott, Mark J Caulfield, Padhraig Gormley, Verneri Anttila, Priit Palta, Tonu Esko, Tune H Pers, Kai-How Farh, Ester Cuenca-Leon, Mikko Muona, Nicholas A Furlotte, Tobias Kurth, Andres Ingason, George McMahon, Lannie Ligthart, Gisela M Terwindt, Mikko Kallela, Tobias M Freilinger, Caroline Ran, Scott G Gordon, Anine H Stam, Stacy Steinberg, Guntram Borck, Markku Koiranen, Lydia Quaye, Hieab H H Adams, Terho Lehtimäki, Antti-Pekka Sarin, Juho Wedenoja, David A Hinds, Julie E Buring, Markus Schürks, Paul M Ridker, Maria Gudlaug Hrafnsdottir, Hreinn Stefansson, Susan M Ring, Jouke-Jan Hottenga, Brenda W J H Penninx, Markus Färkkilä, Ville Artto, Mari Kaunisto, Salli Vepsäläinen, Rainer Malik, Andrew C Heath, Pamela A F Madden, Nicholas G Martin, Grant W Montgomery, Mitja I Kurki, Mart Kals, Reedik Mägi, Kalle Pärn, Eija Hämäläinen, Hailiang Huang, Andrea E Byrnes, Lude Franke, Jie Huang, Evie Stergiakouli, Phil H Lee, Cynthia Sandor, Caleb Webber, Zameel Cader, Bertram Muller-Myhsok, Stefan Schreiber, Thomas Meitinger, Johan G Eriksson, Veikko Salomaa, Kauko Heikkilä, Elizabeth Loehrer, Andre G Uitterlinden, Albert Hofman, Cornelia M van Duijn, Lynn Cherkas, Linda M Pedersen, Audun Stubhaug, Christopher S Nielsen, Minna Männikkö, Evelin Mihailov, Lili Milani, Hartmut Göbel, Ann-Louise Esserlind, Anne Francke Christensen, Thomas Folkmann Hansen, Thomas Werge, Jaakko Kaprio, Arpo J Aromaa, Olli Raitakari, M Arfan Ikram, Tim Spector, Marjo-Riitta Järvelin, Andres Metspalu, Christian Kubisch, David P Strachan, Michel D Ferrari, Andrea C Belin, Martin Dichgans, Maija Wessman, Arn M J M van den Maagdenberg, Dorret I Boomsma, George Davey Smith, Kari Stefansson, Nicholas Eriksson, Mark J Daly, Benjamin M Neale, Jes Olesen, Daniel I Chasman, Dale R Nyholt, Aarno Palotie, Masato Akiyama, Varinder S Alg, Sigrid Børte, Joseph P Broderick, Ben M Brumpton, Jérôme Dauvillier, Hubert Desal, Christian Dina, Christoph M Friedrich, Emília I Gaál-Paavola, Jean-Christophe Gentric, Sven Hirsch, Isabel C Hostettler, Henry Houlden, Kristian Hveem, Juha E Jääskeläinen, Marianne Bakke Johnsen, Liming Li, Kuang Lin, Antti Lindgren, Olivier Martin, Koichi Matsuda, Iona Y Millwood, Olivier Naggara, Mika Niemelä, Joanna Pera, Richard Redon, Guy A Rouleau, Marie Søfteland Sandvei, Sabine Schilling, Eimad Shotar, Agnieszka Slowik, Chikashi Terao, W M Monique Verschuren, Robin G Walters, David J Werring, Cristen J Willer, Daniel Woo, Bradford B Worrall, Sirui Zhou, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, and Admin, Oskar
Subjects: Advanced and Specialized Nursing, Incidence, risk assessment, Smoking/epidemiology, intracranial aneurysm, genetic heterogeneity, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Risk Factors, Intracranial Aneurysm/epidemiology, Humans, Subarachnoid Hemorrhage/epidemiology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, genetics, Neurology (clinical), aneurysmal subarachnoid hemorrhage, genetic, Cardiology and Cardiovascular Medicine
Abstract: Background: Recently, common genetic risk factors for intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (ASAH) were found to explain a large amount of disease heritability and therefore have potential to be used for genetic risk prediction. We constructed a genetic risk score to (1) predict ASAH incidence and IA presence (combined set of unruptured IA and ASAH) and (2) assess its association with patient characteristics. Methods: A genetic risk score incorporating genetic association data for IA and 17 traits related to IA (so-called metaGRS) was created using 1161 IA cases and 407 392 controls from the UK Biobank population study. The metaGRS was validated in combination with risk factors blood pressure, sex, and smoking in 828 IA cases and 68 568 controls from the Nordic HUNT population study. Furthermore, we assessed association between the metaGRS and patient characteristics in a cohort of 5560 IA patients. Results: Per SD increase of metaGRS, the hazard ratio for ASAH incidence was 1.34 (95% CI, 1.20–1.51) and the odds ratio for IA presence 1.09 (95% CI, 1.01–1.18). Upon including the metaGRS on top of clinical risk factors, the concordance index to predict ASAH hazard increased from 0.63 (95% CI, 0.59–0.67) to 0.65 (95% CI, 0.62–0.69), while prediction of IA presence did not improve. The metaGRS was statistically significantly associated with age at ASAH (β=−4.82×10 −3 per year [95% CI, −6.49×10 −3 to −3.14×10 −3 ]; P =1.82×10 −8 ), and location of IA at the internal carotid artery (odds ratio=0.92 [95% CI, 0.86–0.98]; P =0.0041). Conclusions: The metaGRS was predictive of ASAH incidence, although with limited added value over clinical risk factors. The metaGRS was not predictive of IA presence. Therefore, we do not recommend using this metaGRS in daily clinical care. Genetic risk does partly explain the clinical heterogeneity of IA warranting prioritization of clinical heterogeneity in future genetic prediction studies of IA and ASAH.
Published: 2023
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26. Analysis of genetic dominance in the UK Biobank

Author: Duncan S. Palmer, Wei Zhou, Liam Abbott, Emilie M. Wigdor, Nikolas Baya, Claire Churchhouse, Cotton Seed, Tim Poterba, Daniel King, Masahiro Kanai, Alex Bloemendal, and Benjamin M. Neale
Subjects: Multidisciplinary
Abstract: Classical statistical genetics theory defines dominance as any deviation from a purely additive, or dosage, effect of a genotype on a trait, which is known as the dominance deviation. Dominance is well documented in plant and animal breeding. Outside of rare monogenic traits, however, evidence in humans is limited. We systematically examined common genetic variation across 1060 traits in a large population cohort (UK Biobank, N = 361,194 samples analyzed) for evidence of dominance effects. We then developed a computationally efficient method to rapidly assess the aggregate contribution of dominance deviations to heritability. Lastly, observing that dominance associations are inherently less correlated between sites at a genomic locus than their additive counterparts, we explored whether they may be leveraged to identify causal variants more confidently.
Published: 2023
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27. Polygenic architecture of rare coding variation across 394,783 exomes

Author: Daniel J. Weiner, Ajay Nadig, Karthik A. Jagadeesh, Kushal K. Dey, Benjamin M. Neale, Elise B. Robinson, Konrad J. Karczewski, and Luke J. O’Connor
Subjects: Multidisciplinary
Published: 2023
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28. LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis.

Author: Jie Zheng 0006, Mesut A. Erzurumluoglu, Benjamin L. Elsworth, John P. Kemp, Laurence J. Howe, Philip C. Haycock, Gibran Hemani, Katherine Tansey, Charles Laurin, Early Genetics, Lifecourse Epidemiology (EAGLE) Eczema Consortium, Beate St. Pourcain, Nicole M. Warrington, Hilary K. Finucane, Alkes L. Price, Brendan K. Bulik-Sullivan, Verneri Anttila, Lavinia Paternoster, Tom R. Gaunt, David M. Evans 0002, and Benjamin M. Neale
Published: 2017
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29. Genetic structure correlates with ethnolinguistic diversity in eastern and southern Africa

Author: Nastassja Koen, Wilfred E. Injera, Roxanne James, Edith Kwobah, Dan J. Stein, Sohini Ramachandran, Abebaw Fekadu, Anne Stevenson, Alicia R. Martin, Karestan C. Koenen, Rocky E. Stroud, Solomon Teferra, Gabriel Kigen, Zukiswa Zingela, Elizabeth G. Atkinson, Henry Musinguzi, Linnet Ongeri, Allan Kalungi, Charles R. Newton, Fred K. Ashaba, Yakov Pichkar, NeuroGAP-Psychosis Study Team, Welelta Shiferaw, Bizu Gelaye, Melkam Alemayehu, Rehema M. Mwema, Benjamin M. Neale, Mark Baker, Carter P. Newman, Nicole Creanza, Tamrat Abebe, Joseph Kyebuzibwa, Zan Koenig, Shareefa Dalvie, Lori B. Chibnik, Mark J. Daly, Raj Ramesar, Lerato Majara, Lukoye Atwoli, Dickens Akena, Symon M. Kariuki, Stella Gichuru, and Team, NeuroGAP-Psychosis Study
Subjects: Genetic diversity, medicine.medical_specialty, Genetic Structures, media_common.quotation_subject, Black People, Genetic Variation, Genealogy, Africa, Southern, Geography, Variation (linguistics), Genetics, Population, Genetic variation, Genetic structure, medicine, Genetics, Medical genetics, Humans, Three generations, Genetics (clinical), Diversity (politics), media_common
Abstract: SummaryAfrican populations are the most diverse in the world yet are sorely underrepresented in medical genetics research. Here, we examine the structure of African populations using genetic and comprehensive multigenerational ethnolinguistic data from the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) consisting of 900 individuals from Ethiopia, Kenya, South Africa, and Uganda. We find that self-reported language classifications meaningfully tag underlying genetic variation that would be missed with consideration of geography alone, highlighting the importance of culture in shaping genetic diversity. Leveraging our uniquely rich multi-generational ethnolinguistic metadata, we track language transmission through the pedigree, observing the disappearance of several languages in our cohort as well as notable shifts in frequency over three generations. We find suggestive evidence for the rate of language transmission in matrilineal groups having been higher than that for patrilineal ones. We highlight both the diversity of variation within the African continent, as well as how within-Africa variation can be informative for broader variant interpretation; many variants appearing rare elsewhere are common in parts of Africa. The work presented here improves the understanding of the spectrum of genetic variation in African populations and highlights the enormous and complex genetic and ethnolinguistic diversity within Africa.
Published: 2022
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30. Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia

Author: Duncan S. Palmer, Daniel P. Howrigan, Sinéad B. Chapman, Rolf Adolfsson, Nick Bass, Douglas Blackwood, Marco P. M. Boks, Chia-Yen Chen, Claire Churchhouse, Aiden P. Corvin, Nicholas Craddock, David Curtis, Arianna Di Florio, Faith Dickerson, Nelson B. Freimer, Fernando S. Goes, Xiaoming Jia, Ian Jones, Lisa Jones, Lina Jonsson, Rene S. Kahn, Mikael Landén, Adam E. Locke, Andrew M. McIntosh, Andrew McQuillin, Derek W. Morris, Michael C. O’Donovan, Roel A. Ophoff, Michael J. Owen, Nancy L. Pedersen, Danielle Posthuma, Andreas Reif, Neil Risch, Catherine Schaefer, Laura Scott, Tarjinder Singh, Jordan W. Smoller, Matthew Solomonson, David St. Clair, Eli A. Stahl, Annabel Vreeker, James T. R. Walters, Weiqing Wang, Nicholas A. Watts, Robert Yolken, Peter P. Zandi, Benjamin M. Neale, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Psychiatry, Child and Adolescent Psychiatry / Psychology, Human genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, and Amsterdam Reproduction & Development (AR&D)
Subjects: Bipolar Disorder, Human Genome, A Kinase Anchor Proteins, Biological Sciences, Serious Mental Illness, Medical and Health Sciences, Article, Brain Disorders, Mental Health, SDG 3 - Good Health and Well-being, Clinical Research, Exome Sequencing, Schizophrenia, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Exome, Aetiology, Genome-Wide Association Study, Biotechnology, Developmental Biology
Abstract: We report results from the Bipolar Exome (BipEx) collaboration analysis of whole-exome sequencing of 13,933 patients with bipolar disorder (BD) matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in patients with BD among genes under strong evolutionary constraint in both major BD subtypes. We find enrichment of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from genome-wide association studies (GWASs) of BD, however, are not significantly enriched for ultra-rare PTVs. Combining gene-level results with SCHEMA, AKAP11 emerges as a definitive risk gene (odds ratio (OR) = 7.06, P = 2.83 × 10−9). At the protein level, AKAP-11 interacts with GSK3B, the hypothesized target of lithium, a primary treatment for BD. Our results lend support to BD’s polygenicity, demonstrating a role for rare coding variation as a significant risk factor in BD etiology.
Published: 2022
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31. Wrestling with Social and Behavioral Genomics: Risks, Potential Benefits, and Ethical Responsibility

Author: Michelle N. Meyer, Paul S. Appelbaum, Daniel J. Benjamin, Shawneequa L. Callier, Nathaniel Comfort, Dalton Conley, Jeremy Freese, Nanibaa' A. Garrison, Evelynn M. Hammonds, K. Paige Harden, Sandra Soo‐Jin Lee, Alicia R. Martin, Daphne Oluwaseun Martschenko, Benjamin M. Neale, Rohan H. C. Palmer, James Tabery, Eric Turkheimer, Patrick Turley, and Erik Parens
Subjects: Philosophy, Issues, ethics and legal aspects, Health (social science), Health Policy, General Medicine
Published: 2023
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32. Genome-wide Association Study Points to Novel Locus for Gilles de la Tourette Syndrome

Author: Fotis Tsetsos, Apostolia Topaloudi, Pritesh Jain, Zhiyu Yang, Dongmei Yu, Petros Kolovos, Zeynep Tumer, Renata Rizzo, Andreas Hartmann, Christel Depienne, Yulia Worbe, Kirsten R. Müller-Vahl, Danielle C. Cath, Dorret I. Boomsma, Tomasz Wolanczyk, Cezary Zekanowski, Csaba Barta, Zsofia Nemoda, Zsanett Tarnok, Shanmukha S. Padmanabhuni, Joseph D. Buxbaum, Dorothy Grice, Jeffrey Glennon, Hreinn Stefansson, Bastian Hengerer, Evangelia Yannaki, John A. Stamatoyannopoulos, Noa Benaroya-Milshtein, Francesco Cardona, Tammy Hedderly, Isobel Heyman, Chaim Huyser, Pablo Mir, Astrid Morer, Norbert Mueller, Alexander Munchau, Kerstin J. Plessen, Cesare Porcelli, Veit Roessner, Susanne Walitza, Anette Schrag, Davide Martino, Jay A. Tischfield, Gary A. Heiman, A. Jeremy Willsey, Andrea Dietrich, Lea K. Davis, James J. Crowley, Carol A. Mathews, Jeremiah M. Scharf, Marianthi Georgitsi, Pieter J. Hoekstra, Peristera Paschou, Cathy L. Barr, James R. Batterson, Cheston Berlin, Cathy L. Budman, Giovanni Coppola, Nancy J. Cox, Sabrina Darrow, Yves Dion, Nelson B. Freimer, Marco A. Grados, Erica Greenberg, Matthew E. Hirschtritt, Alden Y. Huang, Cornelia Illmann, Robert A. King, Roger Kurlan, James F. Leckman, Gholson J. Lyon, Irene A. Malaty, William M. McMahon, Benjamin M. Neale, Michael S. Okun, Lisa Osiecki, Mary M. Robertson, Guy A. Rouleau, Paul Sandor, Harvey S. Singer, Jan H. Smit, Jae Hoon Sul, Christos Androutsos, Entela Basha, Luca Farkas, Jakub Fichna, Piotr Janik, Mira Kapisyzi, Iordanis Karagiannidis, Anastasia Koumoula, Peter Nagy, Joanna Puchala, Natalia Szejko, Urszula Szymanska, Vaia Tsironi, Alan Apter, Juliane Ball, Benjamin Bodmer, Emese Bognar, Judith Buse, Marta Correa Vela, Carolin Fremer, Blanca Garcia-Delgar, Mariangela Gulisano, Annelieke Hagen, Julie Hagstrøm, Marcos Madruga-Garrido, Alessandra Pellico, Daphna Ruhrman, Jaana Schnell, Paola Rosaria Silvestri, Liselotte Skov, Tamar Steinberg, Friederike Tagwerker Gloor, Victoria L. Turner, Elif Weidinger, John Alexander, Tamas Aranyi, Wim R. Buisman, Jan K. Buitelaar, Nicole Driessen, Petros Drineas, Siyan Fan, Natalie J. Forde, Sarah Gerasch, Odile A. van den Heuvel, Cathrine Jespersgaard, Ahmad S. Kanaan, Harald E. Möller, Muhammad S. Nawaz, Ester Nespoli, Luca Pagliaroli, Geert Poelmans, Petra J.W. Pouwels, Francesca Rizzo, Dick J. Veltman, Ysbrand D. van der Werf, Joanna Widomska, Nuno R. Zilhäo, Lawrence W. Brown, Keun-Ah Cheon, Barbara J. Coffey, Thomas V. Fernandez, Donald L. Gilbert, Hyun Ju Hong, Laura Ibanez-Gomez, Eun-Joo Kim, Young Key Kim, Young-Shin Kim, Yun-Joo Koh, Sodahm Kook, Samuel Kuperman, Bennett L. Leventhal, Athanasios Maras, Tara L. Murphy, Eun-Young Shin, Dong-Ho Song, Jungeun Song, Matthew W. State, Frank Visscher, Sheng Wang, Samuel H. Zinner, Psychiatry, APH - Mental Health, APH - Methodology, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Anatomy and neurosciences, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Neurodegeneration, Radiology and nuclear medicine, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Systems & Network Neuroscience, Biological Psychology, and Amsterdam Reproduction & Development
Subjects: meta-analysis, Medizin, GWAS, Biological Psychiatry, NR2F1, Tourette Syndrome
Abstract: Background: Tourette syndrome (TS) is a childhood-onset neurodevelopmental disorder of complex genetic architecture and is characterized by multiple motor tics and at least one vocal tic persisting for more than 1 year. Methods: We performed a genome-wide meta-analysis integrating a novel TS cohort with previously published data, resulting in a sample size of 6133 individuals with TS and 13,565 ancestry-matched control participants. Results: We identified a genome-wide significant locus on chromosome 5q15. Integration of expression quantitative trait locus, Hi-C (high-throughput chromosome conformation capture), and genome-wide association study data implicated the NR2F1 gene and associated long noncoding RNAs within the 5q15 locus. Heritability partitioning identified statistically significant enrichment in brain tissue histone marks, while polygenic risk scoring of brain volume data identified statistically significant associations with right and left thalamus volumes and right putamen volume. Conclusions: Our work presents novel insights into the neurobiology of TS, thereby opening up new directions for future studies.
Published: 2023
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33. Nuclear genetic control of mtDNA copy number and heteroplasmy in humans

Author: Rahul Gupta, Masahiro Kanai, Timothy J. Durham, Kristin Tsuo, Jason G. McCoy, Patrick F. Chinnery, Konrad J. Karczewski, Sarah E. Calvo, Benjamin M. Neale, and Vamsi K. Mootha
Subjects: Article
Abstract: Human mitochondria contain a high copy number, maternally transmitted genome (mtDNA) that encodes 13 proteins required for oxidative phosphorylation. Heteroplasmy arises when multiple mtDNA variants co-exist in an individual and can exhibit complex dynamics in disease and in aging. As all proteins involved in mtDNA replication and maintenance are nuclear-encoded, heteroplasmy levels can, in principle, be under nuclear genetic control, however this has never been shown in humans. Here, we develop algorithms to quantify mtDNA copy number (mtCN) and heteroplasmy levels using blood-derived whole genome sequences from 274,832 individuals of diverse ancestry and perform GWAS to identify nuclear loci controlling these traits. After careful correction for blood cell composition, we observe that mtCN declines linearly with age and is associated with 92 independent nuclear genetic loci. We find that nearly every individual carries heteroplasmic variants that obey two key patterns: (1) heteroplasmic single nucleotide variants are somatic mutations that accumulate sharply after age 70, while (2) heteroplasmic indels are maternally transmitted as mtDNA mixtures with resulting levels influenced by 42 independent nuclear loci involved in mtDNA replication, maintenance, and novel pathways. These nuclear loci do not appear to act by mtDNA mutagenesis, but rather, likely act by conferring a replicative advantage to specific mtDNA molecules. As an illustrative example, the most common heteroplasmy we identify is a length variant carried by >50% of humans at position m.302 within a G-quadruplex known to serve as a replication switch. We find that this heteroplasmic variant exertscis-acting genetic control over mtDNA abundance and is itself undertrans-acting genetic control of nuclear loci encoding protein components of this regulatory switch. Our study showcases how nuclear haplotype can privilege the replication of specific mtDNA molecules to shape mtCN and heteroplasmy dynamics in the human population.
Published: 2023

34. An Ethical Framework for Research Using Genetic Ancestry

Author: Anna C. F. Lewis, Santiago J. Molina, Paul S. Appelbaum, Bege Dauda, Agustin Fuentes, Stephanie M. Fullerton, Nanibaa’ A. Garrison, Nayanika Ghosh, Robert C. Green, Evelynn M. Hammonds, Janina M. Jeff, David S. Jones, Eimear E. Kenny, Peter Kraft, Madelyn Mauro, Anil P. S. Ori, Aaron Panofsky, Mashaal Sohail, Benjamin M. Neale, and Danielle S. Allen
Subjects: Issues, ethics and legal aspects, History and Philosophy of Science, Health Policy, General Medicine
Published: 2023
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35. Meta-analysis fine-mapping is often miscalibrated at single-variant resolution

Author: Masahiro Kanai, Roy Elzur, Wei Zhou, Mark J. Daly, Hilary K. Finucane, Kuan-Han H. Wu, Humaira Rasheed, Kristin Tsuo, Jibril B. Hirbo, Ying Wang, Arjun Bhattacharya, Huiling Zhao, Shinichi Namba, Ida Surakka, Brooke N. Wolford, Valeria Lo Faro, Esteban A. Lopera-Maya, Kristi Läll, Marie-Julie Favé, Juulia J. Partanen, Sinéad B. Chapman, Juha Karjalainen, Mitja Kurki, Mutaamba Maasha, Ben M. Brumpton, Sameer Chavan, Tzu-Ting Chen, Michelle Daya, Yi Ding, Yen-Chen A. Feng, Lindsay A. Guare, Christopher R. Gignoux, Sarah E. Graham, Whitney E. Hornsby, Nathan Ingold, Said I. Ismail, Ruth Johnson, Triin Laisk, Kuang Lin, Jun Lv, Iona Y. Millwood, Sonia Moreno-Grau, Kisung Nam, Priit Palta, Anita Pandit, Michael H. Preuss, Chadi Saad, Shefali Setia-Verma, Unnur Thorsteinsdottir, Jasmina Uzunovic, Anurag Verma, Matthew Zawistowski, Xue Zhong, Nahla Afifi, Kawthar M. Al-Dabhani, Asma Al Thani, Yuki Bradford, Archie Campbell, Kristy Crooks, Geertruida H. de Bock, Scott M. Damrauer, Nicholas J. Douville, Sarah Finer, Lars G. Fritsche, Eleni Fthenou, Gilberto Gonzalez-Arroyo, Christopher J. Griffiths, Yu Guo, Karen A. Hunt, Alexander Ioannidis, Nomdo M. Jansonius, Takahiro Konuma, Ming Ta Michael Lee, Arturo Lopez-Pineda, Yuta Matsuda, Riccardo E. Marioni, Babak Moatamed, Marco A. Nava-Aguilar, Kensuke Numakura, Snehal Patil, Nicholas Rafaels, Anne Richmond, Agustin Rojas-Muñoz, Jonathan A. Shortt, Peter Straub, Ran Tao, Brett Vanderwerff, Manvi Vernekar, Yogasudha Veturi, Kathleen C. Barnes, Marike Boezen, Zhengming Chen, Chia-Yen Chen, Judy Cho, George Davey Smith, Lude Franke, Eric R. Gamazon, Andrea Ganna, Tom R. Gaunt, Tian Ge, Hailiang Huang, Jennifer Huffman, Nicholas Katsanis, Jukka T. Koskela, Clara Lajonchere, Matthew H. Law, Liming Li, Cecilia M. Lindgren, Ruth J.F. Loos, Stuart MacGregor, Koichi Matsuda, Catherine M. Olsen, David J. Porteous, Jordan A. Shavit, Harold Snieder, Tomohiro Takano, Richard C. Trembath, Judith M. Vonk, David C. Whiteman, Stephen J. Wicks, Cisca Wijmenga, John Wright, Jie Zheng, Xiang Zhou, Philip Awadalla, Michael Boehnke, Carlos D. Bustamante, Nancy J. Cox, Segun Fatumo, Daniel H. Geschwind, Caroline Hayward, Kristian Hveem, Eimear E. Kenny, Seunggeun Lee, Yen-Feng Lin, Hamdi Mbarek, Reedik Mägi, Hilary C. Martin, Sarah E. Medland, Yukinori Okada, Aarno V. Palotie, Bogdan Pasaniuc, Daniel J. Rader, Marylyn D. Ritchie, Serena Sanna, Jordan W. Smoller, Kari Stefansson, David A. van Heel, Robin G. Walters, Sebastian Zöllner, null Biobank of the Americas, null Biobank Japan Project, null BioMe, null BioVU, null CanPath - Ontario Health Study, null China Kadoorie Biobank Collaborative Group, null Colorado Center for Personalized Medicine, null deCODE Genetics, null Estonian Biobank, FinnGen, null Generation Scotland, null Genes & Health Research Team, null LifeLines, null Mass General Brigham Biobank, null Michigan Genomics Initiative, null National Biobank of Korea, null Penn Medicine BioBank, null Qatar Biobank, null The Qskin Sun and Health Study, null Taiwan Biobank, null The Hunt Study, null Ucla Atlas Community Health Initiative, null Uganda Genome Resource, null Uk Biobank, Alicia R. Martin, Cristen J. Willer, Benjamin M. Neale, Institute for Molecular Medicine Finland, Samuli Olli Ripatti / Principal Investigator, Complex Disease Genetics, Genomics of Neurological and Neuropsychiatric Disorders, Data Science Genetic Epidemiology Lab, Research Programs Unit, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, and University of Helsinki
Subjects: biobank, meta-analysis, genome-wide association study, fine-mapping, Genetics, 1184 Genetics, developmental biology, physiology, GWAS, 3111 Biomedicine, heterogeneity, summary statistics, Biochemistry, Genetics and Molecular Biology (miscellaneous), linkage disequilibrium, miscalibration
Abstract: Funding Information: We acknowledge all the participants and researchers of the 23 biobanks that have contributed to the GBMI. Biobank-specific acknowledgments are included in the Data S3 . We thank H. Huang, A.R. Martin, B.M. Neale, Y. Okada, K. Tsuo, J.C. Ulirsch, Y. Wang, and all the members of Finucane and Daly labs for their helpful feedback. M.K. was supported by a Nakajima Foundation Fellowship and the Masason Foundation . H.K.F. was funded by NIH grant DP5 OD024582 . Publisher Copyright: © 2022 The Author(s) Meta-analysis is pervasively used to combine multiple genome-wide association studies (GWASs). Fine-mapping of meta-analysis studies is typically performed as in a single-cohort study. Here, we first demonstrate that heterogeneity (e.g., of sample size, phenotyping, imputation) hurts calibration of meta-analysis fine-mapping. We propose a summary statistics-based quality-control (QC) method, suspicious loci analysis of meta-analysis summary statistics (SLALOM), that identifies suspicious loci for meta-analysis fine-mapping by detecting outliers in association statistics. We validate SLALOM in simulations and the GWAS Catalog. Applying SLALOM to 14 meta-analyses from the Global Biobank Meta-analysis Initiative (GBMI), we find that 67% of loci show suspicious patterns that call into question fine-mapping accuracy. These predicted suspicious loci are significantly depleted for having nonsynonymous variants as lead variant (2.7×; Fisher's exact p = 7.3 × 10−4). We find limited evidence of fine-mapping improvement in the GBMI meta-analyses compared with individual biobanks. We urge extreme caution when interpreting fine-mapping results from meta-analysis of heterogeneous cohorts.
Published: 2022

36. A scoping review of guidelines for the use of race, ethnicity, and ancestry reveals widespread consensus but also points of ongoing disagreement

Author: Madelyn Mauro, Danielle S. Allen, Bege Dauda, Santiago J. Molina, Benjamin M. Neale, and Anna C.F. Lewis
Subjects: Problem Behavior, Consensus, Asian People, Genetics, Ethnicity, Humans, Review, Genetics (clinical), Research Personnel
Abstract: The use of population descriptors such as race, ethnicity, and ancestry in science, medicine, and public health has a long, complicated, and at times dark history, particularly for genetics, given the field’s perceived importance for understanding between-group differences. The historical and potential harms that come with irresponsible use of these categories suggests a clear need for definitive guidance about when and how they can be used appropriately. However, while many prior authors have provided such guidance, no established consensus exists, and the extant literature has not been examined for implied consensus and sources of disagreement. Here, we present the results of a scoping review of published normative recommendations regarding the use of population categories, particularly in genetics research. Following PRISMA guidelines, we extracted recommendations from n = 121 articles matching inclusion criteria. Articles were published consistently throughout the time period examined and in a broad range of journals, demonstrating an ongoing and interdisciplinary perceived need for guidance. Examined recommendations fall under one of eight themes identified during analysis. Seven are characterized by broad agreement across articles; one, “appropriate definitions of population categories and contexts for use,” revealed substantial fundamental disagreement among articles. Additionally, while many articles focus on the inappropriate use of race, none fundamentally problematize ancestry. This work can be a resource to researchers looking for normative guidance on the use of population descriptors and can orient authors of future guidelines to this complex field, thereby contributing to the development of more effective future guidelines for genetics research.
Published: 2022

37. Improving fine-mapping by modeling infinitesimal effects

Author: Ran Cui, Roy A Elzur, Masahiro Kanai, Jacob C Ulirsch, Omer Weissbrod, Mark J Daly, Benjamin M Neale, Zhou Fan, and Hilary K Finucane
Abstract: Fine-mapping aims to identify genetic variants that causally impact a given phenotype. State-of-the-art Bayesian fine-mapping algorithms (for example: SuSiE1, FINEMAP2,3, ABF4, and COJO5-ABF) are widely applied in practice6–11, but it remains challenging to assess their calibration (i.e., whether or not the posterior probability of causality reflects the true proportion of causal variants) in real data, where model misspecification almost certainly exists and true causal variants are unknown. Here, we present the Replication Failure Rate (RFR), a metric to assess the consistency of fine-mapping results based on downsampling a large cohort. Empirical evaluation of fine-mapping results from SuSiE, FINEMAP and COJO-ABF suggest that these methods may be miscalibrated in the under-conservative direction. Next, we show in simulations that non-sparse genetic architecture can lead to miscalibration, while imputation noise, non-normal effect size distributions, and quality control filters removing potentially causal variants are less likely contributors. Here, we present two new fine-mapping methods, SuSiE-inf and FINEMAP-inf, that extend SuSiE and FINEMAP to incorporate a term for infinitesimal effects in addition to a small number of larger causal effects of interest. Our methods exhibit better calibration in simulations and improved RFR and functional enrichment in real data, with minimal loss of recall and competitive computational cost. Furthermore, using the sparse fine-mapped variants identified by our methods to perform cross-population genetic risk prediction in the UK Biobank, we observed a substantial increase in predictive accuracy over SuSiE and FINEMAP. Our work improves our ability to pinpoint causal variants for complex traits, a fundamental goal of human genetics.
Published: 2022
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38. Reverend Dr. Lindon Eaves: A Career Remembrance

Author: Michael C. Neale, Peter K. Hatemi, Elizabeth C. Prom-Wormley, Benjamin M. Neale, Andrew C. Heath, and Hermine H. Maes
Subjects: Genetics, Genetics (clinical), Ecology, Evolution, Behavior and Systematics
Published: 2022
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39. Multi-PGS enhances polygenic prediction: weighting 937 polygenic scores

Author: Clara Albiñana, Zhihong Zhu, Andrew J. Schork, Andrés Ingason, Hugues Aschard, Isabell Brikell, Cynthia M. Bulik, Liselotte V. Petersen, Esben Agerbo, Jakob Grove, Merete Nordentoft, David M. Hougaard, Thomas Werge, Anders D. Børglum, Preben Bo Mortensen, John J. McGrath, Benjamin M. Neale, Florian Privé, Bjarni J. Vilhjálmsson, Bioinformatics Research Center, Aarhus University [Aarhus], Department of Neurosciences [Univ California San Diego] (Neuro - UC San Diego), School of Medicine [Univ California San Diego] (UC San Diego), University of California [San Diego] (UC San Diego), University of California (UC)-University of California (UC)-University of California [San Diego] (UC San Diego), University of California (UC)-University of California (UC), Department of Cognitive Sciences [Univ California San Diego] (CogSci - UC San Diego), Metacohorts Consortium, Center for Genomic Medicine, Copenhagen University Hospital-Rigshospitalet [Copenhagen], Copenhagen University Hospital, Département de Biologie Computationnelle - Department of Computational Biology, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Karolinska Institutet [Stockholm], University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Génétique des maladies multifactorielles (GMM), Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), IT University of Copenhagen (ITU), Statens Serum Institut [Copenhagen], Center for Genomics and Personalized Medicine [Aarhus, Denmark] (CGPM), Department of Genomics, and MR Solutions Guildford
Subjects: [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics
Abstract: The predictive performance of polygenic scores (PGS) is largely dependent on the number of samples available to train the PGS. Increasing the sample size for a specific phenotype is expensive and takes time, but this sample size can be effectively increased by using genetically correlated phenotypes. We propose a framework to generate multi-PGS from thousands of publicly available genome-wide association studies (GWAS) with no need to individually select the most relevant ones. In this study, the multi-PGS framework increased prediction accuracy over single PGS for all included psychiatric disorders and other available outcomes, with prediction R2 increases of up to 9-fold for attention-deficit/hyperactivity disorder (ADHD) compared to a single PGS. We also generate multi-PGS for phenotypes without an existing GWAS and for case-case predictions, with up to 15-fold increases in prediction accuracy. We benchmark the multi-PGS framework against other methods and highlight its potential application to new emerging biobanks.
Published: 2022
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40. Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies

Author: Pouria Salehi Nowbandegani, Anthony Wilder Wohns, Jenna L. Ballard, Eric S. Lander, Alex Bloemendal, Benjamin M. Neale, and Luke J. O’Connor
Abstract: Linkage disequilibrium (LD) is the correlation among nearby genetic variants. In genetic association studies, LD is often modeled using massive local correlation matrices, but this approach is slow, especially in ancestrally diverse studies. Here, we introduce LD graphical models (LDGMs), which are an extremely sparse and efficient representation of LD. LDGMs are derived from genome-wide genealogies; statistical relationships among alleles in the LDGM correspond to genealogical relationships among haplotypes. We publish LDGMs and ancestry specific LDGM precision matrices for 18 million common SNPs (MAF>1%) in five ancestry groups, validate their accuracy, and demonstrate order-of-magnitude improvements in runtime for commonly used LD matrix computations. We implement an extremely fast multi-ancestry polygenic prediction method, BLUPx-ldgm, which performs better than a similar method based on the reference LD correlation matrix. LDGMs will enable sophisticated methods that scale to ancestrally genetic association data across millions of variants and individuals.
Published: 2022
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41. Principled distillation of multidimensional UK Biobank data reveals insights into the correlated human phenome

Author: Caitlin E. Carey, Rebecca Shafee, Amanda Elliott, Duncan S. Palmer, John Compitello, Masahiro Kanai, Liam Abbott, Patrick Schultz, Konrad J. Karczewski, Samuel C. Bryant, Caroline M. Cusick, Claire Churchhouse, Daniel P. Howrigan, Daniel King, George Davey Smith, Robbee Wedow, Benjamin M. Neale, Raymond K. Walters, and Elise B. Robinson
Abstract: Broad yet detailed data collected in biobanks captures variation reflective of human health and behavior, but insights are hard to extract given their complexity and scale. In the largest factor analysis to date, we distill hundreds of medical record codes, physical assays, and survey items from UK Biobank into 35 understandable latent constructs. The identified factors recapitulate known disease classifications, highlight the relevance of psychiatric constructs, improve measurement of health-related behavior, and disentangle elements of socioeconomic status. We demonstrate the power of this principled data reduction approach to clarify genetic signal, enhance discovery, and identify associations between underlying phenotypic structure and health outcomes such as mortality. We emphasize the importance of considering the interwoven nature of the human phenome when evaluating large-scale patterns relevant to public health.
Published: 2022
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42. Incorporating family history of disease improves polygenic risk scores in diverse populations

Author: Margaux L.A. Hujoel, Po-Ru Loh, Benjamin M. Neale, and Alkes L. Price
Abstract: Polygenic risk scores (PRSs) derived from genotype data and family history (FH) of disease provide valuable information for predicting disease risk, but PRSs perform poorly when applied to diverse populations. Here, we explore methods for combining both types of information (PRS-FH) in UK Biobank data. PRSs were trained using all British individuals (n = 409,000), and target samples consisted of unrelated non-British Europeans (n = 42,000), South Asians (n = 7,000), or Africans (n = 7,000). We evaluated PRS, FH, and PRS-FH using liability-scale
Published: 2022

43. Differences in the genetic architecture of common and rare variants in childhood, persistent and late-diagnosed attention-deficit hyperactivity disorder

Author: Veera M. Rajagopal, Jinjie Duan, Laura Vilar-Ribó, Jakob Grove, Tetyana Zayats, J. Antoni Ramos-Quiroga, F. Kyle Satterstrom, María Soler Artigas, Jonas Bybjerg-Grauholm, Marie Bækvad-Hansen, Thomas D. Als, Anders Rosengren, Mark J. Daly, Benjamin M. Neale, Merete Nordentoft, Thomas Werge, Ole Mors, David M. Hougaard, Preben B. Mortensen, Marta Ribasés, Anders D. Børglum, Ditte Demontis, Institute for Molecular Medicine Finland, and University of Helsinki
Subjects: Adult, RISK, Multifactorial Inheritance, HERITABILITY, 1184 Genetics, developmental biology, physiology, Comorbidity, ASSOCIATION, Article, EVOLUTION, ENVIRONMENTAL-INFLUENCES, GENOME, SEVERITY, Attention Deficit Disorder with Hyperactivity, Neurodevelopmental Disorders, Attention Deficit Disorder with Hyperactivity/diagnosis, Genetics, Humans, ADHD, Genetic Predisposition to Disease, DEFICIT/HYPERACTIVITY DISORDER, TRAJECTORIES
Abstract: Analyses of the polygenic architecture of childhood, persistent and late-diagnosed attention-deficit hyperactivity disorder (ADHD) in a Danish population-based case-cohort sample identify differences among ADHD subgroups with respect to common and rare variants. Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder with onset in childhood (childhood ADHD); two-thirds of affected individuals continue to have ADHD in adulthood (persistent ADHD), and sometimes ADHD is diagnosed in adulthood (late-diagnosed ADHD). We evaluated genetic differences among childhood (n = 14,878), persistent (n = 1,473) and late-diagnosed (n = 6,961) ADHD cases alongside 38,303 controls, and rare variant differences in 7,650 ADHD cases and 8,649 controls. We identified four genome-wide significant loci for childhood ADHD and one for late-diagnosed ADHD. We found increased polygenic scores for ADHD in persistent ADHD compared with the other two groups. Childhood ADHD had higher genetic overlap with hyperactivity and autism compared with late-diagnosed ADHD and the highest burden of rare protein-truncating variants in evolutionarily constrained genes. Late-diagnosed ADHD had a larger genetic overlap with depression than childhood ADHD and no increased burden in rare protein-truncating variants. Overall, these results suggest a genetic influence on age at first ADHD diagnosis, persistence of ADHD and the different comorbidity patterns among the groups.
Published: 2022
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44. Polygenic architecture of rare coding variation across 400,000 exomes

Author: Daniel J. Weiner, Ajay Nadig, Karthik A. Jagadeesh, Kushal K. Dey, Benjamin M. Neale, Elise B. Robinson, Konrad J. Karczewski, and Luke J. O’Connor
Abstract: Both common and rare genetic variants influence complex traits and common diseases. Genome-wide association studies have discovered thousands of common-variant associations, and more recently, large-scale exome sequencing studies have identified rare-variant associations in hundreds of genes1–3. However, rare-variant genetic architecture is not well characterized, and the relationship between common- and rare-variant architecture is unclear4. Here, we quantify the heritability explained by gene-wise burden of rare coding variants and compare the genetic architecture of common and rare variation across 22 common traits and diseases in 400,000 UK Biobank exomes5. Rare coding variants (AF = 1e-6 - 1e-3) explain 1.3% (SE = 0.03%) of phenotypic variance on average – much less than common variants – and most burden heritability is explained by ultra-rare loss-of-function variants (AF = 1e-6 - 1e-5). Common and rare variants implicate the same cell types, with similar enrichments, and they have pleiotropic effects on the same pairs of traits, with similar genetic correlations. They partially colocalize at individual genes and loci, but not to the same extent: burden heritability is strongly concentrated in a limited number of significant genes (median: 6 genes explaining 19% of h2), while common-variant heritability is much more polygenic. Burden heritability is also more strongly concentrated in constrained genes (median enrichment: 4.5x vs. 2.1x for common variants), indicating that negative selection affects common- and rare-variant architecture differently. Finally, we find that burden heritability for schizophrenia and bipolar disorder6,7 is approximately 2%. Our results show that there are a tractable number of large-effect genes to discover by studying rare variants, that common and rare associations are mechanistically convergent, and that rare coding variants will contribute only modestly to missing heritability and population risk stratification.
Published: 2022
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45. Hematopoietic mosaic chromosomal alterations increase the risk for diverse types of infection

Author: Seyedeh M. Zekavat, Iuliana Ionita-Laza, Pradeep Natarajan, Zhaolong Yu, Kaavya Paruchuri, Akhil Pampana, Eric A. Engels, Scott T. Weiss, Steven A. McCarroll, Shu-Hong Lin, Matthew S. Lebo, Mark J. Daly, Mitchell J. Machiela, Muredach P. Reilly, Romit Bhattacharya, Puja Kohli, Xiaoxi Liu, Mesbah Uddin, Jordan W. Smoller, Robert C. Green, Chen Wang, James P. Pirruccello, Alexander G. Bick, Yixuan Ye, Andrea Ganna, Aoxing Liu, Po-Ru Loh, Benjamin M. Neale, Giulio Genovese, Patrick T. Ellinor, Elizabeth W. Karlson, Chikashi Terao, Krzysztof Kiryluk, Yoichiro Kamatani, Hongyu Zhao, Benjamin L. Ebert, and Derek Brown
Subjects: 0301 basic medicine, business.industry, Cancer, Genome-wide association study, General Medicine, medicine.disease, Article, General Biochemistry, Genetics and Molecular Biology, Sepsis, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Immune system, Infectious disease (medical specialty), 030220 oncology & carcinogenesis, Genotype, Immunology, medicine, Risk factor, business, Genotyping
Abstract: Age is the dominant risk factor for infectious diseases, but the mechanisms linking the two are incompletely understood1,2. Age-related mosaic chromosomal alterations (mCAs) detected from blood-derived DNA genotyping, are structural somatic variants associated with aberrant leukocyte cell counts, hematological malignancy, and mortality3-11. Whether mCAs represent independent risk factors for infection is unknown. Here we use genome-wide genotyping of blood DNA to show that mCAs predispose to diverse infectious diseases. We analyzed mCAs from 767,891 individuals without hematological cancer at DNA acquisition across four countries. Expanded mCA (cell fraction10%) prevalence approached 4% by 60 years of age and was associated with diverse incident infections, including sepsis, pneumonia, and coronavirus disease 2019 (COVID-19) hospitalization. A genome-wide association study of expanded mCAs identified 63 significant loci. Germline genetic alleles associated with expanded mCAs were enriched at transcriptional regulatory sites for immune cells. Our results link mCAs with impaired immunity and predisposition to infections. Furthermore, these findings may also have important implications for the ongoing COVID-19 pandemic, particularly in prioritizing individual preventive strategies and evaluating immunization responses.
Published: 2021
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46. Tractor uses local ancestry to enable inclusion of admixed individuals into GWAS and boost power

Author: Marcos L. Santoro, Elizabeth G. Atkinson, Konrad J. Karczewski, Adam X. Maihofer, Karestan C. Koenen, Jacob C. Ulirsch, Masahiro Kanai, Alicia R. Martin, Caroline M. Nievergelt, Hilary K. Finucane, Yoichiro Kamatani, Mark J. Daly, Yukinori Okada, and Benjamin M. Neale
Subjects: Tractor, business.product_category, Genome-wide association study, Computational biology, Biology, Polymorphism, Single Nucleotide, White People, Article, 03 medical and health sciences, 0302 clinical medicine, Genetics, Guanine Nucleotide Exchange Factors, Humans, Genetic risk, 030304 developmental biology, Genetic association, Homeodomain Proteins, 0303 health sciences, Models, Genetic, Regression analysis, Replicate, Software package, Lipids, Pedigree, Cholesterol blood, Black or African American, Cholesterol, Haplotypes, business, Software, 030217 neurology & neurosurgery, Genome-Wide Association Study, Transcription Factors
Abstract: Admixed populations are routinely excluded from genomic studies due to concerns over population structure. Here, we present a statistical framework and software package, Tractor, to facilitate the inclusion of admixed individuals in association studies by leveraging local ancestry. We test Tractor with simulated and empirical two-way admixed African–European cohorts. Tractor generates accurate ancestry-specific effect-size estimates and P values, can boost genome-wide association study (GWAS) power and improves the resolution of association signals. Using a local ancestry-aware regression model, we replicate known hits for blood lipids, discover novel hits missed by standard GWAS and localize signals closer to putative causal variants. Tractor is a statistical framework that facilitates the inclusion of admixed individuals in association studies by leveraging local ancestry. Tractor generates accurate ancestry-specific effect-size estimates and improves the resolution of association signals.
Published: 2021

47. Investigating Shared Genetic Basis Across Tourette Syndrome and Comorbid Neurodevelopmental Disorders Along the Impulsivity-Compulsivity Spectrum

Author: Jan Haavik, Naomi R. Wray, Phil Lee, Bernie Devlin, Anders D. Børglum, Lea K. Davis, Carol A. Mathews, Peristera Paschou, Barbara Franke, Jeremiah M. Scharf, Manuel Mattheisen, Zhiyu Yang, James J. Crowley, Stephen V. Faraone, Sang Hong Lee, Csaba Barta, Dongmei Yu, Søren Dalsgaard, Fotis Tsetsos, Jordan W. Smoller, Tetyana Zayats, Mark J. Daly, Benjamin M. Neale, Hanrui Wu, Valsamma Eapen, Yang, Zhiyu, Wu, Hanrui, Lee, Phil H, Tsetsos, Fotis, Lee, Sang Hong, and Paschou, Peristera
Subjects: 0301 basic medicine, Obsessive-Compulsive Disorder, Autism Spectrum Disorder, Single-nucleotide polymorphism, Comorbidity, Biology, Impulsivity, ASD, behavioral disciplines and activities, Tourette syndrome, Genetic correlation, 03 medical and health sciences, All institutes and research themes of the Radboud University Medical Center, 0302 clinical medicine, mental disorders, medicine, ADHD, Humans, Biological Psychiatry, Genetic association, Genetics, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], OCD, medicine.disease, Cross-disorder genetic analysis, Genetic architecture, 3. Good health, GWAS meta-analysis, 030104 developmental biology, Attention Deficit Disorder with Hyperactivity, Autism spectrum disorder, Impulsive Behavior, Etiology, medicine.symptom, 030217 neurology & neurosurgery, Genome-Wide Association Study, Tourette Syndrome
Abstract: BACKGROUND: Tourette syndrome (TS) is often found comorbid with other neurodevelopmental disorders across the impulsivity-compulsivity spectrum, with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) as most prevalent. This points to the possibility of a common etiological thread along an impulsivity-compulsivity continuum.METHODS: Investigating the shared genetic basis across TS, ADHD, ASD, and OCD, we undertook an evaluation of cross-disorder genetic architecture and systematic meta-analysis, integrating summary statistics from the latest genome-wide association studies (93,294 individuals, 6,788,510 markers).RESULTS: As previously identified, a common unifying factor connects TS, ADHD, and ASD, while TS and OCD show the highest genetic correlation in pairwise testing among these disorders. Thanks to a more homogeneous set of disorders and a targeted approach that is guided by genetic correlations, we were able to identify multiple novel hits and regions that seem to play a pleiotropic role for the specific disorders analyzed here and could not be identified through previous studies. In the TS-ADHD-ASD genome-wide association study single nucleotide polymorphism-based and gene-based meta-analysis, we uncovered 13 genome-wide significant regions that host single nucleotide polymorphisms with a high posterior probability for association with all three studied disorders (m-value > 0.9), 11 of which were not identified in previous cross-disorder analysis. In contrast, we also identified two additional pleiotropic regions in the TS-OCD meta-analysis. Through conditional analysis, we highlighted genes and genetic regions that play a specific role in a TS-ADHD-ASD genetic factor versus TS-OCD. Cross-disorder tissue specificity analysis implicated the hypothalamus-pituitary-adrenal gland axis in TS-ADHD-ASD.CONCLUSIONS: Our work underlines the value of redefining the framework for research across traditional diagnostic categories.
Published: 2021
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48. Challenges and Opportunities for Developing More Generalizable Polygenic Risk Scores

Author: Ying Wang, Kristin Tsuo, Masahiro Kanai, Benjamin M. Neale, and Alicia R. Martin
Subjects: Multifactorial Inheritance, Risk Factors, Humans, Genetic Predisposition to Disease, General Medicine, Biomarkers, Article, Genome-Wide Association Study
Abstract: Polygenic risk scores (PRS) estimate an individual's genetic likelihood of complex traits and diseases by aggregating information across multiple genetic variants identified from genome-wide association studies. PRS can predict a broad spectrum of diseases and have therefore been widely used in research settings. Some work has investigated their potential applications as biomarkers in preventative medicine, but significant work is still needed to definitively establish and communicate absolute risk to patients for genetic and modifiable risk factors across demographic groups. However, the biggest limitation of PRS currently is that they show poor generalizability across diverse ancestries and cohorts. Major efforts are underway through methodological development and data generation initiatives to improve their generalizability. This review aims to comprehensively discuss current progress on the development of PRS, the factors that affect their generalizability, and promising areas for improving their accuracy, portability, and implementation.
Published: 2022

49. Rare coding variants in ten genes confer substantial risk for schizophrenia

Author: Tarjinder Singh, Timothy Poterba, David Curtis, Huda Akil, Mariam Al Eissa, Jack D. Barchas, Nicholas Bass, Tim B. Bigdeli, Gerome Breen, Evelyn J. Bromet, Peter F. Buckley, William E. Bunney, Jonas Bybjerg-Grauholm, William F. Byerley, Sinéad B. Chapman, Wei J. Chen, Claire Churchhouse, Nicholas Craddock, Caroline M. Cusick, Lynn DeLisi, Sheila Dodge, Michael A. Escamilla, Saana Eskelinen, Ayman H. Fanous, Stephen V. Faraone, Alessia Fiorentino, Laurent Francioli, Stacey B. Gabriel, Diane Gage, Sarah A. Gagliano Taliun, Andrea Ganna, Giulio Genovese, David C. Glahn, Jakob Grove, Mei-Hua Hall, Eija Hämäläinen, Henrike O. Heyne, Matti Holi, David M. Hougaard, Daniel P. Howrigan, Hailiang Huang, Hai-Gwo Hwu, René S. Kahn, Hyun Min Kang, Konrad J. Karczewski, George Kirov, James A. Knowles, Francis S. Lee, Douglas S. Lehrer, Francesco Lescai, Dolores Malaspina, Stephen R. Marder, Steven A. McCarroll, Andrew M. McIntosh, Helena Medeiros, Lili Milani, Christopher P. Morley, Derek W. Morris, Preben Bo Mortensen, Richard M. Myers, Merete Nordentoft, Niamh L. O’Brien, Ana Maria Olivares, Dost Ongur, Willem H. Ouwehand, Duncan S. Palmer, Tiina Paunio, Digby Quested, Mark H. Rapaport, Elliott Rees, Brandi Rollins, F. Kyle Satterstrom, Alan Schatzberg, Edward Scolnick, Laura J. Scott, Sally I. Sharp, Pamela Sklar, Jordan W. Smoller, Janet L. Sobell, Matthew Solomonson, Eli A. Stahl, Christine R. Stevens, Jaana Suvisaari, Grace Tiao, Stanley J. Watson, Nicholas A. Watts, Douglas H. Blackwood, Anders D. Børglum, Bruce M. Cohen, Aiden P. Corvin, Tõnu Esko, Nelson B. Freimer, Stephen J. Glatt, Christina M. Hultman, Andrew McQuillin, Aarno Palotie, Carlos N. Pato, Michele T. Pato, Ann E. Pulver, David St. Clair, Ming T. Tsuang, Marquis P. Vawter, James T. Walters, Thomas M. Werge, Roel A. Ophoff, Patrick F. Sullivan, Michael J. Owen, Michael Boehnke, Michael C. O’Donovan, Benjamin M. Neale, Mark J. Daly, Psychiatry, HUS Psychiatry, Clinicum, University of Helsinki, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, Department of Psychiatry, Centre of Excellence in Complex Disease Genetics, Research Programs Unit, and Aarno Palotie / Principal Investigator
Subjects: Multidisciplinary, Schizophrenia/genetics, MUTATIONS, Receptors, N-Methyl-D-Aspartate/genetics, Genetic Predisposition to Disease/genetics, 3112 Neurosciences, ASSOCIATION, Neurodevelopmental Disorders/genetics, Receptors, N-Methyl-D-Aspartate, INDIVIDUALS, Neurodevelopmental Disorders, Case-Control Studies, Mutation, Schizophrenia, Humans, Genetic Predisposition to Disease, Exome, 3111 Biomedicine, BURDEN
Abstract: Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3–50, P < 2.14 × 10−6) and 32 genes at a false discovery rate of 1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach.
Published: 2022
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50. Non-parametric Polygenic Risk Prediction via Partitioned GWAS Summary Statistics

Author: Maxim Imakaev, Nathan O. Stitziel, Benjamin M. Neale, Nikolaos A. Patsopoulos, Sekar Kathiresan, Shamil R. Sunyaev, Sung Chun, and Daniel Hui
Subjects: Male, Multifactorial Inheritance, Linkage disequilibrium, Genotype, Quantitative Trait Loci, Genome-wide association study, Disease, Computational biology, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Article, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Genetics, Humans, Genetics (clinical), Aged, 030304 developmental biology, 0303 health sciences, Models, Genetic, Nonparametric statistics, Middle Aged, Heritability, Genetic architecture, Phenotype, Diabetes Mellitus, Type 2, Trait, Female, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the trait’s heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in the practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual-level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for breast cancer, type 2 diabetes, inflammatory bowel disease, and coronary heart disease, all of which have available early intervention or prevention treatments.
Published: 2020
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