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1. Cell-type-specific Alzheimer’s disease polygenic risk scores are associated with distinct disease processes in Alzheimer’s disease

Author: Hyun-Sik Yang, Ling Teng, Daniel Kang, Vilas Menon, Tian Ge, Hilary K. Finucane, Aaron P. Schultz, Michael Properzi, Hans-Ulrich Klein, Lori B. Chibnik, Julie A. Schneider, David A. Bennett, Timothy J. Hohman, Richard P. Mayeux, Keith A. Johnson, Philip L. De Jager, and Reisa A. Sperling
Subjects: Science
Abstract: Abstract Many of the Alzheimer’s disease (AD) risk genes are specifically expressed in microglia and astrocytes, but how and when the genetic risk localizing to these cell types contributes to AD pathophysiology remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets and uncover the impact of cell-type-specific genetic risk on AD endophenotypes. In an autopsy dataset spanning all stages of AD (n = 1457), the astrocytic ADPRS affected diffuse and neuritic plaques (amyloid-β), while microglial ADPRS affected neuritic plaques, microglial activation, neurofibrillary tangles (tau), and cognitive decline. In an independent neuroimaging dataset of cognitively unimpaired elderly (n = 2921), astrocytic ADPRS was associated with amyloid-β, and microglial ADPRS was associated with amyloid-β and tau, connecting cell-type-specific genetic risk with AD pathology even before symptom onset. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage.
Published: 2023
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2. Identifying the Common Genetic Basis of Antidepressant Response

Author: Oliver Pain, Karen Hodgson, Vassily Trubetskoy, Stephan Ripke, Victoria S. Marshe, Mark J. Adams, Enda M. Byrne, Adrian I. Campos, Tania Carrillo-Roa, Annamaria Cattaneo, Thomas D. Als, Daniel Souery, Mojca Z. Dernovsek, Chiara Fabbri, Caroline Hayward, Neven Henigsberg, Joanna Hauser, James L. Kennedy, Eric J. Lenze, Glyn Lewis, Daniel J. Müller, Nicholas G. Martin, Benoit H. Mulsant, Ole Mors, Nader Perroud, David J. Porteous, Miguel E. Rentería, Charles F. Reynolds, III, Marcella Rietschel, Rudolf Uher, Eleanor M. Wigmore, Wolfgang Maier, Naomi R. Wray, Katherine J. Aitchison, Volker Arolt, Bernhard T. Baune, Joanna M. Biernacka, Guido Bondolfi, Katharina Domschke, Masaki Kato, Qingqin S. Li, Yu-Li Liu, Alessandro Serretti, Shih-Jen Tsai, Gustavo Turecki, Richard Weinshilboum, Andrew M. McIntosh, Cathryn M. Lewis, Siegfried Kasper, Joseph Zohar, Stuart Montgomery, Diego Albani, Gianluigi Forloni, Panagiotis Ferentinos, Dan Rujescu, Julien Mendlewicz, Manuel Mattheisen, Maciej Trzaskowski, Abdel Abdellaoui, Esben Agerbo, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Tim B. Bigdeli, Elisabeth B. Binder, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, Toni-Kim Clarke, Jonathan R.I. Coleman, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Nick Craddock, Gregory E. Crawford, Gail Davies, Ian J. Deary, Franziska Degenhardt, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Valentina Escott-Price, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Jerome C. Foo, Andreas J. Forstner, Josef Frank, Héléna A. Gaspar, Michael Gill, Fernando S. Goes, Scott D. Gordon, Jakob Grove, Lynsey S. Hall, Christine Søholm Hansen, Thomas F. Hansen, Stefan Herms, Ian B. Hickie, Per Hoffmann, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, David M. Hougaard, David M. Howard, Marcus Ising, Rick Jansen, Ian Jones, Lisa A. Jones, Eric Jorgenson, James A. Knowles, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Donald J. MacIntyre, Dean F. MacKinnon, Robert M. Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Peter McGuffin, Sarah E. Medland, Divya Mehta, Christel M. Middeldorp, Evelin Mihailov, Yuri Milaneschi, Lili Milani, Francis M. Mondimore, Grant W. Montgomery, Sara Mostafavi, Niamh Mullins, Matthias Nauck, Bernard Ng, Michel G. Nivard, Dale R. Nyholt, Paul F. O’Reilly, Hogni Oskarsson, Michael J. Owen, Jodie N. Painter, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Roseann E. Peterson, Wouter J. Peyrot, Giorgio Pistis, Danielle Posthuma, Jorge A. Quiroz, Per Qvist, John P. Rice, Brien P. Riley, Margarita Rivera, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Jianxin Shi, Stanley I. Shyn, Engilbert Sigurdsson, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Hreinn Stefansson, Stacy Steinberg, Fabian Streit, Jana Strohmaier, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, André G. Uitterlinden, Daniel Umbricht, Sandra Van der Auwera, Albert M. van Hemert, Alexander Viktorin, Peter M. Visscher, Yunpeng Wang, Bradley T. Webb, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Stephanie H. Witt, Yang Wu, Hualin S. Xi, Jian Yang, Futao Zhang, Klaus Berger, Dorret I. Boomsma, Sven Cichon, Udo Dannlowski, E.J.C. de Geus, J. Raymond DePaulo, Enrico Domenici, Tõnu Esko, Hans J. Grabe, Steven P. Hamilton, Andrew C. Heath, Kenneth S. Kendler, Stefan Kloiber, Susanne Lucae, Pamela A.F. Madden, Patrik K. Magnusson, Andres Metspalu, Preben Bo Mortensen, Bertram Müller-Myhsok, Merete Nordentoft, Markus M. Nöthen, Michael C. O’Donovan, Sara A. Paciga, Nancy L. Pedersen, Brenda W.J.H. Penninx, Roy H. Perlis, James B. Potash, Martin Preisig, Catherine Schaefer, Thomas G. Schulze, Jordan W. Smoller, Kari Stefansson, Henning Tiemeier, Henry Völzke, Myrna M. Weissman, Thomas Werge, Douglas F. Levinson, Gerome Breen, Anders D. Børglum, and Patrick F. Sullivan
Subjects: Antidepressant response, Depression, Genetics, GWAS, MDD, Polygenic score, Psychiatry, RC435-571
Abstract: Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods: Genome-wide analysis of remission (nremit = 1852, nnonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism–based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism–based heritability was significantly different from zero for remission (h2 = 0.132, SE = 0.056) but not for percentage improvement (h2 = −0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.
Published: 2022
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3. 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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4. Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs

Author: Qingbo S. Wang, David R. Kelley, Jacob Ulirsch, Masahiro Kanai, Shuvom Sadhuka, Ran Cui, Carlos Albors, Nathan Cheng, Yukinori Okada, The Biobank Japan Project, Francois Aguet, Kristin G. Ardlie, Daniel G. MacArthur, and Hilary K. Finucane
Subjects: Science
Abstract: Finding causal variants and genes from GWAS loci results remains a challenge. Here, the authors train a model to predict if a variant affects nearby gene expression, and apply the method to identify new possible causal eQTLs and mechanisms of GWAS loci.
Published: 2021
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5. Prioritizing disease and trait causal variants at the TNFAIP3 locus using functional and genomic features

Author: John P. Ray, Carl G. de Boer, Charles P. Fulco, Caleb A. Lareau, Masahiro Kanai, Jacob C. Ulirsch, Ryan Tewhey, Leif S. Ludwig, Steven K. Reilly, Drew T. Bergman, Jesse M. Engreitz, Robbyn Issner, Hilary K. Finucane, Eric S. Lander, Aviv Regev, and Nir Hacohen
Subjects: Science
Abstract: While genome-wide association studies have yielded thousands of trait-associated loci, identifying causal variants remains challenging. Here, the authors perform seven genomics assays in various cell types to prioritize genetic variants in the TNFAIP3 locus, and report high-priority variants within disease-associated haplotypes.
Published: 2020
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6. Publisher Correction: Shared heritability and functional enrichment across six solid cancers

Author: Xia Jiang, Hilary K. Finucane, Fredrick R. Schumacher, Stephanie L. Schmit, Jonathan P. Tyrer, Younghun Han, Kyriaki Michailidou, Corina Lesseur, Karoline B. Kuchenbaecker, Joe Dennis, David V. Conti, Graham Casey, Mia M. Gaudet, Jeroen R. Huyghe, Demetrius Albanes, Melinda C. Aldrich, Angeline S. Andrew, Irene L. Andrulis, Hoda Anton-Culver, Antonis C. Antoniou, Natalia N. Antonenkova, Susanne M. Arnold, Kristan J. Aronson, Banu K. Arun, Elisa V. Bandera, Rosa B. Barkardottir, Daniel R. Barnes, Jyotsna Batra, Matthias W. Beckmann, Javier Benitez, Sara Benlloch, Andrew Berchuck, Sonja I. Berndt, Heike Bickeböller, Stephanie A. Bien, Carl Blomqvist, Stefania Boccia, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Hiltrud Brauch, Hermann Brenner, James D. Brenton, Mark N. Brook, Joan Brunet, Hans Brunnström, Daniel D. Buchanan, Barbara Burwinkel, Ralf Butzow, Gabriella Cadoni, Trinidad Caldés, Maria A. Caligo, Ian Campbell, Peter T. Campbell, Géraldine Cancel-Tassin, Lisa Cannon-Albright, Daniele Campa, Neil Caporaso, André L. Carvalho, Andrew T. Chan, Jenny Chang-Claude, Stephen J. Chanock, Chu Chen, David C. Christiani, Kathleen B. M. Claes, Frank Claessens, Judith Clements, J. Margriet Collée, Marcia Cruz Correa, Fergus J. Couch, Angela Cox, Julie M. Cunningham, Cezary Cybulski, Kamila Czene, Mary B. Daly, Anna deFazio, Peter Devilee, Orland Diez, Manuela Gago-Dominguez, Jenny L. Donovan, Thilo Dörk, Eric J. Duell, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Christopher K. Edlund, Digna R. Velez Edwards, Carolina Ellberg, D. Gareth Evans, Peter A. Fasching, Robert L. Ferris, Triantafillos Liloglou, Jane C. Figueiredo, Olivia Fletcher, Renée T. Fortner, Florentia Fostira, Silvia Franceschi, Eitan Friedman, Steven J. Gallinger, Patricia A. Ganz, Judy Garber, José A. García-Sáenz, Simon A. Gayther, Graham G. Giles, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Ellen L. Goode, Marc T. Goodman, Gary Goodman, Kjell Grankvist, Mark H. Greene, Henrik Gronberg, Jacek Gronwald, Pascal Guénel, Niclas Håkansson, Per Hall, Ute Hamann, Freddie C. Hamdy, Robert J. Hamilton, Jochen Hampe, Aage Haugen, Florian Heitz, Rolando Herrero, Peter Hillemanns, Michael Hoffmeister, Estrid Høgdall, Yun-Chul Hong, John L. Hopper, Richard Houlston, Peter J. Hulick, David J. Hunter, David G. Huntsman, Gregory Idos, Evgeny N. Imyanitov, Sue Ann Ingles, Claudine Isaacs, Anna Jakubowska, Paul James, Mark A. Jenkins, Mattias Johansson, Mikael Johansson, Esther M. John, Amit D. Joshi, Radka Kaneva, Beth Y. Karlan, Linda E. Kelemen, Tabea Kühl, Kay-Tee Khaw, Elza Khusnutdinova, Adam S. Kibel, Lambertus A. Kiemeney, Jeri Kim, Susanne K. Kjaer, Julia A. Knight, Manolis Kogevinas, Zsofia Kote-Jarai, Stella Koutros, Vessela N. Kristensen, Jolanta Kupryjanczyk, Martin Lacko, Stephan Lam, Diether Lambrechts, Maria Teresa Landi, Philip Lazarus, Nhu D. Le, Eunjung Lee, Flavio Lejbkowicz, Heinz-Josef Lenz, Goska Leslie, Davor Lessel, Jenny Lester, Douglas A. Levine, Li Li, Christopher I. Li, Annika Lindblom, Noralane M. Lindor, Geoffrey Liu, Fotios Loupakis, Jan Lubiński, Lovise Maehle, Christiane Maier, Arto Mannermaa, Loic Le Marchand, Sara Margolin, Taymaa May, Lesley McGuffog, Alfons Meindl, Pooja Middha, Austin Miller, Roger L. Milne, Robert J. MacInnis, Francesmary Modugno, Marco Montagna, Victor Moreno, Kirsten B. Moysich, Lorelei Mucci, Kenneth Muir, Anna Marie Mulligan, Katherine L. Nathanson, David E. Neal, Andrew R. Ness, Susan L. Neuhausen, Heli Nevanlinna, Polly A. Newcomb, Lisa F. Newcomb, Finn Cilius Nielsen, Liene Nikitina-Zake, Børge G. Nordestgaard, Robert L. Nussbaum, Kenneth Offit, Edith Olah, Ali Amin Al Olama, Olufunmilayo I. Olopade, Andrew F. Olshan, Håkan Olsson, Ana Osorio, Hardev Pandha, Jong Y. Park, Nora Pashayan, Michael T. Parsons, Tanja Pejovic, Kathryn L. Penney, Wilbert H. M. Peters, Catherine M. Phelan, Amanda I. Phipps, Dijana Plaseska-Karanfilska, Miranda Pring, Darya Prokofyeva, Paolo Radice, Kari Stefansson, Susan J. Ramus, Leon Raskin, Gad Rennert, Hedy S. Rennert, Elizabeth J. van Rensburg, Marjorie J. Riggan, Harvey A. Risch, Angela Risch, Monique J. Roobol, Barry S. Rosenstein, Mary Anne Rossing, Kim De Ruyck, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Matthew B. Schabath, Johanna Schleutker, Marjanka K. Schmidt, V. Wendy Setiawan, Hongbing Shen, Erin M. Siegel, Weiva Sieh, Christian F. Singer, Martha L. Slattery, Karina Dalsgaard Sorensen, Melissa C. Southey, Amanda B. Spurdle, Janet L. Stanford, Victoria L. Stevens, Sebastian Stintzing, Jennifer Stone, Karin Sundfeldt, Rebecca Sutphen, Anthony J. Swerdlow, Eloiza H. Tajara, Catherine M. Tangen, Adonina Tardon, Jack A. Taylor, M. Dawn Teare, Manuel R. Teixeira, Mary Beth Terry, Kathryn L. Terry, Stephen N. Thibodeau, Mads Thomassen, Line Bjørge, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Paul A. Townsend, Ruth C. Travis, Nadine Tung, Shelley S. Tworoger, Cornelia M. Ulrich, Nawaid Usmani, Celine M. Vachon, Els Van Nieuwenhuysen, Ana Vega, Miguel Elías Aguado-Barrera, Qin Wang, Penelope M. Webb, Clarice R. Weinberg, Stephanie Weinstein, Mark C. Weissler, Jeffrey N. Weitzel, Catharine M. L. West, Emily White, Alice S. Whittemore, H-Erich Wichmann, Fredrik Wiklund, Robert Winqvist, Alicja Wolk, Penella Woll, Michael Woods, Anna H. Wu, Xifeng Wu, Drakoulis Yannoukakos, Wei Zheng, Shanbeh Zienolddiny, Argyrios Ziogas, Kristin K. Zorn, Jacqueline M. Lane, Richa Saxena, Duncan Thomas, Rayjean J. Hung, Brenda Diergaarde, James McKay, Ulrike Peters, Li Hsu, Montserrat García-Closas, Rosalind A. Eeles, Georgia Chenevix-Trench, Paul J. Brennan, Christopher A. Haiman, Jacques Simard, Douglas F. Easton, Stephen B. Gruber, Paul D. P. Pharoah, Alkes L. Price, Bogdan Pasaniuc, Christopher I. Amos, Peter Kraft, and Sara Lindström
Subjects: Science
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2019
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7. Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection

Author: Armin P. Schoech, Daniel M. Jordan, Po-Ru Loh, Steven Gazal, Luke J. O’Connor, Daniel J. Balick, Pier F. Palamara, Hilary K. Finucane, Shamil R. Sunyaev, and Alkes L. Price
Subjects: Science
Abstract: Negative selection removes deleterious genetic variation, and can influence genetic architectures and evolution of complex traits. Here, the authors analyze data from 25 UK Biobank diseases and complex traits, and quantify frequency-dependent genetic architectures which suggests actions of negative selection.
Published: 2019
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8. Shared heritability and functional enrichment across six solid cancers

Author: Xia Jiang, Hilary K. Finucane, Fredrick R. Schumacher, Stephanie L. Schmit, Jonathan P. Tyrer, Younghun Han, Kyriaki Michailidou, Corina Lesseur, Karoline B. Kuchenbaecker, Joe Dennis, David V. Conti, Graham Casey, Mia M. Gaudet, Jeroen R. Huyghe, Demetrius Albanes, Melinda C. Aldrich, Angeline S. Andrew, Irene L. Andrulis, Hoda Anton-Culver, Antonis C. Antoniou, Natalia N. Antonenkova, Susanne M. Arnold, Kristan J. Aronson, Banu K. Arun, Elisa V. Bandera, Rosa B. Barkardottir, Daniel R. Barnes, Jyotsna Batra, Matthias W. Beckmann, Javier Benitez, Sara Benlloch, Andrew Berchuck, Sonja I. Berndt, Heike Bickeböller, Stephanie A. Bien, Carl Blomqvist, Stefania Boccia, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Hiltrud Brauch, Hermann Brenner, James D. Brenton, Mark N. Brook, Joan Brunet, Hans Brunnström, Daniel D. Buchanan, Barbara Burwinkel, Ralf Butzow, Gabriella Cadoni, Trinidad Caldés, Maria A. Caligo, Ian Campbell, Peter T. Campbell, Géraldine Cancel-Tassin, Lisa Cannon-Albright, Daniele Campa, Neil Caporaso, André L. Carvalho, Andrew T. Chan, Jenny Chang-Claude, Stephen J. Chanock, Chu Chen, David C. Christiani, Kathleen B. M. Claes, Frank Claessens, Judith Clements, J. Margriet Collée, Marcia Cruz Correa, Fergus J. Couch, Angela Cox, Julie M. Cunningham, Cezary Cybulski, Kamila Czene, Mary B. Daly, Anna deFazio, Peter Devilee, Orland Diez, Manuela Gago-Dominguez, Jenny L. Donovan, Thilo Dörk, Eric J. Duell, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Christopher K. Edlund, Digna R Velez Edwards, Carolina Ellberg, D. Gareth Evans, Peter A. Fasching, Robert L. Ferris, Triantafillos Liloglou, Jane C. Figueiredo, Olivia Fletcher, Renée T. Fortner, Florentia Fostira, Silvia Franceschi, Eitan Friedman, Steven J. Gallinger, Patricia A. Ganz, Judy Garber, José A. García-Sáenz, Simon A. Gayther, Graham G. Giles, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Ellen L. Goode, Marc T. Goodman, Gary Goodman, Kjell Grankvist, Mark H. Greene, Henrik Gronberg, Jacek Gronwald, Pascal Guénel, Niclas Håkansson, Per Hall, Ute Hamann, Freddie C. Hamdy, Robert J. Hamilton, Jochen Hampe, Aage Haugen, Florian Heitz, Rolando Herrero, Peter Hillemanns, Michael Hoffmeister, Estrid Høgdall, Yun-Chul Hong, John L. Hopper, Richard Houlston, Peter J. Hulick, David J. Hunter, David G. Huntsman, Gregory Idos, Evgeny N. Imyanitov, Sue Ann Ingles, Claudine Isaacs, Anna Jakubowska, Paul James, Mark A. Jenkins, Mattias Johansson, Mikael Johansson, Esther M. John, Amit D. Joshi, Radka Kaneva, Beth Y. Karlan, Linda E. Kelemen, Tabea Kühl, Kay-Tee Khaw, Elza Khusnutdinova, Adam S. Kibel, Lambertus A. Kiemeney, Jeri Kim, Susanne K. Kjaer, Julia A. Knight, Manolis Kogevinas, Zsofia Kote-Jarai, Stella Koutros, Vessela N. Kristensen, Jolanta Kupryjanczyk, Martin Lacko, Stephan Lam, Diether Lambrechts, Maria Teresa Landi, Philip Lazarus, Nhu D. Le, Eunjung Lee, Flavio Lejbkowicz, Heinz-Josef Lenz, Goska Leslie, Davor Lessel, Jenny Lester, Douglas A. Levine, Li Li, Christopher I. Li, Annika Lindblom, Noralane M. Lindor, Geoffrey Liu, Fotios Loupakis, Jan Lubiński, Lovise Maehle, Christiane Maier, Arto Mannermaa, Loic Le Marchand, Sara Margolin, Taymaa May, Lesley McGuffog, Alfons Meindl, Pooja Middha, Austin Miller, Roger L. Milne, Robert J. MacInnis, Francesmary Modugno, Marco Montagna, Victor Moreno, Kirsten B. Moysich, Lorelei Mucci, Kenneth Muir, Anna Marie Mulligan, Katherine L. Nathanson, David E. Neal, Andrew R. Ness, Susan L. Neuhausen, Heli Nevanlinna, Polly A. Newcomb, Lisa F. Newcomb, Finn Cilius Nielsen, Liene Nikitina-Zake, Børge G. Nordestgaard, Robert L. Nussbaum, Kenneth Offit, Edith Olah, Ali Amin Al Olama, Olufunmilayo I. Olopade, Andrew F. Olshan, Håkan Olsson, Ana Osorio, Hardev Pandha, Jong Y. Park, Nora Pashayan, Michael T. Parsons, Tanja Pejovic, Kathryn L. Penney, Wilbert H M. Peters, Catherine M. Phelan, Amanda I. Phipps, Dijana Plaseska-Karanfilska, Miranda Pring, Darya Prokofyeva, Paolo Radice, Kari Stefansson, Susan J. Ramus, Leon Raskin, Gad Rennert, Hedy S. Rennert, Elizabeth J. van Rensburg, Marjorie J. Riggan, Harvey A. Risch, Angela Risch, Monique J. Roobol, Barry S. Rosenstein, Mary Anne Rossing, Kim De Ruyck, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Matthew B. Schabath, Johanna Schleutker, Marjanka K. Schmidt, V. Wendy Setiawan, Hongbing Shen, Erin M. Siegel, Weiva Sieh, Christian F. Singer, Martha L. Slattery, Karina Dalsgaard Sorensen, Melissa C. Southey, Amanda B. Spurdle, Janet L. Stanford, Victoria L. Stevens, Sebastian Stintzing, Jennifer Stone, Karin Sundfeldt, Rebecca Sutphen, Anthony J. Swerdlow, Eloiza H. Tajara, Catherine M. Tangen, Adonina Tardon, Jack A. Taylor, M. Dawn Teare, Manuel R. Teixeira, Mary Beth Terry, Kathryn L. Terry, Stephen N. Thibodeau, Mads Thomassen, Line Bjørge, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Paul A. Townsend, Ruth C. Travis, Nadine Tung, Shelley S. Tworoger, Cornelia M. Ulrich, Nawaid Usmani, Celine M. Vachon, Els Van Nieuwenhuysen, Ana Vega, Miguel Elías Aguado-Barrera, Qin Wang, Penelope M. Webb, Clarice R. Weinberg, Stephanie Weinstein, Mark C. Weissler, Jeffrey N. Weitzel, Catharine M. L. West, Emily White, Alice S. Whittemore, H-Erich Wichmann, Fredrik Wiklund, Robert Winqvist, Alicja Wolk, Penella Woll, Michael Woods, Anna H. Wu, Xifeng Wu, Drakoulis Yannoukakos, Wei Zheng, Shanbeh Zienolddiny, Argyrios Ziogas, Kristin K. Zorn, Jacqueline M. Lane, Richa Saxena, Duncan Thomas, Rayjean J. Hung, Brenda Diergaarde, James McKay, Ulrike Peters, Li Hsu, Montserrat García-Closas, Rosalind A. Eeles, Georgia Chenevix-Trench, Paul J. Brennan, Christopher A. Haiman, Jacques Simard, Douglas F. Easton, Stephen B. Gruber, Paul D. P. Pharoah, Alkes L. Price, Bogdan Pasaniuc, Christopher I. Amos, Peter Kraft, and Sara Lindström
Subjects: Science
Abstract: Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.
Published: 2019
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9. For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets.

Author: Brian L. Trippe, Hilary K. Finucane, and Tamara Broderick
Published: 2021

10. 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

11. Mapping the convergence of genes for coronary artery disease onto endothelial cell programs

Author: Gavin R. Schnitzler, Helen Kang, Vivian S. Lee-Kim, X. Rosa Ma, Tony Zeng, Ramcharan S. Angom, Shi Fang, Shamsudheen Karuthedath Vellarikkal, Ronghao Zhou, Katherine Guo, Oscar Sias-Garcia, Alex Bloemendal, Glen Munson, Philine Guckelberger, Tung H. Nguyen, Drew T. Bergman, Nathan Cheng, Brian Cleary, Krishna Aragam, Debabrata Mukhopadhyay, Eric S. Lander, Hilary K. Finucane, Rajat M. Gupta, and Jesse M. Engreitz
Abstract: Genome-wide association studies (GWAS) have discovered thousands of risk loci for common, complex diseases, each of which could point to genes and gene programs that influence disease. For some diseases, it has been observed that GWAS signals converge on a smaller number of biological programs, and that this convergence can help to identify causal genes1–6. However, identifying such convergence remains challenging: each GWAS locus can have many candidate genes, each gene might act in one or more possible programs, and it remains unclear which programs might influence disease risk. Here, we developed a new approach to address this challenge, by creating unbiased maps to link disease variants to genes to programs (V2G2P) in a given cell type. We applied this approach to study the role of endothelial cells in the genetics of coronary artery disease (CAD). To link variants to genes, we constructed enhancer-gene maps using the Activity-by-Contact model7,8. To link genes to programs, we applied CRISPRi-Perturb-seq9–12to knock down all expressed genes within ±500 Kb of 306 CAD GWAS signals13,14and identify their effects on gene expression programs using single-cell RNA-sequencing. By combining these variant-to-gene and gene-to-program maps, we find that 43 of 306 CAD GWAS signals converge onto 5 gene programs linked to the cerebral cavernous malformations (CCM) pathway—which is known to coordinate transcriptional responses in endothelial cells15, but has not been previously linked to CAD risk. The strongest regulator of these programs isTLNRD1, which we show is a new CAD gene and novel regulator of the CCM pathway.TLNRD1loss-of-function alters actin organization and barrier function in endothelial cellsin vitro, and heart development in zebrafishin vivo. Together, our study identifies convergence of CAD risk loci into prioritized gene programs in endothelial cells, nominates new genes of potential therapeutic relevance for CAD, and demonstrates a generalizable strategy to connect disease variants to functions.
Published: 2022

12. 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

13. Designing floating codes for expected performance.

Author: Hilary K. Finucane, Zhenming Liu, and Michael Mitzenmacher
Published: 2008
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14. Direct characterization of cis-regulatory elements and functional dissection of complex genetic associations using HCR–FlowFISH

Author: Jacob C. Ulirsch, Masahiro Kanai, Alan Gutierrez, Steven K. Reilly, Kousuke Mouri, Daniel Berenzy, Susan Kales, Ryan Tewhey, Ava Mackay-Smith, Pardis C. Sabeti, Redwan M Bhuiyan, Sager J. Gosai, Michael L. Stitzel, Hilary K. Finucane, Adrianne Gladden-Young, and Gina M Butler
Subjects: Fatty Acid Desaturases, Quantitative Trait Loci, Locus (genetics), Computational biology, Regulatory Sequences, Nucleic Acid, Biology, Polymorphism, Single Nucleotide, Genome, Article, Delta-5 Fatty Acid Desaturase, Proto-Oncogene Proteins, Genetic variation, Genetics, Deoxyribonuclease I, Humans, CRISPR, Gene silencing, Clustered Regularly Interspaced Short Palindromic Repeats, GATA1 Transcription Factor, Epigenetics, Gene, In Situ Hybridization, Fluorescence, Adaptor Proteins, Signal Transducing, Models, Genetic, Bayes Theorem, LIM Domain Proteins, Flow Cytometry, K562 Cells, Function (biology), RNA, Guide, Kinetoplastida
Abstract: Effective interpretation of genome function and genetic variation requires a shift from epigenetic mapping of cis-regulatory elements (CREs) to characterization of endogenous function. We developed hybridization chain reaction fluorescence in situ hybridization coupled with flow cytometry (HCR-FlowFISH), a broadly applicable approach to characterize CRISPR-perturbed CREs via accurate quantification of native transcripts, alongside CRISPR activity screen analysis (CASA), a hierarchical Bayesian model to quantify CRE activity. Across >325,000 perturbations, we provide evidence that CREs can regulate multiple genes, skip over the nearest gene and display activating and/or silencing effects. At the cholesterol-level-associated FADS locus, we combine endogenous screens with reporter assays to exhaustively characterize multiple genome-wide association signals, functionally nominate causal variants and, importantly, identify their target genes.
Published: 2021

15. 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

16. Genome-wide pleiotropy analysis of coronary artery disease and pneumonia identifies shared immune pathways

Author: Zhi Yu, Seyedeh M. Zekavat, Sara Haidermota, Rachel Bernardo, Bryan T. MacDonald, Peter Libby, Hilary K. Finucane, and Pradeep Natarajan
Subjects: Multidisciplinary, ADAMTS7 Protein, Humans, Genetic Pleiotropy, Genetic Predisposition to Disease, Coronary Artery Disease, Pneumonia, cardiovascular diseases, Polymorphism, Single Nucleotide, Receptors, Interleukin-6, Genome-Wide Association Study
Abstract: Coronary artery disease (CAD) remains the leading cause of death despite scientific advances. Elucidating shared CAD/pneumonia pathways may reveal novel insights regarding CAD pathways. We performed genome-wide pleiotropy analyses of CAD and pneumonia, examined the causal effects of the expression of genes near independently replicated SNPs and interacting genes with CAD and pneumonia, and tested interactions between disruptive coding mutations of each pleiotropic gene and smoking status on CAD and pneumonia risks. Identified pleiotropic SNPs were annotated to ADAMTS7 and IL6R . Increased ADAMTS7 expression across tissues consistently showed decreased risk for CAD and increased risk for pneumonia; increased IL6R expression showed increased risk for CAD and decreased risk for pneumonia. We similarly observed opposing CAD/pneumonia effects for NLRP3 . Reduced ADAMTS7 expression conferred a reduced CAD risk without increased pneumonia risk only among never-smokers. Genetic immune-inflammatory axes of CAD linked to respiratory infections implicate ADAMTS7 and IL6R , and related genes.
Published: 2022

17. Identifying the Common Genetic Basis of Antidepressant Response

Author: Sara A. Paciga, Richard M. Weinshilboum, Andrew M. McIntosh, Tim B. Bigdeli, Stephanie H. Witt, Sven Cichon, Glyn Lewis, Henning Teismann, Brenda W.J.H. Penninx, Gerome Breen, Roseann E. Peterson, Saira Saeed Mirza, Diego Albani, Lisa Jones, Andreas J. Forstner, Sara Mostafavi, Julien Bryois, Qingqin S. Li, Kenneth S. Kendler, Thomas Damm Als, Fernando S. Goes, Marie Bækvad-Hansen, Nancy L. Pedersen, Gianluigi Forloni, Per Qvist, Carsten Horn, Per Hoffmann, Steven P. Hamilton, Georg Homuth, Michael Gill, Julien Mendlewicz, Katharina Domschke, Volker Arolt, Adrian I. Campos, Christine Søholm Hansen, Scott D. Gordon, Hogni Oskarsson, Peter McGuffin, Oliver Pain, Eric Jorgenson, Victoria S. Marshe, Stacy Steinberg, Bertram Müller-Myhsok, Mark Adams, J. Raymond DePaulo, Rick Jansen, Katherine J. Aitchison, Vassily Trubetskoy, Henry Völzke, Manuel Mattheisen, Bernard Ng, James A. Knowles, Dorret I. Boomsma, Tracy Air, Elisabeth B. Binder, Ian B. Hickie, Christel M. Middeldorp, Tõnu Esko, David M. Hougaard, E.J.C. de Geus, Toni-Kim Clarke, Helena Gaspar, Bernhard T. Baune, Abdel Abdellaoui, Engilbert Sigurdsson, Andres Metspalu, Klaus Berger, Jorge A. Quiroz, Patrick F. Sullivan, Aartjan T.F. Beekman, Thomas Hansen, Panagiotis Ferentinos, Jürgen Wellmann, Miguel E. Rentería, Daniel Umbricht, Marcella Rietschel, Stanley I. Shyn, Chiara Fabbri, Hreinn Stefansson, Jerome C. Foo, Daniel Souery, Zoltán Kutalik, Yu-Li Liu, Paul F. O'Reilly, Michael John Owen, Nese Direk, Douglas F. Levinson, Stuart Montgomery, Hamdi Mbarek, David M. Howard, Guido Bondolfi, Lucía Colodro-Conde, Pippa A. Thomson, Merete Nordentoft, Stefan Kloiber, Yunpeng Wang, Michael Conlon O'Donovan, Grant C.B. Sinnamon, Alexander Viktorin, Hilary K. Finucane, Esben Agerbo, Stefan Herms, Markus M. Nöthen, Till F. M. Andlauer, Divya Mehta, Bradley T. Webb, Joanna M. Biernacka, David J. Porteous, Jordan W. Smoller, Jonathan R. I. Coleman, Dean F. MacKinnon, Farnush Farhadi Hassan Kiadeh, Baptiste Couvy-Duchesne, Evelin Mihailov, Eleanor M. Wigmore, Franziska Degenhardt, Jianxin Shi, Dale R. Nyholt, Enda M. Byrne, Stephan Ripke, Ole Mors, Patrik K. E. Magnusson, Eric J. Lenze, Warren W. Kretzschmar, Masaki Kato, Marcus Ising, Ian Jones, Lynsey S. Hall, Wouter J. Peyrot, Ling Shen, Nader Perroud, Na Cai, Maciej Trzaskowski, Matthias Nauck, Isaac S. Kohane, Enrico Domenici, Fabian Streit, James L. Kennedy, Peter M. Visscher, Valentina Escott-Price, Donald J. MacIntyre, Enrique Castelao, Margarita Rivera, Mojca Z. Dernovsek, John P. Rice, Joseph Zohar, Gail Davies, Andrew C. Heath, Josef Frank, Wesley K. Thompson, Caroline Hayward, Penelope A. Lind, Thorgeir E. Thorgeirsson, Rudolf Uher, Jana Strohmaier, Henriette N. Buttenschøn, Erin C. Dunn, Jonas Bybjerg-Grauholm, Alexander Teumer, Jakob Grove, Eske M. Derks, Nicholas G. Martin, Jodie N. Painter, Myrna M. Weissman, Preben Bo Mortensen, Michel G. Nivard, Catherine Schaefer, Yihan Li, Daniel J. Smith, Shih-Jen Tsai, Niamh Mullins, Jian Yang, Marianne Giørtz Pedersen, Dan Rujescu, Thomas G. Schulze, Lili Milani, Yuri Milaneschi, Giorgio Pistis, James B. Potash, Neven Henigsberg, Nicholas John Craddock, Karen Hodgson, Silviu-Alin Bacanu, Shantel Weinsheimer, Charles F. Reynolds, Johannes H. Smit, Gonneke Willemsen, Futao Zhang, Henning Tiemeier, Grant W. Montgomery, Martin Preisig, Udo Dannlowski, Thalia C. Eley, Thomas Werge, Katherine E. Tansey, Jane H. Christensen, Julia Kraft, Ian J. Deary, Cathryn M. Lewis, Sarah E. Medland, André G. Uitterlinden, Daniel J. Müller, Carsten Bøcker Pedersen, Gustavo Turecki, Hans J. Grabe, Matthew Traylor, Brien P. Riley, Roy H. Perlis, Patrick J. McGrath, Conor V. Dolan, Hualin S. Xi, Jonathan Marchini, Robert A. Schoevers, Albert M. van Hemert, Anders D. Børglum, Susanne Lucae, Jouke-Jan Hottenga, Kari Stefansson, Benoit H. Mulsant, Francis M. Mondimore, Naomi R. Wray, Yang Wu, Wolfgang Maier, Danielle Posthuma, Annamaria Cattaneo, Gregory E. Crawford, Siegfried Kasper, Alessandro Serretti, Tania Carrillo-Roa, Robert Maier, Pamela A. F. Madden, Eva C. Schulte, Jens Treutlein, Joanna Hauser, Sandra Van der Auwera, Psychiatry, APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Complex Trait Genetics, APH - Methodology, Human genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Reproduction & Development (AR&D), Adult Psychiatry, Clinical Cognitive Neuropsychiatry Research Program (CCNP), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Epidemiology, Child and Adolescent Psychiatry / Psychology, and Internal Medicine
Subjects: Oncology, MDD, medicine.medical_specialty, Single-nucleotide polymorphism, Genome-wide association study, Biology, Antidepressant response, Depression, GWAS, Genetics, Polygenic score, SDG 3 - Good Health and Well-being, Internal medicine, Genetic variation, medicine, ddc:610, Genetic association, General Medicine, Heritability, medicine.disease, Schizophrenia, Sample size determination, Settore BIO/14 - Farmacologia, Major depressive disorder
Abstract: Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction.Methods: Genome-wide analysis of remission (nremit = 1852, nnonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism–based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA.Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism–based heritability was significantly different from zero for remission (h2 = 0.132, SE = 0.056) but not for percentage improvement (h2 = −0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response.Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.
Published: 2022

18. Leveraging fine-mapping and multipopulation training data to improve cross-population polygenic risk scores

Author: Omer, Weissbrod, Masahiro, Kanai, Huwenbo, Shi, Steven, Gazal, Wouter J, Peyrot, Amit V, Khera, Yukinori, Okada, Alicia R, Martin, Hilary K, Finucane, Yukihiro, Koretsune, APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Complex Trait Genetics, and Psychiatry
Subjects: Multifactorial Inheritance, Risk Factors, Genetics, Humans, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Genome-Wide Association Study
Abstract: Polygenic risk scores suffer reduced accuracy in non-European populations, exacerbating health disparities. We propose PolyPred, a method that improves cross-population polygenic risk scores by combining two predictors: a new predictor that leverages functionally informed fine-mapping to estimate causal effects (instead of tagging effects), addressing linkage disequilibrium differences, and BOLT-LMM, a published predictor. When a large training sample is available in the non-European target population, we propose PolyPred+, which further incorporates the non-European training data. We applied PolyPred to 49 diseases/traits in four UK Biobank populations using UK Biobank British training data, and observed relative improvements versus BOLT-LMM ranging from +7% in south Asians to +32% in Africans, consistent with simulations. We applied PolyPred+ to 23 diseases/traits in UK Biobank east Asians using both UK Biobank British and Biobank Japan training data, and observed improvements of +24% versus BOLT-LMM and +12% versus PolyPred. Summary statistics-based analogs of PolyPred and PolyPred+ attained similar improvements.
Published: 2022

19. Prioritizing disease and trait causal variants at the TNFAIP3 locus using functional and genomic features

Author: Nir Hacohen, Caleb A. Lareau, Drew T. Bergman, Leif S. Ludwig, Masahiro Kanai, Robbyn Issner, John P. Ray, Steven K. Reilly, Eric S. Lander, Jesse M. Engreitz, Carl G. de Boer, Ryan Tewhey, Jacob C. Ulirsch, Charles P. Fulco, Aviv Regev, and Hilary K. Finucane
Subjects: 0301 basic medicine, Epigenomics, CRISPR-Cas9 genome editing, Linkage disequilibrium, Multifactorial Inheritance, Science, General Physics and Astronomy, Single-nucleotide polymorphism, Locus (genetics), Genomics, Biology, Proof of Concept Study, General Biochemistry, Genetics and Molecular Biology, Article, Linkage Disequilibrium, Autoimmune Diseases, 03 medical and health sciences, 0302 clinical medicine, Cell Line, Tumor, Genetic variation, Immunogenetics, Humans, Genetic Predisposition to Disease, lcsh:Science, Tumor Necrosis Factor alpha-Induced Protein 3, Genetic association, Genetics, Multidisciplinary, Haplotype, Genetic Variation, Functional genomics, General Chemistry, 030104 developmental biology, Haplotypes, Genetic Loci, Trait, lcsh:Q, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Genome-wide association studies have associated thousands of genetic variants with complex traits and diseases, but pinpointing the causal variant(s) among those in tight linkage disequilibrium with each associated variant remains a major challenge. Here, we use seven experimental assays to characterize all common variants at the multiple disease-associated TNFAIP3 locus in five disease-relevant immune cell lines, based on a set of features related to regulatory potential. Trait/disease-associated variants are enriched among SNPs prioritized based on either: (1) residing within CRISPRi-sensitive regulatory regions, or (2) localizing in a chromatin accessible region while displaying allele-specific reporter activity. Of the 15 trait/disease-associated haplotypes at TNFAIP3, 9 have at least one variant meeting one or both of these criteria, 5 of which are further supported by genetic fine-mapping. Our work provides a comprehensive strategy to characterize genetic variation at important disease-associated loci, and aids in the effort to identify trait causal genetic variants., While genome-wide association studies have yielded thousands of trait-associated loci, identifying causal variants remains challenging. Here, the authors perform seven genomics assays in various cell types to prioritize genetic variants in the TNFAIP3 locus, and report high-priority variants within disease-associated haplotypes.
Published: 2020

20. Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders

Author: Gabriëlla A.M. Blokland, Jakob Grove, Chia-Yen Chen, Chris Cotsapas, Stuart Tobet, Robert Handa, David St Clair, Todd Lencz, Bryan J. Mowry, Sathish Periyasamy, Murray J. Cairns, Paul A. Tooney, Jing Qin Wu, Brian Kelly, George Kirov, Patrick F. Sullivan, Aiden Corvin, Brien P. Riley, Tõnu Esko, Lili Milani, Erik G. Jönsson, Aarno Palotie, Hannelore Ehrenreich, Martin Begemann, Agnes Steixner-Kumar, Pak C. Sham, Nakao Iwata, Daniel R. Weinberger, Pablo V. Gejman, Alan R. Sanders, Joseph D. Buxbaum, Dan Rujescu, Ina Giegling, Bettina Konte, Annette M. Hartmann, Elvira Bramon, Robin M. Murray, Michele T. Pato, Jimmy Lee, Ingrid Melle, Espen Molden, Roel A. Ophoff, Andrew McQuillin, Nicholas J. Bass, Rolf Adolfsson, Anil K. Malhotra, Nicholas G. Martin, Janice M. Fullerton, Philip B. Mitchell, Peter R. Schofield, Andreas J. Forstner, Franziska Degenhardt, Sabrina Schaupp, Ashley L. Comes, Manolis Kogevinas, José Guzman-Parra, Andreas Reif, Fabian Streit, Lea Sirignano, Sven Cichon, Maria Grigoroiu-Serbanescu, Joanna Hauser, Jolanta Lissowska, Fermin Mayoral, Bertram Müller-Myhsok, Beata Świątkowska, Thomas G. Schulze, Markus M. Nöthen, Marcella Rietschel, John Kelsoe, Marion Leboyer, Stéphane Jamain, Bruno Etain, Frank Bellivier, John B. Vincent, Martin Alda, Claire O’Donovan, Pablo Cervantes, Joanna M. Biernacka, Mark Frye, Susan L. McElroy, Laura J. Scott, Eli A. Stahl, Mikael Landén, Marian L. Hamshere, Olav B. Smeland, Srdjan Djurovic, Arne E. Vaaler, Ole A. Andreassen, Bernhard T. Baune, Tracy Air, Martin Preisig, Rudolf Uher, Douglas F. Levinson, Myrna M. Weissman, James B. Potash, Jianxin Shi, James A. Knowles, Roy H. Perlis, Susanne Lucae, Dorret I. Boomsma, Brenda W.J.H. Penninx, Jouke-Jan Hottenga, Eco J.C. de Geus, Gonneke Willemsen, Yuri Milaneschi, Henning Tiemeier, Hans J. Grabe, Alexander Teumer, Sandra Van der Auwera, Uwe Völker, Steven P. Hamilton, Patrik K.E. Magnusson, Alexander Viktorin, Divya Mehta, Niamh Mullins, Mark J. Adams, Gerome Breen, Andrew M. McIntosh, Cathryn M. Lewis, David M. Hougaard, Merete Nordentoft, Ole Mors, Preben B. Mortensen, Thomas Werge, Thomas D. Als, Anders D. Børglum, Tracey L. Petryshen, Jordan W. Smoller, Jill M. Goldstein, Stephan Ripke, Benjamin M. Neale, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberly D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, David Curtis, Michael Davidson, Kenneth L. Davis, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, 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, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, 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, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee Chee Keong, 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, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Sandra Meier, Carin J. Meijer, Bela Melegh, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Vihra Milanova, Younes Mokrab, Derek W. Morris, Kieran C. Murphy, Inez Myin-Germeys, 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, 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, Ulrich Schall, Christian R. Schubert, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Hon-Cheong So, Chris C.A. Spencer, 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, Douglas H.R. Blackwood, Ariel Darvasi, Enrico Domenici, Michael Gill, Hugh Gurling, Christina M. Hultman, Assen V. Jablensky, Kenneth S. Kendler, Jo Knight, Qingqin S. Li, Jianjun Liu, Steven A. McCarroll, Jennifer L. Moran, Michael J. Owen, Carlos N. Pato, Danielle Posthuma, Pamela Sklar, Jens R. Wendland, Mark J. Daly, Michael C. O’Donovan, Peter Donnelly, Ines Barroso, Jenefer M. Blackwell, Matthew A. Brown, Juan P. Casas, Panos Deloukas, Audrey Duncanson, Janusz Jankowski, Hugh S. Markus, Christopher G. Mathew, Colin N.A. Palmer, Robert Plomin, Anna Rautanen, Stephen J. Sawcer, Richard C. Trembath, Ananth C. Viswanathan, Nicholas W. Wood, Gavin Band, Céline Bellenguez, Colin Freeman, Eleni Giannoulatou, Garrett Hellenthal, Richard Pearson, Matti Pirinen, Amy Strange, Zhan Su, Damjan Vukcevic, Cordelia Langford, Hannah Blackburn, Suzannah J. Bumpstead, Serge Dronov, Sarah Edkins, Matthew Gillman, Emma Gray, Rhian Gwilliam, Naomi Hammond, Sarah E. Hunt, Alagurevathi Jayakumar, Jennifer Liddle, Owen T. McCann, Simon C. Potter, Radhi Ravindrarajah, Michelle Ricketts, Avazeh Tashakkori-Ghanbaria, Matthew Waller, Paul Weston, Pamela Whittaker, Sara Widaa, Mark I. McCarthy, Maria J. Arranz, Steven Bakker, Stephan Bender, Benedicto Crespo-Facorro, Jeremy Hall, Conrad Iyegbe, Stephen Lawrie, Kuang Lin, Don H. Linszen, Ignacio Mata, Muriel Walshe, Matthias Weisbrod, Durk Wiersma, Vassily Trubetskoy, Yunpeng Wang, Jonathan R.I. Coleman, Héléna A. Gaspar, Christiaan A. de Leeuw, Jennifer M. Whitehead Pavlides, Maciej Trzaskowski, Enda M. Byrne, Liam Abbott, Huda Akil, Diego Albani, Ney Alliey-Rodriguez, Adebayo Anjorin, Verneri Antilla, Swapnil Awasthi, Judith A. Badner, Marie Bækvad-Hansen, Jack D. Barchas, Nicholas Bass, Michael Bauer, Richard Belliveau, Carsten Bøcker Pedersen, Erlend Bøen, Marco P. Boks, James Boocock, Monika Budde, William Bunney, Margit Burmeister, Jonas Bybjerg-Grauholm, Miquel Casas, Felecia Cerrato, Kimberly Chambert, Alexander W. Charney, Danfeng Chen, Claire Churchhouse, Toni-Kim Clarke, William Coryell, David W. Craig, Cristiana Cruceanu, Piotr M. Czerski, Anders M. Dale, Simone de Jong, Jurgen Del-Favero, J. Raymond DePaulo, Amanda L. Dobbyn, Ashley Dumont, Torbjørn Elvsåshagen, Chun Chieh Fan, Sascha B. Fischer, Matthew Flickinger, Tatiana M. Foroud, Liz Forty, Christine Fraser, 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, Weihua Guan, Martin Hautzinger, Urs Heilbronner, Maria Hipolito, Dominic Holland, Laura Huckins, Jessica S. Johnson, Radhika Kandaswamy, Robert Karlsson, Sarah Kittel-Schneider, 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, Anna Maaser, Donald J. MacIntyre, Pamela B. Mahon, Lina Martinsson, Steve McCarroll, Peter McGuffin, Melvin G. McInnis, James D. McKay, Helena Medeiros, Sarah E. Medland, Fan Meng, Grant W. Montgomery, Thomas W. Mühleisen, 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, Amy Perry, Andrea Pfennig, Eline J. Regeer, Céline S. Reinbold, John P. Rice, Fabio Rivas, Margarita Rivera, Euijung Ryu, Cristina Sánchez-Mora, Alan F. Schatzberg, William A. Scheftner, Nicholas J. Schork, Cynthia Shannon Weickert, Tatyana Shehktman, Paul D. Shilling, Claire Slaney, Janet L. Sobell, Christine Søholm Hansen, Anne T. Spijker, Michael Steffens, John S. Strauss, Szabolcs Szelinger, Robert C. Thompson, Thorgeir E. Thorgeirsson, Jens Treutlein, Helmut Vedder, Weiqing Wang, Stanley J. Watson, Thomas W. Weickert, Simon Xi, Wei Xu, Allan H. Young, Peter Zandi, Peng Zhang, Sebastian Zöllner, Abdel Abdellaoui, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Aartjan T.F. Beekman, Elisabeth B. Binder, Julien Bryois, Henriette N. Buttenschøn, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Gregory E. Crawford, Gail Davies, Ian J. Deary, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Jerome C. Foo, Fernando S. Goes, Lynsey S. Hall, Thomas F. Hansen, Ian B. Hickie, Georg Homuth, Carsten Horn, David M. Howard, Marcus Ising, Rick Jansen, Ian Jones, Lisa A. Jones, Eric Jorgenson, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Dean F. MacKinnon, Robert M. Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Christel M. Middeldorp, Evelin Mihailov, Francis M. Mondimore, Sara Mostafavi, Matthias Nauck, Bernard Ng, Michel G. Nivard, Dale R. Nyholt, Paul F. O'Reilly, Hogni Oskarsson, Jodie N. Painter, Roseann E. Peterson, Wouter J. Peyrot, Giorgio Pistis, Jorge A. Quiroz, Per Qvist, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Stanley I. Shyn, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Katherine E. Tansey, Henning Teismann, Wesley Thompson, Pippa A. Thomson, Matthew Traylor, André G. Uitterlinden, Daniel Umbricht, Albert M. van Hemert, Shantel Marie Weinsheimer, Jürgen Wellmann, Yang Wu, Hualin S. Xi, Jian Yang, Futao Zhang, Volker Arolt, Klaus Berger, Udo Dannlowski, Katharina Domschke, Caroline Hayward, Andrew C. Heath, Stefan Kloiber, Glyn Lewis, Pamela AF. Madden, Patrik K. Magnusson, Preben Bo Mortensen, Michael C. O'Donovan, Sara A. Paciga, Nancy L. Pedersen, David J. Porteous, Catherine Schaefer, Henry Völzke, Marco Bortolato, Janita Bralten, Cynthia M. Bulik, Christie L. Burton, Caitlin E. Carey, Lea K. Davis, Laramie E. Duncan, Howard J. Edenberg, Lauren Erdman, Stephen V. Faraone, Slavina B. Goleva, Wei Guo, Christopher Hübel, Laura M. Huckins, Ekaterina A. Khramtsova, Joanna Martin, Carol A. Mathews, Elise Robinson, Eli Stahl, Barbara E. Stranger, Michela Traglia, Raymond K. Walters, Lauren A. Weiss, Stacey J. Winham, Yin Yao, Kristjar Skajaa, Markus Nöthen, Michael Owen, Robert H. Yolken, Niels Plath, Jonathan Mill, Daniel Geschwind, Psychiatry 1, RS: MHeNs - R2 - Mental Health, Psychiatrie & Neuropsychologie, Centre of Excellence in Complex Disease Genetics, Research Programme of Molecular Medicine, Research Programs Unit, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, Functional Genomics, Biological Psychology, APH - Mental Health, APH - Methodology, Sociology and Social Gerontology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Blokland, Gabriella AM, Grove, Jakob, Chen, Chia Yen, Cotsapas, Chris, Tobet, Stuart, Handa, Robert, Lee, Sang Hong, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Sex Differences Cross-Disorder Analysis Group of the Psychiatric Genomics Consortium, iPSYCH, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Human genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Reproduction & Development (AR&D), Child and Adolescent Psychiatry / Psychology, Adult Psychiatry, ANS - Complex Trait Genetics, and ANS - Mood, Anxiety, Psychosis, Stress & Sleep
Subjects: 0301 basic medicine, Male, Bipolar Disorder, Schizophrenia/genetics, LD SCORE REGRESSION, Genome-wide association study, 0302 clinical medicine, Receptors, SCHIZOPHRENIA, Psychotic Disorders/genetics, KYNURENINE PATHWAY METABOLISM, Genetics, RISK, Sex Characteristics, Vascular Endothelial Growth Factor, Bipolar Disorder/genetics, Major/genetics, Single Nucleotide, AFFECTIVE STIMULI IMPACT, Schizophrenia, Sulfurtransferases, Major depressive disorder, Female, Depressive Disorder, Major/genetics, Bipolar disorder, Locus (genetics), Genomics, Biology, Polymorphism, Single Nucleotide, Article, DYSPHORIC MOOD, 03 medical and health sciences, Sex differences, medicine, Humans, Genetic Predisposition to Disease, ddc:610, Polymorphism, GENOME-WIDE ASSOCIATION, Genotype-by-sex interaction, Biological Psychiatry, Depressive Disorder, Major, Depressive Disorder, GENDER-DIFFERENCES, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], PARAVENTRICULAR NUCLEUS, 3112 Neurosciences, Endothelial Cells, MAJOR DEPRESSION, medicine.disease, Genetic architecture, 030104 developmental biology, Mood, Receptors, Vascular Endothelial Growth Factor, Psychotic Disorders, 3111 Biomedicine, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Contains fulltext : 248656.pdf (Publisher’s version ) (Closed access) BACKGROUND: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. METHODS: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. RESULTS: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10(-8)), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10(-6)) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10(-7); rs73033497, p = 8.8 × 10(-7); rs7914279, p = 6.4 × 10(-7)), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10(-7)) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10(-7)), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10(-7)) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). CONCLUSIONS: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
Published: 2022

21. Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Author: Niamh Mullins, JooEun Kang, Adrian I. Campos, Jonathan R.I. Coleman, Alexis C. Edwards, Hanga Galfalvy, Daniel F. Levey, Adriana Lori, Andrey Shabalin, Anna Starnawska, Mei-Hsin Su, Hunna J. Watson, Mark Adams, Swapnil Awasthi, Michael Gandal, Jonathan D. Hafferty, Akitoyo Hishimoto, Minsoo Kim, Satoshi Okazaki, Ikuo Otsuka, Stephan Ripke, Erin B. Ware, Andrew W. Bergen, Wade H. Berrettini, Martin Bohus, Harry Brandt, Xiao Chang, Wei J. Chen, Hsi-Chung Chen, Steven Crawford, Scott Crow, Emily DiBlasi, Philibert Duriez, Fernando Fernández-Aranda, Manfred M. Fichter, Steven Gallinger, Stephen J. Glatt, Philip Gorwood, Yiran Guo, Hakon Hakonarson, Katherine A. Halmi, Hai-Gwo Hwu, Sonia Jain, Stéphane Jamain, Susana Jiménez-Murcia, Craig Johnson, Allan S. Kaplan, Walter H. Kaye, Pamela K. Keel, James L. Kennedy, Kelly L. Klump, Dong Li, Shih-Cheng Liao, Klaus Lieb, Lisa Lilenfeld, Chih-Min Liu, Pierre J. Magistretti, Christian R. Marshall, James E. Mitchell, Eric T. Monson, Richard M. Myers, Dalila Pinto, Abigail Powers, Nicolas Ramoz, Stefan Roepke, Vsevolod Rozanov, Stephen W. Scherer, Christian Schmahl, Marcus Sokolowski, Michael Strober, Laura M. Thornton, Janet Treasure, Ming T. Tsuang, Stephanie H. Witt, D. Blake Woodside, Zeynep Yilmaz, Lea Zillich, Rolf Adolfsson, Ingrid Agartz, Tracy M. Air, Martin Alda, Lars Alfredsson, Ole A. Andreassen, Adebayo Anjorin, Vivek Appadurai, María Soler Artigas, Sandra Van der Auwera, M. Helena Azevedo, Nicholas Bass, Claiton H.D. Bau, Bernhard T. Baune, Frank Bellivier, Klaus Berger, Joanna M. Biernacka, Tim B. Bigdeli, Elisabeth B. Binder, Michael Boehnke, Marco P. Boks, Rosa Bosch, David L. Braff, Richard Bryant, Monika Budde, Enda M. Byrne, Wiepke Cahn, Miguel Casas, Enrique Castelao, Jorge A. Cervilla, Boris Chaumette, Sven Cichon, Aiden Corvin, Nicholas Craddock, David Craig, Franziska Degenhardt, Srdjan Djurovic, Howard J. Edenberg, Ayman H. Fanous, Jerome C. Foo, Andreas J. Forstner, Mark Frye, Janice M. Fullerton, Justine M. Gatt, Pablo V. Gejman, Ina Giegling, Hans J. Grabe, Melissa J. Green, Eugenio H. Grevet, Maria Grigoroiu-Serbanescu, Blanca Gutierrez, Jose Guzman-Parra, Steven P. Hamilton, Marian L. Hamshere, Annette Hartmann, Joanna Hauser, Stefanie Heilmann-Heimbach, Per Hoffmann, Marcus Ising, Ian Jones, Lisa A. Jones, Lina Jonsson, René S. Kahn, John R. Kelsoe, Kenneth S. Kendler, Stefan Kloiber, Karestan C. Koenen, Manolis Kogevinas, Bettina Konte, Marie-Odile Krebs, Mikael Landén, Jacob Lawrence, Marion Leboyer, Phil H. Lee, Douglas F. Levinson, Calwing Liao, Jolanta Lissowska, Susanne Lucae, Fermin Mayoral, Susan L. McElroy, Patrick McGrath, Peter McGuffin, Andrew McQuillin, Sarah E. Medland, Divya Mehta, Ingrid Melle, Yuri Milaneschi, Philip B. Mitchell, Esther Molina, Gunnar Morken, Preben Bo Mortensen, Bertram Müller-Myhsok, Caroline Nievergelt, Vishwajit Nimgaonkar, Markus M. Nöthen, Michael C. O’Donovan, Roel A. Ophoff, Michael J. Owen, Carlos Pato, Michele T. Pato, Brenda W.J.H. Penninx, Jonathan Pimm, Giorgio Pistis, James B. Potash, Robert A. Power, Martin Preisig, Digby Quested, Josep Antoni Ramos-Quiroga, Andreas Reif, Marta Ribasés, Vanesa Richarte, Marcella Rietschel, Margarita Rivera, Andrea Roberts, Gloria Roberts, Guy A. Rouleau, Diego L. Rovaris, Dan Rujescu, Cristina Sánchez-Mora, Alan R. Sanders, Peter R. Schofield, Thomas G. Schulze, Laura J. Scott, Alessandro Serretti, Jianxin Shi, Stanley I. Shyn, Lea Sirignano, Pamela Sklar, Olav B. Smeland, Jordan W. Smoller, Edmund J.S. Sonuga-Barke, Gianfranco Spalletta, John S. Strauss, Beata Świątkowska, Maciej Trzaskowski, Gustavo Turecki, Laura Vilar-Ribó, John B. Vincent, Henry Völzke, James T.R. Walters, Cynthia Shannon Weickert, Thomas W. Weickert, Myrna M. Weissman, Leanne M. Williams, Naomi R. Wray, Clement C. Zai, Allison E. Ashley-Koch, Jean C. Beckham, Elizabeth R. Hauser, Michael A. Hauser, Nathan A. Kimbrel, Jennifer H. Lindquist, Benjamin McMahon, David W. Oslin, Xuejun Qin, Esben Agerbo, Anders D. Børglum, Gerome Breen, Annette Erlangsen, Tõnu Esko, Joel Gelernter, David M. Hougaard, Ronald C. Kessler, Henry R. Kranzler, Qingqin S. Li, Nicholas G. Martin, Andrew M. McIntosh, Ole Mors, Merete Nordentoft, Catherine M. Olsen, David Porteous, Robert J. Ursano, Danuta Wasserman, Thomas Werge, David C. Whiteman, Cynthia M. Bulik, Hilary Coon, Ditte Demontis, Anna R. Docherty, Po-Hsiu Kuo, Cathryn M. Lewis, J. John Mann, Miguel E. Rentería, Daniel J. Smith, Eli A. Stahl, Murray B. Stein, Fabian Streit, Virginia Willour, Douglas M. Ruderfer, Manuel Mattheisen, Abdel Abdellaoui, Mark J. Adams, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Jane Hvarregaard Christensen, Toni-Kim Clarke, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Nick Craddock, Gregory E. Crawford, Gail Davies, Eske M. 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J., Wasserman, D., Coon, H., Demontis, D., Docherty, A. R., Kuo, P. -H., Mann, J. J., Renteria, M. E., Stein, M. B., Willour, V., Psychiatry, Biological Psychology, APH - Methodology, APH - Mental Health, APH - Health Behaviors & Chronic Diseases, AMS - Sports, AMS - Ageing & Vitality, APH - Personalized Medicine, Amsterdam Neuroscience - Complex Trait Genetics, Complex Trait Genetics, Institute for Molecular Medicine Finland, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, Genomics of Neurological and Neuropsychiatric Disorders, HUS Psychiatry, Department of Public Health, Clinicum, Nuorisopsykiatria, Faculty Common Matters (Faculty of Social Sciences), Samuli Olli Ripatti / Principal Investigator, Complex Disease Genetics, Biostatistics Helsinki, Anna Keski-Rahkonen / Principal Investigator, Elisabeth Ingrid Maria Widen / Principal Investigator, Genomic Discoveries and Clinical Translation, Internal medicine, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Digital Health, Mullins N., Kang J., Campos A.I., Coleman J.R.I., Edwards A.C., Galfalvy H., Levey D.F., Lori A., Shabalin A., Starnawska A., Su M.-H., Watson H.J., Adams M., Awasthi S., Gandal M., Hafferty J.D., Hishimoto A., Kim M., Okazaki S., Otsuka I., Ripke S., Ware E.B., Bergen A.W., Berrettini W.H., Bohus M., Brandt H., Chang X., Chen W.J., Chen H.-C., Crawford S., Crow S., DiBlasi E., Duriez P., Fernandez-Aranda F., Fichter M.M., Gallinger S., Glatt S.J., Gorwood P., Guo Y., Hakonarson H., Halmi K.A., Hwu H.-G., Jain S., Jamain S., Jimenez-Murcia S., Johnson C., Kaplan A.S., Kaye W.H., Keel P.K., Kennedy J.L., Klump K.L., Li D., Liao S.-C., Lieb K., Lilenfeld L., Liu C.-M., Magistretti P.J., Marshall C.R., Mitchell J.E., Monson E.T., Myers R.M., Pinto D., Powers A., Ramoz N., Roepke S., Rozanov V., Scherer S.W., Schmahl C., Sokolowski M., Strober M., Thornton L.M., Treasure J., Tsuang M.T., Witt S.H., Woodside D.B., Yilmaz Z., Zillich L., Adolfsson R., Agartz I., Air T.M., Alda M., Alfredsson L., Andreassen O.A., Anjorin A., Appadurai V., Soler Artigas M., Van der Auwera S., Azevedo M.H., Bass N., Bau C.H.D., Baune B.T., Bellivier F., Berger K., Biernacka J.M., Bigdeli T.B., Binder E.B., Boehnke M., Boks M.P., Bosch R., Braff D.L., Bryant R., Budde M., Byrne E.M., Cahn W., Casas M., Castelao E., Cervilla J.A., Chaumette B., Cichon S., Corvin A., Craddock N., Craig D., Degenhardt F., Djurovic S., Edenberg H.J., Fanous A.H., Foo J.C., Forstner A.J., Frye M., Fullerton J.M., Gatt J.M., Gejman P.V., Giegling I., Grabe H.J., Green M.J., Grevet E.H., Grigoroiu-Serbanescu M., Gutierrez B., Guzman-Parra J., Hamilton S.P., Hamshere M.L., Hartmann A., Hauser J., Heilmann-Heimbach S., Hoffmann P., Ising M., Jones I., Jones L.A., Jonsson L., Kahn R.S., Kelsoe J.R., Kendler K.S., Kloiber S., Koenen K.C., Kogevinas M., Konte B., Krebs M.-O., Landen M., Lawrence J., Leboyer M., Lee P.H., Levinson D.F., Liao C., Lissowska J., Lucae S., Mayoral F., McElroy S.L., McGrath P., McGuffin P., McQuillin A., Medland S.E., Mehta D., Melle I., Milaneschi Y., Mitchell P.B., Molina E., Morken G., Mortensen P.B., Muller-Myhsok B., Nievergelt C., Nimgaonkar V., Nothen M.M., O'Donovan M.C., Ophoff R.A., Owen M.J., Pato C., Pato M.T., Penninx B.W.J.H., Pimm J., Pistis G., Potash J.B., Power R.A., Preisig M., Quested D., Ramos-Quiroga J.A., Reif A., Ribases M., Richarte V., Rietschel M., Rivera M., Roberts A., Roberts G., Rouleau G.A., Rovaris D.L., Rujescu D., Sanchez-Mora C., Sanders A.R., Schofield P.R., Schulze T.G., Scott L.J., Serretti A., Shi J., Shyn S.I., Sirignano L., Sklar P., Smeland O.B., Smoller J.W., Sonuga-Barke E.J.S., Spalletta G., Strauss J.S., Swiatkowska B., Trzaskowski M., Turecki G., Vilar-Ribo L., Vincent J.B., Volzke H., Walters J.T.R., Shannon Weickert C., Weickert T.W., Weissman M.M., Williams L.M., Wray N.R., Zai C.C., Ashley-Koch A.E., Beckham J.C., Hauser E.R., Hauser M.A., Kimbrel N.A., Lindquist J.H., McMahon B., Oslin D.W., Qin X., Mattheisen M., Abdellaoui A., Adams M.J., Agerbo E., Andlauer T.F.M., Bacanu S.-A., Baekvad-Hansen M., Beekman A.T.F., Bryois J., Buttenschon H.N., Bybjerg-Grauholm J., Cai N., Christensen J.H., Clarke T.-K., Colodro-Conde L., Couvy-Duchesne B., Crawford G.E., Davies G., Derks E.M., Direk N., Dolan C.V., Dunn E.C., Eley T.C., Escott-Price V., Hassan Kiadeh F.F., Finucane H.K., Frank J., Gaspar H.A., Gill M., Goes F.S., Gordon S.D., Weinsheimer S.M., Wellmann J., Willemsen G., Wu Y., Xi H.S., Yang J., Zhang F., Arolt V., Boomsma D.I., Dannlowski U., de Geus E.J.C., Depaulo J.R., Domenici E., Domschke K., Esko T., Grove J., Hall L.S., Hansen C.S., Hansen T.F., Herms S., Hickie I.B., Homuth G., Horn C., Hottenga J.-J., Hougaard D.M., Howard D.M., Jansen R., Jorgenson E., Knowles J.A., Kohane I.S., Kraft J., Kretzschmar W.W., Kutalik Z., Li Y., Lind P.A., MacIntyre D.J., MacKinnon D.F., Maier R.M., Maier W., Marchini J., Mbarek H., Middeldorp C.M., Mihailov E., Milani L., Mondimore F.M., Montgomery G.W., Mostafavi S., Nauck M., Ng B., Nivard M.G., Nyholt D.R., O'Reilly P.F., Oskarsson H., Hayward C., Heath A.C., Lewis G., Li Q.S., Madden P.A.F., Magnusson P.K., Martin N.G., McIntosh A.M., Metspalu A., Mors O., Nordentoft M., Paciga S.A., Pedersen N.L., Painter J.N., Pedersen C.B., Pedersen M.G., Peterson R.E., Peyrot W.J., Posthuma D., Quiroz J.A., Qvist P., Rice J.P., Riley B.P., Mirza S.S., Schoevers R., Schulte E.C., Shen L., Sigurdsson E., Sinnamon G.C.B., Smit J.H., Smith D.J., Stefansson H., Steinberg S., Streit F., Strohmaier J., Tansey K.E., Teismann H., Teumer A., Thompson W., Thomson P.A., Thorgeirsson T.E., Traylor M., Treutlein J., Trubetskoy V., Uitterlinden A.G., Umbricht D., der Auwera S.V., van Hemert A.M., Viktorin A., Visscher P.M., Wang Y., Webb B.T., Perlis R.H., Porteous D.J., Schaefer C., Stefansson K., Tiemeier H., Uher R., Werge T., Lewis C.M., Breen G., Borglum A.D., Sullivan P.F., O'Connell K.S., Coombes B., Qiao Z., Als T.D., Borte S., Charney A.W., Drange O.K., Gandal M.J., Hagenaars S.P., Ikeda M., Kamitaki N., Krebs K., Panagiotaropoulou G., Schilder B.M., Sloofman L.G., Winsvold B.S., Won H.-H., Abramova L., Adorjan K., Al Eissa M., Albani D., Alliey-Rodriguez N., Antilla V., Antoniou A., Baek J.H., Bauer M., Beins E.C., Bergen S.E., Birner A., Boen E., Brum M., Brumpton B.M., Brunkhorst-Kanaan N., Byerley W., Cairns M., Cervantes P., Cruceanu C., Cuellar-Barboza A., Cunningham J., Curtis D., Czerski P.M., Dale A.M., Dalkner N., David F.S., Dobbyn A.L., Douzenis A., Elvsashagen T., Ferrier I.N., Fiorentino A., Foroud T.M., Forty L., Frei O., Freimer N.B., Frisen L., Gade K., Garnham J., Gelernter J., Gizer I.R., Gordon-Smith K., Greenwood T.A., Ha K., Haraldsson M., Hautzinger M., Heilbronner U., Hellgren D., Holmans P.A., Huckins L., Johnson J.S., Kalman J.L., Kamatani Y., Kittel-Schneider S., Koromina M., Kranz T.M., Kranzler H.R., Kubo M., Kupka R., Kushner S.A., Lavebratt C., Leber M., Lee H.-J., Levy S.E., Lewis C., Lundberg M., Magnusson S.H., Maihofer A., Malaspina D., Maratou E., Martinsson L., McGregor N.W., McKay J.D., Medeiros H., Millischer V., Moran J.L., Morris D.W., Muhleisen T.W., O'Brien N., O'Donovan C., Olde Loohuis L.M., Oruc L., Papiol S., Pardinas A.F., Perry A., Pfennig A., Porichi E., Raj T., Rapaport M.H., Regeer E.J., Rivas F., Roth J., Roussos P., Ruderfer D.M., Senner F., Sharp S., Shilling P.D., Slaney C., Sobell J.L., Artigas M.S., Spijker A.T., Stein D.J., Terao C., Toma C., Tooney P., Tsermpini E.-E., Vawter M.P., Vedder H., Xi S., Xu W., Kay Yang J.M., Young A.H., Young H., Zandi P.P., Zhou H., HUNT All-In Psychiatry, Babadjanova G., Backlund L., Bengesser S., Blackwood D.H.R., Carr V.J., Catts S., Dikeos D., Etain B., Ferentinos P., Gawlik M., Gershon E.S., Henskens F., Hillert J., Hong K.S., Hultman C.M., Hveem K., Iwata N., Jablensky A.V., Kirov G., Lochner C., Loughland C., Mathews C.A., McMahon F.J., Michie P., Mowry B., Neale B.M., Nievergelt C.M., Oedegaard K.J., Olsson T., Pantelis C., Patrinos G.P., Reininghaus E.Z., Saito T., Schall U., Schalling M., Scott R.J., Weickert C.S., Stordal E., Vaaler A.E., Vieta E., Waldman I.D., Zwart J.-A., Nurnberger J.I., Stahl E.A., Di Florio A., Adan R.A.H., Ando T., Aschauer H., Baker J.H., Bencko V., Birgegard A., Boden J.M., Boehm I., Boni C., Perica V.B., Buehren K., Bulik C.M., Burghardt R., Carlberg L., Cassina M., Clementi M., Cone R.D., Courtet P., Crowley J.J., Danner U.N., Davis O.S.P., de Zwaan M., Dedoussis G., Degortes D., DeSocio J.E., Dick D.M., Dina C., Dmitrzak-Weglarz M., Martinez E.D., Duncan L.E., Egberts K., Mattingsdal M., McDevitt S., Meulenbelt I., Micali N., Mitchell J., Mitchell K., Monteleone P., Monteleone A.M., Munn-Chernoff M.A., Nacmias B., Navratilova M., Ntalla I., Olsen C.M., O'Toole J.K., Padyukov L., Palotie A., Pantel J., Papezova H., Parker R., Pearson J.F., Ehrlich S., Escaramis G., Espeseth T., Estivill X., Farmer A., Favaro A., Fischer K., Floyd J.A.B., Focker M., Foretova L., Forzan M., Franklin C.S., Gambaro G., Giuranna J., Giusti-Rodriquez P., Gonidakis F., Gordon S., Mayora M.G., Guillaume S., Hanscombe K.B., Hatzikotoulas K., Hebebrand J., Helder S.G., Henders A.K., Herpertz-Dahlmann B., Herzog W., Hinney A., Horwood L.J., Hubel C., Petersen L.V., Purves K.L., Raevuori A., Reichborn-Kjennerud T., Ricca V., Ripatti S., Ritschel F., Roberts M., Rybakowski F., Santonastaso P., Scherag A., Schmidt U., Schork N.J., Schosser A., Seitz J., Slachtova L., Slagboom P.E., Slof-Op 't Landt M.C.T., Slopien A., Soranzo N., Sorbi S., Southam L., Steen V.W., Huckins L.M., Hudson J.I., Imgart H., Inoko H., Janout V., Jordan J., Julia A., Kalsi G., Kaminska D., Kaprio J., Karhunen L., Karwautz A., Kas M.J.H., Kennedy M.A., Keski-Rahkonen A., Kiezebrink K., Kim Y.-R., Kirk K.M., Klareskog L., Knudsen G.P.S., Larsen J.T., Le Hellard S., Leppa V.M., Lichtenstein P., Lin B.D., Lundervold A., Luykx J., Maj M., Mannik K., Marsal S., Stuber G.D., Szatkiewicz J.P., Tachmazidou I., Tenconi E., Tortorella A., Tozzi F., Tsitsika A., Tyszkiewicz-Nwafor M., Tziouvas K., van Elburg A.A., van Furth E.F., Wade T.D., Wagner G., Walton E., Whiteman D.C., Wichmann H.E., Widen E., Yao S., Zeggini E., Zerwas S., Zipfel S., Jungkunz M., Dietl L., Schwarze C.E., Dahmen N., Schott B.H., Mobascher A., Crivelli S., Dennis M.F., Harvey P.D., Carter B.W., Huffman J.E., Jacobson D., Madduri R., Olsen M.K., Pestian J., Gaziano J.M., Muralidhar S., Ramoni R., Beckham J., Chang K.-M., O'Donnell C.J., Tsao P.S., Breeling J., Huang G., Romero J.P.C., Moser J., Whitbourne S.B., Brewer J.V., Aslan M., Connor T., Argyres D.P., Stephens B., Brophy M.T., Humphries D.E., Selva L.E., Do N., Shayan S., Cho K., Pyarajan S., Hauser E., Sun Y., Zhao H., Wilson P., McArdle R., Dellitalia L., Mattocks K., Harley J., Zablocki C.J., Whittle J., Jacono F., Gutierrez S., Gibson G., Hammer K., Kaminsky L., Villareal G., Kinlay S., Xu J., Hamner M., Mathew R., Bhushan S., Iruvanti P., Godschalk M., Ballas Z., Ivins D., Mastorides S., Moorman J., Gappy S., Klein J., Ratcliffe N., Florez H., Okusaga O., Murdoch M., Sriram P., Yeh S.S., Tandon N., Jhala D., Aguayo S., Cohen D., Sharma S., Liangpunsakul S., Oursler K.A., Whooley M., Ahuja S., Constans J., Meyer P., Greco J., Rauchman M., Servatius R., Gaddy M., Wallbom A., Morgan T., Stapley T., Sherman S., Ross G., Tsao P., Strollo P., Boyko E., Meyer L., Gupta S., Huq M., Fayad J., Hung A., Lichy J., Hurley R., Robey B., Striker R., Erlangsen A., Kessler R.C., Porteous D., Ursano R.J., Wasserman D., Coon H., Demontis D., Docherty A.R., Kuo P.-H., Mann J.J., Renteria M.E., Stein M.B., and Willour V.
Subjects: LD SCORE REGRESSION, Genome-wide association study, Suicide, Attempted, 3124 Neurology and psychiatry, 0302 clinical medicine, Risk Factors, Insomnia, Suicide attempt, GWAS, Suïcidi, Depression (differential diagnoses), Cause of death, Psychiatry, 0303 health sciences, Factors de risc en les malalties, Mental Disorders, Genetic Correlation, Genome-wide Association Study, Pleiotropy, Polygenicity, Suicide, Suicide Attempt, DEPRESSION, 3. Good health, Genetic correlation, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Depressive Disorder, Major, Mental illness, Cohort, SEX, medicine.symptom, Human, medicine.medical_specialty, Risk factors in diseases, BF, Locus (genetics), BEHAVIORS, Psykiatri, EVENTS, 03 medical and health sciences, SDG 3 - Good Health and Well-being, medicine, ddc:610, GENOME-WIDE ASSOCIATION, IDEATION, Socioeconomic status, METAANALYSIS, Biological Psychiatry, 030304 developmental biology, business.industry, Risk Factor, Genetic architecture, THOUGHTS, RC0321, business, Malalties mentals, 030217 neurology & neurosurgery
Abstract: Statistical analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org) hosted by SURFsara and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu), which is supported by the Office of Research Infrastructure of the National Institutes of Health (Grant Nos. S10OD018522 and S10OD026880). This work was conducted in part using the resources of the Advanced Computing Center for Research and Education at Vanderbilt University, Nashville, TN. This work was funded by the National Institutes of Health (Grant Nos. R01MH116269 and R01MH121455 [to DMR]), NIGMS of the National Institutes of Health (Grant No. T32GM007347 [to JK]), and the Brain & Behavior Research Foundation (NARSAD Young Investigator Award No. 29551 [to NM])., BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders., Office of Research Infrastructure of the National Institutes of Health S10OD018522 S10OD026880, United States Department of Health & Human Services, National Institutes of Health (NIH) - USA R01MH116269 R01MH121455, NIH National Institute of General Medical Sciences (NIGMS) T32GM007347 NARSAD 29551
Published: 2022

22. Global Biobank Meta-analysis Initiative: powering genetic discovery across human diseases

Author: Sarah Finer, Yen-Feng Lin, Michigan Genomics Initiative, Valeria Lo Faro, Benjamin M. Neale, Nathan Ingold, Estonian Biobank, Peter Straub, Jasmina Uzunovic, Triin Laisk, Whitney E. Hornsby, Sebastian Zoellner, Takahiro Konuma, Jordan A. Shavit, Masahiro Kanai, Xue Zhong, Stephen J. Wicks, Taiwan Biobank, Arjun Bhattacharya, Nicholas J. Douville, Yi Ding, BioVU, Jennifer E. Huffman, Christopher R. Gignoux, Kristian Hveem, Serena Sanna, Brooke N. Wolford, Mitja I. Kurki, Aarno Palotie, Yukinori Okada, FinnGen, Clara Lajonchere, Ida Surakka, Mass General Brigham Biobank, Jie Zheng, Caroline Hayward, Riccardo E. Marioni, Chris Griffiths, Lars G. Fritsche, Rasheed Humaira, Ben Michael Brumpton, Kristi Läll, Kuang Lin, Jordan W. Smoller, Lude Franke, Michelle Daya, David C. Whiteman, Karen A. Hunt, Harold Snieder, Jun Lv, Stuart MacGregor, Alicia R. Martin, Juha Karjalainen, Jonathan A. Shortt, Kuan-Han H. Wu, Jibril B Hirbo, Sameer Chavan, Marie-Julie Favé, Snehal Patil, Kristy Crooks, Sarah E. Graham, Tzu-Ting Chen, Michael Preuss, Matthew Zawistowski, Yen-Chen Anne Feng, Iona Y Millwood, Cisca Wijmenga, Cristen J. Willer, Jansonius Nomdo, Kristin Tsuo, Qimr Berghofer Biobank, Koichi Matsuda, LifeLines, Shinichi Namba, Nicholas M. Rafaels, Priit Palta, Unnur Thorsteinsdottir, Chia-Yen Chen, Generation Scotland, Cecilia M. Lindgren, Huiling Zhao, Andrea Ganna, Bogdan Pasaniuc, Maasha Mutaamba, Nancy J. Cox, Zhengming Chen, George Davey Smith, Mark J. Daly, Sarah E. Medland, Yu Guo, Daniel H. Geschwind, Matthew Law, Judith M. Vonk, Eimear E. Kenny, David J. Porteous, Tian Ge, Judy H. Cho, UK Biobank, Ruth J. F. Loos, Eric R. Gamazon, Wei Zhou, Richard C. Trembath, Philip Awadalla, Kathleen C. Barnes, David A. van Heel, Kari Stefansson, Archie Campbell, Hilary C. Martin, Tom R. Gaunt, Ruth E. Johnson, Sinéad B. Chapman, Esteban A Lopera-Maya, Michael Boehnke, Brett Vanderwerff, Catherine M. Olsen, Marike Boezen, Anita Pandit, BioMe, Ran Tao, Hilary K. Finucane, Anne Richmond, Ying Wang, Liming Li, Geertruida H. de Bock, John Wright, Xiang Zhou, Robin G. Walters, Reedik Mägi, and Hailiang Huang
Subjects: Disease gene, 0303 health sciences, South asia, Collaborative network, Genome-wide association study, Computational biology, Biology, Biobank, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Baseline characteristics, Meta-analysis, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract: SummaryBiobanks are being established across the world to understand the genetic, environmental, and epidemiological basis of human diseases with the goal of better prevention and treatments. Genome-wide association studies (GWAS) have been very successful at mapping genomic loci for a wide range of human diseases and traits, but in general, lack appropriate representation of diverse ancestries - with most biobanks and preceding GWAS studies composed of individuals of European ancestries. Here, we introduce the Global Biobank Meta-analysis Initiative (GBMI) -- a collaborative network of 19 biobanks from 4 continents representing more than 2.1 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWAS generated using harmonized genotypes and phenotypes from member biobanks. GBMI brings together results from GWAS analysis across 6 main ancestry groups: approximately 33,000 of African ancestry either from Africa or from admixed-ancestry diaspora (AFR), 18,000 admixed American (AMR), 31,000 Central and South Asian (CSA), 341,000 East Asian (EAS), 1.4 million European (EUR), and 1,600 Middle Eastern (MID) individuals. In this flagship project, we generated GWASs from across 14 exemplar diseases and endpoints, including both common and less prevalent diseases that were previously understudied. Using the genetic association results, we validate that GWASs conducted in biobanks worldwide can be successfully integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics between biobanks. We demonstrate the value of this collaborative effort to improve GWAS power for diseases, increase representation, benefit understudied diseases, and improve risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of the studied traits.
Published: 2021

23. Insights from complex trait fine-mapping across diverse populations

Author: Qingbo Wang, Hannah Jacobs, Yukinori Okada, Saori Sakaue, Benjamin M. Neale, Juha Karjalainen, Konrad J. Karczewski, Kaur Alasoo, Nurlan Kerimov, Ryan Tewhey, Yoichiro Kamatani, Pardis C. Sabeti, Koichi Matsuda, Christian Benner, Eric B. Fauman, Masahiro Kanai, FinnGen, François Aguet, Kazuyoshi Ishigaki, Mark J. Daly, Jacob C. Ulirsch, Hilary K. Finucane, Mitja I. Kurki, Aarno Palotie, Kristin G. Ardlie, and Steven K. Reilly
Subjects: 0303 health sciences, Genome-wide association study, Biology, Biobank, 03 medical and health sciences, 0302 clinical medicine, Evolutionary biology, Trait, Identification (biology), Allele, Allele frequency, Gene, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract: Despite the great success of genome-wide association studies (GWAS) in identifying genetic loci significantly associated with diseases, the vast majority of causal variants underlying disease-associated loci have not been identified1–3. To create an atlas of causal variants, we performed and integrated fine-mapping across 148 complex traits in three large-scale biobanks (BioBank Japan4,5, FinnGen6, and UK Biobank7,8; total n = 811,261), resulting in 4,518 variant-trait pairs with high posterior probability (> 0.9) of causality. Of these, we found 285 high-confidence variant-trait pairs replicated across multiple populations, and we characterized multiple contributors to the surprising lack of overlap among fine-mapping results from different biobanks. By studying the bottlenecked Finnish and Japanese populations, we identified 21 and 26 putative causal coding variants with extreme allele frequency enrichment (> 10-fold) in these two populations, respectively. Aggregating data across populations enabled identification of 1,492 unique fine-mapped coding variants and 176 genes in which multiple independent coding variants influence the same trait (i.e., with an allelic series of coding variants). Our results demonstrate that fine-mapping in diverse populations enables novel insights into the biology of complex traits by pinpointing high-confidence causal variants for further characterization.
Published: 2021

24. Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Author: Wei Zhou, Masahiro Kanai, 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, Hilary K. Finucane, 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, Alicia R. Martin, Cristen J. Willer, Mark J. Daly, Benjamin M. Neale, Samuli Olli Ripatti / Principal Investigator, University of Helsinki, Institute for Molecular Medicine Finland, Complex Disease Genetics, Genomics of Neurological and Neuropsychiatric Disorders, Data Science Genetic Epidemiology Lab, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, Basic and Translational Research and Imaging Methodology Development in Groningen (BRIDGE), Life Course Epidemiology (LCE), Damage and Repair in Cancer Development and Cancer Treatment (DARE), Perceptual and Cognitive Neuroscience (PCN), Groningen Research Institute for Asthma and COPD (GRIAC), Stem Cell Aging Leukemia and Lymphoma (SALL), and Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI)
Subjects: biobank, meta-analysis, genetic association studies, 1184 Genetics, developmental biology, physiology, GWAS, 3111 Biomedicine, biobank meta-analysis, ancestry diversity, phenotype harmonization
Abstract: Funding Information: The work of the contributing biobanks was supported by numerous grants from governmental and charitable bodies. Biobank-specific acknowledgments and more detailed acknowledgments are included in Data S2. Initiative management, S.B.C. J.C. N.J.C. M.J.D. E.E.K. A.R.M. B.M.N. Y.O. A.V.P. D.A.v.H. R.G.W. C.J.W. W.Z. and S.Z.; individual biobank analysis, A.B. Y.B. B.M.B. C.D.B. S.C. T.-T.C. K.C. S.M.D. M.D. G.H.d.B. Y.D. N.J.D. M.-J.F. Y.-C.A.F. S.F. V.L.F. L.G.F. E.R.G. T.R.G. D.H.G. C.R.G. G.G.-A. S.E.G. L.A.G. C.H. J.B.H. W.E.H. H.H. K.H. N.I. A.I. R.J. M. Kurki, J.K. N.K. E.E.K. J.T.K. M. Kanai, T.L. K.L. M.H.L. S.L. K.L. Y.-F.L. V.L.F. R.J.F.L. E.A.L.-M. A.R.-M. S.M.-G. R.M. R.E.M. H.C.M. A.R.M. Y.M. H.M. S.E.M. I.Y.M. B.M. S.M. K.N. S.N. M.A.N.-A. K.N. Y.O. P.P. A.L.-P. A.P. B.P. S.P. M.H.P. D.J.R. N.R. M.D.R. A.R. C.S. S.S. S.S.S. J.A.S. P.S. I.S. T.T. R.T. K.T. J.U. D.A.v.H. B.V. M.V. Y.V. J.M.V. R.G.W. Y.W. S.J.W. B.N.W. K.-H.H.W. M.Z. X.Z. and S.Z.; individual biobank management, N.A. A.A.T. K.M.A.-D. P.A. K.C.B. M. Boehnke, M. Boezen, C.D.B. A.C. Z.C. C.-Y.C. J.C. N.J.C. S.M.D. S.F. Y.-C.A.F. S.F. E.F. T.G. C.R.G. C.J.G. Y.G. H.H. K.A.H. K.H. S.I.I. N.M.J. N.K. E.E.K. J.T.K. C.L. M.H.L. M.T.M.L. L.L. K.L. Y.-F.L. R.J.F.L. J.L. S.M. Y.M. K.M. I.Y.M. Y.O. C.M.O. A.V.P. B.P. D.J.P. D.J.R. M.D.R. S.S. J.W.S. H.S. K.S. T.T. U.T. R.C.T. D.A.v.H. M.V. R.G.W. D.C.W. C.W. J.W. M.Z. X.Z. and S.Z.; study design and interpretation of results, A.B. M. Boehnke, M. Boezen, B.M.B. T.-T.C. C.-Y.C. M.J.D. G.D.S. N.J.D. S.F. M.-J.F. H.K.F. E.R.G. A.G. T.G. J.B.H. J.H. K.H. R.J. M.K. E.E.K. T.K. C.M.L. V.L.F. E.A.L.-M. A.R.M. S.N. B.M.N. C.M.O. J.J.P. B.P. N.R. H.R. J.A.S. I.S. K.T. D.A.v.H. R.G.W. Y.W. D.C.W. S.J.W. C.J.W. B.N.W. J.W. K.-H.H.W. M.Z. H.Z. J.Z. W.Z. X.Z. and S.Z.; drafted and edited the paper, A.B. M. Boehnke, M. Boezen, M.J.D. G.H.d.B. N.J.D. T.R.G. J.B.H. N.I. N.M.J. M.K. V.L.F. S.M. A.R.M. H.M. S.N. B.M.N. C.M.O. B.P. H.R. C.S. J.A.S. J.W.S. K.T. Y.W. D.C.W. C.J.W. K.-H.H.W. H.Z. J.Z. W.Z. and S.Z.; primary meta-analysis and quality control, M.J.D. H.K.F. M. Kanai, J.K. J.T.K. M. Kurki, M.M. B.M.N. C.J.W. K.-H.H.W. and W.Z.; drug discovery: S.N. T.K. K.-H.H.W. W.Z. and Y.O.; fine mapping, M. Kanai, W.Z. M.J.D. and H.K.F.; polygenic risk score, Y.W. S.N. E.A.L.-M. S.K. K.T. K.L. M. Kanai, W.Z. K.W. M.-J.F. L.B. P.A. P.D. V.L.F. R.M. Y.M. B.B. S.S. J.U. E.R.G. N.J.C. I.S. Y.O. A.R.M. and J.B.H.; proteome-wide Mendelian randomization, H.Z. H.R. A.B. G.H. G.D.S. B.M.B. W.Z. B.M.N. T.R.G. and J.Z.; transcriptome-wide association study, A.B. J.B.H. W.Z. J.Z. M. Kanai, B.P. E.R.G. and N.J.C.; asthma, K.T. W.Z. Y.W. M. Kanai, S.N. Y.O. B.M.N. M.J.D. and A.R.M.; heart failure, K.-H.H.W. N.J.D. B.N.W. I.S. S.E.G. J.B.H. N.J.C. M.P. R.J.F.L. M.J.D. B.M.N. W.Z. W.E.H. and C.J.W.; idiopathic pulmonary fibrosis, J.J.P. W.Z. M.J.D. J.T.K. N.J.C. and J.B.H.; primary open-angle glaucoma, V.L.F. A.B. W.Z. Y.W. K.L. M. Kanai, E.A.L.-M. P.S. R.T. X.Z. S.N. S.S. Y.O. N.I. S.M. H.S. I.S. C.W. A.R.M. E.R.G. N.M.J. N.J.C. and J.B.H.; stroke, I.S. K.-H.H.W. W.H. B.N.W. W.Z. J.E.H. A.P. B.B. A.H.S. M.E.G. R.G.W. K.H. C.K. S.Z. M.J.D. B.M.N. and C.J.W.; venous thromboembolism, B.N.W. I.S. K.-H.H.W. B.B. V.L.F. K.T. M.D. B.N. W.Z. J.A.S. and C.J.W. All authors reviewed the manuscript. M.J.D. is a founder of Maze Therapeutics. B.M.N. is a member of the scientific advisory board at Deep Genomics and a consultant for Camp4 Therapeutics, Takeda Pharmaceutical, and Biogen. The spouse of C.J.W. works at Regeneron Pharmaceuticals. C.-Y.C. is employed by Biogen. C.R.G. owns stock in 23andMe, Inc. T.R.G. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. E.E.K. has received speaker fees from Regeneron, Illumina, and 23andMe and is a member of the advisory board for Galateo Bio. R.E.M. has received speaker fees from Illumina and is a scientific advisor to the Epigenetic Clock Development Foundation. G.D.S. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. K.S. and U.T. are employed by deCODE Genetics/Amgen, Inc. J.Z. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. S.M. is a co-founder of and holds stock in Seonix Bio. Publisher Copyright: © 2022 Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)—a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.
Published: 2022

25. Genome-wide pleiotropy analysis of coronary artery disease and pneumonia identifies shared immune pathways

Author: Hilary K. Finucane, Pradeep Natarajan, Seyedeh M. Zekavat, Rachel Bernardo, Peter Libby, Sara Haidermota, and Zhi Yu
Subjects: business.industry, CAD, Single-nucleotide polymorphism, medicine.disease, Bioinformatics, Genome, Coronary artery disease, Pneumonia, Pleiotropy, Medicine, cardiovascular diseases, business, Gene, Cause of death
Abstract: Coronary artery disease (CAD) remains the leading cause of death despite scientific advances. Elucidating shared CAD/pneumonia pathways may reveal novel insights regarding CAD pathways. We performed genome-wide pleiotropy analyses of CAD and pneumonia, examined the causal effects of the expression of genes near independently replicated SNPs and interacting genes with CAD and pneumonia, and tested interactions between disruptive coding mutations of each pleiotropic gene and smoking status on CAD and pneumonia risks. Identified pleiotropic SNPs were annotated to ADAMTS7 and IL6R. Increased ADAMTS7 expression across tissues consistently showed decreased risk for CAD and increased risk for pneumonia; increased IL6R expression showed increased risk for CAD and decreased risk for pneumonia. We similarly observed opposing CAD/pneumonia effects for NLRP3. Reduced ADAMTS7 expression conferred a reduced CAD risk without increased pneumonia risk only among never-smokers. Genetic immune-inflammatory axes of CAD linked to respiratory infections implicate ADAMTS7 and IL6R, and related genes.
Published: 2021

26. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants

Author: Helgadottir A, Giannakopoulou O, Costanzo Mc, Heribert Schunkert, Giardoglou P, Markus M. Nöthen, Zhou W, Thomas Meitinger, Deepak Atri, Murgia F, Amit Khera, Tao Jiang, Munz M, Jeanette Erdmann, Patrick T. Ellinor, Marju Orho-Melander, Rajat M. Gupta, Kazuyoshi Ishigaki, Satoshi Koyama, Güldener U, Dongkeun Jang, Hilary K. Finucane, George Hindy, George Dedoussis, Cristen J. Willer, Johan L.M. Björkegren, Aris Baras, Marc S. Sabatine, Flannick J, Arno Ruusalepp, Alanna C. Morrison, Danesh J, Christopher P. Nelson, Nicholas A Marston, Thorgeirsson G, Ida Surakka, Sherliker P, Kastrati A, Ibrahim M, Ito K, Robert Clarke, Christopher Grace, Minxian Wang, Boerwinkle E, Haider Smi, Anuj Goel, Ben Michael Brumpton, Lijiang Ma, Sekar Kathiresan, Li L, Pang S, Carolina Roselli, Issei Komuro, de Vries Ps, Kristian Hveem, Hilma Holm, Adam S. Butterworth, Lotta La, Panagiotis Deloukas, Unnur Thorsteinsdottir, Thorsten Kessler, Kamanu Fk, Roberts R, Arnar Do, Tom R. Webb, Ulirsch Jk, Jonas B. Nielsen, Reinberger T, Martin Farrall, Daniel F. Gudbjartsson, Elle M. Weeks, Kari Stefansson, Brooke N. Wolford, Krishna G. Aragam, Hugh Watkins, von Scheidt M, Yoichiro Kamatani, Pierre Zalloua, Christian T. Ruff, Muñoz Venegas L, Iftikhar J. Kullo, Gudmar Thorleifsson, Stavroula Kanoni, Olle Melander, Nilesh J. Samani, Michael R. Brown, Loukianos S. Rallidis, Jemma C. Hopewell, and Mucha S
Subjects: Coronary artery disease, Pathogenesis, medicine, CAD, Genome-wide association study, Vascular proliferation, Computational biology, Biology, Disease pathogenesis, medicine.disease, Gene
Abstract: Rapid progress of the discovery of genetic loci associated with common, complex diseases has outpaced the elucidation of mechanisms pertinent to disease pathogenesis. To address relevant barriers for coronary artery disease (CAD), we combined genetic discovery analyses with downstream characterization of likely causal variants, genes, and biological pathways. Specifically, we conducted a genome-wide association study (GWAS) comprising 181,522 cases of CAD among 1,165,690 participants. We detected 241 associations, including 54 associations and 30 loci not previously linked to CAD. Next, we prioritized likely causal variants using functionally-informed fine-mapping, yielding 42 associations with fewer than five variants in the 95% credible set. Combining eight complementary predictors, we prioritized 185 candidate causal genes, including 94 genes supported by three or more predictors. Similarity-based clustering underscored a role for early developmental processes, cell cycle signaling, and vascular proliferation in the pathogenesis of CAD. Our analysis identifies and systematically characterizes risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.
Published: 2021

27. Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs

Author: Ran Cui, Shuvom Sadhuka, Hilary K. Finucane, David R. Kelley, Carlos Albors, Yukinori Okada, François Aguet, Masahiro Kanai, Kristin G. Ardlie, Daniel G. MacArthur, Nathan Cheng, Qingbo Wang, and Jacob C. Ulirsch
Subjects: 0301 basic medicine, Epigenomics, Adult, Candidate gene, endocrine system diseases, Computer science, Science, Quantitative Trait Loci, General Physics and Astronomy, Datasets as Topic, Context (language use), Genome-wide association study, Computational biology, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Leverage (statistics), Humans, Genetic variation, Transcriptomics, Multidisciplinary, Gene Expression Profiling, Supervised learning, Chromosome Mapping, Computational Biology, General Chemistry, Biobank, 030104 developmental biology, Gene expression, Supervised Machine Learning, Experimental methods, 030217 neurology & neurosurgery
Abstract: The large majority of variants identified by GWAS are non-coding, motivating detailed characterization of the function of non-coding variants. Experimental methods to assess variants’ effect on gene expressions in native chromatin context via direct perturbation are low-throughput. Existing high-throughput computational predictors thus have lacked large gold standard sets of regulatory variants for training and validation. Here, we leverage a set of 14,807 putative causal eQTLs in humans obtained through statistical fine-mapping, and we use 6121 features to directly train a predictor of whether a variant modifies nearby gene expression. We call the resulting prediction the expression modifier score (EMS). We validate EMS by comparing its ability to prioritize functional variants with other major scores. We then use EMS as a prior for statistical fine-mapping of eQTLs to identify an additional 20,913 putatively causal eQTLs, and we incorporate EMS into co-localization analysis to identify 310 additional candidate genes across UK Biobank phenotypes., Finding causal variants and genes from GWAS loci results remains a challenge. Here, the authors train a model to predict if a variant affects nearby gene expression, and apply the method to identify new possible causal eQTLs and mechanisms of GWAS loci.
Published: 2021

28. Interrogation of human hematopoiesis at single-cell and single-variant resolution

Author: Leif S. Ludwig, Rany M. Salem, Jacob C. Ulirsch, Joel N. Hirschhorn, Ansuman T. Satpathy, Caleb A. Lareau, Erik L. Bao, Michael H. Guo, Christian Benner, Jason D. Buenrostro, Vijay G. Sankaran, Hilary K. Finucane, Martin J. Aryee, and Vinay K. Kartha
Subjects: 0303 health sciences, Linkage disequilibrium, Computational biology, Biology, Phenotype, Chromatin, 03 medical and health sciences, 0302 clinical medicine, Regulatory sequence, Genetic variation, Genetics, Enhancer, Gene, 030217 neurology & neurosurgery, 030304 developmental biology, Epigenomics
Abstract: Widespread linkage disequilibrium and incomplete annotation of cell-to-cell state variation represent substantial challenges to elucidating mechanisms of trait-associated genetic variation. Here we perform genetic fine-mapping for blood cell traits in the UK Biobank to identify putative causal variants. These variants are enriched in genes encoding proteins in trait-relevant biological pathways and in accessible chromatin of hematopoietic progenitors. For regulatory variants, we explore patterns of developmental enhancer activity, predict molecular mechanisms, and identify likely target genes. In several instances, we localize multiple independent variants to the same regulatory element or gene. We further observe that variants with pleiotropic effects preferentially act in common progenitor populations to direct the production of distinct lineages. Finally, we leverage fine-mapped variants in conjunction with continuous epigenomic annotations to identify trait-cell type enrichments within closely related populations and in single cells. Our study provides a comprehensive framework for single-variant and single-cell analyses of genetic associations.
Published: 2019

29. Genomics of body fat percentage may contribute to sex bias in anorexia nervosa

Author: Mariaelisa Graff, Julius S. Ngwa, Paul F. O'Reilly, Christopher Hübel, Tsegaselassie Workalemahu, Jonathan R. I. Coleman, Kirstin L. Purves, Cynthia M. Bulik, Gerome Breen, Hilary K. Finucane, Inga Prokopenko, Helena Gaspar, Ken B. Hanscombe, and Magic Investigators
Subjects: 0301 basic medicine, Male, Anorexia Nervosa, LOCI, Physiology, Genome-wide association study, Body fat percentage, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Body Mass Index, shared genetics, 0302 clinical medicine, Databases, Genetic, Eating Disorders Working Group of the Psychiatric Genomics Consortium, WIDE ASSOCIATION, GWAS, Genetics (clinical), Research Articles, Genetics & Heredity, Psychiatry, Schizophrenia Working Group of the Psychiatric Genomics Consortium, HERITABILITY, Genomics, Middle Aged, genetic correlation, MAGIC investigators, 3. Good health, fat-free mass, Psychiatry and Mental health, female, Phenotype, Adipose Tissue, Anorexia nervosa (differential diagnoses), eating disorder, Body Composition, Life Sciences & Biomedicine, Sex ratio, Research Article, Adult, fat‐free mass, GENETIC-BASIS, Biology, Genetic correlation, POOLED ANALYSIS, 03 medical and health sciences, Cellular and Molecular Neuroscience, MASS INDEX, Sex Factors, RISK-FACTOR, GLYCEMIC TRAITS, Humans, Genetic Predisposition to Disease, METAANALYSIS, 0604 Genetics, Science & Technology, 1103 Clinical Sciences, Anthropometry, Heritability, 030104 developmental biology, BIOLOGICAL INSIGHTS, Case-Control Studies, Tourette Syndrome/Obsessive-Compulsive Disorder Working Group of the Psychiatric Genomics Consortium, 1109 Neurosciences, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Anorexia nervosa (AN) occurs nine times more often in females than in males. Although environmental factors likely play a role, the reasons for this imbalanced sex ratio remain unresolved. AN displays high genetic correlations with anthropometric and metabolic traits. Given sex differences in body composition, we investigated the possible metabolic underpinnings of female propensity for AN. We conducted sex-specific GWAS in a healthy and medication-free subsample of the UK Biobank (n = 155,961), identifying 77 genome-wide significant loci associated with body fat percentage (BF%) and 174 with fat-free mass (FFM). Partitioned heritability analysis showed an enrichment for central nervous tissue-associated genes for BF%, which was more prominent in females than males. Genetic correlations of BF% and FFM with the largest GWAS of AN by the Psychiatric Genomics Consortium were estimated to explore shared genomics. The genetic correlations of BF%male and BF%female with AN differed significantly from each other (p
Published: 2018

30. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants

Author: Krishna G, Aragam, Tao, Jiang, Anuj, Goel, Stavroula, Kanoni, Brooke N, Wolford, Deepak S, Atri, Elle M, Weeks, Minxian, Wang, George, Hindy, Wei, Zhou, Christopher, Grace, Carolina, Roselli, Nicholas A, Marston, Frederick K, Kamanu, Ida, Surakka, Loreto Muñoz, Venegas, Paul, Sherliker, Satoshi, Koyama, Kazuyoshi, Ishigaki, Bjørn O, Åsvold, Michael R, Brown, Ben, Brumpton, Paul S, de Vries, Olga, Giannakopoulou, Panagiota, Giardoglou, Daniel F, Gudbjartsson, Ulrich, Güldener, Syed M Ijlal, Haider, Anna, Helgadottir, Maysson, Ibrahim, Adnan, Kastrati, Thorsten, Kessler, Theodosios, Kyriakou, Tomasz, Konopka, Ling, Li, Lijiang, Ma, Thomas, Meitinger, Sören, Mucha, Matthias, Munz, Federico, Murgia, Jonas B, Nielsen, Markus M, Nöthen, Shichao, Pang, Tobias, Reinberger, Gavin, Schnitzler, Damian, Smedley, Gudmar, Thorleifsson, Moritz, von Scheidt, Jacob C, Ulirsch, David O, Arnar, Noël P, Burtt, Maria C, Costanzo, Jason, Flannick, Kaoru, Ito, Dong-Keun, Jang, Yoichiro, Kamatani, Amit V, Khera, Issei, Komuro, Iftikhar J, Kullo, Luca A, Lotta, Christopher P, Nelson, Robert, Roberts, Gudmundur, Thorgeirsson, Unnur, Thorsteinsdottir, Thomas R, Webb, Aris, Baras, Johan L M, Björkegren, Eric, Boerwinkle, George, Dedoussis, Hilma, Holm, Kristian, Hveem, Olle, Melander, Alanna C, Morrison, Marju, Orho-Melander, Loukianos S, Rallidis, Arno, Ruusalepp, Marc S, Sabatine, Kari, Stefansson, Pierre, Zalloua, Patrick T, Ellinor, Martin, Farrall, John, Danesh, Christian T, Ruff, Hilary K, Finucane, Jemma C, Hopewell, Robert, Clarke, Rajat M, Gupta, Jeanette, Erdmann, Nilesh J, Samani, Heribert, Schunkert, Hugh, Watkins, Cristen J, Willer, Panos, Deloukas, Sekar, Kathiresan, Adam S, Butterworth, and Consortium, The CARDIoGRAMplusC4D
Subjects: Genetics
Abstract: The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR–Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.
Published: 2021

31. Genome-wide enhancer maps link risk variants to disease genes

Author: Tejal A. Patwardhan, Fritz Lekschas, Jesse M. Engreitz, Alkes L. Price, Hanspeter Pfister, Mark J. Daly, Glen Munson, Michael Kane, Jacob C. Ulirsch, Helen Y. Kang, Nir Hacohen, Ramnik J. Xavier, Anshul Kundaje, Heini M. Natri, Elle M. Weeks, Tung T. Nguyen, Drew T. Bergman, Benjamin R. Doughty, Thouis R. Jones, Eric S. Lander, Joseph Nasser, Kristy Mualim, Thomas Eisenhaure, Ryan L. Collins, Philine Guckelberger, Kushal K. Dey, John P. Ray, Ang Cui, Hilary K. Finucane, Charles P. Fulco, Hailiang Huang, Charles B. Epstein, and Institute for Molecular Medicine Finland
Subjects: Male, Genomics, Genome-wide association study, Computational biology, Biology, Genome, Article, Cell Line, 03 medical and health sciences, Cyclophilins, 0302 clinical medicine, CRISPR, Humans, Genetic Predisposition to Disease, Enhancer, Gene, 030304 developmental biology, 0303 health sciences, Multidisciplinary, Translational bioinformatics, Chromosomes, Human, Pair 10, Genome, Human, Macrophages, 1184 Genetics, developmental biology, physiology, Genetic Variation, Dendritic Cells, Inflammatory Bowel Diseases, Human genetics, Mitochondria, Enhancer Elements, Genetic, Phenotype, Organ Specificity, Female, 3111 Biomedicine, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Genome-wide association studies (GWAS) have identified thousands of noncoding loci that are associated with human diseases and complex traits, each of which could reveal insights into the mechanisms of disease1. Many of the underlying causal variants may affect enhancers2,3, but we lack accurate maps of enhancers and their target genes to interpret such variants. We recently developed the activity-by-contact (ABC) model to predict which enhancers regulate which genes and validated the model using CRISPR perturbations in several cell types4. Here we apply this ABC model to create enhancer–gene maps in 131 human cell types and tissues, and use these maps to interpret the functions of GWAS variants. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577 genes that appear to influence multiple phenotypes through variants in enhancers that act in different cell types. In inflammatory bowel disease (IBD), causal variants are enriched in predicted enhancers by more than 20-fold in particular cell types such as dendritic cells, and ABC achieves higher precision than other regulatory methods at connecting noncoding variants to target genes. These variant-to-function maps reveal an enhancer that contains an IBD risk variant and that regulates the expression of PPIF to alter the membrane potential of mitochondria in macrophages. Our study reveals principles of genome regulation, identifies genes that affect IBD and provides a resource and generalizable strategy to connect risk variants of common diseases to their molecular and cellular functions. Mapping enhancer regulation across human cell types and tissues illuminates genome function and provides a resource to connect risk variants for common diseases to their molecular and cellular functions.
Published: 2021

32. Significance testing for small annotations in stratified LD-Score regression

Author: Luke J. O’Connor, Neale Bm, Katherine Tashman, Hilary K. Finucane, and Ran Cui
Subjects: Computer science, business.industry, Heritability, Machine learning, computer.software_genre, Regression, Small set, Set (abstract data type), Annotation, Standard error, Artificial intelligence, business, computer, Jackknife resampling, Type I and type II errors
Abstract: S-LDSC is a widely used heritability enrichment method that has helped gain biological insights into numerous complex traits. It has primarily been used to analyze large annotations that contain approximately 0.5% of SNPs or more. Here, we show in simulation that, when applied to small annotations, the block jackknife-based significance testing used in S-LDSC does not always control type 1 error. We show that the inflation of type 1 error for small annotations is due both to the noisiness of the jackknife estimate of the standard error and to the non-normality of the regression coefficient estimates. We use the percent of 0.01 centimorgan blocks in the genome overlapped by the annotation to quantify the size of an annotation and the extent to which the SNPs in the annotation cluster together, and we find thresholds on this value above which type 1 error is controlled. We have implemented a test in the LDSC software that informs users when they compute LD scores for an annotation if the annotation does not pass the threshold for producing controlled type 1 error.Author SummaryGenetics is a rapidly evolving field that allows us to link our genetic code to the physiological manifestations of disease. A key part of this work is finding regions of the genome that contribute disproportionately to the genetic underpinnings of a disease. A commonly used tool to provide such insight is stratified LD score regression (S-LDSC). S-LDSC allows us to estimate how much a set of genomic regions contributes to the overall heritability of a phenotype, and to test whether this is more than we would expect by chance. Here we show that when we apply S-LDSC to a small set of genomic regions, it does not give an accurate test of whether this set of genomic regions contributes more than we would expect by chance to the phenotype. We characterize what it means to be a “small” set of genomic regions, and we set thresholds to restrict which annotations we test to prevent false positive results.This helps to ensure that as we continue to pursue genetic analyses at scale, we report only truly significant results that will help us further understand the etiology of many of the traits we study.
Published: 2021

33. Estimating heritability and its enrichment in tissue-specific gene sets in admixed populations

Author: Yang, Luo, Xinyi, Li, Xin, Wang, Steven, Gazal, Josep Maria, Mercader, Benjamin M, Neale, Jose C, Florez, Adam, Auton, Alkes L, Price, Hilary K, Finucane, and Soumya, Raychaudhuri
Subjects: AcademicSubjects/SCI01140, Multifactorial Inheritance, Genetics, Population, Phenotype, Quantitative Trait, Heritable, Genotyping Techniques, Humans, General Article, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Genome-Wide Association Study
Abstract: It is important to study the genetics of complex traits in diverse populations. Here, we introduce covariate-adjusted linkage disequilibrium (LD) score regression (cov-LDSC), a method to estimate SNP-heritability (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}})$\end{document} and its enrichment in homogenous and admixed populations with summary statistics and in-sample LD estimates. In-sample LD can be estimated from a subset of the genome-wide association studies samples, allowing our method to be applied efficiently to very large cohorts. In simulations, we show that unadjusted LDSC underestimates \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$\end{document} by 10–60% in admixed populations; in contrast, cov-LDSC is robustly accurate. We apply cov-LDSC to genotyping data from 8124 individuals, mostly of admixed ancestry, from the Slim Initiative in Genomic Medicine for the Americas study, and to approximately 161 000 Latino-ancestry individuals, 47 000 African American-ancestry individuals and 135 000 European-ancestry individuals, as classified by 23andMe. We estimate \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$\end{document} and detect heritability enrichment in three quantitative and five dichotomous phenotypes, making this, to our knowledge, the most comprehensive heritability-based analysis of admixed individuals to date. Most traits have high concordance of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$\end{document} and consistent tissue-specific heritability enrichment among different populations. However, for age at menarche, we observe population-specific heritability estimates of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$\end{document}. We observe consistent patterns of tissue-specific heritability enrichment across populations; for example, in the limbic system for BMI, the per-standardized-annotation effect size \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$ \tau $\end{document}* is 0.16 ± 0.04, 0.28 ± 0.11 and 0.18 ± 0.03 in the Latino-, African American- and European-ancestry populations, respectively. Our approach is a powerful way to analyze genetic data for complex traits from admixed populations.
Published: 2021

34. Misuse of the term ‘trans-ethnic’ in genomics research

Author: Mireille Kamariza, David S. Jones, Lorin Crawford, and Hilary K. Finucane
Subjects: Genetics, MEDLINE, Ethnic group, Genomics, Biology, Data science, Term (time)
Abstract: A concerning trend in genetics is the common use of the term ‘trans-ethnic’ to describe analyses that combine or compare several ancestrally diverse populations. In this commentary, we discuss how this term is inaccurate and alienating. We propose that geneticists avoid using the term trans-ethnic entirely and that researchers across disciplines reach a new consensus about the best terms to use to describe the populations we study.
Published: 2021

35. A cross-disorder dosage sensitivity map of the human genome

Author: Swaroop Aradhya, Konrad J. Karczewski, Farid Ullah, Georgios Kellaris, Diane Lucente, Benjamin M. Neale, Selin Everett, Xander Nuttle, Daniel P. Howrigan, Ryan L. Collins, Michael E. Talkowski, Hilary K. Finucane, Alexandre Reymond, Eleonora Porcu, Jack Fu, Zoltán Kutalik, Nicholas Katsanis, Ludmilla Matyakhina, Kiana Mohajeri, Chelsea Lowther, Kaitlin E. Samocha, Hakon Hakonarson, Jennelle C. Hodge, Lisa-Marie Niestroj, Erica E. Davis, James F. Gusella, Shamil R. Sunyaev, Jacob C. Ulirsch, Harrison Brand, Jeanne Meck, Joseph T. Glessner, Philip M. Boone, and Dennis Lal
Subjects: Genetics, Gene duplication, medicine, Autism, Human genome, Disease, Copy-number variation, Biology, medicine.disease, Haploinsufficiency, Gene, Exome sequencing
Abstract: SUMMARYRare deletions and duplications of genomic segments, collectively known as rare copy number variants (rCNVs), contribute to a broad spectrum of human diseases. To date, most disease-association studies of rCNVs have focused on recognized genomic disorders or on the impact of haploinsufficiency caused by deletions. By comparison, our understanding of duplications in disease remains rudimentary as very few individual genes are known to be triplosensitive (i.e., duplication intolerant). In this study, we meta-analyzed rCNVs from 753,994 individuals across 30 primarily neurological disease phenotypes to create a genome-wide catalog of rCNV association statistics across disorders. We discovered 114 rCNV-disease associations at 52 distinct loci surpassing genome-wide significance (P=3.72×10−6), 42% of which involve duplications. Using Bayesian fine-mapping methods, we further prioritized 38 novel triplosensitive disease genes (e.g., GMEB2 in brain abnormalities), including three known haploinsufficient genes that we now reveal as bidirectionally dosage sensitive (e.g., ANKRD11 in growth abnormalities). By integrating our results with prior literature, we found that disease-associated rCNV segments were enriched for genes constrained against damaging coding variation and identified likely dominant driver genes for about one-third (32%) of rCNV segments based on de novo mutations from exome sequencing studies of developmental disorders. However, while the presence of constrained driver genes was a common feature of many pathogenic large rCNVs across disorders, most of the rCNVs showing genome-wide significant association were incompletely penetrant (mean odds ratio=11.6) and we also identified two examples of noncoding disease-associated rCNVs (e.g., intronic CADM2 deletions in behavioral disorders). Finally, we developed a statistical model to predict dosage sensitivity for all genes, which defined 3,006 haploinsufficient and 295 triplosensitive genes where the effect sizes of rCNVs were comparable to deletions of genes constrained against truncating mutations. These dosage sensitivity scores classified disease genes across molecular mechanisms, prioritized pathogenic de novo rCNVs in children with autism, and revealed features that distinguished haploinsufficient and triplosensitive genes, such as insulation from other genes and local cis-regulatory complexity. Collectively, the cross-disorder rCNV maps and metrics derived in this study provide the most comprehensive assessment of dosage sensitive genomic segments and genes in disease to date and set the foundation for future studies of dosage sensitivity throughout the human genome.
Published: 2021

36. Leveraging fine-mapping and non-European training data to improve cross-population polygenic risk scores

Author: Wouter J. Peyrot, Hilary K. Finucane, Amit Khera, Masahiro Kanai, Huwenbo Shi, Alicia R. Martin, Steven Gazal, Alkes L. Price, Yukinori Okada, and Omer Weissbrod
Subjects: education.field_of_study, Training set, Population, Causal effect, Ethnic group, Single-nucleotide polymorphism, Polygenic risk score, Biology, education, Biobank, Health equity, Demography
Abstract: Polygenic risk scores (PRS) based on European training data suffer reduced accuracy in non-European target populations, exacerbating health disparities. This loss of accuracy predominantly stems from LD differences, MAF differences (including population-specific SNPs), and/or causal effect size differences. PRS based on training data from the non-European target population do not suffer from these limitations, but are currently limited by much smaller training sample sizes. Here, we propose PolyPred, a method that improves cross-population polygenic prediction by combining two complementary predictors: a new predictor that leverages functionally informed fine-mapping to estimate causal effects (instead of tagging effects), addressing LD differences; and BOLT-LMM, a published predictor. In the special case where a large training sample is available in the non-European target population (or a closely related population), we propose PolyPred+, which further incorporates the non-European training data, addressing MAF differences and causal effect size differences. PolyPred and PolyPred+ require individual-level training data (for their BOLT-LMM component), but we also propose analogous methods that replace the BOLT-LMM component with summary statistic-based components if only summary statistics are available. We applied PolyPred to 49 diseases and complex traits in 4 UK Biobank populations using UK Biobank British training data (averageN=325K), and observed statistically significant average relative improvements in prediction accuracy vs. BOLT-LMM ranging from +7% in South Asians to +32% in Africans (and vs. LD-pruning + P-value thresholding (P+T) ranging from +77% to +164%), consistent with simulations. We applied PolyPred+ to 23 diseases and complex traits in UK Biobank East Asians using both UK Biobank British (averageN=325K) and Biobank Japan (averageN=124K) training data, and observed statistically significant average relative improvements in prediction accuracy of +24% vs. BOLT-LMM and +12% vs. PolyPred. The summary statistic-based analogues of PolyPred and PolyPred+ attained similar improvements. In conclusion, PolyPred and PolyPred+ improve cross-population polygenic prediction accuracy, ameliorating health disparities.
Published: 2021

37. A Comparison of Ten Polygenic Score Methods for Psychiatric Disorders Applied Across Multiple Cohorts

Author: Guiyan Ni, Jian Zeng, Joana A. Revez, Ying Wang, Zhili Zheng, Tian Ge, Restuadi Restuadi, Jacqueline Kiewa, Dale R. Nyholt, Jonathan R.I. Coleman, Jordan W. Smoller, Jian Yang, Peter M. Visscher, Naomi R. Wray, Stephan Ripke, Benjamin M. Neale, Aiden Corvin, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau, 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. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, 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, Psychosis Endophenotypes International Consortium, 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, 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, Kari Stefansson, Wellcome Trust Case-Control Consortium, 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, Maciej Trzaskowski, Enda M. Byrne, Abdel Abdellaoui, Mark J. Adams, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Elisabeth B. Binder, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, Toni-Kim Clarke, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Gregory E. Crawford, Gail Davies, Ian J. Deary, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Jerome C. Foo, Andreas J. Forstner, Héléna A. Gaspar, Fernando S. Goes, Scott D. Gordon, Jakob Grove, Lynsey S. Hall, Christine Søholm Hansen, Thomas F. Hansen, Ian B. Hickie, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, David M. Howard, Marcus Ising, Rick Jansen, Ian Jones, Lisa A. Jones, Eric Jorgenson, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Donald J. MacIntyre, Dean F. MacKinnon, Robert M. Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Peter McGuffin, Sarah E. Medland, Divya Mehta, Christel M. Middeldorp, Evelin Mihailov, Yuri Milaneschi, Francis M. Mondimore, Grant W. Montgomery, Sara Mostafavi, Niamh Mullins, Matthias Nauck, Bernard Ng, Michel G. Nivard, Paul F. O’Reilly, Hogni Oskarsson, Jodie N. Painter, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Roseann E. Peterson, Wouter J. Peyrot, Giorgio Pistis, Jorge A. Quiroz, Per Qvist, John P. Rice, Margarita Rivera, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Stanley I. Shyn, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Fabian Streit, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, Vassily Trubetskoy, André G. Uitterlinden, Daniel Umbricht, Sandra Van der Auwera, Albert M. van Hemert, Alexander Viktorin, Yunpeng Wang, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Yang Wu, Hualin S. Xi, Futao Zhang, Volker Arolt, Bernhard T. Baune, Klaus Berger, Dorret I. Boomsma, Udo Dannlowski, E.J.C. de Geus, J. Raymond DePaulo, Katharina Domschke, Hans J. Grabe, Steven P. Hamilton, Caroline Hayward, Andrew C. Heath, Stefan Kloiber, Glyn Lewis, Susanne Lucae, Pamela A.F. Madden, Patrik K. Magnusson, Nicholas G. Martin, Preben Bo Mortensen, Merete Nordentoft, Sara A. Paciga, Nancy L. Pedersen, Adult Psychiatry, APH - Mental Health, ANS - Complex Trait Genetics, ANS - Mood, Anxiety, Psychosis, Stress & Sleep, Ni, Guiyan, Zeng, Jian, Revez, Joana A., Wang, Ying, Zhili, Zheng, Ge, Tian, Restuadi, Restuadi, Kiewa, Jacqueline, Nyholt, Dale R, Coleman, Jonathan RI, Smoller, Jordan W, Lee, S Hong, APH - Methodology, Biological Psychology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Econometrics, Psychiatry, Department of Technology and Operations Management, Child and Adolescent Psychiatry / Psychology, Epidemiology, Erasmus MC other, Urology, Internal Medicine, Medical Informatics, Immunology, Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Reproduction & Development (AR&D), and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep
Subjects: 0301 basic medicine, Multifactorial Inheritance, medicine.medical_specialty, LDpred2, BF, Genomics, Disease, Major depressive disorder, risk prediction, 03 medical and health sciences, 0302 clinical medicine, MegaPRS, SDG 3 - Good Health and Well-being, medicine, Humans, Genetic Predisposition to Disease, ddc:610, Genetic risk, Psychiatry, Biological Psychiatry, Genetic association, Depressive Disorder, Major, business.industry, Mental Disorders, medicine.disease, Genetic architecture, Polygenic scores, Risk prediction, polygenic scores, PRS-CS, psychiatric disorders, 030104 developmental biology, SBayesR, Schizophrenia, Cohort, Lassosum, RC0321, business, Psychiatric disorders, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: BACKGROUND: Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies. PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors.METHODS: The Psychiatric Genomics Consortium Working Groups for schizophrenia and major depressive disorder bring together many independently collected case-control cohorts. We used these resources (31,328 schizophrenia cases, 41,191 controls; 248,750 major depressive disorder cases, 563,184 controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and 9 methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) were compared.RESULTS: Compared with PC+T, the other 9 methods gave higher prediction statistics, MegaPRS, LDPred2, and SBayesR significantly so, explaining up to 9.2% variance in liability for schizophrenia across 30 target cohorts, an increase of 44%. For major depressive disorder across 26 target cohorts, these statistics were 3.5% and 59%, respectively.CONCLUSIONS: Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparisons and are recommended in applications to psychiatric disorders.
Published: 2021

38. OUP accepted manuscript

Author: Benjamin M. Neale, Adam Auton, Xin Wang, Alkes L. Price, Soumya Raychaudhuri, Yang Luo, Jose C. Florez, Steven Gazal, Josep M. Mercader, Xinyi Li, and Hilary K. Finucane
Subjects: African american, education.field_of_study, Extramural, Population, Genetic data, General Medicine, Heritability, Biology, Combinatorics, Genetics, Genomic medicine, education, Molecular Biology, Genetics (clinical), Genotype determination, Tissue specific gene
Abstract: It is important to study the genetics of complex traits in diverse populations. Here, we introduce covariate-adjusted linkage disequilibrium (LD) score regression (cov-LDSC), a method to estimate SNP-heritability (${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}})$ and its enrichment in homogenous and admixed populations with summary statistics and in-sample LD estimates. In-sample LD can be estimated from a subset of the genome-wide association studies samples, allowing our method to be applied efficiently to very large cohorts. In simulations, we show that unadjusted LDSC underestimates ${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$ by 10-60% in admixed populations; in contrast, cov-LDSC is robustly accurate. We apply cov-LDSC to genotyping data from 8124 individuals, mostly of admixed ancestry, from the Slim Initiative in Genomic Medicine for the Americas study, and to approximately 161 000 Latino-ancestry individuals, 47 000 African American-ancestry individuals and 135 000 European-ancestry individuals, as classified by 23andMe. We estimate ${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$ and detect heritability enrichment in three quantitative and five dichotomous phenotypes, making this, to our knowledge, the most comprehensive heritability-based analysis of admixed individuals to date. Most traits have high concordance of ${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$ and consistent tissue-specific heritability enrichment among different populations. However, for age at menarche, we observe population-specific heritability estimates of ${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$. We observe consistent patterns of tissue-specific heritability enrichment across populations; for example, in the limbic system for BMI, the per-standardized-annotation effect size $ \tau $* is 0.16 ± 0.04, 0.28 ± 0.11 and 0.18 ± 0.03 in the Latino-, African American- and European-ancestry populations, respectively. Our approach is a powerful way to analyze genetic data for complex traits from admixed populations.
Published: 2021

39. Genome-wide functional screen of 3'UTR variants uncovers causal variants for human disease and evolution

Author: Joe R. Davis, Jacob C. Ulirsch, Pardis C. Sabeti, Mehmet Hakan Guney, Ryan Tewhey, Dustin Griesemer, Carl D. Novina, Masahiro Kanai, David K. Yang, James R. Xue, Steven K. Reilly, Hilary K. Finucane, Kalki Kukreja, Jeremy Luban, Stephen B. Montgomery, and John C. Butts
Subjects: Untranslated region, Quantitative Trait Loci, Genome-wide association study, Biology, Genome, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, Genes, Reporter, Humans, Disease, Allele, Gene, 3' Untranslated Regions, Alleles, Genetics, Three prime untranslated region, Genetic Variation, Phenotype, Biological Evolution, Gene Expression Regulation, Polyribosomes, RNA, Functional genomics, Algorithms, Genome-Wide Association Study
Abstract: 3' untranslated region (3'UTR) variants are strongly associated with human traits and diseases, yet few have been causally identified. We developed the massively parallel reporter assay for 3'UTRs (MPRAu) to sensitively assay 12,173 3'UTR variants. We applied MPRAu to six human cell lines, focusing on genetic variants associated with genome-wide association studies (GWAS) and human evolutionary adaptation. MPRAu expands our understanding of 3'UTR function, suggesting that simple sequences predominately explain 3'UTR regulatory activity. We adapt MPRAu to uncover diverse molecular mechanisms at base pair resolution, including an adenylate-uridylate (AU)-rich element of LEPR linked to potential metabolic evolutionary adaptations in East Asians. We nominate hundreds of 3'UTR causal variants with genetically fine-mapped phenotype associations. Using endogenous allelic replacements, we characterize one variant that disrupts a miRNA site regulating the viral defense gene TRIM14 and one that alters PILRB abundance, nominating a causal variant underlying transcriptional changes in age-related macular degeneration.
Published: 2020

40. Leveraging supervised learning for functionally-informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs

Author: Nathan Cheng, Shuvom Sadhuka, Qingbo Wang, Hilary K. Finucane, Yukinori Okada, Daniel G. MacArthur, David R. Kelley, Carlos Albors, Kristin G. Ardlie, Ran Cui, François Aguet, Masahiro Kanai, and Jacob C. Ulirsch
Subjects: Candidate gene, Computer science, Supervised learning, Leverage (statistics), Genome-wide association study, Computational biology, Experimental methods, Biobank
Abstract: The large majority of variants identified by GWAS are non-coding, motivating detailed characterization of the function of non-coding variants. Experimental methods to assess variants’ effect on gene expressions in native chromatin context via direct perturbation are low-throughput. Existing high-throughput computational predictors thus have lacked large gold standard sets of regulatory variants for training and validation. Here, we leverage a set of 14,807 putative causal eQTLs in humans obtained through statistical fine-mapping, and we use 6,121 features to directly train a predictor of whether a variant modifies nearby gene expression. We call the resulting prediction the expression modifier score (EMS). We validate EMS by comparing its ability to prioritize functional variants with other major scores. We then use EMS as a prior for statistical fine-mapping of eQTLs to identify an additional 20,913 putatively causal eQTLs, and we incorporate EMS into co-localization analysis to identify 310 additional candidate genes across UK Biobank phenotypes.
Published: 2020

41. Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases

Author: Alex K. Shalek, Elle M. Weeks, Ashwin N. Ananthakrishnan, Eric S. Lander, Tejal A. Patwardhan, Ramnik J. Xavier, Aviv Regev, Joel N. Hirschhorn, Katherine Tashman, Jenkai Miao, Moshe Biton, Jose Ordovas-Montanes, Rebecca S. Fine, Kasper Lage, Masahiro Kanai, Charles P. Fulco, Taibo Li, Hilary K. Finucane, François Aguet, Joseph Nasser, Rajat M. Gupta, Kristin G. Ardlie, Christopher Smillie, Nathan Cheng, Jesse M. Engreitz, Jacob C. Ulirsch, and Brian L. Trippe
Subjects: Novel gene, Biological pathway, Red Blood Cell Count, Gene expression, Genome-wide association study, Computational biology, Biology, Gene, Gene prioritization, Genetic association
Abstract: Genome-wide association studies (GWAS) are a valuable tool for understanding the biology of complex traits, but the associations found rarely point directly to causal genes. Here, we introduce a new method to identify the causal genes by integrating GWAS summary statistics with gene expression, biological pathway, and predicted protein-protein interaction data. We further propose an approach that effectively leverages both polygenic and locus-specific genetic signals by combining results across multiple gene prioritization methods, increasing confidence in prioritized genes. Using a large set of gold standard genes to evaluate our approach, we prioritize 8,402 unique gene-trait pairs with greater than 75% estimated precision across 113 complex traits and diseases, including known genes such as SORT1 for LDL cholesterol, SMIM1 for red blood cell count, and DRD2 for schizophrenia, as well as novel genes such as TTC39B for cholelithiasis. Our results demonstrate that a polygenic approach is a powerful tool for gene prioritization and, in combination with locus-specific signal, improves upon existing methods.
Published: 2020

42. Genome-wide maps of enhancer regulation connect risk variants to disease genes

Author: Tejal A. Patwardhan, Tom M. Eisenhaure, Benjamin R. Doughty, Jacob C. Ulirsch, Thouis R. Jones, Tung T. Nguyen, Michael Kane, Kushal K. Dey, Helen Y. Kang, Philine Guckelberger, Mark J. Daly, Elle M. Weeks, Joseph Nasser, Drew T. Bergman, Anshul Kundaje, Jesse M. Engreitz, Ang Cui, Hilary K. Finucane, Alkes L. Price, Glen Munson, John P. Ray, Nir Hacohen, Kristy Mualim, Eric S. Lander, Heini M. Natri, Charles B. Epstein, Ramnik J. Xavier, Charles P. Fulco, Hailiang Huang, and Ryan L. Collins
Subjects: PPIF, CRISPR, Genome-wide association study, Computational biology, Biology, Enhancer, Genome, Gene, Phenotype, Genetic association
Abstract: Genome-wide association studies have now identified tens of thousands of noncoding loci associated with human diseases and complex traits, each of which could reveal insights into biological mechanisms of disease. Many of the underlying causal variants are thought to affect enhancers, but we have lacked genome-wide maps of enhancer-gene regulation to interpret such variants. We previously developed the Activity-by-Contact (ABC) Model to predict enhancer-gene connections and demonstrated that it can accurately predict the results of CRISPR perturbations across several cell types. Here, we apply this ABC Model to create enhancer-gene maps in 131 cell types and tissues, and use these maps to interpret the functions of fine-mapped GWAS variants. For inflammatory bowel disease (IBD), causal variants are >20-fold enriched in enhancers in particular cell types, and ABC outperforms other regulatory methods at connecting noncoding variants to target genes. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577 genes that appear to influence multiple phenotypes via variants in enhancers that act in different cell types. Guided by these variant-to-function maps, we show that an enhancer containing an IBD risk variant regulates the expression ofPPIFto tune mitochondrial membrane potential. Together, our study reveals insights into principles of genome regulation, illuminates mechanisms that influence IBD, and demonstrates a generalizable strategy to connect common disease risk variants to their molecular and cellular functions.
Published: 2020

43. The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls

Author: Jonathan R.I. Coleman, Héléna A. Gaspar, Julien Bryois, Gerome Breen, Enda M. Byrne, Andreas J. Forstner, Peter A. Holmans, Christiaan A. de Leeuw, Manuel Mattheisen, Andrew McQuillin, Jennifer M. Whitehead Pavlides, Tune H. Pers, Stephan Ripke, Eli A. Stahl, Stacy Steinberg, Vassily Trubetskoy, Maciej Trzaskowski, Yunpeng Wang, Liam Abbott, Abdel Abdellaoui, Mark J. Adams, Annelie Nordin Adolfsson, Esben Agerbo, Huda Akil, Diego Albani, Ney Alliey-Rodriguez, Thomas D. Als, Till F.M. Andlauer, Adebayo Anjorin, Verneri Antilla, Sandra Van der Auwera, Swapnil Awasthi, Silviu-Alin Bacanu, Judith A. Badner, Marie Bækvad-Hansen, Jack D. Barchas, Nicholas Bass, Michael Bauer, Aartjan T.F. Beekman, Richard Belliveau, Sarah E. Bergen, Tim B. Bigdeli, Elisabeth B. Binder, Erlend Bøen, Marco Boks, James Boocock, Monika Budde, William Bunney, Margit Burmeister, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, William Byerley, Na Cai, Miquel Casas, Enrique Castelao, Felecia Cerrato, Pablo Cervantes, Kimberly Chambert, Alexander W. Charney, Danfeng Chen, Jane Hvarregaard Christensen, Claire Churchhouse, David St Clair, Toni-Kim Clarke, Lucía Colodro-Conde, William Coryell, Baptiste Couvy-Duchesne, David W. Craig, Gregory E. Crawford, Cristiana Cruceanu, Piotr M. Czerski, Anders M. Dale, Gail Davies, Ian J. Deary, Franziska Degenhardt, Jurgen Del-Favero, J Raymond DePaulo, Eske M. Derks, Nese Direk, Srdjan Djurovic, Amanda L. Dobbyn, Conor V. Dolan, Ashley Dumont, Erin C. Dunn, Thalia C. Eley, Torbjørn Elvsåshagen, Valentina Escott-Price, Chun Chieh Fan, Hilary K. Finucane, Sascha B. Fischer, Matthew Flickinger, Jerome C. Foo, Tatiana M. Foroud, Liz Forty, Josef Frank, Christine Fraser, Nelson B. Freimer, Louise Frisén, Katrin Gade, Diane Gage, Julie Garnham, Claudia Giambartolomei, Fernando S. Goes, Jaqueline Goldstein, Scott D. Gordon, Katherine Gordon-Smith, Elaine K. Green, Melissa J. Green, Tiffany A. Greenwood, Jakob Grove, Weihua Guan, Lynsey S. Hall, Marian L. Hamshere, Christine Søholm Hansen, Thomas F. Hansen, Martin Hautzinger, Urs Heilbronner, Albert M. van Hemert, Stefan Herms, Ian B. Hickie, Maria Hipolito, Per Hoffmann, Dominic Holland, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, Laura Huckins, Marcus Ising, Stéphane Jamain, Rick Jansen, Jessica S. Johnson, Simone de Jong, Eric Jorgenson, Anders Juréus, Radhika Kandaswamy, Robert Karlsson, James L. Kennedy, Farnush Farhadi Hassan Kiadeh, Sarah Kittel-Schneider, James A. Knowles, Manolis Kogevinas, Isaac S. Kohane, Anna C. Koller, Julia Kraft, Warren W. Kretzschmar, Jesper Krogh, Ralph Kupka, Zoltán Kutalik, Catharina Lavebratt, Jacob Lawrence, William B. Lawson, Markus Leber, Phil H. Lee, Shawn E. Levy, Jun Z. Li, Yihan Li, Penelope A. Lind, Chunyu Liu, Loes M. Olde Loohuis, Anna Maaser, Donald J. MacIntyre, Dean F. MacKinnon, Pamela B. Mahon, Wolfgang Maier, Robert M. Maier, Jonathan Marchini, Lina Martinsson, Hamdi Mbarek, Steve McCarroll, Patrick McGrath, Peter McGuffin, Melvin G. McInnis, James D. McKay, Helena Medeiros, Sarah E. Medland, Divya Mehta, Fan Meng, Christel M. Middeldorp, Evelin Mihailov, Yuri Milaneschi, Lili Milani, Saira Saeed Mirza, Francis M. Mondimore, Grant W. Montgomery, Derek W. Morris, Sara Mostafavi, Thomas W. Mühleisen, Niamh Mullins, Matthias Nauck, Bernard Ng, Hoang Nguyen, Caroline M. Nievergelt, Michel G. Nivard, Evaristus A. Nwulia, Dale R. Nyholt, Claire O'Donovan, Paul F. O'Reilly, Anil P.S. Ori, Lilijana Oruc, Urban Ösby, Hogni Oskarsson, Jodie N. Painter, José Guzman Parra, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Amy Perry, Roseann E. Peterson, Erik Pettersson, Wouter J. Peyrot, Andrea Pfennig, Giorgio Pistis, Shaun M. Purcell, Jorge A. Quiroz, Per Qvist, Eline J. Regeer, Andreas Reif, Céline S. Reinbold, John P. Rice, Brien P. Riley, Fabio Rivas, Margarita Rivera, Panos Roussos, Douglas M. Ruderfer, Euijung Ryu, Cristina Sánchez-Mora, Alan F. Schatzberg, William A. Scheftner, Robert Schoevers, Nicholas J. Schork, Eva C. Schulte, Tatyana Shehktman, Ling Shen, Jianxin Shi, Paul D. Shilling, Stanley I. Shyn, Engilbert Sigurdsson, Claire Slaney, Olav B. Smeland, Johannes H. Smit, Daniel J. Smith, Janet L. Sobell, Anne T. Spijker, Michael Steffens, John S. Strauss, Fabian Streit, Jana Strohmaier, Szabolcs Szelinger, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Robert C. Thompson, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, André G. Uitterlinden, Daniel Umbricht, Helmut Vedder, Alexander Viktorin, Peter M. Visscher, Weiqing Wang, Stanley J. Watson, Bradley T. Webb, Cynthia Shannon Weickert, Thomas W. Weickert, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Stephanie H. Witt, Yang Wu, Hualin S. Xi, Wei Xu, Jian Yang, Allan H. Young, Peter Zandi, Peng Zhang, Futao Zhang, Sebastian Zollner, Rolf Adolfsson, Ingrid Agartz, Martin Alda, Volker Arolt, Lena Backlund, Bernhard T. Baune, Frank Bellivier, Klaus Berger, Wade H. Berrettini, Joanna M. Biernacka, Douglas H.R. Blackwood, Michael Boehnke, Dorret I. Boomsma, Aiden Corvin, Nicholas Craddock, Mark J. Daly, Udo Dannlowski, Enrico Domenici, Katharina Domschke, Tõnu Esko, Bruno Etain, Mark Frye, Janice M. Fullerton, Elliot S. Gershon, E.J.C. de Geus, Michael Gill, Fernando Goes, Hans J. Grabe, Maria Grigoroiu-Serbanescu, Steven P. Hamilton, Joanna Hauser, Caroline Hayward, Andrew C. Heath, David M. Hougaard, Christina M. Hultman, Ian Jones, Lisa A. Jones, René S. Kahn, Kenneth S. Kendler, George Kirov, Stefan Kloiber, Mikael Landén, Marion Leboyer, Glyn Lewis, Qingqin S. Li, Jolanta Lissowska, Susanne Lucae, Pamela A.F. Madden, Patrik K. Magnusson, 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, Nancy L. Pedersen, Brenda W.J. H. Penninx, Roy H. Perlis, David J. Porteous, Danielle Posthuma, James B. Potash, Martin Preisig, Josep Antoni Ramos-Quiroga, Marta Ribasés, Marcella Rietschel, Guy A. Rouleau, Catherine Schaefer, Martin Schalling, Peter R. Schofield, Thomas G. Schulze, Alessandro Serretti, Jordan W. Smoller, Hreinn Stefansson, Kari Stefansson, Eystein Stordal, Henning Tiemeier, Gustavo Turecki, Rudolf Uher, Arne E. Vaaler, Eduard Vieta, John B. Vincent, Henry Völzke, Myrna M. Weissman, Thomas Werge, Ole A. Andreassen, Anders D. Børglum, Sven Cichon, Howard J. Edenberg, Arianna Di Florio, John Kelsoe, Douglas F. Levinson, Cathryn M. Lewis, John I. Nurnberger, Roel A. Ophoff, Laura J. Scott, Pamela Sklar, Patrick F. Sullivan, Naomi R. Wray, APH - Methodology, Biological Psychology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, APH - Mental Health, Amsterdam Neuroscience - Complex Trait Genetics, Complex Trait Genetics, Epidemiology, Erasmus MC other, Urology, Psychiatry, Internal Medicine, Medical Informatics, Immunology, Child and Adolescent Psychiatry / Psychology, Adult Psychiatry, Coleman J.R.I., Gaspar H.A., Bryois J., Byrne E.M., Forstner A.J., Holmans P.A., de Leeuw C.A., Mattheisen M., McQuillin A., Whitehead Pavlides J.M., Pers T.H., Ripke S., Stahl E.A., Steinberg S., Trubetskoy V., Trzaskowski M., Wang Y., Abbott L., Abdellaoui A., Adams M.J., Adolfsson A.N., Agerbo E., Akil H., Albani D., Alliey-Rodriguez N., Als T.D., Andlauer T.F.M., Anjorin A., Antilla V., Van der Auwera S., Awasthi S., Bacanu S.-A., Badner J.A., Baekvad-Hansen M., Barchas J.D., Bass N., Bauer M., Beekman A.T.F., Belliveau R., Bergen S.E., Bigdeli T.B., Binder E.B., Boen E., Boks M., Boocock J., Budde M., Bunney W., Burmeister M., Buttenschon H.N., Bybjerg-Grauholm J., Byerley W., Cai N., Casas M., Castelao E., Cerrato F., Cervantes P., Chambert K., Charney A.W., Chen D., Christensen J.H., Churchhouse C., St Clair D., Clarke T.-K., Colodro-Conde L., Coryell W., Couvy-Duchesne B., Craig D.W., Crawford G.E., Cruceanu C., Czerski P.M., Dale A.M., Davies G., Deary I.J., Degenhardt F., Del-Favero J., DePaulo J.R., Derks E.M., Direk N., Djurovic S., Dobbyn A.L., Dolan C.V., Dumont A., Dunn E.C., Eley T.C., Elvsashagen T., Escott-Price V., Fan C.C., Finucane H.K., Fischer S.B., Flickinger M., Foo J.C., Foroud T.M., Forty L., Frank J., Fraser C., Freimer N.B., Frisen L., Gade K., Gage D., Garnham J., Giambartolomei C., Goes F.S., Goldstein J., Gordon S.D., Gordon-Smith K., Green E.K., Green M.J., Greenwood T.A., Grove J., Guan W., Hall L.S., Hamshere M.L., Hansen C.S., Hansen T.F., Hautzinger M., Heilbronner U., van Hemert A.M., Herms S., Hickie I.B., Hipolito M., Hoffmann P., Holland D., Homuth G., Horn C., Hottenga J.-J., Huckins L., Ising M., Jamain S., Jansen R., Johnson J.S., de Jong S., Jorgenson E., Jureus A., Kandaswamy R., Karlsson R., Kennedy J.L., Hassan Kiadeh F.F., Kittel-Schneider S., Knowles J.A., Kogevinas M., Kohane I.S., Koller A.C., Kraft J., Kretzschmar W.W., Krogh J., Kupka R., Kutalik Z., Lavebratt C., Lawrence J., Lawson W.B., Leber M., Lee P.H., Levy S.E., Li J.Z., Li Y., Lind P.A., Liu C., Olde Loohuis L.M., Maaser A., MacIntyre D.J., MacKinnon D.F., Mahon P.B., Maier W., Maier R.M., Marchini J., Martinsson L., Mbarek H., McCarroll S., McGrath P., McGuffin P., McInnis M.G., McKay J.D., Medeiros H., Medland S.E., Mehta D., Meng F., Middeldorp C.M., Mihailov E., Milaneschi Y., Milani L., Mirza S.S., Mondimore F.M., Montgomery G.W., Morris D.W., Mostafavi S., Muhleisen T.W., Mullins N., Nauck M., Ng B., Nguyen H., Nievergelt C.M., Nivard M.G., Nwulia E.A., Nyholt D.R., O'Donovan C., O'Reilly P.F., Ori A.P.S., Oruc L., Osby U., Oskarsson H., Painter J.N., Parra J.G., Pedersen C.B., Pedersen M.G., Perry A., Peterson R.E., Pettersson E., Peyrot W.J., Pfennig A., Pistis G., Purcell S.M., Quiroz J.A., Qvist P., Regeer E.J., Reif A., Reinbold C.S., Rice J.P., Riley B.P., Rivas F., Rivera M., Roussos P., Ruderfer D.M., Ryu E., Sanchez-Mora C., Schatzberg A.F., Scheftner W.A., Schoevers R., Schork N.J., Schulte E.C., Shehktman T., Shen L., Shi J., Shilling P.D., Shyn S.I., Sigurdsson E., Slaney C., Smeland O.B., Smit J.H., Smith D.J., Sobell J.L., Spijker A.T., Steffens M., Strauss J.S., Streit F., Strohmaier J., Szelinger S., Tansey K.E., Teismann H., Teumer A., Thompson R.C., Thompson W., Thomson P.A., Thorgeirsson T.E., Traylor M., Treutlein J., Uitterlinden A.G., Umbricht D., Vedder H., Viktorin A., Visscher P.M., Wang W., Watson S.J., Webb B.T., Weickert C.S., Weickert T.W., Weinsheimer S.M., Wellmann J., Willemsen G., Witt S.H., Wu Y., Xi H.S., Xu W., Yang J., Young A.H., Zandi P., Zhang P., Zhang F., Zollner S., Adolfsson R., Agartz I., Alda M., Arolt V., Backlund L., Baune B.T., Bellivier F., Berger K., Berrettini W.H., Biernacka J.M., Blackwood D.H.R., Boehnke M., Boomsma D.I., Corvin A., Craddock N., Daly M.J., Dannlowski U., Domenici E., Domschke K., Esko T., Etain B., Frye M., Fullerton J.M., Gershon E.S., de Geus E.J.C., Gill M., Goes F., Grabe H.J., Grigoroiu-Serbanescu M., Hamilton S.P., Hauser J., Hayward C., Heath A.C., Hougaard D.M., Hultman C.M., Jones I., Jones L.A., Kahn R.S., Kendler K.S., Kirov G., Kloiber S., Landen M., Leboyer M., Lewis G., Li Q.S., Lissowska J., Lucae S., Madden P.A.F., Magnusson P.K., Martin N.G., Mayoral F., McElroy S.L., McIntosh A.M., McMahon F.J., Melle I., Metspalu A., Mitchell P.B., Morken G., Mors O., Mortensen P.B., Muller-Myhsok B., Myers R.M., Neale B.M., Nimgaonkar V., Nordentoft M., Nothen M.M., O'Donovan M.C., Oedegaard K.J., Owen M.J., Paciga S.A., Pato C., Pato M.T., Pedersen N.L., Penninx B.W.J.H., Perlis R.H., Porteous D.J., Posthuma D., Potash J.B., Preisig M., Ramos-Quiroga J.A., Ribases M., Rietschel M., Rouleau G.A., Schaefer C., Schalling M., Schofield P.R., Schulze T.G., Serretti A., Smoller J.W., Stefansson H., Stefansson K., Stordal E., Tiemeier H., Turecki G., Uher R., Vaaler A.E., Vieta E., Vincent J.B., Volzke H., Weissman M.M., Werge T., Andreassen O.A., Borglum A.D., Cichon S., Edenberg H.J., Di Florio A., Kelsoe J., Levinson D.F., Lewis C.M., Nurnberger J.I., Ophoff R.A., Scott L.J., Sklar P., Sullivan P.F., Wray N.R., and Breen G.
Subjects: 0301 basic medicine, Netherlands Twin Register (NTR), Genetic correlation, Genome-wide association study, Mood Disorder, Bipolar disorder, Population, BF, Genomics, Major depressive disorder, Affective disorder, Article, Mice, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, mental disorders, medicine, Animals, ddc:610, education, Depression (differential diagnoses), Biological Psychiatry, 030304 developmental biology, Genetic association, Genetics, Depressive Disorder, Major, 0303 health sciences, education.field_of_study, Animal, business.industry, Risk Factor, medicine.disease, 3. Good health, Affective disorders, 030104 developmental biology, Mood, Mood disorders, RC0321, Biological psychiatry, business, 030217 neurology & neurosurgery, Clinical psychology
Abstract: BackgroundMood disorders (including major depressive disorder and bipolar disorder) affect 10-20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Despite their diagnostic distinction, multiple approaches have shown considerable sharing of risk factors across the mood disorders.MethodsTo clarify their shared molecular genetic basis, and to highlight disorder-specific associations, we meta-analysed data from the latest Psychiatric Genomics Consortium (PGC) genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; non-overlapping N = 609,424).ResultsSeventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More genome-wide significant loci from the PGC analysis of major depression than bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment – positive in bipolar disorder but negative in major depressive disorder.ConclusionsThe mood disorders share several genetic associations, and can be combined effectively to increase variant discovery. However, we demonstrate several differences between these disorders. Analysing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.
Published: 2020

44. Tractor: A framework allowing for improved inclusion of admixed individuals in large-scale association studies

Author: Elizabeth G. Atkinson, Yukinori Okada, Adam X. Maihofer, Caroline M. Nievergelt, Mark J. Daly, Konrad J. Karczewski, Jacob C. Ulirsch, Neale Bm, Alicia R. Martin, Hilary K. Finucane, Marcos L. Santoro, Yoichiro Kamatani, Karestan C. Koenen, and Masahiro Kanai
Subjects: Tractor, 0303 health sciences, Empirical data, business.product_category, Computer science, Genome-wide association study, Regression analysis, Computational biology, Replicate, Software package, 03 medical and health sciences, 0302 clinical medicine, Scale (social sciences), business, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract: Admixed populations are routinely excluded from medical 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 testTractorwith simulations and empirical data focused on admixed African-European individuals.Tractorgenerates ancestryspecific effect size estimates, can boost GWAS power, and improves the resolution of association signals. Using a local ancestry aware regression model, we replicate known hits for blood lipids in admixed populations, discover novel hits missed by standard GWAS procedures, and localize signals closer to putative causal variants.
Published: 2020

45. HCR-FlowFISH: A flexible CRISPR screening method to identify cis-regulatory elements and their target genes

Author: Susan Kales, Pardis C. Sabeti, Jacob C. Ulirsch, Hilary K. Finucane, Austin J. Gutierrez, Masahiro Kanai, Sager J. Gosai, Ryan Tewhey, Daniel Berenzy, Steven K. Reilly, Gina M Butler, and Adrianne Gladden-Young
Subjects: LMO2, Gene expression, Gene cluster, CRISPR, GATA1, Computational biology, Biology, Gene, Phenotype, Genome
Abstract: CRISPR screens for cis-regulatory elements (CREs) have shown unprecedented power to endogenously characterize the non-coding genome. To characterize CREs we developed HCR-FlowFISH (Hybridization Chain Reaction Fluorescent In-Situ Hybridization coupled with Flow Cytometry), which directly quantifies native transcripts within their endogenous loci following CRISPR perturbations of regulatory elements, eliminating the need for restrictive phenotypic assays such as growth or transcript-tagging. HCR-FlowFISH accurately quantifies gene expression across a wide range of transcript levels and cell types. We also developed CASA (CRISPR Activity Screen Analysis), a hierarchical Bayesian model to identify and quantify CRE activity. Using >270,000 perturbations, we identified CREs for GATA1, HDAC6, ERP29, LMO2, MEF2C, CD164, NMU, FEN1 and the FADS gene cluster. Our methods detect subtle gene expression changes and identify CREs regulating multiple genes, sometimes at different magnitudes and directions. We demonstrate the power of HCR-FlowFISH to parse genome-wide association signals by nominating causal variants and target genes.
Published: 2020

46. Estimating cross-population genetic correlations of causal effect sizes

Author: Kevin Galinsky, Hilary K. Finucane, Brielin C. Brown, Yakir A. Reshef, Nick Patterson, Noah Zaitlen, Po-Ru Loh, and Alkes L. Price
Subjects: 0303 health sciences, education.field_of_study, Linkage disequilibrium, Epidemiology, 030305 genetics & heredity, Population, Single-nucleotide polymorphism, Biology, Quantitative trait locus, Genetic correlation, Genetic architecture, Correlation, 03 medical and health sciences, Genetic epidemiology, Statistics, education, Genetics (clinical), 030304 developmental biology
Abstract: Recent studies have examined the genetic correlations of single-nucleotide polymorphism (SNP) effect sizes across pairs of populations to better understand the genetic architectures of complex traits. These studies have estimated ρ g , the cross-population correlation of joint-fit effect sizes at genotyped SNPs. However, the value of ρ g depends both on the cross-population correlation of true causal effect sizes ( ρ b ) and on the similarity in linkage disequilibrium (LD) patterns in the two populations, which drive tagging effects. Here, we derive the value of the ratio ρ g / ρ b as a function of LD in each population. By applying existing methods to obtain estimates of ρ g , we can use this ratio to estimate ρ b . Our estimates of ρ b were equal to 0.55 ( SE = 0.14) between Europeans and East Asians averaged across nine traits in the Genetic Epidemiology Research on Adult Health and Aging data set, 0.54 ( SE = 0.18) between Europeans and South Asians averaged across 13 traits in the UK Biobank data set, and 0.48 ( SE = 0.06) and 0.65 ( SE = 0.09) between Europeans and East Asians in summary statistic data sets for type 2 diabetes and rheumatoid arthritis, respectively. These results implicate substantially different causal genetic architectures across continental populations.
Published: 2018

47. Functional architecture of low-frequency variants highlights strength of negative selection across coding and non-coding annotations

Author: Shamil R. Sunyaev, Po-Ru Loh, Andrea Ganna, Steven Gazal, Armin P. Schoech, Hilary K. Finucane, and Alkes L. Price
Subjects: 0301 basic medicine, Linkage disequilibrium, Genome-wide association study, Biology, Polymorphism, Single Nucleotide, Linkage Disequilibrium, White People, Article, Combinatorics, Open Reading Frames, 03 medical and health sciences, Gene Frequency, Missing heritability problem, Genetics, Humans, Selection, Genetic, Allele, Allele frequency, Alleles, Biological Specimen Banks, Genetic Variation, Molecular Sequence Annotation, Heritability, United Kingdom, Genetic architecture, Minor allele frequency, Genetics, Population, 030104 developmental biology, Genome-Wide Association Study
Abstract: Common variant heritability has been widely reported to be concentrated in variants within cell-type-specific non-coding functional annotations, but little is known about low-frequency variant functional architectures. We partitioned the heritability of both low-frequency (0.5%≤ minor allele frequency
Published: 2018

48. Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk

Author: Luke J. O’Connor, Alkes L. Price, Pier Francesco Palamara, David R. Kelley, Jacob C. Ulirsch, Dylan Kotliar, Luca Pinello, Farhad Hormozdiari, Ryan P. Adams, Bryce van de Geijn, Joseph Nasser, Sharon R. Grossman, Po-Ru Loh, Steven Gazal, Gaurav Bhatia, Nick Patterson, Hilary K. Finucane, Yakir A. Reshef, and Alexander Gusev
Subjects: 0301 basic medicine, Multifactorial Inheritance, Linkage disequilibrium, Quantitative Trait Loci, Genome-wide association study, Single-nucleotide polymorphism, Computational biology, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, Genome, Article, Linkage Disequilibrium, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Genetics, Humans, SNP, Disease, Genetic Predisposition to Disease, Allele, Transcription factor, 030304 developmental biology, 0303 health sciences, Binding Sites, Blood Cells, Phenotype, 030104 developmental biology, Gene Expression Regulation, Expression quantitative trait loci, Blood Chemical Analysis, 030217 neurology & neurosurgery, Genome-Wide Association Study, Protein Binding, Transcription Factors
Abstract: Biological interpretation of GWAS data frequently involves analyzing unsigned genomic annotations comprising SNPs involved in a biological process and assessing enrichment for disease signal. However, it is often possible to generate signed annotations quantifying whether each SNP allele promotes or hinders a biological process, e.g., binding of a transcription factor (TF). Directional effects of such annotations on disease risk enable stronger statements about causal mechanisms of disease than enrichments of corresponding unsigned annotations. Here we introduce a new method, signed LD profile regression, for detecting such directional effects using GWAS summary statistics, and we apply the method using 382 signed annotations reflecting predicted TF binding. We show via theory and simulations that our method is well-powered and is well-calibrated even when TF binding sites co-localize with other enriched regulatory elements, which can confound unsigned enrichment methods. We further validate our method by showing that it recovers known transcriptional regulators when applied to molecular QTL in blood. We then apply our method to eQTL in 48 GTEx tissues, identifying 651 distinct TF-tissue expression associations at per-tissue FDR < 5%, including 30 associations with robust evidence of tissue specificity. Finally, we apply our method to 46 diseases and complex traits (averageN= 289,617) and identify 77 annotation-trait associations at per-trait FDR < 5% representing 12 independent TF-trait associations, and we conduct gene-set enrichment analyses to characterize the underlying transcriptional programs. Our results implicate new causal disease genes (including causal genes at known GWAS loci), and in some cases suggest a detailed mechanism for a causal gene’s effect on disease. Our method provides a new way to leverage functional data to draw inferences about disease etiology.
Published: 2018

49. Does Childhood Trauma Moderate Polygenic Risk for Depression?

Author: Wouter J. Peyrot, Sandra Van der Auwera, Yuri Milaneschi, Conor V. Dolan, Pamela A.F. Madden, Patrick F. Sullivan, Jana Strohmaier, Stephan Ripke, Marcella Rietschel, Michel G. Nivard, Niamh Mullins, Grant W. Montgomery, Anjali K. Henders, Andrew C. Heat, Helen L. Fisher, Erin C. Dunn, Enda M. Byrne, Tracy A. Air, Bernhard T. Baune, Gerome Breen, Douglas F. Levinson, Cathryn M. Lewis, Nick G. Martin, Elliot N. Nelson, Dorret I. Boomsma, Hans J. Grabe, Naomi R. Wray, Brenda W.J.H. Penninx, Manuel Mattheisen, Maciej Trzaskowski, Abdel Abdellaoui, Mark J. Adams, Esben Agerbo, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Tim B. Bigdeli, Elisabeth B. Binder, Douglas H.R. Blackwood, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, Toni-Kim Clarke, Jonathan R.I. Coleman, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Nick Craddock, Gregory E. Crawford, Gail Davies, Ian J. Deary, Franziska Degenhardt, Eske M. Derks, Nese Direk, Thalia C. Eley, Valentina Escott-Price, null Farnush, Farhadi Hassan Kiadeh, Hilary K. Finucane, Andreas J. Forstner, Josef Frank, Héléna A. Gaspar, Michael Gill, Fernando S. Goes, Scott D. Gordon, Jakob Grove, Lynsey S. Hall, Christine Søholm Hansen, Thomas F. Hansen, Stefan Herms, Ian B. Hicki, Per Hoffmann, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, David M. Hougaard, Marcus Ising, Rick Jansen, Eric Jorgenson, James A. Knowles, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Jesper Krogh, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Donald J. MacIntyre, Dean F. MacKinnon, Robert M. Maier, Wolfgang Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Peter McGuffin, Sarah E. Medland, Divya Mehta, Christel M. Middeldorp, Evelin Mihailov, Lili Milani, Francis M. Mondimore, Sara Mostafavi, Matthias Nauck, Bernard Ng, Dale R. Nyholt, Paul F. O’Reilly, Hogni Oskarsson, Michael J. Owen, Jodie N. Painter, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Roseann E. Peterson, Erik Pettersson, Giorgio Pistis, Danielle Posthuma, Jorge A. Quiroz, Per Qvist, John P. Rice, Brien P. Riley, Margarita Rivera, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Jianxin Shi, Stanley I. Shyn, Engilbert Sigurdsson, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Hreinn Stefansson, Stacy Steinberg, Fabian Streit, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, Vassily Trubetskoy, André G. Uitterlinden, Daniel Umbricht, Albert M. van Hemert, Alexander Viktorin, Peter M. Visscher, Yunpeng Wang, Bradley T. Webb, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Stephanie H. Witt, Yang Wu, Hualin S. Xi, Jian Yang, Futao Zhang, Volker Arolt, Klaus Berger, Sven Cichon, Udo Dannlowski, E.J.C. de Geus, J. Raymond DePaulo, Enrico Domenici, Katharina Domschke, Tõnu Esko, Steven P. Hamilton, Caroline Hayward, Andrew C. Heath, Kenneth S. Kendler, Stefan Kloiber, Glyn Lewis, Qingqin S. Li, Susanne Lucae, Patrik K. Magnusson, Nicholas G. Martin, Andrew M. McIntosh, Andres Metspalu, Ole Mors, Preben Bo Mortensen, Bertram Müller-Myhsok, Merete Nordentoft, Markus M. Nöthen, Michael C. O'Donovan, Sara A. Paciga, Nancy L. Pedersen, Roy H. Perlis, David J. Porteous, James B. Potash, Martin Preisig, Catherine Schaefer, Thomas G. Schulze, Jordan W. Smoller, Kari Stefansson, Henning Tiemeier, Rudolf Uher, Henry Völzke, Myrna M. Weissman, Thomas Werge, Anders D. Børglum, Biological Psychology, APH - Methodology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Adult Psychiatry, ARD - Amsterdam Reproduction and Development, Epidemiology, Urology, Child and Adolescent Psychiatry / Psychology, Internal Medicine, Medical Informatics, Immunology, Psychiatry, Amsterdam Reproduction & Development (AR&D), Human genetics, Epidemiology and Data Science, and APH - Digital Health
Subjects: 0301 basic medicine, Child abuse, Adult, Male, Netherlands Twin Register (NTR), medicine.medical_specialty, Multifactorial Inheritance, polygenic risk, SDG 16 - Peace, interaction, Risk Assessment, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, mental disorders, medicine, Journal Article, Humans, genetics, Genetic Predisposition to Disease, Child Abuse, Psychiatry, Child, Biological Psychiatry, Psychiatric Status Rating Scales, Depressive Disorder, Major, childhood trauma, Genetic heterogeneity, Depression, Adult Survivors of Child Abuse, SDG 16 - Peace, Justice and Strong Institutions, Case-control study, Odds ratio, medicine.disease, Justice and Strong Institutions, meta-analysis, 030104 developmental biology, Physical abuse, Logistic Models, 5-HTTLPR, Meta-analysis, Case-Control Studies, Major depressive disorder, Female, Gene-Environment Interaction, Psychology, 030217 neurology & neurosurgery
Abstract: BackgroundThe heterogeneity of genetic effects on major depressive disorder (MDD) may be partly attributable to moderation of genetic effects by environment, such as exposure to childhood trauma (CT). Indeed, previous findings in two independent cohorts showed evidence for interaction between polygenic risk scores (PRSs) and CT, albeit in opposing directions. This study aims to meta-analyze MDD-PRS × CT interaction results across these two and other cohorts, while applying more accurate PRSs based on a larger discovery sample.MethodsData were combined from 3024 MDD cases and 2741 control subjects from nine cohorts contributing to the MDD Working Group of the Psychiatric Genomics Consortium. MDD-PRS were based on a discovery sample of ∼110,000 independent individuals. CT was assessed as exposure to sexual or physical abuse during childhood. In a subset of 1957 cases and 2002 control subjects, a more detailed five-domain measure additionally included emotional abuse, physical neglect, and emotional neglect.ResultsMDD was associated with the MDD-PRS (odds ratio [OR] = 1.24, p = 3.6 × 10-5, R2 = 1.18%) and with CT (OR = 2.63, p = 3.5 × 10-18 and OR = 2.62, p = 1.4 ×10-5 for the two- and five-domain measures, respectively). No interaction was found between MDD-PRS and the two-domain and five-domain CT measure (OR = 1.00, p = .89 and OR = 1.05, p = .66).ConclusionsNo meta-analytic evidence for interaction between MDD-PRS and CT was found. This suggests that the previously reported interaction effects, although both statistically significant, can best be interpreted as chance findings. Further research is required, but this study suggests that the genetic heterogeneity of MDD is not attributable to genome-wide moderation of genetic effects by CT.
Published: 2018

50. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression

Author: Jens Treutlein, James B. Potash, Cheynna A. Crowley, Paul F. O'Reilly, Francis M. Mondimore, Nicholas G. Martin, Jodie N. Painter, Qingqin S. Li, Tõnu Esko, Michael Conlon O'Donovan, Markus M. Nöthen, Toni-Kim Clarke, Roseann E. Peterson, Shantel Weinsheimer, Naomi R. Wray, Marie Bækvad-Hansen, Pamela F.A. Madden, Johannes H. Smit, Gonneke Willemsen, Thomas Hansen, Andrew C. Heath, Carsten Horn, Udo Dannlowski, Fulai Jin, Robert A. Schoevers, Jian Yang, Nicholas Eriksson, Marianne Giørtz Pedersen, Patrik K. E. Magnusson, Hans J. Grabe, Michael Gill, Lili Milani, Caroline Hayward, Shaun Purcell, Stanley I. Shyn, Penelope A. Lind, Giorgio Pistis, Michel G. Nivard, Thorgeir E. Thorgeirsson, Abdel Abdellaoui, Andres Metspalu, David J. Porteous, Anders D. Børglum, Christine Søholm Hansen, Scott D. Gordon, Nicholas John Craddock, Susanne Lucae, Douglas Blackwood, Jürgen Wellmann, Till M.F. Andlauer, Wesley K. Thompson, Chao Tian, Rudolf Uher, Nese Direk, Yuri Milaneschi, Paola Giusti-Rodríguez, Rick Jansen, Marcus Ising, Yang Wu, Jesper Krogh, Merete Nordentoft, Jouke-Jan Hottenga, Robert Maier, Ming Hu, Kari Stefansson, Glyn Lewis, Peter McGuffin, Wolfgang Maier, Erin C. Dunn, Bradley T. Webb, Gerome Breen, Henning Teismann, Eric Jorgenson, Jorge A. Quiroz, Brenda W.J.H. Penninx, Jonas Bybjerg-Grauholm, Warren W. Kretzschmar, Dean F. MacKinnon, Craig A. Stockmeier, Wouter J. Peyrot, Enrico Domenici, E. C.J. De Geus, Alexander Teumer, Henry Völzke, Yihan Li, Michael John Owen, Manuel Mattheisen, Bernard Ng, Baptiste Couvy-Duchesne, Daniel J. Smith, Jana Strohmaier, Vassily Trubetskoy, Volker Arolt, Douglas F. Levinson, Futao Zhang, Daniel Umbricht, Aartjan F.T. Beekman, David A. Hinds, Bernhard T. Baune, Henning Tiemeier, Hualin S. Xi, Hamdi Mbarek, Steven P. Hamilton, Stefan Kloiber, Fernando S. Goes, Jianxin Shi, Marcella Rietschel, Dale R. Nyholt, Zoltán Kutalik, Niamh Mullins, Grant W. Montgomery, Henriette N. Buttenschøn, Georg Homuth, Katharina Domschke, Alexander Viktorin, Hilary K. Finucane, Ashley R. Winslow, Saira Saeed Mirza, Fabian Streit, Erik Pettersson, Martin Preisig, Danielle Posthuma, Stephan Ripke, Lucía Colodro-Conde, Thalia C. Eley, Pippa A. Thomson, Thomas Werge, Enrique Castelao, Klaus Berger, Yun Li, Stacy Steinberg, Dorret I. Boomsma, Matthias Nauck, Sara Mostafavi, Jacqueline M. Lane, Katherine E. Tansey, Divya Mehta, Gregory E. Crawford, Andreas J. Forstner, Jane H. Christensen, Silviu Alin Bacanu, Julia Kraft, David M. Hougaard, Peter M. Visscher, Valentina Escott-Price, Donald J. MacIntyre, Sarah E. Medland, Per Qvist, Kenneth S. Kendler, Jordan W. Smoller, J. Raymond DePaulo, Ian J. Deary, Thomas G. Schulze, Julien Bryois, Ian B. Hickie, Helena Gaspar, Jonathan Mill, James A. Knowles, Cathryn M. Lewis, Hassan S. Dashti, Stefan Herms, Margarita Rivera, John P. Rice, Lynsey S. Hall, Eilis Hannon, Nancy L. Pedersen, Eva C. Schulte, Hreinn Stefansson, Maciej Trzaskowski, André G. Uitterlinden, Bertram Müller-Myhsok, Gail Davies, Mark Adams, Jakob Grove, Eske M. Derks, Sven Cichon, Jonathan I.R. Coleman, Sandra Van der Auwera, Myrna M. Weissman, Preben Bo Mortensen, Josef Frank, Enda M. Byrne, Esben Agerbo, Engilbert Sigurdsson, Xiaoxiao Liu, Patrick F. Sullivan, Carsten Bøcker Pedersen, Ole Mors, Catherine Schaefer, Richa Saxena, Albert M. van Hemert, Jonathan Marchini, Hogni Oskarsson, Franziska Degenhardt, Tracy Air, Elisabeth B. Binder, Christel M. Middeldorp, Farnush Hassan Farhadi Kiadeh, Conor V. Dolan, Sara A. Paciga, Per Hoffmann, Leina Lu, Andrew M. McIntosh, Tim B. Bigdeli, Stephanie H. Witt, Matthew Traylor, Grant Sinnamon, Brien P. Riley, Roy H. Perlis, Patrick J. McGrath, Craig L. Hyde, Ling Shen, Na Cai, Yunpeng Wang, Evelin Mihailov, Isaac S. Kohane, APH - Mental Health, Adult Psychiatry, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Biological Psychology, APH - Methodology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Integrative Neurophysiology, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Psychiatry, Amsterdam Reproduction & Development (AR&D), Human genetics, Epidemiology and Data Science, APH - Digital Health, Epidemiology, Child and Adolescent Psychiatry / Psychology, Internal Medicine, eQTLGen, 23andMe, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Perceptual and Cognitive Neuroscience (PCN), and Clinical Cognitive Neuropsychiatry Research Program (CCNP)
Subjects: 0301 basic medicine, Male, Netherlands Twin Register (NTR), Multifactorial Inheritance, Schizophrenia/genetics, LD SCORE REGRESSION, LOCI, Genome-wide association study, Bioinformatics, 0302 clinical medicine, Risk Factors, POLYGENIC RISK, Depression (differential diagnoses), 3. Good health, Phenotype, Schizophrenia, Meta-analysis, MENDELIAN RANDOMIZATION, Genome-Wide Association Study/methods, Major depressive disorder, Female, Depressive Disorder, Major/genetics, EUROPE 2010, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, ddc:570, MENTAL-DISORDERS, Mendelian randomization, SYSTEMATIC ANALYSIS, Genetics, medicine, Journal Article, Humans, Genetic Predisposition to Disease, METAANALYSIS, EDUCATIONAL-ATTAINMENT, Depressive Disorder, Major, Case-control study, Case-Control Studies, medicine.disease, Genetic architecture, BODY-MASS INDEX, 030104 developmental biology, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened\ud risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified\ud 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and\ud implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved\ud in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression\ud with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were\ud putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry\ud lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression\ud and imply that a continuous measure of risk underlies the clinical phenotype.
Published: 2018

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