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1. Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation

Author

Vaid, Akhil, Somani, Sulaiman, Russak, Adam J, De Freitas, Jessica K, Chaudhry, Fayzan F, Paranjpe, Ishan, Johnson, Kipp W, Lee, Samuel J, Miotto, Riccardo, Richter, Felix, Zhao, Shan, Beckmann, Noam D, Naik, Nidhi, Kia, Arash, Timsina, Prem, Lala, Anuradha, Paranjpe, Manish, Golden, Eddye, Danieletto, Matteo, Singh, Manbir, Meyer, Dara, O'Reilly, Paul F, Huckins, Laura, Kovatch, Patricia, Finkelstein, Joseph, Freeman, Robert M., Argulian, Edgar, Kasarskis, Andrew, Percha, Bethany, Aberg, Judith A, Bagiella, Emilia, Horowitz, Carol R, Murphy, Barbara, Nestler, Eric J, Schadt, Eric E, Cho, Judy H, Cordon-Cardo, Carlos, Fuster, Valentin, Charney, Dennis S, Reich, David L, Bottinger, Erwin P, Levin, Matthew A, Narula, Jagat, Fayad, Zahi A, Just, Allan C, Charney, Alexander W, Nadkarni, Girish N, and Glicksberg, Benjamin S

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundCOVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. ObjectiveThe aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. MethodsWe used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19–positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. ResultsUpon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. ConclusionsWe externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.

Published
2020
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2. Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder.

Author

Nievergelt, Caroline, Maihofer, Adam, Atkinson, Elizabeth, Chen, Chia-Yen, Choi, Karmel, Coleman, Jonathan, Daskalakis, Nikolaos, Duncan, Laramie, Polimanti, Renato, Aaronson, Cindy, Amstadter, Ananda, Andersen, Soren, Andreassen, Ole, Arbisi, Paul, Ashley-Koch, Allison, Austin, S, Avdibegoviç, Esmina, Babić, Dragan, Bacanu, Silviu-Alin, Baker, Dewleen, Batzler, Anthony, Beckham, Jean, Belangero, Sintia, Benjet, Corina, Bergner, Carisa, Bierer, Linda, Biernacka, Joanna, Bierut, Laura, Bisson, Jonathan, Boks, Marco, Bolger, Elizabeth, Brandolino, Amber, Breen, Gerome, Bressan, Rodrigo, Bryant, Richard, Bustamante, Angela, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Børglum, Anders, Børte, Sigrid, Cahn, Leah, Calabrese, Joseph, Caldas-de-Almeida, Jose, Chatzinakos, Chris, Cheema, Sheraz, Clouston, Sean, Colodro-Conde, Lucía, Coombes, Brandon, Cruz-Fuentes, Carlos, Dale, Anders, Dalvie, Shareefa, Davis, Lea, Deckert, Jürgen, Delahanty, Douglas, Dennis, Michelle, Desarnaud, Frank, DiPietro, Christopher, Disner, Seth, Docherty, Anna, Domschke, Katharina, Dyb, Grete, Kulenović, Alma, Edenberg, Howard, Evans, Alexandra, Fabbri, Chiara, Fani, Negar, Farrer, Lindsay, Feder, Adriana, Feeny, Norah, Flory, Janine, Forbes, David, Franz, Carol, Galea, Sandro, Garrett, Melanie, Gelaye, Bizu, Gelernter, Joel, Geuze, Elbert, Gillespie, Charles, Goleva, Slavina, Gordon, Scott, Goçi, Aferdita, Grasser, Lana, Guindalini, Camila, Haas, Magali, Hagenaars, Saskia, Hauser, Michael, Heath, Andrew, Hemmings, Sian, Hesselbrock, Victor, Hickie, Ian, Hogan, Kelleigh, Hougaard, David, Huang, Hailiang, Huckins, Laura, Hveem, Kristian, Jakovljević, Miro, Javanbakht, Arash, Jenkins, Gregory, Johnson, Jessica, and Jones, Ian

Subjects
Humans, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Neurobiology, Polymorphism, Single Nucleotide, Stress Disorders, Post-Traumatic, White People, White, Black or African American, American Indian or Alaska Native
Abstract

Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

Published
2024

3. Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals.

Author

Zhou, Hang, Kember, Rachel, Deak, Joseph, Xu, Heng, Toikumo, Sylvanus, Yuan, Kai, Lind, Penelope, Farajzadeh, Leila, Wang, Lu, Hatoum, Alexander, Johnson, Jessica, Lee, Hyunjoon, Mallard, Travis, Xu, Jiayi, Johnston, Keira, Johnson, Emma, Nielsen, Trine, Galimberti, Marco, Dao, Cecilia, Levey, Daniel, Overstreet, Cassie, Byrne, Enda, Gillespie, Nathan, Gordon, Scott, Hickie, Ian, Whitfield, John, Xu, Ke, Zhao, Hongyu, Huckins, Laura, Davis, Lea, Sanchez-Roige, Sandra, Madden, Pamela, Heath, Andrew, Medland, Sarah, Martin, Nicholas, Ge, Tian, Smoller, Jordan, Hougaard, David, Børglum, Anders, Demontis, Ditte, Krystal, John, Gaziano, J, Edenberg, Howard, Agrawal, Arpana, Justice, Amy, Stein, Murray, Kranzler, Henry, and Gelernter, Joel

Subjects
Humans, Genetic Predisposition to Disease, Genome-Wide Association Study, Phenotype, Polymorphism, Single Nucleotide, Racial Groups, Alcoholism
Abstract

Problematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.

Published
2023

5. Leveraging base-pair mammalian constraint to understand genetic variation and human disease

Author

Sullivan, Patrick F, Meadows, Jennifer RS, Gazal, Steven, Phan, BaDoi N, Li, Xue, Genereux, Diane P, Dong, Michael X, Bianchi, Matteo, Andrews, Gregory, Sakthikumar, Sharadha, Nordin, Jessika, Roy, Ananya, Christmas, Matthew J, Marinescu, Voichita D, Wang, Chao, Wallerman, Ola, Xue, James, Yao, Shuyang, Sun, Quan, Szatkiewicz, Jin, Wen, Jia, Huckins, Laura M, Lawler, Alyssa, Keough, Kathleen C, Zheng, Zhili, Zeng, Jian, Wray, Naomi R, Li, Yun, Johnson, Jessica, Chen, Jiawen, Paten, Benedict, Reilly, Steven K, Hughes, Graham M, Weng, Zhiping, Pollard, Katherine S, Pfenning, Andreas R, Forsberg-Nilsson, Karin, Karlsson, Elinor K, Lindblad-Toh, Kerstin, Armstrong, Joel C, Birren, Bruce W, Bredemeyer, Kevin R, Breit, Ana M, Clawson, Hiram, Damas, Joana, Di Palma, Federica, Diekhans, Mark, Eizirik, Eduardo, Fan, Kaili, Fanter, Cornelia, Foley, Nicole M, Garcia, Carlos J, Gatesy, John, Goodman, Linda, Grimshaw, Jenna, Halsey, Michaela K, Harris, Andrew J, Hickey, Glenn, Hiller, Michael, Hindle, Allyson G, Hubley, Robert M, Johnson, Jeremy, Juan, David, Kaplow, Irene M, Kirilenko, Bogdan, Koepfli, Klaus-Peter, Korstian, Jennifer M, Kowalczyk, Amanda, Kozyrev, Sergey V, Lawler, Alyssa J, Lawless, Colleen, Lehmann, Thomas, Levesque, Danielle L, Lewin, Harris A, Lind, Abigail, Mackay-Smith, Ava, Marques-Bonet, Tomas, Mason, Victor C, Meyer, Wynn K, Moore, Jill E, Moreira, Lucas R, Moreno-Santillan, Diana D, Morrill, Kathleen M, Muntané, Gerard, Murphy, William J, and Navarro, Arcadi

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Clinical Research, Human Genome, Brain Disorders, Generic health relevance, Animals, Humans, Biological Evolution, Genetic Variation, Genome, Human, Genome-Wide Association Study, Genomics, Molecular Sequence Annotation, Polymorphism, Single Nucleotide, Disease, Zoonomia Consortium§, General Science & Technology
Abstract

Thousands of genomic regions have been associated with heritable human diseases, but attempts to elucidate biological mechanisms are impeded by an inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function, agnostic to cell type or disease mechanism. Single-base phyloP scores from 240 mammals identified 3.3% of the human genome as significantly constrained and likely functional. We compared phyloP scores to genome annotation, association studies, copy-number variation, clinical genetics findings, and cancer data. Constrained positions are enriched for variants that explain common disease heritability more than other functional annotations. Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

Published
2023

10. Using phenotype risk scores to enhance gene discovery for generalized anxiety disorder and posttraumatic stress disorder.

Author

Wendt, Frank, Pathak, Gita, Deak, Joseph, De Angelis, Flavio, Koller, Dora, Cabrera-Mendoza, Brenda, Lebovitch, Dannielle, Levey, Daniel, Stein, Murray, Kranzler, Henry, Koenen, Karestan, Gelernter, Joel, Huckins, Laura, and Polimanti, Renato

Subjects
Anxiety Disorders, Depressive Disorder, Major, Female, Genome-Wide Association Study, Humans, Male, Phenotype, Risk Factors, Stress Disorders, Post-Traumatic
Abstract

UK Biobank (UKB) is a key contributor in mental health genome-wide association studies (GWAS) but only ~31% of participants completed the Mental Health Questionnaire (MHQ responders). We predicted generalized anxiety disorder (GAD), posttraumatic stress disorder (PTSD), and major depression symptoms using elastic net regression in the ~69% of UKB participants lacking MHQ data (MHQ non-responders; NTraining = 50%; NTest = 50%), maximizing the informative sample for these traits. MHQ responders were more likely to be female, from higher socioeconomic positions, and less anxious than non-responders. Genetic correlation of GAD and PTSD between MHQ responders and non-responders ranged from 0.636 to 1.08; both were predicted by polygenic scores generated from independent cohorts. In meta-analyses of GAD (N = 489,579) and PTSD (N = 497,803), we discovered many novel genomic risk loci (13 for GAD and 40 for PTSD). Transcriptomic analyses converged on altered regulation of prenatal dorsolateral prefrontal cortex in these disorders. Our results provide one roadmap by which sample size and statistical power may be improved for gene discovery of incompletely ascertained traits in the UKB and other biobanks with limited mental health assessment.

Published
2022

14. Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study

Author

Hu, Yao, Bien, Stephanie A, Nishimura, Katherine K, Haessler, Jeffrey, Hodonsky, Chani J, Baldassari, Antoine R, Highland, Heather M, Wang, Zhe, Preuss, Michael, Sitlani, Colleen M, Wojcik, Genevieve L, Tao, Ran, Graff, Mariaelisa, Huckins, Laura M, Sun, Quan, Chen, Ming-Huei, Mousas, Abdou, Auer, Paul L, Lettre, Guillaume, Tang, Weihong, Qi, Lihong, Thyagarajan, Bharat, Buyske, Steve, Fornage, Myriam, Hindorff, Lucia A, Li, Yun, Lin, Danyu, Reiner, Alexander P, North, Kari E, Loos, Ruth JF, Raffield, Laura M, Peters, Ulrike, Avery, Christy L, and Kooperberg, Charles

Subjects
Clinical Research, Hematology, Genetics, American Indian or Alaska Native, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Leukocytes, Phenotype, Polymorphism, Single Nucleotide, GWAS, White blood cells, Platelets, Multi-ethnic, Blood Cell Consortium, Biological Sciences, Information and Computing Sciences, Medical and Health Sciences, Bioinformatics
Abstract

BackgroundCirculating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented.ResultsWe performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance (P < 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance (P < 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations.ConclusionsOur results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.

Published
2021

15. Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics.

Author

Lam, Max, Chen, Chia-Yen, Ge, Tian, Xia, Yan, Hill, David W, Trampush, Joey W, Yu, Jin, Knowles, Emma, Davies, Gail, Stahl, Eli A, Huckins, Laura, Liewald, David C, Djurovic, Srdjan, Melle, Ingrid, Christoforou, Andrea, Reinvang, Ivar, DeRosse, Pamela, Lundervold, Astri J, Steen, Vidar M, Espeseth, Thomas, Räikkönen, Katri, Widen, Elisabeth, Palotie, Aarno, Eriksson, Johan G, Giegling, Ina, Konte, Bettina, Hartmann, Annette M, Roussos, Panos, Giakoumaki, Stella, Burdick, Katherine E, Payton, Antony, Ollier, William, Chiba-Falek, Ornit, Koltai, Deborah C, Need, Anna C, Cirulli, Elizabeth T, Voineskos, Aristotle N, Stefanis, Nikos C, Avramopoulos, Dimitrios, Hatzimanolis, Alex, Smyrnis, Nikolaos, Bilder, Robert M, Freimer, Nelson B, Cannon, Tyrone D, London, Edythe, Poldrack, Russell A, Sabb, Fred W, Congdon, Eliza, Conley, Emily Drabant, Scult, Matthew A, Dickinson, Dwight, Straub, Richard E, Donohoe, Gary, Morris, Derek, Corvin, Aiden, Gill, Michael, Hariri, Ahmad R, Weinberger, Daniel R, Pendleton, Neil, Bitsios, Panos, Rujescu, Dan, Lahti, Jari, Le Hellard, Stephanie, Keller, Matthew C, Andreassen, Ole A, Deary, Ian J, Glahn, David C, Huang, Hailiang, Liu, Chunyu, Malhotra, Anil K, and Lencz, Todd

Subjects
Humans, Nootropic Agents, Cognition, Schizophrenia, Genome-Wide Association Study, Transcriptome, Psychiatry, Medical and Health Sciences, Psychology and Cognitive Sciences
Abstract

Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.

Published
2021

18. Schizophrenia risk conferred by rare protein-truncating variants is conserved across diverse human populations

Author

Liu, Dongjing, Meyer, Dara, Fennessy, Brian, Feng, Claudia, Cheng, Esther, Johnson, Jessica S., Park, You Jeong, Rieder, Marysia-Kolbe, Ascolillo, Steven, de Pins, Agathe, Dobbyn, Amanda, Lebovitch, Dannielle, Moya, Emily, Nguyen, Tan-Hoang, Wilkins, Lillian, Hassan, Arsalan, Burdick, Katherine E., Buxbaum, Joseph D., Domenici, Enrico, Frangou, Sophia, Hartmann, Annette M., Laurent-Levinson, Claudine, Malhotra, Dheeraj, Pato, Carlos N., Pato, Michele T., Ressler, Kerry, Roussos, Panos, Rujescu, Dan, Arango, Celso, Bertolino, Alessandro, Blasi, Giuseppe, Bocchio-Chiavetto, Luisella, Campion, Dominique, Carr, Vaughan, Fullerton, Janice M., Gennarelli, Massimo, González-Peñas, Javier, Levinson, Douglas F., Mowry, Bryan, Nimgaokar, Vishwajit L., Pergola, Giulio, Rampino, Antonio, Cervilla, Jorge A., Rivera, Margarita, Schwab, Sibylle G., Wildenauer, Dieter B., Daly, Mark, Neale, Benjamin, Singh, Tarjinder, O’Donovan, Michael C., Owen, Michael J., Walters, James T., Ayub, Muhammad, Malhotra, Anil K., Lencz, Todd, Sullivan, Patrick F., Sklar, Pamela, Stahl, Eli A., Huckins, Laura M., and Charney, Alexander W.

Published
2023
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19. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Author

Mullins, Niamh, Forstner, Andreas J, O’Connell, Kevin S, Coombes, Brandon, Coleman, Jonathan RI, Qiao, Zhen, Als, Thomas D, Bigdeli, Tim B, Børte, Sigrid, Bryois, Julien, Charney, Alexander W, Drange, Ole Kristian, Gandal, Michael J, Hagenaars, Saskia P, Ikeda, Masashi, Kamitaki, Nolan, Kim, Minsoo, Krebs, Kristi, Panagiotaropoulou, Georgia, Schilder, Brian M, Sloofman, Laura G, Steinberg, Stacy, Trubetskoy, Vassily, Winsvold, Bendik S, Won, Hong-Hee, Abramova, Liliya, Adorjan, Kristina, Agerbo, Esben, Al Eissa, Mariam, Albani, Diego, Alliey-Rodriguez, Ney, Anjorin, Adebayo, Antilla, Verneri, Antoniou, Anastasia, Awasthi, Swapnil, Baek, Ji Hyun, Bækvad-Hansen, Marie, Bass, Nicholas, Bauer, Michael, Beins, Eva C, Bergen, Sarah E, Birner, Armin, Bøcker Pedersen, Carsten, Bøen, Erlend, Boks, Marco P, Bosch, Rosa, Brum, Murielle, Brumpton, Ben M, Brunkhorst-Kanaan, Nathalie, Budde, Monika, Bybjerg-Grauholm, Jonas, Byerley, William, Cairns, Murray, Casas, Miquel, Cervantes, Pablo, Clarke, Toni-Kim, Cruceanu, Cristiana, Cuellar-Barboza, Alfredo, Cunningham, Julie, Curtis, David, Czerski, Piotr M, Dale, Anders M, Dalkner, Nina, David, Friederike S, Degenhardt, Franziska, Djurovic, Srdjan, Dobbyn, Amanda L, Douzenis, Athanassios, Elvsåshagen, Torbjørn, Escott-Price, Valentina, Ferrier, I Nicol, Fiorentino, Alessia, Foroud, Tatiana M, Forty, Liz, Frank, Josef, Frei, Oleksandr, Freimer, Nelson B, Frisén, Louise, Gade, Katrin, Garnham, Julie, Gelernter, Joel, Giørtz Pedersen, Marianne, Gizer, Ian R, Gordon, Scott D, Gordon-Smith, Katherine, Greenwood, Tiffany A, Grove, Jakob, Guzman-Parra, José, Ha, Kyooseob, Haraldsson, Magnus, Hautzinger, Martin, Heilbronner, Urs, Hellgren, Dennis, Herms, Stefan, Hoffmann, Per, Holmans, Peter A, Huckins, Laura, Jamain, Stéphane, Johnson, Jessica S, and Kalman, Janos L

Subjects
Biological Sciences, Genetics, Biotechnology, Serious Mental Illness, Human Genome, Bipolar Disorder, Neurosciences, Brain Disorders, Mental Health, Aetiology, 2.1 Biological and endogenous factors, Neurological, Mental health, Good Health and Well Being, Case-Control Studies, Chromosomes, Human, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Major Histocompatibility Complex, Multifactorial Inheritance, Phenotype, Quantitative Trait Loci, Risk Factors, HUNT All-In Psychiatry, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

Published
2021

20. Shared genetic risk between eating disorder‐ and substance‐use‐related phenotypes: Evidence from genome‐wide association studies

Author

Munn‐Chernoff, Melissa A, Johnson, Emma C, Chou, Yi‐Ling, Coleman, Jonathan RI, Thornton, Laura M, Walters, Raymond K, Yilmaz, Zeynep, Baker, Jessica H, Hübel, Christopher, Gordon, Scott, Medland, Sarah E, Watson, Hunna J, Gaspar, Héléna A, Bryois, Julien, Hinney, Anke, Leppä, Virpi M, Mattheisen, Manuel, Ripke, Stephan, Yao, Shuyang, Giusti‐Rodríguez, Paola, Hanscombe, Ken B, Adan, Roger AH, Alfredsson, Lars, Ando, Tetsuya, Andreassen, Ole A, Berrettini, Wade H, Boehm, Ilka, Boni, Claudette, Perica, Vesna Boraska, Buehren, Katharina, Burghardt, Roland, Cassina, Matteo, Cichon, Sven, Clementi, Maurizio, Cone, Roger D, Courtet, Philippe, Crow, Scott, Crowley, James J, Danner, Unna N, Davis, Oliver SP, de Zwaan, Martina, Dedoussis, George, Degortes, Daniela, DeSocio, Janiece E, Dick, Danielle M, Dikeos, Dimitris, Dina, Christian, Dmitrzak‐Weglarz, Monika, Docampo, Elisa, Duncan, Laramie E, Egberts, Karin, Ehrlich, Stefan, Escaramís, Geòrgia, Esko, Tõnu, Estivill, Xavier, Farmer, Anne, Favaro, Angela, Fernández‐Aranda, Fernando, Fichter, Manfred M, Fischer, Krista, Föcker, Manuel, Foretova, Lenka, Forstner, Andreas J, Forzan, Monica, Franklin, Christopher S, Gallinger, Steven, Giegling, Ina, Giuranna, Johanna, Gonidakis, Fragiskos, Gorwood, Philip, Mayora, Monica Gratacos, Guillaume, Sébastien, Guo, Yiran, Hakonarson, Hakon, Hatzikotoulas, Konstantinos, Hauser, Joanna, Hebebrand, Johannes, Helder, Sietske G, Herms, Stefan, Herpertz‐Dahlmann, Beate, Herzog, Wolfgang, Huckins, Laura M, Hudson, James I, Imgart, Hartmut, Inoko, Hidetoshi, Janout, Vladimir, Jiménez‐Murcia, Susana, Julià, Antonio, Kalsi, Gursharan, Kaminská, Deborah, Karhunen, Leila, Karwautz, Andreas, Kas, Martien JH, Kennedy, James L, Keski‐Rahkonen, Anna, Kiezebrink, Kirsty, Kim, Youl‐Ri, Klump, Kelly L, Knudsen, Gun Peggy S, and La Via, Maria C

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Epidemiology, Health Sciences, Psychology, Pharmacology and Pharmaceutical Sciences, Nutrition, Brain Disorders, Alcoholism, Alcohol Use and Health, Mental Health, Eating Disorders, Substance Misuse, Genetics, Tobacco Smoke and Health, Tobacco, Human Genome, Drug Abuse (NIDA only), Prevention, Clinical Research, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Aetiology, Mental health, Good Health and Well Being, Alcoholism, Depressive Disorder, Major, Feeding and Eating Disorders, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Schizophrenia, Substance-Related Disorders, Tobacco Use Disorder, eating disorders, genetic correlation, substance use, Medical and Health Sciences, Psychology and Cognitive Sciences, Substance Abuse, Biomedical and clinical sciences, Health sciences
Abstract

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.

Published
2021

21. Molecular states during acute COVID-19 reveal distinct etiologies of long-term sequelae

Author

Thompson, Ryan C., Simons, Nicole W., Wilkins, Lillian, Cheng, Esther, Del Valle, Diane Marie, Hoffman, Gabriel E., Cervia, Carlo, Fennessy, Brian, Mouskas, Konstantinos, Francoeur, Nancy J., Johnson, Jessica S., Lepow, Lauren, Le Berichel, Jessica, Chang, Christie, Beckmann, Aviva G., Wang, Ying-chih, Nie, Kai, Zaki, Nicholas, Tuballes, Kevin, Barcessat, Vanessa, Cedillo, Mario A., Yuan, Dan, Huckins, Laura, Roussos, Panos, Marron, Thomas U., Glicksberg, Benjamin S., Nadkarni, Girish, Heath, James R., Gonzalez-Kozlova, Edgar, Boyman, Onur, Kim-Schulze, Seunghee, Sebra, Robert, Merad, Miriam, Gnjatic, Sacha, Schadt, Eric E., Charney, Alexander W., and Beckmann, Noam D.

Published
2023
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22. Analysis of Genetically Regulated Gene Expression Identifies a Prefrontal PTSD Gene, SNRNP35, Specific to Military Cohorts

Author

Huckins, Laura M, Chatzinakos, Chris, Breen, Michael S, Hartmann, Jakob, Klengel, Torsten, da Silva Almeida, Ana C, Dobbyn, Amanda, Girdhar, Kiran, Hoffman, Gabriel E, Klengel, Claudia, Logue, Mark W, Lori, Adriana, Maihofer, Adam X, Morrison, Filomene G, Nguyen, Hoang T, Park, Yongjin, Ruderfer, Douglas, Sloofman, Laura G, van Rooij, Sanne JH, Consortium, PTSD Working Group of Psychiatric Genomics, Baker, Dewleen G, Chen, Chia-Yen, Cox, Nancy, Duncan, Laramie E, Geyer, Mark A, Glatt, Stephen J, Im, Hae Kyung, Risbrough, Victoria B, Smoller, Jordan W, Stein, Dan J, Yehuda, Rachel, Liberzon, Israel, Koenen, Karestan C, Jovanovic, Tanja, Kellis, Manolis, Miller, Mark W, Bacanu, Silviu-Alin, Nievergelt, Caroline M, Buxbaum, Joseph D, Sklar, Pamela, Ressler, Kerry J, Stahl, Eli A, and Daskalakis, Nikolaos P

Subjects
Genetics, Brain Disorders, Post-Traumatic Stress Disorder (PTSD), Mental Health, Neurosciences, 1.1 Normal biological development and functioning, Underpinning research, Neurological, Animals, Case-Control Studies, Cohort Studies, Dexamethasone, Down-Regulation, Gene Expression Regulation, Gene Regulatory Networks, Genetic Predisposition to Disease, Humans, Leukocytes, Male, Mice, Mice, Inbred C57BL, Military Personnel, Prefrontal Cortex, RNA Interference, RNA, Small Interfering, Repressor Proteins, Ribonucleoproteins, Small Nuclear, Stress Disorders, Post-Traumatic, PTSD Working Group of Psychiatric Genomics Consortium, GWAS, PTSD, blood, civilian, glucocorticoid, military, prefrontal cortex, sex, splicing, transcriptomic imputation, genetics, Transcriptomic Imputation, trauma, Biochemistry and Cell Biology, Medical Physiology
Abstract

To reveal post-traumatic stress disorder (PTSD) genetic risk influences on tissue-specific gene expression, we use brain and non-brain transcriptomic imputation. We impute genetically regulated gene expression (GReX) in 29,539 PTSD cases and 166,145 controls from 70 ancestry-specific cohorts and identify 18 significant GReX-PTSD associations corresponding to specific tissue-gene pairs. The results suggest substantial genetic heterogeneity based on ancestry, cohort type (military versus civilian), and sex. Two study-wide significant PTSD associations are identified in European and military European cohorts; ZNF140 is predicted to be upregulated in whole blood, and SNRNP35 is predicted to be downregulated in dorsolateral prefrontal cortex, respectively. In peripheral leukocytes from 175 marines, the observed PTSD differential gene expression correlates with the predicted differences for these individuals, and deployment stress produces glucocorticoid-regulated expression changes that include downregulation of both ZNF140 and SNRNP35. SNRNP35 knockdown in cells validates its functional role in U12-intron splicing. Finally, exogenous glucocorticoids in mice downregulate prefrontal Snrnp35 expression.

Published
2020

24. Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression

Author

Seah, Carina, Breen, Michael S., Rusielewicz, Tom, Bader, Heather N., Xu, Changxin, Hunter, Christopher J., McCarthy, Barry, Deans, P. J. Michael, Chattopadhyay, Mitali, Goldberg, Jordan, Desarnaud, Frank, Makotkine, Iouri, Flory, Janine D., Bierer, Linda M., Staniskyte, Migle, Noggle, Scott A., Huckins, Laura M., Paull, Daniel, Brennand, Kristen J., and Yehuda, Rachel

Published
2022
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26. Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa

Author

Watson, Hunna J, Yilmaz, Zeynep, Thornton, Laura M, Hübel, Christopher, Coleman, Jonathan RI, Gaspar, Héléna A, Bryois, Julien, Hinney, Anke, Leppä, Virpi M, Mattheisen, Manuel, Medland, Sarah E, Ripke, Stephan, Yao, Shuyang, Giusti-Rodríguez, Paola, Hanscombe, Ken B, Purves, Kirstin L, Adan, Roger AH, Alfredsson, Lars, Ando, Tetsuya, Andreassen, Ole A, Baker, Jessica H, Berrettini, Wade H, Boehm, Ilka, Boni, Claudette, Perica, Vesna Boraska, Buehren, Katharina, Burghardt, Roland, Cassina, Matteo, Cichon, Sven, Clementi, Maurizio, Cone, Roger D, Courtet, Philippe, Crow, Scott, Crowley, James J, Danner, Unna N, Davis, Oliver SP, de Zwaan, Martina, Dedoussis, George, Degortes, Daniela, DeSocio, Janiece E, Dick, Danielle M, Dikeos, Dimitris, Dina, Christian, Dmitrzak-Weglarz, Monika, Docampo, Elisa, Duncan, Laramie E, Egberts, Karin, Ehrlich, Stefan, Escaramís, Geòrgia, Esko, Tõnu, Estivill, Xavier, Farmer, Anne, Favaro, Angela, Fernández-Aranda, Fernando, Fichter, Manfred M, Fischer, Krista, Föcker, Manuel, Foretova, Lenka, Forstner, Andreas J, Forzan, Monica, Franklin, Christopher S, Gallinger, Steven, Giegling, Ina, Giuranna, Johanna, Gonidakis, Fragiskos, Gorwood, Philip, Mayora, Monica Gratacos, Guillaume, Sébastien, Guo, Yiran, Hakonarson, Hakon, Hatzikotoulas, Konstantinos, Hauser, Joanna, Hebebrand, Johannes, Helder, Sietske G, Herms, Stefan, Herpertz-Dahlmann, Beate, Herzog, Wolfgang, Huckins, Laura M, Hudson, James I, Imgart, Hartmut, Inoko, Hidetoshi, Janout, Vladimir, Jiménez-Murcia, Susana, Julià, Antonio, Kalsi, Gursharan, Kaminská, Deborah, Kaprio, Jaakko, Karhunen, Leila, Karwautz, Andreas, Kas, Martien JH, Kennedy, James L, Keski-Rahkonen, Anna, Kiezebrink, Kirsty, Kim, Youl-Ri, Klareskog, Lars, Klump, Kelly L, Knudsen, Gun Peggy S, La Via, Maria C, Le Hellard, Stephanie, and Levitan, Robert D

Subjects
Biological Sciences, Genetics, Anorexia, Serious Mental Illness, Nutrition, Prevention, Mental Health, Clinical Research, Human Genome, Brain Disorders, Pediatric, Eating Disorders, Mental health, Adult, Anorexia Nervosa, Body Mass Index, Case-Control Studies, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Male, Mental Disorders, Metabolic Diseases, Phenotype, Prognosis, Quantitative Trait Loci, Anorexia Nervosa Genetics Initiative, Eating Disorders Working Group of the Psychiatric Genomics Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness1, affecting 0.9-4% of women and 0.3% of men2-4, with twin-based heritability estimates of 50-60%5. Mortality rates are higher than those in other psychiatric disorders6, and outcomes are unacceptably poor7. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI)8,9 and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.

Published
2019

27. Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways.

Author

Lam, Max, Hill, W David, Trampush, Joey W, Yu, Jin, Knowles, Emma, Davies, Gail, Stahl, Eli, Huckins, Laura, Liewald, David C, Djurovic, Srdjan, Melle, Ingrid, Sundet, Kjetil, Christoforou, Andrea, Reinvang, Ivar, DeRosse, Pamela, Lundervold, Astri J, Steen, Vidar M, Espeseth, Thomas, Räikkönen, Katri, Widen, Elisabeth, Palotie, Aarno, Eriksson, Johan G, Giegling, Ina, Konte, Bettina, Hartmann, Annette M, Roussos, Panos, Giakoumaki, Stella, Burdick, Katherine E, Payton, Antony, Ollier, William, Chiba-Falek, Ornit, Attix, Deborah K, Need, Anna C, Cirulli, Elizabeth T, Voineskos, Aristotle N, Stefanis, Nikos C, Avramopoulos, Dimitrios, Hatzimanolis, Alex, Arking, Dan E, Smyrnis, Nikolaos, Bilder, Robert M, Freimer, Nelson A, Cannon, Tyrone D, London, Edythe, Poldrack, Russell A, Sabb, Fred W, Congdon, Eliza, Conley, Emily Drabant, Scult, Matthew A, Dickinson, Dwight, Straub, Richard E, Donohoe, Gary, Morris, Derek, Corvin, Aiden, Gill, Michael, Hariri, Ahmad R, Weinberger, Daniel R, Pendleton, Neil, Bitsios, Panos, Rujescu, Dan, Lahti, Jari, Le Hellard, Stephanie, Keller, Matthew C, Andreassen, Ole A, Deary, Ian J, Glahn, David C, Malhotra, Anil K, and Lencz, Todd

Subjects
Humans, Genetic Predisposition to Disease, Cognition, Cognition Disorders, Schizophrenia, Synaptic Transmission, Polymorphism, Single Nucleotide, Adult, Educational Status, Genome-Wide Association Study, Neurodevelopmental Disorders, GWAS, cognitive ability, educational attainment, genetic correlation, pathways, pleiotropy, schizophrenia, Serious Mental Illness, Neurosciences, Biotechnology, Mental Health, Genetics, Brain Disorders, Prevention, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Mental health, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected ("concordant") direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive ("discordant") relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms-early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways-that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness.

Published
2019

28. Publisher Correction: Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection

Author

Pardiñas, Antonio F, Holmans, Peter, Pocklington, Andrew J, Escott-Price, Valentina, Ripke, Stephan, Carrera, Noa, Legge, Sophie E, Bishop, Sophie, Cameron, Darren, Hamshere, Marian L, Han, Jun, Hubbard, Leon, Lynham, Amy, Mantripragada, Kiran, Rees, Elliott, MacCabe, James H, McCarroll, Steven A, Baune, Bernhard T, Breen, Gerome, Byrne, Enda M, Dannlowski, Udo, Eley, Thalia C, Hayward, Caroline, Martin, Nicholas G, McIntosh, Andrew M, Plomin, Robert, Porteous, David J, Wray, Naomi R, Caballero, Armando, Geschwind, Daniel H, Huckins, Laura M, Ruderfer, Douglas M, Santiago, Enrique, Sklar, Pamela, Stahl, Eli A, Won, Hyejung, Agerbo, Esben, Als, Thomas D, Andreassen, Ole A, Bækvad-Hansen, Marie, Mortensen, Preben Bo, Pedersen, Carsten Bøcker, Børglum, Anders D, Bybjerg-Grauholm, Jonas, Djurovic, Srdjan, Durmishi, Naser, Pedersen, Marianne Giørtz, Golimbet, Vera, Grove, Jakob, Hougaard, David M, Mattheisen, Manuel, Molden, Espen, Mors, Ole, Nordentoft, Merete, Pejovic-Milovancevic, Milica, Sigurdsson, Engilbert, Silagadze, Teimuraz, Hansen, Christine Søholm, Stefansson, Kari, Stefansson, Hreinn, Steinberg, Stacy, Tosato, Sarah, Werge, Thomas, Collier, David A, Rujescu, Dan, Kirov, George, Owen, Michael J, O’Donovan, Michael C, and Walters, James TR

Subjects
GERAD1 Consortium, CRESTAR Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019

29. Genetic analyses of diverse populations improves discovery for complex traits.

Author

Wojcik, Genevieve L, Graff, Mariaelisa, Nishimura, Katherine K, Tao, Ran, Haessler, Jeffrey, Gignoux, Christopher R, Highland, Heather M, Patel, Yesha M, Sorokin, Elena P, Avery, Christy L, Belbin, Gillian M, Bien, Stephanie A, Cheng, Iona, Cullina, Sinead, Hodonsky, Chani J, Hu, Yao, Huckins, Laura M, Jeff, Janina, Justice, Anne E, Kocarnik, Jonathan M, Lim, Unhee, Lin, Bridget M, Lu, Yingchang, Nelson, Sarah C, Park, Sung-Shim L, Poisner, Hannah, Preuss, Michael H, Richard, Melissa A, Schurmann, Claudia, Setiawan, Veronica W, Sockell, Alexandra, Vahi, Karan, Verbanck, Marie, Vishnu, Abhishek, Walker, Ryan W, Young, Kristin L, Zubair, Niha, Acuña-Alonso, Victor, Ambite, Jose Luis, Barnes, Kathleen C, Boerwinkle, Eric, Bottinger, Erwin P, Bustamante, Carlos D, Caberto, Christian, Canizales-Quinteros, Samuel, Conomos, Matthew P, Deelman, Ewa, Do, Ron, Doheny, Kimberly, Fernández-Rhodes, Lindsay, Fornage, Myriam, Hailu, Benyam, Heiss, Gerardo, Henn, Brenna M, Hindorff, Lucia A, Jackson, Rebecca D, Laurie, Cecelia A, Laurie, Cathy C, Li, Yuqing, Lin, Dan-Yu, Moreno-Estrada, Andres, Nadkarni, Girish, Norman, Paul J, Pooler, Loreall C, Reiner, Alexander P, Romm, Jane, Sabatti, Chiara, Sandoval, Karla, Sheng, Xin, Stahl, Eli A, Stram, Daniel O, Thornton, Timothy A, Wassel, Christina L, Wilkens, Lynne R, Winkler, Cheryl A, Yoneyama, Sachi, Buyske, Steven, Haiman, Christopher A, Kooperberg, Charles, Le Marchand, Loic, Loos, Ruth JF, Matise, Tara C, North, Kari E, Peters, Ulrike, Kenny, Eimear E, and Carlson, Christopher S

Subjects
Humans, Body Height, Cohort Studies, Genetics, Medical, Multifactorial Inheritance, Minority Groups, African Continental Ancestry Group, Asian Continental Ancestry Group, Hispanic Americans, Women's Health, United States, Female, Male, Health Status Disparities, Genome-Wide Association Study, Health Equity, Genetics, Medical, General Science & Technology
Abstract

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions13-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.

Published
2019

30. Publisher Correction: Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Author

Huckins, Laura M, Dobbyn, Amanda, Ruderfer, Douglas M, Hoffman, Gabriel, Wang, Weiqing, Pardiñas, Antonio F, Rajagopal, Veera M, Als, Thomas D, T. Nguyen, Hoang, Girdhar, Kiran, Boocock, James, Roussos, Panos, Fromer, Menachem, Kramer, Robin, Domenici, Enrico, Gamazon, Eric R, Purcell, Shaun, Demontis, Ditte, Børglum, Anders D, Walters, James TR, O’Donovan, Michael C, Sullivan, Patrick, Owen, Michael J, Devlin, Bernie, Sieberts, Solveig K, Cox, Nancy J, Im, Hae Kyung, Sklar, Pamela, and Stahl, Eli A

Subjects
Genetics, Neurosciences, Human Genome, Serious Mental Illness, Schizophrenia, Brain Disorders, Mental Health, Biotechnology, Mental health, CommonMind Consortium, Schizophrenia Working Group of the Psychiatric Genomics Consortium, iPSYCH-GEMS Schizophrenia Working Group, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

In the HTML version of the article originally published, the author group 'The Schizophrenia Working Group of the Psychiatric Genomics Consortium' was displayed incorrectly. The error has been corrected in the HTML version of the article.

Published
2019

31. Genome-wide association study identifies 30 loci associated with bipolar disorder

Author

Stahl, Eli A, Breen, Gerome, Forstner, Andreas J, McQuillin, Andrew, Ripke, Stephan, Trubetskoy, Vassily, Mattheisen, Manuel, Wang, Yunpeng, Coleman, Jonathan RI, Gaspar, Héléna A, de Leeuw, Christiaan A, Steinberg, Stacy, Pavlides, Jennifer M Whitehead, Trzaskowski, Maciej, Byrne, Enda M, Pers, Tune H, Holmans, Peter A, Richards, Alexander L, Abbott, Liam, Agerbo, Esben, Akil, Huda, Albani, Diego, Alliey-Rodriguez, Ney, Als, Thomas D, Anjorin, Adebayo, Antilla, Verneri, Awasthi, Swapnil, Badner, Judith A, Bækvad-Hansen, Marie, Barchas, Jack D, Bass, Nicholas, Bauer, Michael, Belliveau, Richard, Bergen, Sarah E, Pedersen, Carsten Bøcker, Bøen, Erlend, Boks, Marco P, Boocock, James, Budde, Monika, Bunney, William, Burmeister, Margit, Bybjerg-Grauholm, Jonas, Byerley, William, Casas, Miquel, Cerrato, Felecia, Cervantes, Pablo, Chambert, Kimberly, Charney, Alexander W, Chen, Danfeng, Churchhouse, Claire, Clarke, Toni-Kim, Coryell, William, Craig, David W, Cruceanu, Cristiana, Curtis, David, Czerski, Piotr M, Dale, Anders M, de Jong, Simone, Degenhardt, Franziska, Del-Favero, Jurgen, DePaulo, J Raymond, Djurovic, Srdjan, Dobbyn, Amanda L, Dumont, Ashley, Elvsåshagen, Torbjørn, Escott-Price, Valentina, Fan, Chun Chieh, Fischer, Sascha B, Flickinger, Matthew, Foroud, Tatiana M, Forty, Liz, Frank, Josef, Fraser, Christine, Freimer, Nelson B, Frisén, Louise, Gade, Katrin, Gage, Diane, Garnham, Julie, Giambartolomei, Claudia, Pedersen, Marianne Giørtz, Goldstein, Jaqueline, Gordon, Scott D, Gordon-Smith, Katherine, Green, Elaine K, Green, Melissa J, Greenwood, Tiffany A, Grove, Jakob, Guan, Weihua, Guzman-Parra, José, Hamshere, Marian L, Hautzinger, Martin, Heilbronner, Urs, Herms, Stefan, Hipolito, Maria, Hoffmann, Per, Holland, Dominic, Huckins, Laura, Jamain, Stéphane, Johnson, Jessica S, and Juréus, Anders

Subjects
Biological Sciences, Genetics, Serious Mental Illness, Mental Health, Human Genome, Brain Disorders, Schizophrenia, Aetiology, 2.1 Biological and endogenous factors, Mental health, Bipolar Disorder, Case-Control Studies, Depressive Disorder, Major, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Polymorphism, Single Nucleotide, Psychotic Disorders, Systems Biology, eQTLGen Consortium, BIOS Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P

Published
2019

32. Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Author

Huckins, Laura M, Dobbyn, Amanda, Ruderfer, Douglas M, Hoffman, Gabriel, Wang, Weiqing, Pardiñas, Antonio F, Rajagopal, Veera M, Als, Thomas D, T. Nguyen, Hoang, Girdhar, Kiran, Boocock, James, Roussos, Panos, Fromer, Menachem, Kramer, Robin, Domenici, Enrico, Gamazon, Eric R, Purcell, Shaun, Demontis, Ditte, Børglum, Anders D, Walters, James TR, O’Donovan, Michael C, Sullivan, Patrick, Owen, Michael J, Devlin, Bernie, Sieberts, Solveig K, Cox, Nancy J, Im, Hae Kyung, Sklar, Pamela, and Stahl, Eli A

Subjects
Biological Sciences, Genetics, Mental Health, Brain Disorders, Human Genome, Schizophrenia, 2.1 Biological and endogenous factors, Aetiology, Mental health, Brain, Case-Control Studies, Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk, Transcriptome, CommonMind Consortium, Schizophrenia Working Group of the Psychiatric Genomics Consortium, iPSYCH-GEMS Schizophrenia Working Group, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

Published
2019

35. Altered gene expression and PTSD symptom dimensions in World Trade Center responders

Author

Marchese, Shelby, Cancelmo, Leo, Diab, Olivia, Cahn, Leah, Aaronson, Cindy, Daskalakis, Nikolaos P., Schaffer, Jamie, Horn, Sarah R., Johnson, Jessica S., Schechter, Clyde, Desarnaud, Frank, Bierer, Linda M., Makotkine, Iouri, Flory, Janine D., Crane, Michael, Moline, Jacqueline M., Udasin, Iris G., Harrison, Denise J., Roussos, Panos, Charney, Dennis S., Koenen, Karestan C., Southwick, Steven M., Yehuda, Rachel, Pietrzak, Robert H., Huckins, Laura M., and Feder, Adriana

Published
2022
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37. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection

Author

Pardiñas, Antonio F, Holmans, Peter, Pocklington, Andrew J, Escott-Price, Valentina, Ripke, Stephan, Carrera, Noa, Legge, Sophie E, Bishop, Sophie, Cameron, Darren, Hamshere, Marian L, Han, Jun, Hubbard, Leon, Lynham, Amy, Mantripragada, Kiran, Rees, Elliott, MacCabe, James H, McCarroll, Steven A, Baune, Bernhard T, Breen, Gerome, Byrne, Enda M, Dannlowski, Udo, Eley, Thalia C, Hayward, Caroline, Martin, Nicholas G, McIntosh, Andrew M, Plomin, Robert, Porteous, David J, Wray, Naomi R, Caballero, Armando, Geschwind, Daniel H, Huckins, Laura M, Ruderfer, Douglas M, Santiago, Enrique, Sklar, Pamela, Stahl, Eli A, Won, Hyejung, Agerbo, Esben, Als, Thomas D, Andreassen, Ole A, Bækvad-Hansen, Marie, Mortensen, Preben Bo, Pedersen, Carsten Bøcker, Børglum, Anders D, Bybjerg-Grauholm, Jonas, Djurovic, Srdjan, Durmishi, Naser, Pedersen, Marianne Giørtz, Golimbet, Vera, Grove, Jakob, Hougaard, David M, Mattheisen, Manuel, Molden, Espen, Mors, Ole, Nordentoft, Merete, Pejovic-Milovancevic, Milica, Sigurdsson, Engilbert, Silagadze, Teimuraz, Hansen, Christine Søholm, Stefansson, Kari, Stefansson, Hreinn, Steinberg, Stacy, Tosato, Sarah, Werge, Thomas, GERAD1 Consortium, CRESTAR Consortium, Collier, David A, Rujescu, Dan, Kirov, George, Owen, Michael J, O’Donovan, Michael C, and Walters, James TR

Subjects
Serious Mental Illness, Brain Disorders, Human Genome, Genetics, Mental Health, Biotechnology, Schizophrenia, 2.1 Biological and endogenous factors, Aetiology, Mental health, Good Health and Well Being, Alleles, Case-Control Studies, Gene Frequency, Genes, Lethal, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Inheritance Patterns, Polymorphism, Single Nucleotide, Selection, Genetic, GERAD1 Consortium, CRESTAR Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide insights. We report a new genome-wide association study of schizophrenia (11,260 cases and 24,542 controls), and through meta-analysis with existing data we identify 50 novel associated loci and 145 loci in total. Through integrating genomic fine-mapping with brain expression and chromosome conformation data, we identify candidate causal genes within 33 loci. We also show for the first time that the common variant association signal is highly enriched among genes that are under strong selective pressures. These findings provide new insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation-intolerant genes and suggest a mechanism by which common risk variants persist in the population.

Published
2018

40. List of contributors

Author

Al-Chalabi, Nzaar, primary, Andreassen, Ole A., additional, Baron, David, additional, Blum, Kenneth, additional, Bowirrat, Abdalla, additional, Brady, Philip, additional, Brewer, Raymond, additional, Cadet, Jean Lud, additional, Corvin, Aiden, additional, Cote, Alanna, additional, De Luca, Vincenzo, additional, Deckert, Jürgen, additional, Diehl, Caroline K., additional, Dolžan, Vita, additional, Erhardt, Angelika, additional, Fatemi, Ali Bani, additional, Febo, Marcelo, additional, Ferrera, Alessandra G., additional, Frei, Oleksandr, additional, Gold, Mark S., additional, Goldberg, Joseph F., additional, Heron, Elizabeth A., additional, Hindley, Guy, additional, Huckins, Laura M., additional, Igblom, Amarachukwu, additional, Juki, Marin M., additional, K. Davis, Lea, additional, Kiri Dennis, Jessica, additional, Kong, Camillia, additional, Kores Plesničar, Blanka, additional, Mattheisen, Manuel, additional, Miller, Gregory A., additional, Mishrekar, Asmita, additional, Nemeroff, Charles B., additional, Nurnberger, John I., additional, Ormond, Cathal, additional, O’Connell, Kevin S., additional, Pisanu, Claudia, additional, Qian, Jessica, additional, Ramoz, Nicolas, additional, Rockstroh, Brigitte, additional, Ryan, Niamh M., additional, Samsom, James N., additional, Shadrin, Alexey, additional, Smeland, Olav B., additional, Squassina, Alessio, additional, Terzi, Tea, additional, Thanos, Panayotis K., additional, Tsermpini, Evangelia Eirini, additional, Wang, Yin, additional, Wang, Yunpeng, additional, Wong, Albert H.C., additional, Yee, Cindy M., additional, Young, Hannah, additional, and Zhou, Young, additional

Published
2022
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41. Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder

Author

Nievergelt, Caroline M., Maihofer, Adam X., Atkinson, Elizabeth G., Chen, Chia Yen, Choi, Karmel W., Coleman, Jonathan R.I., Daskalakis, Nikolaos P., Duncan, Laramie E., Polimanti, Renato, Aaronson, Cindy, Amstadter, Ananda B., Andersen, Soren B., Andreassen, Ole A., Arbisi, Paul A., Ashley-Koch, Allison E., Austin, S. Bryn, Avdibegoviç, Esmina, Babić, Dragan, Bacanu, Silviu Alin, Baker, Dewleen G., Batzler, Anthony, Beckham, Jean C., Belangero, Sintia, Benjet, Corina, Bergner, Carisa, Bierer, Linda M., Biernacka, Joanna M., Bierut, Laura J., Bisson, Jonathan I., Boks, Marco P., Bolger, Elizabeth A., Brandolino, Amber, Breen, Gerome, Bressan, Rodrigo Affonseca, Bryant, Richard A., Bustamante, Angela C., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Børglum, Anders D., Børte, Sigrid, Cahn, Leah, Calabrese, Joseph R., Caldas-de-Almeida, Jose Miguel, Chatzinakos, Chris, Cheema, Sheraz, Clouston, Sean A.P., Colodro-Conde, Lucía, Coombes, Brandon J., Cruz-Fuentes, Carlos S., Dale, Anders M., Dalvie, Shareefa, Davis, Lea K., Deckert, Jürgen, Delahanty, Douglas L., Dennis, Michelle F., Desarnaud, Frank, DiPietro, Christopher P., Disner, Seth G., Docherty, Anna R., Domschke, Katharina, Dyb, Grete, Kulenović, Alma Džubur, Edenberg, Howard J., Evans, Alexandra, Fabbri, Chiara, Fani, Negar, Farrer, Lindsay A., Feder, Adriana, Feeny, Norah C., Flory, Janine D., Forbes, David, Franz, Carol E., Galea, Sandro, Garrett, Melanie E., Gelaye, Bizu, Gelernter, Joel, Geuze, Elbert, Gillespie, Charles F., Goleva, Slavina B., Gordon, Scott D., Goçi, Aferdita, Grasser, Lana Ruvolo, Guindalini, Camila, Haas, Magali, Hagenaars, Saskia, Hauser, Michael A., Heath, Andrew C., Hemmings, Sian M.J., Hesselbrock, Victor, Hickie, Ian B., Hogan, Kelleigh, Hougaard, David Michael, Huang, Hailiang, Huckins, Laura M., Hveem, Kristian, Jakovljević, Miro, Javanbakht, Arash, Jenkins, Gregory D., Johnson, Jessica, Jones, Ian, Jovanovic, Tanja, Karstoft, Karen Inge, Kaufman, Milissa L., Kennedy, James L., Kessler, Ronald C., Khan, Alaptagin, Kimbrel, Nathan A., King, Anthony P., Koen, Nastassja, Kotov, Roman, Kranzler, Henry R., Krebs, Kristi, Kremen, William S., Kuan, Pei Fen, Lawford, Bruce R., Lebois, Lauren A.M., Lehto, Kelli, Levey, Daniel F., Lewis, Catrin, Liberzon, Israel, Linnstaedt, Sarah D., Logue, Mark W., Lori, Adriana, Lu, Yi, Luft, Benjamin J., Lupton, Michelle K., Luykx, Jurjen J., Makotkine, Iouri, Maples-Keller, Jessica L., Marchese, Shelby, Marmar, Charles, Martin, Nicholas G., Martínez-Levy, Gabriela A., McAloney, Kerrie, McFarlane, Alexander, McLaughlin, Katie A., McLean, Samuel A., Medland, Sarah E., Mehta, Divya, Meyers, Jacquelyn, Michopoulos, Vasiliki, Mikita, Elizabeth A., Milani, Lili, Milberg, William, Miller, Mark W., Morey, Rajendra A., Morris, Charles Phillip, Mors, Ole, Mortensen, Preben Bo, Mufford, Mary S., Nelson, Elliot C., Nordentoft, Merete, Norman, Sonya B., Nugent, Nicole R., O’Donnell, Meaghan, Orcutt, Holly K., Pan, Pedro M., Panizzon, Matthew S., Pathak, Gita A., Peters, Edward S., Peterson, Alan L., Peverill, Matthew, Pietrzak, Robert H., Polusny, Melissa A., Porjesz, Bernice, Powers, Abigail, Qin, Xue Jun, Ratanatharathorn, Andrew, Risbrough, Victoria B., Roberts, Andrea L., Rothbaum, Alex O., Rothbaum, Barbara O., Roy-Byrne, Peter, Ruggiero, Kenneth J., Rung, Ariane, Runz, Heiko, Rutten, Bart P.F., de Viteri, Stacey Saenz, Salum, Giovanni Abrahão, Sampson, Laura, Sanchez, Sixto E., Santoro, Marcos, Seah, Carina, Seedat, Soraya, Seng, Julia S., Shabalin, Andrey, Sheerin, Christina M., Silove, Derrick, Smith, Alicia K., Smoller, Jordan W., Sponheim, Scott R., Stein, Dan J., Stensland, Synne, Stevens, Jennifer S., Sumner, Jennifer A., Teicher, Martin H., Thompson, Wesley K., Tiwari, Arun K., Trapido, Edward, Uddin, Monica, Ursano, Robert J., Valdimarsdóttir, Unnur, Van Hooff, Miranda, Vermetten, Eric, Vinkers, Christiaan H., Voisey, Joanne, Wang, Yunpeng, Wang, Zhewu, Waszczuk, Monika, Weber, Heike, Wendt, Frank R., Werge, Thomas, Williams, Michelle A., Williamson, Douglas E., Winsvold, Bendik S., Winternitz, Sherry, Wolf, Christiane, Wolf, Erika J., Xia, Yan, Xiong, Ying, Yehuda, Rachel, Young, Keith A., Young, Ross Mc D., Zai, Clement C., Zai, Gwyneth C., Zervas, Mark, Zhao, Hongyu, Zoellner, Lori A., Zwart, John Anker, deRoon-Cassini, Terri, van Rooij, Sanne J.H., van den Heuvel, Leigh L., Stein, Murray B., Ressler, Kerry J., Koenen, Karestan C., Nievergelt, Caroline M., Maihofer, Adam X., Atkinson, Elizabeth G., Chen, Chia Yen, Choi, Karmel W., Coleman, Jonathan R.I., Daskalakis, Nikolaos P., Duncan, Laramie E., Polimanti, Renato, Aaronson, Cindy, Amstadter, Ananda B., Andersen, Soren B., Andreassen, Ole A., Arbisi, Paul A., Ashley-Koch, Allison E., Austin, S. Bryn, Avdibegoviç, Esmina, Babić, Dragan, Bacanu, Silviu Alin, Baker, Dewleen G., Batzler, Anthony, Beckham, Jean C., Belangero, Sintia, Benjet, Corina, Bergner, Carisa, Bierer, Linda M., Biernacka, Joanna M., Bierut, Laura J., Bisson, Jonathan I., Boks, Marco P., Bolger, Elizabeth A., Brandolino, Amber, Breen, Gerome, Bressan, Rodrigo Affonseca, Bryant, Richard A., Bustamante, Angela C., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Børglum, Anders D., Børte, Sigrid, Cahn, Leah, Calabrese, Joseph R., Caldas-de-Almeida, Jose Miguel, Chatzinakos, Chris, Cheema, Sheraz, Clouston, Sean A.P., Colodro-Conde, Lucía, Coombes, Brandon J., Cruz-Fuentes, Carlos S., Dale, Anders M., Dalvie, Shareefa, Davis, Lea K., Deckert, Jürgen, Delahanty, Douglas L., Dennis, Michelle F., Desarnaud, Frank, DiPietro, Christopher P., Disner, Seth G., Docherty, Anna R., Domschke, Katharina, Dyb, Grete, Kulenović, Alma Džubur, Edenberg, Howard J., Evans, Alexandra, Fabbri, Chiara, Fani, Negar, Farrer, Lindsay A., Feder, Adriana, Feeny, Norah C., Flory, Janine D., Forbes, David, Franz, Carol E., Galea, Sandro, Garrett, Melanie E., Gelaye, Bizu, Gelernter, Joel, Geuze, Elbert, Gillespie, Charles F., Goleva, Slavina B., Gordon, Scott D., Goçi, Aferdita, Grasser, Lana Ruvolo, Guindalini, Camila, Haas, Magali, Hagenaars, Saskia, Hauser, Michael A., Heath, Andrew C., Hemmings, Sian M.J., Hesselbrock, Victor, Hickie, Ian B., Hogan, Kelleigh, Hougaard, David Michael, Huang, Hailiang, Huckins, Laura M., Hveem, Kristian, Jakovljević, Miro, Javanbakht, Arash, Jenkins, Gregory D., Johnson, Jessica, Jones, Ian, Jovanovic, Tanja, Karstoft, Karen Inge, Kaufman, Milissa L., Kennedy, James L., Kessler, Ronald C., Khan, Alaptagin, Kimbrel, Nathan A., King, Anthony P., Koen, Nastassja, Kotov, Roman, Kranzler, Henry R., Krebs, Kristi, Kremen, William S., Kuan, Pei Fen, Lawford, Bruce R., Lebois, Lauren A.M., Lehto, Kelli, Levey, Daniel F., Lewis, Catrin, Liberzon, Israel, Linnstaedt, Sarah D., Logue, Mark W., Lori, Adriana, Lu, Yi, Luft, Benjamin J., Lupton, Michelle K., Luykx, Jurjen J., Makotkine, Iouri, Maples-Keller, Jessica L., Marchese, Shelby, Marmar, Charles, Martin, Nicholas G., Martínez-Levy, Gabriela A., McAloney, Kerrie, McFarlane, Alexander, McLaughlin, Katie A., McLean, Samuel A., Medland, Sarah E., Mehta, Divya, Meyers, Jacquelyn, Michopoulos, Vasiliki, Mikita, Elizabeth A., Milani, Lili, Milberg, William, Miller, Mark W., Morey, Rajendra A., Morris, Charles Phillip, Mors, Ole, Mortensen, Preben Bo, Mufford, Mary S., Nelson, Elliot C., Nordentoft, Merete, Norman, Sonya B., Nugent, Nicole R., O’Donnell, Meaghan, Orcutt, Holly K., Pan, Pedro M., Panizzon, Matthew S., Pathak, Gita A., Peters, Edward S., Peterson, Alan L., Peverill, Matthew, Pietrzak, Robert H., Polusny, Melissa A., Porjesz, Bernice, Powers, Abigail, Qin, Xue Jun, Ratanatharathorn, Andrew, Risbrough, Victoria B., Roberts, Andrea L., Rothbaum, Alex O., Rothbaum, Barbara O., Roy-Byrne, Peter, Ruggiero, Kenneth J., Rung, Ariane, Runz, Heiko, Rutten, Bart P.F., de Viteri, Stacey Saenz, Salum, Giovanni Abrahão, Sampson, Laura, Sanchez, Sixto E., Santoro, Marcos, Seah, Carina, Seedat, Soraya, Seng, Julia S., Shabalin, Andrey, Sheerin, Christina M., Silove, Derrick, Smith, Alicia K., Smoller, Jordan W., Sponheim, Scott R., Stein, Dan J., Stensland, Synne, Stevens, Jennifer S., Sumner, Jennifer A., Teicher, Martin H., Thompson, Wesley K., Tiwari, Arun K., Trapido, Edward, Uddin, Monica, Ursano, Robert J., Valdimarsdóttir, Unnur, Van Hooff, Miranda, Vermetten, Eric, Vinkers, Christiaan H., Voisey, Joanne, Wang, Yunpeng, Wang, Zhewu, Waszczuk, Monika, Weber, Heike, Wendt, Frank R., Werge, Thomas, Williams, Michelle A., Williamson, Douglas E., Winsvold, Bendik S., Winternitz, Sherry, Wolf, Christiane, Wolf, Erika J., Xia, Yan, Xiong, Ying, Yehuda, Rachel, Young, Keith A., Young, Ross Mc D., Zai, Clement C., Zai, Gwyneth C., Zervas, Mark, Zhao, Hongyu, Zoellner, Lori A., Zwart, John Anker, deRoon-Cassini, Terri, van Rooij, Sanne J.H., van den Heuvel, Leigh L., Stein, Murray B., Ressler, Kerry J., and Koenen, Karestan C.

Abstract

Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation., Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

Published
2024

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

Author

Byrne, Enda M., Forstner, Andreas J., Holmans, Peter A., de Leeuw, Christiaan A., Mattheisen, Manuel, McQuillin, Andrew, Whitehead Pavlides, Jennifer M., Pers, Tune H., Ripke, Stephan, Stahl, Eli A., Steinberg, Stacy, Trubetskoy, Vassily, Trzaskowski, Maciej, Wang, Yunpeng, Abbott, Liam, Abdellaoui, Abdel, Adams, Mark J., Adolfsson, Annelie Nordin, Agerbo, Esben, Akil, Huda, Albani, Diego, Alliey-Rodriguez, Ney, Als, Thomas D., Andlauer, Till F.M., Anjorin, Adebayo, Antilla, Verneri, Van der Auwera, Sandra, Awasthi, Swapnil, Bacanu, Silviu-Alin, Badner, Judith A., Bækvad-Hansen, Marie, Barchas, Jack D., Bass, Nicholas, Bauer, Michael, Beekman, Aartjan T.F., Belliveau, Richard, Bergen, Sarah E., Bigdeli, Tim B., Binder, Elisabeth B., Bøen, Erlend, Boks, Marco, Boocock, James, Budde, Monika, Bunney, William, Burmeister, Margit, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Byerley, William, Cai, Na, Casas, Miquel, Castelao, Enrique, Cerrato, Felecia, Cervantes, Pablo, Chambert, Kimberly, Charney, Alexander W., Chen, Danfeng, Christensen, Jane Hvarregaard, Churchhouse, Claire, St Clair, David, Clarke, Toni-Kim, Colodro-Conde, Lucía, Coryell, William, Couvy-Duchesne, Baptiste, Craig, David W., Crawford, Gregory E., Cruceanu, Cristiana, Czerski, Piotr M., Dale, Anders M., Davies, Gail, Deary, Ian J., Degenhardt, Franziska, Del-Favero, Jurgen, DePaulo, J Raymond, Derks, Eske M., Direk, Nese, Djurovic, Srdjan, Dobbyn, Amanda L., Dolan, Conor V., Dumont, Ashley, Dunn, Erin C., Eley, Thalia C., Elvsåshagen, Torbjørn, Escott-Price, Valentina, Fan, Chun Chieh, Finucane, Hilary K., Fischer, Sascha B., Flickinger, Matthew, Foo, Jerome C., Foroud, Tatiana M., Forty, Liz, Frank, Josef, Fraser, Christine, Freimer, Nelson B., Frisén, Louise, Gade, Katrin, Gage, Diane, Garnham, Julie, Giambartolomei, Claudia, Goes, Fernando S., Goldstein, Jaqueline, Gordon, Scott D., Gordon-Smith, Katherine, Green, Elaine K., Green, Melissa J., Greenwood, Tiffany A., Grove, Jakob, Guan, Weihua, Hall, Lynsey S., Hamshere, Marian L., Hansen, Christine Søholm, Hansen, Thomas F., Hautzinger, Martin, Heilbronner, Urs, van Hemert, Albert M., Herms, Stefan, Hickie, Ian B., Hipolito, Maria, Hoffmann, Per, Holland, Dominic, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Huckins, Laura, Ising, Marcus, Jamain, Stéphane, Jansen, Rick, Johnson, Jessica S., de Jong, Simone, Jorgenson, Eric, Juréus, Anders, Kandaswamy, Radhika, Karlsson, Robert, Kennedy, James L., Hassan Kiadeh, Farnush Farhadi, Kittel-Schneider, Sarah, Knowles, James A., Kogevinas, Manolis, Kohane, Isaac S., Koller, Anna C., Kraft, Julia, Kretzschmar, Warren W., Krogh, Jesper, Kupka, Ralph, Kutalik, Zoltán, Lavebratt, Catharina, Lawrence, Jacob, Lawson, William B., Leber, Markus, Lee, Phil H., Levy, Shawn E., Li, Jun Z., Li, Yihan, Lind, Penelope A., Liu, Chunyu, Olde Loohuis, Loes M., Maaser, Anna, MacIntyre, Donald J., MacKinnon, Dean F., Mahon, Pamela B., Maier, Wolfgang, Maier, Robert M., Marchini, Jonathan, Martinsson, Lina, Mbarek, Hamdi, McCarroll, Steve, McGrath, Patrick, McGuffin, Peter, McInnis, Melvin G., McKay, James D., Medeiros, Helena, Medland, Sarah E., Mehta, Divya, Meng, Fan, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Mirza, Saira Saeed, Mondimore, Francis M., Montgomery, Grant W., Morris, Derek W., Mostafavi, Sara, Mühleisen, Thomas W., Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nguyen, Hoang, Nievergelt, Caroline M., Nivard, Michel G., Nwulia, Evaristus A., Nyholt, Dale R., O'Donovan, Claire, O'Reilly, Paul F., Ori, Anil P.S., Oruc, Lilijana, Ösby, Urban, Oskarsson, Hogni, Painter, Jodie N., Parra, José Guzman, Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Perry, Amy, Peterson, Roseann E., Pettersson, Erik, Peyrot, Wouter J., Pfennig, Andrea, Pistis, Giorgio, Purcell, Shaun M., Quiroz, Jorge A., Qvist, Per, Regeer, Eline J., Reif, Andreas, Reinbold, Céline S., Rice, John P., Riley, Brien P., Rivas, Fabio, Rivera, Margarita, Roussos, Panos, Ruderfer, Douglas M., Ryu, Euijung, Sánchez-Mora, Cristina, Schatzberg, Alan F., Scheftner, William A., Schoevers, Robert, Schork, Nicholas J., Schulte, Eva C., Shehktman, Tatyana, Shen, Ling, Shi, Jianxin, Shilling, Paul D., Shyn, Stanley I., Sigurdsson, Engilbert, Slaney, Claire, Smeland, Olav B., Smit, Johannes H., Smith, Daniel J., Sobell, Janet L., Spijker, Anne T., Steffens, Michael, Strauss, John S., Streit, Fabian, Strohmaier, Jana, Szelinger, Szabolcs, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Robert C., Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Uitterlinden, André G., Umbricht, Daniel, Vedder, Helmut, Viktorin, Alexander, Visscher, Peter M., Wang, Weiqing, Watson, Stanley J., Webb, Bradley T., Weickert, Cynthia Shannon, Weickert, Thomas W., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Xu, Wei, Yang, Jian, Young, Allan H., Zandi, Peter, Zhang, Peng, Zhang, Futao, Zollner, Sebastian, Adolfsson, Rolf, Agartz, Ingrid, Alda, Martin, Arolt, Volker, Backlund, Lena, Baune, Bernhard T., Bellivier, Frank, Berger, Klaus, Berrettini, Wade H., Biernacka, Joanna M., Blackwood, Douglas H.R., Boehnke, Michael, Boomsma, Dorret I., Corvin, Aiden, Craddock, Nicholas, Daly, Mark J., Dannlowski, Udo, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Etain, Bruno, Frye, Mark, Fullerton, Janice M., Gershon, Elliot S., de Geus, E.J.C., Gill, Michael, Goes, Fernando, Grabe, Hans J., Grigoroiu-Serbanescu, Maria, Hamilton, Steven P., Hauser, Joanna, Hayward, Caroline, Heath, Andrew C., Hougaard, David M., Hultman, Christina M., Jones, Ian, Jones, Lisa A., Kahn, René S., Kendler, Kenneth S., Kirov, George, Kloiber, Stefan, Landén, Mikael, Leboyer, Marion, Lewis, Glyn, Li, Qingqin S., Lissowska, Jolanta, Lucae, Susanne, Madden, Pamela A.F., Magnusson, Patrik K., Martin, Nicholas G., Mayoral, Fermin, McElroy, Susan L., McIntosh, Andrew M., McMahon, Francis J., Melle, Ingrid, Metspalu, Andres, Mitchell, Philip B., Morken, Gunnar, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Myers, Richard M., Neale, Benjamin M., Nimgaonkar, Vishwajit, Nordentoft, Merete, Nöthen, Markus M., O'Donovan, Michael C., Oedegaard, Ketil J., Owen, Michael J., Paciga, Sara A., Pato, Carlos, Pato, Michele T., Pedersen, Nancy L., Penninx, Brenda W.J. H., Perlis, Roy H., Porteous, David J., Posthuma, Danielle, Potash, James B., Preisig, Martin, Ramos-Quiroga, Josep Antoni, Ribasés, Marta, Rietschel, Marcella, Rouleau, Guy A., Schaefer, Catherine, Schalling, Martin, Schofield, Peter R., Schulze, Thomas G., Serretti, Alessandro, Smoller, Jordan W., Stefansson, Hreinn, Stefansson, Kari, Stordal, Eystein, Tiemeier, Henning, Turecki, Gustavo, Uher, Rudolf, Vaaler, Arne E., Vieta, Eduard, Vincent, John B., Völzke, Henry, Weissman, Myrna M., Werge, Thomas, Andreassen, Ole A., Børglum, Anders D., Cichon, Sven, Edenberg, Howard J., Di Florio, Arianna, Kelsoe, John, Levinson, Douglas F., Lewis, Cathryn M., Nurnberger, John I., Ophoff, Roel A., Scott, Laura J., Sklar, Pamela, Sullivan, Patrick F., Wray, Naomi R., Coleman, Jonathan R.I., Gaspar, Héléna A., Bryois, Julien, and Breen, Gerome

Published
2020
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44. Evaluation of imputation performance of multiple reference panels in a Pakistani population

Author

Xu, Jiayi, primary, Liu, Dongjing, additional, Hassan, Arsalan, additional, Genovese, Giulio, additional, Cote, Alanna C, additional, Fennessy, Brian, additional, Cheng, Esther, additional, Charney, Alexander W., additional, Knowles, James A., additional, Ayub, Muhammad, additional, Peterson, Roseann E., additional, Bigdeli, Tim B., additional, and Huckins, Laura M, additional

Published
2023
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46. Associations Between Attention-Deficit/Hyperactivity Disorder and Various Eating Disorders: A Swedish Nationwide Population Study Using Multiple Genetically Informative Approaches

Author

Adan, Roger, Ando, Tetsuya, Baker, Jessica, Bergen, Andrew, Berrettini, Wade, Birgegård, Andreas, Boni, Claudette, Boraska Perica, Vesna, Brandt, Harry, Burghardt, Roland, Cassina, Matteo, Cesta, Carolyn, Clementi, Maurizio, Coleman, Joni, Cone, Roger, Courtet, Philippe, Crawford, Steven, Crow, Scott, Crowley, James, Danner, Unna, Davis, Oliver, de Zwaan, Martina, Dedoussis, George, Degortes, Daniela, DeSocio, Janiece, Dick, Danielle, Dikeos, Dimitris, Dmitrzak-Weglarz, Monika, Docampo, Elisa, Egberts, Karin, Ehrlich, Stefan, Escaramís, Geòrgia, Esko, Tõnu, Estivill, Xavier, Favaro, Angela, Fernández-Aranda, Fernando, Fichter, Manfred, Finan, Chris, Fischer, Krista, Föcker, Manuel, Foretova, Lenka, Forzan, Monica, Franklin, Christopher, Gaspar, Héléna, Gonidakis, Fragiskos, Gorwood, Philip, Gratacos, Monica, Guillaume, Sébastien, Guo, Yiran, Hakonarson, Hakon, Halmi, Katherine, Hatzikotoulas, Konstantinos, Hauser, Joanna, Hebebrand, Johannes, Helder, Sietske, Hendriks, Judith, Herpertz-Dahlmann, Beate, Herzog, Wolfgang, Hilliard, Christopher, Hinney, Anke, Huckins, Laura, Hudson, James, Huemer, Julia, Imgart, Hartmut, Inoko, Hidetoshi, Jiménez-Murcia, Susana, Johnson, Craig, Jordan, Jenny, Juréus, Anders, Kalsi, Gursharan, Kaminska, Debora, Kaplan, Allan, Kaprio, Jaakko, Karhunen, Leila, Karwautz, Andreas, Kas, Martien, Kaye, Walter, Kennedy, James, Kennedy, Martin, Keski-Rahkonen, Anna, Kiezebrink, Kirsty, Kim, Youl-Ri, Klump, Kelly, Knudsen, Gun Peggy, Koeleman, Bobby, Koubek, Doris, La Via, Maria, Landén, Mikael, Levitan, Robert, Li, Dong, Lichtenstein, Paul, Lilenfeld, Lisa, Lissowska, Jolanta, Magistretti, Pierre, Maj, Mario, Mannik, Katrin, Martin, Nicholas, McDevitt, Sara, McGuffin, Peter, Merl, Elisabeth, Metspalu, Andres, Meulenbelt, Ingrid, Micali, Nadia, Mitchell, James, Mitchell, Karen, Monteleone, Palmiero, Monteleone, Alessio Maria, Mortensen, Preben, Munn-Chernoff, Melissa, Nacmias, Benedetta, Nilsson, Ida, Norring, Claes, Ntalla, Ioanna, O’Toole, Julie, Pantel, Jacques, Papezova, Hana, Parker, Richard, Rabionet, Raquel, Raevuori, Anu, Rajewski, Andrzej, Ramoz, Nicolas, Rayner, N. William, Reichborn-Kjennerud, Ted, Ricca, Valdo, Ripke, Stephan, Ritschel, Franziska, Roberts, Marion, Rotondo, Alessandro, Rybakowski, Filip, Santonastaso, Paolo, Scherag, André, Schmidt, Ulrike, Schork, Nicholas, Schosser, Alexandra, Seitz, Jochen, Slachtova, Lenka, Slagboom, P. Eline, Slof-Op’t Landt, Margarita, Slopien, Agnieszka, Smith, Tosha, Sorbi, Sandro, Strengman, Eric, Strober, Michael, Sullivan, Patrick, Szatkiewicz, Jin, Szeszenia-Dabrowska, Neonila, Tachmazidou, Ioanna, Tenconi, Elena, Thornton, Laura, Tortorella, Alfonso, Tozzi, Federica, Treasure, Janet, Tsitsika, Artemis, Tziouvas, Konstantinos, van Elburg, Annemarie, van Furth, Eric, Wade, Tracey, Wagner, Gudrun, Walton, Esther, Watson, Hunna, Woodside, D. Blake, Yao, Shuyang, Yilmaz, Zeynep, Zeggini, Eleftheria, Zerwas, Stephanie, Zipfel, Stephan, Alfredsson, Lars, Andreassen, Ole, Aschauer, Harald, Barrett, Jeffrey, Bencko, Vladimir, Carlberg, Laura, Cichon, Sven, Cohen-Woods, Sarah, Dina, Christian, Ding, Bo, Espeseth, Thomas, Floyd, James, Gallinger, Steven, Gambaro, Giovanni, Giegling, Ina, Herms, Stefan, Janout, Vladimir, Julià, Antonio, Klareskog, Lars, Le Hellard, Stephanie, Leboyer, Marion, Lundervold, Astri, Marsal, Sara, Mattingsdal, Morten, Navratilova, Marie, Ophoff, Roel, Palotie, Aarno, Pinto, Dalila, Ripatti, Samuli, Rujescu, Dan, Scherer, Stephen, Scott, Laura, Sladek, Robert, Soranzo, Nicole, Southam, Lorraine, Steen, Vidar, Wichmann, H-Erich, Widen, Elisabeth, Breen, Gerome, Bulik, Cynthia, Kuja-Halkola, Ralf, Martin, Joanna, Lu, Yi, Hübel, Christopher, Almqvist, Catarina, Thornton, Laura M., Magnusson, Patrik K., Bulik, Cynthia M., and Larsson, Henrik

Published
2019
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47. Using ancestry-informative markers to identify fine structure across 15 populations of European origin

Author

Huckins, Laura M, Boraska, Vesna, Franklin, Christopher S, Floyd, James AB, Southam, Lorraine, Sullivan, Patrick F, Bulik, Cynthia M, Collier, David A, Tyler-Smith, Chris, Zeggini, Eleftheria, and Tachmazidou, Ioanna

Subjects
Biological Sciences, Genetics, Clinical Research, Human Genome, Anorexia Nervosa, Gene Frequency, Genetic Markers, Genetics, Population, Genome-Wide Association Study, Genotyping Techniques, Humans, Oligonucleotide Array Sequence Analysis, Phylogeography, Polymorphism, Single Nucleotide, Principal Component Analysis, Reproducibility of Results, Sample Size, White People, GCAN, WTCCC3, Clinical Sciences, Genetics & Heredity, Clinical sciences
Abstract

The Wellcome Trust Case Control Consortium 3 anorexia nervosa genome-wide association scan includes 2907 cases from 15 different populations of European origin genotyped on the Illumina 670K chip. We compared methods for identifying population stratification, and suggest list of markers that may help to counter this problem. It is usual to identify population structure in such studies using only common variants with minor allele frequency (MAF) >5%; we find that this may result in highly informative SNPs being discarded, and suggest that instead all SNPs with MAF >1% may be used. We established informative axes of variation identified via principal component analysis and highlight important features of the genetic structure of diverse European-descent populations, some studied for the first time at this scale. Finally, we investigated the substructure within each of these 15 populations and identified SNPs that help capture hidden stratification. This work can provide information regarding the designing and interpretation of association results in the International Consortia.

Published
2014

50. MULTI-ANCESTRY PHENOME-WIDE ASSOCIATION ANALYSES OF GENETIC LIABILITY FOR PROBLEMATIC ALCOHOL USE

Author

Kember, Rachel, primary, Johnson, Jessica, additional, Johnston, Keira J.A., additional, Lee, Hyunjoon, additional, Xu, Jiayi, additional, Davis, Lea K., additional, Smoller, Jordan W., additional, Mallard, Travis T., additional, Huckins, Laura M., additional, Sanchez-Roige, Sandra, additional, Kranzler, Henry R., additional, Gelernter, Joel, additional, and Zhou, Hang, additional

Published
2023
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