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2. Deep learning-based phenotype imputation on population-scale biobank data increases genetic discoveries.

Author

An, Ulzee, Pazokitoroudi, Ali, Alvarez, Marcus, Huang, Lianyun, Bacanu, Silviu, Schork, Andrew, Kendler, Kenneth, Pajukanta, Päivi, Flint, Jonathan, Cai, Na, Dahl, Andy, Sankararaman, Sriram, and Zaitlen, Noah

Subjects
Humans, Genome-Wide Association Study, Genotype, Biological Specimen Banks, Deep Learning, Polymorphism, Single Nucleotide, Phenotype
Abstract

Biobanks that collect deep phenotypic and genomic data across many individuals have emerged as a key resource in human genetics. However, phenotypes in biobanks are often missing across many individuals, limiting their utility. We propose AutoComplete, a deep learning-based imputation method to impute or fill-in missing phenotypes in population-scale biobank datasets. When applied to collections of phenotypes measured across ~300,000 individuals from the UK Biobank, AutoComplete substantially improved imputation accuracy over existing methods. On three traits with notable amounts of missingness, we show that AutoComplete yields imputed phenotypes that are genetically similar to the originally observed phenotypes while increasing the effective sample size by about twofold on average. Further, genome-wide association analyses on the resulting imputed phenotypes led to a substantial increase in the number of associated loci. Our results demonstrate the utility of deep learning-based phenotype imputation to increase power for genetic discoveries in existing biobank datasets.

Published
2023

3. Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder

Author

Dahl, Andrew, Thompson, Michael, An, Ulzee, Krebs, Morten, Appadurai, Vivek, Border, Richard, Bacanu, Silviu-Alin, Werge, Thomas, Flint, Jonathan, Schork, Andrew J, Sankararaman, Sriram, Kendler, Kenneth S, and Cai, Na

Subjects
Biological Sciences, Genetics, Brain Disorders, Depression, Human Genome, Biotechnology, Mental Health, Serious Mental Illness, Humans, Depressive Disorder, Major, Genetic Predisposition to Disease, Biological Specimen Banks, Genome-Wide Association Study, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each. We use phenotype imputation to integrate information across hundreds of MDD-relevant phenotypes, which significantly increases genome-wide association study (GWAS) power and polygenic risk score (PRS) prediction accuracy of the deepest available MDD phenotype in UK Biobank, LifetimeMDD. We demonstrate that imputation preserves specificity in its genetic architecture using a novel PRS-based pleiotropy metric. We further find that integration via summary statistics also enhances GWAS power and PRS predictions, but can introduce nonspecific genetic effects depending on input. Our work provides a simple and scalable approach to improve genetic studies in large biobanks by integrating shallow and deep phenotypes.

Published
2023

5. Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference

Author

Meng, Xiangrui, Navoly, Georgina, Giannakopoulou, Olga, Levey, Daniel F., Koller, Dora, Pathak, Gita A., Koen, Nastassja, Lin, Kuang, Adams, Mark J., Rentería, Miguel E., Feng, Yanzhe, Gaziano, J. Michael, Stein, Dan J., Zar, Heather J., Campbell, Megan L., van Heel, David A., Trivedi, Bhavi, Finer, Sarah, McQuillin, Andrew, Bass, Nick, Chundru, V. Kartik, Martin, Hilary C., Huang, Qin Qin, Valkovskaya, Maria, Chu, Chia-Yi, Kanjira, Susan, Kuo, Po-Hsiu, Chen, Hsi-Chung, Tsai, Shih-Jen, Liu, Yu-Li, Kendler, Kenneth S., Peterson, Roseann E., Cai, Na, Fang, Yu, Sen, Srijan, Scott, Laura J., Burmeister, Margit, Loos, Ruth J. F., Preuss, Michael H., Actkins, Ky’Era V., Davis, Lea K., Uddin, Monica, Wani, Agaz H., Wildman, Derek E., Aiello, Allison E., Ursano, Robert J., Kessler, Ronald C., Kanai, Masahiro, Okada, Yukinori, Sakaue, Saori, Rabinowitz, Jill A., Maher, Brion S., Uhl, George, Eaton, William, Cruz-Fuentes, Carlos S., Martinez-Levy, Gabriela A., Campos, Adrian I., Millwood, Iona Y., Chen, Zhengming, Li, Liming, Wassertheil-Smoller, Sylvia, Jiang, Yunxuan, Tian, Chao, Martin, Nicholas G., Mitchell, Brittany L., Byrne, Enda M., Awasthi, Swapnil, Coleman, Jonathan R. I., Ripke, Stephan, Sofer, Tamar, Walters, Robin G., McIntosh, Andrew M., Polimanti, Renato, Dunn, Erin C., Stein, Murray B., Gelernter, Joel, Lewis, Cathryn M., and Kuchenbaecker, Karoline

Published
2024
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6. Polygenic profiles define aspects of clinical heterogeneity in attention deficit hyperactivity disorder

Author

LaBianca, Sonja, Brikell, Isabell, Helenius, Dorte, Loughnan, Robert, Mefford, Joel, Palmer, Clare E., Walker, Rebecca, Gådin, Jesper R., Krebs, Morten, Appadurai, Vivek, Vaez, Morteza, Agerbo, Esben, Pedersen, Marianne Giørtz, Børglum, Anders D., Hougaard, David M., Mors, Ole, Nordentoft, Merete, Mortensen, Preben Bo, Kendler, Kenneth S., Jernigan, Terry L., Geschwind, Daniel H., Ingason, Andrés, Dahl, Andrew W., Zaitlen, Noah, Dalsgaard, Søren, Werge, Thomas M., and Schork, Andrew J.

Published
2024
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10. Cross-trait assortative mating is widespread and inflates genetic correlation estimates

Author

Border, Richard, Athanasiadis, Georgios, Buil, Alfonso, Schork, Andrew J, Cai, Na, Young, Alexander I, Werge, Thomas, Flint, Jonathan, Kendler, Kenneth S, Sankararaman, Sriram, Dahl, Andy W, and Zaitlen, Noah A

Subjects
Biological Psychology, Biological Sciences, Genetics, Psychology, Humans, Cell Communication, Multifactorial Inheritance, Phenotype, Genome-Wide Association Study, General Science & Technology
Abstract

The observation of genetic correlations between disparate human traits has been interpreted as evidence of widespread pleiotropy. Here, we introduce cross-trait assortative mating (xAM) as an alternative explanation. We observe that xAM affects many phenotypes and that phenotypic cross-mate correlation estimates are strongly associated with genetic correlation estimates (R2=74%). We demonstrate that existing xAM plausibly accounts for substantial fractions of genetic correlation estimates and that previously reported genetic correlation estimates between some pairs of psychiatric disorders are congruent with xAM alone. Finally, we provide evidence for a history of xAM at the genetic level using cross-trait even/odd chromosome polygenic score correlations. Together, our results demonstrate that previous reports have likely overestimated the true genetic similarity between many phenotypes.

Published
2022

14. Multivariate GWAS of psychiatric disorders and their cardinal symptoms reveal two dimensions of cross-cutting genetic liabilities

Author

Mallard, Travis T, Linnér, Richard Karlsson, Grotzinger, Andrew D, Sanchez-Roige, Sandra, Seidlitz, Jakob, Okbay, Aysu, de Vlaming, Ronald, Meddens, S Fleur W, Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics, Palmer, Abraham A, Davis, Lea K, Tucker-Drob, Elliot M, Kendler, Kenneth S, Keller, Matthew C, Koellinger, Philipp D, and Harden, K Paige

Subjects
Biological Psychology, Biological Sciences, Genetics, Psychology, Behavioral and Social Science, Brain Disorders, Depression, Schizophrenia, Mental Health, Human Genome, Mental Illness, Serious Mental Illness, Neurosciences, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Mental health, Good Health and Well Being, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium
Abstract

Understanding which biological pathways are specific versus general across diagnostic categories and levels of symptom severity is critical to improving nosology and treatment of psychopathology. Here, we combine transdiagnostic and dimensional approaches to genetic discovery for the first time, conducting a novel multivariate genome-wide association study of eight psychiatric symptoms and disorders broadly related to mood disturbance and psychosis. We identify two transdiagnostic genetic liabilities that distinguish between common forms of psychopathology versus rarer forms of serious mental illness. Biological annotation revealed divergent genetic architectures that differentially implicated prenatal neurodevelopment and neuronal function and regulation. These findings inform psychiatric nosology and biological models of psychopathology, as they suggest that the severity of mood and psychotic symptoms present in serious mental illness may reflect a difference in kind rather than merely in degree.

Published
2022

19. Socioeconomic position indicators and risk of alcohol-related medical conditions: A national cohort study from Sweden

Author

Edwards, Alexis C., Larsson Lönn, Sara, Chartier, Karen G., Lannoy, Séverine, Sundquist, Jan, Kendler, Kenneth S., and Sundquist, Kristina

Subjects
EPUB (Standard), Infection control, Physical instruments, Drinking of alcoholic beverages, Liability (Law), Acamprosate, Biological sciences, World Health Organization
Abstract

Background Alcohol consumption contributes to excess morbidity and mortality in part through the development of alcohol-related medical conditions (AMCs, including alcoholic cardiomyopathy, hepatitis, cirrhosis, etc.). The current study aimed to clarify the extent to which risk for these outcomes differs as a function of socioeconomic position (SEP), as discrepancies could lead to exacerbated health disparities. Methods and findings We used longitudinal Swedish national registries to estimate the individual and joint associations between 2 SEP indicators, educational attainment and income level, and risk of AMC based on International Classification of Diseases codes, while controlling for other sociodemographic covariates and psychiatric illness. We conducted Cox proportional hazards models in sex-stratified analyses (N = 1,162,679 females and N = 1,196,659 males), beginning observation at age 40 with follow-up through December 2018, death, or emigration. By the end of follow-up, 4,253 (0.37%) females and 11,183 (0.93%) males had received an AMC registration, corresponding to overall AMC incidence rates among females and males of 2.01 and 5.20, respectively. In sex-stratified models adjusted for birth year, marital status, region of origin, internalizing and externalizing disorder registrations, and alcohol use disorder (AUD) registration, lower educational attainment was associated with higher risk of AMC in both females (hazard ratios [HRs] = 1.40 to 2.46 for low- and mid-level educational attainment across 0 to 15 years of observation) and males (HRs = 1.13 to 1.48). Likewise, risk of AMC was increased for those with lower income levels (females: HRs = 1.10 to 5.86; males: HRs = 1.07 to 6.41). In secondary analyses, we further adjusted for aggregate familial risk of AUD by including family genetic risk scores for AUD (FGRS.sub.AUD ), estimated using medical, pharmacy, and criminal registries in extended families, as covariates. While FGRS.sub.AUD were associated with risk of AMC in adjusted models (HR = 1.17 for females and HR = 1.21 for males), estimates for education and income level remained largely unchanged. Furthermore, FGRS.sub.AUD interacted with income level, but not education level, such that those at higher familial liability to AUD were more susceptible to the adverse effect of low income. Limitations of these analyses include the possibility of false negatives for psychiatric illness registrations, changes in income after age 40 that were not accounted for due to modeling restrictions, restriction to residents of a high-income country, and the inability to account for individual-level alcohol consumption using registry data. Conclusions Using comprehensive national registry data, these analyses demonstrate that individuals with lower levels of education and/or income are at higher risk of developing AMC. These associations persist even when accounting for a range of sociodemographic, psychiatric, and familial risk factors. Differences in risk could contribute to further health disparities, potentially warranting increased screening and prevention efforts in clinical and public health settings., Author(s): Alexis C. Edwards 1,*, Sara Larsson Lönn 2, Karen G. Chartier 1,3, Séverine Lannoy 1, Jan Sundquist 2,4,5, Kenneth S. Kendler 1, Kristina Sundquist 2,4,5 Introduction Excessive alcohol use [...]

Published
2024
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20. Genome-wide association analyses using machine learning-based phenotyping reveal genetic architecture of occupational creativity and overlap with psychiatric disorders

Author

Kim, Hyejin, Ahn, Yeeun, Yoon, Joohyun, Jung, Kyeongmin, Kim, Soyeon, Shim, Injeong, Park, Tae Hwan, Ko, Hyunwoong, Jung, Sang-Hyuk, Kim, Jaeyoung, Park, Sanghyeon, Lee, Dong June, Choi, Sunho, Cha, Soojin, Kim, Beomsu, Cho, Min Young, Cho, Hyunbin, Kim, Dan Say, Jang, Yoonjeong, Ihm, Hong Kyu, Park, Woong-Yang, Bakhshi, Hasan, O`Connell, Kevin S., Andreassen, Ole A., Kendler, Kenneth S., Myung, Woojae, and Won, Hong-Hee

Published
2024
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24. Genome-wide analyses of smoking behaviors in schizophrenia: Findings from the Psychiatric Genomics Consortium

Author

Peterson, Roseann E, Bigdeli, Tim B, Ripke, Stephan, Bacanu, Silviu-Alin, Gejman, Pablo V, Levinson, Douglas F, Li, Qingqin S, Rujescu, Dan, Rietschel, Marcella, Weinberger, Daniel R, Straub, Richard E, Walters, James TR, Owen, Michael J, O'Donovan, Michael C, Mowry, Bryan J, Ophoff, Roel A, Andreassen, Ole A, Esko, Tõnu, Petryshen, Tracey L, Kendler, Kenneth S, Consortium, Schizophrenia Working Group of the Psychiatric Genomics, and Fanous, Ayman H

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Schizophrenia, Tobacco Smoke and Health, Substance Misuse, Prevention, Behavioral and Social Science, Biotechnology, Tobacco, Brain Disorders, Genetics, Mental Health, Serious Mental Illness, Human Genome, Mental health, Good Health and Well Being, Adult, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Membrane Proteins, Nerve Tissue Proteins, Phenotype, Polymorphism, Single Nucleotide, Smoking, GWAS, Smoking initiation, Cigarettes per day, Pleiotropy, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Clinical and health psychology
Abstract

While 17% of US adults use tobacco regularly, smoking rates among persons with schizophrenia are upwards of 60%. Research supports a shared etiological basis for smoking and schizophrenia, including findings from genome-wide association studies (GWAS). However, few studies have directly tested whether the same or distinct genetic variants also influence smoking behavior among schizophrenia cases. Using data from the Psychiatric Genomics Consortium (PGC) study of schizophrenia (35476 cases, 46839 controls), we estimated genetic correlations between these traits and tested whether polygenic risk scores (PRS) constructed from the results of smoking behaviors GWAS were associated with schizophrenia risk or smoking behaviors among schizophrenia cases. Results indicated significant genetic correlations of schizophrenia with smoking initiation (rg = 0.159; P = 5.05 × 10-10), cigarettes-smoked-per-day (rg = 0.094; P = 0.006), and age-of-onset of smoking (rg = 0.10; P = 0.009). Comparing smoking behaviors among schizophrenia cases to the general population, we observe positive genetic correlations for smoking initiation (rg = 0.624, P = 0.002) and cigarettes-smoked-per-day (rg = 0.689, P = 0.120). Similarly, TAG-based PRS for smoking initiation and cigarettes-smoked-per-day were significantly associated with smoking initiation (P = 3.49 × 10-5) and cigarettes-smoked-per-day (P = 0.007) among schizophrenia cases. We performed the first GWAS of smoking behavior among schizophrenia cases and identified a novel association with cigarettes-smoked-per-day upstream of the TMEM106B gene on chromosome 7p21.3 (rs148253479, P = 3.18 × 10-8, n = 3520). Results provide evidence of a partially shared genetic basis for schizophrenia and smoking behaviors. Additionally, genetic risk factors for smoking behaviors were largely shared across schizophrenia and non-schizophrenia populations. Future research should address mechanisms underlying these associations to aid both schizophrenia and smoking treatment and prevention efforts.

Published
2021

25. Polygenic contributions to alcohol use and alcohol use disorders across population-based and clinically ascertained samples

Author

Johnson, Emma C, Sanchez-Roige, Sandra, Acion, Laura, Adams, Mark J, Bucholz, Kathleen K, Chan, Grace, Chao, Michael J, Chorlian, David B, Dick, Danielle M, Edenberg, Howard J, Foroud, Tatiana, Hayward, Caroline, Heron, Jon, Hesselbrock, Victor, Hickman, Matthew, Kendler, Kenneth S, Kinreich, Sivan, Kramer, John, Kuo, Sally I-Chun, Kuperman, Samuel, Lai, Dongbing, McIntosh, Andrew M, Meyers, Jacquelyn L, Plawecki, Martin H, Porjesz, Bernice, Porteous, David, Schuckit, Marc A, Su, Jinni, Zang, Yong, Palmer, Abraham A, Agrawal, Arpana, Clarke, Toni-Kim, and Edwards, Alexis C

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Neurosciences, Brain Disorders, Clinical Research, Genetics, Underage Drinking, Substance Misuse, Pediatric, Alcoholism, Alcohol Use and Health, Good Health and Well Being, Alcohol Drinking, Alcoholism, Cohort Studies, Genome-Wide Association Study, Humans, Longitudinal Studies, Phenotype, Scotland, Alcohol consumption, alcohol dependence, alcohol use disorder, AUDIT, genetics, GWAS, polygenic risk score, Public Health and Health Services, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

BackgroundStudies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds.MethodsWe examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes.ResultsIn COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47-0.68%, p = 2.0 × 10-8-1.0 × 10-10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10-8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10-6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10-11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10-7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10-16).ConclusionsAUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.

Published
2021

27. Increasing the resolution and precision of psychiatric genome-wide association studies by re-imputing summary statistics using a large, diverse reference panel.

Author

Chatzinakos, Chris, Lee, Donghyung, Cai, Na, Vladimirov, Vladimir, Webb, Bradley, Riley, Brien, Flint, Jonathan, Kendler, Kenneth, Ressler, Kerry, Daskalakis, Nikolaos, and Bacanu, Silviu-Alin

Subjects
GWAS, direct imputation, genetics, summary statistcis, Cohort Studies, Gene Frequency, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Mental Disorders, Phenotype, Polymorphism, Single Nucleotide, Reference Standards, Software
Abstract

Genotype imputation across populations of mixed ancestry is critical for optimal discovery in large-scale genome-wide association studies (GWAS). Methods for direct imputation of GWAS summary-statistics were previously shown to be practically as accurate as summary statistics produced after raw genotype imputation, while incurring orders of magnitude lower computational burden. Given that direct imputation needs a precise estimation of linkage-disequilibrium (LD) and that most of the methods using a small reference panel for example, ~2,500-subject coming from the 1000 Genome-Project, there is a great need for much larger and more diverse reference panels. To accurately estimate the LD needed for an exhaustive analysis of any cosmopolitan cohort, we developed DISTMIX2. DISTMIX2: (a) uses a much larger and more diverse reference panel compared to traditional reference panels, and (b) can estimate weights of ethnic-mixture based solely on Z-scores, when allele frequencies are not available. We applied DISTMIX2 to GWAS summary-statistics from the psychiatric genetic consortium (PGC). DISTMIX2 uncovered signals in numerous new regions, with most of these findings coming from the rarer variants. Rarer variants provide much sharper location for the signals compared with common variants, as the LD for rare variants extends over a lower distance than for common ones. For example, while the original PGC post-traumatic stress disorder GWAS found only 3 marginal signals for common variants, we now uncover a very strong signal for a rare variant in PKN2, a gene associated with neuronal and hippocampal development. Thus, DISTMIX2 provides a robust and fast (re)imputation approach for most psychiatric GWAS-studies.

Published
2021

28. Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

Author

Marshall, Christian R., Merico, Daniele, Thiruvahindrapuram, Bhooma, Wang, Zhouzhi, Scherer, Stephen W., Howrigan, Daniel P, Ripke, Stephan, Bulik-Sullivan, Brendan, Farh, Kai-How, Fromer, Menachem, Goldstein, Jacqueline I., Huang, Hailiang, Lee, Phil, Daly, Mark J., Neale, Benjamin M., Belliveau, Richard A., Jr., Bergen, Sarah E., Bevilacqua, Elizabeth, Chambert, Kimberley D., O'Dushlaine, Colm, Scolnick, Edward M., Smoller, Jordan W., Moran, Jennifer L., Palotie, Aarno, Petryshen, Tracey L., Wu, Wenting, Greer, Douglas S., Antaki, Danny, Shetty, Aniket, Gujral, Madhusudan, Brandler, William M., Malhotra, Dheeraj, Fuentes Fajarado, Karin V., Maile, Michelle S., Holmans, Peter A., Carrera, Noa, Craddock, Nick, Escott-Price, Valentina, Georgieva, Lyudmila, Hamshere, Marian L., Kavanagh, David, Legge, Sophie E., Pocklington, Andrew J., Richards, Alexander L., Ruderfer, Douglas M., Williams, Nigel M., Kirov, George, Owen, Michael J., Pinto, Dalila, Cai, Guiqing, Davis, Kenneth L., Drapeau, Elodie, Friedman, Joseph I, Haroutunian, Vahram, Parkhomenko, Elena, Reichenberg, Abraham, Silverman, Jeremy M., Buxbaum, Joseph D., Domenici, Enrico, Agartz, Ingrid, Djurovic, Srdjan, Mattingsdal, Morten, Melle, Ingrid, Andreassen, Ole A., Jönsson, Erik G., Söderman, Erik, Albus, Margot, Alexander, Madeline, Laurent, Claudine, Levinson, Douglas F., Amin, Farooq, Atkins, Joshua, Cairns, Murray J., Scott, Rodney J., Tooney, Paul A., Wu, Jing Qin, Bacanu, Silviu A., Bigdeli, Tim B., Reimers, Mark A., Webb, Bradley T., Wolen, Aaron R., Wormley, Brandon K., Kendler, Kenneth S., Riley, Brien P., Kähler, Anna K., Magnusson, Patrik K.E., Hultman, Christina M., Bertalan, Marcelo, Hansen, Thomas, Olsen, Line, Rasmussen, Henrik B., Werge, Thomas, Mattheisen, Manuel, Black, Donald W., Bruggeman, Richard, Buccola, Nancy G., Buckner, Randy L., Roffman, Joshua L., Byerley, William, Cahn, Wiepke, Kahn, René S, Strengman, Eric, Ophoff, Roel A., Carr, Vaughan J., Catts, Stanley V., Henskens, Frans A., Loughland, Carmel M., Michie, Patricia T., Pantelis, Christos, Schall, Ulrich, Jablensky, Assen V., Kelly, Brian J., Campion, Dominique, Cantor, Rita M., Cheng, Wei, Cloninger, C. Robert, Svrakic, Dragan M, Cohen, David, Cormican, Paul, Donohoe, Gary, Morris, Derek W., Corvin, Aiden, Gill, Michael, Crespo-Facorro, Benedicto, Crowley, James J., Farrell, Martilias S., Giusti-Rodríguez, Paola, Kim, Yunjung, Szatkiewicz, Jin P., Williams, Stephanie, Curtis, David, Pimm, Jonathan, Gurling, Hugh, McQuillin, Andrew, Davidson, Michael, Weiser, Mark, Degenhardt, Franziska, Forstner, Andreas J., Herms, Stefan, Hoffmann, Per, Hofman, Andrea, Cichon, Sven, Nöthen, Markus M., Del Favero, Jurgen, DeLisi, Lynn E., McCarley, Robert W., Levy, Deborah L., Mesholam-Gately, Raquelle I., Seidman, Larry J., Dikeos, Dimitris, Papadimitriou, George N., Dinan, Timothy, Duan, Jubao, Sanders, Alan R., Gejman, Pablo V., Gershon, Elliot S., Dudbridge, Frank, Eichhammer, Peter, Eriksson, Johan, Salomaa, Veikko, Essioux, Laurent, Fanous, Ayman H., Knowles, James A., Pato, Michele T., Pato, Carlos N., Frank, Josef, Meier, Sandra, Schulze, Thomas G., Strohmaier, Jana, Witt, Stephanie H., Rietschel, Marcella, Franke, Lude, Karjalainen, Juha, Freedman, Robert, Olincy, Ann, Freimer, Nelson B., Purcell, Shaun M., Roussos, Panos, Stahl, Eli A., Sklar, Pamela, Giegling, Ina, Hartmann, Annette M., Konte, Bettina, Rujescu, Dan, Godard, Stephanie, Hirschhorn, Joel N., Pers, Tune H., Price, Alkes, Esko, Tõnu, Gratten, Jacob, Lee, S. Hong, Visscher, Peter M., Wray, Naomi R., Mowry, Bryan J., de Haan, Lieuwe, Meijer, Carin J., Hansen, Mark, Ikeda, Masashi, Iwata, Nakao, Joa, Inge, Kalaydjieva, Luba, Keller, Matthew C., Kennedy, James L., Zai, Clement C., Knight, Jo, Lerer, Bernard, Liang, Kung-Yee, Lieberman, Jeffrey, Stroup, T. Scott, Lönnqvist, Jouko, Suvisaari, Jaana, Maher, Brion S., Maier, Wolfgang, Mallet, Jacques, McDonald, Colm, McIntosh, Andrew M., Blackwood, Douglas H.R., Metspalu, Andres, Milani, Lili, Milanova, Vihra, Mokrab, Younes, Collier, David A., Müller-Myhsok, Bertram, Murphy, Kieran C., Murray, Robin M., Powell, John, Myin-Germeys, Inez, Van Os, Jim, Nenadic, Igor, Nertney, Deborah A., Nestadt, Gerald, Pulver, Ann E., Nicodemus, Kristin K., Nisenbaum, Laura, Nordin, Annelie, Adolfsson, Rolf, O'Callaghan, Eadbhard, Oh, Sang-Yun, O'Neill, F. Anthony, Paunio, Tiina, Pietiläinen, Olli, Perkins, Diana O., Quested, Digby, Savitz, Adam, Li, Qingqin S., Schwab, Sibylle G., Shi, Jianxin, Spencer, Chris C.A., Thirumalai, Srinivas, Veijola, Juha, Waddington, John, Walsh, Dermot, Wildenauer, Dieter B., Bramon, Elvira, Darvasi, Ariel, Posthuma, Danielle, St. Clair, David, Shanta, Omar, Klein, Marieke, Park, Peter J., Weinberger, Daniel, Moran, John V., Gage, Fred H., Vaccarino, Flora M., Gleeson, Joseph, Mathern, Gary, Courchesne, Eric, Roy, Subhojit, Bizzotto, Sara, Coulter, Michael, Dias, Caroline, D'Gama, Alissa, Ganz, Javier, Hill, Robert, Huang, August Yue, Khoshkhoo, Sattar, Kim, Sonia, Lodato, Michael, Miller, Michael, Borges-Monroy, Rebeca, Rodin, Rachel, Zhou, Zinan, Bohrson, Craig, Chu, Chong, Cortes-Ciriano, Isidro, Dou, Yanmei, Galor, Alon, Gulhan, Doga, Kwon, Minseok, Luquette, Joe, Viswanadham, Vinay, Jones, Attila, Rosenbluh, Chaggai, Cho, Sean, Langmead, Ben, Thorpe, Jeremy, Erwin, Jennifer, Jaffe, Andrew, McConnell, Michael, Narurkar, Rujuta, Paquola, Apua, Shin, Jooheon, Straub, Richard, Abyzov, Alexej, Bae, Taejeong, Jang, Yeongjun, Wang, Yifan, Gage, Fred, Linker, Sara, Reed, Patrick, Wang, Meiyan, Urban, Alexander, Zhou, Bo, Zhu, Xiaowei, Pattni, Reenal, Amero, Aitor Serres, Juan, David, Lobon, Irene, Marques-Bonet, Tomas, Moruno, Manuel Solis, Perez, Raquel Garcia, Povolotskaya, Inna, Soriano, Eduardo, Averbuj, Dan, Ball, Laurel, Breuss, Martin, Yang, Xiaoxu, Chung, Changuk, Emery, Sarah B., Flasch, Diane A., Kidd, Jeffrey M., Kopera, Huira C., Kwan, Kenneth Y., Mills, Ryan E., Moldovan, John B., Sun, Chen, Zhao, Xuefang, Zhou, Weichen, Frisbie, Trenton J., Cherskov, Adriana, Fasching, Liana, Jourdon, Alexandre, Pochareddy, Sirisha, Scuderi, Soraya, Sestan, Nenad, Maury, Eduardo A., Sherman, Maxwell A., Genovese, Giulio, Gilgenast, Thomas G., Kamath, Tushar, Burris, S.J., Rajarajan, Prashanth, Flaherty, Erin, Akbarian, Schahram, Chess, Andrew, McCarroll, Steven A., Loh, Po-Ru, Phillips-Cremins, Jennifer E., Brennand, Kristen J., Macosko, Evan Z., Walters, James T.R., O’Donovan, Michael, Sullivan, Patrick, Sebat, Jonathan, Lee, Eunjung A., and Walsh, Christopher A.

Published
2023
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29. Retraction Note: Identification of de novo mutations in prenatal neurodevelopment-associated genes in schizophrenia in two Han Chinese patient-sibling family-based cohorts.

Author

Jiang, Shan, Zhou, Daizhan, Wang, Yin-Ying, Jia, Peilin, Wan, Chunling, Li, Xingwang, He, Guang, Cao, Dongmei, Jiang, Xiaoqian, Kendler, Kenneth S, Tsuang, Ming, Mize, Travis, Wu, Jain-Shing, Lu, Yimei, He, Lin, Chen, Jingchun, Zhao, Zhongming, and Chen, Xiangning

Subjects
Clinical Sciences, Public Health and Health Services, Psychology
Abstract

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1038/s41398-020-00987-z.

Published
2020

30. A large-scale genome-wide association study meta-analysis of cannabis use disorder.

Author

Johnson, Emma C, Demontis, Ditte, Thorgeirsson, Thorgeir E, Walters, Raymond K, Polimanti, Renato, Hatoum, Alexander S, Sanchez-Roige, Sandra, Paul, Sarah E, Wendt, Frank R, Clarke, Toni-Kim, Lai, Dongbing, Reginsson, Gunnar W, Zhou, Hang, He, June, Baranger, David AA, Gudbjartsson, Daniel F, Wedow, Robbee, Adkins, Daniel E, Adkins, Amy E, Alexander, Jeffry, Bacanu, Silviu-Alin, Bigdeli, Tim B, Boden, Joseph, Brown, Sandra A, Bucholz, Kathleen K, Bybjerg-Grauholm, Jonas, Corley, Robin P, Degenhardt, Louisa, Dick, Danielle M, Domingue, Benjamin W, Fox, Louis, Goate, Alison M, Gordon, Scott D, Hack, Laura M, Hancock, Dana B, Hartz, Sarah M, Hickie, Ian B, Hougaard, David M, Krauter, Kenneth, Lind, Penelope A, McClintick, Jeanette N, McQueen, Matthew B, Meyers, Jacquelyn L, Montgomery, Grant W, Mors, Ole, Mortensen, Preben B, Nordentoft, Merete, Pearson, John F, Peterson, Roseann E, Reynolds, Maureen D, Rice, John P, Runarsdottir, Valgerdur, Saccone, Nancy L, Sherva, Richard, Silberg, Judy L, Tarter, Ralph E, Tyrfingsson, Thorarinn, Wall, Tamara L, Webb, Bradley T, Werge, Thomas, Wetherill, Leah, Wright, Margaret J, Zellers, Stephanie, Adams, Mark J, Bierut, Laura J, Boardman, Jason D, Copeland, William E, Farrer, Lindsay A, Foroud, Tatiana M, Gillespie, Nathan A, Grucza, Richard A, Harris, Kathleen Mullan, Heath, Andrew C, Hesselbrock, Victor, Hewitt, John K, Hopfer, Christian J, Horwood, John, Iacono, William G, Johnson, Eric O, Kendler, Kenneth S, Kennedy, Martin A, Kranzler, Henry R, Madden, Pamela AF, Maes, Hermine H, Maher, Brion S, Martin, Nicholas G, McGue, Matthew, McIntosh, Andrew M, Medland, Sarah E, Nelson, Elliot C, Porjesz, Bernice, Riley, Brien P, Stallings, Michael C, Vanyukov, Michael M, Vrieze, Scott, Psychiatric Genomics Consortium Substance Use Disorders Workgroup, Davis, Lea K, Bogdan, Ryan, Gelernter, Joel, and Edenberg, Howard J

Subjects
Psychiatric Genomics Consortium Substance Use Disorders Workgroup, Humans, Marijuana Abuse, Risk, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

BackgroundVariation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder.MethodsTo conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations.FindingsWe identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia.InterpretationThese findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder.FundingNational Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.

Published
2020

31. Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia

Author

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

Published
2023
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33. Identification of de novo mutations in prenatal neurodevelopment-associated genes in schizophrenia in two Han Chinese patient-sibling family-based cohorts.

Author

Jiang, Shan, Zhou, Daizhan, Wang, Yin-Ying, Jia, Peilin, Wan, Chunling, Li, Xingwang, He, Guang, Cao, Dongmei, Jiang, Xiaoqian, Kendler, Kenneth S, Tsuang, Ming, Mize, Travis, Wu, Jain-Shing, Lu, Yimei, He, Lin, Chen, Jingchun, Zhao, Zhongming, and Chen, Xiangning

Subjects
Clinical Sciences, Public Health and Health Services, Psychology
Abstract

Schizophrenia (SCZ) is a severe psychiatric disorder with a strong genetic component. High heritability of SCZ suggests a major role for transmitted genetic variants. Furthermore, SCZ is also associated with a marked reduction in fecundity, leading to the hypothesis that alleles with large effects on risk might often occur de novo. In this study, we conducted whole-genome sequencing for 23 families from two cohorts with unaffected siblings and parents. Two nonsense de novo mutations (DNMs) in GJC1 and HIST1H2AD were identified in SCZ patients. Ten genes (DPYSL2, NBPF1, SDK1, ZNF595, ZNF718, GCNT2, SNX9, AACS, KCNQ1, and MSI2) were found to carry more DNMs in SCZ patients than their unaffected siblings by burden test. Expression analyses indicated that these DNM implicated genes showed significantly higher expression in prefrontal cortex in prenatal stage. The DNM in the GJC1 gene is highly likely a loss function mutation (pLI = 0.94), leading to the dysregulation of ion channel in the glutamatergic excitatory neurons. Analysis of rare variants in independent exome sequencing dataset indicates that GJC1 has significantly more rare variants in SCZ patients than in unaffected controls. Data from genome-wide association studies suggested that common variants in the GJC1 gene may be associated with SCZ and SCZ-related traits. Genes co-expressed with GJC1 are involved in SCZ, SCZ-associated pathways, and drug targets. These evidences suggest that GJC1 may be a risk gene for SCZ and its function may be involved in prenatal and early neurodevelopment, a vulnerable period for developmental disorders such as SCZ.

Published
2020

34. Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium

Author

Polimanti, Renato, Walters, Raymond K, Johnson, Emma C, McClintick, Jeanette N, Adkins, Amy E, Adkins, Daniel E, Bacanu, Silviu-Alin, Bierut, Laura J, Bigdeli, Tim B, Brown, Sandra, Bucholz, Kathleen K, Copeland, William E, Costello, E Jane, Degenhardt, Louisa, Farrer, Lindsay A, Foroud, Tatiana M, Fox, Louis, Goate, Alison M, Grucza, Richard, Hack, Laura M, Hancock, Dana B, Hartz, Sarah M, Heath, Andrew C, Hewitt, John K, Hopfer, Christian J, Johnson, Eric O, Kendler, Kenneth S, Kranzler, Henry R, Krauter, Kenneth, Lai, Dongbing, Madden, Pamela AF, Martin, Nicholas G, Maes, Hermine H, Nelson, Elliot C, Peterson, Roseann E, Porjesz, Bernice, Riley, Brien P, Saccone, Nancy, Stallings, Michael, Wall, Tamara L, Webb, Bradley T, Wetherill, Leah, Edenberg, Howard J, Agrawal, Arpana, and Gelernter, Joel

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Drug Abuse (NIDA only), Substance Misuse, Neurosciences, Brain Disorders, Human Genome, Genetics, Mental Health, Aetiology, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Analgesics, Opioid, Behavior, Addictive, Female, Genetic Predisposition to Disease, Genetic Variation, Genome, Human, Genome-Wide Association Study, Genomics, Humans, Male, Multifactorial Inheritance, Opioid-Related Disorders, Psychiatric Genomics Consortium Substance Use Disorders Workgroup, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

To provide insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing 4503 OD cases, 4173 opioid-exposed controls, and 32,500 opioid-unexposed controls, including participants of European and African descent (EUR and AFR, respectively). Among the variants identified, rs9291211 was associated with OE (exposed vs. unexposed controls; EUR z = -5.39, p = 7.2 × 10-8). This variant regulates the transcriptomic profiles of SLC30A9 and BEND4 in multiple brain tissues and was previously associated with depression, alcohol consumption, and neuroticism. A phenome-wide scan of rs9291211 in the UK Biobank (N > 360,000) found association of this variant with propensity to use dietary supplements (p = 1.68 × 10-8). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8 (EUR + AFR z = 4.69, p = 10-6), which was previously associated with educational attainment, risk-taking behaviors, and schizophrenia. In addition, rs201123820 showed a genome-wide significant difference between OD cases and unexposed controls (AFR z = 5.55, p = 2.9 × 10-8) and a significant association with musculoskeletal disorders in the UK Biobank (p = 4.88 × 10-7). A polygenic risk score (PRS) based on a GWAS of risk-tolerance (n = 466,571) was positively associated with OD (OD vs. unexposed controls, p = 8.1 × 10-5; OD cases vs. exposed controls, p = 0.054) and OE (exposed vs. unexposed controls, p = 3.6 × 10-5). A PRS based on a GWAS of neuroticism (n = 390,278) was positively associated with OD (OD vs. unexposed controls, p = 3.2 × 10-5; OD vs. exposed controls, p = 0.002) but not with OE (p = 0.67). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls in studies of addiction.

Published
2020

35. Pathway-based polygene risk for severe depression implicates drug metabolism in CONVERGE.

Author

Docherty, Anna, Moscati, Arden, Bigdeli, Tim, Edwards, Alexis, Peterson, Roseann, Adkins, Daniel, Anderson, John, Flint, Jonathan, Kendler, Kenneth, and Bacanu, Silviu-Alin

Subjects
CONVERGE, depression, drug metabolism, genetic, polygenic, Adult, Age of Onset, Asian People, Case-Control Studies, China, Depressive Disorder, Major, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Middle Aged, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Recurrence, Risk Factors
Abstract

BACKGROUND: The Psychiatric Genomics Consortium (PGC) has made major advances in the molecular etiology of MDD, confirming that MDD is highly polygenic. Pathway enrichment results from PGC meta-analyses can also be used to help inform molecular drug targets. Prior to any knowledge of molecular biomarkers for MDD, drugs targeting molecular pathways (MPs) proved successful in treating MDD. It is possible that examining polygenicity within specific MPs implicated in MDD can further refine molecular drug targets. METHODS: Using a large case-control GWAS based on low-coverage whole genome sequencing (N = 10 640) in Han Chinese women, we derived polygenic risk scores (PRS) for MDD and for MDD specific to each of over 300 MPs previously shown to be relevant to psychiatric diagnoses. We then identified sets of PRSs, accounting for critical covariates, significantly predictive of case status. RESULTS: Over and above global MDD polygenic risk, polygenic risk within the GO: 0017144 drug metabolism pathway significantly predicted recurrent depression after multiple testing correction. Secondary transcriptomic analysis suggests that among genes in this pathway, CYP2C19 (family of Cytochrome P450) and CBR1 (Carbonyl Reductase 1) might be most relevant to MDD. Within the cases, pathway-based risk was additionally associated with age at onset of MDD. CONCLUSIONS: Results indicate that pathway-based risk might inform etiology of recurrent major depression. Future research should examine whether polygenicity of the drug metabolism gene pathway has any association with clinical presentation or treatment response. We discuss limitations to the generalizability of these preliminary findings, and urge replication in future research.

Published
2020

36. Minimal phenotyping yields genome-wide association signals of low specificity for major depression.

Author

Cai, Na, Revez, Joana, Adams, Mark, Andlauer, Till, Breen, Gerome, Byrne, Enda, Clarke, Toni-Kim, Forstner, Andreas, Grabe, Hans, Hamilton, Steven, Levinson, Douglas, Lewis, Cathryn, Lewis, Glyn, Martin, Nicholas, Milaneschi, Yuri, Mors, Ole, Müller-Myhsok, Bertram, Penninx, Brenda, Perlis, Roy, Pistis, Giorgio, Potash, James, Preisig, Martin, Shi, Jianxin, Smoller, Jordan, Streit, Fabien, Tiemeier, Henning, Uher, Rudolf, Van der Auwera, Sandra, Viktorin, Alexander, Weissman, Myrna, Kendler, Kenneth, and Flint, Jonathan

Subjects
Adult, Aged, Bipolar Disorder, Depressive Disorder, Major, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Sensitivity and Specificity
Abstract

Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD.

Published
2020

37. Retracted: Identification of de novo mutations in prenatal neurodevelopment-associated genes in schizophrenia in two Han Chinese patient-sibling family-based cohorts

Author

Jiang, Shan, Zhou, Daizhan, Wang, Yin-Ying, Jia, Peilin, Wan, Chunling, Li, Xingwang, He, Guang, Cao, Dongmei, Jiang, Xiaoqian, Kendler, Kenneth S, Tsuang, Ming, Mize, Travis, Wu, Jain-Shing, Lu, Yimei, He, Lin, Chen, Jingchun, Zhao, Zhongming, and Chen, Xiangning

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Serious Mental Illness, Brain Disorders, Neurosciences, Clinical Research, Schizophrenia, Pediatric, Human Genome, Biotechnology, Mental Health, Prevention, Genetics, Genetic Testing, 2.1 Biological and endogenous factors, Aetiology, Mental health, China, Connexins, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Mutation, Siblings, Clinical Sciences, Public Health and Health Services, Clinical sciences, Biological psychology
Abstract

Schizophrenia (SCZ) is a severe psychiatric disorder with a strong genetic component. High heritability of SCZ suggests a major role for transmitted genetic variants. Furthermore, SCZ is also associated with a marked reduction in fecundity, leading to the hypothesis that alleles with large effects on risk might often occur de novo. In this study, we conducted whole-genome sequencing for 23 families from two cohorts with unaffected siblings and parents. Two nonsense de novo mutations (DNMs) in GJC1 and HIST1H2AD were identified in SCZ patients. Ten genes (DPYSL2, NBPF1, SDK1, ZNF595, ZNF718, GCNT2, SNX9, AACS, KCNQ1, and MSI2) were found to carry more DNMs in SCZ patients than their unaffected siblings by burden test. Expression analyses indicated that these DNM implicated genes showed significantly higher expression in prefrontal cortex in prenatal stage. The DNM in the GJC1 gene is highly likely a loss function mutation (pLI = 0.94), leading to the dysregulation of ion channel in the glutamatergic excitatory neurons. Analysis of rare variants in independent exome sequencing dataset indicates that GJC1 has significantly more rare variants in SCZ patients than in unaffected controls. Data from genome-wide association studies suggested that common variants in the GJC1 gene may be associated with SCZ and SCZ-related traits. Genes co-expressed with GJC1 are involved in SCZ, SCZ-associated pathways, and drug targets. These evidences suggest that GJC1 may be a risk gene for SCZ and its function may be involved in prenatal and early neurodevelopment, a vulnerable period for developmental disorders such as SCZ.

Published
2020

44. A Dynamical Systems View of Psychiatric Disorders—Practical Implications

Author

Scheffer, Marten, primary, Bockting, Claudi L., additional, Borsboom, Denny, additional, Cools, Roshan, additional, Delecroix, Clara, additional, Hartmann, Jessica A., additional, Kendler, Kenneth S., additional, van de Leemput, Ingrid, additional, van der Maas, Han L. J., additional, van Nes, Egbert, additional, Mattson, Mark, additional, McGorry, Pat D., additional, and Nelson, Barnaby, additional

Published
2024
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45. A Dynamical Systems View of Psychiatric Disorders—Theory

Author

Scheffer, Marten, primary, Bockting, Claudi L., additional, Borsboom, Denny, additional, Cools, Roshan, additional, Delecroix, Clara, additional, Hartmann, Jessica A., additional, Kendler, Kenneth S., additional, van de Leemput, Ingrid, additional, van der Maas, Han L. J., additional, van Nes, Egbert, additional, Mattson, Mark, additional, McGorry, Pat D., additional, and Nelson, Barnaby, additional

Published
2024
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48. Genetic architecture of 11 major psychiatric disorders at biobehavioral, functional genomic and molecular genetic levels of analysis

Author

Grotzinger, Andrew D., Mallard, Travis T., Akingbuwa, Wonuola A., Ip, Hill F., Adams, Mark J., Lewis, Cathryn M., McIntosh, Andrew M., Grove, Jakob, Dalsgaard, Søren, Lesch, Klaus-Peter, Strom, Nora, Meier, Sandra M., Mattheisen, Manuel, Børglum, Anders D., Mors, Ole, Breen, Gerome, Lee, Phil H., Kendler, Kenneth S., Smoller, Jordan W., Tucker-Drob, Elliot M., and Nivard, Michel G.

Published
2022
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49. Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Author

Trubetskoy, Vassily, Pardiñas, Antonio F., Qi, Ting, Panagiotaropoulou, Georgia, Awasthi, Swapnil, Bigdeli, Tim B., Bryois, Julien, Chen, Chia-Yen, Dennison, Charlotte A., Hall, Lynsey S., Lam, Max, Watanabe, Kyoko, Frei, Oleksandr, Ge, Tian, Harwood, Janet C., Koopmans, Frank, Magnusson, Sigurdur, Richards, Alexander L., Sidorenko, Julia, Wu, Yang, Zeng, Jian, Grove, Jakob, Kim, Minsoo, Li, Zhiqiang, Voloudakis, Georgios, Zhang, Wen, Adams, Mark, Agartz, Ingrid, Atkinson, Elizabeth G., Agerbo, Esben, Al Eissa, Mariam, Albus, Margot, Alexander, Madeline, Alizadeh, Behrooz Z., Alptekin, Köksal, Als, Thomas D., Amin, Farooq, Arolt, Volker, Arrojo, Manuel, Athanasiu, Lavinia, Azevedo, Maria Helena, Bacanu, Silviu A., Bass, Nicholas J., Begemann, Martin, Belliveau, Richard A., Bene, Judit, Benyamin, Beben, Bergen, Sarah E., Blasi, Giuseppe, Bobes, Julio, Bonassi, Stefano, Braun, Alice, Bressan, Rodrigo Affonseca, Bromet, Evelyn J., Bruggeman, Richard, Buckley, Peter F., Buckner, Randy L., Bybjerg-Grauholm, Jonas, Cahn, Wiepke, Cairns, Murray J., Calkins, Monica E., Carr, Vaughan J., Castle, David, Catts, Stanley V., Chambert, Kimberley D., Chan, Raymond C. K., Chaumette, Boris, Cheng, Wei, Cheung, Eric F. C., Chong, Siow Ann, Cohen, David, Consoli, Angèle, Cordeiro, Quirino, Costas, Javier, Curtis, Charles, Davidson, Michael, Davis, Kenneth L., de Haan, Lieuwe, Degenhardt, Franziska, DeLisi, Lynn E., Demontis, Ditte, Dickerson, Faith, Dikeos, Dimitris, Dinan, Timothy, Djurovic, Srdjan, Duan, Jubao, Ducci, Giuseppe, Dudbridge, Frank, Eriksson, Johan G., Fañanás, Lourdes, Faraone, Stephen V., Fiorentino, Alessia, Forstner, Andreas, Frank, Josef, Freimer, Nelson B., Fromer, Menachem, Frustaci, Alessandra, Gadelha, Ary, Genovese, Giulio, Gershon, Elliot S., Giannitelli, Marianna, Giegling, Ina, Giusti-Rodríguez, Paola, Godard, Stephanie, Goldstein, Jacqueline I., González Peñas, Javier, González-Pinto, Ana, Gopal, Srihari, Gratten, Jacob, Green, Michael F., Greenwood, Tiffany A., Guillin, Olivier, Gülöksüz, Sinan, Gur, Raquel E., Gur, Ruben C., Gutiérrez, Blanca, Hahn, Eric, Hakonarson, Hakon, Haroutunian, Vahram, Hartmann, Annette M., Harvey, Carol, Hayward, Caroline, Henskens, Frans A., Herms, Stefan, Hoffmann, Per, Howrigan, Daniel P., Ikeda, Masashi, Iyegbe, Conrad, Joa, Inge, Julià, Antonio, Kähler, Anna K., Kam-Thong, Tony, Kamatani, Yoichiro, Karachanak-Yankova, Sena, Kebir, Oussama, Keller, Matthew C., Kelly, Brian J., Khrunin, Andrey, Kim, Sung-Wan, Klovins, Janis, Kondratiev, Nikolay, Konte, Bettina, Kraft, Julia, Kubo, Michiaki, Kučinskas, Vaidutis, Kučinskiene, Zita Ausrele, Kusumawardhani, Agung, Kuzelova-Ptackova, Hana, Landi, Stefano, Lazzeroni, Laura C., Lee, Phil H., Legge, Sophie E., Lehrer, Douglas S., Lencer, Rebecca, Lerer, Bernard, Li, Miaoxin, Lieberman, Jeffrey, Light, Gregory A., Limborska, Svetlana, Liu, Chih-Min, Lönnqvist, Jouko, Loughland, Carmel M., Lubinski, Jan, Luykx, Jurjen J., Lynham, Amy, Macek, Jr, Milan, Mackinnon, Andrew, Magnusson, Patrik K. E., Maher, Brion S., Maier, Wolfgang, Malaspina, Dolores, Mallet, Jacques, Marder, Stephen R., Marsal, Sara, Martin, Alicia R., Martorell, Lourdes, Mattheisen, Manuel, McCarley, Robert W., McDonald, Colm, McGrath, John J., Medeiros, Helena, Meier, Sandra, Melegh, Bela, Melle, Ingrid, Mesholam-Gately, Raquelle I., Metspalu, Andres, Michie, Patricia T., Milani, Lili, Milanova, Vihra, Mitjans, Marina, Molden, Espen, Molina, Esther, Molto, María Dolores, Mondelli, Valeria, Moreno, Carmen, Morley, Christopher P., Muntané, Gerard, Murphy, Kieran C., Myin-Germeys, Inez, Nenadić, Igor, Nestadt, Gerald, Nikitina-Zake, Liene, Noto, Cristiano, Nuechterlein, Keith H., O’Brien, Niamh Louise, O’Neill, F. Anthony, Oh, Sang-Yun, Olincy, Ann, Ota, Vanessa Kiyomi, Pantelis, Christos, Papadimitriou, George N., Parellada, Mara, Paunio, Tiina, Pellegrino, Renata, Periyasamy, Sathish, Perkins, Diana O., Pfuhlmann, Bruno, Pietiläinen, Olli, Pimm, Jonathan, Porteous, David, Powell, John, Quattrone, Diego, Quested, Digby, Radant, Allen D., Rampino, Antonio, Rapaport, Mark H., Rautanen, Anna, Reichenberg, Abraham, Roe, Cheryl, Roffman, Joshua L., Roth, Julian, Rothermundt, Matthias, Rutten, Bart P. F., Saker-Delye, Safaa, Salomaa, Veikko, Sanjuan, Julio, Santoro, Marcos Leite, Savitz, Adam, Schall, Ulrich, Scott, Rodney J., Seidman, Larry J., Sharp, Sally Isabel, Shi, Jianxin, Siever, Larry J., Sigurdsson, Engilbert, Sim, Kang, Skarabis, Nora, Slominsky, Petr, So, Hon-Cheong, Sobell, Janet L., Söderman, Erik, Stain, Helen J., Steen, Nils Eiel, Steixner-Kumar, Agnes A., Stögmann, Elisabeth, Stone, William S., Straub, Richard E., Streit, Fabian, Strengman, Eric, Stroup, T. Scott, Subramaniam, Mythily, Sugar, Catherine A., Suvisaari, Jaana, Svrakic, Dragan M., Swerdlow, Neal R., Szatkiewicz, Jin P., Ta, Thi Minh Tam, Takahashi, Atsushi, Terao, Chikashi, Thibaut, Florence, Toncheva, Draga, Tooney, Paul A., Torretta, Silvia, Tosato, Sarah, Tura, Gian Battista, Turetsky, Bruce I., Üçok, Alp, Vaaler, Arne, van Amelsvoort, Therese, van Winkel, Ruud, Veijola, Juha, Waddington, John, Walter, Henrik, Waterreus, Anna, Webb, Bradley T., Weiser, Mark, Williams, Nigel M., Witt, Stephanie H., Wormley, Brandon K., Wu, Jing Qin, Xu, Zhida, Yolken, Robert, Zai, Clement C., Zhou, Wei, Zhu, Feng, Zimprich, Fritz, Atbaşoğlu, Eşref Cem, Ayub, Muhammad, Benner, Christian, Bertolino, Alessandro, Black, Donald W., Bray, Nicholas J., Breen, Gerome, Buccola, Nancy G., Byerley, William F., Chen, Wei J., Cloninger, C. Robert, Crespo-Facorro, Benedicto, Donohoe, Gary, Freedman, Robert, Galletly, Cherrie, Gandal, Michael J., Gennarelli, Massimo, Hougaard, David M., Hwu, Hai-Gwo, Jablensky, Assen V., McCarroll, Steven A., Moran, Jennifer L., Mors, Ole, Mortensen, Preben B., Müller-Myhsok, Bertram, Neil, Amanda L., Nordentoft, Merete, Pato, Michele T., Petryshen, Tracey L., Pirinen, Matti, Pulver, Ann E., Schulze, Thomas G., Silverman, Jeremy M., Smoller, Jordan W., Stahl, Eli A., Tsuang, Debby W., Vilella, Elisabet, Wang, Shi-Heng, Xu, Shuhua, Adolfsson, Rolf, Arango, Celso, Baune, Bernhard T., Belangero, Sintia Iole, Børglum, Anders D., Braff, David, Bramon, Elvira, Buxbaum, Joseph D., Campion, Dominique, Cervilla, Jorge A., Cichon, Sven, Collier, David A., Corvin, Aiden, Curtis, David, Forti, Marta Di, Domenici, Enrico, Ehrenreich, Hannelore, Escott-Price, Valentina, Esko, Tõnu, Fanous, Ayman H., Gareeva, Anna, Gawlik, Micha, Gejman, Pablo V., Gill, Michael, Glatt, Stephen J., Golimbet, Vera, Hong, Kyung Sue, Hultman, Christina M., Hyman, Steven E., Iwata, Nakao, Jönsson, Erik G., Kahn, René S., Kennedy, James L., Khusnutdinova, Elza, Kirov, George, Knowles, James A., Krebs, Marie-Odile, Laurent-Levinson, Claudine, Lee, Jimmy, Lencz, Todd, Levinson, Douglas F., Li, Qingqin S., Liu, Jianjun, Malhotra, Anil K., Malhotra, Dheeraj, McIntosh, Andrew, McQuillin, Andrew, Menezes, Paulo R., Morgan, Vera A., Morris, Derek W., Mowry, Bryan J., Murray, Robin M., Nimgaonkar, Vishwajit, Nöthen, Markus M., Ophoff, Roel A., Paciga, Sara A., Palotie, Aarno, Pato, Carlos N., Qin, Shengying, Rietschel, Marcella, Riley, Brien P., Rivera, Margarita, Rujescu, Dan, Saka, Meram C., Sanders, Alan R., Schwab, Sibylle G., Serretti, Alessandro, Sham, Pak C., Shi, Yongyong, St Clair, David, Stefánsson, Hreinn, Stefansson, Kari, Tsuang, Ming T., van Os, Jim, Vawter, Marquis P., Weinberger, Daniel R., Werge, Thomas, Wildenauer, Dieter B., Yu, Xin, Yue, Weihua, Holmans, Peter A., Pocklington, Andrew J., Roussos, Panos, Vassos, Evangelos, Verhage, Matthijs, Visscher, Peter M., Yang, Jian, Posthuma, Danielle, Andreassen, Ole A., Kendler, Kenneth S., Owen, Michael J., Wray, Naomi R., Daly, Mark J., Huang, Hailiang, Neale, Benjamin M., Sullivan, Patrick F., Ripke, Stephan, Walters, James T. R., and O’Donovan, Michael C.

Published
2022
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