Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry

• Type of Material: Article
• Authors: Tim B. Bigdeli, Suny Downstate Medical Center; Giulio Genovese, Broad Institute of MIT and Harvard; Penelope Georgakopoulos, Suny Downstate Medical Center; Jacquelyn L. Meyers, Suny Downstate Medical Center; Roseann E. Peterson, Virginia Commonwealth University; Conrad O. Iyegbe, Kings College London; Helena Medeiros, Suny Downstate Medical Center; Jorge Valderrama, Suny Downstate Medical Center; Eric D. Achtyes, Cherry Health; Roman Kotov, SUNY Stony Brook; Eli A. Stahl, Icahn School of Medicine at Mount Sinai; Becky Kinkead, Emory University; Mark Rapaport, Emory University; Michele T. Pato, Suny Downstate Medical Center; Steven A. McCarroll, Broad Institute of MIT and Harvard; Carlos N. Pato, Suny Downstate Medical Center
• Language: English
• Date: 2020-10-01
• Publisher: Springer Nature
• Publication Version: Final Published Version
• Copyright Statement: © 2019, The Author(s).
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1038/s41380-019-0517-y
• Title of Journal or Parent Work: Molecular Psychiatry
• Volume: 25
• Issue: 10
• Start Page: 2455
• End Page: 2467
• Grant/Funding Information: REP was supported by NIH K01 grant MH113848.; The GPC was supported by grants R01 MH085548 and R01 MH104964 from the National Institute of Mental Health (NIMH), and genotyping of samples was provided by the Stanley Center for Psychiatric Research at Broad Institute.; JLM was supported by National Institutes of Health (NIH) K01 grant DA037914.; Some statistical analyses were carried out on the Genetic Cluster Computer (http://www.geneticcluster.org) which is financially supported by the Netherlands Scientific Organization (NWO 480-05-003) along with a supplement from the Dutch Brain Foundation and the VU University Amsterdam.; Funding support for the Whole Genome Association Study of Bipolar Disorder and the Genome-Wide Association of Schizophrenia Study was provided by the NIMH (R01 MH67257, R01 MH59588, R01 MH59571, R01 MH59565, R01 MH59587, R01 MH60870, R01 MH59566, R01 MH59586, R01 MH61675, R01 MH60879, R01 MH81800, U01 MH46276, U01 MH46289, U01 MH46318, U01 MH79469, and U01 MH79470) and the genotyping of samples was provided through the Genetic Association Information Network (GAIN).; The Consortium on the Genetics of Schizophrenia (COGS) was supported by grants R01 MH065571, R01 MH065588, R01 MH065562, R01 MH065707, R01 MH065554, R01 MH065578, R01 MH065558, R01 MH86135, and R01 MH094320 from the NIMH.
• Keywords: SUSCEPTIBILITY; Psychiatry; MUTATIONS; LOCI; BURDEN; Neurosciences & Neurology; Science & Technology; METAANALYSIS; TRAIT; Life Sciences & Biomedicine; Biochemistry & Molecular Biology; SET; Neurosciences; GENOME-WIDE ASSOCIATION
• Research Categories: Psychology, Clinical; Biology, Genetics

Abstract

Schizophrenia is a common, chronic and debilitating neuropsychiatric syndrome affecting tens of millions of individuals worldwide. While rare genetic variants play a role in the etiology of schizophrenia, most of the currently explained liability is within common variation, suggesting that variation predating the human diaspora out of Africa harbors a large fraction of the common variant attributable heritability. However, common variant association studies in schizophrenia have concentrated mainly on cohorts of European descent. We describe genome-wide association studies of 6152 cases and 3918 controls of admixed African ancestry, and of 1234 cases and 3090 controls of Latino ancestry, representing the largest such study in these populations to date. Combining results from the samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC) study of schizophrenia yielded seven newly genome-wide significant loci, and we identified an additional eight loci by incorporating the results from samples with Latino ancestry. Leveraging population differences in patterns of linkage disequilibrium, we achieve improved fine-mapping resolution at 22 previously reported and 4 newly significant loci. Polygenic risk score profiling revealed improved prediction based on trans-ancestry meta-analysis results for admixed African (Nagelkerke’s R2 = 0.032; liability R2 = 0.017; P < 10−52), Latino (Nagelkerke’s R2 = 0.089; liability R2 = 0.021; P < 10−58), and European individuals (Nagelkerke’s R2 = 0.089; liability R2 = 0.037; P < 10−113), further highlighting the advantages of incorporating data from diverse human populations.