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

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.

Low generalizability of polygenic scores in African populations due to genetic and environmental diversity

“…When predicting traits using the UKB, BBJ, and PAGE meta-analysis as a discovery cohort, we find that prediction accuracy increases most for the AMR, EAS, and AFR target populations, which more closely resemble the ancestry patterns of PAGE and BBJ ( Figure 4B ). These findings are consistent with ancestry-matched discovery data disproportionately improving prediction accuracy in the corresponding target population (Bigdeli et al, 2019;Lam et al, 2019;Martin et al, 2019) .…”

“…While PRS currently have limited portability, increased diversity in genetic studies is already decreasing prediction accuracy gaps across populations (Bigdeli et al, 2019;Kuchenbaecker et al, 2019) . This is consistent with causal genetic effects tending to be similar across populations but with LD and allele frequency differences modifying marginal effect size estimates (Martin et al, 2019) .…”

“…African ancestry populations also have shorter blocks of linkage disequilibrium, which improves resolution to fine-map causal variants (Genovese et al, 2010) . PRS accuracy is lowest in African ancestry populations due to GWAS study biases (Martin et al, 2019) , but when GWAS include these and other diverse populations, PRS predict traits such as schizophrenia more accurately across all populations compared to single-ancestry GWAS (Bigdeli et al, 2019) .…”

Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics

“…First, previously published RBC trait genome-wide association study (GWAS) populations have mostly been ancestrally homogeneous [31][32][33][34][35][36][37][38][39]. Utilization of diverse study populations can improve identification of rare or ancestry-specific variants located in biological pathways that affect phenotypes in global populations and, when summary data are made publicly available, enable construction of broadly applicable polygenic risk scores [40]. Relatedly, gaps between estimated heritability and the proportion of variance explained by GWAS findings suggest that additional associations remain to be identified, including rare variants and independent secondary associations at known loci that are both more likely to be ancestrally specific [12,41,42].…”

Missing in Action: African Ancestry Brain Research

“…The NIH has launched the “All of Us” project, an ambitious program to acquire health information and sequence the genomes of 1 million individuals, with a target of 50% from minority populations. Some GWASs of individuals of AA with psychiatric disorders are finally ongoing in the United States and in Africa ( Bigdeli et al., 2019 ). Also in Africa, The Human Heredity and Health in Africa (H3Africa) consortium is an effort to build partnerships of scientists across several African countries and study primarily general medical and infectious diseases.…”