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.

Fig. 1

Ancestry assignment and Manhattan plots for trans-ancestry meta-analyses of GPC-AA and GPC-Latino with PGC-SCZ2. a PCA-based clustering of GPC participants shaded by broad ancestry assignment. b Red and blue dashed lines denote thresholds for genome-wide significance (P < 5 × 10⁻⁸) and replication follow-up in PGC-SCZ2 (P < 10⁻⁶). For newly genome-wide significant regions, the top SNP within a 3 Mb region is displayed as a diamond; nearby SNPs in linkage disequilibrium (r² > 0.1) are highlighted

Fig. 2

Trans-ancestry association of polygenic risk scores with schizophrenia. For scores based on PGC-SCZ2, GPC-AA or GPC-Latino, and meta-analysis results, the variance in risk explained in the other study is shown on the y-axis in terms of R² on the liability scale. a Scores based on various P value inclusion thresholds are displayed as shaded bars; b scores based on P_T < 0.5 and varying pairwise LD between SNPs are displayed as shaded bars. Analyses of PGC-SCZ2 and meta-analysis scores utilized an independent cohort of European ancestry GPC participants

Fig. 3

Regional association plots for selected schizophrenia associations with improved fine-mapping resolution in trans-ancestry meta-analysis. For each selected region, association results for PGC-SCZ2 and meta-analysis of PGC-SCZ2 with GPC-AA are shown in the first and second panels, respectively. The strength of LD of each SNP with the “index” SNP, displayed as a large purple diamond, is indicated by its color. Genomic intervals corresponding to SNPs with LD r² > 0.6 to the index SNP (“rsq6”) and 99% credible sets in PGC-SCZ2 (“pgc”) and the present analysis (“meta”) are displayed. Plots were created using the LocusZoom standalone software [54]