| Author |
Chen, Y; Liu, SH; Ren, ZY; Wang, FR; Liang, QM; Jiang, Y; Dai, RJ; Duan, FY; Han, C; Ning, ZL; Xia, Y; Li, M; Yuan, K; Qiu, WY; Yan, XX; Dai, JP; Kopp, RF; Huang, JF; Xu, SH; Tang, BS; Wu, LQ; Gamazon, ER; Bigdeli, T; Gershon, E; Huang, HL; Ma, C; Liu, CY; Chen, C |
| Abstract |
Research on brain expression quantitative trait loci (eQTLs) has illuminated the genetic underpinnings of schizophrenia (SCZ). Yet mostof these studies have been centered on European populations, leading to a constrained understanding of population diversities and dis-ease risks. To address this gap, we examined genotype and RNA-seq data from African Americans (AA,n 1/4 158), Europeans (EUR,n 1/4 408), and East Asians (EAS,n 1/4 217). When comparing eQTLs between EUR and non-EUR populations, we observed concordant patternsof genetic regulatory effect, particularly in terms of the effect sizes of the eQTLs. However, 343,737cis-eQTLs linked to 1,276 genes and198,769 SNPs were found to be specific to non-EUR populations. Over 90% of observed population differences in eQTLs could be tracedback to differences in allele frequency. Furthermore, 35% of these eQTLs were notably rare in the EUR population. Integrating braineQTLs with SCZ signals from diverse populations, we observed a higher disease heritability enrichment of brain eQTLs in matched pop-ulations compared to mismatched ones. Prioritization analysis identified five risk genes (SFXN2,VPS37B,DENR,FTCDNL1, andNT5DC2) and three potential regulatory variants in known risk genes (CNNM2,MTRFR, andMPHOSPH9) that were missed in theEUR dataset. Our findings underscore that increasing genetic ancestral diversity is more efficient for power improvement than merelyincreasing the sample size within single-ancestry eQTLs datasets. Such a strategy will not only improve our understanding of the bio-logical underpinnings of population structures but also pave the way for the identification of risk genes in SCZ |
