Key Laboratory of Animal Models and Human Disease Mechanisms, CAS

Genome-wide association study followed by trans-ancestry meta-analysis identify 17 new risk loci for schizophrenia. BMC Med, 2021.

Title:Genome-wide association study followed by trans-ancestry meta-analysis identify 17 new risk loci for schizophrenia.

Author:Liu K,Pu J, Nie Z , Shi YL, Jiang LP, Wu QS, Chen YB, Yang CP.

Publication Name: BMC Med

Pub Year: 2021

Doi: 10.1186/s12916-021-02039-9

IF: 8.775

Abstract:

Background Over 200 schizophrenia risk loci have been identified by genome-wide association studies (GWASs). However, the majority of risk loci were identified in populations of European ancestry (EUR), potentially missing important biological insights. It is important to perform 5 GWASs in non-European populations. Methods To identify novel schizophrenia risk loci, we conducted a GWAS in Han Chinese population (3493 cases and 4709 controls). We then performed a large-scale meta-analysis (a total of 143,438 subjects) through combining our results with previous GWASs conducted in EAS and EUR. In addition, we also carried out comprehensive post-GWAS analysis, including heritability partitioning, enrichment of schizophrenia associations in tissues and cell types, trancscriptome-wide association study (TWAS), expression quantitative trait loci (eQTL) and differential expression analysis. Results We identified two new schizophrenia risk loci, including associations in SHISA9 (rs7192086, P = 4.92 x 10(-08)) and PES1 (rs57016637, P = 2.33 x 10(-11)) in Han Chinese population. A fixed-effect meta-analysis (a total of 143,438 subjects) with summary statistics from EAS and EUR identifies 15 novel genome-wide significant risk loci. Heritability partitioning with linkage disequilibrium score regression (LDSC) reveals a significant enrichment of schizophrenia heritability in conserved genomic regions, promoters, and enhancers. Tissue and cell-type enrichment analyses show that schizophrenia associations are significantly enriched in human brain tissues and several types of neurons, including cerebellum neurons, telencephalon inhibitory, and excitatory neurons. Polygenic risk score profiling reveals that GWAS summary statistics from trans-ancestry meta-analysis (EAS + EUR) improves prediction performance in predicting the case/control status of our sample. Finally, transcriptome-wide association study (TWAS) identifies risk genes whose cis-regulated expression change may have a role in schizophrenia. Conclusions Our study identifies 17 novel schizophrenia risk loci and highlights the importance and necessity of conducting genetic study in different populations. These findings not only provide new insights into genetic etiology of schizophrenia, but also facilitate to delineate the pathophysiology of schizophrenia and develop new therapeutic targets.