Integration analysis of methylation quantitative trait loci and GWAS identify three schizophrenia risk variants.

Abstract

Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with schizophrenia (SCZ). However, prioritizing risk variants and regulatory elements for follow-up functional studies remains a major challenge. Therefore, we performed an integrated analysis to identify variants who affect methylation levels of nearby genes and contribute to the risk of SCZ, and to explore the potential role of these variants in SCZ pathogenesis. First, we used the Summary data-based Mendelian Randomization (SMR) method to integrate GWAS and methylation quantitative trait loci data. Then, the SNP-methylation combinations as associated with SCZ were replicated across multiple samples. Totally, we identified and replicated 14 and one SNP-methylation combinations in blood and brain tissues, respectively, that significantly associated with SCZ. Furthermore, our expression quantitative trait loci analysis, differential methylation analysis, neuroimaging genetics, and cognitive genetics analysis consistently supported the potential roles of these 15 SNPs in the pathogenesis of SCZ. Finally, using the convergent functional genomics method, we prioritized three risk SNPs, including rs3765971 (RERE, PSMR = 3.87 × 10-8), rs55742290 (ARL6IP4, PSMR = 1.50 × 10-7), and rs7293091 (CENPM, PSMR = 5.09 × 10-7), may represent promising risk variants in SCZ. These convergent lines of evidence suggest that three risk variants may be involved in the pathogenesis of SCZ. Further investigation of the roles of these variants in the pathogenesis of SCZ is warranted.