Genome-wide sequencing-based identification of methylation quantitative trait loci and their role in schizophrenia risk

Kira A. Perzel Mandell, Nicholas J. Eagles, Richard Wilton, Amanda J. Price, Stephen A. Semick, Leonardo Collado-Torres, William S. Ulrich, Ran Tao, Shizhong Han, Alexander S. Szalay, Thomas M. Hyde, Joel E. Kleinman, Daniel R. Weinberger () and Andrew E. Jaffe ()
Additional contact information
Kira A. Perzel Mandell: Johns Hopkins Medical Campus
Nicholas J. Eagles: Johns Hopkins Medical Campus
Richard Wilton: Johns Hopkins University
Amanda J. Price: Johns Hopkins Medical Campus
Stephen A. Semick: Johns Hopkins Medical Campus
Leonardo Collado-Torres: Johns Hopkins Medical Campus
William S. Ulrich: Johns Hopkins Medical Campus
Ran Tao: Johns Hopkins Medical Campus
Shizhong Han: Johns Hopkins Medical Campus
Alexander S. Szalay: Johns Hopkins University
Thomas M. Hyde: Johns Hopkins Medical Campus
Joel E. Kleinman: Johns Hopkins Medical Campus
Daniel R. Weinberger: Johns Hopkins Medical Campus
Andrew E. Jaffe: Johns Hopkins Medical Campus

Nature Communications, 2021, vol. 12, issue 1, 1-12

Abstract: Abstract DNA methylation (DNAm) is an epigenetic regulator of gene expression and a hallmark of gene-environment interaction. Using whole-genome bisulfite sequencing, we have surveyed DNAm in 344 samples of human postmortem brain tissue from neurotypical subjects and individuals with schizophrenia. We identify genetic influence on local methylation levels throughout the genome, both at CpG sites and CpH sites, with 86% of SNPs and 55% of CpGs being part of methylation quantitative trait loci (meQTLs). These associations can further be clustered into regions that are differentially methylated by a given SNP, highlighting the genes and regions with which these loci are epigenetically associated. These findings can be used to better characterize schizophrenia GWAS-identified variants as epigenetic risk variants. Regions differentially methylated by schizophrenia risk-SNPs explain much of the heritability associated with risk loci, despite covering only a fraction of the genomic space. We provide a comprehensive, single base resolution view of association between genetic variation and genomic methylation, and implicate schizophrenia GWAS-associated variants as influencing the epigenetic plasticity of the brain.

Date: 2021
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DOI: 10.1038/s41467-021-25517-3

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