Abstract
DNA methylation has a great potential for understanding the aetiology of common complex traits such as Type 2 diabetes (T2D). Here we perform genome-wide methylated DNA immunoprecipitation sequencing (MeDIP-seq) in whole-blood-derived DNA from 27 monozygotic twin pairs and follow up results with replication and integrated omics analyses. We identify predominately hypermethylated T2D-related differentially methylated regions (DMRs) and replicate the top signals in 42 unrelated T2D cases and 221 controls. The strongest signal is in the promoter of the MALT1 gene, involved in insulin and glycaemic pathways, and related to taurocholate levels in blood. Integrating the DNA methylome findings with T2D GWAS meta-analysis results reveals a strong enrichment for DMRs in T2D-susceptibility loci. We also detect signals specific to T2D-discordant twins in the GPR61 and PRKCB genes. These replicated T2D associations reflect both likely causal and consequential pathways of the disease. The analysis indicates how an integrated genomics and epigenomics approach, utilizing an MZ twin design, can provide pathogenic insights as well as potential drug targets and biomarkers for T2D and other complex traits.
Highlights
DNA methylation has a great potential for understanding the aetiology of common complex traits such as Type 2 diabetes (T2D)
We assessed evidence of differentially methylated regions (DMRs) in T2D (T2D-DMRs) in the entire sample of 27 MZ twin pairs, which consisted of 17 T2D discordant, 3 T2D concordant and 7 healthy control concordant twin pairs (Supplementary Data 1)
Taking the false discovery rate (FDR) 25% cutoff as our suggestive T2DDMR set, approximately two-thirds of the observed suggestive T2D-DMRs are hypermethylated in cases (Fig. 1)
Summary
DNA methylation has a great potential for understanding the aetiology of common complex traits such as Type 2 diabetes (T2D). Finding diseaseassociated DNA methylation variation will provide insight into novel molecular disease mechanisms, may help to predict disease status and potentially generate novel treatment methods The identification of these genome-wide differentially methylated regions (DMRs) in association with complex phenotypes through epigenome wide association studies[3,4], is substantially improved by a powerful disease-discordant identical twin model[5]. We compare genome-wide DNA methylation profiles in T2D to identify DMRs in the total set of 27 discordant and concordant pairs of monozygotic (MZ) adult twins using a mixed effect model. We follow these up with analysis restricted to the 17 T2D-discordant MZ twins to identify genetically independent DMRs (giDMRs) with a paired model. We replicate our results in an independent sample of 263 unrelated cases (42) and controls (221)
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