DNA methylation and gene expression analysis in adipose tissue to identify new loci associated with T2D development in obesity

BACKGROUND: Obesity is accompanied by excess adipose fat storage, which may lead to adipose dysfunction, insulin resistance, and type 2 diabetes (T2D). Currently, the tendency to develop T2D in obesity cannot be explained by genetic variation alone—epigenetic mechanisms, such as DNA methylation, might be involved. Here, we aimed to identify changes in DNA methylation and gene expression in visceral adipose tissue (VAT) that might underlie T2D susceptibility in patients with obesity. METHODS: We investigated DNA methylation and gene expression in VAT biopsies from 19 women with obesity, without (OND = 9) or with T2D (OD = 10). Differences in genome-scale methylation (differentially methylated CpGs [DMCs], false discovery rate < 0.05; and differentially methylated regions [DMRs], p value < 0.05) and gene expression (DEGs, p value <0.05) between groups were assessed. We searched for overlap between altered methylation and expression and the impact of altered DNA methylation on gene expression, using bootstrap Pearson correlation. The relationship of altered DNA methylation to T2D-related traits was also tested. RESULTS: We identified 11 120 DMCs and 96 DMRs distributed across all chromosomes, with the greatest density of epigenomic alterations at the MHC locus. These alterations were found in newly and previously T2D-related genes. Several of these findings were supported by validation and extended multi-ethnic analyses. Of 252 DEGs in the OD group, 68 genes contained DMCs (n = 88), of which 24 demonstrated a significant relationship between gene expression and methylation (p values <0.05). Of these, 16, including ATP11A, LPL and EHD2 also showed a significant correlation with fasting glucose and HbA1c levels. CONCLUSIONS: Our results revealed novel candidate genes related to T2D pathogenesis in obesity. These genes show perturbations in DNA methylation and expression profiles in patients with obesity and diabetes. Methylation profiles were able to discriminate OND from OD individuals; DNA methylation is thus a potential biomarker.