Epigenome-wide association in adipose tissue from the METSIM cohort. (16th March 2018)

• Record Type: Journal Article
• Authors: Orozco, Luz D; Farrell, Colin; Hale, Christopher; Rubbi, Liudmilla; Rinaldi, Arturo; Civelek, Mete; Pan, Calvin; Lam, Larry; Montoya, Dennis; Edillor, Chantle; Seldin, Marcus; Boehnke, Michael; Mohlke, Karen L; Jacobsen, Steve; Kuusisto, Johanna; Laakso, Markku; Lusis, Aldons J; Pellegrini, Matteo
• Is Part Of: Human molecular genetics. Volume 27:Number 10(2018:May 15)
• Page Start: 1830
• Page End: 1846
• Publication Date: 2018-03-16
• Subjects: Human molecular genetics -- Periodicals; Human chromosome abnormalities -- Periodicals; 572.8
• DOI: 10.1093/hmg/ddy093
• Languages: English
• ISSNs: 0964-6906

Abstract

Abstract: Most epigenome-wide association studies to date have been conducted in blood. However, metabolic syndrome is mediated by a dysregulation of adiposity and therefore it is critical to study adipose tissue in order to understand the effects of this syndrome on epigenomes. To determine if natural variation in DNA methylation was associated with metabolic syndrome traits, we profiled global methylation levels in subcutaneous abdominal adipose tissue. We measured association between 32 clinical traits related to diabetes and obesity in 201 people from the Metabolic Syndrome in Men cohort. We performed epigenome-wide association studies between DNA methylation levels and traits, and identified associations for 13 clinical traits in 21 loci. We prioritized candidate genes in these loci using expression quantitative trait loci, and identified 18 high confidence candidate genes, including known and novel genes associated with diabetes and obesity traits. Using methylation deconvolution, we examined which cell types may be mediating the associations, and concluded that most of the loci we identified were specific to adipocytes. We determined whether the abundance of cell types varies with metabolic traits, and found that macrophages increased in abundance with the severity of metabolic syndrome traits. Finally, we developed a DNA methylation-based biomarker to assess type 2 diabetes risk in adipose tissue. In conclusion, our results demonstrate that profiling DNA methylation in adipose tissue is a powerful tool for understanding the molecular effects of metabolic syndrome on adipose tissue, and can be used in conjunction with traditional genetic analyses to further characterize this disorder.