Investigating Genomic Regulatory Elements in Adipocytes via Computational Analysis

Obesity prevalence has more than doubled since the 1980s. One possible consequence of obesity is insulin resistance (IR), a condition underlying type 2 diabetes mellitus (T2DM). So far, genome wide association studies (GWAS) have attributed 18% of heritable risk for T2DM to genetic variants, but one shortcoming of GWAS is knowing which genes are affected by identified variants. This study aimed to confront this weakness and investigate how epigenetic regulation affects metabolic phenotype. Three histone marks (H3K27ac, H3K4me1, H3K4me3) were targeted by chromatin immunoprecipitation for in vivo samples collected from human subcutaneous adipocytes and metabolically-relevant tissue samples curated from the ENCODE database. We developed the Extremity analysis method to identify enhancers and promoters enriched in histone ChIP-Seq data. Additionally, a full suite of well-established bioinformatics methods were employed, including differential enrichment analysis (DEA) and motif enrichment analysis (MEA), and existing obesity related GWAS were incorporated. Close correlation was found between Extremity and DEA, MEA provided enriched motifs that bind known adipogenic TFs, and the GWAS showed variants in T2DM and WHRadjBMI overlapping H3K4me3 have less heritability in adipocytes than the other two marks. This study provides a new method and potential targets for further understanding epigenetic variation and its effect on metabolic phenotype