Genome-wide association studies have identified 46 replicated genetic loci for coronary heart disease (CHD), and 104 loci associated at a 5% false discovery rate. However, the regulatory mechanisms of these associations largely remain elusive. Given that the majority of these CHD-associated loci reside in non-coding regions, they are predicted to function via context-specific gene regulation. Recent high-throughput assays of regulatory function include the assay for transposase-accessible chromatin using sequencing (ATAC-seq) and chromatin immunoprecipitation-sequencing (ChIP-seq). ATAC-seq utilizes a Tn5 transposase to fragment and tag accessible DNA sequences, which are often coupled to transcription factor occupancy identified by ChIP-seq. Importantly, this assay may reveal the spatio-temporal regulatory profiles in limited numbers of primary cells. Using ATAC-seq in human coronary artery smooth muscle cells (HCASMC) we identified 147,173 accessible chromatin peaks in control versus 198,976 peaks in TGF-beta-stimulated cells (136,446 shared peaks). Using
de novo
motif enrichment analysis we identified significant enrichment of specific AP-1 family members (29.2% vs. 5.1% background), chromatin remodeling, and SMC differentiation transcription factors. Using functional enrichment analysis of ChIP-seq and CHD-overlapping regions we observed enrichment of the hypoxia inducible factor 1 (HIF-1) and TGF-beta signaling pathways (1.5x10
-22
and 5.6x10
-18
, respectively) and relevant phenotypes, including cell migration and blood vessel morphology. Finally, we utilized these regulatory maps to explore the causal mechanisms underlying CHD-associated variants at four loci using haplotype-specific chromatin immunoprecipitation (haploChIP) and luciferase reporter assays. Taken together, these results suggest that genome-wide approaches such as ATAC-seq can be leveraged to map context-specific regulatory mechanisms of non-coding variants associated with complex diseases such as CHD, and reveal new biological and molecular insights into targeting heritable disease risk.
Insight Gained from Genome-Wide Interaction and Enrichment Analysis on Weight Gain During Citalopram Treatment