Integrative functional genomics identifies regulatory mechanisms at coronary artery disease loci.

Clint L Miller,Ljubica Perisic,Oscar Franzén,Christer Betsholtz,Thomas Quertermous,Eric E Schadt,Trieu Nguyen,Milos Pjanic,Ting Wang,Ulf Hedin,Themistocles L Assimes,Arno Ruusalepp,Jonathan D Lee,Oliver Wang,Ramendra K Kundu,Deshna Majmudar,Ariella Cohain,Stephen B Montgomery,Johan Björkegren ,Juyong Brian Kim

doi:10.1038/ncomms12092

Abstract

Coronary artery disease (CAD) is the leading cause of mortality and morbidity, driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies have identified >150 loci associated with CAD and myocardial infarction susceptibility in humans. A majority of these variants reside in non-coding regions and are co-inherited with hundreds of candidate regulatory variants, presenting a challenge to elucidate their functions. Herein, we use integrative genomic, epigenomic and transcriptomic profiling of perturbed human coronary artery smooth muscle cells and tissues to begin to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps, we prioritize 64 candidate variants and perform allele-specific binding and expression analyses at seven top candidate loci: 9p21.3, SMAD3, PDGFD, IL6R, BMP1, CCDC97/TGFB1 and LMOD1. We validate our findings in expression quantitative trait loci cohorts, which together reveal new links between CAD associations and regulatory function in the appropriate disease context.

Highlights

Coronary artery disease (CAD) is the leading cause of mortality and morbidity, driven by both genetic and environmental risk factors
Developed methods to interrogate chromatin accessibility include the Assay for Transposase Accessible Chromatin (ATAC-seq), which has an advantage over other methods in that it requires a fraction of the starting material to simultaneously assess chromatin state, nucleosome profiles and transcription factor (TF) footprints[28]
We obtained an average of 100 million Tn5-integrated mapped reads (200 million paired) and average detection of B150,000 open chromatin peaks per sample, which resulted in high signal-to-noise ratios (Fig. 1a; Supplementary Fig. 2a–c), low individual sample variability (r2 1⁄4 0.94 biological replicates; Fig. 1b), and robust CTCF centred footprints and resolved nucleosome profiles (Supplementary Fig. 3)

Summary

Introduction

Coronary artery disease (CAD) is the leading cause of mortality and morbidity, driven by both genetic and environmental risk factors. We use integrative genomic, epigenomic and transcriptomic profiling of perturbed human coronary artery smooth muscle cells and tissues to begin to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps, we prioritize 64 candidate variants and perform allele-specific binding and expression analyses at seven top candidate loci: 9p21.3, SMAD3, PDGFD, IL6R, BMP1, CCDC97/TGFB1 and LMOD1. We employ ATAC-seq to generate epigenomic profiles in primary cultured HCASMCs stimulated with various growth factors, as well as in normal and atherosclerotic human coronary artery tissues We integrate these data with chromatin immunoprecipitation-sequencing (ChIP-seq) profiles for TF binding and the active enhancer histone modification H3K27ac to define HCASMC-enriched cis-regulatory mechanisms (Supplementary Fig. 1). These multi-dimensional data further advance our understanding of non-coding regulatory variation in a complex disease, such as CAD

Methods

Results

Conclusion