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Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. We identified a number of candidate mechanisms for smooth muscle cell transition states and identified putative binding sites for risk variants. We further employed DNA element to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. This single cell atlas provides a critical step towards interpreting cis-regulatory mechanisms in the vessel wall across the continuum of CAD risk.

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