Single cell variant to enhancer to gene map for coronary artery disease [ChIP-seq]

Although genome wide association studies (GWAS) in large populations have identified hundreds of variants associated with common diseases such as coronary artery disease (CAD), most variants lie within non-coding regions of the genome, rendering it difficult to determine the downstream causal gene and cell type. Here, we performed paired single nucleus gene expression and chromatin accessibility profiling from 44 human coronary arteries. To link disease variants to molecular traits, we developed a meta-map of 88 samples and discovered 11,182 single-cell chromatin accessibility quantitative trait loci (caQTLs). Heritability enrichment analysis and disease variant mapping demonstrated that smooth muscle cells (SMCs) harbor the greatest genetic risk for CAD. To capture the continuum of SMC cell states in disease we used single cell caQTL modeling for the first time in tissue to uncover QTLs which are cell state aware and expand our insight into gene regulation in heterogenous cell populations. We identified a variant in the COL4A1/COL4A2 CAD GWAS locus which becomes a caQTL as SMCs de-differentiate through a transcription factor binding site change for EGR1/2. To unbiasedly prioritize functional candidate genes, we built a genome-wide single cell variant to enhancer to gene (scV2E2G) map in human CAD to link disease variants to causal genes in cell types. Using this approach, we found several hundred genes predicted to be linked to disease variants in different cell types. We validated these predictions using enhancer targeted perturb sequencing (TAP-seq). Next, we performed genome-wide HiC in 16 human coronary arteries to build tissue specific gene regulatory networks and map disease variants to integrated chromatin hubs and distal target genes not previously implicated. Using this approach, we show that rs4887091 within the ADAMTS7 GWAS locus modulates function of a super chromatin interactome through a change in a CTCF binding site. Finally, by integrating human genetics with single cell multi-omics we show that CAD genetic risk is enriched in de-differentiated fibromyocytes. Collectively we provide a disease agnostic framework to translate human genetic findings to identify pathologic cell states and genes driving disease, producing a comprehensive scV2E2G map with genetic and tissue level conviction for future mechanistic and therapeutic studies.