Key result
Integration of massively parallel reporter assays and epigenome profiling in vascular smooth muscle cells identified 122 candidate variants with significant enhancer activity and allelic imbalance.
Why the study?
Identifying functional variants within over 300 CAD-associated genomic loci has been limited largely by linkage disequilibrium, hindering understanding of the molecular mechanisms underlying disease risk.
This study comprehensively fine-maps causal genetic variants that confer increased risk of coronary artery disease through their regulatory effects on vascular smooth muscle cells.
Answers are grounded in this paper and cite their sources.
Candidate CAD variant prioritization may refine loci; leaves open functional validation before any clinical use.
Coronary artery disease (CAD) is a complex disorder with genetic and environmental influences. Genome-wide association studies (GWAS) have identified over 300 genomic loci associated with disease risk. However, identifying the functional variants within these loci has been limited in large part due to linkage disequilibrium. This represents a critical step in understanding the molecular mechanisms underlying disease risk. To identify and prioritize candidate causal CAD-associated variants, we performed lentivirus-based massively parallel reporter assays (lentiMPRAs) in primary vascular smooth muscle cells (SMCs), which play significant roles in atherosclerosis, the underlying cause of CAD. We tested 25892 CAD-associated variants for their allele-specific enhancer activity in quiescent and proliferative SMCs, modeling healthy and disease conditions. We identified 122 candidate variants showing significant enhancer activity and differences in reporter gene expression between risk and non-risk alleles. We also identified 23 variants showing condition-biased allelic imbalance and 41 variants showing sex-biased allelic imbalance. We further functionally characterized 25892 variants by performing CUT&RUN assays to identify variants in enhancer and promoter regions of SMCs. By integrating the results of these experiments, we identified a credible set of 49 CAD-associated variants in functionally relevant regions. Furthermore, by comparing these identified variants with our previously obtained expression quantitative trait loci (eQTL) data, 27 of these 49 variants were associated with SMC gene expression levels. Finally, we performed CRISPRi experiments on 8 variants comprising 9 variant-gene pairs, rs35976034 ( MAP1S ), rs4888409 ( CFDP1 ), rs73193808 ( MAP3K7CL ), rs67631072 ( INPP5B/FHL3 ), rs1651285 ( SNHG18 ), rs17293632 ( SMAD3 ), rs2238792 ( ARVCF ), rs4627080 ( NRIP3 ), to confirm their regulatory potential of nearby gene expression. Taken together, our results comprehensively fine-map the causal variants that confer increased risk of CAD through their effects on vascular smooth muscle cells.
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Barbera et al. (2024) studied Coronary Artery Disease (n=6). Massively parallel reporter assays (lentiMPRAs) and CUT&RUN epigenome profiling vs. Scramble control sequences and non-risk alleles was evaluated on Identification of candidate causal CAD-associated variants showing significant enhancer activity and allelic imbalance. Integration of massively parallel reporter assays and epigenome profiling in vascular smooth muscle cells identified 122 candidate variants with significant enhancer activity and allelic imbalance.
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