Dilated cardiomyopathy (DCM) is a key cause of heart failure, marked by enlargement and dysfunction of the left ventricle. While some genetic factors are known, the contribution of non-coding variants, particularly in regulatory regions, remains largely unexplored. This study integrates chromatin interaction maps and multi-omics data to prioritize candidate regulatory elements and genes associated with DCM. Using Activity-by-Contact (ABC) and Capture Hi-C Omnibus Gene Score (COGS) methods, we compare DCM and control left ventricular (LV) tissues to identify gene-regulatory interactions underlying DCM pathology.
We generated 14.4 billion-HiC reads enabling the detection of 35.5 ± 10.7 million genomic (cis-)interactions in average. PC-HiC experiments generated 5.6 billion reads that we used to identify interacting regions of 18764 promoters. The ABC model was applied to Hi-C data from a cohort of left ventricle heart tissue samples including controls (n=9), and DCM (n=13), incorporating ATAC-seq and H3K27ac ChIP-seq data from ENCODE. This allowed for a comparison of enhancer activity and chromatin interactions, identifying significant enhancer-gene pairs specific to DCM and control conditions. The COGS pipeline was used to analyze PC-HiC data from DCM and control LV tissues, integrating two large DCM GWAS datasets to calculate gene prioritization scores. Besides, random-primer based RNA-Seq, WGS and methylation assays (Infinium EPIC) were performed in the same cohort. This approach enabled the identification of candidate genes likely influenced by DCM-associated regulatory variants, SNPs detected on the GWAS studies, highlighting differences in regulatory landscapes between DCM and control samples.
ABC analysis identified 128709 enhancer-gene interactions in DCM tissue, displaying elevated H3K27ac and ATAC-seq signals in DCM tissues, suggesting active regulatory roles. In control LV tissue, 109771 enhancer-gene pairs were identified, of which 5.2% of the genes showed no overlap with DCM-specific interactions, indicating DCM-specific regulatory shifts. The COGS prioritization approach highlighted 68 genes by correlating fine mapped SNP signals from the GWAS DCM-trait to gene coding regions, using the promoter interacting regions. The prioritized genes included known, such as: FLNC, BAG3 and LMNA, which are associated with cardiac muscle integrity and sarcomere contraction; as well as novel candidates. Both ABC and COGS approaches converged on relevant locus, where enhancer activity corresponded to increased expression of genes. Pathway enrichment analysis showed that 39.7% of prioritized genes mapped to pathways essential for cardiac muscle contraction, while 22.1% were linked to inflammatory signalling and response, underscoring their relevance to DCM pathology.
By integrating ABC and COGS approaches with chromatin interaction data from both DCM and control LV tissues, this study identifies regulatory elements and candidate genes implicated in DCM, emphasizing disease-specific enhancer-promoter interactions. These findings highlight non-coding regions as key contributors to DCM, offering insights into regulatory mechanisms as potential therapeutic targets for heart disease.
