Identifying genetic markers for heterogeneous complex diseases such as heart failure is challenging and requires prohibitively large cohort sizes in genome-wide association studies to meet the stringent threshold of genome-wide statistical significance. On the other hand, chromatin quantitative trait loci, elucidated by direct epigenetic profiling of specific human tissues, may prioritize subthreshold variants for disease association.
Here, we captured noncoding genetic variants by performing epigenetic profiling for enhancer H3K27ac chromatin immunoprecipitation followed by sequencing in 70 human control and end-stage failing hearts. 3879 differential acetylation peaks pointed to pathways altered in heart failure. To identify cardiac histone acetylation quantitative trait loci (haQTLs), we regressed out confounding factors including heart failure disease status and used the G-SCI test1 to call out 1680 haQTLs (FDR, 10%). RNA sequencing performed on the same heart samples proved a subset of haQTLs to have significant association also to gene expression (expression quantitative trait loci), either in cis (180) or through long-range interactions (81), identified by Hi-C and HiChIP performed on a subset of hearts.
In summary, this haQTL dataset should now prove useful for discovering more genetic variants if integrated with further heart-related GWAS. The approach of chromatin QTL and 3-dimensional connectome analyses in disease-relevant tissue promises not just to resolve the identity of functional genetic variants, taking cardiac genomics to its next phase of discovery. However, target genes with correlated expression changes can be accordingly implicated to represent critical pathways for new disease therapy.