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Background: Heart Failure (HF) is driven by the interactions of multiple genetic, epigenetic, and environmental factors both within and between the cell types of the heart. Our lab uses the Hybrid Mouse Diversity Panel (HMDP), a large cohort of inbred mouse strains, to perform systems genetics analyses of isoproterenol-induced cardiac hypertrophy and failure by leveraging the benefits of a curated model organism population to identify key drivers of phenotype. We are now expanding this study into the DNA methylome, which has been convincingly linked to cardiac-associated phenotypic changes in prior studies. Methods and Results: Using Reduced Representational Bisulfite Sequencing, we profiled left ventricular tissue samples from 88 HMDP strains subjected to isoproterenol challenge (30 mg/kg/day for 21 days) and matched control animals. We identified nearly 170,000 CpGs whose methylation status varies across the HMDP and 179 significant associations (FDR of 5%) between CpG methylation and phenotypic variation using the epigenome-wide association study algorithm MACAU, including 37 associations linking CpG methylation in unchallenged hearts to 19 post-challenge phenotypes. To identify high-confidence candidate genes, we combined our loci with data from the Wellcome Trust Mouse Genomes Resource, transcriptomic and metabolomic data from the HMDP, Hi-C data, and cell-type-specific gene expression and methylation data from healthy and failing mouse hearts. We are systematically querying the resulting 78 candidates using in silico and in vitro approaches. These genes include Mospd3 , which is associated with right ventricular hypertrophy and whose knockdown in vitro results in reduced cardiomyocyte hypertrophy and changes to hypertrophy-related gene expression. Also observed were Atp9a , whose expression levels are associated with significant global DNA methylation changes between control and ISO-treated animals and whose knockdown likewise causes a reduction in observed cellular hypertrophy, and Mdga1 , whose promoter methylation status is linked to changes in 5% of expressed genes of the heart during heart failure. Further analysis and in vivo study of these loci will further our understanding of the role of DNA methylation in heart failure.

We previously reported a study of heart failure in a large cohort of inbred mouse strains, the Hybrid Mouse Diversity Panel (HMDP), treated with the beta-adrenergic agonist isoproterenol, which identified over 30 genome-wide significant loci for heart failure-related traits. Our approach combined systems-level tools with the benefits of a curated model organism population to identify genetic variations that drive heart failure. We now expand this study into the epigenome. Recent research has demonstrated that DNA methylation affects the progression of cardiovascular phenotypes. This research suggests that DNA methylation may serve as an additional marker of genes involved in heart failure-associated phenotypes. Using Reduced Representational Bisulfite Sequencing, we profiled left ventricular tissue samples from 88 strains of the HMDP both before and after isoproterenol challenge (30 mg/kg/day for 21 days). We identified approximately 168,000 CpGs that vary across the panel and associated them with a set of phenotypes in both control and treated animals using the epigenome-wide association study (EWAS) algorithm MACAU. 179 significant associations were recovered at an FDR of 5%, including loci that associated pre-treatment CpG methylation with 19 different post-treatment phenotypes. By combining these EWAS loci with information from the Wellcome Trust Mouse Genomes Resource and prior work done in the heart failure HMDP, we identify several high-confidence candidate genes, including Coro1a , a gene whose pre-treatment promoter methylation status predicts post-treatment wall thickening and Eprs , which predicts right ventricular weight post-treatment. Mospd3 , a gene that was associated with right ventricular weight post-treatment in both EWAS and GWAS analyses was studied further using neonatal rat ventricular myocytes. This in vitro work demonstrates that Mospd3 knockdown results in reduced cellular hypertrophy and changes to hypertrophy-related gene expression. Further analysis of the EWAS loci using in vitro and in vivo techniques will likely validate additional genes and elucidate how DNA methylation acts to regulate pathways underlying heart failure.

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. As a potential epigenetic biomarker, DNA methylation differs between healthy and diseased hearts. However, its association according to disease severity has not yet been studied. Here, we sought to investigate how DNA methylation (DNAm) differs across HF disease severity, and study the use of a DNMT methyltransferase inhibitor RG108 on DNAm and its effect on heart function. A fixed dose of Isoprenaline (ISO), or saline control (SAL), administered to a hybrid mouse diversity panel (HMDP) consisting of 85 classical and recombinant inbred mouse strains produced a range of cardiac hypertrophy and/or LV dilatation. Left ventricles were harvested and subjected to genome-wide cardiac DNAm profiling by Reduced Representation Bisulfite Sequencing (RRBS). Unsupervised clustering of the top 1% most variable CpG methylation segregated strains to their genetic origin. Disregarding strain-specific methylation differences, differential methylation between ISO and SAL unexpectedly categorised mice into mild and severe disease responders. In the severe-responder strain BTBRT, the pharmacological DNMT methyltransferase inhibitor, RG108, rescued disease from ISO-response, with accompanying evidence of gene expression recovery. This work establishes the range of cardiac differential DNAm correlating according to disease severity. It displays the involvement of DNA methylation-dependent gene expression changes that turns out to be unique, despite different mouse strain backgrounds. This gives further proof of principle that cardiac DNAm changes represent novel biomarkers for disease stratification and consequent targeted therapy.

Identifying genetic markers for heterogeneous complex diseases such as heart failure has been challenging, and may require prohibitively large cohort sizes in genome-wide association studies (GWAS) in order to meet genome-wide statistical significance. On the other hand, chromatin quantitative trait loci (QTL), elucidated by direct epigenetic profiling of specific human tissues, may contribute towards prioritising sub-threshold variants for disease-association. Here, we captured non-coding genetic variants by performing enhancer H3K27ac ChIP-seq in 70 human control and end-stage failing hearts, mapping out a comprehensive catalogue of 47,321 putative human heart enhancers. 3,897 differential acetylation peaks (FDR 5%) pointed to pathways altered in heart failure (HF). To identify cardiac histone acetylation QTLs (haQTLs), we regressed out confounding factors including HF disease status, and employed the G-SCI test to call out 1,680 haQTLs (FDR 10%). RNA-seq performed on the same heart samples proved a subset of haQTLs to have significant association also to gene expression (expression QTLs), either in cis (180), or through long range interactions (81), identified by Hi-C and Hi-ChIP performed on a subset of hearts. We validated 2 of the haQTLs through base editing to show that the presence of those SNPs indeed affects gene expression in human embryonic stem cells-derived cardiomyocytes. Furthermore, a concordant relationship between the gain or disruption of transcription factor (TF) binding motifs, inferred from alternative alleles at the haQTLs, implied a surprising direct association between these specific TF and local histone acetylation in human hearts. Finally, 62 unique loci were identified by colocalisation of haQTLs with heart-related GWAS datasets. Disease-association for these new loci may indeed be mediated through modification of H3K27-acetylation enrichment and their corresponding gene expression differences.

Systems biology approaches to studying heart failure in humans are hampered by numerous environmental factors and inciting incidents which combine to complicate the application of standard population-based tools and algorithms to the syndrome. We recently reported a study of heart failure in a large cohort of inbred mouse strains (the Hybrid Mouse Diversity Panel; HMDP) treated with the beta-adrenergic agonist isoproterenol. We demonstrated that it was possible to combine systems-level tools with the benefits of an animal model to capture and identify numerous genetic variations which drive heart failure. Recent research on the epigenome has identified changes to DNA methylation which affect the progression of cardiovascular diseases and suggests that DNA methylation may serve as an important additional marker or even driver of genes involved in heart failure-associated phenotypes. We have supplemented our prior study by completing reduced representational bisulfite sequencing on 88 strains from our panel both with and without catecholamine challenge. We have identified 75,000 CpGs which vary among the strains of the HMDP across the genome. Each CpG was mapped to the genome using GWAS to identify methylation quantitative trait loci (mQTLs). These mQTLs were then grouped together to identify mQTL hotspots, regions on the genome which regulate a sizable fractions of all observed CpGs. We then overlapped these hotspots with hotspots which regulate the expression of gene transcripts. Three genomic regions were identified as multi-omic master regulators which affect both DNA methylation and gene expression for over 5% of the expressed transcripts and varying CpGs. Closer examination of these loci identified the serine peptidase inhibitor Serpina3n as a likely candidate gene for the regulation of DNA methylation, gene expression and cardiac phenotypes. Subsequent in vitro and in vivo work demonstrate that Serpina3n knockdown results in reduced cellular hypertrophy and changes to hypertrophy-related gene expression. Further analysis of the other master regulatory regions will likely reveal additional genes which will improve our understanding of how DNA methylation acts to regulate pathways underlying heart failure.