Abstract Wed114: Population-scale Evaluation of Cardiac Cell Type Composition Identifies Novel Drivers of Heart Phenotypes in the Context of Hypertrophy and Failure

Background: Heart failure (HF) is a leading global cause of mortality, driven by both genetic and environmental factors. The role of cardiac cell-type composition (CCC) – the relative proportions of different cell types in the heart – in HF remains incompletely understood. In other organs, cell composition is often studied using single cell sequencing, yet this approach is limited in the heart due to the large size and variable nuclearity of cardiomyocytes (CMs) and still remains prohibitively expensive to perform on large cohorts of individuals. Understanding the genetics of CCC would lead to new avenues for research in HF. Methods and Results: A total of 425 mice from 71 strains of the Collaborative Cross, a genetic reference population with genetic diversity comparable to human populations, were treated with 30ug/g/day of isoproterenol (ISO) via osmotic minipump for three weeks to induce HF. Bulk transcriptomes were generated and analyzed using an algorithmic pipeline that integrated single nucleus sequencing data with the bulk transcriptomes to estimate the proportions of five major cardiac cell types. We observed significant variability in CCC, with CM RNA comprising 79% (+/- 5%) of the cardiac RNA in healthy mice. After ISO treatment, some susceptible strains exhibited up to a 25% reduction in CM RNA and a 7.2-fold increase in fibroblast RNA. To ascertain genetic contributions to CCC, we performed a genome-wide association study (GWAS) on CCC phenotypes. Significant loci (P<2E-5) were identified for each cell type. These include five loci which regulate baseline CM abundance. A notable locus on chromosome 11 (P= 9E-6) overlaps with Adamts2 , a metalloproteinase previously identified by our group as a major driver of HF phenotypes. Strikingly, we also observe that baseline CM abundance was negatively correlated with cardiac hypertrophy afer ISO treatment (R = -0.35, P= 0.0003), suggesting a potential link between CCC in healthy individuals and future risk of HF. Conclusion: Our results show that CCC is a complex trait influenced by known HF-associated genes. This study highlights the potential of analyzing bulk cardiac transcriptomes to uncover novel genetic regulators and underlying mechanisms of CCC and HF pathology.