Abstract
Introduction: Hypertrophic cardiomyopathy (HCM) is a common inherited cardiovascular disease, often resulting in left ventricular outflow tract obstruction, relieved by surgical myectomy. Current treatments are largely palliative and do not target the root causes. Understanding the molecular drivers of the disease could lead to alternative treatment strategies through identification of novel therapeutic targets. Methods: We performed single nuclei RNA-sequencing (snRNA-seq) on thousands of nuclei from 9 patient myectomy samples and septal tissue from 4 unused donor hearts selected randomly without regard to genotype to identify the cell populations and determine the gene expression patterns in individual cells. Each sample was processed individually using Seurat v3 for quality control and normalization. Next, all 13 samples were integrated into a combined dataset for clustering and differential gene expression analysis to identify markers specific to each cluster and to assign cell identities. Results: Our results revealed several clusters of cardiomyocytes with differences in sarcomeric and metabolic gene expression. Several fibroblast populations were also observed. Numerous genes were differentially expressed between the HCM and normal samples. For example, RARRES1 expression was observed in many of the fibroblast populations in the normal samples, but was absent in the HCM samples. RARRES1 is involved in regulating fatty acid metabolism and autophagy, both of which are altered in HCM. Additionally, expression of PLA2G2A was absent in the HCM samples but was present in almost every cell type in the normal controls. PLA2G2A is involved in suppression of RTK mediated hypertrophic signaling, impacts lipid signaling, and has tumor suppressor properties. Thus, both RARRES1 and PLA2G2A may represent novel targets in HCM. Conclusions: This approach reveals novel potential therapeutic targets within common final HCM pathological pathways independent of genotype that have the potential to guide development of alternative treatment strategies. Further analysis of larger datasets using this approach will likely identify even more common pathway targets and identify additional common mechanisms in the pathogenesis of obstructive HCM.
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