The Impact Of Dilated Cardiomyopathy on Cell-Type Diversity and Gene Expression

Abstract

Background: Dilated cardiomyopathy (DCM) is a leading cause of heart failure characterised by enlarged ventricles and reduced cardiac function. Despite advancements, understanding the cellular and molecular processes related to DCM remains challenging. Objectives: This study uses single-cell transcriptomics to identify unique gene expression patterns and cellular diversity in DCM to improve patient stratification and clinical care. Methods: Publicly available single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq) data from normal cardiac tissues and DCM patients were obtained from the GEO dataset GSE183852. The analysis included 269,794 samples from 45 participants, comprising 36,488 DCM cells, 66,669 DCM nuclei, 12,554 healthy cells, and 154,083 healthy nuclei. Data analysis involved quality control, normalisation, data integration, dimensionality reduction, clustering, DE analysis, and Gene set enrichment analysis (GSEA). Results: Principal component analysis identified 50 principal components. Unsupervised cluster annotation revealed 21 cell types in nuclei samples and 15 in cell samples. The analysis showed an underrepresentation of cardiomyocytes in the scRNA samples. Cell composition analysis demonstrated significant differences in cell type abundance between DCM and healthy tissues, including an increased ratio of fibroblasts in DCM and a decrease in cardiomyocytes. DE analysis identified several significant differentially expressed genes (DEGs), MYH6. DEGs were shown to overlap with well-known DCM genes from the PannelApp list. GSEA validated the enrichment of our genes in DCM-associated pathways; moreover, a strong trend of downregulation of many critical pathways was found across many cell types, including metabolic and energy pathways. Conclusion: Despite some limitations of single-cell technology in preserving certain cardiac cell types, the analysis revealed significant differences in cell type abundance and DE profile between healthy and DCM samples. This discovery of distinct gene expression patterns in DCM samples compared to healthy individuals presents potential diagnostic and therapeutic targets, offering hope for improved patient outcomes.