ArticleJournal of translational medicine2025
Comprehensive analysis of scRNA-seq and bulk RNA-seq reveals the non-cardiomyocytes heterogeneity and novel cell populations in dilated cardiomyopathy.
Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Natural killer (NK) cells with downregulated activating receptors and IL-10 production promote Trypanosoma cruzi T-cell responses in subjects in the Chronic phase of Trypanosoma cruzi infection: An exploratory immunological analysis.PLoS neglected tropical diseases · 2026Article
- Review
- Cardiac fibroblasts in myocardial injury and heart failure.European heart journal · 2026Review
- Systems Biology Identifies TARS2 as a Cardiomyocyte Regulator of Mitochondrial Oxidative Stress in Dilated Cardiomyopathy.JACC. Basic to translational science · 2026Article
- scDEBGCL: a deep embedding approach based on bipartite graph contrastive learning for single-cell RNA-seq data.BMC biology · 2026Article
- Correction to: Comprehensive analysis of scRNA-seq and bulk RNA-seq reveals the non-cardiomyocytes heterogeneity and novel cell populations in dilated cardiomyopathy.Journal of translational medicine · 2026Article
- Leveraging Single-Cell Technologies to Advance Understanding of Myocardial Disease.Circulation research · 2026Review
- Identification of non-cardiomyocytes marker genes in patients with diabetes and cardiomyopathy through single-cell analysis.PloS one · 2026Article
- Identification and validation of circadian rhythm and astrocyte-associated diagnostic and therapeutic model for cirrhosis encephalopathy patients via integrative bioinformatic pipelines andFrontiers in neuroscience · 2026Article
- Single-cell RNA sequencing analysis revealed a potential association between ELK3 expression and the progression of multiple myeloma.Frontiers in immunology · 2026Article
- Integrative Transcriptomic-Histological Analysis in Dilated Cardiomyopathy Unveils FGFR1 Inhibition as Anti-Cardiac Fibrotic and Cardioprotective Therapy.JACC. Basic to translational science · 2025Article
- Understanding of the characteristics of fibroblasts in ischemic cardiomyopathy using single-nucleus RNA sequencing.Scientific reports · 2025Article
- Inflammatory and fibrotic signaling pathways mediated by cardiac macrophages in atrial fibrillation.Frontiers in cardiovascular medicine · 2025Review
- Single-cell multi-omics for precision cardiovascular and longevity medicine: from methods to clinical translation.Frontiers in aging · 2025Review
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
Abstract
backgroundDilated cardiomyopathy (DCM) is one of the most common causes of heart failure. Infiltration and alterations in non-cardiomyocytes of the human heart involve crucially in the occurrence of DCM and associated immunotherapeutic approaches.
methodsWe constructed a single-cell transcriptional atlas of DCM and normal patients. Then, the xCell algorithm, EPIC algorithm, MCP counter algorithm, and CIBERSORT method were applied to identify DCM-related cell types with a high degree of precision and specificity using RNA-seq datasets. We further analyzed the heterogeneity among cell types, performed trajectory analysis, examined transcription factor regulatory networks, investigated metabolic heterogeneity, and conducted intercellular communication analysis. Finally, we used bulk RNA-seq data to confirm the roles of M2-like2 subpopulations and GAS6 in DCM.
resultsWe integrated and analyzed Single-cell sequencing (scRNA-seq) data from 7 DCM samples and 3 normal heart tissue samples, totaling 70,958 single-cell data points. Based on gene-specific expression and prior marker genes, we identified 9 distinct subtypes, including fibroblasts, endothelial cells, myeloid cells, pericytes, T/NK cells, smooth muscle cells, neuronal cells, B cells, and cardiomyocytes. Using machine learning methods to quantify bulk RNA-seq data, we found significant differences in fibroblasts, T cells, and macrophages between DCM and normal samples. Further analysis revealed high heterogeneity in tissue preference, gene expression, functional enrichment, immunodynamics, transcriptional regulatory factors, metabolic changes, and communication patterns in fibroblasts and myeloid cells. Among fibroblast subpopulations, proliferative F3 cells were implicated in the fibroblast transition process in DCM, while myofibroblast F6 cells promoted the fibroblast transition to a late cell state in DCM. Additionally, two subpopulations of M2 macrophages, M2-like1 and M2-like2, were identified with distinct features. The M2-like2 cell subpopulation, which was enriched in glycolysis and fatty acid metabolism, involved in inflammation inhibition and fibrosis promotion. Cell‒cell communication analysis indicated the GAS6-MERTK axis might exhibit interaction between M2 macrophage and M2-like1 macrophage. Furthermore, deconvolution analysis for bulk RNA-seq data revealed a significant increase in M2-like2 subpopulations in DCM, suggesting a more important role for this cell population in DCM.
conclusionsWe revealed the heterogeneity of non-cardiomyocytes in DCM and identified subpopulations of myofibroblast and macrophages engaged in DCM, which suggested a potential significance of non-cardiomyocytes in treatment of DCM.
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