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Identification of non-cardiomyocytes marker genes in patients with diabetes and cardiomyopathy through single-cell analysis.

Identification of non-cardiomyocytes marker genes in patients with diabetes and cardiomyopathy through single-cell analysis.

期刊: PloS one 日期: 2026-01-01 PMID: 42247398 DOI: 10.1371/journal.pone.0351057 浏览: 48
作者: Yu W, Chen H, Shi L, Gao G, Wang H
W, Y., H, C., L, S., G, G., & H, W. (2026). Identification of non-cardiomyocytes marker genes in patients with diabetes and cardiomyopathy through single-cell analysis.. PloS one. https://doi.org/10.1371/journal.pone.0351057
W Y, H C, L S, G G, H W. Identification of non-cardiomyocytes marker genes in patients with diabetes and cardiomyopathy through single-cell analysis.. PloS one. 2026; doi: 10.1371/journal.pone.0351057
W Y, H C, L S, et al. Identification of non-cardiomyocytes marker genes in patients with diabetes and cardiomyopathy through single-cell analysis.[J]. PloS one. 2026. DOI: 10.1371/journal.pone.0351057.
@article{w2026,
  author = {Yu W and Chen H and Shi L and Gao G and Wang H},
  title = {Identification of non-cardiomyocytes marker genes in patients with diabetes and cardiomyopathy through single-cell analysis.},
  journal = {PloS one},
  year = {2026},
  doi = {10.1371/journal.pone.0351057},
  note = {PMID: 42247398},
}
TY  - JOUR
AU  - Yu W
AU  - Chen H
AU  - Shi L
AU  - Gao G
AU  - Wang H
TI  - Identification of non-cardiomyocytes marker genes in patients with diabetes and cardiomyopathy through single-cell analysis.
T2  - PloS one
PY  - 2026
DO  - 10.1371/journal.pone.0351057
AN  - PMID:42247398
ER  - 

摘要

BACKGROUND: Diabetic cardiomyopathy (DCM) is a diabetes-related myocardial disorder causing fibrosis, hypertrophy, and progressive diastolic and systolic dysfunction. This study aims to explore how metabolic, inflammatory, and fibrotic mechanisms in non-cardiomyocytes drive DCM to reveal new therapeutic targets. METHODS: Single-cell RNA sequencing (scRNA-seq) was performed to investigate the role of non-cardiomyocytes in DCM, enabling the identification of cell types, gene expression dynamics, and intercellular communication networks in patients with type 2 diabetes. The scRNA-seq data were obtained from the GEO to investigate cell-type-specific contributions and heterogeneity across tissues. Metabolic pathway scores were calculated using scMetabolism. Moreover, cell trajectory analysis and cellular communication studies were performed to examine shared and disease-specific cell populations in diabetes and cardiomyopathy. CCK-8, colony formation, Transwell migration and invasion assays were preformed to explore the function of PTPRC in HUVECs. RESULTS: Using SingleR annotation, we identified eight distinct cell types, with NK cells and smooth muscle cells representing the shared cell populations across both diseases. Cell trajectory analysis revealed three distinct branches based on gene expression over pseudotime, and the top differentially expressed genes in each cell type clustering into six categories. Metabolic pathway analysis predicted that epithelial cells, macrophages, and neurons as the most metabolically active across multiple pathways, highlighting metabolic heterogeneity among patient samples. Additionally, four key signaling pathways associated with NK cells and smooth muscle cells were predicted to emphasize the divergence in gene expression across cell types. PTPRC is implicated in diabetes and cardiomyopathy and functions as a positive regulator of HUVEC viability, clonogenic growth, migration, and invasion. CONCLUSION: This study demonstrates significant heterogeneity among non-cardiomyocytes in patients with diabetes and cardiomyopathy, highlighting the need for targeted therapeutic interventions to address these differences.

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