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Integrated Bioinformatics Analysis Identifies Vascular Endothelial Cell-Related Biomarkers for Hypertrophic Cardiomyopathy

by Ying Wang1, Weijun Zhang1, Fei Cai1, Yong Tao2,*

1 Department of Cardiology, Nantong Third People’s Hospital and the Third People’s Hospital Affiliated to Nantong University, Nantong, 226000, China
2 Department of Intensive Care Unit, Tumor Hospital Affiliated to Nantong University, Nantong Tumor Hospital, Nantong, 226300, China

* Corresponding Author: Yong Tao. Email: email

Congenital Heart Disease 2024, 19(6), 653-669. https://doi.org/10.32604/chd.2025.060406

Abstract

Background: Previous studies combined integrated scRNA-seq with bulk RNA data to screen biomarkers for cardiomyopathy. This study extended this approach to identify biomarkers specific for hypertrophic cardiomyopathy (HCM). Methods: Datasets GSE36961, GSE130036, GSE249925 and GSE203274 were analyzed in this study. ScRNA-seq analysis was employed to identify distinct cell populations. Differentially expression analysis was conducted to screen vascular endothelial cells (VECs)-related feature genes. After calculating VECs score, WGCNA was used to correlate gene modules with the VECs score. Key HCM biomarkers were determined using random forest analysis, and LASSO regression analyses to construct a diagnostic model based on their diagnostic efficacy and differential expression. Results: Our analysis identified nine distinct cell populations, with VECs accounting for a notably higher proportion in HCM samples. Genes associated with the VECs were enriched in the pathways related to blood vessel, immunity and cardiac function. After classifying significant gene modules based on VEC-related genes, a strong correlation between the blue module and the VECs score was detected. Notably, genes in the blue module were enriched in the pathways related to metabolism and immune response. Key genes with a high expression in HCM were determined by intersecting differentially expressed genes (DEGs) in HCM with those in the blue module. Finally, random forest analysis and LASSO regression analysis identified five central hub genes for the diagnosis of HCM, including Dual Specificity Tyrosine Phosphorylation Regulated Kinase 1B (DYRK1B), Growth Arrest and DNA Damage Inducible Alpha (GADD45A), Influenza Virus NS1A Binding Protein (IVNS1ABP), Leiomodin 2 (LMOD2), and Pleckstrin Homology Like Domain Family B Member 2 (PHLDB2). Conclusion: Collectively, our study discovered novel VEC-related biomarkers for HCM and comprehensively examined the mechanisms underlying the pathogenesis of HCM.

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APA Style
Wang, Y., Zhang, W., Cai, F., Tao, Y. (2024). Integrated bioinformatics analysis identifies vascular endothelial cell-related biomarkers for hypertrophic cardiomyopathy. Congenital Heart Disease, 19(6), 653–669. https://doi.org/10.32604/chd.2025.060406
Vancouver Style
Wang Y, Zhang W, Cai F, Tao Y. Integrated bioinformatics analysis identifies vascular endothelial cell-related biomarkers for hypertrophic cardiomyopathy. Congeni Heart Dis. 2024;19(6):653–669. https://doi.org/10.32604/chd.2025.060406
IEEE Style
Y. Wang, W. Zhang, F. Cai, and Y. Tao, “Integrated Bioinformatics Analysis Identifies Vascular Endothelial Cell-Related Biomarkers for Hypertrophic Cardiomyopathy,” Congeni. Heart Dis., vol. 19, no. 6, pp. 653–669, 2024. https://doi.org/10.32604/chd.2025.060406



cc Copyright © 2024 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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