Integrative multi-omics and machine learning identify mechanical stimulus-related genes and immune microenvironment remodeling in heart failure

Background Heart failure (HF) is a leading cause of global morbidity and mortality, driven by complex pathophysiological processes including abnormal mechanical stress and immune microenvironment remodeling. Although mechanical stimulus is known to trigger maladaptive cardiac remodeling, the systematic role of mechanical stimulus-related genes (MSRGs) in HF diagnosis and immune modulation remains poorly defined. This study aims to identify MSRG-based diagnostic biomarkers, characterize molecular subtypes, and explore their cellular localization and immune microenvironment interactions in HF. Methods Bulk transcriptomic data and MSigDB-curated MSRGs were analyzed. Differential expression screening identified MSRGs altered between HF and healthy specimens. Three algorithms—Random Forest, LASSO, and SVM-RFE—were jointly applied to select diagnostic biomarkers and build a nomogram. Consensus clustering defined MSRG-based subtypes, with immune profiles compared across groups. Single-cell sequencing localized key biomarkers in cardiac tissues. A transverse aortic constriction (TAC)-induced rat HF model served for in vivo validation via RT-qPCR, Western blotting, and immunohistochemistry. Results A total of 53 MSRG-related DEGs were identified, from which 11 core diagnostic biomarkers were selected. The nomogram model showed high predictive performance. Consensus clustering revealed two distinct HF subtypes: Cluster A exhibited enhanced metabolic and homeostatic pathways, while Cluster B showed pronounced extracellular matrix remodeling and fibrotic features, with differential immune infiltration. Single-cell analysis demonstrated CASP1 enrichment in macrophages/monocytes and PTN/MDK enrichment in fibroblasts. In vivo validation confirmed significant upregulation of PTN, MDK, and CASP1 at both mRNA and protein levels in TAC hearts, alongside elevated pro-inflammatory cytokines (IL-6, IL-1β) and fibrotic markers, linking mechanical stimulus-related genes to local inflammation and adverse remodeling. Conclusion MSRGs serve as robust diagnostic biomarkers for HF and enable the identification of two molecular subtypes with distinct immune microenvironment and biological pathway profiles. The CASP1-MDK-PTN axis emerges as a potential pathogenic cascade connecting mechanical stress to inflammatory and fibrotic remodeling. These findings provide a framework for early molecular subtyping, improved risk stratification, and targeted immunomodulatory therapy in HF.

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Journal
Frontiers in Cardiovascular Medicine
Published
2026-10-28
DOI
https://doi.org/10.3389/fcvm.2026.1953634
Primary Topic
Cardiac Fibrosis and Remodeling
Type
article
Field-Weighted Citation Impact
0.00

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article

Integrative multi-omics and machine learning identify mechanical stimulus-related genes and immune microenvironment remodeling in heart failure

Cheng Zhang, Linna Zhao, Aiying Li, Jiahuan Sun et al.
6 links
Frontiers in Cardiovascular Medicine
Cardiac Fibrosis and Remodeling
article

Integrative multi-omics and machine learning identify mechanical stimulus-related genes and immune microenvironment remodeling in heart failure

Cheng Zhang, Linna Zhao, Aiying Li, Jiahuan Sun, Chuang Zhang, Xiaodan Wang
article en

Abstract

Background Heart failure (HF) is a leading cause of global morbidity and mortality, driven by complex pathophysiological processes including abnormal mechanical stress and immune microenvironment remodeling. Although mechanical stimulus is known to trigger maladaptive cardiac remodeling, the systematic role of mechanical stimulus-related genes (MSRGs) in HF diagnosis and immune modulation remains poorly defined. This study aims to identify MSRG-based diagnostic biomarkers, characterize molecular subtypes, and explore their cellular localization and immune microenvironment interactions in HF. Methods Bulk transcriptomic data and MSigDB-curated MSRGs were analyzed. Differential expression screening identified MSRGs altered between HF and healthy specimens. Three algorithms—Random Forest, LASSO, and SVM-RFE—were jointly applied to select diagnostic biomarkers and build a nomogram. Consensus clustering defined MSRG-based subtypes, with immune profiles compared across groups. Single-cell sequencing localized key biomarkers in cardiac tissues. A transverse aortic constriction (TAC)-induced rat HF model served for in vivo validation via RT-qPCR, Western blotting, and immunohistochemistry. Results A total of 53 MSRG-related DEGs were identified, from which 11 core diagnostic biomarkers were selected. The nomogram model showed high predictive performance. Consensus clustering revealed two distinct HF subtypes: Cluster A exhibited enhanced metabolic and homeostatic pathways, while Cluster B showed pronounced extracellular matrix remodeling and fibrotic features, with differential immune infiltration. Single-cell analysis demonstrated CASP1 enrichment in macrophages/monocytes and PTN/MDK enrichment in fibroblasts. In vivo validation confirmed significant upregulation of PTN, MDK, and CASP1 at both mRNA and protein levels in TAC hearts, alongside elevated pro-inflammatory cytokines (IL-6, IL-1β) and fibrotic markers, linking mechanical stimulus-related genes to local inflammation and adverse remodeling. Conclusion MSRGs serve as robust diagnostic biomarkers for HF and enable the identification of two molecular subtypes with distinct immune microenvironment and biological pathway profiles. The CASP1-MDK-PTN axis emerges as a potential pathogenic cascade connecting mechanical stress to inflammatory and fibrotic remodeling. These findings provide a framework for early molecular subtyping, improved risk stratification, and targeted immunomodulatory therapy in HF.

Frontiers in Cardiovascular MedicineVol. 13
Hebei University of Chinese Medicine (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 11%
Cardiac Fibrosis and Remodeling
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