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ORIGINAL RESEARCH article

Front. Immunol.

Sec. Molecular Innate Immunity

Identification of MTURN as a Trained Immunity-Related Biomarker for Heart Failure via Integrative Transcriptomic Machine Learning Analysis and Experimental Validation

Provisionally accepted
  • 1University of Cincinnati, Cincinnati, United States
  • 2Wuhan University Renmin Hospital, Wuhan, China
  • 3Ondokuz Mayis Universitesi, Samsun, Türkiye
  • 4London Health Sciences Centre, London, Canada

The final, formatted version of the article will be published soon.

Background: Heart failure (HF) is a global health burden marked by high morbidity and limited treatment efficacy across subtypes. The lack of reliable molecular biomarkers for heart failure impedes personalized therapy. Emerging evidence suggests that macrophage-trained immunity drives chronic inflammation and cardiac remodeling, highlighting immune-related genes as promising biomarkers. Methods: We integrated transcriptomic data from five independent HF cohorts and one macrophage-trained immunity model. Differential expression genes (DEGs) analysis, weighted gene co-expression network analysis (WGCNA), immune infiltration profiling, and six machine-learning algorithms were applied to screen immune-related candidate genes. Functional relevance was assessed by gene set enrichment analysis (GSEA) and single-cell RNA-seq of human cardiac tissue. Finally, we established a THP-1-derived macrophage trained immunity model to validate the paracrine effects of macrophage Maturin (MTURN) and Piezo-type mechanosensitive ion channel component 1 (PIEZO1) in cardiomyocytes. Results: Seven hub genes were identified from HF-DEGs, the trained immunity transcriptional signature, and WGCNA co-expression modules. Among them, MTURN, an evolutionarily conserved regulator of differentiation and inflammation, emerged as the most robust candidate, showing consistent upregulation in HF samples across all cohorts with superior diagnostic performance. Importantly, GSEA linked MTURN to innate immune activation and adhesion/signaling pathways. Single-cell RNA-seq analyses of human cardiac tissue revealed MTURN enrichment in cardiac macrophages with a progressive increase along pseudotime. Experimentally, trained immunity macrophages displayed an elevation of glycolytic and inflammatory markers together with increased MTURN and PIEZO1. Accordingly, the conditioned medium collected from such trained macrophages could upregulate expression of HF markers (i.e., NPPA/B) in AC16 cardiomyocytes. Conclusion: Multi-cohort, single-cell RNA-seq, and experimental data collectively suggest MTURN as a trained immunity-related biomarker for the diagnosis of heart failure with a potential link to PIEZO1-mediated cardiac remodeling.

Keywords: biomarker, Heart Failure, machine learning, MTURN, trained immunity

Received: 04 Nov 2025; Accepted: 30 Jan 2026.

Copyright: © 2026 Yang, Li, Pan, Wang, Huang, Kesten, Peng and Fan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Guo-Chang Fan

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