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Background <p>Myocardial infarction (MI) is a life-threatening cardiovascular disease characterized by high morbidity and mortality. Although advances in clinical management have improved patient outcomes, early diagnosis and effective immunomodulatory therapies remain limited.</p> Objective <p>This paper aims to identify key regulatory genes in MI, uncover their underlying mechanisms of action of the key genes, and facilitate their diagnostic and therapeutic use.</p> Methods <p>In this study, we integrated multiple transcriptomic datasets and applied machine learning approaches, including LASSO regression, to identify a robust 13 key genes significantly associated with MI. GSEA and GSVA were subsequently performed to explore their potential biological functions. The immunological relevance of these genes was evaluated by analyzing their correlations with inflammation-related genes and those involved in immune cell migration. In addition, transcription factor and microRNA (miRNA) regulatory networks were constructed to elucidate upstream regulatory mechanisms. The expression levels of the 13 key genes were validated in MI mouse model.</p> Results <p>Among 11 cardiac cell populations identified, myeloid cells contributed most prominently to MI pathogenesis. A robust 13-gene predictive signature was established, with RNF144B and C5AR1 showing strong associations with immune modulation and disease severity. Correlation analysis demonstrated a significant positive relationship of RNF144B and C5AR1 with immunological roles. TF-gene and miRNA–mRNA regulatory networks supported the post-transcriptional regulation of these genes. In the MI mouse model, expression of the 13 genes was consistent with the risk-prediction model. Molecular docking identified CCX168 as a promising small-molecule candidate targeting RNF144B and C5AR1.</p> Conclusion <p>This study identified 13-gene signature, particularly RNF144B and C5AR1, holds promise as therapeutic targets, providing new insights for immunomodulatory and precision medicine strategies in MI.</p>

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Single-cell transcriptomics and machine learning identify RNF144B and C5AR1 as immune-related molecular signatures and therapeutic targets in myocardial infarction

  • 期刊论文

  • 发表日期：

    2026年4月15日

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  • Yuxin Hu,
  • Lu Chen,
  • Jianmei Sha,
  • Caihong Shao,
  • Junli Gao,
  • Jianhua Yao

摘要

Background

Myocardial infarction (MI) is a life-threatening cardiovascular disease characterized by high morbidity and mortality. Although advances in clinical management have improved patient outcomes, early diagnosis and effective immunomodulatory therapies remain limited.

Objective

This paper aims to identify key regulatory genes in MI, uncover their underlying mechanisms of action of the key genes, and facilitate their diagnostic and therapeutic use.

Methods

In this study, we integrated multiple transcriptomic datasets and applied machine learning approaches, including LASSO regression, to identify a robust 13 key genes significantly associated with MI. GSEA and GSVA were subsequently performed to explore their potential biological functions. The immunological relevance of these genes was evaluated by analyzing their correlations with inflammation-related genes and those involved in immune cell migration. In addition, transcription factor and microRNA (miRNA) regulatory networks were constructed to elucidate upstream regulatory mechanisms. The expression levels of the 13 key genes were validated in MI mouse model.

Results

Among 11 cardiac cell populations identified, myeloid cells contributed most prominently to MI pathogenesis. A robust 13-gene predictive signature was established, with RNF144B and C5AR1 showing strong associations with immune modulation and disease severity. Correlation analysis demonstrated a significant positive relationship of RNF144B and C5AR1 with immunological roles. TF-gene and miRNA–mRNA regulatory networks supported the post-transcriptional regulation of these genes. In the MI mouse model, expression of the 13 genes was consistent with the risk-prediction model. Molecular docking identified CCX168 as a promising small-molecule candidate targeting RNF144B and C5AR1.

Conclusion

This study identified 13-gene signature, particularly RNF144B and C5AR1, holds promise as therapeutic targets, providing new insights for immunomodulatory and precision medicine strategies in MI.