Single-cell transcriptomics and machine learning reveal RNF144B and C5AR1 as immune-related biomarkers and therapeutic targets in myocardial infarction

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.

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. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (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 (Johnson, Law et al.) 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. Furthermore, molecular docking was performed to identify candidate small molecules targeting core genes.

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. GSEA and GSVA further revealed that RNF144B was enriched in the neutrophil degranulation pathway, while C5AR1 was associated with the complement cascade. Correlation analysis demonstrated a significant positive relationship of RNF144B and C5AR1 with immunological roles. Both genes were also positively correlated with classical MI marker genes SERPINE1 and RUNX1. 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 reveals immune-related transcriptional signatures and signaling pathways that drive MI progression. The identified 13-gene signature, particularly RNF144B and C5AR1, holds promise as a diagnostic biomarker and therapeutic target, providing new insights for immunomodulatory and precision medicine strategies in MI. Keywords: Immune microenvironment, myeloid cells, inflammation, RNF144B, MI, immune-targeted therapy

Highlights

• A 13-gene signature was identified to predict MI risk

• RNF144B and C5AR1 are key immune regulators in MI progression

• GSEA and GSVA reveal immune-related pathways of RNF144B and C5AR1

• CCX168 is identified as a potential small-molecule therapy for MI

• Mouse model validates gene expression consistent with the prediction model