Key result
A five-gene diagnostic model (FOXK1, JAM3, LOC100288798, MCM4, and RCAN1) related to lactylation and immune infiltration achieved high predictive accuracy for atrial fibrillation with an AUC of 0.969.
Why the study?
Immune infiltration plays a crucial role in AF pathogenesis through unclear mechanisms, and the association of lactylation with AF remains unexplored.
Observational (n=135)
Effect estimate: AUC 0.969
A novel five-gene signature related to lactylation and immune infiltration demonstrates high diagnostic accuracy for atrial fibrillation and provides insights into its pathogenesis.
Should not yet change AF diagnosis; leaves open lactylation-immune links as a hypothesis-generating biomarker axis.
Background Atrial fibrillation (AF) is a common arrhythmia associated with an increased risk of stroke, heart failure, and mortality. Immune infiltration plays a crucial role in AF pathogenesis, yet its mechanisms remain unclear. Lactylation, a novel post-translational modification, has been implicated in immune regulation, but its association with AF remains unexplored. This study aims to elucidate the relationship between lactylation and immune infiltration in AF and identify potential diagnostic biomarkers. Methods Gene expression data from left atrial tissue samples of AF and sinus rhythm (SR) patients were obtained from the Gene Expression Omnibus (GEO) database (GSE41177, GSE79768, GSE115574, GSE2240, GSE14975, and GSE128188). Differentially expressed genes (DEGs) between AF and SR samples were identified, followed by pathway enrichment and immune infiltration analysis. Correlation analysis and WGCNA were performed to assess interactions between lactylation-related genes and immune-associated DEGs. Machine learning models, including Random Forest and Support Vector Machine (SVM), were applied to select potential AF-related diagnostic biomarkers, and validated in the animal model (beagles; n = 6). Results A total of 5,648 DEGs were identified, including six lactylation-related genes (DDX39A, ARID3A, TKT, NUP50, G6PD, and VCAN). Co-expression and WGCNA analyses identified lactylation- and immune-associated gene modules in AF. Functional enrichment analysis highlighted immune-related pathways such as T cell activation and neutrophil degranulation. A five-gene diagnostic model (FOXK1, JAM3, LOC100288798, MCM4, and RCAN1) achieved high predictive accuracy (AUC = 0.969 in training, 0.907 in self-test, and 0.950, 0.760, 0.890 in independent datasets). Experimental validation confirmed the upregulated expression of these biomarkers in AF. Conclusion This study reveals a strong association between lactylation-related genes and immune infiltration in AF, suggesting their involvement in immune remodeling. The identified five-gene signature serves as a potential diagnostic biomarker set, offering novel insights into AF pathogenesis and contributing to improved diagnosis and targeted therapeutic strategies. Future studies integrating proteomic and single-cell analyses will further clarify the role of lactylation in AF.
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Ma et al. (2025) conducted an observational in Atrial fibrillation (n=135). Lactylation-related gene expression and immune infiltration vs. Sinus rhythm (SR) was evaluated on Diagnostic accuracy of a five-gene model for atrial fibrillation (AUC 0.969). A five-gene diagnostic model (FOXK1, JAM3, LOC100288798, MCM4, and RCAN1) related to lactylation and immune infiltration achieved high predictive accuracy for atrial fibrillation with an AUC of 0.969.
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