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Comprehensive analysis of lactylation-related gene and immune microenvironment in atrial fibrillation

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机构: [1]Yunnan Arrhythmia Research Center, The First People’s Hospital of Yunnan Province & The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China, [2]Department of Cardiology, The Affiliated Dongguan Songshan Lake Central Hospital, Dongguan Key Laboratory of Cardiovascular Aging and Myocardial Regeneration, Dongguan Cardiovascular Research Institute, Dongguan, China, [3]Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China, [4]Cardiovascular Research Institute, Wuhan University, Wuhan, China, [5]Hubei Key Laboratory of Cardiology, Wuhan, China, [6]Department of Pathology, The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
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关键词: atrial fibrillation lactylation immune infiltration machine learning diagnostic biomarkers

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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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大类 | 3 区 医学
小类 | 3 区 心脏和心血管系统
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Q2 CARDIAC & CARDIOVASCULAR SYSTEMS

影响因子: 最新[2023版] 最新五年平均 出版当年[2024版] 出版当年五年平均 出版前一年[2023版]

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第一作者机构: [1]Yunnan Arrhythmia Research Center, The First People’s Hospital of Yunnan Province & The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China,
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通讯机构: [3]Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China, [4]Cardiovascular Research Institute, Wuhan University, Wuhan, China, [5]Hubei Key Laboratory of Cardiology, Wuhan, China,
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