Comprehensive analysis of lactylation-related gene and immune microenvironment in atrial fibrillation
BackgroundAtrial 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 implicat...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-04-01
|
| Series: | Frontiers in Cardiovascular Medicine |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2025.1567310/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849710470626279424 |
|---|---|
| author | Yazhe Ma Youcheng Wang Yuanjia Ke Yuanjia Ke Yuanjia Ke Qingyan Zhao Qingyan Zhao Qingyan Zhao Jie Fan Yang Chen |
| author_facet | Yazhe Ma Youcheng Wang Yuanjia Ke Yuanjia Ke Yuanjia Ke Qingyan Zhao Qingyan Zhao Qingyan Zhao Jie Fan Yang Chen |
| author_sort | Yazhe Ma |
| collection | DOAJ |
| description | BackgroundAtrial 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.MethodsGene 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).ResultsA 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.ConclusionThis 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. |
| format | Article |
| id | doaj-art-816a1d37accf4dc38ffe30099d3dd2f4 |
| institution | DOAJ |
| issn | 2297-055X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cardiovascular Medicine |
| spelling | doaj-art-816a1d37accf4dc38ffe30099d3dd2f42025-08-20T03:14:53ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2025-04-011210.3389/fcvm.2025.15673101567310Comprehensive analysis of lactylation-related gene and immune microenvironment in atrial fibrillationYazhe Ma0Youcheng Wang1Yuanjia Ke2Yuanjia Ke3Yuanjia Ke4Qingyan Zhao5Qingyan Zhao6Qingyan Zhao7Jie Fan8Yang Chen9Yunnan Arrhythmia Research Center, The First People's Hospital of Yunnan Province & The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, ChinaDepartment of Cardiology, The Affiliated Dongguan Songshan Lake Central Hospital, Dongguan Key Laboratory of Cardiovascular Aging and Myocardial Regeneration, Dongguan Cardiovascular Research Institute, Dongguan, ChinaDepartment of Cardiology, Renmin Hospital of Wuhan University, Wuhan, ChinaCardiovascular Research Institute, Wuhan University, Wuhan, ChinaHubei Key Laboratory of Cardiology, Wuhan, ChinaDepartment of Cardiology, Renmin Hospital of Wuhan University, Wuhan, ChinaCardiovascular Research Institute, Wuhan University, Wuhan, ChinaHubei Key Laboratory of Cardiology, Wuhan, ChinaYunnan Arrhythmia Research Center, The First People's Hospital of Yunnan Province & The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, ChinaDepartment of Pathology, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, ChinaBackgroundAtrial 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.MethodsGene 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).ResultsA 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.ConclusionThis 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.https://www.frontiersin.org/articles/10.3389/fcvm.2025.1567310/fullatrial fibrillationlactylationimmune infiltrationmachine learningdiagnostic biomarkers |
| spellingShingle | Yazhe Ma Youcheng Wang Yuanjia Ke Yuanjia Ke Yuanjia Ke Qingyan Zhao Qingyan Zhao Qingyan Zhao Jie Fan Yang Chen Comprehensive analysis of lactylation-related gene and immune microenvironment in atrial fibrillation Frontiers in Cardiovascular Medicine atrial fibrillation lactylation immune infiltration machine learning diagnostic biomarkers |
| title | Comprehensive analysis of lactylation-related gene and immune microenvironment in atrial fibrillation |
| title_full | Comprehensive analysis of lactylation-related gene and immune microenvironment in atrial fibrillation |
| title_fullStr | Comprehensive analysis of lactylation-related gene and immune microenvironment in atrial fibrillation |
| title_full_unstemmed | Comprehensive analysis of lactylation-related gene and immune microenvironment in atrial fibrillation |
| title_short | Comprehensive analysis of lactylation-related gene and immune microenvironment in atrial fibrillation |
| title_sort | comprehensive analysis of lactylation related gene and immune microenvironment in atrial fibrillation |
| topic | atrial fibrillation lactylation immune infiltration machine learning diagnostic biomarkers |
| url | https://www.frontiersin.org/articles/10.3389/fcvm.2025.1567310/full |
| work_keys_str_mv | AT yazhema comprehensiveanalysisoflactylationrelatedgeneandimmunemicroenvironmentinatrialfibrillation AT youchengwang comprehensiveanalysisoflactylationrelatedgeneandimmunemicroenvironmentinatrialfibrillation AT yuanjiake comprehensiveanalysisoflactylationrelatedgeneandimmunemicroenvironmentinatrialfibrillation AT yuanjiake comprehensiveanalysisoflactylationrelatedgeneandimmunemicroenvironmentinatrialfibrillation AT yuanjiake comprehensiveanalysisoflactylationrelatedgeneandimmunemicroenvironmentinatrialfibrillation AT qingyanzhao comprehensiveanalysisoflactylationrelatedgeneandimmunemicroenvironmentinatrialfibrillation AT qingyanzhao comprehensiveanalysisoflactylationrelatedgeneandimmunemicroenvironmentinatrialfibrillation AT qingyanzhao comprehensiveanalysisoflactylationrelatedgeneandimmunemicroenvironmentinatrialfibrillation AT jiefan comprehensiveanalysisoflactylationrelatedgeneandimmunemicroenvironmentinatrialfibrillation AT yangchen comprehensiveanalysisoflactylationrelatedgeneandimmunemicroenvironmentinatrialfibrillation |