ORIGINAL RESEARCH article
Front. Mol. Biosci.
Sec. Molecular Diagnostics and Therapeutics
Volume 12 - 2025 | doi: 10.3389/fmolb.2025.1595048
This article is part of the Research TopicTransforming Chronic Disease Treatment with AI and Big DataView all articles
Comprehensive Bioinformatics Analysis of the Common Mechanism of Atherosclerosis and Atrial Fibrillation: Emphasizing Mitochondrial Metabolic Disorder and Immune Inflammation
Provisionally accepted
- 1Department of cardiology, First People's Hospital of Xuzhou, Xuzhou, China
- 2Department of Cardiology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China
- 3Department of Nephrology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu Province, China
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Introduction: Atherosclerosis (AS) and atrial fibrillation (AF) are clinically intertwined cardiovascular disorders, yet their shared pathophysiological mechanisms remain poorly understood. Mitochondrial dysfunction and immune dysregulation have been implicated separately in both diseases, but their potential crosstalk in driving comorbidity is unexplored. This study aims to uncover common molecular pathways linking AS and AF, focusing on mitochondrial metabolism and immune response, and to identify diagnostic biomarkers using integrative bioinformatics approaches.Methods: Transcriptomic datasets of AS and AF were analyzed through GO and KEGG enrichment to identify shared biological themes. WWGCNA prioritized 35 mitochondrial genes associated with both diseases. Three machine learning algorithms (LASSO, SVM, and random forest) were applied to screen hub genes, followed by validation in independent datasets. Immune infiltration and single-cell transcriptomic analyses were conducted to assess immune-microenvironment interactions and gene expression at cellular resolution.Results: GO/KEGG analyses revealed dominant enrichment in mitochondrial oxidative phosphorylation and immune-inflammatory pathways for AS and AF. WGCNA identified 35 mitochondrial hub genes, with MRPS23 and CASP8 emerging as key candidates via machine learning. MRPS23 showed significant downregulation in AS tissues and cellular heterogeneity in scRNA-seq (single-cell RNA sequencing), while both genes exhibited strong correlations with immune cell subsets in both diseases.This study establishes MRPS23 as a novel biomarker bridging mitochondrial dysfunction and immune dysregulation in AS and AF comorbidity. Its decline in AS suggests a potential role in mitochondrial ribosomal integrity loss driving metabolic stress, while immune-microenvironment interactions highlight its pleiotropic impacts on inflammatory cascades. These findings advance the " mitochondria-immune axis " paradigm for cardiovascular comorbidity, offering MRPS23 as a dual-disease therapeutic target. Further validation in preclinical models and clinical cohorts is needed to translate these insights into diagnostic or therapeutic applications.
Keywords: Atherosclerosis, Atrial Fibrillation, Bioinformatics analysis, mitochondria metabolism, immune inflammation, machine learning
Received: 17 Mar 2025; Accepted: 20 May 2025.
Copyright: © 2025 Bian, Dai, Lei and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Chen Bian, Department of cardiology, First People's Hospital of Xuzhou, Xuzhou, China
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