Evidence map›Paper›PMID 40607061›Full record

ArticleFrontiers in molecular biosciences2025

Comprehensive bioinformatics analysis of the common mechanism of atherosclerosis and atrial fibrillation: emphasizing mitochondrial metabolic disorder and immune inflammation.

Rui Dai, Xiaotong Lei, Xiaojun Liu, Chen Bian

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In one paragraph

Article in Frontiers in molecular biosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Rui DaiDepartment of Cardiology, Xuzhou First People's Hospital (The Affiliated Xuzhou Municipal Hospital of Xuzhou Medical University), Xuzhou, China.
Xiaotong LeiDepartment of Nephrology, Xuzhou First People's Hospital (The Affiliated Xuzhou Municipal Hospital of Xuzhou Medical University), Xuzhou, China.
Xiaojun LiuDepartment of Cardiology, Xuzhou First People's Hospital (The Affiliated Xuzhou Municipal Hospital of Xuzhou Medical University), Xuzhou, China.
Chen BianDepartment of Cardiology, Xuzhou First People's Hospital (The Affiliated Xuzhou Municipal Hospital of Xuzhou Medical University), Xuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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. Conclusion: 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.

Indexed as

atherosclerosisatrial fibrillationbioinformatics analysisimmune inflammationmachine learningmitochondria metabolism

Identifiers

PMID40607061
PMCPMC12215116

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