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Mitophagy related diagnostic biomarkers for coronary in-stent restenosis identified using machine learning and bioinformatics

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机构: [1]Kunming Univ Sci & Technol, Hosp Joint Logist Support Force PLA 926, Affiliated Hosp, Dept Cardiol, Kaiyuan 661600, Yunnan, Peoples R China [2]920 Hosp Joint Logist Support Force PLA, Dept Cardiol, Kunming 650032, Yunnan, Peoples R China [3]Fujian Med Univ, Hosp Joint Logist Support Force PLA 900, Dept Cardiol, Fuzong Clin Med Coll, Fuzhou 350025, Fujian, Peoples R China [4]Fujian Med Univ, Hosp Joint Logist Support Force PLA 900, Dept Geriatr, Fuzong Clin Med Coll, Fuzhou 350025, Fujian, Peoples R China
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关键词: Coronary artery disease In-stent restenosis Mitophagy Machine learning Biomarkers Immune infiltration

摘要:
Percutaneous coronary intervention (PCI) combined with stent implantation is currently one of the most effective treatments for coronary artery disease (CAD). However, in-stent restenosis (ISR) significantly compromises its long-term efficacy. Mitophagy plays a crucial role in vascular homeostasis, yet its role in ISR remains unclear. This study aims to identify mitophagy-related biomarkers for ISR and explore their underlying molecular mechanisms. Through differential gene expression analysis between ISR and Control samples in the combined dataset, 169 differentially expressed genes (DEGs) were identified. Twenty-three differentially expressed mitophagy-related genes (DEMRGs) were identified by intersecting with mitophagy-related genes (MRGs) from the GeneCards, and functional enrichment analysis indicated their significant involvement in mitophagy-related biological processes. Using Weighted Gene Co-expression Network Analysis (WGCNA) and three machine learning algorithms (Logistic-LASSO, RF, and SVM-RFE), LRRK2, and ANKRD13A were identified as mitophagy-related biomarkers for ISR. The nomogram based on these two genes also exhibited promising diagnostic performance for ISR. Gene Set Enrichment Analysis (GSEA) as well as immune infiltration analyses showed that these two genes were closely associated with immune and inflammatory responses in ISR. Furthermore, potential small molecule compounds with therapeutic implications for ISR were predicted using the connectivity Map (cMAP) database. This study systematically investigated mitophagy-related biomarkers for ISR and their potential biological functions, providing new insights into early diagnosis and precision treatment strategies for ISR.

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大类 | 2 区 综合性期刊
小类 | 2 区 综合性期刊
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Q1 MULTIDISCIPLINARY SCIENCES
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Q1 MULTIDISCIPLINARY SCIENCES

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第一作者机构: [1]Kunming Univ Sci & Technol, Hosp Joint Logist Support Force PLA 926, Affiliated Hosp, Dept Cardiol, Kaiyuan 661600, Yunnan, Peoples R China [2]920 Hosp Joint Logist Support Force PLA, Dept Cardiol, Kunming 650032, Yunnan, Peoples R China
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