ORIGINAL RESEARCH article
Front. Immunol.
Sec. Inflammation
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1594085
This article is part of the Research TopicDecoding the Mito-Immune Axis: Impact of Mitochondria on Immune Regulation and Pathogen DefenseView all articles
Identification of mitophagy-related biomarkers in severe acute pancreatitis: integration of WGCNA, machine learning algorithms and scRNA-seq
Provisionally accepted
- Xuanwu Hospital, Capital Medical University, Beijing, China
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Mitophagy is a highly conserved cellular process in eukaryotic cells that selectively clears dysfunctional or damaged mitochondria through autophagy mechanisms to maintain mitochondrial homeostasis. However, the role of mitophagy in the pathogenesis of severe acute pancreatitis (SAP) has not been fully investigated.In this study, we aimed to identify crucial mitophagy-related genes in SAP to provide a theoretical basis for in-depth mechanistic investigations. We downloaded the GSE194331 dataset from the Gene Expression Omnibus (GEO), identified differentially expressed genes (DEGs), and using weighted gene co-expression network analysis (WGCNA) and three machine learning algorithms, we identified MAPK14 as a crucial mitophagy-related genes in SAP. In addition, single sample gene set enrichment analysis (ssGSEA) showed that MAPK14 was strongly associated with immune cell infiltration. Analysis of single-cell RNA sequencing (scRNA-seq) data from the GSE279876 dataset revealed that MAPK14 was highly expressed in pancreatic macrophages, suggesting that macrophage-derived MAPK14 may potentially regulate inflammation in SAP. Finally, we preliminarily validated using the SAP mouse model that inhibiting the protein encoded by MAPK14 increased the expression of mitophagy marker proteins and significantly alleviated SAP inflammation. Our study highlights the potential role of the mitophagy-related gene MAPK14 in SAP pathogenesis, providing important insights for future investigations into mitophagy-mediated immune mechanisms in SAP.
Keywords: Severe acute pancreatitis, mitophagy, MAPK14, P38α, WGCNA, machine learning, Immune Cell Infiltration, single-cell RNA sequencing
Received: 15 Mar 2025; Accepted: 12 May 2025.
Copyright: © 2025 Li, Xie, Wang, Haoyu, Lu and Cao. 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: Fei Li, Xuanwu Hospital, Capital Medical University, Beijing, China
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