Suppr超能文献

重症急性胰腺炎中自噬相关生物标志物的鉴定:加权基因共表达网络分析、机器学习算法和单细胞RNA测序的整合

Identification of mitophagy-related biomarkers in severe acute pancreatitis: integration of WGCNA, machine learning algorithms and scRNA-seq.

作者信息

Xie Xiaozhou, Wang Zheng, Zhang Haoyu, Lu Jiongdi, Cao Feng, Li Fei

机构信息

Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.

Clinical Center for Acute Pancreatitis, Capital Medical University, Beijing, China.

出版信息

Front Immunol. 2025 May 28;16:1594085. doi: 10.3389/fimmu.2025.1594085. eCollection 2025.

Abstract

BACKGROUND

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.

METHODS

We downloaded the GSE194331 dataset from the Gene Expression Omnibus (GEO), identified differentially expressed genes (DEGs), and used weighted gene co-expression network analysis (WGCNA) and three machine learning algorithms to identify crucial genes. In addition, single sample gene set enrichment analysis (ssGSEA) was conducted to explore the relationship between crucial genes and immune infiltration. The expression of crucial genes at the single-cell level was analyzed using single-cell RNA sequencing (scRNA seq) data from the GSE279876 dataset. Finally, we established the SAP mouse model and conducted preliminary validation of the mechanism of crucial genes in SAP.

RESULT

We identified MAPK14 as a crucial mitophagy-related gene in SAP by intersecting the results of DEGs, WGCNA, and three machine learning algorithms. In addition, ssGSEA revealed that MAPK14 was strongly associated with immune cell infiltration. The analysis of scRNA-seq data 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.

CONCLUSION

Inhibition of MAPK14 activation may alleviate SAP by enhancing mitophagy. 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.

摘要

背景

线粒体自噬是真核细胞中一种高度保守的细胞过程,其通过自噬机制选择性清除功能失调或受损的线粒体,以维持线粒体稳态。然而,线粒体自噬在重症急性胰腺炎(SAP)发病机制中的作用尚未得到充分研究。在本研究中,我们旨在鉴定SAP中关键的线粒体自噬相关基因,为深入的机制研究提供理论依据。

方法

我们从基因表达综合数据库(GEO)下载了GSE194331数据集,鉴定差异表达基因(DEG),并使用加权基因共表达网络分析(WGCNA)和三种机器学习算法来鉴定关键基因。此外,进行单样本基因集富集分析(ssGSEA)以探索关键基因与免疫浸润之间的关系。使用来自GSE279876数据集的单细胞RNA测序(scRNA seq)数据在单细胞水平分析关键基因的表达。最后,我们建立了SAP小鼠模型,并对关键基因在SAP中的机制进行了初步验证。

结果

通过整合DEG、WGCNA和三种机器学习算法的结果,我们鉴定出MAPK14是SAP中关键的线粒体自噬相关基因。此外,ssGSEA显示MAPK14与免疫细胞浸润密切相关。scRNA-seq数据分析显示MAPK14在胰腺巨噬细胞中高表达,这表明巨噬细胞来源的MAPK14可能潜在地调节SAP中的炎症。最后,我们使用SAP小鼠模型初步验证,抑制MAPK14编码的蛋白可增加线粒体自噬标记蛋白的表达,并显著减轻SAP炎症。

结论

抑制MAPK14激活可能通过增强线粒体自噬来减轻SAP。我们的研究突出了线粒体自噬相关基因MAPK14在SAP发病机制中的潜在作用,为未来研究线粒体自噬介导的SAP免疫机制提供了重要见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13cd/12151840/2a56fa193bdd/fimmu-16-1594085-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验