{"title":"Identification of metabolism regulators as diagnostic markers for ulcerative colitis and their correlation with immune infiltration.","authors":"Qilong Duan, Peng Liu, Hualei Chen, Yuanyuan Ding, Xiaoming Xu","doi":"10.5114/pjp.2025.153972","DOIUrl":null,"url":null,"abstract":"<p><p>This study determined novel metabolism-related diagnostic biomarkers for ulcer-ative colitis (UC) and assessed their correlation with immune cell infiltration levels. Transcriptome data of UC was downloaded from the Gene Expression Omnibus (GEO) database, metabolism-related genes were summarised from the Gene Set Enrichment Analysis (GSEA) database. A total of 537 metabolism-related differen-tially expressed genes (DEGs) in UC were applied to functional enrichment analy-sis. We processed least absolute shrinkage and selection operator (LASSO) regres-sion analysis and support vector machine-recursive feature elimination (SVM-RFE). We obtained 6 potential metabolism-related diagnostic biomarkers (CHST13, ETNK1, LPCAT1, PDE6A, PLA2G2A, and UGT2A3). Expression patterns and diagnostic ROC curves were depicted in both the training and testing co-horts to verify their diagnostic value. Immune infiltration analysis indicated that UC samples have more abundant infiltration levels of immune cells. Fur-thermore, the upregulated diagnostic biomarkers significantly positively cor-related with B cell memory, T cell CD4 memory activated, dendritic cells ac-tivated, etc., while the downregulated ones mainly significantly positively correlated with mast cells resting, NK cells activated, and macrophages M2. Our study primarily identified 6 metabolism regulators (CHST13, ETNK1, LP-CAT1, PDE6A, PLA2G2A, and UGT2A3) as potential diagnostic biomarkers for UC and determined their correlation with immune infiltration.</p>","PeriodicalId":49692,"journal":{"name":"Polish Journal of Pathology","volume":"76 2","pages":"110-119"},"PeriodicalIF":0.6000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Polish Journal of Pathology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.5114/pjp.2025.153972","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PATHOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
This study determined novel metabolism-related diagnostic biomarkers for ulcer-ative colitis (UC) and assessed their correlation with immune cell infiltration levels. Transcriptome data of UC was downloaded from the Gene Expression Omnibus (GEO) database, metabolism-related genes were summarised from the Gene Set Enrichment Analysis (GSEA) database. A total of 537 metabolism-related differen-tially expressed genes (DEGs) in UC were applied to functional enrichment analy-sis. We processed least absolute shrinkage and selection operator (LASSO) regres-sion analysis and support vector machine-recursive feature elimination (SVM-RFE). We obtained 6 potential metabolism-related diagnostic biomarkers (CHST13, ETNK1, LPCAT1, PDE6A, PLA2G2A, and UGT2A3). Expression patterns and diagnostic ROC curves were depicted in both the training and testing co-horts to verify their diagnostic value. Immune infiltration analysis indicated that UC samples have more abundant infiltration levels of immune cells. Fur-thermore, the upregulated diagnostic biomarkers significantly positively cor-related with B cell memory, T cell CD4 memory activated, dendritic cells ac-tivated, etc., while the downregulated ones mainly significantly positively correlated with mast cells resting, NK cells activated, and macrophages M2. Our study primarily identified 6 metabolism regulators (CHST13, ETNK1, LP-CAT1, PDE6A, PLA2G2A, and UGT2A3) as potential diagnostic biomarkers for UC and determined their correlation with immune infiltration.
本研究确定了溃疡性结肠炎(UC)的新型代谢相关诊断生物标志物,并评估了它们与免疫细胞浸润水平的相关性。从Gene Expression Omnibus (GEO)数据库下载UC的转录组数据,从Gene Set Enrichment Analysis (GSEA)数据库汇总代谢相关基因。利用UC中537个代谢相关差异表达基因(DEGs)进行功能富集分析。我们进行了最小绝对收缩和选择算子(LASSO)回归分析和支持向量机递归特征消除(SVM-RFE)。我们获得了6个潜在的代谢相关诊断生物标志物(CHST13、ETNK1、LPCAT1、PDE6A、PLA2G2A和UGT2A3)。在训练组和测试组中绘制表达模式和诊断ROC曲线,以验证其诊断价值。免疫浸润分析表明UC样品中免疫细胞浸润水平更丰富。此外,上调的诊断生物标志物与B细胞记忆、T细胞CD4记忆活化、树突状细胞活化等显著正相关,而下调的诊断生物标志物主要与肥大细胞静息、NK细胞活化、巨噬细胞M2显著正相关。我们的研究主要确定了6种代谢调节因子(CHST13、ETNK1、LP-CAT1、PDE6A、PLA2G2A和UGT2A3)作为UC的潜在诊断生物标志物,并确定了它们与免疫浸润的相关性。
期刊介绍:
Polish Journal of Pathology is an official magazine of the Polish Association of Pathologists and the Polish Branch of the International Academy of Pathology. For the last 18 years of its presence on the market it has published more than 360 original papers and scientific reports, often quoted in reviewed foreign magazines. A new extended Scientific Board of the quarterly magazine comprises people with recognised achievements in pathomorphology and biology, including molecular biology and cytogenetics, as well as clinical oncology. Polish scientists who are working abroad and are international authorities have also been invited. Apart from presenting scientific reports, the magazine will also play a didactic and training role.