PDF(Pubmed)
Abstract：
Metabolic-associated steatohepatitis (MASH) and ulcerative colitis (UC) exhibit a complex interconnection with immune dysfunction, dysbiosis of the gut microbiota, and activation of inflammatory pathways. This study aims to identify and validate critical butyrate metabolism-related shared genes between both UC and MASH. Clinical information and gene expression profiles were sourced from the Gene Expression Omnibus (GEO) database. Shared butyrate metabolism-related differentially expressed genes (sBM-DEGs) between UC and MASH were identified via various bioinformatics methods. Functional enrichment analysis was performed, and UC patients were categorized into subtypes using the consensus clustering algorithm based on sBM-DEGs. Key genes within sBM-DEGs were screened through Random Forest, Support Vector Machines-Recursive Feature Elimination, and Light Gradient Boosting. The diagnostic efficacy of these genes was evaluated using receiver operating characteristic (ROC) analysis on independent datasets. Additionally, the expression levels of characteristic genes were validated across multiple independent datasets and human specimens. Forty-nine shared DEGs between UC and MASH were identified, with enrichment analysis highlighting significant involvement in immune, inflammatory, and metabolic pathways. The intersection of butyrate metabolism-related genes with these DEGs produced 10 sBM-DEGs. These genes facilitated the identification of molecular subtypes of UC patients using an unsupervised clustering approach. ANXA5, CD44, and SLC16A1 were pinpointed as hub genes through machine learning algorithms and feature importance rankings. ROC analysis confirmed their diagnostic efficacy in UC and MASH across various datasets. Additionally, the expression levels of these three hub genes showed significant correlations with immune cells. These findings were validated across independent datasets and human specimens, corroborating the bioinformatics analysis results. Integrated bioinformatics identified three significant biomarkers, ANXA5, CD44, and SLC16A1, as DEGs linked to butyrate metabolism. These findings offer new insights into the role of butyrate metabolism in the pathogenesis of UC and MASH, suggesting its potential as a valuable diagnostic biomarker.
摘要：
代谢相关脂肪性肝炎（MASH）和溃疡性结肠炎（UC）表现出复杂的相互联系与免疫功能障碍，肠道微生物群的生态失调，和炎症途径的激活。本研究旨在鉴定和验证UC和MASH之间关键的丁酸代谢相关共享基因。临床信息和基因表达谱来源于基因表达综合(GEO)数据库。通过各种生物信息学方法鉴定了UC和MASH之间共享的丁酸代谢相关差异表达基因（sBM-DEGs）。进行了功能富集分析，使用基于sBM-DEGs的共识聚类算法将UC患者分为亚型。通过随机森林筛选sBM-DEGs中的关键基因，支持向量机-递归特征消除，和光梯度提升。使用独立数据集上的接受者操作特征(ROC)分析来评估这些基因的诊断功效。此外,特征基因的表达水平在多个独立数据集和人类样本中进行了验证.确定了UC和MASH之间的49个共享DEG，富集分析强调了免疫的重要参与，炎症，和代谢途径。丁酸代谢相关基因与这些DEGs的交叉产生10个sBM-DEGs。这些基因有助于使用无监督聚类方法鉴定UC患者的分子亚型。ANXA5、CD44和SLC16A1通过机器学习算法和特征重要性排名被确定为中心基因。ROC分析在各种数据集上证实了它们在UC和MASH中的诊断功效。此外,这三个hub基因的表达水平与免疫细胞呈显著相关。这些发现在独立的数据集和人体样本中得到了验证，证实了生物信息学分析结果。综合生物信息学确定了三个重要的生物标志物，ANXA5、CD44和SLC16A1，作为与丁酸代谢相关的DEGs。这些发现为丁酸代谢在UC和MASH发病机理中的作用提供了新的见解。表明其作为有价值的诊断生物标志物的潜力。
