Ni Man, Peng Weilong, Wang Xiaoguang, Li Jingui
School of Veterinary Medicine, Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, 225009, People's Republic of China.
Joint International Research Laboratory of Agriculture and Agri-Product Safety, the Ministry of Education of China, Yangzhou University, Yangzhou, Jiangsu, 225009, People's Republic of China.
J Inflamm Res. 2025 Feb 6;18:1839-1853. doi: 10.2147/JIR.S504040. eCollection 2025.
An increasing proportion of the aging population has led to a rapid increase in the number of elderly patients with ulcerative colitis (UC). However, the molecular mechanisms by which aging causes UC remain unclear. In this study, we explored the role of aging-related genes (ARGs) in UC pathogenesis and diagnosis prediction.
Gene expression data were obtained from four independent datasets (GSE75214, GSE87466, GSE94648, and GSE169568) in the GEO database, and ARGs were derived from multiple public databases. After identifying UC-related ARGs, consistent clustering was performed to screen aging-related molecular subtypes, followed by the exploration of differences in the immune microenvironment and pathways between distinct subtypes. Next, core module genes were screened using WGCNA and then the hub genes were characterized using LASSO and random forest methods. Besides, the associations between hub genes, immune cells, and key pathways were explored. Finally, the expression levels of key genes were determined in a dextran sulfate sodium (DSS)-induced UC mouse model by qRT-PCR.
UC samples were classified into two subtypes (1 and 2), which displayed significant differences in the immune landscape and JAK/STAT signaling pathways. A series of machine learning algorithms was used to screen two feature genes (ETS1 and IL7R) to establish the diagnostic model, which exhibited satisfactory diagnostic efficiency. In addition, these hub genes were closely associated with the infiltration of specific immune cells (such as neutrophils, memory B cells, and M2 macrophages) as well as with the JAK/STAT pathway. Later, experimental validation confirmed that ETS1 expression was markedly increased in a mouse model of UC.
Overall, aging, immune dysregulation, and UC process are closely associated. The identified feature genes, particularly ETS1, could serve as novel diagnostic biomarkers for UC. These findings have the potential to enhance the understanding of the age-related mechanisms of UC.
老龄化人口比例的不断增加导致老年溃疡性结肠炎(UC)患者数量迅速上升。然而,衰老导致UC的分子机制仍不清楚。在本研究中,我们探讨了衰老相关基因(ARGs)在UC发病机制和诊断预测中的作用。
从基因表达综合数据库(GEO)中的四个独立数据集(GSE75214、GSE87466、GSE94648和GSE169568)获取基因表达数据,ARGs来自多个公共数据库。在鉴定出与UC相关的ARGs后,进行一致性聚类以筛选衰老相关分子亚型,随后探索不同亚型之间免疫微环境和通路的差异。接下来,使用加权基因共表达网络分析(WGCNA)筛选核心模块基因,然后使用套索(LASSO)和随机森林方法鉴定枢纽基因。此外,还探索了枢纽基因、免疫细胞和关键通路之间的关联。最后,通过实时定量聚合酶链反应(qRT-PCR)在葡聚糖硫酸钠(DSS)诱导的UC小鼠模型中测定关键基因的表达水平。
UC样本被分为两个亚型(1和2),它们在免疫格局和JAK/STAT信号通路中表现出显著差异。使用一系列机器学习算法筛选出两个特征基因(ETS1和IL7R)以建立诊断模型,该模型表现出令人满意的诊断效率。此外,这些枢纽基因与特定免疫细胞(如中性粒细胞、记忆B细胞和M2巨噬细胞)的浸润以及JAK/STAT通路密切相关。随后,实验验证证实UC小鼠模型中ETS1表达明显增加。
总体而言,衰老、免疫失调和UC进程密切相关。鉴定出的特征基因,特别是ETS1,可作为UC的新型诊断生物标志物。这些发现有可能增进对UC年龄相关机制的理解。