免疫系统
疾病
衰老
计算生物学
生物
发病机制
支持向量机
免疫学
生物信息学
医学
遗传学
计算机科学
机器学习
病理
作者
Wenyu Zhang,Xianzong Ma,Wenqing Tian,Yong‐sheng Teng,Meihua Ji
标识
DOI:10.3389/fimmu.2025.1616531
摘要
Background Crohn’s disease (CD) is a complex and heterogeneous inflammatory disease whose most important feature is immune dysregulation. As a basic cell response, cellular senescence (CS) can regulate the immune response involved in a variety of inflammatory diseases. However, the role of CS in the pathogenesis and diagnosis prediction of CD are still unknown. Methods We utilized CD-related datasets from the GEO database for differential gene expression analysis, and CS related differentially expressed genes (CSRDEGs) in CD by a comprehensive bioinformatics analysis encompassing GSEA, WGCNA, and various interaction networks. The support vector machine (SVM) algorithm, random forest algorithm and LASSO regression analysis was used to construct a diagnostic model. And based on CSRDEGs, we further constructed a Cellular senescence score (CSscore) model. Different disease subtypes (cluster1/cluster2) were identified by the consensus clustering method. The assessment of immune cell infiltration and its correlation with CSRDEGs was analyzed by ssGAEA and CIBERSORT. Results We identified 10 hub CS related differentially expressed genes (CSRDEGs) in CD. Based on CSRDEGs, we further constructed a diagnostic model (AUC = 0.880) containing 5 CSRDEGs ( CDKN1A , IL1A , PML , SIRT1 , and STAT3 ) through machine learning algorithm and other methods and analyzed the correlation with immune cell infiltration. In addition, a CS Scores model (Low or High) based on the 7 CSRDEGs ( CDKN2B , IGFBP7 , IL1A , IL6 , PML , SIRT1 , and STAT3 ) shows different characteristics, reaffirming the inflammatory regulatory role of CS in CD. Finally, the subtype construction (cluster1 and cluster2) based on 10 CSRDEGs shows the heterogeneity of the disease and affirms that CS is a prominent feature of CD. Conclusions These results suggest that CS is an important feature of CD, and CSRDEGs can be used to construct disease diagnostic models and distinguish disease subtypes. Further investigation of the mechanism of immune dysregulation caused by CS can deepen our understanding of the pathogenesis of CD.
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