Abstract
Crohn's disease (CD) is a complex chronic inflammatory bowel disorder characterized by the absence of reliable biomarkers and effective targeted treatments. Recent evidence has suggested a role for S-palmitoylation, a reversible post-translational modification, in immune regulation and intestinal inflammation. However, a systematic, gene-centric investigation explicitly linking S-palmitoylation to the pathogenesis and diagnosis of CD has not been conducted. To address this gap, our study employs a comprehensive bioinformatic analysis to identify and validate key genes associated with both CD and S-palmitoylation, assessing their potential as diagnostic biomarkers and therapeutic targets. Utilizing data from the Gene Expression Omnibus (GEO, GSE83448) and GeneCards, we identified 23 S-palmitoylation-associated differentially expressed genes (SP-DEGs) in CD. Functional enrichment analysis indicated their significant roles in cysteine-specific S-palmitoylation and immunometabolic regulation. We applied machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE), to select nine hub genes. Validation in two independent cohorts (GSE16879 and GSE59071) and ROC analysis confirmed ZDHHC23 and IFITM1 as biomarkers with high diagnostic value. These genes also exhibited correlations with immune infiltration patterns, as determined by cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), MCPcounter, and QuanTIseq. In vitro experiments corroborated consistent changes in mRNA and protein expression for both ZDHHC23 and IFITM1, reinforcing their involvement in CD. This study offers systematic insights into the functional roles of S-palmitoylation-related genes in CD, providing a novel theoretical foundation for the development of diagnostic and targeted therapeutic strategies.