Mingyue Fu,1,2,* Diliaremu Aihemaiti,1,2,* Haowen Fu,1,2,* Na Li,1,2 Yifan Yuan,3 Mei Ye1,2 

1Department of Gastroenterology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei, People’s Republic of China; 2Hubei Clinical Centre and Key Laboratory of Intestinal and Colorectal Diseases, Zhongnan Hospital, Wuhan University, Wuhan, Hubei, People’s Republic of China; 3Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Yifan Yuan; Mei Ye, Email yifanyuan95@163.com; wumeiye08@163.com

Background: Crohn’s disease (CD) is a persistent inflammatory condition that impacts the gastrointestinal system and is characterized by a multifaceted pathogenesis involving genetic, immune, and environmental components. This study primarily investigates the relationship between gene expression and immune cell infiltration in CD, focusing on disulfidptosis—a novel form of cell death caused by abnormal disulfide accumulation—and its impact on various immune cell populations. By identifying key disulfidptosis-related genes (DRGs) and exploring their association with distinct gene expression subtypes, this research aims to enhance our understanding of CD and potentially other autoimmune diseases.
Methods: Gene expression data from intestinal biopsy samples were collected from both individuals with CD and healthy controls, and these data were retrieved from the GEO database. Through gene expression level comparisons, various differentially expressed genes (DEGs) were identified. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to reveal the biological processes and pathways linked to these DEGs. Later, immune cell infiltration was evaluated. Hub candidate DRGs were identified using machine learning algorithms. Validation of the expression of hub DRGs was carried out using quantitative real-time polymerase chain reaction. The hub DRGs were subjected to unsupervised hierarchical clustering to classify CD patients into subtypes. The characteristics of each subtype were then analyzed.
Results: Two hub DRGs (NDUFA11 and LRPPRC) were identified. NDUFA11 showed a significantly positive association with the abundance of Th17 cells. Conversely, higher expression levels of LRPPRC were associated with a reduced abundance of various immune cells, particularly monocytes. CD patients were classified into two disulfidptosis-related subtypes. Cluster B patients exhibited lower immune infiltration and milder clinical presentation.
Conclusion: LRPPRC and NDUFA11 are identified as hub DRGs in CD, with potential roles in disulfidptosis and immune regulation. The disulfidptosis subtypes provide new insights into disease progression.

Keywords: Crohn’s disease, disulfidptosis, machine learning, expression pattern, immune cell infiltration