ArticleFrontiers in immunology2024
Constructing models for Crohn's disease diagnosis and prediction of infliximab non-response based on angiogenesis-related genes.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 4 citations in OpenAlex.
- Artificial intelligence use for precision medicine in inflammatory bowel disease: a systematic review.American journal of translational research · 2025Review
- Developing models for the diagnosing of ulcerative colitis and prognosis of anti-TNF-α non-response based on neutrophil extracellular trap-associated genes.Frontiers in immunology · 2025Article
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6 authors at 1 institution in 1 country.
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Abstract
Background: Angiogenesis response plays a crucial role in the occurrence and development of Crohn's disease (CD) and may involve the mechanism of infliximab non-response. However, the role of angiogenesis-related genes in Crohn's disease has not been comprehensively studied. This study aimed to explore the expression profiles of angiogenesis-related genes in CD patients and construct models for disease diagnosis and prediction of infliximab non-response. Methods: CD-related microarray datasets were collected from the GEO database. Unsupervised consensus clustering analysis was performed based on differentially expressed angiogenesis-related genes to divide CD samples into two distinct clusters. Weighted gene co-expression network analysis (WGCNA) was conducted on the clusters to identify angiogenesis-related module. Based on the differentially expressed genes in the module, machine learning algorithms were employed to further identify hub genes and construct a disease diagnostic model. Subsequently, treatment outcome-related genes were extracted from these hub genes, and a predictive model for infliximab non-response in CD patients was ultimately built. Results: Based on angiogenesis-related genes, we identified two distinct CD clusters (C1 and C2). Compared to C1, the metabolic pathways in C2 were significantly upregulated, and there was a higher abundance of cell clusters such as M1 macrophages and plasma cells. Additionally, C2 showed a poorer response to infliximab. Furthermore, a predictive model for infliximab non-response in CD patients was constructed based on the hub genes, and it was successfully validated using an external dataset. Conclusion: Comprehensive analysis of angiogenesis-related genes revealed different clusters of CD, which exhibited differential response rates to infliximab. The construction of models provides a reference for disease diagnosis and drug selection, aiding in clinical decision-making.
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