ArticleFrontiers in immunology2023
Exploration of the shared pathways and common biomarker PAN3 in ankylosing spondylitis and ulcerative colitis using integrated bioinformatics analysis.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Ulcerative colitis: signaling pathways, therapeutic targets and interventional strategies.Signal transduction and targeted therapy · 2026Review
- A systematic longitudinal study of microbiome: integrating temporal-spatial dimensions with causal and deep learning models.BMC genomics · 2025Article
- Regulation of ulcerative colitis progression by ferroptosis pathway genes: HSP90AA1, SNCA, TLR4, and PTGS2.American journal of translational research · 2025Article
- Integrated analysis of genes shared between type 2 diabetes mellitus and osteoporosis.Frontiers in pharmacology · 2024Article
- Unraveling Shared Diagnostic Biomarkers of Fibromyalgia in Ankylosing Spondylitis: Evidence from Comprehensive Bioinformatic Analysis and Experimental Validation.Journal of inflammation research · 2024Article
- Exploring shared pathways and the shared biomarker ERRFI1 in Obstructive sleep apnoea and atherosclerosis using integrated bioinformatics analysis.Scientific reports · 2023Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Ulcerative colitis (UC) is a chronic autoimmune-related disease that causes inflammation of the intestine. Ankylosing spondylitis (AS) is a common extraintestinal complication of UC involving the sacroiliac joint. However, the pathogenesis of AS secondary to UC has not been studied. This study aimed to investigate the shared pathways and potential common biomarkers of UC and AS. Methods: Microarray data downloaded from the Gene Expression Omnibus (GEO) database were used to screen differentially expressed genes (DEGs) in the UC and AS datasets. Weighted gene co-expression network analysis (WGCNA) was performed to identify co-expression modules related to UC and AS. Shared genes were then further analyzed for functional pathway enrichment. Next, the optimal common biomarker was selected using SVM-RFF and further validated using two independent GEO datasets. Finally, immune infiltration analysis was used to investigate the correlation of immune cell infiltration with common biomarkers in UC and AS. Results: A total of 4428 and 2438 DEGs in UC and AS, respectively, were screened. Four modules were identified as significant for UC and AS using WGCNA. A total of 25 genes overlapped with the strongest positive and negative modules of UC and AS. KEGG analysis showed these genes may be involved in the mitogen-activated protein kinase (MAPK) signaling pathway. GO analysis indicated that these genes were significantly enriched for RNA localization. Conclusion: This study first explored the common pathways and genetic diagnostic markers involved in UC and AS using bioinformatic analysis. Results suggest that the MAPK signaling pathway may be associated with both pathogeneses and that
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