Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1075
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
98%
921
2 minutes
20
Ulcerative colitis (UC) is an increasingly prevalent inflammatory condition affecting the intestinal mucosa, while nonspecific orbital inflammation (NSOI) is a common non-neoplastic orbital disorder. Exploring the molecular interplay between UC and NSOI may help physicians make earlier diagnoses and enhance treatment approaches. We analyzed gene expression datasets (GSE58331, GSE105149, GSE206285, and GSE179285) for UC and NSOI from the GEO database. Using WGCNA and differential expression analysis, we identified genes commonly altered in both diseases. GO enrichment, PPI networks, and transcription factor prediction were performed using Cytoscape plugins (cytoHubba and iRegulon). Machine learning techniques were employed to assess transcription factor activity and evaluate potential therapeutic targets among the hub genes. We conducted an association analysis using the TwoSampleMR package in R to explore potential causal relationships between NSOI and UC. A total of 85 intersecting genes between NSOI and UC were identified, and enrichment analyses revealed their roles in immune and inflammatory processes. Key biomarkers, including CXCL10, CXCR4, CXCL9, CD27, SELL, MMP9, CD79A, CD3E, GZMK, and CCL19, were highlighted, linking them to processes such as leukocyte migration, viral response, and monocyte differentiation. STAT1 was identified as a shared transcription factor influencing both diseases. Machine learning algorithms identified eight potential genes for diagnostic and therapeutic use, with CXCL10 emerging as a key player in the pathogenesis of NSOI and UC. CXCL10 likely regulates CXCR4, LCK, CCR7, and other genes involved in pathways such as cytokine-cytokine receptor interactions, HIV-1 infection, and Epstein-Barr virus infection. This study offers insights into the co-pathogenic mechanisms of UC and NSOI, providing a foundation for further mechanistic research and therapeutic development.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11871363 | PMC |
http://dx.doi.org/10.1038/s41598-025-89344-y | DOI Listing |