Exploration of the shared pathways and common biomarker PAN3 in ankylosing spondylitis and ulcerative colitis using integrated bioinformatics analysis

被引:4
作者
Zhang, Minna [1 ]
Zhou, Junyi [2 ]
Wang, Honggang [1 ,3 ]
He, Le [1 ]
Wang, Jingyi [1 ]
Yang, Xiaozhong [1 ]
Zhong, Xiaomin [2 ]
机构
[1] Nanjing Med Univ, Dept Gastroenterol, Affiliated Huaian Peoples Hosp 1, Huaian, Jiangsu, Peoples R China
[2] Xuzhou Med Univ, Dept Oncol, Huaian Clin Coll, Huaian, Jiangsu, Peoples R China
[3] Nanjing Med Univ, Digest Dis Ctr, Affiliated Huaian Peoples Hosp 1, Huaian, Jiangsu, Peoples R China
关键词
ulcerative colitis; ankylosing spondylitis; weighted gene co-expression network analysis; mitogen-activated protein kinase; PAN3; INFLAMMATORY-BOWEL-DISEASE; EXTRAINTESTINAL MANIFESTATIONS; PATHOGENESIS; INHIBITION; PREVALENCE; CELLS;
D O I
10.3389/fimmu.2023.1089622
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
BackgroundUlcerative 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. MethodsMicroarray 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. ResultsA 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. PAN3 was selected as the optimal common biomarker for UC and AS. Immune infiltration analysis showed that the expression of PAN3 was correlated with changes in immune cells. ConclusionThis 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 PAN3 may be a potential diagnostic marker for patients with UC complicated by AS.
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页数:13
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