Exploring the common diagnostic gene KCNJ15 and shared pathway of ankylosing spondylitis and ulcerative colitis through integrated bioinformatics
Introduction: The similarity between ankylosing spondylitis (AS) and ulcerative colitis (UC) in incidence rate and pathogenesis has been revealed. But the common pathogenesis that explains the relationship between AS and UC is still lacked, and the related genetic research is limited. We purposed to...
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| Format: | Article |
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Frontiers Media S.A.
2023-05-01
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| Series: | Frontiers in Physiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphys.2023.1146538/full |
| _version_ | 1797833178256244736 |
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| author | Su-Zhe Zhou Su-Zhe Zhou Li Shen Zhong-Biao Fu Hao Li Ying-Lian Pan Run-Ze Yu |
| author_facet | Su-Zhe Zhou Su-Zhe Zhou Li Shen Zhong-Biao Fu Hao Li Ying-Lian Pan Run-Ze Yu |
| author_sort | Su-Zhe Zhou |
| collection | DOAJ |
| description | Introduction: The similarity between ankylosing spondylitis (AS) and ulcerative colitis (UC) in incidence rate and pathogenesis has been revealed. But the common pathogenesis that explains the relationship between AS and UC is still lacked, and the related genetic research is limited. We purposed to explore shared biomarkers and pathways of AS and UC through integrated bioinformatics.Methods: Gene expression data of AS and UC were obtained in the GEO database. We applied weighted gene co-expression network analysis (WGCNA) to identify AS-related and UC-related co-expression gene modules. Subsequently, machine learning algorithm was used to further screen hub genes. We validated the expression level and diagnostic efficiency of the shared diagnostic gene of AS and UC in external datasets. Gene set enrichment analysis (GSEA) was applied to analyze pathway-level changes between disease group and normal group. Finally, we analyzed the relationship between hub biomarker and immune microenvironment by using the CIBERSORT deconvolution algorithm.Results: 203 genes were obtained by overlapping AS-related gene module and UC-related gene module. Through SVM-RFE algorithm, 19 hub diagnostic genes were selected for AS in GSE25101 and 6 hub diagnostic genes were selected for UC in GSE94648. KCNJ15 was obtained as a common diagnostic gene of AS and UC. The expression of KCNJ15 was validated in independent datasets, and the results showed that KCNJ15 were similarly upregulated in AS samples and UC samples. Besides, ROC analysis also revealed that KCNJ15 had good diagnostic efficacy. The GSEA analysis revealed that oxidative phosphorylation pathway was the shared pathway of AS and UC. In addition, CIBERSORT results revealed the correlation between KCNJ15 gene and immune microenvironment in AS and UC.Conclusion: We have explored a common diagnostic gene KCNJ15 and a shared oxidative phosphorylation pathway of AS and UC through integrated bioinformatics, which may provide a potential diagnostic biomarker and novel insight for studying the mechanism of AS-related UC. |
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| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-04-09T14:19:15Z |
| publishDate | 2023-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj.art-1fc26ca32e8b403ab3187b74d3b210b62023-05-05T04:29:13ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2023-05-011410.3389/fphys.2023.11465381146538Exploring the common diagnostic gene KCNJ15 and shared pathway of ankylosing spondylitis and ulcerative colitis through integrated bioinformaticsSu-Zhe Zhou0Su-Zhe Zhou1Li Shen2Zhong-Biao Fu3Hao Li4Ying-Lian Pan5Run-Ze Yu6Department of Orthopedics, Anhui No 2 Provincial People’s Hospital, Hefei, ChinaDepartment of General Practice, Hefei BOE Hospital, Hefei, ChinaBeijing United Family Hospital, Beijing, ChinaDepartment of Gastroenterology, The Gastroenterology Clinical Medical Center of Hainan Province, The Second Affiliated Hospital of Hai Nan Medical University, Haikou, ChinaGraduate School, Tianjin Medical University, Tianjin, ChinaDepartment of Medical Oncology, The First Affiliated Hospital of Hainan Medical University, Haikou, ChinaDepartment of Orthopedics, Anhui No 2 Provincial People’s Hospital, Hefei, ChinaIntroduction: The similarity between ankylosing spondylitis (AS) and ulcerative colitis (UC) in incidence rate and pathogenesis has been revealed. But the common pathogenesis that explains the relationship between AS and UC is still lacked, and the related genetic research is limited. We purposed to explore shared biomarkers and pathways of AS and UC through integrated bioinformatics.Methods: Gene expression data of AS and UC were obtained in the GEO database. We applied weighted gene co-expression network analysis (WGCNA) to identify AS-related and UC-related co-expression gene modules. Subsequently, machine learning algorithm was used to further screen hub genes. We validated the expression level and diagnostic efficiency of the shared diagnostic gene of AS and UC in external datasets. Gene set enrichment analysis (GSEA) was applied to analyze pathway-level changes between disease group and normal group. Finally, we analyzed the relationship between hub biomarker and immune microenvironment by using the CIBERSORT deconvolution algorithm.Results: 203 genes were obtained by overlapping AS-related gene module and UC-related gene module. Through SVM-RFE algorithm, 19 hub diagnostic genes were selected for AS in GSE25101 and 6 hub diagnostic genes were selected for UC in GSE94648. KCNJ15 was obtained as a common diagnostic gene of AS and UC. The expression of KCNJ15 was validated in independent datasets, and the results showed that KCNJ15 were similarly upregulated in AS samples and UC samples. Besides, ROC analysis also revealed that KCNJ15 had good diagnostic efficacy. The GSEA analysis revealed that oxidative phosphorylation pathway was the shared pathway of AS and UC. In addition, CIBERSORT results revealed the correlation between KCNJ15 gene and immune microenvironment in AS and UC.Conclusion: We have explored a common diagnostic gene KCNJ15 and a shared oxidative phosphorylation pathway of AS and UC through integrated bioinformatics, which may provide a potential diagnostic biomarker and novel insight for studying the mechanism of AS-related UC.https://www.frontiersin.org/articles/10.3389/fphys.2023.1146538/fullankylosing spondylitisulcerative colitisWGCNAmachine learning algorithmimmune cells infiltration |
| spellingShingle | Su-Zhe Zhou Su-Zhe Zhou Li Shen Zhong-Biao Fu Hao Li Ying-Lian Pan Run-Ze Yu Exploring the common diagnostic gene KCNJ15 and shared pathway of ankylosing spondylitis and ulcerative colitis through integrated bioinformatics Frontiers in Physiology ankylosing spondylitis ulcerative colitis WGCNA machine learning algorithm immune cells infiltration |
| title | Exploring the common diagnostic gene KCNJ15 and shared pathway of ankylosing spondylitis and ulcerative colitis through integrated bioinformatics |
| title_full | Exploring the common diagnostic gene KCNJ15 and shared pathway of ankylosing spondylitis and ulcerative colitis through integrated bioinformatics |
| title_fullStr | Exploring the common diagnostic gene KCNJ15 and shared pathway of ankylosing spondylitis and ulcerative colitis through integrated bioinformatics |
| title_full_unstemmed | Exploring the common diagnostic gene KCNJ15 and shared pathway of ankylosing spondylitis and ulcerative colitis through integrated bioinformatics |
| title_short | Exploring the common diagnostic gene KCNJ15 and shared pathway of ankylosing spondylitis and ulcerative colitis through integrated bioinformatics |
| title_sort | exploring the common diagnostic gene kcnj15 and shared pathway of ankylosing spondylitis and ulcerative colitis through integrated bioinformatics |
| topic | ankylosing spondylitis ulcerative colitis WGCNA machine learning algorithm immune cells infiltration |
| url | https://www.frontiersin.org/articles/10.3389/fphys.2023.1146538/full |
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