Integrative bioinformatics analysis and experimental validation of key biomarkers for risk stratification in primary biliary cholangitis
Abstract Background Primary biliary cholangitis (PBC) is an autoimmune liver disease, whose etiology is yet to be fully elucidated. Currently, ursodeoxycholic acid (UDCA) is the only first-line drug. However, 40% of PBC patients respond poorly to it and carry a potential risk of disease progression....
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-10-01
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| Series: | Arthritis Research & Therapy |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13075-023-03163-y |
| _version_ | 1827633524986871808 |
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| author | Siyuan Tian Yinan Hu Miao Zhang Kemei Wang Guanya Guo Bo Li Yulong Shang Ying Han |
| author_facet | Siyuan Tian Yinan Hu Miao Zhang Kemei Wang Guanya Guo Bo Li Yulong Shang Ying Han |
| author_sort | Siyuan Tian |
| collection | DOAJ |
| description | Abstract Background Primary biliary cholangitis (PBC) is an autoimmune liver disease, whose etiology is yet to be fully elucidated. Currently, ursodeoxycholic acid (UDCA) is the only first-line drug. However, 40% of PBC patients respond poorly to it and carry a potential risk of disease progression. So, in this study, we aimed to explore new biomarkers for risk stratification in PBC patients to enhance treatment. Methods We first downloaded the clinical characteristics and microarray datasets of PBC patients from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified and subjected to enrichment analysis. Hub genes were further validated in multiple public datasets and PBC mouse model. Furthermore, we also verified the expression of the hub genes and developed a predictive model in our clinical specimens. Results A total of 166 DEGs were identified in the GSE79850 dataset, including 95 upregulated and 71 downregulated genes. Enrichment analysis indicated that DEGs were significantly enriched in inflammatory or immune-related process. Among these DEGs, 15 risk-related genes were recognized and further validated in the GSE119600 cohort. Then, TXNIP, CD44, ENTPD1, and PDGFRB were identified as candidate hub genes. Finally, we proceeded to the next screening with these four genes in our serum samples and developed a three-gene panel. The gene panel could effectively identify those patients at risk of disease progression, yielding an AUC of 0.777 (95% CI, 0.657–0.870). Conclusions In summary, combining bioinformatics analysis and experiment validation, we identified TXNIP, CD44, and ENTPD1 as promising biomarkers for risk stratification in PBC patients. |
| first_indexed | 2024-03-09T15:00:45Z |
| format | Article |
| id | doaj.art-1df9ff9b52a2451ba1d3890a69a1f61b |
| institution | Directory Open Access Journal |
| issn | 1478-6362 |
| language | English |
| last_indexed | 2024-03-09T15:00:45Z |
| publishDate | 2023-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Arthritis Research & Therapy |
| spelling | doaj.art-1df9ff9b52a2451ba1d3890a69a1f61b2023-11-26T13:54:42ZengBMCArthritis Research & Therapy1478-63622023-10-0125111410.1186/s13075-023-03163-yIntegrative bioinformatics analysis and experimental validation of key biomarkers for risk stratification in primary biliary cholangitisSiyuan Tian0Yinan Hu1Miao Zhang2Kemei Wang3Guanya Guo4Bo Li5Yulong Shang6Ying Han7State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Air Force Medical UniversityState Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Air Force Medical UniversityState Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Air Force Medical UniversityState Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Air Force Medical UniversityState Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Air Force Medical UniversityState Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Air Force Medical UniversityState Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Air Force Medical UniversityState Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Air Force Medical UniversityAbstract Background Primary biliary cholangitis (PBC) is an autoimmune liver disease, whose etiology is yet to be fully elucidated. Currently, ursodeoxycholic acid (UDCA) is the only first-line drug. However, 40% of PBC patients respond poorly to it and carry a potential risk of disease progression. So, in this study, we aimed to explore new biomarkers for risk stratification in PBC patients to enhance treatment. Methods We first downloaded the clinical characteristics and microarray datasets of PBC patients from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified and subjected to enrichment analysis. Hub genes were further validated in multiple public datasets and PBC mouse model. Furthermore, we also verified the expression of the hub genes and developed a predictive model in our clinical specimens. Results A total of 166 DEGs were identified in the GSE79850 dataset, including 95 upregulated and 71 downregulated genes. Enrichment analysis indicated that DEGs were significantly enriched in inflammatory or immune-related process. Among these DEGs, 15 risk-related genes were recognized and further validated in the GSE119600 cohort. Then, TXNIP, CD44, ENTPD1, and PDGFRB were identified as candidate hub genes. Finally, we proceeded to the next screening with these four genes in our serum samples and developed a three-gene panel. The gene panel could effectively identify those patients at risk of disease progression, yielding an AUC of 0.777 (95% CI, 0.657–0.870). Conclusions In summary, combining bioinformatics analysis and experiment validation, we identified TXNIP, CD44, and ENTPD1 as promising biomarkers for risk stratification in PBC patients.https://doi.org/10.1186/s13075-023-03163-yPrimary biliary cholangitisGEO databaseBiomarkerBioinformatics analysisRisk stratification |
| spellingShingle | Siyuan Tian Yinan Hu Miao Zhang Kemei Wang Guanya Guo Bo Li Yulong Shang Ying Han Integrative bioinformatics analysis and experimental validation of key biomarkers for risk stratification in primary biliary cholangitis Arthritis Research & Therapy Primary biliary cholangitis GEO database Biomarker Bioinformatics analysis Risk stratification |
| title | Integrative bioinformatics analysis and experimental validation of key biomarkers for risk stratification in primary biliary cholangitis |
| title_full | Integrative bioinformatics analysis and experimental validation of key biomarkers for risk stratification in primary biliary cholangitis |
| title_fullStr | Integrative bioinformatics analysis and experimental validation of key biomarkers for risk stratification in primary biliary cholangitis |
| title_full_unstemmed | Integrative bioinformatics analysis and experimental validation of key biomarkers for risk stratification in primary biliary cholangitis |
| title_short | Integrative bioinformatics analysis and experimental validation of key biomarkers for risk stratification in primary biliary cholangitis |
| title_sort | integrative bioinformatics analysis and experimental validation of key biomarkers for risk stratification in primary biliary cholangitis |
| topic | Primary biliary cholangitis GEO database Biomarker Bioinformatics analysis Risk stratification |
| url | https://doi.org/10.1186/s13075-023-03163-y |
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