Identification of new diagnostic targets for hepatitis B virus‐induced liver fibrosis
Abstract Background Liver fibrosis is a transitional stage from hepatitis to cirrhosis, and hepatitis B virus (HBV) is the most common cause of liver disease. Transcriptome sequencing technology and bioinformatics analysis are increasingly being used to screen diagnostic targets for liver fibrosis....
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Wiley
2024-03-01
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| Online Access: | https://doi.org/10.1002/ila2.30 |
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| author | Ying Wang Shuo Qin Meng Yang Xiaoling Wang |
| author_facet | Ying Wang Shuo Qin Meng Yang Xiaoling Wang |
| author_sort | Ying Wang |
| collection | DOAJ |
| description | Abstract Background Liver fibrosis is a transitional stage from hepatitis to cirrhosis, and hepatitis B virus (HBV) is the most common cause of liver disease. Transcriptome sequencing technology and bioinformatics analysis are increasingly being used to screen diagnostic targets for liver fibrosis. Methods The GSE171294 dataset of HBV‐induced liver fibrosis tissue and normal tissue was obtained from the Gene Expression Omnibus (GEO) public database and used to screen for differentially expressed mRNAs using R software. mRNAs with |log fold change| >1 and p < 0.05 were considered to be differentially expressed. A heat map was drawn to visualize the expression patterns of the differentially expressed mRNAs. To screen for candidate target mRNAs, the differentially expressed mRNAs were annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis. Finally, a protein–protein interaction (PPI) network was constructed to analyze the relationships between the differentially expressed mRNAs. Results A total of 243 differentially expressed mRNAs were identified (p < 0.05); 129 were up‐regulated and 114 were down‐regulated. The up‐regulated and down‐regulated mRNAs were significantly enriched in 16 and 8 KEGG pathways, respectively. The enriched KEGG pathways included Salmonella infection, Protein processing in the endoplasmic reticulum, IL‐17 signaling pathway, and Aldosterone synthesis and secretion. The enriched GO terms were related mainly to cell proliferation, apoptosis, endoplasmic reticulum complex assembly, and myosin synthesis. The PPI network contained 161 nodes and 120 pairs of interactions. The top 10 key nodes were CAV1, CD4, NR3C1, PDIA3, EZR, IRF4, SOX9, HSP90AB1, CD40, and SEC13. Conclusions Bioinformatics analysis of the transcriptome sequencing data in the GSE171294 dataset identified CD4, NR3C1, and EZR and other genes at key nodes as new targets for the treatment of liver fibrosis caused by HBV. These results provide new insights for HBV‐induced liver fibrosis research and clinical treatment. |
| format | Article |
| id | doaj-art-a097a2051ea24be8a6a7fd3e38e077c1 |
| institution | Kabale University |
| issn | 2834-443X 2834-4448 |
| language | English |
| publishDate | 2024-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | iLabmed |
| spelling | doaj-art-a097a2051ea24be8a6a7fd3e38e077c12025-08-20T04:01:16ZengWileyiLabmed2834-443X2834-44482024-03-0121273710.1002/ila2.30Identification of new diagnostic targets for hepatitis B virus‐induced liver fibrosisYing Wang0Shuo Qin1Meng Yang2Xiaoling Wang3Department of Clinical Laboratory Shanxi Hospital of Traditional Chinese Medicine Taiyuan Shanxi Province ChinaAcademy of Medical Sciences Shanxi Medical University Taiyuan Shanxi Province ChinaDepartment of Clinical Laboratory Shanxi Hospital of Traditional Chinese Medicine Taiyuan Shanxi Province ChinaDepartment of Clinical Laboratory Shanxi Hospital of Traditional Chinese Medicine Taiyuan Shanxi Province ChinaAbstract Background Liver fibrosis is a transitional stage from hepatitis to cirrhosis, and hepatitis B virus (HBV) is the most common cause of liver disease. Transcriptome sequencing technology and bioinformatics analysis are increasingly being used to screen diagnostic targets for liver fibrosis. Methods The GSE171294 dataset of HBV‐induced liver fibrosis tissue and normal tissue was obtained from the Gene Expression Omnibus (GEO) public database and used to screen for differentially expressed mRNAs using R software. mRNAs with |log fold change| >1 and p < 0.05 were considered to be differentially expressed. A heat map was drawn to visualize the expression patterns of the differentially expressed mRNAs. To screen for candidate target mRNAs, the differentially expressed mRNAs were annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis. Finally, a protein–protein interaction (PPI) network was constructed to analyze the relationships between the differentially expressed mRNAs. Results A total of 243 differentially expressed mRNAs were identified (p < 0.05); 129 were up‐regulated and 114 were down‐regulated. The up‐regulated and down‐regulated mRNAs were significantly enriched in 16 and 8 KEGG pathways, respectively. The enriched KEGG pathways included Salmonella infection, Protein processing in the endoplasmic reticulum, IL‐17 signaling pathway, and Aldosterone synthesis and secretion. The enriched GO terms were related mainly to cell proliferation, apoptosis, endoplasmic reticulum complex assembly, and myosin synthesis. The PPI network contained 161 nodes and 120 pairs of interactions. The top 10 key nodes were CAV1, CD4, NR3C1, PDIA3, EZR, IRF4, SOX9, HSP90AB1, CD40, and SEC13. Conclusions Bioinformatics analysis of the transcriptome sequencing data in the GSE171294 dataset identified CD4, NR3C1, and EZR and other genes at key nodes as new targets for the treatment of liver fibrosis caused by HBV. These results provide new insights for HBV‐induced liver fibrosis research and clinical treatment.https://doi.org/10.1002/ila2.30expression profilesHBVliver fibrosistranscriptome sequencing |
| spellingShingle | Ying Wang Shuo Qin Meng Yang Xiaoling Wang Identification of new diagnostic targets for hepatitis B virus‐induced liver fibrosis iLabmed expression profiles HBV liver fibrosis transcriptome sequencing |
| title | Identification of new diagnostic targets for hepatitis B virus‐induced liver fibrosis |
| title_full | Identification of new diagnostic targets for hepatitis B virus‐induced liver fibrosis |
| title_fullStr | Identification of new diagnostic targets for hepatitis B virus‐induced liver fibrosis |
| title_full_unstemmed | Identification of new diagnostic targets for hepatitis B virus‐induced liver fibrosis |
| title_short | Identification of new diagnostic targets for hepatitis B virus‐induced liver fibrosis |
| title_sort | identification of new diagnostic targets for hepatitis b virus induced liver fibrosis |
| topic | expression profiles HBV liver fibrosis transcriptome sequencing |
| url | https://doi.org/10.1002/ila2.30 |
| work_keys_str_mv | AT yingwang identificationofnewdiagnostictargetsforhepatitisbvirusinducedliverfibrosis AT shuoqin identificationofnewdiagnostictargetsforhepatitisbvirusinducedliverfibrosis AT mengyang identificationofnewdiagnostictargetsforhepatitisbvirusinducedliverfibrosis AT xiaolingwang identificationofnewdiagnostictargetsforhepatitisbvirusinducedliverfibrosis |