Identification of novel key genes and potential candidate small molecule drugs in diabetic kidney disease using comprehensive bioinformatics analysis
Objective: The currently established diagnostic and prognostic tools for diabetic kidney disease (DKD) have limitations, which demands the necessity to find new genes and pathways associated with diagnosis and treatment. Our study aims to reveal the gene expression alteration and discover critical g...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.934555/full |
| _version_ | 1798042995527778304 |
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| author | Bin Li Bin Li Siyang Ye Siyang Ye Yuting Fan Yuting Fan Yi Lin Yi Lin Suchun Li Suchun Li Huajing Peng Huajing Peng Hui Diao Hui Diao Wei Chen Wei Chen |
| author_facet | Bin Li Bin Li Siyang Ye Siyang Ye Yuting Fan Yuting Fan Yi Lin Yi Lin Suchun Li Suchun Li Huajing Peng Huajing Peng Hui Diao Hui Diao Wei Chen Wei Chen |
| author_sort | Bin Li |
| collection | DOAJ |
| description | Objective: The currently established diagnostic and prognostic tools for diabetic kidney disease (DKD) have limitations, which demands the necessity to find new genes and pathways associated with diagnosis and treatment. Our study aims to reveal the gene expression alteration and discover critical genes involved in the development of DKD, thus providing novel diagnostic molecular markers and therapeutic targets.Materials and methods: The differences of infiltrating immune cells within kidney were compared between healthy living donors and DKD patients. Besides, differentially expressed genes (DEGs) within kidney from healthy living donor, early stage DKD and advanced stage DKD samples were detected. Furthermore, the weighted co-expressed network (WGCNA) and protein-protein interaction (PPI) network were constructed, followed by recognition of core hub genes and module analysis. Receiver operating characteristic (ROC) curve analysis was implemented to determine the diagnostic value of hub genes, correlation analysis was employed to explore the association between hub genes and infiltrating immune cells, and certain hub genes was validated by quantitative real-time PCR and immunohistochemistry staining in cultured tubule cells and diabetic mice kidney. Finally, the candidate small molecules as potential drugs to treat DKD were anticipated through utilizing virtual screening and molecular docking investigation.Results: Our study revealed significantly higher proportion of infiltrating immune cells within kidney from DKD patients via probing the immune landscape by single-cell transcriptomics. Besides, 126 commonly shared DEGs identified among three group samples were enriched in immune biological process. In addition, the ROC curve analysis demonstrated the strong diagnostic accuracy of recognized hub genes (NFKB1, DYRK2, ATAD2, YAP1, and CHD3) from PPI network. Correlation analysis further confirmed the positive association between these hub genes with infiltrating natural killer cells. More importantly, the mRNA transcripts and protein abundance of YAP1 were significantly higher in high glucose-treated renal tubule cells and diabetic mice kidney, and the small molecules exhibiting the best binding affinities with YAP1 were predicted and acquired.Conclusion: Our findings for the first time indicate that NFKB1, DYRK2, ATAD2, YAP1, and CHD3 might be potential novel biomarkers and therapeutic targets for DKD, providing insights into the molecular mechanisms underlying the pathogenesis of DKD. |
| first_indexed | 2024-04-11T22:43:24Z |
| format | Article |
| id | doaj.art-56b452ae7485400d8917b8d5b405bff0 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-11T22:43:24Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-56b452ae7485400d8917b8d5b405bff02022-12-22T03:58:53ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-08-011310.3389/fgene.2022.934555934555Identification of novel key genes and potential candidate small molecule drugs in diabetic kidney disease using comprehensive bioinformatics analysisBin Li0Bin Li1Siyang Ye2Siyang Ye3Yuting Fan4Yuting Fan5Yi Lin6Yi Lin7Suchun Li8Suchun Li9Huajing Peng10Huajing Peng11Hui Diao12Hui Diao13Wei Chen14Wei Chen15Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaNHC Key Laboratory of Clinical Nephrology (Sun Yat-sen University) and Guangdong Provincial Key Laboratory of Nephrology, Guangzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaNHC Key Laboratory of Clinical Nephrology (Sun Yat-sen University) and Guangdong Provincial Key Laboratory of Nephrology, Guangzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaNHC Key Laboratory of Clinical Nephrology (Sun Yat-sen University) and Guangdong Provincial Key Laboratory of Nephrology, Guangzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaNHC Key Laboratory of Clinical Nephrology (Sun Yat-sen University) and Guangdong Provincial Key Laboratory of Nephrology, Guangzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaNHC Key Laboratory of Clinical Nephrology (Sun Yat-sen University) and Guangdong Provincial Key Laboratory of Nephrology, Guangzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaNHC Key Laboratory of Clinical Nephrology (Sun Yat-sen University) and Guangdong Provincial Key Laboratory of Nephrology, Guangzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaNHC Key Laboratory of Clinical Nephrology (Sun Yat-sen University) and Guangdong Provincial Key Laboratory of Nephrology, Guangzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaNHC Key Laboratory of Clinical Nephrology (Sun Yat-sen University) and Guangdong Provincial Key Laboratory of Nephrology, Guangzhou, ChinaObjective: The currently established diagnostic and prognostic tools for diabetic kidney disease (DKD) have limitations, which demands the necessity to find new genes and pathways associated with diagnosis and treatment. Our study aims to reveal the gene expression alteration and discover critical genes involved in the development of DKD, thus providing novel diagnostic molecular markers and therapeutic targets.Materials and methods: The differences of infiltrating immune cells within kidney were compared between healthy living donors and DKD patients. Besides, differentially expressed genes (DEGs) within kidney from healthy living donor, early stage DKD and advanced stage DKD samples were detected. Furthermore, the weighted co-expressed network (WGCNA) and protein-protein interaction (PPI) network were constructed, followed by recognition of core hub genes and module analysis. Receiver operating characteristic (ROC) curve analysis was implemented to determine the diagnostic value of hub genes, correlation analysis was employed to explore the association between hub genes and infiltrating immune cells, and certain hub genes was validated by quantitative real-time PCR and immunohistochemistry staining in cultured tubule cells and diabetic mice kidney. Finally, the candidate small molecules as potential drugs to treat DKD were anticipated through utilizing virtual screening and molecular docking investigation.Results: Our study revealed significantly higher proportion of infiltrating immune cells within kidney from DKD patients via probing the immune landscape by single-cell transcriptomics. Besides, 126 commonly shared DEGs identified among three group samples were enriched in immune biological process. In addition, the ROC curve analysis demonstrated the strong diagnostic accuracy of recognized hub genes (NFKB1, DYRK2, ATAD2, YAP1, and CHD3) from PPI network. Correlation analysis further confirmed the positive association between these hub genes with infiltrating natural killer cells. More importantly, the mRNA transcripts and protein abundance of YAP1 were significantly higher in high glucose-treated renal tubule cells and diabetic mice kidney, and the small molecules exhibiting the best binding affinities with YAP1 were predicted and acquired.Conclusion: Our findings for the first time indicate that NFKB1, DYRK2, ATAD2, YAP1, and CHD3 might be potential novel biomarkers and therapeutic targets for DKD, providing insights into the molecular mechanisms underlying the pathogenesis of DKD.https://www.frontiersin.org/articles/10.3389/fgene.2022.934555/fulldiabetic kidney diseasebioinformatics analysissmall-molecule drugsdifferentially expressed genesnovel biomarkersyes-associated protein 1 |
| spellingShingle | Bin Li Bin Li Siyang Ye Siyang Ye Yuting Fan Yuting Fan Yi Lin Yi Lin Suchun Li Suchun Li Huajing Peng Huajing Peng Hui Diao Hui Diao Wei Chen Wei Chen Identification of novel key genes and potential candidate small molecule drugs in diabetic kidney disease using comprehensive bioinformatics analysis Frontiers in Genetics diabetic kidney disease bioinformatics analysis small-molecule drugs differentially expressed genes novel biomarkers yes-associated protein 1 |
| title | Identification of novel key genes and potential candidate small molecule drugs in diabetic kidney disease using comprehensive bioinformatics analysis |
| title_full | Identification of novel key genes and potential candidate small molecule drugs in diabetic kidney disease using comprehensive bioinformatics analysis |
| title_fullStr | Identification of novel key genes and potential candidate small molecule drugs in diabetic kidney disease using comprehensive bioinformatics analysis |
| title_full_unstemmed | Identification of novel key genes and potential candidate small molecule drugs in diabetic kidney disease using comprehensive bioinformatics analysis |
| title_short | Identification of novel key genes and potential candidate small molecule drugs in diabetic kidney disease using comprehensive bioinformatics analysis |
| title_sort | identification of novel key genes and potential candidate small molecule drugs in diabetic kidney disease using comprehensive bioinformatics analysis |
| topic | diabetic kidney disease bioinformatics analysis small-molecule drugs differentially expressed genes novel biomarkers yes-associated protein 1 |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.934555/full |
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