Screening and Identification of Hub Genes in the Development of Early Diabetic Kidney Disease Based on Weighted Gene Co-Expression Network Analysis
ObjectiveThe study aimed to screen key genes in early diabetic kidney disease (DKD) and predict their biological functions and signaling pathways using bioinformatics analysis of gene chips interrelated to early DKD in the Gene Expression Omnibus database.MethodsGene chip data for early DKD was obta...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-06-01
|
| Series: | Frontiers in Endocrinology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2022.883658/full |
| _version_ | 1827378646135865344 |
|---|---|
| author | Ran Wei Jingtao Qiao Di Cui Qi Pan Lixin Guo |
| author_facet | Ran Wei Jingtao Qiao Di Cui Qi Pan Lixin Guo |
| author_sort | Ran Wei |
| collection | DOAJ |
| description | ObjectiveThe study aimed to screen key genes in early diabetic kidney disease (DKD) and predict their biological functions and signaling pathways using bioinformatics analysis of gene chips interrelated to early DKD in the Gene Expression Omnibus database.MethodsGene chip data for early DKD was obtained from the Gene Expression Omnibus expression profile database. We analyzed differentially expressed genes (DEGs) between patients with early DKD and healthy controls using the R language. For the screened DEGs, we predicted the biological functions and relevant signaling pathways by enrichment analysis of Gene Ontology (GO) biological functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways. Using the STRING database and Cytoscape software, we constructed a protein interaction network to screen hub pathogenic genes. Finally, we performed immunohistochemistry on kidney specimens from the Beijing Hospital to verify the above findings.ResultsA total of 267 differential genes were obtained using GSE142025, namely, 176 upregulated and 91 downregulated genes. GO functional annotation enrichment analysis indicated that the DEGs were mainly involved in immune inflammatory response and cytokine effects. KEGG pathway analysis indicated that C-C receptor interactions and the IL-17 signaling pathway are essential for early DKD. We identified FOS, EGR1, ATF3, and JUN as hub sites of protein interactions using a protein–protein interaction network and module analysis. We performed immunohistochemistry (IHC) on five samples of early DKD and three normal samples from the Beijing Hospital to label the proteins. This demonstrated that FOS, EGR1, ATF3, and JUN in the early DKD group were significantly downregulated.ConclusionThe four hub genes FOS, EGR1, ATF3, and JUN were strongly associated with the infiltration of monocytes, M2 macrophages, and T regulatory cells in early DKD samples. We revealed that the expression of immune response or inflammatory genes was suppressed in early DKD. Meanwhile, the FOS group of low-expression genes showed that the activated biological functions included mRNA methylation, insulin receptor binding, and protein kinase A binding. These genes and pathways may serve as potential targets for treating early DKD. |
| first_indexed | 2024-03-08T13:00:00Z |
| format | Article |
| id | doaj.art-1883bd3c8706436680a45692b34e86fe |
| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-03-08T13:00:00Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Endocrinology |
| spelling | doaj.art-1883bd3c8706436680a45692b34e86fe2024-01-19T09:51:32ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922022-06-011310.3389/fendo.2022.883658883658Screening and Identification of Hub Genes in the Development of Early Diabetic Kidney Disease Based on Weighted Gene Co-Expression Network AnalysisRan Wei0Jingtao Qiao1Di Cui2Qi Pan3Lixin Guo4Department of Endocrinology, Peking University Fifth School of Clinical Medicine, Beijing, ChinaDepartment of Endocrinology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, ChinaDepartment of Pathology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, ChinaDepartment of Endocrinology, Peking University Fifth School of Clinical Medicine, Beijing, ChinaDepartment of Endocrinology, Peking University Fifth School of Clinical Medicine, Beijing, ChinaObjectiveThe study aimed to screen key genes in early diabetic kidney disease (DKD) and predict their biological functions and signaling pathways using bioinformatics analysis of gene chips interrelated to early DKD in the Gene Expression Omnibus database.MethodsGene chip data for early DKD was obtained from the Gene Expression Omnibus expression profile database. We analyzed differentially expressed genes (DEGs) between patients with early DKD and healthy controls using the R language. For the screened DEGs, we predicted the biological functions and relevant signaling pathways by enrichment analysis of Gene Ontology (GO) biological functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways. Using the STRING database and Cytoscape software, we constructed a protein interaction network to screen hub pathogenic genes. Finally, we performed immunohistochemistry on kidney specimens from the Beijing Hospital to verify the above findings.ResultsA total of 267 differential genes were obtained using GSE142025, namely, 176 upregulated and 91 downregulated genes. GO functional annotation enrichment analysis indicated that the DEGs were mainly involved in immune inflammatory response and cytokine effects. KEGG pathway analysis indicated that C-C receptor interactions and the IL-17 signaling pathway are essential for early DKD. We identified FOS, EGR1, ATF3, and JUN as hub sites of protein interactions using a protein–protein interaction network and module analysis. We performed immunohistochemistry (IHC) on five samples of early DKD and three normal samples from the Beijing Hospital to label the proteins. This demonstrated that FOS, EGR1, ATF3, and JUN in the early DKD group were significantly downregulated.ConclusionThe four hub genes FOS, EGR1, ATF3, and JUN were strongly associated with the infiltration of monocytes, M2 macrophages, and T regulatory cells in early DKD samples. We revealed that the expression of immune response or inflammatory genes was suppressed in early DKD. Meanwhile, the FOS group of low-expression genes showed that the activated biological functions included mRNA methylation, insulin receptor binding, and protein kinase A binding. These genes and pathways may serve as potential targets for treating early DKD.https://www.frontiersin.org/articles/10.3389/fendo.2022.883658/fullbioinformaticsWGCNAGSEA analysisearly diabetic kidney diseasehub gene |
| spellingShingle | Ran Wei Jingtao Qiao Di Cui Qi Pan Lixin Guo Screening and Identification of Hub Genes in the Development of Early Diabetic Kidney Disease Based on Weighted Gene Co-Expression Network Analysis Frontiers in Endocrinology bioinformatics WGCNA GSEA analysis early diabetic kidney disease hub gene |
| title | Screening and Identification of Hub Genes in the Development of Early Diabetic Kidney Disease Based on Weighted Gene Co-Expression Network Analysis |
| title_full | Screening and Identification of Hub Genes in the Development of Early Diabetic Kidney Disease Based on Weighted Gene Co-Expression Network Analysis |
| title_fullStr | Screening and Identification of Hub Genes in the Development of Early Diabetic Kidney Disease Based on Weighted Gene Co-Expression Network Analysis |
| title_full_unstemmed | Screening and Identification of Hub Genes in the Development of Early Diabetic Kidney Disease Based on Weighted Gene Co-Expression Network Analysis |
| title_short | Screening and Identification of Hub Genes in the Development of Early Diabetic Kidney Disease Based on Weighted Gene Co-Expression Network Analysis |
| title_sort | screening and identification of hub genes in the development of early diabetic kidney disease based on weighted gene co expression network analysis |
| topic | bioinformatics WGCNA GSEA analysis early diabetic kidney disease hub gene |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2022.883658/full |
| work_keys_str_mv | AT ranwei screeningandidentificationofhubgenesinthedevelopmentofearlydiabetickidneydiseasebasedonweightedgenecoexpressionnetworkanalysis AT jingtaoqiao screeningandidentificationofhubgenesinthedevelopmentofearlydiabetickidneydiseasebasedonweightedgenecoexpressionnetworkanalysis AT dicui screeningandidentificationofhubgenesinthedevelopmentofearlydiabetickidneydiseasebasedonweightedgenecoexpressionnetworkanalysis AT qipan screeningandidentificationofhubgenesinthedevelopmentofearlydiabetickidneydiseasebasedonweightedgenecoexpressionnetworkanalysis AT lixinguo screeningandidentificationofhubgenesinthedevelopmentofearlydiabetickidneydiseasebasedonweightedgenecoexpressionnetworkanalysis |