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Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy
OBJECTIVES: The underlying molecular mechanisms of diabetic nephropathy have yet not been investigated clearly. In this investigation, we aimed to identify key genes involved in the pathogenesis and prognosis of diabetic nephropathy. METHODS: We downloaded next-generation sequencing data set GSE1420...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9661593/ https://www.ncbi.nlm.nih.gov/pubmed/36385790 http://dx.doi.org/10.1177/20503121221137005 |
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author | Joshi, Harish Vastrad, Basavaraj Joshi, Nidhi Vastrad, Chanabasayya |
author_facet | Joshi, Harish Vastrad, Basavaraj Joshi, Nidhi Vastrad, Chanabasayya |
author_sort | Joshi, Harish |
collection | PubMed |
description | OBJECTIVES: The underlying molecular mechanisms of diabetic nephropathy have yet not been investigated clearly. In this investigation, we aimed to identify key genes involved in the pathogenesis and prognosis of diabetic nephropathy. METHODS: We downloaded next-generation sequencing data set GSE142025 from Gene Expression Omnibus database having 28 diabetic nephropathy samples and nine normal control samples. The differentially expressed genes between diabetic nephropathy and normal control samples were analyzed. Biological function analysis of the differentially expressed genes was enriched by Gene Ontology and REACTOME pathways. Then, we established the protein–protein interaction network, modules, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network. Hub genes were validated by using receiver operating characteristic curve analysis. RESULTS: A total of 549 differentially expressed genes were detected including 275 upregulated and 274 downregulated genes. The biological process analysis of functional enrichment showed that these differentially expressed genes were mainly enriched in cell activation, integral component of plasma membrane, lipid binding, and biological oxidations. Analyzing the protein–protein interaction network, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network, we screened hub genes MDFI, LCK, BTK, IRF4, PRKCB, EGR1, JUN, FOS, ALB, and NR4A1 by the Cytoscape software. The receiver operating characteristic curve analysis confirmed that hub genes were of diagnostic value. CONCLUSIONS: Taken above, using integrated bioinformatics analysis, we have identified key genes and pathways in diabetic nephropathy, which could improve our understanding of the cause and underlying molecular events, and these key genes and pathways might be therapeutic targets for diabetic nephropathy. |
format | Online Article Text |
id | pubmed-9661593 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-96615932022-11-15 Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy Joshi, Harish Vastrad, Basavaraj Joshi, Nidhi Vastrad, Chanabasayya SAGE Open Med Original Research Article OBJECTIVES: The underlying molecular mechanisms of diabetic nephropathy have yet not been investigated clearly. In this investigation, we aimed to identify key genes involved in the pathogenesis and prognosis of diabetic nephropathy. METHODS: We downloaded next-generation sequencing data set GSE142025 from Gene Expression Omnibus database having 28 diabetic nephropathy samples and nine normal control samples. The differentially expressed genes between diabetic nephropathy and normal control samples were analyzed. Biological function analysis of the differentially expressed genes was enriched by Gene Ontology and REACTOME pathways. Then, we established the protein–protein interaction network, modules, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network. Hub genes were validated by using receiver operating characteristic curve analysis. RESULTS: A total of 549 differentially expressed genes were detected including 275 upregulated and 274 downregulated genes. The biological process analysis of functional enrichment showed that these differentially expressed genes were mainly enriched in cell activation, integral component of plasma membrane, lipid binding, and biological oxidations. Analyzing the protein–protein interaction network, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network, we screened hub genes MDFI, LCK, BTK, IRF4, PRKCB, EGR1, JUN, FOS, ALB, and NR4A1 by the Cytoscape software. The receiver operating characteristic curve analysis confirmed that hub genes were of diagnostic value. CONCLUSIONS: Taken above, using integrated bioinformatics analysis, we have identified key genes and pathways in diabetic nephropathy, which could improve our understanding of the cause and underlying molecular events, and these key genes and pathways might be therapeutic targets for diabetic nephropathy. SAGE Publications 2022-11-11 /pmc/articles/PMC9661593/ /pubmed/36385790 http://dx.doi.org/10.1177/20503121221137005 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Article Joshi, Harish Vastrad, Basavaraj Joshi, Nidhi Vastrad, Chanabasayya Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy |
title | Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy |
title_full | Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy |
title_fullStr | Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy |
title_full_unstemmed | Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy |
title_short | Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy |
title_sort | integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9661593/ https://www.ncbi.nlm.nih.gov/pubmed/36385790 http://dx.doi.org/10.1177/20503121221137005 |
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