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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...

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Autores principales: Joshi, Harish, Vastrad, Basavaraj, Joshi, Nidhi, Vastrad, Chanabasayya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
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.
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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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