Cargando…
Microarray analysis reveals gene and microRNA signatures in diabetic kidney disease
The current study aimed to identify therapeutic gene and microRNA (miRNA) biomarkers for diabetic kidney disease (DKD). The public expression profile GSE30122 was used. Following data preprocessing, the limma package was used to select differentially-expressed genes (DEGs) in DKD glomeruli samples a...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783455/ https://www.ncbi.nlm.nih.gov/pubmed/29207157 http://dx.doi.org/10.3892/mmr.2017.8177 |
_version_ | 1783295281454907392 |
---|---|
author | Cui, Chengji Cui, Yabin Fu, Yanyan Ma, Sichao Zhang, Shoulin |
author_facet | Cui, Chengji Cui, Yabin Fu, Yanyan Ma, Sichao Zhang, Shoulin |
author_sort | Cui, Chengji |
collection | PubMed |
description | The current study aimed to identify therapeutic gene and microRNA (miRNA) biomarkers for diabetic kidney disease (DKD). The public expression profile GSE30122 was used. Following data preprocessing, the limma package was used to select differentially-expressed genes (DEGs) in DKD glomeruli samples and tubuli samples and they were compared with corresponding controls. Then overlapping DEGs in glomeruli and tubuli were identified and enriched analysis was performed. In addition, protein-protein interaction (PPI) network analysis as well as sub-network analysis was conducted. miRNAs of the overlapping DEGs were investigated using WebGestal. A total of 139 upregulated and 28 downregulated overlapping DEGs were selected, which were primarily associated with pathways involved in extracellular matrix (ECM)-receptor interactions and cytokine-cytokine receptor interactions. CD44, fibronectin 1, C-C motif chemokine ligand 5 and C-X-C motif chemokine receptor 4 were four primary nodes in the PPI network. miRNA (miR)-17-5p, miR-20a and miR-106a were important and nuclear receptor subfamily 4 group A member 3 (NR4A3), protein tyrosine phosphatase, receptor type O (PTPRO) and Kruppel like factor 9 (KLF9) were all predicted as target genes of the three miRNAs in the integrated miRNA-target network. Several genes were identified in DKD, which may be involved in pathways such as ECM-receptor interaction and cytokine-cytokine receptor interaction. Three miRNAs may also be used as biomarkers for therapy of DKD, including miR-17-5p, miR-20a and miR-106a, with the predicted targets of NR4A3, PTPRO and KLF9. |
format | Online Article Text |
id | pubmed-5783455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-57834552018-02-05 Microarray analysis reveals gene and microRNA signatures in diabetic kidney disease Cui, Chengji Cui, Yabin Fu, Yanyan Ma, Sichao Zhang, Shoulin Mol Med Rep Articles The current study aimed to identify therapeutic gene and microRNA (miRNA) biomarkers for diabetic kidney disease (DKD). The public expression profile GSE30122 was used. Following data preprocessing, the limma package was used to select differentially-expressed genes (DEGs) in DKD glomeruli samples and tubuli samples and they were compared with corresponding controls. Then overlapping DEGs in glomeruli and tubuli were identified and enriched analysis was performed. In addition, protein-protein interaction (PPI) network analysis as well as sub-network analysis was conducted. miRNAs of the overlapping DEGs were investigated using WebGestal. A total of 139 upregulated and 28 downregulated overlapping DEGs were selected, which were primarily associated with pathways involved in extracellular matrix (ECM)-receptor interactions and cytokine-cytokine receptor interactions. CD44, fibronectin 1, C-C motif chemokine ligand 5 and C-X-C motif chemokine receptor 4 were four primary nodes in the PPI network. miRNA (miR)-17-5p, miR-20a and miR-106a were important and nuclear receptor subfamily 4 group A member 3 (NR4A3), protein tyrosine phosphatase, receptor type O (PTPRO) and Kruppel like factor 9 (KLF9) were all predicted as target genes of the three miRNAs in the integrated miRNA-target network. Several genes were identified in DKD, which may be involved in pathways such as ECM-receptor interaction and cytokine-cytokine receptor interaction. Three miRNAs may also be used as biomarkers for therapy of DKD, including miR-17-5p, miR-20a and miR-106a, with the predicted targets of NR4A3, PTPRO and KLF9. D.A. Spandidos 2018-02 2017-11-28 /pmc/articles/PMC5783455/ /pubmed/29207157 http://dx.doi.org/10.3892/mmr.2017.8177 Text en Copyright: © Cui et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Cui, Chengji Cui, Yabin Fu, Yanyan Ma, Sichao Zhang, Shoulin Microarray analysis reveals gene and microRNA signatures in diabetic kidney disease |
title | Microarray analysis reveals gene and microRNA signatures in diabetic kidney disease |
title_full | Microarray analysis reveals gene and microRNA signatures in diabetic kidney disease |
title_fullStr | Microarray analysis reveals gene and microRNA signatures in diabetic kidney disease |
title_full_unstemmed | Microarray analysis reveals gene and microRNA signatures in diabetic kidney disease |
title_short | Microarray analysis reveals gene and microRNA signatures in diabetic kidney disease |
title_sort | microarray analysis reveals gene and microrna signatures in diabetic kidney disease |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783455/ https://www.ncbi.nlm.nih.gov/pubmed/29207157 http://dx.doi.org/10.3892/mmr.2017.8177 |
work_keys_str_mv | AT cuichengji microarrayanalysisrevealsgeneandmicrornasignaturesindiabetickidneydisease AT cuiyabin microarrayanalysisrevealsgeneandmicrornasignaturesindiabetickidneydisease AT fuyanyan microarrayanalysisrevealsgeneandmicrornasignaturesindiabetickidneydisease AT masichao microarrayanalysisrevealsgeneandmicrornasignaturesindiabetickidneydisease AT zhangshoulin microarrayanalysisrevealsgeneandmicrornasignaturesindiabetickidneydisease |