Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis
Abstract Aims/Introduction The aim of the present study was to identify candidate differentially expressed genes (DEGs) and pathways using bioinformatics analysis, and to improve our understanding of the cause and potential molecular events of diabetic nephropathy. Materials and Methods Two cohort p...
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Format: | Article |
Language: | English |
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Wiley
2019-07-01
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Series: | Journal of Diabetes Investigation |
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Online Access: | https://doi.org/10.1111/jdi.12986 |
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doaj-0910392a44f6469eaf3d8d6abdbeffe7 |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiao‐dong Geng Wei‐wei Wang Zhe Feng Ran Liu Xiao‐long Cheng Wan‐jun Shen Zhe‐yi Dong Guang‐yan Cai Xiang‐mei Chen Quan Hong Di Wu |
spellingShingle |
Xiao‐dong Geng Wei‐wei Wang Zhe Feng Ran Liu Xiao‐long Cheng Wan‐jun Shen Zhe‐yi Dong Guang‐yan Cai Xiang‐mei Chen Quan Hong Di Wu Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis Journal of Diabetes Investigation Bioinformatics analysis Diabetic nephropathy Differentially expressed genes |
author_facet |
Xiao‐dong Geng Wei‐wei Wang Zhe Feng Ran Liu Xiao‐long Cheng Wan‐jun Shen Zhe‐yi Dong Guang‐yan Cai Xiang‐mei Chen Quan Hong Di Wu |
author_sort |
Xiao‐dong Geng |
title |
Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis |
title_short |
Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis |
title_full |
Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis |
title_fullStr |
Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis |
title_full_unstemmed |
Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis |
title_sort |
identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis |
publisher |
Wiley |
series |
Journal of Diabetes Investigation |
issn |
2040-1116 2040-1124 |
publishDate |
2019-07-01 |
description |
Abstract Aims/Introduction The aim of the present study was to identify candidate differentially expressed genes (DEGs) and pathways using bioinformatics analysis, and to improve our understanding of the cause and potential molecular events of diabetic nephropathy. Materials and Methods Two cohort profile datasets (GSE30528 and GSE33744) were integrated and used for deep analysis. We sorted DEGs and analyzed differential pathway enrichment. DEG‐associated ingenuity pathway analysis was carried out. The screened gene expression feature was verified in the db/db mouse kidney cortex. Then, rat mesangial cells cultured with high‐concentration glucose were used for verification. The target genes of transcriptional factor E26 transformation‐specific‐1 (ETS1) were predicted with online tools and validated using chromatin immunoprecipitation assay quantitative polymerase chain reaction. Results The two GSE datasets identified 89 shared DEGs; 51 were upregulated; and 38 were downregulated. Most of the DEGs were significantly enriched in cell adhesion, the plasma membrane, the extracellular matrix and the extracellular region. Quantitative reverse transcription polymerase chain reaction analysis validated the upregulated expression of Itgb2, Cd44, Sell, Fn1, Tgfbi and Il7r, and the downregulated expression of Igfbp2 and Cd55 in the db/db mouse kidney cortex. Chromatin immunoprecipitation assay quantitative polymerase chain reaction showed that Itgb2 was the target gene of transcription factor Ets1. ETS1 knockdown in rat mesangial cells decreased integrin subunit beta 2 expression. Conclusion We found that EST1 functioned as an important transcription factor in diabetic nephropathy development through the promotion of integrin subunit beta 2 expression. EST1 might be a drug target for diabetic nephropathy treatment. |
topic |
Bioinformatics analysis Diabetic nephropathy Differentially expressed genes |
url |
https://doi.org/10.1111/jdi.12986 |
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spelling |
doaj-0910392a44f6469eaf3d8d6abdbeffe72021-05-02T01:03:44ZengWileyJournal of Diabetes Investigation2040-11162040-11242019-07-0110497298410.1111/jdi.12986Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysisXiao‐dong Geng0Wei‐wei Wang1Zhe Feng2Ran Liu3Xiao‐long Cheng4Wan‐jun Shen5Zhe‐yi Dong6Guang‐yan Cai7Xiang‐mei Chen8Quan Hong9Di Wu10Department of Nephrology Chinese PLA General Hospital Chinese PLA Institute of Nephrology State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Chinese PLA Medical School BeijingChinaDepartment of Thoracic Surgery Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing ChinaDepartment of Nephrology Chinese PLA General Hospital Chinese PLA Institute of Nephrology State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Chinese PLA Medical School BeijingChinaDepartment of Nephrology Chinese PLA General Hospital Chinese PLA Institute of Nephrology State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Chinese PLA Medical School BeijingChinaDepartment of Nephrology Chinese PLA General Hospital Chinese PLA Institute of Nephrology State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Chinese PLA Medical School BeijingChinaDepartment of Nephrology Chinese PLA General Hospital Chinese PLA Institute of Nephrology State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Chinese PLA Medical School BeijingChinaDepartment of Nephrology Chinese PLA General Hospital Chinese PLA Institute of Nephrology State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Chinese PLA Medical School BeijingChinaDepartment of Nephrology Chinese PLA General Hospital Chinese PLA Institute of Nephrology State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Chinese PLA Medical School BeijingChinaDepartment of Nephrology Chinese PLA General Hospital Chinese PLA Institute of Nephrology State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Chinese PLA Medical School BeijingChinaDepartment of Nephrology Chinese PLA General Hospital Chinese PLA Institute of Nephrology State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Chinese PLA Medical School BeijingChinaDepartment of Nephrology Chinese PLA General Hospital Chinese PLA Institute of Nephrology State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Chinese PLA Medical School BeijingChinaAbstract Aims/Introduction The aim of the present study was to identify candidate differentially expressed genes (DEGs) and pathways using bioinformatics analysis, and to improve our understanding of the cause and potential molecular events of diabetic nephropathy. Materials and Methods Two cohort profile datasets (GSE30528 and GSE33744) were integrated and used for deep analysis. We sorted DEGs and analyzed differential pathway enrichment. DEG‐associated ingenuity pathway analysis was carried out. The screened gene expression feature was verified in the db/db mouse kidney cortex. Then, rat mesangial cells cultured with high‐concentration glucose were used for verification. The target genes of transcriptional factor E26 transformation‐specific‐1 (ETS1) were predicted with online tools and validated using chromatin immunoprecipitation assay quantitative polymerase chain reaction. Results The two GSE datasets identified 89 shared DEGs; 51 were upregulated; and 38 were downregulated. Most of the DEGs were significantly enriched in cell adhesion, the plasma membrane, the extracellular matrix and the extracellular region. Quantitative reverse transcription polymerase chain reaction analysis validated the upregulated expression of Itgb2, Cd44, Sell, Fn1, Tgfbi and Il7r, and the downregulated expression of Igfbp2 and Cd55 in the db/db mouse kidney cortex. Chromatin immunoprecipitation assay quantitative polymerase chain reaction showed that Itgb2 was the target gene of transcription factor Ets1. ETS1 knockdown in rat mesangial cells decreased integrin subunit beta 2 expression. Conclusion We found that EST1 functioned as an important transcription factor in diabetic nephropathy development through the promotion of integrin subunit beta 2 expression. EST1 might be a drug target for diabetic nephropathy treatment.https://doi.org/10.1111/jdi.12986Bioinformatics analysisDiabetic nephropathyDifferentially expressed genes |