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Bioinformatic analysis reveals novel hub genes and pathways associated with hypertensive nephropathy
Author(s) -
Chen Xiaolei,
Cao Yiling,
Wang Zheng,
Zhang Dongmei,
Tang Wanxin
Publication year - 2019
Publication title -
nephrology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 61
eISSN - 1440-1797
pISSN - 1320-5358
DOI - 10.1111/nep.13508
Subject(s) - gene , microarray analysis techniques , medicine , microarray , computational biology , bioinformatics , genetics , gene expression , biology
ABSTRACT Aim Hypertensive nephropathy (HTN) is one of the leading causes of end‐stage renal disease and is closely associated with inflammation and tubule‐interstitial fibrosis. The molecular mechanism underlying HTN remains unclear. This study used bioinformatic analysis to identify the novel gene targets for HTN. Methods We downloaded the microarray data of GSE99325 and GSE32591 from Gene Expression Omnibus. The dataset comprised 20 HTN and 15 normal samples. The differentially expressed genes (DEG) were identified, and then gene ontology (GO) enrichment was performed, and a GO tree was constructed by using clusterProfiler and ClueGO. In addition, a protein–protein interaction network was established using the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape. The novel hub genes were validated in in vitro experiments. Results A total of 267 genes (117 up‐regulated and 150 down‐regulated genes) were identified as DEG. GO analysis and the GO tree indicated that the DEG were mainly associated with steroid hormone response and the extracellular matrix. Based on the protein–protein interaction network, we screened out several novel hub genes. Considering the findings and the literature review, we focused on and validated the dual specificity phosphatase 1, tissue inhibitor of matrix metalloproteinases 1, fos proto‐oncogene and jun proto‐oncogenes, which may play significant roles in the pathogenesis of HTN. These findings were consistent with the bioinformatic results for the in vitro validation. Conclusion This study identified for the first time novel hub genes with microarray data in HTN by using bioinformatic analysis and provided novel evidence and clues for future works.