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Copyright (c) 2023 Yangwenxuan Han, Xiaoyan Liu, Jing Shang, Na Li, Chunjian Zhang, Ying Li, Jiaxin Zheng
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The undersigned hereby assign all rights, included but not limited to copyright, for this manuscript to CMB Association upon its submission for consideration to publication on Cellular and Molecular Biology. The rights assigned include, but are not limited to, the sole and exclusive rights to license, sell, subsequently assign, derive, distribute, display and reproduce this manuscript, in whole or in part, in any format, electronic or otherwise, including those in existence at the time this agreement was signed. The authors hereby warrant that they have not granted or assigned, and shall not grant or assign, the aforementioned rights to any other person, firm, organization, or other entity. All rights are automatically restored to authors if this manuscript is not accepted for publication.Bioinformatics-based analysis of core genes and pathway enrichment in early diabetic nephropathy
Corresponding Author(s) : Jiaxin Zheng
Cellular and Molecular Biology,
Vol. 69 No. 7: Issue 7
Abstract
Diabetic nephropathy (DN) is the main cause of end-stage renal disease (ESRD). Bioinformatics technology was adopted to screen and analyze the core genes of early DN to explore its pathogenesis. GSE30528, GSE96804, and GSE30122 chip data were obtained from Gene Expression Omnibus (GEO) database to screen DN and healthy controls for differentially expressed genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) for functional annotation and signaling pathway enrichment; String and Cytoscape were used for protein-protein interaction (PPI) network construction and core gene screening, NCBI-Genes to search the expression profile of core genes. 17 common genes were screened, with 6 genes up-regulated and 11 genes down-regulated. The major functional annotations of differential genes were the generation of precursor metabolites and energy, Immune response, and Phosphorylation. They were concentrated on Focal adhesion, PI3K/Akt signaling pathway, and Human papillomavirus infection pathway. The expressions of VEGFA and THBS1 were down-regulated, while the expressions of ITGB1, MMP7, and SOX9 were up-regulated. The core genes VEGFA and THBS1 were highly expressed in Thyroid and Appendix, but lowly expressed in Testis. MMP7 was highly expressed in the Gall bladder and low in the Adrenal. SOX9 was highly expressed in Thyroid and lowly expressed in the bone marrow. ITGB1 was highly expressed in Fat and low in Pancreas. Bioinformatics technology can mine chip data and present new targets for diagnosing and treating DN, but further verification is needed.
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