Identification of key biomarkers in diabetic nephropathy via bioinformatic analysis. Issue 5 (28th November 2018)

• Record Type: Journal Article
• Authors: Zeng, Mengru; Liu, Jialu; Yang, Wenxia; Zhang, Shumin; Liu, Fuyou; Dong, Zheng; Peng, Youming; Sun, Lin; Xiao, Li
• Is Part Of: Journal of cellular biochemistry. Volume 120:Issue 5(2019)
• Page Start: 8676
• Page End: 8688
• Publication Date: 2018-11-28
• Subjects: biomarkers -- computational biology -- diabetic nephropathies -- diagnosis -- therapeutics; Cytochemistry -- Periodicals; 572
• DOI: 10.1002/jcb.28155
• Languages: English
• ISSNs: 0730-2312

Abstract

Abstract: Diabetic nephropathy (DN) is a major cause of end‐stage renal disease. Although intense efforts have been made to elucidate the pathogenesis, the molecular mechanisms of DN remain to be clarified. To identify the candidate genes in the progression of DN, microarray datasets GSE30122, GSE30528, and GSE47183 were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified, and function enrichment analyses were performed. The protein‐protein interaction network was constructed and the module analysis was performed using the Search Tool for the Retrieval of Interacting Genes and Cytoscape. A total of 61 DEGs were identified. The enriched functions and pathways of the DEGs included glomerulus development, extracellular exosome, collagen binding, and the PI3K‐Akt signaling pathway. Fifteen hub genes were identified and biological process analysis revealed that these genes were mainly enriched in acute inflammatory response, inflammatory response, and blood vessel development. Correlation analysis between unexplored hub genes and clinical features of DN suggested that COL6A3, MS4A6A, PLCE1, TNNC1, TNNI1, TNN2, and VSIG4 may involve in the progression of DN. In conclusion, DEGs and hub genes identified in this study may deepen our understanding of molecular mechanisms underlying the progression of DN, and provide candidate targets for diagnosis and treatment of DN. Abstract : To identify candidate genes in the progression of diabetic nephropathy, microarray datasets GSE30122, GSE30528, and GSE47183 were downloaded from the Gene Expression Omnibus database. The differentially expressed genes were identified, and function enrichment analyses were performed.