Identification of key biomarkers in diabetic nephropathy via bioinformatic analysis

Mengru Zeng, Jialu Liu, Wenxia Yang, Shumin Zhang, Fuyou Liu, Zheng Dong, Youming Peng, Lin Sun, Li Xiao

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)8676-8688
Number of pages13
JournalJournal of cellular biochemistry
Issue number5
StatePublished - May 2019


  • biomarkers
  • computational biology
  • diabetic nephropathies
  • diagnosis
  • therapeutics

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Cell Biology


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