FEBS Open Bio (Aug 2021)

Identification of differentially expressed genes in diabetic kidney disease by RNA‐Seq analysis of venous blood platelets

  • Bao Long Zhang,
  • Xiu Hong Yang,
  • Hui Min Jin,
  • Xiao Li Zhan

DOI
https://doi.org/10.1002/2211-5463.13199
Journal volume & issue
Vol. 11, no. 8
pp. 2095 – 2109

Abstract

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Diabetic kidney disease (DKD) is the leading cause of end‐stage renal disease. However, because of shared complications between DKD and chronic kidney disease (CKD), the description and characterization of DKD remain ambiguous in the clinic, hindering the diagnosis and treatment of early‐stage DKD patients. Although estimated glomerular filtration rate and albuminuria are well‐established biomarkers of DKD, early‐stage DKD is rarely accompanied by a high estimated glomerular filtration rate, and thus there is a need for new sensitive biomarkers. Transcriptome profiling of kidney tissue has been reported previously, although RNA sequencing (RNA‐Seq) analysis of the venous blood platelets in DKD patients has not yet been described. In the present study, we performed RNA‐Seq analysis of venous blood platelets from three patients with CKD, five patients with DKD and 10 healthy controls, and compared the results with a CKD‐related microarray dataset. In total, 2097 genes with differential transcript levels were identified in platelets of DKD patients and healthy controls, and 462 genes with differential transcript levels were identified in platelets of DKD patients and CKD patients. Through Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, we selected 11 pathways, from which nine potential biomarkers (IL‐1B, CD‐38, CSF1R, PPARG, NR1H3, DDO, HDC, DPYS and CAD) were identified. Furthermore, by comparing the RNA‐Seq results with the GSE30566 dataset, we found that the biomarker KCND3 was the only up‐regulated gene in DKD patients. These biomarkers may have potential application for the therapy and diagnosis of DKD, as well aid in determining the mechanisms underlying DKD.

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