Zhang Bao Long, Yang Xiu Hong, Jin Hui Min, Zhan Xiao Li
The Institutes of Biomedical Sciences (IBS), Fudan University, Shanghai, China.
Division of Nephrology, Pudong Medical Center, Shanghai Pudong Hospital, Fudan University, Shanghai, China.
FEBS Open Bio. 2021 Aug;11(8):2095-2109. doi: 10.1002/2211-5463.13199. Epub 2021 Jul 2.
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.
糖尿病肾病(DKD)是终末期肾病的主要病因。然而,由于DKD与慢性肾脏病(CKD)存在共同的并发症,DKD在临床上的描述和特征仍不明确,这阻碍了早期DKD患者的诊断和治疗。尽管估算肾小球滤过率和蛋白尿是DKD公认的生物标志物,但早期DKD很少伴有高估算肾小球滤过率,因此需要新的敏感生物标志物。此前已有关于肾组织转录组分析的报道,不过尚未有对DKD患者静脉血血小板进行RNA测序(RNA-Seq)分析的描述。在本研究中,我们对3例CKD患者、5例DKD患者和10名健康对照者的静脉血血小板进行了RNA-Seq分析,并将结果与一个CKD相关的微阵列数据集进行了比较。总共在DKD患者和健康对照者的血小板中鉴定出2097个转录水平有差异的基因,在DKD患者和CKD患者的血小板中鉴定出462个转录水平有差异的基因。通过京都基因与基因组百科全书(KEGG)通路富集分析,我们选择了11条通路,从中鉴定出9种潜在生物标志物(IL-1B、CD-38、CSF1R、PPARG、NR1H3、DDO、HDC、DPYS和CAD)。此外,通过将RNA-Seq结果与GSE30566数据集进行比较,我们发现生物标志物KCND3是DKD患者中唯一上调的基因。这些生物标志物可能在DKD的治疗和诊断中具有潜在应用,也有助于确定DKD的潜在机制。