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Identification of differentially expressed genes in diabetic kidney disease by RNA-Seq analysis of venous blood
Bao Long Zhang1, Xiu Hong Yang2, Hui Min Jin2
1The Institutes of Biomedical Sciences (IBS), Fudan University, Shanghai, China.
Insights
Researchers identified novel blood platelet biomarkers for diabetic kidney disease (DKD) by analyzing gene expression. These findings offer new diagnostic and therapeutic targets for early-stage DKD, improving patient outcomes.
Area of Science:
- Nephrology
- Genomics
- Biomarker Discovery
Background:
- Diabetic kidney disease (DKD) is a major cause of end-stage renal disease, but its early diagnosis is challenging due to ambiguous clinical characteristics and limitations of current biomarkers like estimated glomerular filtration rate and albuminuria.
- Existing methods for DKD characterization often fail to detect early-stage disease, necessitating the search for more sensitive diagnostic markers.
Purpose of the Study:
- To identify novel, sensitive biomarkers for early-stage diabetic kidney disease (DKD) using RNA sequencing (RNA-Seq) analysis of venous blood platelets.
- To compare gene expression profiles in platelets from DKD patients, chronic kidney disease (CKD) patients, and healthy controls.
Main Methods:
- Performed RNA-Seq analysis on venous blood platelets from 5 DKD patients, 3 CKD patients, and 10 healthy controls.
- Compared RNA-Seq data with a CKD-related microarray dataset (GSE30566).
- Utilized Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to identify potential biomarkers.
Main Results:
- Identified 2097 differentially expressed genes between DKD patients and healthy controls, and 462 between DKD and CKD patients in blood platelets.
- Discovered nine potential biomarkers (IL-1B, CD-38, CSF1R, PPARG, NR1H3, DDO, HDC, DPYS, and CAD) through pathway analysis.
- Found KCND3 as the sole upregulated gene in DKD patients when comparing RNA-Seq results with the GSE30566 dataset.
Conclusions:
- Blood platelet RNA-Seq analysis reveals significant gene expression differences in DKD patients.
- Identified several potential biomarkers (e.g., IL-1B, CD-38, KCND3) that may aid in DKD diagnosis and therapy.
- These novel biomarkers could improve early detection and understanding of DKD mechanisms.
Abstract:
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.
