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Comprehensive Diagnostics of Diabetic Nephropathy by Transcriptome RNA Sequencing
Lei Lei1, Yihua Bai1, Yang Fan1
1Department of Nephrology, The Second Hospital Affiliated to Kunming Medical University, Kunming, Yunnan, People's Republic of China.
Diabetes, Metabolic Syndrome and Obesity : Targets and Therapy
|October 14, 2022
Summary
Diabetic nephropathy (DN) diagnosis is challenging. This study identifies three key genes (DDX58, SAMD9L, TLR6) as potential diagnostic biomarkers for DN, showing high accuracy in distinguishing patients from healthy individuals.
Area of Science:
- Bioinformatics
- Molecular Biology
- Genomics
Background:
- Diabetic nephropathy (DN) is a leading cause of end-stage renal disease.
- Current diagnostic approaches for DN are controversial due to lesion heterogeneity and complex mechanisms.
Purpose of the Study:
- To develop a bioinformatics-based diagnostic model for discriminating DN patients from healthy subjects.
- To identify novel diagnostic biomarkers for diabetic nephropathy.
Main Methods:
- Transcriptome sequencing of DN patients and healthy volunteers.
- Construction of a competing endogenous RNA (ceRNA) network.
- Identification of hub genes using CytoHubba and LASSO regression.
- Validation of biomarker expression via qRT-PCR and Western blot.
Main Results:
- A ceRNA network identified 10 hub genes associated with viral infection and immune responses.
- A diagnostic model comprising DDX58, SAMD9L, and TLR6 demonstrated high diagnostic power (AUC=1).
- DDX58, SAMD9L, and TLR6 were upregulated in DN patients at both transcriptomic and protein levels.
Conclusions:
- Differentially expressed hub genes, including DDX58, SAMD9L, and TLR6, show promise as novel diagnostic biomarkers for diabetic nephropathy.
- The identified biomarkers are strongly associated with viral infection pathways in DN.
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