12.02.2024 | Original Article
Exosomal UMOD gene expression and urinary uromodulin level as early noninvasive diagnostic biomarkers for diabetic nephropathy in type 2 diabetic patients
verfasst von:
Shaimaa I. Barr, Sahar S. Bessa, Tarek M. Mohamed, Eman M. Abd El-Azeem
Erschienen in:
Diabetology International
Einloggen, um Zugang zu erhalten
Abstract
Background
Diabetic nephropathy (DN) is the leading cause of end-stage renal disease. Exosomes are promising biomarkers for disease diagnosis and uromodulin is a kidney-specific protein. So, this study was designed to investigate the change in the gene expression of urinary exosomal uromodulin mRNA and urinary uromodulin level and determine the diagnostic potential of these noninvasive biomarkers in the early stage of diabetic nephropathy in type 2 diabetic patients.
Method
This study included 100 participants; urinary exosomes were isolated using polyethylene glycol (PEG). Gene expression of exosomal uromodulin mRNA was determined by quantitative real-time polymerase chain reaction (q-RT-PCR). The urinary uromodulin levels were determined by an enzyme-linked immunosorbent assay (ELISA).
Result
In this study, the gene expression of exosomal uromodulin (UMOD) mRNA and the level of urinary uromodulin showed a significant increase in all diabetic groups with and without nephropathy compared to the control group. The exosomal UMOD mRNA showed a significant positive correlation with urinary uromodulin in all groups. Multiple logistic regression showed that urinary uromodulin was an independent determinant for DN. A diagnostic model of two indicators, exosomal UMOD mRNA and urinary uromodulin, can significantly predict DN. The area under the curve is 0.095, with a 95% confidence interval of 0.98–1, and 0.81, with a 95% confidence interval of 0.69–0.92, for the exosomal UMOD mRNA and urinary uromodulin, respectively.
Conclusion
Urinary exosomal mRNA of UMOD and urinary uromodulin levels are progressively elevated in an early stage of DN, even before the microalbuminuria stage, so they could be used as early predictors for DN.