Potential Plasma Metabolite Biomarkers of Diabetic Nephropathy: Untargeted Metabolomics Study

• Published in: Journal of personalized medicine Vol. 12; no. 11; p. 1889
• Main Authors: Trifonova, Oxana P., Maslov, Dmitry L., Balashova, Elena E., Lichtenberg, Steven, Lokhov, Petr G.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 11.11.2022; MDPI
• Subjects: Bioinformatics; Biomarkers; blood metabolite; Chromatography; Creatinine; Data analysis; Diabetes; Diabetes mellitus (insulin dependent); diabetic nephropathy; Diagnosis; diagnostics; Disease; Drug therapy; Endocrinology; Glomerular filtration rate; Ions; Kidneys; Mann-Whitney U test; Mass spectrometry; Mass spectroscopy; Medical research; Metabolites; Metabolomics; Monosaccharides; Nephropathy; NMR; Nuclear magnetic resonance; Organic acids; Plasma; Precision medicine; Renal failure; Scientific imaging; United States > US; Germany
• ISSN: 2075-4426; 2075-4426
• DOI: 10.3390/jpm12111889

Diabetic nephropathy (DN) is one of the specific complications of diabetes mellitus and one of the leading kidney-related disorders, often requiring renal replacement therapy. Currently, the tests commonly used for the diagnosis of DN, albuminuria (AU) and glomerular filtration rate (GFR), have limited sensitivity and specificity and can usually be noted when typical morphological changes in the kidney have already been manifested. That is why the extreme urgency of the problem of early diagnosis of this disease exists. The untargeted metabolomics analysis of blood plasma samples from 80 patients with type 1 diabetes and early and late stages of DN according to GFR was performed using direct injection mass spectrometry and bioinformatics analysis for diagnosing signatures construction. Among the dysregulated metabolites, combinations of 15 compounds, including amino acids and derivatives, monosaccharides, organic acids, and uremic toxins were selected for signatures for DN diagnosis. The selected metabolite combinations have shown high performance for diagnosing of DN, especially for the late stage (up to 99%). Despite the metabolite signature determined for the early stage of DN being characterized by a diagnostic performance of 81%, these metabolites as potential biomarkers might be useful in the evaluation of treatment of the disease, especially at early stages that may reduce the risk of kidney failure development.