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• W2948152052 abstract "Abstract Background Several small molecule biomarkers have been reported in the literature for prediction and diagnosis of (pre)diabetes, its co-morbidities and complications. Here, we report the development and validation of a novel, quantitative, analytical method for use in the diabetes clinic. This method enables the determination of a selected panel of 36 metabolite biomarkers from human plasma. Methods Based on a review of the literature and our own data, we selected a panel of metabolites indicative of various clinically-relevant pathogenic stages of diabetes. We combined these candidate biomarkers into a single ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method and optimized it, prioritizing simplicity of sample preparation and time needed for analysis, enabling high-throughput analysis in clinical laboratory settings. Results We validated the method in terms of limit of (a) detection (LOD), (b) limit of quantitation (LOQ), (c) linearity ( R 2 ), (d) linear range, and (e) intra- and inter-day repeatability of each metabolite. The method’s performance was demonstrated in the analysis of selected samples from a diabetes cohort study. Metabolite levels were associated with clinical measurements and kidney complications in type 1 diabetes (T1D) patients. Specifically, both amino acids and amino acid-related analytes were associated with macro-albuminuria. Additionally, specific bile acids were associated with kidney function, anti-hypertensive medication, statin medication and clinical lipid measurements. Conclusions The developed analytical method is suitable for robust determination of selected plasma metabolites in the diabetes clinic." @default.
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• W2948152052 date "2019-06-09" @default.
• W2948152052 modified "2023-10-16" @default.
• W2948152052 title "Targeted Clinical Metabolomics Platform for the Stratification of Diabetic Patients" @default.
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• W2948152052 doi "https://doi.org/10.1101/664052" @default.
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