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Open AccessArticle

Targeted Clinical Metabolite Profiling Platform for the Stratification of Diabetic Patients

1
Steno Diabetes Center Copenhagen, 2820 Gentofte, Denmark
2
Drug Research Program, Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, 00014 Helsinki, Finland
3
Department of Clinical Medicine, University of Copenhagen, 1165 Copenhagen, Denmark
4
Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, 20520 Turku, Finland
5
School of Medical Sciences, Örebro University, 702 81 Örebro, Sweden
6
Department of Chemistry, Örebro University, 702 81 Örebro, Sweden
*
Author to whom correspondence should be addressed.
Current affiliation: Biosyntia ApS, 2100 Copenhagen, Denmark.
Metabolites 2019, 9(9), 184; https://doi.org/10.3390/metabo9090184
Received: 1 August 2019 / Revised: 30 August 2019 / Accepted: 11 September 2019 / Published: 14 September 2019
(This article belongs to the Special Issue Metabolomics 2019)
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 method for the determination of a selected panel of 34 metabolite biomarkers from human plasma. 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. We validated the method in terms of limits of detection (LOD) and quantitation (LOQ), linearity (R2), and 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, as well as specific bile acids, were associated with macro-albuminuria. Additionally, specific bile acids were associated with glycemic control, anti-hypertensive medication, statin medication, and clinical lipid measurements. The developed analytical method is suitable for robust determination of selected plasma metabolites in the diabetes clinic. View Full-Text
Keywords: clinical diagnostics; diabetes; metabolomics; mass spectrometry clinical diagnostics; diabetes; metabolomics; mass spectrometry
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MDPI and ACS Style

Ahonen, L.; Jäntti, S.; Suvitaival, T.; Theilade, S.; Risz, C.; Kostiainen, R.; Rossing, P.; Orešič, M.; Hyötyläinen, T. Targeted Clinical Metabolite Profiling Platform for the Stratification of Diabetic Patients. Metabolites 2019, 9, 184.

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