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Targeted Clinical Metabolite Profiling Platform for the Stratification of Diabetic Patients

Targeted Clinical Metabolite Profiling Platform for the Stratification of Diabetic Patients

Authors :
Linda Ahonen
Sirkku Jäntti
Tommi Suvitaival
Simone Theilade
Claudia Risz
Risto Kostiainen
Peter Rossing
Matej Orešič
Tuulia Hyötyläinen
Source :
Metabolites, Vol 9, Iss 9, p 184 (2019)
Publication Year :
2019
Publisher :
MDPI AG, 2019.

Abstract

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.

Details

Language :
English
ISSN :
22181989
Volume :
9
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Metabolites
Publication Type :
Academic Journal
Accession number :
edsdoj.527d204177f6488eacb9c61a10b270eb
Document Type :
article
Full Text :
https://doi.org/10.3390/metabo9090184