Targeted Clinical Metabolite Profiling Platform for the Stratification of Diabetic Patients

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Ahonen , L , Jäntti , S , Suvitaival , T , Theilade , S , Risz , C , Kostiainen , R , Rossing , P , Oresic , M & Hyötyläinen , T 2019 , ' Targeted Clinical Metabolite Profiling Platform for the Stratification of Diabetic Patients ' , Metabolites , vol. 9 , no. 9 , 184 . https://doi.org/10.3390/metabo9090184

Title: Targeted Clinical Metabolite Profiling Platform for the Stratification of Diabetic Patients
Author: Ahonen, Linda; Jäntti, Sirkku; Suvitaival, Tommi; Theilade, Simone; Risz, Claudia; Kostiainen, Risto; Rossing, Peter; Oresic, Matej; Hyötyläinen , Tuulia
Contributor organization: Division of Pharmaceutical Chemistry and Technology
Drug Research Program
Risto Kostiainen / Principal Investigator
University Management
Date: 2019-09
Language: eng
Number of pages: 21
Belongs to series: Metabolites
ISSN: 2218-1989
DOI: https://doi.org/10.3390/metabo9090184
URI: http://hdl.handle.net/10138/306195
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 (R-2), 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.
Subject: clinical diagnostics
diabetes
metabolomics
mass spectrometry
AMINO-ACIDS
INSULIN-RESISTANCE
RISK
ALBUMINURIA
PROGRESSION
PREDICTORS
DIAGNOSIS
DISEASE
1182 Biochemistry, cell and molecular biology
317 Pharmacy
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion


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