scholarly journals Targeted Clinical Metabolomics Platform for the Stratification of Diabetic Patients

2019 ◽  
Author(s):  
Linda Ahonen ◽  
Sirkku Jäntti ◽  
Tommi Suvitaival ◽  
Simone Theilade ◽  
Claudia Risz ◽  
...  
Keyword(s):  
Analytical Method ◽  
High Performance ◽  
Clinical Laboratory ◽  
Plasma Metabolites ◽  
Diabetic Patients ◽  
Diabetes Clinic ◽  
High Throughput Analysis ◽  
Limit Of Quantitation ◽  
Liquid Chromatography Tandem Mass

AbstractBackgroundSeveral 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.MethodsBased 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.ResultsWe validated the method in terms of limit of (a) detection (LOD), (b) limit of quantitation (LOQ), (c) linearity (R2), (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.ConclusionsThe developed analytical method is suitable for robust determination of selected plasma metabolites in the diabetes clinic.

scholarly journals Targeted Clinical Metabolite Profiling Platform for the Stratification of Diabetic Patients

Metabolites ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 184 ◽  
Author(s):  
Ahonen ◽  
Jäntti ◽  
Suvitaival ◽  
Theilade ◽  
Risz ◽  
...  
Keyword(s):  
Bile Acids ◽  
High Performance ◽  
Clinical Laboratory ◽  
Plasma Metabolites ◽  
Diabetic Patients ◽  
Diabetes Clinic ◽  
High Throughput Analysis ◽  
Liquid Chromatography Tandem Mass ◽  
Clinical Measurements

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.

scholarly journals Determination of Levamisole and Mebendazole and Its Two Metabolite Residues in Three Poultry Species by HPLC-MS/MS

Foods ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2841
Author(s):  
Pengfei Gao ◽  
Peiyang Zhang ◽  
Yawen Guo ◽  
Zhaoyuan He ◽  
Yuhao Dong ◽  
...  
Keyword(s):  
High Performance ◽  
Solid Phase ◽  
Gradient Elution ◽  
Column Temperature ◽  
Mobile Phases ◽  
Relative Standard ◽  
Limit Of Quantitation ◽  
Liquid Chromatography Tandem Mass ◽  
Peak Areas

A high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method was developed to simultaneously analyze levamisole (LMS) and mebendazole (MBZ) and its two metabolites, 5-hydroxymebendazole (HMBZ) and 2-amino-5-benzoylbenzimidazole (AMBZ), in poultry muscle (chicken, duck and goose). In the sample preparation process, basic ethyl acetate was used as the extraction agent, and the extracted samples were back-extracted with hydrochloric acid, purified by Oasis MCX solid-phase extraction (SPE) cartridges, and reconstituted in the initial mobile phase after being blown dry with nitrogen. Chromatographic separation was performed on an Xbridge C18 column (4.6 mm × 150 mm, 5 μm) with 0.1% formic acid in water and acetonitrile as the mobile phases, and gradient elution was performed at a flow rate of 0.6 mL/min and a column temperature of 35 °C. In blank poultry muscle samples, the spiked concentrations of LMS, MBZ, HMBZ, and AMBZ were within the range of the limit of quantitation (LOQ) to 25 μg/kg. The peak areas of the four target drugs had a good linear relationship with the concentration, and the determination coefficient (R2) values were higher than 0.9990. The average recoveries of LMS, MBZ, HMBZ, and AMBZ were 86.77–96.94%; the intraday relative standard deviations (RSDs) were 1.75–4.99% at LOQ, 0.5 maximum residue limit (MRL), 1.0 MRL, and 2.0 MRL; the interday RSDs were 2.54–5.52%; and the LODs and LOQs were 0.04–0.30 μg/kg and 0.12–0.80 μg/kg, respectively.

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