TY - JOUR

T1 - Correlation of plasma metabolites with glucose and lipid fluxes in human insulin resistance

AU - Hartstra, Annick V

AU - de Groot, Pieter F

AU - Mendes Bastos, Diogo

AU - Levin, Evgeni

AU - Serlie, Mireille J

AU - Soeters, Maarten R

AU - Pekmez, Ceyda Tugba

AU - Dragsted, Lars Ove

AU - Ackermans, Mariette T

AU - Groen, Albert K

AU - Nieuwdorp, Max

N1 - CURIS 2020 NEXS 084

PY - 2020

Y1 - 2020

N2 - Objective: Insulin resistance develops prior to the onset of overt type 2 diabetes, making its early detection vital. Direct accurate evaluation is currently only possible with complex examinations like the stable isotope-based hyperinsulinemic euglycemic clamp (HIEC). Metabolomic profiling enables the detection of thousands of plasma metabolites, providing a tool to identify novel biomarkers in human obesity. Design: Liquid chromatography mass spectrometry–based untargeted plasma metabolomics was applied in 60 participants with obesity with a large range of peripheral insulin sensitivity as determined via a two-step HIEC with stable isotopes [6,6-2H2]glucose and [1,1,2,3,3-2H5]glycerol. This additionally enabled measuring insulin-regulated lipolysis, which combined with metabolomics, to the knowledge of this research group, has not been reported on before. Results: Several plasma metabolites were identified that significantly correlated with glucose and lipid fluxes, led by plasma (gamma-glutamyl)citrulline, followed by betaine, beta-cryptoxanthin, fructosyllysine, octanylcarnitine, sphingomyelin (d18:0/18:0, d19:0/17:0) and thyroxine. Subsequent machine learning analysis showed that a panel of these metabolites derived from a number of metabolic pathways may be used to predict insulin resistance, dominated by non-essential amino acid citrulline and its metabolite gamma-glutamylcitrulline. Conclusion: This approach revealed a number of plasma metabolites that correlated reasonably well with glycemic and lipolytic flux parameters, measured using gold standard techniques. These metabolites may be used to predict the rate of glucose disposal in humans with obesity to a similar extend as HOMA, thus providing potential novel biomarkers for insulin resistance.

AB - Objective: Insulin resistance develops prior to the onset of overt type 2 diabetes, making its early detection vital. Direct accurate evaluation is currently only possible with complex examinations like the stable isotope-based hyperinsulinemic euglycemic clamp (HIEC). Metabolomic profiling enables the detection of thousands of plasma metabolites, providing a tool to identify novel biomarkers in human obesity. Design: Liquid chromatography mass spectrometry–based untargeted plasma metabolomics was applied in 60 participants with obesity with a large range of peripheral insulin sensitivity as determined via a two-step HIEC with stable isotopes [6,6-2H2]glucose and [1,1,2,3,3-2H5]glycerol. This additionally enabled measuring insulin-regulated lipolysis, which combined with metabolomics, to the knowledge of this research group, has not been reported on before. Results: Several plasma metabolites were identified that significantly correlated with glucose and lipid fluxes, led by plasma (gamma-glutamyl)citrulline, followed by betaine, beta-cryptoxanthin, fructosyllysine, octanylcarnitine, sphingomyelin (d18:0/18:0, d19:0/17:0) and thyroxine. Subsequent machine learning analysis showed that a panel of these metabolites derived from a number of metabolic pathways may be used to predict insulin resistance, dominated by non-essential amino acid citrulline and its metabolite gamma-glutamylcitrulline. Conclusion: This approach revealed a number of plasma metabolites that correlated reasonably well with glycemic and lipolytic flux parameters, measured using gold standard techniques. These metabolites may be used to predict the rate of glucose disposal in humans with obesity to a similar extend as HOMA, thus providing potential novel biomarkers for insulin resistance.

KW - Citrulline

KW - Human insulin resistance

KW - Plasma metabolites

KW - Stable isotope hyperinsulinemic clamp

UR - http://www.scopus.com/inward/record.url?scp=85079197932&partnerID=8YFLogxK

U2 - 10.1002/osp4.402

DO - 10.1002/osp4.402

M3 - Journal article

C2 - 32523723

AN - SCOPUS:85079197932

VL - 6

SP - 340

EP - 349

JO - Obesity Science & Practice

JF - Obesity Science & Practice

SN - 2055-2238

IS - 3

ER -