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

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

Effects of brown seaweeds on postprandial glucose, insulin and appetite in humans – A randomized, 3-way, blinded, cross-over meal study

Seaweed including brown seaweeds with rich bioactive components may be efficacious for a glycaemic management strategy and appetite control. We investigated the effects of two brown edible seaweeds, Laminaria digitata (LD) and Undaria pinnatifida (UP), on postprandial glucose metabolism and appetite following a starch load in a human meal study. Methods: Twenty healthy subjects were enrolled in a randomized, 3-way, blinded cross-over trial. The study was registered under ClinicalTrials.gov Identifier no. NCT00123456. At each test day, the subjects received one of three meals comprising 30 g of starch with 5 g of LD or UP or an energy-adjusted control meal containing pea protein. Fasting and postprandial blood glucose, insulin, C-peptide and glucagonlike peptide-1 (GLP-1) concentrations were measured. Subjective appetite sensations were scored using visual analogue scales (VAS). Results: Linear mixed model (LMM) analysis showed a lower blood glucose, insulin and C-peptide response following the intake of LD and UP, after correction for body weight. Participants weighing 63 kg had a reduced glucose response compared to control meal between 40 and 90 min both following LD and UP meals. Furthermore, LMM analysis for C-peptide showed a significantly lower response after intake of LD. Compared to the control meal, GLP-1 response was higher after the LD meal, both before and after the body weight adjustment. The VAS scores showed a decreased appetite sensation after intake of the seaweeds. Ad-libitum food intake was not different three hours after the seaweed meals compared to control. Conclusions: Concomitant ingestion of brown seaweeds may help improving postprandial glycaemic and appetite control in healthy and normal weight adults, depending on the dose per body weight