Arachidonic acid and glucose uptake by freshly isolated human adipocytes

Metabolic signatures of cultured human adipocytes from metabolically healthy versus unhealthy obese individuals

Background and Aims

Among obese subjects, metabolically healthy and unhealthy obesity (MHO/MUHO) can be differentiated: the latter is characterized by whole-body insulin resistance, hepatic steatosis, and subclinical inflammation. Aim of this study was, to identify adipocyte-specific metabolic signatures and functional biomarkers for MHO versus MUHO.

Methods

10 insulin-resistant (IR) vs. 10 insulin-sensitive (IS) non-diabetic morbidly obese (BMI >40 kg/m²) Caucasians were matched for gender, age, BMI, and percentage of body fat. From subcutaneous fat biopsies, primary preadipocytes were isolated and differentiated to adipocytes in vitro. About 280 metabolites were investigated by a targeted metabolomic approach intracellularly, extracellularly, and in plasma.

Results/Interpretation

Among others, aspartate was reduced intracellularly to one third (p = 0.0039) in IR adipocytes, pointing to a relative depletion of citric acid cycle metabolites or reduced aspartate uptake in MUHO. Other amino acids, already known to correlate with diabetes and/or obesity, were identified to differ between MUHO's and MHO's adipocytes, namely glutamine, histidine, and spermidine. Most species of phosphatidylcholines (PCs) were lower in MUHO's extracellular milieu, though simultaneously elevated intracellularly, e.g., PC aa C32∶3, pointing to increased PC synthesis and/or reduced PC release. Furthermore, altered arachidonic acid (AA) metabolism was found: 15(S)-HETE (15-hydroxy-eicosatetraenoic acid; 0 vs. 120pM; p = 0.0014), AA (1.5-fold; p = 0.0055) and docosahexaenoic acid (DHA, C22∶6; 2-fold; p = 0.0033) were higher in MUHO. This emphasizes a direct contribution of adipocytes to local adipose tissue inflammation. Elevated DHA, as an inhibitor of prostaglandin synthesis, might be a hint for counter-regulatory mechanisms in MUHO.

Conclusion/Interpretation

We identified adipocyte-inherent metabolic alterations discriminating between MHO and MUHO.

Novel biomarkers for pre-diabetes identified by metabolomics

A targeted metabolomics approach was used to identify candidate biomarkers of pre-diabetes. The relevance of the identified metabolites is further corroborated with a protein-metabolite interaction network and gene expression data.

Three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine C2) were found with significantly altered levels in pre-diabetic individuals compared with normal controls.

Lower levels of glycine and LPC (18:2) were found to predict risks for pre-diabetes and type 2 diabetes (T2D).

Seven T2D-related genes (PPARG, TCF7L2, HNF1A, GCK, IGF1, IRS1 and IDE) are functionally associated with the three identified metabolites.

The unique combination of methodologies, including prospective population-based and nested case–control, as well as cross-sectional studies, was essential for the identification of the reported biomarkers.

Type 2 diabetes (T2D) can be prevented in pre-diabetic individuals with impaired glucose tolerance (IGT). Here, we have used a metabolomics approach to identify candidate biomarkers of pre-diabetes. We quantified 140 metabolites for 4297 fasting serum samples in the population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort. Our study revealed significant metabolic variation in pre-diabetic individuals that are distinct from known diabetes risk indicators, such as glycosylated hemoglobin levels, fasting glucose and insulin. We identified three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine) that had significantly altered levels in IGT individuals as compared to those with normal glucose tolerance, with P-values ranging from 2.4 × 10⁻⁴ to 2.1 × 10⁻¹³. Lower levels of glycine and LPC were found to be predictors not only for IGT but also for T2D, and were independently confirmed in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort. Using metabolite–protein network analysis, we identified seven T2D-related genes that are associated with these three IGT-specific metabolites by multiple interactions with four enzymes. The expression levels of these enzymes correlate with changes in the metabolite concentrations linked to diabetes. Our results may help developing novel strategies to prevent T2D.