Changes in Circulating Metabolites during Weight Loss and Weight Loss Maintenance in Relation to Cardiometabolic Risk.

(1) Background: There is a substantial lack of knowledge of the biochemical mechanisms by which weight loss and weight regain exert their beneficial and adverse effects, respectively, on cardiometabolic outcomes. We examined associations between changes in circulating metabolites and changes in cardiometabolic risk factors during diet-induced weight loss and weight loss maintenance. (2) Methods: This prospective analysis of data from the Satiety Innovation (SATIN) study involved adults living with overweight and obesity (mean age=47.5). One hundred sixty-two subjects achieving ≥8% weight loss during an initial 8-week low-calorie diet (LCD) were included in a 12-week weight loss maintenance period. Circulating metabolites (m=123) were profiled using a targeted multiplatform approach. Data were analyzed using multivariate linear regression models. (3) Results: Decreases in the concentrations of several phosphatidylcholines (PCs), sphingomyelins (SMs), and valine were consistently associated with decreases in total (TChol) and low-density lipoprotein cholesterol (LDL-C) levels during the LCD. Increases in PCs and SMs were significantly associated with increases in TChol and LDL-C during the weight loss maintenance period. Decreases and increases in PCs during LCD and maintenance period, respectively, were associated with decreases in the levels of triglycerides. (4) Conclusions: The results of this study suggest that decreases in circulating PCs and SMs during weight loss and the subsequent weight loss maintenance period may decrease the cardiovascular risk through impacting TChol and LDL-C.

Circulating Metabolites Associated with Body Fat and Lean Mass in Adults with Overweight/Obesity.

The interplay between fat mass and lean mass within human metabolism is not completely understood. We aimed to identify specific circulating metabolomic profiles associated with these body composition compartments. Cross-sectional analyses were conducted over 236 adults with overweight/obesity from the Satiety Innovation (SATIN) study. Body composition was assessed by dual-energy X-ray absorptiometry. A targeted multiplatform metabolite profiling approach was applied. Associations between 168 circulating metabolites and the body composition measures were assessed using elastic net regression analyses. The accuracy of the multimetabolite weighted models was evaluated using a 10-fold cross-validation approach and the Pearson's correlation coefficients between metabolomic profiles and body compartments were estimated. Two different profiles including 86 and 65 metabolites were selected for % body fat and lean mass. These metabolites mainly consisted of lipids (sphingomyelins, phosphatidylcholines, lysophosphatidylcholines), acylcarnitines, and amino acids. Several metabolites overlapped between these body composition measures but none of them towards the same direction. The Pearson correlation coefficients between the metabolomic profiles and % body fat or lean mass were 0.80 and 0.79, respectively. Our findings suggest alterations in lipid metabolism, fatty acid oxidation, and protein degradation with increased adiposity and decreased lean body mass. These findings could help us to better understand the interplay between body composition compartments with human metabolic processes.

Circulating Metabolites Associated with Postprandial Satiety in Overweight/Obese Participants: The SATIN Study.

Scope: To identify a metabolomic profile related to postprandial satiety sensations involved in appetite control would help for a better understanding of the regulation of food intake. Methods and Results: A cross-sectional analysis of plasma metabolites was conducted over 151 overweight/obese adults from the "Satiety Innovation"-SATIN study, a randomized clinical trial of a 12-week weight-loss maintenance period. Postprandial satiety sensations (3 h-iAUC) were assessed by visual analogue scale (VAS) at the beginning and at the end of the study. Fasting plasma metabolites were profiled using a targeted multiplatform metabolomics approach before each appetite test meal. Associations between 124 metabolites and iAUC-satiety were assessed using elastic net linear regression analyses. The accuracy of the multimetabolite weighted models for iAUC-VAS was evaluated using a 10-fold cross-validation (CV) approach and the Pearson's correlation coefficients were estimated. Five and three metabolites were selected in the first and the second assessments, respectively. Circulating glycine and linoleic acid concentrations were consistently and positively associated with higher iAUC-satiety in both visits. Sucrose and sphingomyelins (C32:2, C38:1) were negatively associated with iAUC-satiety in the first visit. The Pearson correlations coefficients between the metabolomic profiles and iAUC-satiety in the first and the second appetite assessments were 0.37 and 0.27, respectively. Conclusion: Higher glycine and linoleic acid were moderately but consistently associated with higher postprandial satiety in two different appetite assessments in overweight and obese subjects.

Plasma metabolites associated with homeostatic model assessment of insulin resistance: metabolite-model design and external validation.

Different plasma metabolites have been related to insulin resistance (IR). However, there is a lack of metabolite models predicting IR with external validation. The aim of this study is to identify a multi-metabolite model associated to the homeostatic model assessment (HOMA)-IR values. We performed a cross-sectional metabolomics analysis of samples collected from overweight and obese subjects from two independent studies. The training step was performed in 236 subjects from the SATIN study and validated in 102 subjects from the GLYNDIET study. Plasma metabolomics profile was analyzed using three different approaches: GC/quadrupole-TOF, LC/quadrupole-TOF, and nuclear magnetic resonance (NMR). Associations between metabolites and HOMA-IR were assessed using elastic net regression analysis with a leave-one-out cross validation (CV) and 100 CV runs. HOMA-IR was analyzed both as linear and categorical (median or lower versus higher than the median). Receiver operating characteristic curves were constructed based on metabolites' weighted models. A set of 30 metabolites discriminating extremes of HOMA-IR were consistently selected. These metabolites comprised some amino acids, lipid species and different organic acids. The area under the curve (AUC) for the discrimination between HOMA-IR extreme categories was 0.82 (95% CI: 0.74-0.90), based on the multi-metabolite model weighted with the regression coefficients of metabolites in the validation dataset. We identified a set of metabolites discriminating between extremes of HOMA-IR and able to predict HOMA-IR with high accuracy.

Roux-En-Y Gastric Bypass and Sleeve Gastrectomy Does Not Affect Food Preferences When Assessed by an Ad libitum Buffet Meal.

BACKGROUND: Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) lead to a reduction in energy intake. It is uncertain whether this reduction is simply due to eating smaller portions or if surgery changes food preferences towards less energy-dense food. Previous results rely on verbal reports, which may be prone to recall bias and underestimation of especially unhealthy foods. METHODS: Using an ad libitum buffet meal targeting direct behavior, we investigated if RYGB and SG surgery leads to changes in food preferences. In addition, we assessed food preferences by a picture display test to explore differences between a method relying on verbal report and a method assessing direct behavior. RESULTS: Forty-one subjects (BMI 45.0 ± 6.8 kg/m2) completed a visit pre- and 6 months post-RYGB (n = 31) and SG (n = 10). Mean BMI decreased with 11.7 ± 0.6 kg/m2 and total energy intake at the buffet meal with 54% (4491 ± 208 kJ vs. 2083 ± 208 kJ, P < 0.001), respectively. However, relative energy intake from the following food categories: high-fat, low-fat, sweet, savory, high-fat-savory, high-fat-sweet, low-fat-savory, and low-fat-sweet, as well as energy density did not change following surgery (all P ≥ 0.18). In contrast, the picture display test showed that food from the low-fat-savory group was chosen more often post-surgery (34 ± 8% vs. 65 ± 9%, P = 0.02). CONCLUSION: The reduction in energy intake after RYGB and SG surgery and the subsequent weight loss seems to be primarily related to a reduction in portion sizes and not by changes in food preferences towards less energy-dense foods. These results underline the necessity of investigating eating behavior by targeting direct behavior.