Bariatric surgery is associated with weight loss attributed to reduced caloric intake, mechanical changes, and alterations in gut hormones. However, some studies have suggested a heightened incidence of colorectal cancer (CRC) has been associated with bariatric surgery, emphasizing the importance of identifying mechanisms of risk. The objective of this study was to determine if bariatric surgery is associated with decreases in fecal short-chain fatty acids (SCFA), a group of bacterial metabolites of fiber. Fecal samples (n = 22) were collected pre- (~6 weeks) and post-bariatric surgery (~4 months) in patients undergoing Roux-en-Y gastric bypass and sleeve gastrectomy. SCFA levels were quantified using liquid chromatography/mass spectrometry. Dietary intake was quantified using 24-h dietary recalls. Using an aggregate variable, straight SCFAs significantly decreased by 27% from pre- to post-surgery, specifically acetate, propionate, butyrate, and valerate. Pre-surgery weight was inversely associated with butyrate, with no association remaining post-surgery. Multiple food groups were positively (sugars, milk, and red and orange vegetables) and inversely (animal protein) associated with SCFA levels. Our results suggest a potential mechanism linking dietary intake and SCFA levels with CRC risk post-bariatric surgery with implications for interventions to increase SCFA levels.

Introduction: Test performance screening measures for dysglycemia have not been evaluated prospectively in youth. This study evaluated the prospective test performance of random glucose (RG), 1-hour nonfasting glucose challenge test (1-h GCT), Hemoglobin A1c (HbA1c), fructosamine (FA), and 1,5-Anhydroglucitol (1,5-AG) for identifying dysglycemia. Methods: Youth ages 8-17 years with overweight or obesity (body mass index, BMI, ≥85th percentile) without known diabetes completed nonfasting tests at baseline (n=176) and returned an average of 1.1 years later for two formal fasting 2-hour oral glucose tolerance tests. Outcomes included glucose-defined dysglycemia (fasting plasma glucose ≥100 mg/dL or 2-hour plasma glucose ≥140 mg/dL) or elevated HbA1c (≥5.7%). Longitudinal test performance was evaluated using receiver operating characteristic (ROC) curves and calculation of area under the curve (AUC). Results: Glucose-defined dysglycemia, elevated HbA1c, and either dysglycemia or elevated HbA1c were present in 15 (8.5%), 11 (6.3%), and 23 (13.1%) participants at baseline, and 16 (9.1%), 18 (10.3%), and 28 (15.9%) participants at follow-up. For prediction of glucose-defined dysglycemia at follow-up, RG, 1-h GCT, and HbA1c had similar performance (0.68 (95% CI 0.55-0.80), 0.76 (95% CI 0.64-0.89), and 0.70 (95% CI 0.56-0.84)), while FA and 1,5-AG performed poorly. For prediction of HbA1c at follow-up, baseline HbA1c had strong performance (AUC 0.93 (95% CI 0.88-0.98)), RG had moderate performance (AUC 0.67 (0.54-0.79)), while 1-h GCT, FA, and 1,5-AG performed poorly. Conclusion: HbA1c and nonfasting glucose tests had reasonable longitudinal discrimination identifying adolescents at risk for dysglycemia, but performance depended on outcome definition.

Summary Background Alterations in body composition (BC) during adolescence relates to future metabolic risk, yet underlying mechanisms remain unclear. Objectives To assess the association between the metabolome with changes in adiposity (body mass index [BMI], waist circumference [WC], triceps skinfold [TS], fat percentage [BF%]) and muscle mass (MM). Methods In Mexican adolescents (n = 352), untargeted serum metabolomics was profiled at baseline. and data were reduced by pairing hierarchical clustering with confirmatory factor analysis, yielding 30 clusters with 51 singleton metabolites. At the baseline and follow‐up visits (1.6–3.5 years apart), anthropometry was collected to identify associations between baseline metabolite clusters and change in BC (∆) using seemingly unrelated and linear regression. Results Between visits, MM increased in boys and adiposity increased in girls. Sex differences were observed between metabolite clusters and changes in BC. In boys, aromatic amino acids (AAA), branched chain amino acids (BCAA) and fatty acid oxidation metabolites were associated with increases in ∆BMI, and ∆BF%. Phospholipids were associated with decreases in ∆TS and ∆MM. Negative associations were observed for ∆MM in boys with a cluster including AAA and BCAA, whereas positive associations were found for a cluster containing tryptophan metabolites. Few associations were observed between metabolites and BC change in girls, with one cluster comprising methionine, proline and lipids associated with decreases in ∆BMI, ∆WC and ∆MM. Conclusion Sex‐specific associations between the metabolome and change in BC were observed, highlighting metabolic pathways underlying adolescent physical growth.

Untargeted liquid chromatography−mass spectrometry metabolomics studies are typically performed under roughly identical experimental settings. Measurements acquired with different LC-MS protocols or following extended time intervals harbor significant variation in retention times and spectral abundances due to altered chromatographic, spectrometric, and other factors, raising many data analysis challenges. We developed a computational workflow for merging and harmonizing metabolomics data acquired under disparate LC-MS conditions. Plasma metabolite profiles were collected from two sets of maternal subjects three years apart using distinct instruments and LC-MS procedures. Metabolomics features were aligned using metabCombiner to generate lists of compounds detected across all experimental batches. We applied data set-specific normalization methods to remove interbatch and interexperimental variation in spectral intensities, enabling statistical analysis on the assembled data matrix. Bioinformatics analyses revealed large-scale metabolic changes in maternal plasma between the first and third trimesters of pregnancy and between maternal plasma and umbilical cord blood. We observed increases in steroid hormones and free fatty acids from the first trimester to term of gestation, along with decreases in amino acids coupled to increased levels in cord blood. This work demonstrates the viability of integrating nonidentically acquired LC-MS metabolomics data and its utility in unconventional metabolomics study designs.