Metabolic Profile and Metabolite Analyses in Extreme Weight Responders to Gastric Bypass Surgery

胃旁路手术后体重骤减患者的代谢特征和代谢物分析

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Abstract

BACKGROUND: Roux-en-Y gastric bypass (RYGB) surgery belongs to the most frequently performed surgical therapeutic strategies against adiposity and its comorbidities. However, outcome is limited in a substantial cohort of patients with inadequate primary weight loss or considerable weight regain. In this study, gut microbiota composition and systemically released metabolites were analyzed in a cohort of extreme weight responders after RYGB. METHODS: Patients (n = 23) were categorized based on excess weight loss (EWL) at a minimum of two years after RYGB in a good responder (EWL 93 ± 4.3%) or a bad responder group (EWL 19.5 ± 13.3%) for evaluation of differences in metabolic outcome, eating behavior and gut microbiota taxonomy and metabolic activity. RESULTS: Mean BMI was 47.2 ± 6.4 kg/m(2) in the bad vs. 26.6 ± 1.2 kg/m(2) in the good responder group (p = 0.0001). We found no difference in hunger and satiety sensation, in fasting or postprandial gut hormone release, or in gut microbiota composition between both groups. Differences in weight loss did not reflect in metabolic outcome after RYGB. While fecal and circulating metabolite analyses showed higher levels of propionate (p = 0.0001) in good and valerate (p = 0.04) in bad responders, respectively, conjugated primary and secondary bile acids were higher in good responders in the fasted (p = 0.03) and postprandial state (GCA, p = 0.02; GCDCA, p = 0.02; TCA, p = 0.01; TCDCA, p = 0.02; GDCA, p = 0.05; GUDCA, p = 0.04; TLCA, p = 0.04). CONCLUSIONS: Heterogenous weight loss response to RYGB surgery separates from patients' metabolic outcome, and is linked to unique serum metabolite signatures post intervention. These findings suggest that the level of adiposity reduction alone is insufficient to assess the metabolic success of RYGB surgery, and that longitudinal metabolite profiling may eventually help us to identify markers that could predict individual adiposity response to surgery and guide patient selection and counseling.

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