Time course metabolome of Roux-en-Y gastric bypass confirms correlation between leptin, body weight and the microbiome.
Loqmane SeridiGregory C LeoG Lynis DohmWalter J PoriesJames LenhardPublished in: PloS one (2018)
Roux-en-Y gastric bypass (RYGB) is an effective way to lose weight and reverse type 2 diabetes. We profiled the metabolome of 18 obese patients (nine euglycemic and nine diabetics) that underwent RYGB surgery and seven lean subjects. Plasma samples from the obese patients were collected before the surgery and one week and three months after the surgery. We analyzed the metabolome in association to five hormones (Adiponectin, Insulin, Ghrelin, Leptin, and Resistin), four peptide hormones (GIP, Glucagon, GLP1, and PYY), and two cytokines (IL-6 and TNF). PCA showed samples cluster by surgery time and many microbially driven metabolites (indoles in particular) correlated with the three months after the surgery. Network analysis of metabolites revealed a connection between carbohydrate (mannosamine and glucosamine) and glyoxylate and confirms glyoxylate association to diabetes. Only leptin and IL-6 had a significant association with the measured metabolites. Leptin decreased immediately after RYGB (before significant weight loss), whereas IL-6 showed no consistent response to RYGB. Moreover, leptin associated with tryptophan in support of the possible role of leptin in the regulation of serotonin synthesis pathways in the gut. These results suggest a potential link between gastric leptin and microbial-derived metabolites in the context of obesity and diabetes.
Keyphrases
- roux en y gastric bypass
- weight loss
- obese patients
- bariatric surgery
- gastric bypass
- glycemic control
- type diabetes
- minimally invasive
- coronary artery bypass
- ms ms
- body weight
- surgical site infection
- insulin resistance
- cardiovascular disease
- metabolic syndrome
- randomized controlled trial
- acute coronary syndrome
- single cell
- risk assessment
- percutaneous coronary intervention
- adipose tissue
- weight gain
- skeletal muscle
- body mass index
- network analysis
- postmenopausal women
- growth hormone