Gut microbiota composition is influenced by environmental factors and has been shown to impact body metabolism. Objective: To assess the gut microbiota profile before and after Roux-en-Y gastric bypass (RYGB) and the correlation with food intake and postoperative type 2 diabetes remission (T2Dr). Design: Gut microbiota profile from obese diabetic women was evaluated before (n = 25) and 3 (n = 20) and 12 months (n = 14) after RYGB, using MiSeq Illumina-based V4 bacterial 16S rRNA gene profiling. Data on food intake (7-day record) and T2Dr (American Diabetes Association (ADA) criteria) were recorded. Results: Preoperatively, the abundance of five bacteria genera differed between patients with (57%) and without T2Dr (p < 0.050). Preoperative gut bacteria genus signature was able to predict the T2Dr status with 0.94 accuracy ROC curve (receiver operating characteristic curve). Postoperatively (vs. preoperative), the relative abundance of some gut bacteria genera changed, the gut microbial richness increased, and the Firmicutes to Bacteroidetes ratio (rFB) decreased (p < 0.05) regardless of T2Dr. Richness levels was correlated with dietary profile pre and postoperatively, mainly displaying positive and inverse correlations with fiber and lipid intakes, respectively (p < 0.05). Conclusions: Gut microbiota profile was influenced by RYGB and correlated with diet and T2Dr preoperatively, suggesting the possibility to assess its composition to predict postoperative T2Dr.
ObjectiveTo describe the protocol of the SURgically induced Metabolic effects on the Human GastroIntestinal Tract (SURMetaGIT) study, a clinical pan-omics study exploring the gastrointestinal tract as a central organ driving remission of type 2 diabetes mellitus (T2DM) after Roux-en-Y gastric bypass (RYGB). The main points considered in the study’s design and challenges faced in its application are detailed.MethodsThis observational, longitudinal, prospective study involved collection of gastrointestinal biopsy specimens, faeces, urine, and blood from 25 obese women with T2DM who were candidates for RYGB (20 patients for omics assessment and 5 for omics validation). These collections were performed preoperatively and 3 and 24 months postoperatively. Gastrointestinal transcriptomics; faecal metagenomics and metabolomics; plasma proteomics, lipidomics, and metabolomics; and biochemical, nutritional, and metabolic data were assessed to identify their short- and long-term correlations with T2DM remission.ResultsData were collected from 20 patients before and 3 months after RYGB. These patients have nearly completed the 2-year follow-up assessments. The five additional patients are currently being selected for omics data validation.ConclusionThe multi-integrated pan-omics approach of the SURMetaGIT study enables integrated analysis of data that will contribute to the understanding of molecular mechanisms involved in T2DM remission after RYGB.
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