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Baseline gut microbiome ecology predicts long-term fat mass loss after bariatric surgery: evidence for a thrifty
Enzamaría Fidilio1,2, Marta Comas Martínez1,2, Vanesa Flores1
1Endocrinology and Nutrition Department, Vall d'Hebron University Hospital, Barcelona, Spain.
Abstract:
Bariatric surgery (BS) induces weight loss, but long-term success involves complex host-microbiome interactions. We evaluated the longitudinal impact of BS, microbiome resilience, and Mediterranean Diet (MedDiet) adherence up to 24 months. This prospective observational study included 85 patients with severe obesity undergoing BS and 21 normal-weight healthy controls (HC). MedDiet adherence (PREDIMED) was assessed before surgery. Fecal microbiota (16S-rRNA sequencing) and metabolomics (1H-NMR spectroscopy) were analyzed at baseline and at 1-, 6-, and 12-months post-BS. Clinical outcomes and fat mass, evaluated by bioimpedanciometry, were tracked up to 24 months. At baseline, patients exhibited higher microbial Shannon diversity than controls (p = 0.041), alongside a dysfunctional microbiome and metabolome characterized by a higher Firmicutes/Bacteroidetes ratio and elevated levels of branched-chain amino acids (p < 0.0001). Ordinary Least Squares (OLS) regression analysis revealed that MedDiet adherence and type 2 diabetes status significantly modulated baseline diversity. At 12 months post-BS, the gut ecosystem underwent profound remodeling, characterized by depletion of Bifidobacterium spp. and an increase in butyrate levels (p < 0.0001), establishing a novel adaptive state distinct from HC. Baseline gut ecology significantly conditioned long-term BS outcomes: patients in the highest quartile of baseline Bifidobacterium spp. lost significantly less fat mass at 24 months than those in the lowest (6.6% vs. 13.2%, p = 0.010). High baseline Bifidobacterium abundance paradoxically acts as a "thrifty microbiome," potentially maximizing energy harvest and limiting surgery-induced fat loss. Overall, BS induces adaptive microbiome restoration rather than true normalization, highlighting the potential for precision interventions prior to surgery.
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