Person: Fernández Ruiz, Virginia Esperanza
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Plasma short-chain fatty acid changes after bariatric surgery in patients with severe obesity
Background: Obesity has reached epidemic dimensions in recent decades. Bariatric surgery (BS) is one of the most effective interventions for weight loss and metabolic improvement in patients with obesity. Short-chain fatty acids (SCFA) are gut microbiota-derived metabolites with a key role in body weight control and insulin sensitivity. Although BS is known to induce significant changes in the gut microbiota composition, its impact on the circulating levels of certain metabolites produced by the gut microbiota such as SCFA remains poorly understood. Objective: To determine the impact of BS on the circulating SCFA levels in patients with severe obesity. Setting University hospital. Methods: An observational, prospective study was performed on 51 patients undergoing Roux-en-Y gastric bypass. Plasma samples were collected at baseline (1 day before surgery) and at 6 and 12 months after BS. Plasma SCFA levels were determined by liquid chromatography–mass spectrometry. Results: The results revealed significant changes in the circulating levels of SCFA after BS. A marked increase in propionate, butyrate, isobutyrate, and isovalerate levels and a decrease in acetate, valerate, hexanoate, and heptanoate levels were observed 12 months after BS. Furthermore, the changes in the levels of propionate, butyrate, and isobutyrate negatively correlated with changes in body mass index, while those of isobutyrate correlated negatively with changes in the homeostatic model assessment for insulin resistance index. Conclusion: These results suggest that propionate, butyrate, and isobutyrate levels could be related to weight loss and improved insulin sensitivity in patients with severe obesity after BS.
An explainable machine-learning model using baseline gut microbiota, circulating short-chain fatty acids, and clinical features to predict weight-loss response after Roux-en-Y gastric bypass
Background: Roux-en-Y gastric bypass (RYGB) is one of the most effective treatments for severe obesity; however, postoperative weight-loss response remains heterogeneous. To address this variability, we developed an explainable machine-learning (ML) model integrating baseline gut microbiota composition, circulating short-chain fatty acids (SCFAs), and clinical features to predict weight-loss outcomes after RYGB. Methods: In this prospective cohort study, 143 patients undergoing RYGB were followed for 12 and 24 months. The participants were classified as high- or low-responders based on achieving ≥30% total weight loss (%TWL). Gut microbiota composition was assessed using 16S rRNA gene sequencing. Circulating SCFAs were quantified by liquid chromatography–mass spectrometry. Microbiome-only, clinical–metabolic, and combined models were developed using LASSO logistic regression. Internal validation was performed using stratified repeated five-fold cross-validation with 20 repetitions, and performance was estimated from participant-level out-of-fold predictions. Shapley Additive Explanations (SHAP) were used descriptively to interpret model behavior. Results: At 12 and 24 months after RYGB, 94 and 83 participants achieved ≥30% TWL, respectively. Baseline anthropometric parameters did not differ between the response groups. The baseline alpha diversity was higher in high responders at both 12 and 24 months (P = 0.009 and P = 0.021, respectively). At the taxonomic level, baseline Beijerinckiaceae and Lactobacillaceae were associated with weight loss outcomes. Clinical–metabolic and combined models showed good internal discrimination, particularly at 12 months. However, adding microbiome features did not produce a consistent improvement over the clinical–metabolic model. SHAP values highlighted inflammation-related markers (cholinesterase and C-reactive protein) as the main predictors of 12-month weight loss; heptanoate levels and Coriobacteriaceae abundance were also relevant contributors. Conclusions: Baseline combined ML models integrating baseline gut microbiota, circulating SCFAs, and clinical features provided moderate, internally validated discrimination for marked weight-loss response after RYGB, with the strongest performance observed at 12 months. These findings support further evaluation of preoperative ML models for patient stratification. Microbiome and circulating SCFA features may provide complementary biological and interpretive information, but their incremental predictive and clinical value requires further validation. -----------
The role of PCSK9 in metabolic dysfunction-associated steatotic liver disease and its impact on bariatric surgery outcomes
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is closely tied to obesity. The degree ranges from steatosis (MASL) and steatohepatitis (MASH) to liver cirrhosis. PCSK9 controls cholesterol and lipid particle transport to the liver. PCSK9 might interfere with the pathophysiology of MASLD and bariatric surgery (BS) outcomes of patients with MASLD. Objectives: Evaluate the relationship between serum and hepatic PCSK9 levels with the degree of MASLD and the metabolic outcome of BS. Setting: University Hospital, Spain. Methods: A total of 110 patients with obesity undergoing BS were classified according to liver histology as controls, MAS, and MASH. PCSK9 levels in serum were measured before and 6 months after BS using enzyme-linked immunosorbent assay. PCSK9 protein and mRNA levels in liver tissue were analyzed by immunohistochemistry and reverse transcriptase-polymerase chain reaction, respectively. Results: Hepatic PCSK9 protein levels were diminished in MASL and MASH compared with patients without MASLD and showed a strong negative association with MASLD severity scores. Liver PCSK9 mRNA was higher in MASH compared with controls and MASL and showed positive associations with MASLD severity scores. There were no differences in serum PCSK9 pre or postBS between the groups. Pre- and postsurgery serum PCSK9 positively correlated with cholesterol fold-changes and body mass index (BMI), cholesterol, and low-density lipoprotein -cholesterol fold-changes, respectively. PCSK9 fold-change positively correlated with BMI changes and was the sole variable explaining BMI fold changes in a regression model. Conclusions: PCSK9 mRNA and protein in the liver might be associated with the degree of MASLD. Serum PCSK9 may be associated with cholesterol and/or BMI fold changes. Serum changes of PCSK9 after BS could explain BMI loss outcome.
A novel model for predicting diabetes remission after bariatric surgery based on the measurement of C-peptide and creatinine in serum: a pilot study
Background and aims: Bariatric surgery is effective for treating type 2 diabetes (T2D) in patients with obesity, although a significant proportion of these patients do not achieve diabetes remission after the surgery even after significant weight loss and metabolic improvement. C-peptide is a valuable marker of beta cell function and insulin secretion, but renal function must be considered when interpreting measurements in patients with T2D. The study aims to investigate the association of serum levels of C-peptide adjusted for creatinine with diabetes remission and glycemic target achievement after bariatric surgery in patients with obesity and T2D. Methods and results: Prospective data from a cohort of 84 patients with obesity and T2D submitted to Roux-en-Y gastric bypass (RYGB) were collected at baseline and at least a 6-month follow up. A multivariate binomial regression model showed that Ln(C-peptide/creatinine) and age were significantly associated with 6-month T2D remission. The area under the curve for the receiver operating characteristic analysis (AUROC) to predict remission was 0.87, and more accurate than the AUROC based on C-peptide levels alone (0.75). The same model was also able to predict achieving an HbA1c target of 7 % (53 mmol/mol) (AUROC 0.96). Conclusion: In conclusion, Ln(C-peptide/creatinine) ratio could be a useful tool in predicting T2D remission and target achievement after RYGB surgery, providing a more accurate reflection of beta cell function in bariatric patients.
The role of PCSK9 in metabolic dysfunction-associated steatotic liver disease and its impact on bariatric surgery outcomes
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is closely tied to obesity. The degree ranges from steatosis (MASL) and steatohepatitis (MASH) to liver cirrhosis. PCSK9 controls cholesterol and lipid particle transport to the liver. PCSK9 might interfere with the pathophysiology of MASLD and bariatric surgery (BS) outcomes of patients with MASLD. Objectives: Evaluate the relationship between serum and hepatic PCSK9 levels with the degree of MASLD and the metabolic outcome of BS. Setting: University Hospital, Spain. Methods: A total of 110 patients with obesity undergoing BS were classified according to liver histology as controls, MAS, and MASH. PCSK9 levels in serum were measured before and 6 months after BS using enzyme-linked immunosorbent assay. PCSK9 protein and mRNA levels in liver tissue were analyzed by immunohistochemistry and reverse transcriptase-polymerase chain reaction, respectively. Results: Hepatic PCSK9 protein levels were diminished in MASL and MASH compared with patients without MASLD and showed a strong negative association with MASLD severity scores. Liver PCSK9 mRNA was higher in MASH compared with controls and MASL and showed positive associations with MASLD severity scores. There were no differences in serum PCSK9 pre or postBS between the groups. Pre- and postsurgery serum PCSK9 positively correlated with cholesterol fold-changes and body mass index (BMI), cholesterol, and low-density lipoprotein -cholesterol fold-changes, respectively. PCSK9 fold-change positively correlated with BMI changes and was the sole variable explaining BMI fold changes in a regression model. Conclusions: PCSK9 mRNA and protein in the liver might be associated with the degree of MASLD. Serum PCSK9 may be associated with cholesterol and/or BMI fold changes. Serum changes of PCSK9 after BS could explain BMI loss outcome.