Gut Microbiota-specific Profile Prior to Surgery for Predicting Type 2 Diabetes Remission in Patients Undergoing Sleeve Gastrectomy

The predictive role of baseline gut microbiota in type 2 diabetes (T2D) remission after bariatric surgery remains unexplored. This study aimed to identify specific gut microbiota profiles prior to surgery associated with T2D remission following sleeve gastrectomy (SG). This was an observational study including participants with a body mass index (BMI) ≥ 40 kg/m2 and T2D who underwent SG, and had preoperative stool samples available. Gut microbiota was analayzed by 16 S rRNA sequencing. Participants were classified into remission and non-remission groups based on T2D status one year after SG. A total of forty-six participants were included. After adjusting for baseline confounders (i.e., age, HbA1c levels, T2D duration, and insulin treatment), preoperative gut microbiota diversity showed no statistically significant differences between groups, except for Pielou’s evenness index, which was significantly higher in the non-remission group (p = 0.01). ANCOM-BC2 analysis identified an enrichment in Fusicatenibacter, Holdemanella and Senegalimassilia in the non-remission group, whereas Eggerthella, Flavonifractor, Ruminococcaceae g__Incertae Sedis and Ruminococcus gnavus group were enriched in the remission group. Furthermore, insulin treatment and the gut microbial taxa Ruminococcaceae g__Incertae Sedis, Fusicatenibacter, and Eggerthella emerged as potential predictors of T2D remission. Functional analysis using PICRUSt2 revealed increased carbohydrate metabolism pathways in the remission group. Baseline gut microbiota composition may serve as an independent predictor of T2D remission in patients undergoing SG, and could become a potentially relevant biomarker, complementing other existing clinical predictors. The predictive role of baseline gut microbiota in type 2 diabetes (T2D) remission after sleeve gastrectomy (SG) remains unexplored. We show that distinct preoperative gut microbiota composition patterns can be observed in patients who achieve T2D remission compared with those who do not. Baseline gut microbiota composition may serve as a biomarker of T2D remission in patients undergoing SG.

Authors

Institutions

Publication Details

Journal
Obesity Surgery
Published
2026-03-26
DOI
https://doi.org/10.1007/s11695-026-08612-6
Primary Topic
Bariatric Surgery and Outcomes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Gut Microbiota-specific Profile Prior to Surgery for Predicting Type 2 Diabetes Remission in Patients Undergoing Sleeve Gastrectomy

Luís Ocaña-Wilhelmi, Manuela G. López, Lourdes Garrido-Sanchez, José Ignacio Martínez-Montoro et al.
Obesity Surgery
Bariatric Surgery and Outcomes
article

Gut Microbiota-specific Profile Prior to Surgery for Predicting Type 2 Diabetes Remission in Patients Undergoing Sleeve Gastrectomy

Luís Ocaña-Wilhelmi, Manuela G. López, Lourdes Garrido-Sanchez, José Ignacio Martínez-Montoro, Francisco J Tinahones, Raquel Sancho-Marín, Rocío Soler-Humanes, Carolina Gutiérrez-Repiso, Nerea Ruiz-Campos
article en

Abstract

The predictive role of baseline gut microbiota in type 2 diabetes (T2D) remission after bariatric surgery remains unexplored. This study aimed to identify specific gut microbiota profiles prior to surgery associated with T2D remission following sleeve gastrectomy (SG). This was an observational study including participants with a body mass index (BMI) ≥ 40 kg/m2 and T2D who underwent SG, and had preoperative stool samples available. Gut microbiota was analayzed by 16 S rRNA sequencing. Participants were classified into remission and non-remission groups based on T2D status one year after SG. A total of forty-six participants were included. After adjusting for baseline confounders (i.e., age, HbA1c levels, T2D duration, and insulin treatment), preoperative gut microbiota diversity showed no statistically significant differences between groups, except for Pielou’s evenness index, which was significantly higher in the non-remission group (p = 0.01). ANCOM-BC2 analysis identified an enrichment in Fusicatenibacter, Holdemanella and Senegalimassilia in the non-remission group, whereas Eggerthella, Flavonifractor, Ruminococcaceae g__Incertae Sedis and Ruminococcus gnavus group were enriched in the remission group. Furthermore, insulin treatment and the gut microbial taxa Ruminococcaceae g__Incertae Sedis, Fusicatenibacter, and Eggerthella emerged as potential predictors of T2D remission. Functional analysis using PICRUSt2 revealed increased carbohydrate metabolism pathways in the remission group. Baseline gut microbiota composition may serve as an independent predictor of T2D remission in patients undergoing SG, and could become a potentially relevant biomarker, complementing other existing clinical predictors. The predictive role of baseline gut microbiota in type 2 diabetes (T2D) remission after sleeve gastrectomy (SG) remains unexplored. We show that distinct preoperative gut microbiota composition patterns can be observed in patients who achieve T2D remission compared with those who do not. Baseline gut microbiota composition may serve as a biomarker of T2D remission in patients undergoing SG.

Obesity Surgery
Centro de Investigación Biomédica en Red (ES), Andalusian Centre for Nanomedicine and Biotechnology (ES), Hospital Clínico Universitario Virgen de la Victoria (ES), Instituto de Investigación Biomédica de Málaga (ES), Universidad de Málaga (ES)
Good health and well-being
Openalex Percentile: Top 7%
Bariatric Surgery and Outcomes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.