Gut Microbiota Patterns Predicting Long-Term Weight Loss Success in Individuals with Obesity Undergoing Nonsurgical Therapy

Background: The long-term success of nonsurgical weight reduction programs is variable; thus, predictors of outcome are of major interest. We hypothesized that the intestinal microbiota known to be linked with diet and obesity contain such predictive elements. Methods: Metagenome analysis by shotgun...

Full description

Saved in:
Bibliographic Details
Published in:Nutrients 2022-08, Vol.14 (15), p.3182
Main Authors: Bischoff, Stephan C., Nguyen, Nguyen K., Seethaler, Benjamin, Beisner, Julia, Kügler, Philipp, Stefan, Thorsten
Format: Article
Language:English
Subjects:
Bacteria
Body mass
Body mass index
Body size
Body weight loss
Clinical trials
Diet
Digestive system
DNA sequencing
Gastrointestinal surgery
Genera
Intestinal microflora
Mathematical models
Metabolism
Microbiota
Obesity
Predictions
Software
Statistical methods
Statistical models
Success
Taxonomy
Weight control
Weight loss
Weight reduction
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Background: The long-term success of nonsurgical weight reduction programs is variable; thus, predictors of outcome are of major interest. We hypothesized that the intestinal microbiota known to be linked with diet and obesity contain such predictive elements. Methods: Metagenome analysis by shotgun sequencing of stool DNA was performed in a cohort of 15 adults with obesity (mean body mass index 43.1 kg/m2) who underwent a one-year multidisciplinary weight loss program and another year of follow-up. Eight individuals were persistently successful (mean relative weight loss 18.2%), and seven individuals were not successful (0.2%). The relationship between relative abundancies of bacterial genera/species and changes in relative weight loss or body mass index was studied using three different statistical modeling methods. Results: When combining the predictor variables selected by the applied statistical modeling, we identified seven bacterial genera and eight bacterial species as candidates for predicting success of weight loss. By classification of relative weight-loss predictions for each patient using 2–5 term models, 13 or 14 out of 15 individuals were predicted correctly. Conclusions: Our data strongly suggest that gut microbiota patterns allow individual prediction of long-term weight loss success. Prediction accuracy seems to be high but needs confirmation by larger prospective trials.
ISSN:2072-6643
2072-6643
DOI:10.3390/nu14153182