The Baseline Gut Microbiota Directs Dieting-Induced Weight Loss Trajectories

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Background & Aims: Elucidating key factors affecting personal responses to food is the first step toward implementing personalized nutrition strategies in for example weight loss programs. Here, we aimed to identify factors of importance for individual weight loss trajectories in a natural setting where participants were provided dietary advice but otherwise asked to self-manage the daily caloric intake and data reporting. Methods: A 6-month weight-reduction program with longitudinal collection of dietary, physical activity, body weight, and fecal microbiome data as well as single-nucleotide polymorphism genotypes in 83 participants was conducted, followed by integration of the high-dimensional data to define the most determining factors for weight loss in a dietician-guided, smartphone-assisted dieting program. Results: The baseline gut microbiota was found to outperform other factors as a predieting predictor of individual weight loss trajectories. Weight loss was also linked to the magnitude of changes in abundances of certain bacterial species during dieting. Ruminococcus gnavus (MGS0160) was significantly enriched in obese individuals and decreased during weight loss. Akkermansia muciniphila (MGS0120) and Alistipes obesi (MGS0342) were significantly enriched in lean individuals, and their abundance increased during dieting. Finally, Blautia wexlerae (MGS0575) and Bacteroides dorei (MGS0187) were the strongest predictors for weight loss when present in high abundance at baseline. Conclusion: Altogether, the baseline gut microbiota was found to excel as a central personal factor in capturing the relationship between dietary factors and weight loss among individuals on a dieting program.

OriginalsprogEngelsk
TidsskriftGastroenterology
Vol/bind160
Udgave nummer6
Sider (fra-til)2029-2042, e1-e16
ISSN0016-5085
DOI
StatusUdgivet - 2021

Bibliografisk note

Funding Information:
Funding This research was supported by National Key Research and Development Program of China (no. 2017YFC0909700 ) and Shenzhen Municipal Government of China (no. DRC-SZ [2015]162 and no. CXB201108250098A ).

ID: 272063107