Fluhr · Nature 2021 · Preclinical animal experimental study with preliminary human cross-sectional cohort · n=?

Gut microbiota modulates weight gain in mice after discontinued smoke exposure.

Cited 94 times in the scientific literature.

Level 5 - mechanism / opinion, no new human data

Preclinical animal model with mechanistic experiments and preliminary cross-sectional human observational data

PubMed 34880502 · doi:10.1038/s41586-021-04194-8 · record verified 2026-08-30

What was done

Researchers used mouse models to investigate how cigarette smoke exposure and cessation affect the gut microbiome and subsequent weight gain. They tested whether microbiome depletion via antibiotics could prevent smoking-cessation-induced weight gain and performed fecal microbiota transplantation from smoke-exposed mice into germ-free, smoke-naive mice across different diets and strains. They also evaluated metabolic pathways involving dietary choline, dimethylglycine, and N-acetylglycine, supplemented by preliminary observations in a small cross-sectional human cohort.

What was found

The abstract reports no specific numerical effect sizes, sample sizes, or statistical values. Directionally, smoke exposure induced dysbiosis driven by smoke-related metabolites. Antibiotic-induced microbiome depletion prevented smoking-cessation weight gain in mice, whereas fecal transfer from smoke-exposed mice induced excessive weight gain in germ-free mice. Metabolically, this process involved increased shunting of dietary choline to dimethylglycine (increasing energy harvest) alongside depletion of N-acetylglycine.

Why it matters

Weight gain after smoking cessation is a major barrier to quitting, occurring even without increased caloric intake. Identifying a gut-microbiota-driven metabolic mechanism offers potential therapeutic targets to mitigate weight gain during smoking cessation.

Limits

The primary findings are derived from mouse models, which may not fully reflect human physiology. The human cohort was small and cross-sectional, precluding causal inference in people. Exact sample sizes, effect sizes, dietary parameters, and quantitative metrics are omitted from the abstract.

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