Interaction between dietary omega‐3 polyunsaturated fatty acids, obesity and gut microbiota in preclinical models: A systematic review of randomized controlled trials
Bibliographic record
Abstract
Emerging research underscores the potential of omega-3 polyunsaturated fatty acids (PUFAs) in weight reduction and modulation of the gut microbiota. The current review systematically examines the effects of omega-3 PUFA supplementation on body weight regulation and gut microbiota modulation in high-fat diet (HFD)-induced obesity models. The study protocol was registered with PROSPERO (CRD42024559835). Systematic searches were conducted from database inception to May 2025 on PubMed/Embase, Web of Science and selected reference lists. A total of 32 trials were included, with 25 studies employing a HFD along with dietary omega-3 PUFA supplementation and 7 studies with a HFD prior to dietary omega-3 PUFA supplementation. Omega-3 PUFA interventions consistently demonstrated attenuation of HFD-induced weight gain and adiposity, though body weight remained elevated compared to low-fat diet controls. Omega-3 PUFA supplementation also induced significant gut microbiota compositional changes. Specifically, omega-3 PUFAs effectively reduced the Firmicutes/Bacteroidetes (F/B) ratio, reversing a hallmark feature of HFD-induced dysbiosis. Enrichment of beneficial taxa, such as Akkermansia muciniphila, Bifidobacterium and Lactobacillus, was consistently observed, correlating with enhanced short-chain fatty acid (SCFA) production, improved gut barrier integrity and reduced systemic inflammation. Concurrently, omega-3 PUFAs suppressed pathogenic bacteria, such as Desulfovibrio and Lachnoclostridium, which are associated with endotoxaemia and metabolic dysfunction. These preclinical evidence suggest the potential of omega-3 PUFAs as a promising dietary intervention for obesity management through gut microbiota modulation. However, variability in outcomes across studies emphasizes the need for further investigation into the optimal duration, dosage and sources of omega-3 supplementation. Moreover, the synergistic effects of omega-3 PUFA supplements and lifestyle interventions, such as high-intensity interval training (HIIT), which further regulates microbial composition and improves metabolic outcomes, are also highly promising.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".