Plasma Levels of Omega-3 and Omega-6 Derived Oxylipins Are Associated with Fecal Microbiota Composition in Young Adults
Bibliographic record
Abstract
Pre-clinical studies suggest that circulating oxylipins, i.e., the oxidation products of polyunsaturated fatty acids (PUFAs), modulate gut microbiota composition in mice, but there is no information available in humans. Therefore, this study aimed to investigate the relationship between omega-3 and omega-6 derived oxylipins plasma levels and fecal microbiota composition in a cohort of young adults. 80 young adults (74% women; 21.9 ± 2.2 years old) were included in this cross-sectional study. Plasma levels of oxylipins were measured using liquid chromatography-tandem mass spectrometry. Fecal microbiota composition was analyzed by V3-V4 16S rRNA gene sequencing. We observed that plasma levels of omega-3 derived oxylipins were positively associated with the relative abundance of Clostridium cluster IV genus (Firmicutes phylum; rho ≥ 0.415, p ≤ 0.009) and negatively associated with the relative abundance of Sutterella genus (Proteobacteria phylum; rho ≥ −0.270, p ≤ 0.041), respectively. Moreover, plasma levels of omega-6 derived oxylipins were negatively associated with the relative abundance of Acidaminococcus and Phascolarctobacterium genera (Firmicutes phylum; all rho ≥ −0.263, p ≤ 0.024), as well as Sutterella, Succinivibrio, and Gemmiger genera (Proteobacteria phylum; all rho ≥ −0.263, p ≤ 0.024). Lastly, the ratio between omega-6 and omega-3 oxylipins plasma levels was negatively associated with the relative abundance of Clostridium cluster IV genus (Firmicutes phylum; rho = −0.334, p = 0.004) and Butyricimonas genus (Bacteroidetes phylum; rho = −0.292, p = 0.014). In conclusion, our results show that the plasma levels of omega-3 and omega-6 derived oxylipins are associated with the relative abundance of specific fecal bacteria genera.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".