Differential effects of EPA and DHA on plasma and adipose tissue lipid mediators: the ComparED study
Bibliographic record
Abstract
Abstract Oxylipins and endocannabinoids (eCBs) both belong to superclasses of lipid mediators with potent inflammation modulatory activities. The adipose tissue (AT) plays a key role in metabolic syndrome-related inflammation, via altered adipocyte physiology, infiltrated macrophages and altered profile of eCBs. We previously reported that DHA is more potent than EPA at modulating systemic inflammation, but the underlying mechanisms remain unclear. The objective of this study was to compare the individual effect of high-dose DHA and of EPA on circulating lipid mediators, i.e. plasma oxylipins and eCBs, and AT-related inflammation. In a randomized double-blind crossover trial, 154 volunteers with abdominal obesity and low-grade inflammation were subjected to three 10-wk supplementation phases: 1- EPA (2.7 g/d); 2- DHA (2.7 g/d); 3- corn oil (control), each separated by a 9-wk washout. Supplements were provided as re-esterified triacylglycerols. Profiling of plasma oxylipins and eCBs was performed on 58 subjects after each phase. Abdominal subcutaneous AT biopsies were also obtained from 13 individuals after each phase. Plasma DHA-, EPA-, arachidonic acid-derived oxylipins were analyzed by LC-MS. eCBs and some of their bioactive congeners were analyzed in plasma and AT by LC-APCI-MS. Adipocyte diameter was determined by histological analysis and AT macrophage infiltration was quantified by double immunofluorescence. Compared with EPA, DHA increased plasma levels of hydroxy-docosahexaenoic acids (7-, 11-, 14-, 4-, 17-HDOHE; P < 0.0001) and palmitoylethanolamide (PEA; P = 0.04). Compared with DHA, EPA led to higher plasma level of hydroxy-eicosapentaenoic acids (12-, 15-, 5-HEPE; P < 0.0001). In the AT, EPA increased the level of oleoylethanolamide (OEA; P = 0.01) compared with DHA, but no other difference was observed between treatments in adipose eCBs and eCB-related lipids. DHA and EPA did not differentially modify adipocyte size distributions (P > 0.50) and proportions of M1-type and M2-type macrophages (P > 0.30). In conclusion, increased plasma levels of anti-inflammatory DHA-derived oxylipins and plasma PEA may be responsible, at least to some extent, for the more potent anti-inflammatory effects of DHA compared with EPA observed in the ComparED study. Conversely, subcutaneous AT does not seem to be involved in explaining such differences between EPA and DHA.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".