Postprandial enrichment of triacylglycerol-rich lipoproteins with omega-3 fatty acids: lack of an interaction with apolipoprotein E genotype?
Bibliographic record
Abstract
BACKGROUND: We have previously demonstrated that carrying the apolipoprotein (apo) E epsilon 4 (E4+) genotype disrupts omega-3 fatty acids (n - 3 PUFA) metabolism. Here we hypothesise that the postprandial clearance of n - 3 PUFA from the circulation is faster in E4+ compared to non-carriers (E4-). The objective of the study was to investigate the fasted and postprandial fatty acid (FA) profile of triacylglycerol-rich lipoprotein (TRL) fractions: Sf >400 (predominately chylomicron CM), Sf 60 - 400 (VLDL1), and Sf 20 - 60 (VLDL2) according to APOE genotype. METHODS: Postprandial TRL fractions were obtained in 11 E4+ (ϵ3/ϵ4) and 12 E4- (ϵ3/ϵ3) male from the SATgenϵ study following high saturated fat diet + 3.45 g/d of docosahexaenoic acid (DHA) for 8-wk. Blood samples were taken at fasting and 5-h after consuming a test-meal representative of the dietary intervention. FA were characterized by gas chromatography. RESULTS: At fasting, there was a 2-fold higher ratio of eicosapentaenoic acid (EPA) to arachidonic acid (P = 0.046) as well as a trend towards higher relative% of EPA (P = 0.063) in the Sf >400 fraction of E4+. Total n - 3 PUFA in the Sf 60 - 400 and Sf 20 - 60 fractions were not APOE genotype dependant. At 5 h, there was a trend towards a time × genotype interaction (P = 0.081) for EPA in the Sf >400 fraction. When sub-groups were form based on the level of EPA at baseline within the Sf >400 fraction, postprandial EPA (%) was significantly reduced only in the high-EPA group. EPA at baseline significantly predicted the postprandial response in EPA only in E4+ subjects (R2 = 0.816). CONCLUSION: Despite the DHA supplement contain very low levels of EPA, E4+ subjects with high EPA at fasting potentially have disrupted postprandial n - 3 PUFA metabolism after receiving a high-dose of DHA. TRIAL REGISTRATION: Registered at clinicaltrials.gov/show/NCT01544855.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".