MétaCan
Menu
← Back to cohort

Docosahexaenoic Acid is More Effective than Eicosapentaenoic Acid in Increasing the Omega‐3 Index Measured in Red Blood Cell Membranes

2017· article· en· W2901692835 on OpenAlexaffabout
Janie Allaire, William S. Harris, Cécile Vors, André Tchernof, Patrick Couture, Benoı̂t Lamarche

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecUniversité Laval
Fundersnot available
KeywordsEicosapentaenoic acidDocosahexaenoic acidMedicineCrossover studyRed blood cellInternal medicineConfoundingDocosapentaenoic acidFatty acidSubclinical infectionPolyunsaturated fatty acidEndocrinologyChemistryBiochemistryPlacebo

Abstract

fetched live from OpenAlex

Background Whether eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids have distinct effects on cardiometabolic risk remains unclear as most studies to date have used a mixture of the two fatty acids in various forms and proportions. The Omega‐3 Index (O3I) reflects the sum of EPA and DHA as percent of fatty acids in red blood cell (RBC) membranes and has been inversely associated with the risk of coronary heart diseases and coronary mortality in epidemiological studies. The objective of this study was to assess if supplementation with high dose EPA differentially modify the O3I compared with high dose DHA in men and women at risk of cardiovascular diseases. Methods Using a randomized double‐blind controlled crossover design, 48 men and 106 women with abdominal obesity and subclinical inflammation were randomized to a sequence of three treatment phases: 1–2.7g/d of EPA, 2–2.7 g/d of DHA, 3‐ and 0g/d of EPA+DHA (corn oil). All supplements were provided as 3×1g capsules for a total of 3g/d. Treatment phases had a duration of ten weeks each and were separated by nine‐week washouts. RBC membrane fatty acid composition was measured at baseline and the end of each phase. Differences in RBC membrane fatty acid composition and in the O3I between treatments were assessed using mixed models for repeated measures. Potential confounders of the response to treatments such as weight, sex, age and O3I baseline values were considered. Results The increase in the O3I after DHA (+87% vs. control, p<0.0001) was significantly greater than after EPA (+52% vs. control, p<0.0001; p<0.0001 between DHA and EPA). There was a significant sex*treatment interaction (p=0.046) in the O3I response to EPA and DHA, with similar O3I changes among men and women in response to EPA (0% difference between sexes), but slightly greater O3I increase after DHA among men (+9% compared with women). EPA supplementation increased docosapentaenoic acid (DPA) proportions in RBCs (+84% vs. control, P<0.0001) while DHA decreased DPA in RBCs (−28% vs. control, p<0.0001; p<0.001 between DHA and EPA). Conclusions High‐dose DHA may be more effective than high dose EPA in increasing the O3I, perhaps even more so among men than among women. Because DPA levels are not accounted for in the O3I, in vivo elongation of EPA to DPA may partly explain the difference between EPA and DHA in modulating the O3I. Long‐term intervention studies are needed to determine how this difference relates to cardiovascular risk in men and women. Support or Funding Information This study was supported by a grant from the Canadian Institutes for Health Research (CIHR, MOP‐123494). Douglas Laboratories provided the EPA, DHA and control capsules used in this study. Janie Allaire is a recipient of a PhD Scholarships from the CIHR and Fonds de recherche du Québec ‐ Santé.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.023
GPT teacher head0.301
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueThe FASEB Journal→Same topicFatty Acid Research and Health→French-language works237,207→