ArticleGenes & nutrition2020
Genetic risk prediction of the plasma triglyceride response to independent supplementations with eicosapentaenoic and docosahexaenoic acids: the ComparED Study.
Article in Genes & nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01810003 (Impact of EPA and DHA Supplementation on Plasma Biomarkers of Inflammation in Men and Women With Metabolic Syndrome), which is not on this map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Impact of EPA and DHA Supplementation on Plasma Biomarkers of Inflammation in Men and Women With Metabolic Syndrome
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Pooled it
- Scientific Opinion on the tolerable upper intake level for supplemental docosahexaenoic acid.EFSA journal. European Food Safety Authority · 2026Article
- Revisiting multi-omics-based predictors of the plasma triglyceride response to an omega-3 fatty acid supplementation.Frontiers in nutrition · 2024Article
- Clinical Practice Guidelines Using GRADE and AGREE II for the Impact of Genetic Variants on Plasma Lipid/Lipoprotein/Apolipoprotein Responsiveness to Omega-3 Fatty Acids.Frontiers in nutrition · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe previously built a genetic risk score (GRS) highly predictive of the plasma triglyceride (TG) response to an omega-3 fatty acid (n-3 FA) supplementation from marine sources. The objective of the present study was to test the potential of this GRS to predict the plasma TG responsiveness to supplementation with either eicosapentaenoic (EPA) or docosahexaenoic (DHA) acids in the Comparing EPA to DHA (ComparED) Study.
methodsThe ComparED Study is a double-blind, controlled, crossover trial, with participants randomized to three supplemented phases of 10 weeks each: (1) 2.7 g/day of DHA, (2) 2.7 g/day of EPA, and (3) 3 g/day of corn oil (control), separated by 9-week washouts. The 31 SNPs used to build the previous GRS were genotyped in 122 participants of the ComparED Study using TaqMan technology. The GRS for each participant was computed by summing the number of rare alleles. Ordinal and binary logistic models, adjusted for age, sex, and body mass index, were used to calculate the ability of the GRS to predict TG responsiveness.
resultsThe GRS predicted TG responsiveness to EPA supplementation (p = 0.006), and a trend was observed for DHA supplementation (p = 0.08). The exclusion of participants with neutral TG responsiveness clarified the association patterns and the predictive capability of the GRS (EPA, p = 0.0003, DHA p = 0.01).
conclusionResults of the present study suggest that the constructed GRS is a good predictor of the plasma TG response to supplementation with either DHA or EPA.
trial registrationClinicalTrials.gov, NCT01810003. The study protocol was registered on March 4, 2013.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.