Systematic Review and Meta-analysis of the Differential Effects of DHA and EPA on Inflammation

Obesity Clinical Trial

Official title:

Do Docosahexaenoic and Eicosapentaenoic Acids Have Similar Effects on Inflammation Markers? A Systematic Review and Meta-analysis of Randomized Controlled Trials

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03520556
• Other study ID #: SRMA-EPA-DHA-INFL
• Status: Completed
• Start date: April 16, 2018
• Est. completion date: April 1, 2020

Study information

• Verified date: August 2022
• Source: Laval University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

According to the World Health Organization, cardiovascular diseases (CVDs) are the number 1 cause of death globally. Systemic and local tissue inflammation is now recognized as a key etiological process leading to CVD. Hence, elevated blood levels of inflammation markers are classified among the well-established risk factors for the development of CVD. Among nutritional strategies to prevent and/or reduce chronic inflammation, long-chain omega 3 PUFA (LCn-3PUFA), notably eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), have raised tremendous interest for their purported anti-inflammatory effects. Previous meta-analysis of randomized controlled trials (RCTs) substantiated the anti-inflammatory effect of LCn-3PUFA supplementation as evidenced by significant reductions in plasma concentrations of specific inflammation markers such as C-reactive protein (CRP) and tumor necrosis factor alpha (TNF-alpha). However, it is stressed that almost all of the reported RCTs have used a mix of EPA and DHA in various ratios, as EPA and DHA occur concomitantly and naturally in food (fish oils) and in most dietary supplements. Yet, several recent RCTs have recently been undertaken to test the hypothesis that not all LCn-3PUFAs are equal, at least when it comes to their anti-inflammatory effects. Accordingly, there is increasing interest and evidence for potential distinctive effects of DHA compared to EPA on systemic inflammation, raising the question: Is DHA a more potent anti-inflammatory nutrient than EPA? To formally answer this question, we will conduct a systematic review and meta-analysis of RCTs to assess and compare the individual anti-inflammatory effects of DHA and of EPA. The present work will be a pairwise and network meta-analysis focusing on RCTs comparing the effects of EPA and DHA on surrogate markers of systemic inflammation. The findings generated by these analyses will provide invaluable and timely comparative information on the specific efficacy of DHA and EPA as one of the key nutritional modalities for the treatment of chronic inflammation in high-risk men and women. This is important considering that LCn-3PUFA supplements are increasingly being used by the population and an ever growing market in the dietary supplements' industry.

Description:

Background: Increased systemic inflammation is positively correlated with the risk for CVD. Among nutritional strategies to prevent and/or reduce chronic inflammation, long-chain omega 3 PUFA (LCn-3PUFA), notably eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), have raised tremendous interest for their purported anti-inflammatory effects.

Need for the proposed research: New emerging data from RCTs suggesting distinct effects of DHA and EPA on systemic inflammation calls for a formal analysis of existing data through a systematic review and meta-analysis, which are considered the gold standard of evidence to inform dietary guidelines.

Objective: To conduct a pairwise and network meta-analysis of RCTs in humans to compare the effects of DHA and EPA on surrogate markers of inflammation.

Design: This systematic review and meta-analysis will be conducted according to the Cochrane Handbook for Systematic Reviews of Interventions and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and The PRISMA Extension Statement for conducting Network Meta-analyses.

Data sources: MEDLINE, EMBASE and The Cochrane Library will be searched using appropriate search terms.

Study selection: RCTs of ≥7 days duration that have specifically compared the effects of DHA to those of EPA, or RCTs that have assessed the effects of DHA or EPA individually compared with a placebo (control), in which changes in plasma concentration of inflammatory markers, namely C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-alpha) and adiponectin, were study outcomes. Literature published in languages other than English or French will be not considered.

Data extraction: Titles and abstracts of studies retrieved using the search strategy will be screened independently by two investigators to identify studies that potentially meet the inclusion criteria outlined above. The full text of these potentially eligible studies will be retrieved and independently assessed for eligibility by two investigators with disagreements being resolved by consensus. Extracted information will include: first author's name, publication year, study design, sample size, subject characteristics (for example sex, age, health and body weight status), EPA and DHA doses, EPA and DHA forms, trial duration, composition of the control supplement, inflammation markers studied and the statistical approach for data analysis. Mean ± SEM differences between various treatments will be extracted for all endpoints. Standard computations and imputations will be used to derive missing variance data. Risk of bias will be assessed using the Cochrane Risk of Bias Tool. The overall quality and strength of the evidence for each outcome will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Risk of bias for network meta-analysis will incorporate assessment of transitivity.

Outcomes: Four outcomes will be assessed: 1) plasma CRP 2) plasma IL-6, 3) plasma TNF-alpha and 4) plasma adiponectin.

Data synthesis: We will use standard Cochrane methods for pairwise meta-analysis and augment this evidence using network meta-analysis methods. Mean differences will be pooled for direct comparisons (DHA vs. EPA) using DerSimonian and Laird random-effects model will be used even in the absence of statistically significant between-study heterogeneity, as they yield more conservative summary effect estimates in the presence of residual heterogeneity. We will present the pooled estimates as mean differences and 95% confidence intervals. We will perform a frequentist network meta-analysis using multivariate meta-analysis model using 'network' suite of commands available in STATA. Mean differences will be pooled for direct comparisons (DHA vs. EPA) and indirect comparisons (DHA vs. placebo and EPA vs. placebo using placebo as the common comparator). We will present the contribution of direct and indirect evidence to mixed evidence using contribution plots. Assumption of consistency will be tested using design-by-treatment model. Paired analyses will be applied for crossover trials. Heterogeneity will be assessed by the Cochran Q statistic and quantified by the I2. To explore sources of heterogeneity, we will conduct sensitivity analyses, in which each study is systematically removed. If there are more than 10 studies, we will also explore sources of heterogeneity using meta-regression analyses and a priori defined subgroup analyses such as body weight status (normal-weight, overweight, obese), health status (for example diabetes, CVD), age, sex, dose, baseline measurements for each outcome, study design (parallel, crossover), study duration, risk of bias, and individual domains of risk of bias. Meta-regression analyses will assess the significance of categorical and continuous subgroup analyses. When more than 10 studies are available, publication bias will be investigated by inspection of funnel plots and formal testing using the Egger test and the Begg test. If publication bias is suspected, we will attempt to adjust for funnel plot asymmetry by imputing the missing study data using the Duval and Tweedie trim and fill method.

Knowledge translation plan: Results from this systematic review and meta-analysis will be disseminated through traditional means such as interactive presentations at local, national, and international scientific meetings and publication in high impact factor journals. Target audiences will include the public health and scientific communities with interest in nutrition, inflammation, and CVD.

Significance: The findings generated by this analysis will provide invaluable and timely comparative information on the specific efficacy of DHA and EPA as one of the key nutritional modalities for the treatment of chronic inflammation in high-risk men and women. This is important considering that LCn-3PUFA supplements are increasingly being used by the population and an ever growing market in the dietary supplements' industry.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 1
• Est. completion date: April 1, 2020
• Est. primary completion date: February 1, 2020
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Randomized controlled trials of =7 days duration in humans

• Suitable control (i.e. fatty acids other than EPA and DHA as control)

• Adults (18 years old and older)

• Viable outcome data

Exclusion Criteria:

• Non-human studies

• Non-randomized treatment allocation

• Randomized controlled trials of <7 days duration

• Lack of a suitable control

• Children

• No viable outcome data

Related Conditions & MeSH terms

• Cardiovascular Diseases
• Chronic Inflammation
• Inflammation
• Metabolic Syndrome
• Obesity
• Overweight

Locations

Country	Name	City	State
Canada	Institute of Nutrition and Functional Foods (INAF)	Quebec

Sponsors (2)

Lead Sponsor	Collaborator
Laval University	University of Toronto

Country where clinical trial is conducted

Canada, 

References & Publications (2)

Vors C, Allaire J, Blanco Mejia S, Khan TA, Sievenpiper JL, Lamarche B. Reply to J Morze and L Schwingshackl. Adv Nutr. 2021 Feb 1;12(1):278-279. doi: 10.1093/advances/nmaa131. — View Citation

Vors C, Allaire J, Mejia SB, Khan TA, Sievenpiper JL, Lamarche B. Comparing the Effects of Docosahexaenoic and Eicosapentaenoic Acids on Inflammation Markers Using Pairwise and Network Meta-Analyses of Randomized Controlled Trials. Adv Nutr. 2021 Feb 1;12 — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Change in plasma concentration of CRP	Change in fasting plasma concentration of CRP with DHA vs. EPA or DHA vs. control or EPA vs. control	Baseline and up to 5 years
Primary	Change in plasma concentration of IL-6	Change in fasting plasma concentration of IL-6 with DHA vs. EPA or DHA vs. control or EPA vs. control	Baseline and up to 5 years
Primary	Change in plasma concentration of TNF-alpha	Change in fasting plasma concentration of TNF-alpha with DHA vs. EPA or DHA vs. control or EPA vs. control	Baseline and up to 5 years
Primary	Change in plasma concentration of adiponectin	Change in fasting plasma concentration of adiponectin with DHA vs. EPA or DHA vs. control or EPA vs. control	Baseline and up to 5 years