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

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.