Genetic Risk Score Predictive of the Plasma Triglyceride Response to an Omega-3 Fatty Acid Supplementation in a Mexican Population

Investigation of the interaction between Genetic Risk Score (GRS) and fatty acid quality indices on mental health among overweight and obese women

BACKGROUND & AIMS

Mental disorders are associated with dietary fatty acids and genome-wide association studies have found multiple risk loci robustly related to depression, anxiety, and stress. The aim of this study is to investigate the interaction of genetic risk score (GRS) and dietary fat quality indices on mental health.

METHODS

This cross-sectional study included 279 overweight and obese women for N6/N3 ratio and 378 overweight and obese women for CSI aged 18-68 years. Using reliable and verified standard protocols, body composition, anthropometric indices, blood pressure, physical activity, and dietary fat quality were measured. Serum samples were used to determine biochemical tests. A genetic risk score (GRS) was calculated using the risk alleles of the three SNPs. A generalized linear model (GLM) was applied to assess the interactions between GRS and fat quality indices. Mental health was evaluated using Depression Anxiety Stress Scales (DASS-21).

RESULTS

The mean (± SD) age and BMI of our participants were 36.48 (8.45) and 30.73 (3.72) kg/m2 respectively. There was a marginally significant mean difference among tertiles of the CSI in terms of stress (P = 0.051), DASS-21 (P = 0.078) in the crude model. After adjusting for age, energy intake, physical activity and BMI in model 1, there was a positive interaction between GRS and T3 of N6/N3 ratio on anxiety (β = 0.91, CI = 0.08,1.75, P = 0.031), depression (β = 1.05, CI = 0.06,2.04, P = 0.037), DASS-21 (β = 2.22, CI= -0.31,4.75, P = 0.086).

CONCLUSION

Our findings indicate that higher ratio of N-6 to N-3 considering genetics were predictive of mental disorder in our population.

Nutrigenetics, omega-3 and plasma lipids/lipoproteins/apolipoproteins with evidence evaluation using the GRADE approach: a systematic review

OBJECTIVES

Despite the uptake of nutrigenetic testing through direct-to-consumer services and healthcare professionals, systematic reviews determining scientific validity are limited in this field. The objective of this review was to: retrieve, synthesise and assess the quality of evidence (confidence) for nutrigenetic approaches related to the effect of genetic variation on plasma lipid, lipoprotein and apolipoprotein responsiveness to omega-3 fatty acid intake.

DESIGN

A systematic review was conducted using three search engines (Embase, Web of Science and Medline) for articles published up until 1 August 2020. We aimed to systematically search, identify (select) and provide a narrative synthesis of all studies that assessed nutrigenetic associations/interactions for genetic variants (comparators) influencing the plasma lipid, lipoprotein and/or apolipoprotein response (outcomes) to omega-3 fatty acid intake (intervention/exposure) in humans-both paediatric and adult populations (population). We further aimed to assess the overall quality of evidence for specific priority nutrigenetic associations/interactions based on the following inclusion criteria: nutrigenetic associations/interactions reported for the same genetic variants (comparators) influencing the same plasma lipid, lipoprotein and/or apolipoprotein response (outcomes) to omega-3 fatty acid intake (intervention/exposure) in humans-both paediatric and adult populations (population) in at least two independent studies, irrespective of the findings. Risk of bias was assessed in individual studies. Evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach with a modification to further consider biological plausibility.

RESULTS

Out of 1830 articles screened, 65 met the inclusion criteria for the narrative synthesis (n=23 observational, n=42 interventional); of these, 25 met the inclusion criteria for GRADE evidence evaluation. Overall, current evidence is insufficient for gene-diet associations related to omega-3 fatty acid intake on plasma apolipoproteins, total cholesterol, high-density lipoprotein-cholesterol, low-density lipoprotein (LDL)-cholesterol and LDL particle size. However, there is strong (GRADE rating: moderate quality) evidence to suggest that male APOE-E4 carriers (rs429358, rs7412) exhibit significant triglyceride reductions in response to omega-3-rich fish oil with a dose-response effect. Moreover, strong (GRADE rating: high quality) evidence suggests that a 31-SNP nutrigenetic risk score can predict plasma triglyceride responsiveness to omega-3-rich fish oil in adults with overweight/obesity from various ethnicities.

CONCLUSIONS

Most evidence in this area is weak, but two specific nutrigenetic interactions exhibited strong evidence, with generalisability limited to specific populations.

PROSPERO REGISTRATION NUMBER

CRD42020185087.

Genomics in Personalized Nutrition: Can You "Eat for Your Genes"?

Genome-wide single nucleotide polymorphism (SNP) data are now quickly and inexpensively acquired, raising the prospect of creating personalized dietary recommendations based on an individual's genetic variability at multiple SNPs. However, relatively little is known about most specific gene-diet interactions, and many molecular and clinical phenotypes of interest (e.g., body mass index [BMI]) involve multiple genes. In this review, we discuss direct to consumer genetic testing (DTC-GT) and the current potential for precision nutrition based on an individual's genetic data. We review important issues such as dietary exposure and genetic architecture addressing the concepts of penetrance, pleiotropy, epistasis, polygenicity, and epigenetics. More specifically, we discuss how they complicate using genotypic data to predict phenotypes as well as response to dietary interventions. Then, several examples (including caffeine sensitivity, alcohol dependence, non-alcoholic fatty liver disease, obesity/appetite, cardiovascular, Alzheimer's disease, folate metabolism, long-chain fatty acid biosynthesis, and vitamin D metabolism) are provided illustrating how genotypic information could be used to inform nutritional recommendations. We conclude by examining ethical considerations and practical applications for using genetic information to inform dietary choices and the future role genetics may play in adopting changes beyond population-wide healthy eating guidelines.

Genetic risk prediction of the plasma triglyceride response to independent supplementations with eicosapentaenoic and docosahexaenoic acids: the ComparED Study

BACKGROUND

We 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.

METHODS

The 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.

RESULTS

The 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).

CONCLUSION

Results 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 REGISTRATION

ClinicalTrials.gov, NCT01810003. The study protocol was registered on March 4, 2013.

Prevention of Potential Adverse Metabolic Effects of a Supplementation with Omega-3 Fatty Acids Using a Genetic Score Approach

INTRODUCTION

The consumption of long-chain omega-3 polyunsaturated fatty acids (n-3 PUFA) has been reported to have beneficial health effects, notably, by reducing plasma triglyceride levels. Nonetheless, a concomitant decrease in insulin sensitivity has also been observed, but is highly variable among subjects. Herein, we aimed to determine the importance of the genetic background in the interindividual variability of the insulin sensitivity response following an n-3 PUFA supplementation.

METHODS

A total of 210 participants completed a 6-week n-3 PUFA supplementation with 5 g/day of fish oil (providing 1.9-2.2 g of eicosapentaenoic acid + 1.1 g of docosahexaenoic acid). Insulin resistance was estimated by the homeostatic model assessment (HOMA-IR), and participants were further classified as high-risk or low-risk depending on their HOMA-IR change following the n-3 PUFA supplementation, as compared to pre-supplementation values. Genome-wide genotyping data were obtained for 138 participants using HumanOmni-5-Quad BeadChips containing 4,301,331 single nucleotide polymorphisms. A genome-wide association analysis (GWAS) was carried out between high-risk and low-risk participants. The population study was split into training (60%) and testing (40%) datasets to assess the predictive accuracy of a genetic risk score (GRS) constructed by summing the number of risk alleles.

RESULTS

Following the n-3 PUFA supplementation, 32 participants had increased HOMA-IR as compared to initial values and were classified as high risk (23.2%), whereas remaining subjects were classified as low risk (n = 106, 76.8%). A total of 8 loci had frequency differences between high-risk and low-risk participants at a suggestive GWAS association threshold (p value <1 × 10-5). After applying 10-fold cross validation, the GRS showed a significant association with the risk of increased HOMA-IR in the testing dataset (OR = 3.16 [95% CI, 1.85-7.14]), with a predictive accuracy of 0.85, and explained 40% of variation in HOMA-IR change.

CONCLUSIONS

These results suggest that the genetic background has a relevant role in the interindividual variability observed in the insulin sensitivity response following an n-3 PUFA supplementation. Subjects being at risk of insulin sensitivity lowering following an n-3 PUFA supplementation may be identified using genetic-based precision nutrition approaches.