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

ω-3 Polyunsaturated Fatty Acid Status Testing in Humans: A Narrative Review of Commercially Available Options

There is an increasing body of evidence supporting a link between low intakes of ω-3 long-chain polyunsaturated fatty acids (LCPUFA) and numerous diseases and health conditions. However, few people are achieving the levels of fish/seafood or eicosapentaenoic acid and docosahexaenoic acid intake recommended in national and international guidelines. Knowledge of a person's ω-3 LCPUFA status will benefit the interpretation of research results and could be expected to lead to an increased effort to increase intake. Dietary intake survey methods are often used as a surrogate for measuring ω-3 PUFA tissue status and its impact on health and functional outcomes. However, because individuals vary widely in their ability to digest and absorb ω-3 PUFA, analytical testing of biological samples is desirable to accurately evaluate ω-3 PUFA status. Adipose tissue is the reference biospecimen for measuring tissue fatty acids, but less-invasive methods, such as measurements in whole blood or its components (e.g., plasma, serum, red blood cell membranes) or breast milk are often used. Numerous commercial laboratories provide fatty acid testing of blood and breast milk samples by different methods and present their results in a variety of reports such as a full fatty acid profile, ω-3 and ω-6 fatty acid profiles, fatty acid ratios, as well as the Omega-3 Index, the Holman Omega-3 Test, OmegaScore, and OmegaCheck, among others. This narrative review provides information about the different ways to measure ω-3 LCPUFA status (including both dietary assessments and selected commercially available analytical tests of blood and breast milk samples) and discusses evidence linking increased ω-3 LCPUFA intake or status to improved health, focusing on cardiovascular, neurological, pregnancy, and eye health, in support of recommendations to increase ω-3 LCPUFA intake and testing.

Obesity and Nutrigenetics Testing: New Insights

BACKGROUND

Obesity results from interactions between environmental factors, lifestyle, and genetics. In this scenario, nutritional genomics and nutrigenetic tests stand out, with the promise of helping patients avoid or treat obesity. This narrative review investigates whether nutrigenetic tests may help to prevent or treat obesity. Scientific studies in PubMed Science Direct were reviewed, focusing on using nutrigenetic tests in obesity. The work showed that few studies address the use of tools in obesity. However, most of the studies listed reported their beneficial effects in weight loss. Ethical conflicts were also discussed, as in most countries, there are no regulations to standardize these tools, and there needs to be more scientific knowledge for health professionals who interpret them. International Societies, such as the Academy of Nutrition and Dietetics and the Brazilian Association for the Study of Obesity and Metabolic Syndrome, do not recommend nutrigenetic tests to prevent or treat obesity, especially in isolation. Advancing nutrigenetics depends on strengthening three pillars: regulation between countries, scientific evidence with clinical validity, and professional training.

A pilot retrospective study of a physician-directed and genomics-based model for precision lifestyle medicine

Precision lifestyle medicine is a relatively new field in primary care, based on the hypothesis that genetic predispositions influence an individual's response to specific interventions such as diet, exercise, and prescription medications. Despite the increase in commercially available genomic testing, few studies have investigated effects of a physician-directed program to optimize chronic disease using genomics-based precision medicine. We performed an pilot, observational cohort study to evaluate effects of the Wild Health program, a physician and health coach service offering genomics-based lifestyle and medical interventions, on biomarkers indicative of chronic disease. 871 patients underwent genomic testing, biomarker testing, and ongoing health coaching after initial medical consultation by a physician. Improvements in several clinically relevant out-of-range biomarkers at baseline were identified in a large proportion of patients treated through lifestyle intervention without the use of prescription medication. Notably, normalization of several biomarkers associated with chronic disease occurred in 47.5% (hemoglobin A1c [HbA1c]), 33.3% (low density lipoprotein particle number [LDL-P]), and 33.2% (C-reactive protein [CRP]). However, due to the inherent limitations of our observational study design and use of retrospective data, ongoing work will be crucial for continuing to shed light on the effectiveness of physician-led, genomics-based lifestyle coaching programs. Future studies would benefit from implementing a randomized controlled study design, tracking specific interventions, and evaluating physiological data, such as BMI.

Update of a Genetic Risk Score Predictive of the Plasma Triglyceride Response to an Omega-3 Fatty Acid Supplementation in the FAS Study

A genetic risk score (GRS) predictive of the plasma triglyceride (TG) response to an omega-3 fatty acid (n-3 FA) supplementation has been previously developed in the Fatty Acid Sensor (FAS) Study. Recently, novel single nucleotide polymorphisms (SNPs) interacting with a fish oil supplementation and associated with plasma lipid levels have been identified in the UK Biobank. The aim of this study was to verify whether the addition of SNPs identified in the UK Biobank to the GRS built in the FAS Study improves its capacity to predict the plasma TG response to an n-3 FA supplementation. SNPs interacting with fish oil supplementation in the modulation of plasma lipid levels in the UK Biobank and associated with plasma TG levels have been genotyped in participants of the FAS Study (n = 141). Participants have been supplemented with 5 g fish oil/day for six weeks. Plasma TG concentrations were measured before and after the supplementation. Based on the initial GRS of 31 SNPs (GRS31), we computed three new GRSs by adding new SNPs identified in the UK Biobank: GRS32 (rs55707100), GRS38 (seven new SNPs specifically associated with plasma TG levels), and GRS46 (all 15 new SNPs associated with plasma lipid levels). The initial GRS31 explained 50.1% of the variance in plasma TG levels during the intervention, whereas GRS32, GRS38, and GRS46 explained 49.1%, 45.9%, and 45%, respectively. A significant impact on the probability of being classified as a responder or a nonresponder was found for each of the GRSs analyzed, but none of them outperformed the predictive capacity of GRS31 in any of the metrics analyzed, i.e., accuracy, area under the response operating curve (AUC-ROC), sensitivity, specificity and McFadden's pseudo R². The addition of SNPs identified in the UK Biobank to the initial GRS31 did not significantly improve its capacity to predict the plasma TG response to an n-3 FA supplementation. Thus, GRS31 still remains the most precise tool so far by which to discriminate the individual responsiveness to n-3 FAs. Further studies are needed in the field to increase our knowledge of factors underlying the heterogeneity observed in the metabolic response to an n-3 FA supplementation.