Nutrigenomics is a branch of nutritional science that explores the effects of nutrients on gene function, as well as the effects of genetic variation on nutrient response. The latter, sometimes referred to as nutrigenetics, focuses on how genetic variation affects biological responses to nutrients and food bioactives. A primary goal of nutrigenomics/nutrigenetics is to identify individuals who may benefit from a particular nutritional intervention (responders), and develop alternatives for those who do not (non-responders). Ultimately, the field aims to inform the development of personalised dietary recommendations that improve upon the current one-size-fits-all, population-based model of nutritional guidelines for optimal health and disease prevention.
The idea of tailoring diet to an individual’s DNA is not novel. Two classic examples of genetic variation affecting response to dietary intake are lactose intolerance and phenylketonuria (PKU). These represent simple gene-diet interactions that involve a single gene and single dietary exposure. As the field progresses, nutrigenomics aims to tackle more complex gene-diet interactions that affect disorders with multifactorial etiologies, such as cardiovascular disease (CVD), obesity, type 2 diabetes (T2D) and cancer. Such disorders are polygenic in nature and can be influenced by multiple dietary exposures. Currently, there are many robust examples of how nutrigenomics studies are examining these complex disorders.
One such study (1) assessing the effects of genetic variants in CYP1A2, a gene which encodes a major caffeine-metabolising enzyme, found that high coffee consumption may be associated with an increased risk of CVD only among individuals with the “slow” caffeine metabolising variant of the gene. Conversely, a protective effect of moderate coffee consumption was actually observed among those with the “fast” caffeine-metabolising genotype. Considerable efforts have also been devoted to determining optimal dietary patterns to prevent obesity, which often progresses to more serious chronic diseases such as CVD and T2D. Individuals with certain versions of the APOA2 gene may be at an increased risk of developing obesity when saturated fat intake is high, but not when saturated fat intake is low (2). Additionally, variations in genes involved in the metabolism of certain micronutrients, including vitamin C, D, B12 and iron, have been shown to modify risk of suboptimal or deficient blood levels of these respective nutrients (3-6).
Whilst these studies and others provide evidence for the potential benefits of personalised nutrition, further research is needed to better understand these associations and how they may differ between various ethnic groups. Furthermore, the ultimate utility of genetic testing for personalised nutrition in health promotion depends on the willingness of individuals to adopt favorable health behaviour changes. Research suggests that individuals find personalised dietary recommendations based on their DNA more useful than general dietary advice and are more likely to make beneficial alterations to their diet (7,8). However, some companies that currently offer personalised genetic testing often provide risk estimates for diseases and various traits that don’t necessarily predict response to specific dietary or lifestyle changes. Delivering actionable genetic information with accompanying advice on dietary modifications required to achieve optimal health may be a more effective way to capitalise on the potential benefits that genetic testing and personalised nutrition have to offer.
Currently, it appears that nutrigenomics/nutrigenetics can aid in achieving and maintaining optimal health, and it has the potential to act as an additional tool in the prevention and management of chronic disease on a global scale. As data on this type of actionable genetic information grows and becomes more widely available, the utility of this technology in health promotion will only become more evident.
1. Cornelis MC, El-Sohemy A, Kabagambe EK, et al. Coffee, CYP1A2 genotype, and risk of myocardial infarction. JAMA 2006;295(10):1135-41.
2. Corella D, Peloso G, Arnett DK, et al. APOA2, dietary fat, and body mass index: replication of a gene-diet interaction in 3 independent populations. Arch Intern Med 2009;169(20):1897-906.
3. Cahill LE, Fontaine-Bisson B, El-Sohemy A. Functional genetic variants of glutathione S-transferase protect against serum ascorbic acid deficiency. Am J Clin Nutr 2009;90(5):1411-7.
4. Slater NA, Rager ML, Havrda DE, et al. Genetic Variation in CYP2R1 and GC Genes Associated With Vitamin D Deficiency Status. J Pharm Pract 2017;30(1):31-36.
5. Tanwar VS, Chand MP, Kumar J, et al. Common variant in FUT2 gene is associated with levels of vitamin B(12) in Indian population. Gene 2013;515(1):224-8.
6. Benyamin B, Ferreira MA, Willemsen G, et al. Common variants in TMPRSS6 are associated with iron status and erythrocyte volume. Nat Genet 2009;41(11):1173-5.
7. Nielsen DE, El-Sohemy A. A randomized trial of genetic information for personalized nutrition. Genes Nutr 2012;7(4):559-66.
8. Nielsen DE, El-Sohemy A. Disclosure of genetic information and change in dietary intake: a randomized controlled trial. PLoS One 2014;9(11):e112665.