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Proponents of consumer genetic tests claim that the information can positively impact health behaviors and aid in chronic disease prevention. However, the effects of disclosing genetic information on dietary intake behavior are not clear. A double-blinded, parallel group, 2:1 online randomized controlled trial was conducted to determine the short- and long-term effects of disclosing nutrition-related genetic information for personalized nutrition on dietary intakes of caffeine, vitamin C, added sugars, and sodium. Participants were healthy men and women aged 20-35 years (n = 138). The intervention group (n = 92) received personalized DNA-based dietary advice for 12-months and the control group (n = 46) received general dietary recommendations with no genetic information for 12-months. Food frequency questionnaires were collected at baseline and 3- and 12-months after the intervention to assess dietary intakes. General linear models were used to compare changes in intakes between those receiving general dietary advice and those receiving DNA-based dietary advice. Compared to the control group, no significant changes to dietary intakes of the nutrients were observed at 3-months. At 12-months, participants in the intervention group who possessed a risk version of the ACE gene, and were advised to limit their sodium intake, significantly reduced their sodium intake (mg/day) compared to the control group (-287.3 ± 114.1 vs. 129.8 ± 118.2, p = 0.008). Those who had the non-risk version of ACE did not significantly change their sodium intake compared to the control group (12-months: -244.2 ± 150.2, p = 0.11). Among those with the risk version of the ACE gene, the proportion who met the targeted recommendation of 1500 mg/day increased from 19% at baseline to 34% after 12 months (p = 0.06). These findings demonstrate that disclosing genetic information for personalized nutrition results in greater changes in intake for some dietary components compared to general population-based dietary advice. ClinicalTrials.gov NCT01353014.

Nutrigenomics forms the basis of personalized nutrition by customizing an individual's dietary plan based on the integration of life stage, current health status, and genome information. Some common genes that are included in nutrition-based multigene test panels include CYP1A2 (rate of caffeine break down), MTHFR (folate usage), NOS3 (risk of elevated triglyceride levels related to omega-3 fat intake), and ACE (blood pressure response in related to sodium intake). The complexity of gene test-based personalized nutrition presents barriers to its implementation. This study aimed to compare a self-driven approach to gene test-based nutrition education versus an integrated practitioner-facilitated method to help develop improved interface tools for personalized nutrition practice. A sequential, explanatory mixed methods investigation of 55 healthy adults (35 to 55 years) was conducted that included (1) a 9-week randomized controlled trial where participants were randomized to receive a standard nutrition-based gene test report (control; n=19) or a practitioner-facilitated personalized nutrition intervention (intervention; n=36) and (2) an interpretative thematic analysis of focus group interview data. Outcome measures included differences in the diet quality score (Healthy Eating Index-Canadian [HEI-C]; proportion [%] of calories from total fat, saturated fat, and sugar; omega 3 fatty acid intake [grams]; sodium intake [milligrams]); as well as health-related quality of life (HRQoL) scale score. Of the 55 (55/58 enrolled, 95%) participants who completed the study, most were aged between 40 and 51 years (n=37, 67%), were female (n=41, 75%), and earned a high household income (n=32, 58%). Compared with baseline measures, group differences were found for the percentage of calories from total fat (mean difference [MD]=-5.1%; Wilks lambda (λ)=0.817, F =11.68; P=.001; eta-squared [η²]=0.183) and saturated fat (MD=-1.7%; λ=0.816; F =11.71; P=.001; η²=0.18) as well as HRQoL scores (MD=8.1 points; λ=0.914; F =4.92; P=.03; η²=0.086) compared with week 9 postintervention measures. Interactions of time-by-group assignment were found for sodium intakes (λ=0.846; F =9.47; P=.003; η²=0.15) and HEI-C scores (λ=0.660; F =27.43; P<.001; η²=0.35). An analysis of phenotypic and genotypic information by group assignment found improved total fat (MD=-5%; λ=0.815; F =11.36; P=.001; η²=0.19) and saturated fat (MD=-1.3%; λ=0.822; F =10.86; P=.002; η²=0.18) intakes. Time-by-group interactions were found for sodium (λ=0.844; F =3.09; P=.04; η²=0.16); a post hoc analysis showed pre/post differences for those in the intervention group that did (preintervention mean 3611 mg, 95% CI 3039-4182; postintervention mean 2135 mg, 95% CI 1564-2705) and did not have the gene risk variant (preintervention mean 3722 mg, 95% CI 2949-4496; postintervention mean 2071 mg, 95% CI 1299-2843). Pre- and postdifferences related to the Dietary Reference Intakes showed increases in the proportion of intervention participants within the acceptable macronutrient distribution ranges for fat (pre/post mean difference=41.2%; P=.02). Analysis of textual data revealed 3 categories of feedback: (1) translation of nutrition-related gene test information to action; (2) facilitation of eating behavior change, particularly for the macronutrients and sodium; and (3) directives for future personalized nutrition practice. Although improvements were observed in both groups, healthy adults appear to derive more health benefits from practitioner-led personalized nutrition interventions. Further work is needed to better facilitate positive changes in micronutrient intakes. ClinicalTrials.gov NCT03310814; http://clinicaltrials.gov/ct2/show/NCT03310814. RR2-10.2196/resprot.9846.

Fatty acid ethanolamides (FAE), a group of lipid mediators derived from long-chain fatty acids (FA), mediate biological activities including activation of cannabinoid receptors, stimulation of fat oxidation and regulation of satiety. However, how circulating FAE levels are influenced by FA intake in humans remains unclear. The objective of the present study was to investigate the response of six major circulating FAE to various dietary oil treatments in a five-period, cross-over, randomised, double-blind, clinical study in volunteers with abdominal obesity. The treatment oils (60 g/12 552 kJ per d (60 g/3000 kcal per d)) provided for 30 d were as follows: conventional canola oil, high oleic canola oil, high oleic canola oil enriched with DHA, flax/safflower oil blend and corn/safflower oil blend. Two SNP associated with FAE degradation and synthesis were studied. Post-treatment results showed overall that plasma FAE levels were modulated by dietary FA and were positively correlated with corresponding plasma FA levels; minor allele (A) carriers of SNP rs324420 in gene fatty acid amide hydrolase produced higher circulating oleoylethanolamide (OEA) ( P =0·0209) and docosahexaenoylethanolamide (DHEA) levels ( P =0·0002). In addition, elevated plasma DHEA levels in response to DHA intake tended to be associated with lower plasma OEA levels and an increased gynoid fat mass. In summary, data suggest that the metabolic and physiological responses to dietary FA may be influenced via circulating FAE. Genetic analysis of rs324420 might help identify a sub-population that appears to benefit from increased consumption of DHA and oleic acid.

Background. Noncommunicable diseases (NCDs) are the first cause of death worldwide. Mediterranean diet may play a crucial role in the prevention of NCDs, and the presence of wine in this diet could play a positive role on health. Methods. 54 healthy volunteers consumed one of the following beverages: red (RW) or white wine (WW), vodka (VDK), and/or Mediterranean meal (MeDM) and high-fat meal (HFM). Results. OxLDL-C changed significantly between baseline versus HFM, MeDM versus HFM, and HFM versus HFM + RW (p<0.05). Significant upregulation of catalase (CAT) was observed only after RW. Conversely, WW, VDK, RW + MeDM, HF + WW, and HF + VDK determined a significant downregulation of CAT gene. Superoxide dismutase 2 (SOD2) gene expression was upregulated in WW, MeDM + VDK, and RW. Contrariwise, HFM + VDK determined a downregulation of its expression. RW, RW + MeDM, and RW + HFM caused the upregulation of glutathione peroxidase-1 (GPX1). Conclusions. Our results suggest that the association of low/moderate intake of alcohol beverages, with nutraceutical-proven effectiveness, and ethanol, in association with a Mediterranean diet, could determine a reduction of atherosclerosis risk onset through a positive modulation of antioxidant gene expression helping in the prevention of inflammatory and oxidative damages.

Response to dietary fat manipulation is highly heterogeneous, yet generic population-based recommendations aimed at reducing the burden of CVD are given. The APOE epsilon genotype has been proposed to be an important determinant of this response. The present study reports on the dietary strategy employed in the SATgenε (SATurated fat and gene APOE) study, to assess the impact of altered fat content and composition on the blood lipid profile according to the APOE genotype. A flexible dietary exchange model was developed to implement three isoenergetic diets: a low-fat (LF) diet (target composition: 24 % of energy (%E) as fat, 8 %E SFA and 59 %E carbohydrate), a high-saturated fat (HSF) diet (38 %E fat, 18 %E SFA and 45 %E carbohydrate) and a HSF-DHA diet (HSF diet with 3 g DHA/d). Free-living participants (n 88; n 44 E3/E3 and n 44 E3/E4) followed the diets in a sequential design for 8 weeks, each using commercially available spreads, oils and snacks with specific fatty acid profiles. Dietary compositional targets were broadly met with significantly higher total fat (42·8 %E and 41·0 %E v. 25·1 %E, P ≤ 0·0011) and SFA (19·3 %E and 18·6 %E v. 8·33 %E, P ≤ 0·0011) intakes during the HSF and HSF-DHA diets compared with the LF diet, in addition to significantly higher DHA intake during the HSF-DHA diet (P ≤ 0·0011). Plasma phospholipid fatty acid analysis revealed a 2-fold increase in the proportion of DHA after consumption of the HSF-DHA diet for 8 weeks, which was independent of the APOE genotype. In summary, the dietary strategy was successfully implemented in a free-living population resulting in well-tolerated diets which broadly met the dietary targets set.

Functional foods and nutraceuticals have received considerable interest in the past decade largely due to increasing consumer awareness of the health benefits associated with food. Diet in human health is no longer a matter of simple nutrition: consumers are more proactive and increasingly interested in the health benefits of functional foods and their role in the prevention of illness and chronic conditions. This, combined with an aging population that focuses not only on longevity but also quality of life, has created a market for functional foods and nutraceuticals. A fully updated and revised second edition, Genomics, Proteomics and Metabolomics in Nutraceuticals and Functional Foods reflects the recent upsurge in \"omics\" technologies and features 48 chapters that cover topics including genomics, proteomics, metabolomics, epigenetics, peptidomics, nutrigenomics and human health, transcriptomics, nutriethics and nanotechnology. This cutting-edge volume, written by a panel of experts from around the globe reviews the latest developments in the field with an emphasis on the application of these novel technologies to functional foods and nutraceuticals.

The concept that interactions between nutrition and genetics determine phenotype was established by Garrod at the beginning of the 20th century through his ground-breaking work on inborn errors of metabolism. A century later, the science and technologies involved in sequencing of the human genome stimulated development of the scientific discipline which we now recognise as nutritional genomics (nutrigenomics). Much of the early hype around possible applications of this new science was unhelpful and raised expectations, which have not been realised as quickly as some would have hoped. However, major advances have been made in quantifying the contribution of genetic variation to a wide range of phenotypes and it is now clear that for nutrition-related phenotypes, such as obesity and common complex diseases, the genetic contribution made by SNP alone is often modest. There is much scope for innovative research to understand the roles of less well explored types of genomic structural variation, e.g. copy number variants, and of interactions between genotype and dietary factors, in phenotype determination. New tools and models, including stem cell-based approaches and genome editing, have huge potential to transform mechanistic nutrition research. Finally, the application of nutrigenomics research offers substantial potential to improve public health e.g. through the use of metabolomics approaches to identify novel biomarkers of food intake, which will lead to more objective and robust measures of dietary exposure. In addition, nutrigenomics may have applications in the development of personalised nutrition interventions, which may facilitate larger, more appropriate and sustained changes in eating (and other lifestyle) behaviours and help to reduce health inequalities.

Health nudge interventions to steer people into healthier lifestyles are increasingly applied by governments worldwide, and it is natural to look to such approaches to improve health by altering what people choose to eat. However, to produce policy recommendations that are likely to be effective, we need to be able to make valid predictions about the consequences of proposed interventions, and for this, we need a better understanding of the determinants of food choice. These determinants include dietary components (e.g. highly palatable foods and alcohol), but also diverse cultural and social pressures, cognitive-affective factors (perceived stress, health attitude, anxiety and depression), and familial, genetic and epigenetic influences on personality characteristics. In addition, our choices are influenced by an array of physiological mechanisms, including signals to the brain from the gastrointestinal tract and adipose tissue, which affect not only our hunger and satiety but also our motivation to eat particular nutrients, and the reward we experience from eating. Thus, to develop the evidence base necessary for effective policies, we need to build bridges across different levels of knowledge and understanding. This requires experimental models that can fill in the gaps in our understanding that are needed to inform policy, translational models that connect mechanistic understanding from laboratory studies to the real life human condition, and formal models that encapsulate scientific knowledge from diverse disciplines, and which embed understanding in a way that enables policy-relevant predictions to be made. Here we review recent developments in these areas.

Nonalcoholic fatty liver disease (NAFLD) represents a global healthcare burden since it is epidemiologically related to obesity, type 2 diabetes (T2D) and Metabolic Syndrome (MetS). It embraces a wide spectrum of hepatic injuries, which include simple steatosis, nonalcoholic steatohepatitis (NASH), fibrosis, cirrhosis and hepatocellular carcinoma (HCC). The susceptibility to develop NAFLD is highly variable and it is influenced by several cues including environmental (i.e., dietary habits and physical activity) and inherited (i.e., genetic/epigenetic) risk factors. Nonetheless, even intestinal microbiota and its by-products play a crucial role in NAFLD pathophysiology. The interaction of dietary exposure with the genome is referred to as ‘nutritional genomics,’ which encompasses both ‘nutrigenetics’ and ‘nutriepigenomics.’ It is focused on revealing the biological mechanisms that entail both the acute and persistent genome-nutrient interactions that influence health and it may represent a promising field of study to improve both clinical and health nutrition practices. Thus, the premise of this review is to discuss the relevance of personalized nutritional advices as a novel therapeutic approach in NAFLD tailored management.