Lipoprotein receptor-related protein 1 variants and dietary fatty acids: meta-analysis of European origin and African American studies

Current challenges and future implications of exploiting the omics data into nutrigenetics and nutrigenomics for personalized diagnosis and nutrition-based care

Nutrigenetics and nutrigenomics, combined with the omics technologies, are a demanding and an increasingly important field in personalizing nutrition-based care to understand an individual's response to nutrition-guided therapy. Omics is defined as the analysis of the large data sets of the biological system featuring transcriptomics, proteomics, and metabolomics and providing new insights into cell regulation. The effect of combining nutrigenetics and nutrigenomics with omics will give insight into molecular analysis, as human nutrition requirements vary per individual. Omics measures modest intraindividual variability and is critical to exploit these data for use in the development of precision nutrition. Omics, combined with nutrigenetics and nutrigenomics, is instrumental in the creation of goals for improving the accuracy of nutrition evaluations. Although dietary-based therapies are provided for various clinical conditions such as inborn errors of metabolism, limited advancement has been done to expand the omics data for a more mechanistic understanding of cellular networks dependent on nutrition-based expression and overall regulation of genes. The greatest challenge remains in the clinical sector to integrate the current data available, overcome the well-established limits of self-reported methods in research, and provide omics data, combined with nutrigenetics and nutrigenomics research, for each individual. Hence, the future seems promising if a design for personalized, nutrition-based diagnosis and care can be implemented practically in the health care sector.

Common Variants in Lipid Metabolism-Related Genes Associate with Fat Mass Changes in Response to Dietary Monounsaturated Fatty Acids in Adults with Abdominal Obesity

BACKGROUND

Different fatty acids (FAs) can vary in their obesogenic effect, and genetic makeup can contribute to fat deposition in response to dietary FA composition. However, the antiobesogenic effects of the interactions between dietary MUFAs and genetics have scarcely been tested in intervention studies.

OBJECTIVE

We evaluated the overall (primary outcome) and genetically modulated (secondary outcome) response in body weight and fat mass to different levels of MUFA consumption.

METHODS

In the Canola Oil Multicenter Intervention Trial II, a randomized, crossover, isocaloric, controlled-feeding multicenter trial, 44 men and 71 women with a mean age of 44 y and an increased waist circumference (men ∼108 cm and women ∼102 cm) consumed each of 3 oils for 6 wk, separated by four 12-wk washout periods. Oils included 2 high-MUFA oils-conventional canola and high-oleic canola (<7% SFAs, >65% MUFAs)-and 1 low-MUFA/high-SFA oil blend (40.2% SFAs, 22.0% MUFAs). Body fat was measured using DXA. Five candidate single-nucleotide polymorphisms (SNPs) were genotyped using qualitative PCR. Data were analyzed using a repeated measures mixed model.

RESULTS

No significant differences were observed in adiposity measures following the consumption of either high-MUFA diet compared with the low-MUFA/high-SFA treatment. However, when stratified by genotype, 3 SNPs within lipoprotein lipase (LPL), adiponectin, and apoE genes influenced, separately, fat mass changes in response to treatment (n = 101). Mainly, the LPL rs13702-CC genotype was associated with lower visceral fat (high-MUFA: -216.2 ± 58.6 g; low-MUFA: 17.2 ± 81.1 g; P = 0.017) and android fat mass (high-MUFA: -267.3 ± 76.4 g; low-MUFA: -21.7 ± 102.2 g; P = 0.037) following average consumption of the 2 high-MUFA diets.

CONCLUSIONS

Common variants in LPL, adiponectin, and apoE genes modulated body fat mass response to dietary MUFAs in an isocaloric diet in adults with abdominal obesity. These findings might eventually help in developing personalized dietary recommendations for weight control. The trial was registered at clinicaltrials.gov as NCT02029833 (https://www.clinicaltrials.gov/ct2/show/NCT02029833?cond=NCT02029833&rank=1).

Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review

Suboptimal nutrition is a leading cause of poor health. Nutrition and policy science have advanced rapidly, creating confusion yet also providing powerful opportunities to reduce the adverse health and economic impacts of poor diets. This review considers the history, new evidence, controversies, and corresponding lessons for modern dietary and policy priorities for cardiovascular diseases, obesity, and diabetes mellitus. Major identified themes include the importance of evaluating the full diversity of diet-related risk pathways, not only blood lipids or obesity; focusing on foods and overall diet patterns, rather than single isolated nutrients; recognizing the complex influences of different foods on long-term weight regulation, rather than simply counting calories; and characterizing and implementing evidence-based strategies, including policy approaches, for lifestyle change. Evidence-informed dietary priorities include increased fruits, nonstarchy vegetables, nuts, legumes, fish, vegetable oils, yogurt, and minimally processed whole grains; and fewer red meats, processed (eg, sodium-preserved) meats, and foods rich in refined grains, starch, added sugars, salt, and trans fat. More investigation is needed on the cardiometabolic effects of phenolics, dairy fat, probiotics, fermentation, coffee, tea, cocoa, eggs, specific vegetable and tropical oils, vitamin D, individual fatty acids, and diet-microbiome interactions. Little evidence to date supports the cardiometabolic relevance of other popular priorities: eg, local, organic, grass-fed, farmed/wild, or non-genetically modified. Evidence-based personalized nutrition appears to depend more on nongenetic characteristics (eg, physical activity, abdominal adiposity, gender, socioeconomic status, culture) than genetic factors. Food choices must be strongly supported by clinical behavior change efforts, health systems reforms, novel technologies, and robust policy strategies targeting economic incentives, schools and workplaces, neighborhood environments, and the food system. Scientific advances provide crucial new insights on optimal targets and best practices to reduce the burdens of diet-related cardiometabolic diseases.

Quantitative Genetics of Food Intake in Drosophila melanogaster

Food intake is an essential animal activity, regulated by neural circuits that motivate food localization, evaluate nutritional content and acceptance or rejection responses through the gustatory system, and regulate neuroendocrine feedback loops that maintain energy homeostasis. Excess food consumption in people is associated with obesity and metabolic and cardiovascular disorders. However, little is known about the genetic basis of natural variation in food consumption. To gain insights in evolutionarily conserved genetic principles that regulate food intake, we took advantage of a model system, Drosophila melanogaster, in which food intake, environmental conditions and genetic background can be controlled precisely. We quantified variation in food intake among 182 inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel (DGRP). We found significant genetic variation in the mean and within-line environmental variance of food consumption and observed sexual dimorphism and genetic variation in sexual dimorphism for both food intake traits (mean and variance). We performed genome wide association (GWA) analyses for mean food intake and environmental variance of food intake (using the coefficient of environmental variation, CV_E, as the metric for environmental variance) and identified molecular polymorphisms associated with both traits. Validation experiments using RNAi-knockdown confirmed 24 of 31 (77%) candidate genes affecting food intake and/or variance of food intake, and a test cross between selected DGRP lines confirmed a SNP affecting mean food intake identified in the GWA analysis. The majority of the validated candidate genes were novel with respect to feeding behavior, and many had mammalian orthologs implicated in metabolic diseases.

Dietary Patterns, Genes, and Health: Challenges and Obstacles to be Overcome

Several dietary approaches have been proposed to prevent the onset of chronic diseases. As yet, no single approach has emerged as having the most consistent health benefits. This arises, in part, due to the fact that diet influences health in the context of individual factors with genetic components. Therefore, the effects of diet on health may be dependent on an individual's genetic background. At this time we lack robust evidence for the effects of interactions between genes and dietary patterns on health. To understand why, I will briefly review the most methodologically strong attempts to identify gene-diet interactions, which will illuminate how the challenges facing all of genetic research apply to the search for gene-diet interactions. Then I will discuss some ways in which these challenges are being addressed that offer hope for the future in which the best diet for an individual is identified based on their genetic variation.

Expression quantitative trait analyses to identify causal genetic variants for type 2 diabetes susceptibility

Type 2 diabetes (T2D) is a common metabolic disorder which is caused by multiple genetic perturbations affecting different biological pathways. Identifying genetic factors modulating the susceptibility of this complex heterogeneous metabolic phenotype in different ethnic and racial groups remains challenging. Despite recent success, the functional role of the T2D susceptibility variants implicated by genome-wide association studies (GWAS) remains largely unknown. Genetic dissection of transcript abundance or expression quantitative trait (eQTL) analysis unravels the genomic architecture of regulatory variants. Availability of eQTL information from tissues relevant for glucose homeostasis in humans opens a new avenue to prioritize GWAS-implicated variants that may be involved in triggering a causal chain of events leading to T2D. In this article, we review the progress made in the field of eQTL research and knowledge gained from those studies in understanding transcription regulatory mechanisms in human subjects. We highlight several novel approaches that can integrate eQTL analysis with multiple layers of biological information to identify ethnic-specific causal variants and gene-environment interactions relevant to T2D pathogenesis. Finally, we discuss how the eQTL analysis mediated search for “missing heritability” may lead us to novel biological and molecular mechanisms involved in susceptibility to T2D.

How does the Mediterranean diet promote cardiovascular health? Current progress toward molecular mechanisms: gene-diet interactions at the genomic, transcriptomic, and epigenomic levels provide novel insights into new mechanisms

Epidemiological evidence supports a health-promoting effect of the Mediterranean Diet (MedDiet), especially in the prevention of cardiovascular diseases. These cardiovascular benefits have been attributed to a number of components of the MedDiet such as monounsaturated fatty acids, antioxidant vitamins and phytochemicals. However, the underlying mechanisms remain unknown. Likewise, little is known about the genes that define inter-individual variation in response to the MedDiet, although the TCF7L2 gene is emerging as an illustrative candidate for determining relative risk of cardiovascular events in response to the MedDiet. Moreover, omics technologies are providing evidence supporting potential mechanisms, some of them implicating epigenetics (i.e. microRNAs, methylation), and certain data suggest that some traditional foods could contribute via microRNAs possibly acting as exogenous regulators of gene expression. Future research should aim at increasing and consolidating the nutrigenetic and nutrigenomic knowledge of the MedDiet in order to provide sound, personalized and optimized nutritional recommendations.

Quantifying diet for nutrigenomic studies

The field of nutrigenomics shows tremendous promise for improved understanding of the effects of dietary intake on health. The knowledge that metabolic pathways may be altered in individuals with genetic variants in the presence of certain dietary exposures offers great potential for personalized nutrition advice. However, although considerable resources have gone into improving technology for measurement of the genome and biological systems, dietary intake assessment remains inadequate. Each of the methods currently used has limitations that may be exaggerated in the context of gene × nutrient interaction in large multiethnic studies. Because of the specificity of most gene × nutrient interactions, valid data are needed for nutrient intakes at the individual level. Most statistical adjustment efforts are designed to improve estimates of nutrient intake distributions in populations and are unlikely to solve this problem. An improved method of direct measurement of individual usual dietary intake that is unbiased across populations is urgently needed.