Gene-Diet Interaction and Precision Nutrition in Obesity

Dietary Fatty Acids and the Metabolic Syndrome: A Personalized Nutrition Approach

Dietary fatty acids are present in a wide variety of foods and appear in different forms and lengths. The different fatty acids are known to have various effects on metabolic health. The metabolic syndrome (MetS) is a constellation of risk factors of chronic diseases. The etiology of the MetS is represented by a complex interplay of genetic and environmental factors. Dietary fatty acids can be important contributors of the evolution or in prevention of the MetS; however, great interindividual variability exists in the response to fatty acids. The identification of genetic variants interacting with fatty acids might explain this heterogeneity in metabolic responses. This chapter reviews the mechanisms underlying the interactions between the different components of the MetS, dietary fatty acids and genes. Challenges surrounding the implementation of personalized nutrition are also covered.

Impact of Genes and Environment on Obesity and Cardiovascular Disease

Obesity and abdominal obesity have been closely related to cardiovascular outcomes, and recent evidence has indicated that environmental and genetic factors act in concert in determining the risks of these conditions. Improving adherence to healthy lifestyle habits and healthy dietary patterns can at least partly counteract genetic variations related to risks of obesity and cardiovascular disease (CVD). Other factors, such as epigenetic alterations, may also modulate a relationship between genetic susceptibility and these disorders. In this review, we highlight data from recent studies on gene and environmental risk factors for obesity and CVD, and describe how these findings might inform understanding of the complex roles of interactions between genes and environmental factors in the development of obesity and CVD.

Alignment of diet prescription to genotype does not promote greater weight loss success in women with obesity participating in an exercise and weight loss program

OBJECTIVE

Genetics contribute to variability in individual response to weight-loss interventions. The objective of this study was to determine the efficacy of a commercially available exercise and weight-loss program and whether alignment of diet to genotype related to lipid metabolism promotes greater success.

DESIGN

Sedentary women with obesity (n = 63) had genotype (FABP2rs1799883, PPARG2rs1801282, ADRB3rs4994C3, ADRB2rs1042713, rs1042714) determined using a direct-to-consumer genetic screening kit purported to promote greater weight-loss success through dietary recommendations based on these genes. Participants were randomly assigned to follow a moderate carbohydrate (MC) or lower carbohydrate (LC) hypo-energetic diet that aligned (A) or did not align (NA) with genotype for 24 weeks while participating in a resistance training and walking program. Data were analysed by general linear model repeated measures adjusted for baseline variables and are presented as mean (95% confidence interval) changes from baseline.

RESULTS

Participants in the LC group experienced greater improvements (p = 0.051, ηp 2 = 0.025) in per cent changes in body composition (weight: MC -3.32 [-1.4, -5.2], LC -5.82 [-4.1, -7.6]; fat mass: MC -7.25 [-3.2, -11.2], LC -10.93 [-7.3, -14.5]; fat-free mass: MC -0.32 [1.4, -2.0], LC -1.48 [0.7, -3.0]; and body fat percentage: MC -4.19 [-1.6, -6.8], LC -5.60 [-3.3, -7.9] %). No significant differences were observed between genotype groups (weight: A -5.00 [-3.3, -6.7], NA -4.14 [-2.2, -6.1]; fat mass: A -10.15 [-7.0, -13.6], NA -8.02 [-4.0, -12.0]; fat-free mass: A -1.23 [0.3, -2.8], NA -0.56 [1.12, -2.3]; and body fat: A -5.28 [-3.0, -7.6], NA -4.51 [-1.9, -7.1] %).

CONCLUSIONS

Adherence to this exercise and weight-loss program promoted improvements in body composition and health outcomes. While individuals following the LC diet experienced greater benefits, alignment of these diets to this genetic profile did not promote greater health outcomes.

Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight

Background and Aim

Individual lipid phenotypes including circulating total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), and triglycerides (TG) determinations are influenced by gene-environment interactions. The aim of this study was to predict blood lipid level (TC, LDL-c, HDL-c, and TG) variability using genetic and lifestyle data in subjects with excessive body weight-for-height.

Methods

This cross-sectional study enrolled 304 unrelated overweight/obese adults of self-reported European ancestry. A total of 95 single nucleotide polymorphisms (SNPs) related to obesity and weight loss were analyzed by a targeted next-generation sequencing system. Relevant genotypes of each SNP were coded as 0 (nonrisk) and 1 (risk). Four genetic risk scores (GRS) for each lipid phenotype were calculated by adding the risk genotypes. Information concerning lifestyle (diet, physical activity, alcohol drinking, and smoking) was obtained using validated questionnaires. Total body fat (TFAT) and visceral fat (VFAT) were determined by dual-energy X-ray absorptiometry.

Results

Overall, 45 obesity-related genetic variants were associated with some of the studied blood lipids. In addition to conventional factors (age, sex, dietary intakes, and alcohol consumption), the calculated GRS significantly contributed to explain their corresponding plasma lipid trait. Thus, HDL-c, TG, TC, and LDL-c serum concentrations were predicted by approximately 28% (optimism-corrected adj. R² = 0.28), 25% (optimism-corrected adj. R² = 0.25), 24% (optimism-corrected adj. R² = 0.24), and 21% (optimism-corrected adj. R²=0.21), respectively. Interestingly, GRS were the greatest contributors to TC (squared partial correlation (PC²) = 0.18) and LDL-c (PC² = 0.18) features. Likewise, VFAT and GRS had a higher impact on HDL-c (PC² = 0.09 and PC² = 0.06, respectively) and TG levels (PC² = 0.20 and PC² = 0.07, respectively) than the rest of variables.

Conclusions

Besides known lifestyle influences, some obesity-related genetic variants could help to predict blood lipid phenotypes.

Genotype-by-sex-by-diet interactions for nutritional preference, dietary consumption, and lipid deposition in a field cricket

Changes in feeding behaviour, especially the overconsumption of calories, has led to a rise in the rates of obesity, diabetes, and other associated disorders in humans and a range of animals inhabiting human-influenced environments. However, understanding the relative contribution of genes, the nutritional environment, and their interaction to dietary intake and lipid deposition in the sexes still remains a major challenge. By combining nutritional geometry with quantitative genetics, we determined the effect of genes, the nutritional environment, and their interaction on the total nutritional preference (TP), total diet eaten (TE), and lipid mass (LM) of male and female black field crickets (Teleogryllus commodus) fed one of four diet pairs (DPs) differing in the ratio of protein to carbohydrate and total nutritional content. We found abundant additive genetic variance for TP, TE, and LM in both sexes and across all four DPs, with significant genetic correlations between TE and TP and between TP and LM in males. We also found significant genotype-by-DP and genotype-by-sex-by-DP interactions for each trait and significant genotype-by-sex interactions for TE and LM. Complex interactions between genes, sex, and the nutritional environment, therefore, play an important role in nutrient regulation and lipid deposition in T. commodus. This finding may also help explain the increasing rate of obesity and the maintenance of sex differences in obesity observed across many animal species, including humans.

An integrated transcriptomic and epigenomic analysis identifies CD44 gene as a potential biomarker for weight loss within an energy-restricted program

PURPOSE

The interindividual variable response to weight-loss treatments requires the search for new predictive biomarkers for improving the success of weight-loss programs. The aim of this study is to identify novel genes that distinguish individual responses to a weight-loss dietary treatment by using the integrative analysis of mRNA expression and DNA methylation arrays.

METHODS

Subjects from Metabolic Syndrome Reduction in Navarra (RESMENA) project were classified as low (LR) or high (HR) responders depending on their weight loss. Transcriptomic (n = 24) and epigenomic (n = 47) patterns were determined by array-based genome-wide technologies in human white blood cells at the baseline of the treatment period. CD44 expression was validated by qRT-PCR and methylation degree of CpGs of the gene was validated by MassARRAY^® EpiTYPER™ in a subsample of 47 subjects. CD44 protein levels were measured by ELISA in human plasma.

RESULTS

Different expression and DNA methylation profiles were identified in LR in comparison to HR. The integrative analysis of both array data identified four genes: CD44, ITPR1, MTSS1 and FBXW5 that were differently methylated and expressed between groups. CD44 showed higher expression and lower DNA methylation levels in LR than in HR. Although differences in CD44 protein levels between LR and HR were not statistically significant, a positive association was observed between CD44 mRNA expression and protein levels.

CONCLUSIONS

In summary, the combination of a genome-wide methylation and expression array dataset can be a useful strategy to identify novel genes that might be considered as predictors of the dietary response. CD44 gene transcription and methylation may be a possible candidate biomarker for weight-loss prediction.

Replication of a Gene-Diet Interaction at CD36, NOS3 and PPARG in Response to Omega-3 Fatty Acid Supplements on Blood Lipids: A Double-Blind Randomized Controlled Trial

BACKGROUND

Modulation of genetic variants on the effect of omega-3 fatty acid supplements on blood lipids is still unclear.

METHODS

In a double-blind randomized controlled trial, 150 patients with type 2 diabetes (T2D) were randomized into omega-3 fatty acid group (n = 56 for fish oil and 44 for flaxseed oil) and control group (n = 50) for 180 days. All patients were genotyped for genetic variants at CD36 (rs1527483), NOS3 (rs1799983) and PPARG (rs1801282). Linear regression was used to examine the interaction between omega-3 fatty acid intervention and CD36, NOS3 or PPARG variants for blood lipids.

FINDINGS

Significant interaction with omega-3 fatty acid supplements was observed for CD36 on triglycerides (p-interaction = 0.042) and PPAGR on low-density lipoprotein-cholesterol (p-interaction = 0.02). We also found a significant interaction between change in erythrocyte phospholipid omega-3 fatty acid composition and NOS3 genotype on triglycerides (p-interaction = 0.042), total cholesterol (p-interaction = 0.013) and ratio of total cholesterol to high-density lipoprotein cholesterol (p-interaction = 0.015). The T2D patients of CD36-G allele, PPARG-G allele and NOS3-A allele tended to respond better to omega-3 fatty acids in improving lipid profiles. The interaction results of the omega-3 fatty acid group were mainly attributed to the fish oil supplements.

INTERPRETATION

This study suggests that T2D patients with different genotypes at CD36, NOS3 and PPARG respond differentially to intervention of omega-3 supplements in blood lipid profiles.

Dietary Polysaccharides in the Amelioration of Gut Microbiome Dysbiosis and Metabolic Diseases

The prevalence of metabolic diseases including obesity, diabetes, cardiovascular diseases, hypertension and cancer has evolved into a global epidemic over the last century. The rate of these disorders is continuously rising due to the lack of effective preventative and therapeutic strategies. This warrants for the development of novel strategies that could help in the prevention, treatment and/ or better management of such disorders. Although the complex pathophysiology of these metabolic diseases is one of the major hurdles in the development of preventive and/or therapeutic strategies, there are some factors that are or can speculated to be more effective to target than others. Recently, gut microbiome has emerged as one of the major contributing factors in metabolic diseases, and developing positive modulators of gut microbiota is being considered to be of significant interest. Natural non-digestible polysaccharides from plants and food sources are considered potent modulators of gut microbiome that can feed certain beneficial microbes in the gut. This has led to an increased interest in the isolation of novel bioactive polysaccharides from different plants and food sources and their application as functional components to modulate the gut microbiome composition to improve host's health including metabolism. Therefore, polysaccharides, as prebiotics components, are being speculated to confer positive effects in managing metabolic diseases like obesity and diabetes. In this review article, we summarize some of the most common polysaccharides from plants and food that impact metabolic health and discuss why and how these could be helpful in preventing or ameliorating metabolic diseases such as obesity, type 2 diabetes, hypertension and dyslipidemia.

Towards utilization of the human genome and microbiome for personalized nutrition

Generalized dietary and lifestyle guidelines have been formulated and published for decades now from a variety of relevant agencies in an attempt to guide people towards healthy choices. As the pandemic rise in metabolic diseases continues to increase, it has become clear that the one-fit-for-all diet approach does not work and that there is a significant variation in inter-individual responses to diet and lifestyle interventions. Recent technological advances have given an unprecedented insight into the sources of this variation, pointing towards our genome and microbiome as potentially and previously under-explored culprits contributing to individually unique dietary responses. Variations in our genome influence the bioavailability and metabolism of nutrients between individuals, while inter-individual compositional variation of commensal gut microbiota leads to different microbe functional potential, metabolite production and metabolism modulation. Quantifying and incorporating these factors into a comprehensive personalized nutrition approach may enable practitioners to rationally incorporate individual nutritional recommendations in combating the metabolic syndrome pandemic.

Precision Nutrition for Targeting Lipid Metabolism in Colorectal Cancer

Cancer is a multistage and multifactorial condition with genetic and environmental factors modulating tumorogenesis and disease progression. Nevertheless, cancer is preventable, as one third of cancer deaths could be avoided by modifying key risk factors. Nutrients can directly affect fundamental cellular processes and are considered among the most important risk factors in colorectal cancer (CRC). Red and processed meat, poultry consumption, fiber, and folate are the best-known diet components that interact with colorectal cancer susceptibility. In addition, the direct association of an unhealthy diet with obesity and dysbiosis opens new routes in the understanding of how daily diet nutrients could influence cancer prognosis. In the “omics” era, traditional nutrition has been naturally evolved to precision nutrition where technical developments have contributed to a more accurate discipline. In this sense, genomic and transcriptomic studies have been extensively used in precision nutrition approaches. However, the relation between CRC carcinogenesis and nutrition factors is more complex than originally expected. Together with classical diet-nutrition-related genes, nowadays, lipid-metabolism-related genes have acquired relevant interest in precision nutrition studies. Lipids regulate very diverse cellular processes from ATP synthesis and the activation of essential cell-signaling pathways to membrane organization and plasticity. Therefore, a wide range of tumorogenic steps can be influenced by lipid metabolism, both in primary tumours and distal metastasis. The extent to which genetic variants, together with the intake of specific dietary components, affect the risk of CRC is currently under investigation, and new therapeutic or preventive applications must be explored in CRC models. In this review, we will go in depth into the study of co-occurring events, which orchestrate CRC tumorogenesis and are essential for the evolution of precision nutrition paradigms. Likewise, we will discuss the application of precision nutrition approaches to target lipid metabolism in CRC.

Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome

The translation of the growing increase of findings emerging from basic nutritional science into meaningful and clinically relevant dietary advices represents nowadays one of the main challenges of clinical nutrition. From nutrigenomics to deep phenotyping, many factors need to be taken into account in designing personalized and unbiased nutritional solutions for individuals or population sub-groups. Likewise, a concerted effort among basic, clinical scientists and health professionals will be needed to establish a comprehensive framework allowing the implementation of these new findings at the population level. In a world characterized by an overwhelming increase in the prevalence of obesity and associated metabolic disturbances, such as type 2 diabetes and cardiovascular diseases, tailored nutrition prescription represents a promising approach for both the prevention and management of metabolic syndrome. This review aims to discuss recent works in the field of precision nutrition analyzing most relevant aspects affecting an individual response to lifestyle/nutritional interventions. Latest advances in the analysis and monitoring of dietary habits, food behaviors, physical activity/exercise and deep phenotyping will be discussed, as well as the relevance of novel applications of nutrigenomics, metabolomics and microbiota profiling. Recent findings in the development of precision nutrition are highlighted. Finally, results from published studies providing examples of new avenues to successfully implement innovative precision nutrition approaches will be reviewed.