CETP genotype and changes in lipid levels in response to weight-loss diet intervention in the POUNDS LOST and DIRECT randomized trials

Cholesteryl Ester Transfer Protein (CETP) Variations in Relation to Lipid Profiles and Cardiovascular Diseases: An Update

Lipid metabolism plays an essential role in the pathogenesis of cardiovascular and metabolic diseases. Cholesteryl ester transfer protein (CETP) is a crucial glycoprotein involved in lipid metabolism by transferring cholesteryl esters (CE) and triglycerides (TG) between plasma lipoproteins. CETP activity results in reduced HDL-C and increased VLDL- and LDL-C concentrations, thus increasing the risk of cardiovascular and metabolic diseases. In this review, we discuss the structure of CETP and its mechanism of action. Furthermore, we focus on recent experiments on animal CETP-expressing models, deciphering the regulation and functions of CETP in various genetic backgrounds and interaction with different external factors. Finally, we discuss recent publications revealing the association of CETP single nucleotide polymorphisms (SNPs) with the risk of cardiovascular and metabolic diseases, lifestyle factors, diet and therapeutic interventions. While CETP SNPs can be used as effective diagnostic markers, diet, lifestyle, gender and ethnic specificity should also be considered for effective treatment.

Triangulating nutrigenomics, metabolomics and microbiomics toward personalized nutrition and healthy living

The unique physiological and genetic characteristics of individuals influence their reactions to different dietary constituents and nutrients. This notion is the foundation of personalized nutrition. The field of nutrigenetics has witnessed significant progress in understanding the impact of genetic variants on macronutrient and micronutrient levels and the individual's responsiveness to dietary intake. These variants hold significant value in facilitating the development of personalized nutritional interventions, thereby enabling the effective translation from conventional dietary guidelines to genome-guided nutrition. Nevertheless, certain obstacles could impede the extensive implementation of individualized nutrition, which is still in its infancy, such as the polygenic nature of nutrition-related pathologies. Consequently, many disorders are susceptible to the collective influence of multiple genes and environmental interplay, wherein each gene exerts a moderate to modest effect. Furthermore, it is widely accepted that diseases emerge because of the intricate interplay between genetic predisposition and external environmental influences. In the context of this specific paradigm, the utilization of advanced "omic" technologies, including epigenomics, transcriptomics, proteomics, metabolomics, and microbiome analysis, in conjunction with comprehensive phenotyping, has the potential to unveil hitherto undisclosed hereditary elements and interactions between genes and the environment. This review aims to provide up-to-date information regarding the fundamentals of personalized nutrition, specifically emphasizing the complex triangulation interplay among microbiota, dietary metabolites, and genes. Furthermore, it highlights the intestinal microbiota's unique makeup, its influence on nutrigenomics, and the tailoring of dietary suggestions. Finally, this article provides an overview of genotyping versus microbiomics, focusing on investigating the potential applications of this knowledge in the context of tailored dietary plans that aim to improve human well-being and overall health.

CETP and APOA2 polymorphisms are associated with weight loss and healthy eating behavior changes in response to digital lifestyle modifications

Response to digital healthcare lifestyle modifications is highly divergent. This study aimed to examine the association between single nucleotide polymorphism (SNP) genotypes and clinical efficacy of a digital healthcare lifestyle modification. We genotyped 97 obesity-related SNPs from 45 participants aged 18-39 years, who underwent lifestyle modification via digital cognitive behavioral therapy for obesity for 8 weeks. Anthropometric, eating behavior phenotypes, and psychological measures were analyzed before and after the intervention to identify their clinical efficacy. CETP (rs9939224) SNP significantly predict "super-responders" with greater body mass index (BMI) reduction (p = 0.028; GG - 2.91%, GT - 9.94%), while APOA2 (rs5082) appeared to have some potential for predicting "poor-responders" with lower BMI reduction (p = 0.005; AA - 6.17%, AG + 2.05%, and GG + 5.11%). These SNPs was also associated with significant differences in eating behavior changes, healthy diet proportions, health diet diversity, emotional and restrained eating behavior changes. Furthermore, classification using gene-gene interactions between rs9939224 and rs5082 significantly predicted the best response, with a greater decrease in BMI (p = 0.038; - 11.45% for the best response group (CEPT GT/TT × APOA2 AA) vs. + 2.62% for the worst response group (CEPT GG × APOA2 AG/GG)). CETP and APOA2 SNPs can be used as candidate markers to predict the efficacy of digital healthcare lifestyle modifications based on genotype-based precision medicine.Trial registration: NCT03465306, ClinicalTrials.gov. Registered March, 2018.

Toward Precision Weight-Loss Dietary Interventions: Findings from the POUNDS Lost Trial

The POUNDS Lost trial is a 2-year clinical trial testing the effects of dietary interventions on weight loss. This study included 811 adults with overweight or obesity who were randomized to one of four diets that contained either 15% or 25% protein and 20% or 40% fat in a 2 × 2 factorial design. By 2 years, participants on average lost from 2.9 to 3.6 kg in body weight in the four intervention arms, while no significant difference was observed across the intervention arms. In POUNDS Lost, we performed a series of ancillary studies to detect intrinsic factors particular to genomic, epigenomic, and metabolomic markers that may modulate changes in weight and other cardiometabolic traits in response to the weight-loss dietary interventions. Genomic variants identified from genome-wide association studies (GWASs) on obesity, type 2 diabetes, glucose and lipid metabolisms, gut microbiome, and dietary intakes have been found to interact with dietary macronutrients (fat, protein, and carbohydrates) in relation to weight loss and changes of body composition and cardiometabolic traits. In addition, we recently investigated epigenomic modifications, particularly blood DNA methylation and circulating microRNAs (miRNAs). We reported DNA methylation levels at NFATC2IP, CPT1A, TXNIP, and LINC00319 were related to weight loss or changes of glucose, lipids, and blood pressure; we also reported thrifty miRNA expression as a significant epigenomic marker related to changes in insulin sensitivity and adiposity. Our studies have also highlighted the importance of temporal changes in novel metabolomic signatures for gut microbiota, bile acids, and amino acids as predictors for achievement of successful weight loss outcomes. Moreover, our studies indicate that biochemical, behavioral, and psychosocial factors such as physical activity, sleep disturbance, and appetite may also modulate metabolic changes during dietary interventions. This review summarized our major findings in the POUNDS Lost trial, which provided preliminary evidence supporting the development of precision diet interventions for obesity management.

DNA Methylation Near CPT1A and Changes in Triglyceride-rich Lipoproteins in Response to Weight-loss Diet Interventions

CONTEXT

Carnitine palmitoyltransferase-1A, encoded by the CPT1A gene, plays a key role in the oxidation of long-chain fatty acids in the mitochondria and may be important in triglyceride metabolism. Previous work has shown that high fat intake was negatively associated with CPT1A methylation and positively associated with CPT1A expression.

OBJECTIVE

We aim to investigate the association of DNA methylation (DNAm) at the CPT1A gene with reductions in triglycerides and triglyceride-rich lipoproteins (TRLs) in response to weight-loss diet interventions.

METHODS

The current study included 538 White participants, who were randomly assigned to 1 of 4 diets varying in macronutrient components. We defined the regional DNAm at CPT1A as the average methylation level over CpGs within 500 bp of the 3 triglyceride-related DNAm sites.

RESULTS

Dietary fat intake significantly modified the association between baseline DNAm at CPT1A and 2-year changes in total plasma triglycerides, independent of concurrent weight loss. Among participants assigned to a low-fat diet, a higher regional DNAm level at CPT1A was associated with a greater reduction in total plasma triglycerides at 2 years (P = .01), compared with those assigned to a high-fat diet (P = .64) (P interaction = .018). Further investigation on lipids and apolipoproteins in very low-density lipoprotein (VLDL) revealed similar interaction patterns for 2-year changes in VLDL-triglycerides, VLDL-cholesterol, and VLDL-apolipoprotein B (P interaction = .009, .002, and .016, respectively), but not for VLDL-apoC-III (P interaction = .36).

CONCLUSION

Participants with a higher regional DNAm level at CPT1A benefit more in long-term improvement in triglycerides, particularly in the TRLs and related apolipoproteins when consuming a low-fat weight-loss diet.

Dietary acid load and its interaction with CETP TaqB1 polymorphisms on lipid profile among patients with Type 2 diabetes mellitus

OBJECTIVE

Gene-diet interaction plays a key role in the inter-individual differences in lipid abnormalities as a major risk factor for cardiovascular diseases (CVDs). Thus, we explored the interaction between CETP TaqB1 polymorphism with dietary acid load (DAL) on lipid profile among type 2 diabetes mellitus (T2DM).

METHOD

This cross-sectional study conducted on 220 Iranian patients with T2DM. Dietary acid load (PRAL and NEAP) was calculated via a validated food-frequency questionnaire (FFQ). The polymerase chain reaction (PCR) used for genotyping Taq1B polymorphism. Biochemical markers were measured by standard protocol. The interaction between CETP Taq1B polymorphism and DAL (PRAL and NEAP) on lipid profile was performed by a generalized linear regression model (GLM).

RESULTS

The overall prevalence of rs708272 genotypes was 8.6%, 72.7% and 18.6% for B1B1, B1B2 and B2B2 genotype respectively. This study showed that people with the B1B1 genotype had greater LDL, TC, LDL/HDL, and TG when they consumed diets that scored higher on the NEAP and PRAL indexes than those with the B1B2 and B2B2 genotypes. Besides, carriers of the B1B1 allele who were in the highest tertile of NEAP, had lower HDL (P Interaction < 0.05).

CONCLUSIONS

In summary, the lipid profile might be improved in B1B1 homozygotes by less adherence to DAL indexes, however, the findings should be validated in high-quality interventional studies.

Nutrition for precision health: The time is now

Precision nutrition has emerged as a boiling area of nutrition research, with a particular focus on revealing the individual variability in response to diets that is determined mainly by the complex interactions of dietary factors with the multi-tiered "omics" makeups. Reproducible findings from the observational studies and diet intervention trials have lent preliminary but consistent evidence to support the fundamental role of gene-diet interactions in determining the individual variability in health outcomes including obesity and weight loss. Recent investigations suggest that the abundance and diversity of the gut microbiome may also modify the dietary effects; however, considerable instability in the results from the microbiome research has been noted. In addition, growing studies suggest that a complicated multiomics algorithm would be developed by incorporating the genome, epigenome, metabolome, proteome, and microbiome in predicting the individual variability in response to diets. Moreover, precision nutrition would also scrutinize the role of biological (circadian) rhythm in determining the individual variability of dietary effects. The evidence gathered from precision nutrition research will be the basis for constructing precision health dietary recommendations, which hold great promise to help individuals and their health care providers create precise and effective diet plans for precision health in the future.

A Nutrigenetic Update on CETP Gene–Diet Interactions on Lipid-Related Outcomes

Purpose of Review

An abnormal lipid profile is considered a main risk factor for cardiovascular diseases and evidence suggests that single nucleotide polymorphisms (SNPs) in the cholesteryl ester transfer protein (CETP) gene contribute to variations in lipid levels in response to dietary intake. The objective of this review was to identify and discuss nutrigenetic studies assessing the interactions between CETP SNPs and dietary factors on blood lipids.

Recent Findings

Relevant articles were obtained through a literature search of PubMed and Google Scholar through to July 2021. An article was included if it examined an interaction between CETP SNPs and dietary factors on blood lipids. From 49 eligible nutrigenetic studies, 27 studies reported significant interactions between 8 CETP SNPs and 17 dietary factors on blood lipids in 18 ethnicities. The discrepancies in the study findings could be attributed to genetic heterogeneity, and differences in sample size, study design, lifestyle and measurement of dietary intake. The most extensively studied ethnicities were those of Caucasian populations and majority of the studies reported an interaction with dietary fat intake. The rs708272 (TaqIB) was the most widely studied CETP SNP, where ‘B1’ allele was associated with higher CETP activity, resulting in lower high-density lipoprotein cholesterol and higher serum triglycerides under the influence of high dietary fat intake.

Summary

Overall, the findings suggest that CETP SNPs might alter blood lipid profiles by modifying responses to diet, but further large studies in multiple ethnic groups are warranted to identify individuals at risk of adverse lipid response to diet.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11883-022-00987-y.

Personalized Nutrition and -Omics

With change in global concern toward food quality over food quantity, consumer concern and choice of healthy food has become a matter of prime importance. It gave rise to concept of “personalized or precision nutrition”. The theory behind personalization of nutrition is supported by multiple factors including advances in food analytics, nutrition based diseases and public health programs, increasing use of information technology in nutrition science, concept of gene-diet interaction and growing consumer capacity or concern by better and healthy foods. The advances in “omics” tools and related analytical techniques have resulted into tremendous scope of their application in nutrition science. As a consequence, a better understanding of underlying interaction between diet and individual is expected with addressing of key challenges for successful implementation of this science. In this chapter, the above aspects are discussed to get an insight into driving factors for increasing concern in personalized nutrition.

Genetic test for the prescription of diets in support of physical activity

Owing to the fields of nutrigenetics and nutrigenomics today we can think of devising approaches to optimize health, delay onset of diseases and reduce its severity according to our genetic blue print. However this requires a deep understanding of nutritional impact on expression of genes that may result in a specific phenotype. The extensive research and observational studies during last two decades reporting interactions between genes, diet and physical activity suggest a cross talk between various genetic and environmental factors and lifestyle interventions. Although considerable efforts have been made in unraveling the mechanisms of gene-diet interactions the scientific evidences behind developing commercial genetic tests for providing personalized nutrition recommendations are still scarce. In this scenario the current mini-review aims to provide useful insights into salient feature of nutrition based genetic research and its commercial application and the ethical issue and concerns related to its outcome.

Associations between Genotype-Diet Interactions and Weight Loss-A Systematic Review

Studies on the interactions between single nucleotide polymorphisms (SNPs) and macronutrient consumption on weight loss are rare and heterogeneous. This review aimed to conduct a systematic literature search to investigate genotype–diet interactions on weight loss. Four databases were searched with keywords on genetics, nutrition, and weight loss (PROSPERO: CRD42019139571). Articles in languages other than English and trials investigating special groups (e.g., pregnant women, people with severe diseases) were excluded. In total, 20,542 articles were identified, and, after removal of duplicates and further screening steps, 27 articles were included. Eligible articles were based on eight trials with 91 SNPs in 63 genetic loci. All articles examined the interaction between genotype and macronutrients (carbohydrates, fat, protein) on the extent of weight loss. However, in most cases, the interaction results were not significant and represented single findings that lack replication. The publications most frequently analyzed genotype–fat intake interaction on weight loss. Since the majority of interactions were not significant and not replicated, a final evaluation of the genotype–diet interactions on weight loss was not possible. In conclusion, no evidence was found that genotype–diet interaction is a main determinant of obesity treatment success, but this needs to be addressed in future studies.

Nutrigenetics-personalized nutrition in obesity and cardiovascular diseases

Epidemiological data support the view that both obesity and cardiovascular diseases (CVD) account for a high proportion of total morbidity and mortality in adults throughout the world. Obesity and CVD have complex interplay mechanisms of genetic and environmental factors, including diet. Nutrition is an environmental factor and it has a predominant and recognizable role in health management and in the prevention of obesity and obesity-related diseases, including CVD. However, there is a marked variation in CVD in patients with obesity and the same dietary pattern. The different genetic polymorphisms could explain this variation, which leads to the emergence of the concept of nutrigenetics. Nutritional genomics or nutrigenetics is the science that studies and characterizes gene variants associated with differential response to specific nutrients and relating this variation to various diseases, such as CVD related to obesity. Thus, the personalized nutrition recommendations, based on the knowledge of an individual's genetic background, might improve the outcomes of a specific dietary intervention and represent a new dietary approach to improve health, reducing obesity and CVD. Given these premises, it is intuitive to suppose that the elucidation of diet and gene interactions could support more specific and effective dietary interventions in both obesity and CVD prevention through personalized nutrition based on nutrigenetics. This review aims to briefly summarize the role of the most important genes associated with obesity and CVD and to clarify the knowledge about the relation between nutrition and gene expression and the role of the main nutrition-related genes in obesity and CVD.

Effects of total fat intake on body fatness in adults

BACKGROUND

The ideal proportion of energy from fat in our food and its relation to body weight is not clear. In order to prevent overweight and obesity in the general population, we need to understand the relationship between the proportion of energy from fat and resulting weight and body fatness in the general population.

OBJECTIVES

To assess the effects of proportion of energy intake from fat on measures of body fatness (including body weight, waist circumference, percentage body fat and body mass index) in people not aiming to lose weight, using all appropriate randomised controlled trials (RCTs) of at least six months duration.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, Clinicaltrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP) to October 2019. We did not limit the search by language.

SELECTION CRITERIA

Trials fulfilled the following criteria: 1) randomised intervention trial, 2) included adults aged at least 18 years, 3) randomised to a lower fat versus higher fat diet, without the intention to reduce weight in any participants, 4) not multifactorial and 5) assessed a measure of weight or body fatness after at least six months. We duplicated inclusion decisions and resolved disagreement by discussion or referral to a third party.

DATA COLLECTION AND ANALYSIS

We extracted data on the population, intervention, control and outcome measures in duplicate. We extracted measures of body fatness (body weight, BMI, percentage body fat and waist circumference) independently in duplicate at all available time points. We performed random-effects meta-analyses, meta-regression, subgrouping, sensitivity, funnel plot analyses and GRADE assessment.

MAIN RESULTS

We included 37 RCTs (57,079 participants). There is consistent high-quality evidence from RCTs that reducing total fat intake results in small reductions in body fatness; this was seen in almost all included studies and was highly resistant to sensitivity analyses (GRADE high-consistency evidence, not downgraded). The effect of eating less fat (compared with higher fat intake) is a mean body weight reduction of 1.4 kg (95% confidence interval (CI) -1.7 to -1.1 kg, in 53,875 participants from 26 RCTs, I² = 75%). The heterogeneity was explained in subgrouping and meta-regression. These suggested that greater weight loss results from greater fat reductions in people with lower fat intake at baseline, and people with higher body mass index (BMI) at baseline. The size of the effect on weight does not alter over time and is mirrored by reductions in BMI (MD -0.5 kg/m², 95% CI -0.6 to -0.3, 46,539 participants in 14 trials, I² = 21%), waist circumference (MD -0.5 cm, 95% CI -0.7 to -0.2, 16,620 participants in 3 trials; I² = 21%), and percentage body fat (MD -0.3% body fat, 95% CI -0.6 to 0.00, P = 0.05, in 2350 participants in 2 trials; I² = 0%). There was no suggestion of harms associated with low fat diets that might mitigate any benefits on body fatness. The reduction in body weight was reflected in small reductions in LDL (-0.13 mmol/L, 95% CI -0.21 to -0.05), and total cholesterol (-0.23 mmol/L, 95% CI -0.32 to -0.14), with little or no effect on HDL cholesterol (-0.02 mmol/L, 95% CI -0.03 to 0.00), triglycerides (0.01 mmol/L, 95% CI -0.05 to 0.07), systolic (-0.75 mmHg, 95% CI -1.42 to -0.07) or diastolic blood pressure(-0.52 mmHg, 95% CI -0.95 to -0.09), all GRADE high-consistency evidence or quality of life (0.04, 95% CI 0.01 to 0.07, on a scale of 0 to 10, GRADE low-consistency evidence).

AUTHORS' CONCLUSIONS

Trials where participants were randomised to a lower fat intake versus a higher fat intake, but with no intention to reduce weight, showed a consistent, stable but small effect of low fat intake on body fatness: slightly lower weight, BMI, waist circumference and percentage body fat compared with higher fat arms. Greater fat reduction, lower baseline fat intake and higher baseline BMI were all associated with greater reductions in weight. There was no evidence of harm to serum lipids, blood pressure or quality of life, but rather of small benefits or no effect.

Lessons Learned from the POUNDS Lost Study: Genetic, Metabolic, and Behavioral Factors Affecting Changes in Body Weight, Body Composition, and Cardiometabolic Risk

PURPOSE OF REVIEW

This paper reviews the genetic and non-genetic factors that provided predictions of, or were associated with, weight loss and other metabolic changes in the POUNDS Lost clinical trial of weight loss. This trial randomized 811 individuals who were overweight or obese to one of four diets that contained either 15% or 25% protein and 20% or 40% fat in a 2 × 2 factorial design. A standard behavioral weight loss program was available for all participants who were followed for 2 years with an 80% completion rate.

RECENT FINDINGS

Nineteen genes and five genetic risk scores were used along with demographic, behavioral, endocrine, and metabolic measurements. Genetic variations in most of the genes were associated with weight loss, but this association often varied with the dietary assignment. A number of demographic and behavioral factors, including attendance at behavioral sessions and food cravings were predictive of weight changes. A high baseline level of free triiodothyronine or free thyroxine predicted the magnitude of weight loss. Several perfluoroakyl compounds predicted more rapid weight regain. Genetic evidence from POUNDS Lost provides guidance toward selection of a personalized weight loss diet and improvement in metabolic profile. There is still room for additional research into the predictors of weight loss.

The interaction of cholesteryl ester transfer protein gene variations and diet on changes in serum lipid profiles

BACKGROUND/OBJECTIVES

Gene-diet interactions may have an important role in the disparities between the lipid responses of individuals to diet. This study aimed to investigate whether polymorphisms (rs5882 and rs3764261) in the cholesteryl ester transfer protein (CETP) gene modify the association of diet with changes in serum lipid profiles.

SUBJECTS/METHODS

A total of 4700 individuals aged ≥18 years were selected from among participants of the Tehran Lipid and Glucose Study. After 3.6 years of follow-up, changes in serum lipid profiles were evaluated. Usual dietary intake was assessed using a validated food frequency questionnaire. DNA samples were genotyped with HumanOmniExpress-24-v1-0 bead chips (containing 649,932 SNP loci).

RESULTS

No significant interaction was found between CETP polymorphisms and dietary patterns in changing lipid profiles. Mean changes of total cholesterol (TC) decreased in higher quartiles of fish intake in A allele carriers (Q1:8.02, Q4:5.58, P_trend = 0.01) compared to the CC genotype (Q1:3.65, Q4:8.93, P_trend = 0.11) (P_i = 0.02). There are ascending trends of changes in triglyceride (TG) concentrations across quartiles of total fat, monounsaturated and saturated fat consumption in G allele carriers of rs5882 compared to the AA genotype. There was a declining trend for mean changes in TG concentrations across quartiles of carbohydrate intake in G allele carriers of rs5882 compared to the AA genotype (P_i = 0.01).

CONCLUSIONS

Our data demonstrated that minor allele carriers of rs5882 had a better TG value than AA homozygote individuals when consuming a low fat and high carbohydrate diet. Fish intake modifies the association of rs3764261with TC concentrations.

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.

Cholesteryl ester transfer protein gene variations and macronutrient intakes interaction in relation to metabolic syndrome: Tehran lipid and glucose study

Objective(s):

There are controversial results regarding the effect of the interaction of CETP polymorphisms with dietary fats on the lipid profiles. The aim of this study was to examine the effect of CETP polymorphisms (rs5882 and rs3764261) and macronutrient intakes interaction in relation to metabolic syndrome (MetS) or its components.

Materials and Methods:

In this nested case-control study, subjects were selected from among participants of the Tehran Lipid and Glucose Study. Cases (n=441) were individually matched with two controls (844 non-MetS subjects). DNA samples were genotyped with HumanOmniExpress-24-v1-0 bead chips, including 649,932 SNP loci.

Results:

The mean ages at baseline were 38.1±10 and 37.0±10 years in women and 36.2±11 and 36.3±11 years in men, respectively in cases and controls. We did not find significant gene-diet interactions between rs5882 and dietary macronutrient intakes in relation to MetS risk. The risk of low HDL-C was lower in the first quartile of MUFA and total fat intake in G allele carriers, compared to AA genotype group. The risk of high BP appeared to increase significantly in higher quartiles of trans-fatty acid intakes (>1.81% of total energy intake) in G allele carriers compared with the AA genotype group. No significant interactions were found between rs3764261 and macronutrient intakes in association with MetS or its components.

Conclusion:

Our findings demonstrate that dietary fats modify the association of rs5882 and risk of low HDL-C and high blood pressure.

Diet in patients with metabolic syndrome: What is the ideal macronutrient composition?

Metabolic syndrome is currently a worldwide epidemic. First-line interventions consist of profound changes in lifestyle, particularly in diet, for which moderate and balanced consumption of macronutrients associated with calorie restriction is recommended. However, in recent years, several studies have proposed that diets that restrict certain macronutrients even further may be better for controlling both weight and metabolic risk factors. In the present paper, we review the currently available evidence on this question, which is difficult to address and control in clinical practice.

Genetic variations of cholesteryl ester transfer protein and diet interactions in relation to lipid profiles and coronary heart disease: a systematic review

Data on diet–genotype interactions in the prevention or treatment of dyslipidemia have increased remarkably. This systematic review aimed to assess nutrigenetic studies regarding the modulating effect of diet on cholesteryl ester transfer protein (CETP) polymorphisms in relation to metabolic traits.

Data were collected through studies published between 2000 and SEP. 2016 using five electronic databases. The quality of eligible studies was assessed using a 12-item quality checklist, derived from the STrengthening the REporting of Genetic Association Studies (STREGA) statement. CETP variants that had associations with lipid profiles in previous studies were extracted for drawing of the linkage disequilibrium (LD) plot.

Among CETP variants, the rs9989419 best represented this genome wide association signal across all populations, based on LD r² estimates from 1000 genomes references. In the 23 found eligible studies (clinical trials and observational), the TaqIB and I405V polymorphisms were the two most intensively studied. Two studies reported the effect of interaction between rs3764261 and diet on lipid levels. Regarding the rs708272 (Taq1B), individuals with the B1 risk allele showed better responses to dietary interventions than those with B2B2 genotype, whereas with I405V, inconsistent results have been reported. Modest alcohol consumption was associated with decreased risk of coronary heart disease among B2 carriers of rs708272.

It is concluded that variations in the CETP gene may modulate the effects of dietary components on metabolic traits. These results have been controversial, indicating complex polygenic factors in metabolic response to diet and lack of uniformity in the study conditions and designs.

Guide for Current Nutrigenetic, Nutrigenomic, and Nutriepigenetic Approaches for Precision Nutrition Involving the Prevention and Management of Chronic Diseases Associated with Obesity

Chronic diseases, including obesity, are major causes of morbidity and mortality in most countries. The adverse impacts of obesity and associated comorbidities on health remain a major concern due to the lack of effective interventions for prevention and management. Precision nutrition is an emerging therapeutic approach that takes into account an individual's genetic and epigenetic information, as well as age, gender, or particular physiopathological status. Advances in genomic sciences are contributing to a better understanding of the role of genetic variants and epigenetic signatures as well as gene expression patterns in the development of diverse chronic conditions, and how they may modify therapeutic responses. This knowledge has led to the search for genetic and epigenetic biomarkers to predict the risk of developing chronic diseases and personalizing their prevention and treatment. Additionally, original nutritional interventions based on nutrients and bioactive dietary compounds that can modify epigenetic marks and gene expression have been implemented. Although caution must be exercised, these scientific insights are paving the way for the design of innovative strategies for the control of chronic diseases accompanying obesity. This document provides a number of examples of the huge potential of understanding nutrigenetic, nutrigenomic, and nutriepigenetic roles in precision nutrition.

Markers of dietary protein intake are associated with successful weight loss in the POUNDS Lost trial

To assess the association of markers for dietary protein intake, measures of dietary adherence and demographic variables with weight loss in the POUNDS Lost study over the first 6 months and again between 6 and 24 months using data from those who completed each period. This is a secondary analysis of pooled data on completers assigned to one of four diets: 65%C/15%P/20%F (AP/LF), 55%C/25%P/20%F (HP/LF), 45%C/15%P/40%F (AP/HF) or 35%C/25%P40%F (HP/HF) in the POUNDS Lost study. Urinary nitrogen excretion, dietary adherence measured by 24-h recall and attendance at sessions, age (above and below 50 years), gender, race/ethnicity and activity by pedometry were analysed. Increased spread between protein intake at baseline and protein at 6 or 24 months, assessed by urinary nitrogen excretion, was associated with greater weight loss from baseline to 2 years. At 6 and 24 months, older age, male gender, body mass index > 30 kg m-2 and adherence to the fat and protein diets were associated with more weight loss. None of these variables was associated with a regain from 6 to 24 months. Weight regain for women in the highest carbohydrate (65%) group was significantly greater (-4.4 kg [95% CI: -5.9, -3.0]) than for women in the lowest carbohydrate group (-1.8 kg [95% CI: -3.2, -0.4 kg]) (P for interaction = 0.012). An increased spread in the difference between baseline and follow-up protein intake was associated with greater weight loss, consistent with the 'protein spread theory'. Women eating the highest carbohydrate diet regained more weight from 6 to 24 months.

Gene-Diet Interaction and Precision Nutrition in Obesity

The rapid rise of obesity during the past decades has coincided with a profound shift of our living environment, including unhealthy dietary patterns, a sedentary lifestyle, and physical inactivity. Genetic predisposition to obesity may have interacted with such an obesogenic environment in determining the obesity epidemic. Growing studies have found that changes in adiposity and metabolic response to low-calorie weight loss diets might be modified by genetic variants related to obesity, metabolic status and preference to nutrients. This review summarized data from recent studies of gene-diet interactions, and discussed integration of research of metabolomics and gut microbiome, as well as potential application of the findings in precision nutrition.

Phenotypic factors influencing the variation in response of circulating cholesterol level to personalised dietary advice in the Food4Me study

Individual response to dietary interventions can be highly variable. The phenotypic characteristics of those who will respond positively to personalised dietary advice are largely unknown. The objective of this study was to compare the phenotypic profiles of differential responders to personalised dietary intervention, with a focus on total circulating cholesterol. Subjects from the Food4Me multi-centre study were classified as responders or non-responders to dietary advice on the basis of the change in cholesterol level from baseline to month 6, with lower and upper quartiles defined as responder and non-responder groups, respectively. There were no significant differences between demographic and anthropometric profiles of the groups. Furthermore, with the exception of alcohol, there was no significant difference in reported dietary intake, at baseline. However, there were marked differences in baseline fatty acid profiles. The responder group had significantly higher levels of stearic acid (18 : 0, P=0·034) and lower levels of palmitic acid (16 : 0, P=0·009). Total MUFA (P=0·016) and total PUFA (P=0·008) also differed between the groups. In a step-wise logistic regression model, age, baseline total cholesterol, glucose, five fatty acids and alcohol intakes were selected as factors that successfully discriminated responders from non-responders, with sensitivity of 82 % and specificity of 83 %. The successful delivery of personalised dietary advice may depend on our ability to identify phenotypes that are responsive. The results demonstrate the potential use of metabolic profiles in identifying response to an intervention and could play an important role in the development of precision nutrition.

Characterizing Blood Metabolomics Profiles Associated with Self-Reported Food Intakes in Female Twins

Using dietary biomarkers in nutritional epidemiological studies may better capture exposure and improve the level at which diet-disease associations can be established and explored. Here, we aimed to identify and evaluate reproducibility of novel biomarkers of reported habitual food intake using targeted and non-targeted metabolomic blood profiling in a large twin cohort. Reported intakes of 71 food groups, determined by FFQ, were assessed against 601 fasting blood metabolites in over 3500 adult female twins from the TwinsUK cohort. For each metabolite, linear regression analysis was undertaken in the discovery group (excluding MZ twin pairs discordant [≥1 SD apart] for food group intake) with each food group as a predictor adjusting for age, batch effects, BMI, family relatedness and multiple testing (1.17x10^-6 = 0.05/[71 food groups x 601 detected metabolites]). Significant results were then replicated (non-targeted: P<0.05; targeted: same direction) in the MZ discordant twin group and results from both analyses meta-analyzed. We identified and replicated 180 significant associations with 39 food groups (P<1.17x10^-6), overall consisting of 106 different metabolites (74 known and 32 unknown), including 73 novel associations. In particular we identified trans-4-hydroxyproline as a potential marker of red meat intake (0.075[0.009]; P = 1.08x10^-17), ergothioneine as a marker of mushroom consumption (0.181[0.019]; P = 5.93x10^-22), and three potential markers of fruit consumption (top association: apple and pears): including metabolites derived from gut bacterial transformation of phenolic compounds, 3-phenylpropionate (0.024[0.004]; P = 1.24x10^-8) and indolepropionate (0.026[0.004]; P = 2.39x10^-9), and threitol (0.033[0.003]; P = 1.69x10^-21). With the largest nutritional metabolomics dataset to date, we have identified 73 novel candidate biomarkers of food intake for potential use in nutritional epidemiological studies. We compiled our findings into the DietMetab database (http://www.twinsuk.ac.uk/dietmetab-data/), an online tool to investigate our top associations.

FTO genotype and weight loss in diet and lifestyle interventions: a systematic review and meta-analysis

BACKGROUND

Studies have suggested that the fat mass and obesity-associated (FTO) genotype is associated with individual variability in weight loss in response to diet/lifestyle interventions, but results are inconsistent.

OBJECTIVE

We aimed to provide a summary of the literature evaluating the relation between the FTO genotype and weight loss in response to diet/lifestyle interventions.

DESIGN

A search of English-language articles in the PubMed and Embase databases (through 30 April 2015) was performed. Eligible studies were diet/lifestyle weight-loss intervention studies conducted in adults that reported changes in body weight or body mass index (BMI) by the FTO variant rs9939609 (or its proxy). Differences in weight loss between FTO genotypes across studies were pooled with the use of fixed-effect models.

RESULTS

A meta-analysis of 10 studies (comprising 6951 participants) that reported the results of additive genetic models showed that individuals with the FTO TA genotype and AA genotype (those with the obesity-predisposing A allele) had 0.18-kg (95% CI: -0.09-, 0.45-kg;P= 0.19; NS) and 0.44-kg (95% CI: 0.09-, 0.79-kg;P= 0.015) greater weight loss, respectively, than those with the TT genotype. A meta-analysis of 14 studies (comprising 7700 participants) that reported the results of dominant genetic models indicated a 0.20-kg (-0.43-, 0.04-kg) greater weight loss in the TA/AA genotype than in the TT genotype (P= 0.10). In addition, differences in weight loss between the AA genotype and TT genotype were significant in studies with a diet intervention only, adjustment for baseline BMI or body weight, and several other subgroups. However, the relatively small number of studies limited these stratified analyses, and there was no statistically significant difference between subgroups.

CONCLUSIONS

This meta-analysis suggests that individuals carrying the homozygous FTO obesity-predisposing allele may lose more weight through diet/lifestyle interventions than noncarriers. Our data provide evidence for genetic variability in response to diet/lifestyle interventions on weight loss, although clinical applications of these findings need further investigations.