TCF7L2 genetic variants modulate the effect of dietary fat intake on changes in body composition during a weight-loss intervention

Precision Nutrition Unveiled: Gene-Nutrient Interactions, Microbiota Dynamics, and Lifestyle Factors in Obesity Management

BACKGROUND

Obesity is a complex metabolic disorder that is associated with several diseases. Recently, precision nutrition (PN) has emerged as a tailored approach to provide individualised dietary recommendations.

AIM

This review discusses the major intrinsic and extrinsic components considered when applying PN during the management of obesity and common associated chronic conditions.

RESULTS

The review identified three main PN components: gene-nutrient interactions, intestinal microbiota, and lifestyle factors. Genetic makeup significantly contributes to inter-individual variations in dietary behaviours, with advanced genome sequencing and population genetics aiding in detecting gene variants associated with obesity. Additionally, PN-based host-microbiota evaluation emerges as an advanced therapeutic tool, impacting disease control and prevention. The gut microbiome's composition regulates diverse responses to nutritional recommendations. Several studies highlight PN's effectiveness in improving diet quality and enhancing adherence to physical activity among obese patients. PN is a key strategy for addressing obesity-related risk factors, encompassing dietary patterns, body weight, fat, blood lipids, glucose levels, and insulin resistance.

CONCLUSION

PN stands out as a feasible tool for effectively managing obesity, considering its ability to integrate genetic and lifestyle factors. The application of PN-based approaches not only improves current obesity conditions but also holds promise for preventing obesity and its associated complications in the long term.

A genomics perspective of personalized prevention and management of obesity

This review discusses the landscape of personalized prevention and management of obesity from a nutrigenetics perspective. Focusing on macronutrient tailoring, we discuss the impact of genetic variation on responses to carbohydrate, lipid, protein, and fiber consumption. Our bioinformatic analysis of genomic variants guiding macronutrient intake revealed enrichment of pathways associated with circadian rhythm, melatonin metabolism, cholesterol and lipoprotein remodeling and PPAR signaling as potential targets of macronutrients for the management of obesity in relevant genetic backgrounds. Notably, our data-based in silico predictions suggest the potential of repurposing the SYK inhibitor fostamatinib for obesity treatment in relevant genetic profiles. In addition to dietary considerations, we address genetic variations guiding lifestyle changes in weight management, including exercise and chrononutrition. Finally, we emphasize the need for a refined understanding and expanded research into the complex genetic landscape underlying obesity and its management.

Specific Genotypes Associated with Differences in Fasting Insulin Levels and Body Mass Index in Healthy Young Males: Implications for Gene-Nutrient Interactions-an Exploratory Study

Background

Genetic variation may significantly impact an individual's susceptibility to diseases, particularly when combined with specific nutrients. Additionally, genetic variations can lead to interindividual differences in metabolic responses.

Objective

The present study explores the association between gene variants and observed interindividual differences in metabolic responses.

Methods

The study included 30 healthy males (aged 20-34) who underwent a fasting period and subsequently consumed a standardized meal. Blood samples were collected both before and after the meal to assess metabolic changes. BMI served as an indirect measure for assessing physiological responses associated with body composition. Appetite changes were assessed using an online Visual Analog 100-point Scale. Buccal swabs were collected to analyze genetic variants in single nucleotide polymorphisms (SNPs).

Results

The data underwent multiple regression analysis, revealing significant associations with 3 SNPs and their metabolic status: the insulin-receptor substrate 1 (IRS1) gene variant rs2943641, genotypes CT and CC, with elevated fasting insulin levels (R2 = 0.639, P = < 0.0001); the mitochondrial uncoupling protein 1 (UCP1) gene variant rs1800592, genotypes GG and GA, with increased BMI (R2 = 0.261, P = 0.007); and the peroxisome proliferator-activated receptor γ2 (PPARγ2) gene variant rs1801282, genotypes GG and GC, with increased BMI (R2 = 0.200, P = 0.024).

Conclusions

Therefore, our study established significant associations between these 3 SNPs and differences in fasting insulin levels and BMI within our cohort.

The Personalized Nutrition Study (POINTS): evaluation of a genetically informed weight loss approach, a Randomized Clinical Trial

Weight loss (WL) differences between isocaloric high-carbohydrate and high-fat diets are generally small; however, individual WL varies within diet groups. Genotype patterns may modify diet effects, with carbohydrate-responsive genotypes losing more weight on high-carbohydrate diets (and vice versa for fat-responsive genotypes). We investigated whether 12-week WL (kg, primary outcome) differs between genotype-concordant and genotype-discordant diets. In this 12-week single-center WL trial, 145 participants with overweight/obesity were identified a priori as fat-responders or carbohydrate-responders based on their combined genotypes at ten genetic variants and randomized to a high-fat (n = 73) or high-carbohydrate diet (n = 72), yielding 4 groups: (1) fat-responders receiving high-fat diet, (2) fat-responders receiving high-carbohydrate diet, (3) carbohydrate-responders receiving high-fat diet, (4) carbohydrate-responders receiving high-carbohydrate diet. Dietitians delivered the WL intervention via 12 weekly diet-specific small group sessions. Outcome assessors were blind to diet assignment and genotype patterns. We included 122 participants (54.4 [SD:13.2] years, BMI 34.9 [SD:5.1] kg/m2, 84% women) in the analyses. Twelve-week WL did not differ between the genotype-concordant (-5.3 kg [SD:1.0]) and genotype-discordant diets (-4.8 kg [SD:1.1]; adjusted difference: -0.6 kg [95% CI: -2.1,0.9], p = 0.50). With the current ability to genotype participants as fat- or carbohydrate-responders, evidence does not support greater WL on genotype-concordant diets. ClinicalTrials identifier: NCT04145466.

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.

Suppression of preadipocyte determination by SOX4 limits white adipocyte hyperplasia in obesity

Preadipocyte determination expanding the pool of preadipocytes is a vital process in adipocyte hyperplasia, but the molecular mechanisms underlying this process are yet to be elucidated. Herein, SRY-related HMG box transcription factor 4 (SOX4) was identified as a critical target in response to BMP4- and TGFβ-regulated preadipocyte determination. SOX4 deficiency is sufficient to promote preadipocyte determination in mesenchymal stem cells (MSCs) and acquisition of preadipocyte properties in nonadipogenic lineages, while its overexpression impairs the adipogenic capacity of preadipocytes and converts them into nonadipogenic lineages. Mechanism studies indicated that SOX4 activates and cooperates with LEF1 to retain the nuclear localization of β-catenin, thus mediating the crosstalk between TGFβ/BMP4 signaling pathway and Wnt signaling pathway to regulate the preadipocyte determination. In vivo studies demonstrated that SOX4 promotes the adipogenic-nonadipogenic conversion and suppresses the adipocyte hyperplasia. Together, our findings highlight the importance of SOX4 in regulating the adipocyte hyperplasia in obesity.

Knockout of ICAT in Adipose Tissue Alleviates Fibro-inflammation in Obese Mice

The E2 promoter binding factor 1 (E2F1) and the Wnt/β-catenin signaling are crucial in regulating metabolic homeostasis including obesity. The β-catenin interacting protein 1 (CTNNBIP1), also known as the inhibitor of β-catenin and TCF4 (ICAT), is required for E2F1 to inhibit the activity of β-catenin. However, the role of ICAT in E2F1 regulating obesity-related metabolic disorders remains unknown. In the present study, male adipose tissue-specific ICAT knockout (ICAT^adi-/-) C57BL/6 J mice and control littermates aged 6-8 weeks were fed with high-fat diet (HFD) for 12 weeks to explore the effect of ICAT on lipid metabolism and obesity-related disorders. Results showed that the adipose tissue-specific ICAT knockout had negligible effect on lipid metabolism, reflected by no difference in body weight, fat mass, and the expression of proteins involved in lipid metabolism in white adipose tissue (WAT) and the liver between the ICAT^adi-/- mice and the control littermate (ICAT^fl/fl) mice. However, the knockout of ICAT reduced inflammatory response in WAT and the liver. Additionally, Sirius red staining results showed that deletion of ICAT attenuated fibrosis and reduced mRNA levels of transforming growth factor β1(TGF-β1), matrix metallopeptidase 2 (Mmp2), Mmp3, and collagen, type V, alpha 1 (Col5a1) in WAT and the liver. These results suggested that knockout of ICAT improved the metabolic abnormalities of obese mice through attenuating adipose tissue and the liver inflammation as well as fibrosis. Our findings may provide a new insight to understand the role of ICAT in inflammation and fibrosis.

In the context of the triple burden of malnutrition: A systematic review of gene-diet interactions and nutritional status

Genetic background interacts with dietary components to modulate nutritional health status. This study aimed to review the evidence for gene-diet interactions in all forms of malnutrition. A comprehensive systematic literature search was conducted through April 2021 to identify observational and intervention studies reporting the effects of gene-diet interactions in over-nutrition, under-nutrition and micronutrient status. Risk of publication bias was assessed using the Quality Criteria Checklist and a tool specifically designed for gene-diet interaction research. 167 studies from 27 populations were included. The majority of studies investigated single nucleotide polymorphisms (SNPs) in overnutrition (n = 158). Diets rich in whole grains, vegetables, fruits and low in total and saturated fats, such as Mediterranean and DASH diets, showed promising effects for reducing obesity risk among individuals who had higher genetic risk scores for obesity, particularly the risk alleles carriers of FTO rs9939609, rs1121980 and rs1421085. Other SNPs in MC4R, PPARG and APOA5 genes were also commonly studied for interaction with diet on overnutrition though findings were inconclusive. Only limited data were found related to undernutrition (n = 1) and micronutrient status (n = 9). The findings on gene-diet interactions in this review highlight the importance of personalized nutrition, and more research on undernutrition and micronutrient status is warranted.

Effect of TCF7L2 on the relationship between lifestyle factors and glycemic parameters: a systematic review

Background

Among candidate genes related to type 2 diabetes (T2DM), one of the strongest genes is Transcription factor 7 like 2 (TCF7L2), regarding the Genome-Wide Association Studies. We aimed to conduct a systematic review of the literature on the modification effect of TCF7L2 on the relation between glycemic parameters and lifestyle factors.

Methods

A systematic literature search was done for relevant publications using electronic databases, including PubMed, EMBASE, Scopus, and Web of Science, from January 1, 2000, to November 2, 2021.

Results

Thirty-eight studies (16 observational studies, six meal test trials, and 16 randomized controlled trials (RCTs)) were included. Most observational studies had been conducted on participants with non-diabetes showing that TCF7L2 modified the association between diet (fatty acids and fiber) and insulin resistance. In addition, findings from meal test trials showed that, compared to non-risk-allele carriers, consumption of meals with different percentages of total dietary fat in healthy risk-allele carriers increased glucose concentrations and impaired insulin sensitivity. However, ten RCTs, with intervention periods of less than ten weeks and more than one year, showed that TCF7L2 did not modify glycemic parameters in response to a dietary intervention involving different macronutrients. However, two weight loss dietary RCTs with more than 1-year duration showed that serum glucose and insulin levels decreased and insulin resistance improved in non-risk allele subjects with overweight/obesity. Regarding artichoke extract supplementation (ALE), two RCTs observed that ALE supplementation significantly decreased insulin concentration and improved insulin resistance in the TT genotype of the rs7903146 variant of TCF7L2. In addition, four studies suggested that physical activity levels and smoking status modified the association between TCF7L2 and glycemic parameters. However, three studies observed no effect of TCF7L2 on glycemic parameters in participants with different levels of physical activity and smoking status.

Conclusion

The modification effects of TCF7L2 on the relation between the lifestyle factors (diet, physical activity, and smoking status) and glycemic parameters were contradictory.

PROSPERO registration number

CRD42020196327

Supplementary Information

The online version contains supplementary material available at 10.1186/s12937-022-00813-w.

Nutrigenetics and nutrigenomics-A personalized approach to nutrition

The prevalence of non-communicable diseases has been on an upward trajectory for some time and this puts an enormous burden on the healthcare expenditure. Lifestyle modifications including dietary interventions hold an immense promise to manage and prevent these diseases. Recent advances in genomic research provide evidence that focussing these efforts on individual variations in abilities to metabolize nutrients (nutrigenetics) and exploring the role of dietary compounds on gene expression (nutrigenomics and nutri-epigenomics) can lead to more meaningful personalized dietary strategies to promote optimal health. This chapter aims to provide examples on these gene-diet interactions at multiple levels to support the need of embedding targeted dietary interventions as a way forward to prevent, avoid and manage diseases.

Interaction of Diet/Lifestyle Intervention and TCF7L2 Genotype on Glycemic Control and Adiposity among Overweight or Obese Adults: Big Data from Seven Randomized Controlled Trials Worldwide

Objective. The strongest locus which associated with type 2 diabetes (T2D) by the common variant rs7903146 is the transcription factor 7-like 2 gene (TCF7L2). We aimed to quantify the interaction of diet/lifestyle interventions and the genetic effect of TCF7L2 rs7903146 on glycemic traits, body weight, or waist circumference in overweight or obese adults in several randomized controlled trials (RCTs).Methods. From October 2016 to May 2018, a large collaborative analysis was performed by pooling individual-participant data from 7 RCTs. These RCTs reported changes in glycemic control and adiposity of the variant rs7903146 after dietary/lifestyle-related interventions in overweight or obese adults. Gene treatment interaction models which used the genetic effect encoded by the allele dose and common covariates were applicable to individual participant data in all studies.Results. In the joint analysis, a total of 7 eligible RCTs were included (n = 4,114 ). Importantly, we observed a significant effect modification of diet/lifestyle-related interventions on the TCF7L2 variant rs7903146 and changes in fasting glucose. Compared with the control group, diet/lifestyle interventions were related to lower fasting glucose by -3.06 (95% CI, -5.77 to -0.36) mg/dL (test for heterogeneity and overall effect: I 2 = 45.1 % , p < 0.05 ; z = 2.20 , p = 0.028 ) per one copy of the TCF7L2 T risk allele. Furthermore, regardless of genetic risk, diet/lifestyle interventions were associated with lower waist circumference. However, there was no significant change for diet/lifestyle interventions in other glycemic control and adiposity traits per one copy of TCF7L2 risk allele.Conclusions. Our findings suggest that carrying the TCF7L2 T risk allele may have a modestly greater benefit for specific diet/lifestyle interventions to improve the control of fasting glucose in overweight or obese adults.

Dietary Macronutrient Intake May Influence the Effects of TCF7L2 rs7901695 Genetic Variants on Glucose Homeostasis and Obesity-Related Parameters: A Cross-Sectional Population-Based Study

Transcription factor-7–like 2 (TCF7L2) is one of the most important susceptibility genes for type 2 diabetes mellitus (T2DM). The aim of our cross-sectional population-based study was to analyze whether daily macronutrient intake may influence the effects of the TCF7L2 rs7901695 genotype on glucose homeostasis and obesity-related parameters. We recruited 810 participants (47.5% men and 52.5% women), 18–79 years old (mean age, 42.1 (±14.5) years), who were genotyped for the common TCF7L2 rs7901695 single-nucleotide polymorphism (SNP), and anthropometric measurements, body composition, body fat distribution (visceral (VAT) and subcutaneous adipose tissue (SAT) content), blood glucose and insulin concentrations after fasting and during OGTTs, and HbA1c were assessed. The VAT/SAT ratio, HOMA-IR (homeostatic model assessment of insulin resistance), HOMA-B (homeostatic model assessment of β-cell function), and CIR30 (corrected insulin response) were calculated. The daily macronutrient intake was evaluated based on 3-day food-intake diaries. Daily physical activity was evaluated based on a validated questionnaire. We performed ANOVA or Kruskal–Wallis tests, and multivariate linear regression models were created to evaluate the effects of dietary macronutrient intake on glucose homeostasis and obesity-related parameters in carriers of the investigated genotypes. This study was registered at ClinicalTrials.gov as NCT03792685. The TT-genotype carriers stratified to the upper protein intake quantiles presented higher HbA1c levels than the CT- and CC-genotype participants in the same quantiles (p = 0.038 and p = 0.022, respectively). Moreover, we observed higher HOMA-IR (p = 0.014), as well as significantly higher blood glucose and insulin concentrations, during the OGTTs for those in the upper quantiles, when compared to subjects from the lower quantiles of protein intake, while the CC-genotype carriers presented significantly lower HbA1c (p = 0.033) and significantly higher CIR30 (p = 0.03). The linear regression models revealed that an increase in energy derived from proteins in TT carriers was associated with higher HbA1c levels (β = 0.37 (95% CI: 0.01–0.74, p = 0.05)), although, in general, carrying the TT genotype, but without considering protein intake, showed an opposite tendency—to lower HbA1c levels (β = −0.22 (95% CI: 0.47 to −0.01, p = 0.05). Among the subjects stratified to the lower quantile of carbohydrate intake, the TT-genotype individuals presented higher HbA1c (p = 0.041), and the CC-genotype subjects presented higher VAT (p = 0.033), lower SAT (p = 0.033), and higher VAT/SAT ratios (p = 0.034). In both the CC- and TT-genotype carriers, we noted higher VAT (p = 0.012 and p = 0.0006, respectively), lower SAT (p = 0.012 and p = 0.0006, respectively) and higher VAT/SAT ratios (p = 0.016 and p = 0.00062, respectively) when dietary fat provided more than 30% of total daily energy intake, without any differences in total body fat content. Our findings suggest that associations of the common TCF7L2 SNP with glucose homeostasis and obesity-related parameters may be dependent on daily macronutrient intake, which warrants further investigations in a larger population, as well as interventional studies.

TCF7L2 rs7903146 polymorphism association with diabetes and obesity in an elderly cohort from Brazil

Background

Type 2 diabetes mellitus (T2DM) and obesity are complex pandemic diseases in the 21st century. Worldwide, the T allele rs7903146 in the TCF7L2 gene is recognized as a strong GWAS signal associated with T2DM. However, the association between the C allele and obesity is still poorly explored and needs to be replicated in other populations. Thus, the primary objectives of this study were to evaluate the TCF7L2 rs7903146 association with T2DM according to BMI status and to determine if this variant is related to obesity and BMI variation in a cohort of elderly Brazilians.

Methods

A total of 1,023 participants from an elderly census-based cohort called SABE (Saúde, Bem Estar e Envelhecimento—Health, Well-Being and Aging) were stratified by BMI status and type 2 diabetes presence. The TCF7L2 genotypes were filtered from the Online Archive of Brazilian Mutations (ABraOM—Online Archive of Brazilian Mutations) database, a web-based public database with sequencing data of samples of the SABE’s participants. Logistic regression models and interaction analyses were performed. The BMI variation (∆BMI) was calculated from anthropometric data collected in up to two time-points with a ten-year-assessment interval.

Results

The association between the rs7903146 T allele and T2DM was inversely proportional to the BMI status, with an increased risk in the normal weight group (OR 3.36; 95% CI [1.46–7.74]; P = 0.004). We confirmed the T allele association with risk for T2DM after adjusting for possible confound ing variables (OR 2.35; 95% CI [1.28–4.32]; P = 0.006). Interaction analysis showed that the increased risk for T2DM conferred by the T allele is modified by BMI (P_interaction = 0.008), age (P_interaction = 0.005) and gender (P_interaction = 0.026). A T allele protective effect against obesity was observed (OR 0.71; 95% CI [0.54–0.94]; P = 0.016). The C allele increased obesity risk (OR 1.40; 95% CI [1.06–1.84]; P = 0.017) and the CC genotype showed a borderline association with abdominal obesity risk (OR 1.28; 95% CI [1.06–1.67]; P = 0.045). The CC genotype increased the obesity risk factor after adjusting for possible confounding variables (OR 1.41; 95% CI [1.06–1.86]; P = 0.017). An increase of the TT genotype in the second tertile of ∆BMI values was observed in participants without type 2 diabetes (OR 5.13; 95% CI [1.40–18.93]; P = 0.009) in the recessive genetic model.

Conclusion

We confirmed that the rs7903146 is both associated with T2DM and obesity. The TCF7L2 rs7903146 T allele increased T2DM risk in the normal weight group and interacted with sex, age and BMI, while the C allele increased obesity risk. The TT genotype was associated with a lesser extent of BMI variation over the SABE study’s 10-year period.

Interaction of diabetes genetic risk and successful lifestyle modification in the Diabetes Prevention Programme

AIM

To test whether diabetes genetic risk modifies the association of successful lifestyle changes with incident diabetes.

MATERIALS AND METHODS

We studied 823 individuals randomized to the intensive lifestyle intervention (ILS) arm of the Diabetes Prevention Programme who were diabetes-free 1 year after enrolment. We tested additive and multiplicative interactions of a 67-variant diabetes genetic risk score (GRS) with achievement of three ILS goals at 1 year (≥7% weight loss, ≥150 min/wk of moderate leisure-time physical activity, and/or a goal for self-reported total fat intake) on the primary outcome of incident diabetes over 3 years of follow-up.

RESULTS

A lower GRS and achieving each or all three ILS goals were each associated with lower incidence of diabetes (all P < 0.05). Additive interactions were significant between the GRS and achievement of the weight loss goal (P < 0.001), physical activity goal (P = 0.02), and all three ILS goals (P < 0.001) for diabetes risk. Achievement of all three ILS goals was associated with 1.8 (95% CI 0.3, 3.4), 3.1 (95% CI 1.5, 4.7), and 3.9 (95% CI 1.6, 6.2) fewer diabetes cases/100-person-years in the first, second and third GRS tertiles (P < 0.001 for trend). Multiplicative interactions between the GRS and ILS goal achievement were significant for the diet goal (P < 0.001), but not for weight loss (P = 0.18) or physical activity (P = 0.62) goals.

CONCLUSIONS

Genetic risk may identify high-risk subgroups for whom successful lifestyle modification is associated with greater absolute reduction in the risk of incident diabetes.

Nutrition, genetic variation and male fertility

Infertility affects nearly 50 million couples worldwide, with 40-50% of cases having a male factor component. It is well established that nutritional status impacts reproductive development, health and function, although the exact mechanisms have not been fully elucidated. Genetic variation that affects nutrient metabolism may impact fertility through nutrigenetic mechanisms. This review summarizes current knowledge on the role of several dietary components (vitamins A, B₁₂, C, D, E, folate, betaine, choline, calcium, iron, caffeine, fiber, sugar, dietary fat, and gluten) in male reproductive health. Evidence of gene-nutrient interactions and their potential effect on fertility is also examined. Understanding the relationship between genetic variation, nutrition and male fertility is key to developing personalized, DNA-based dietary recommendations to enhance the fertility of men who have difficulty conceiving.

TCF7L2 polymorphisms, nut consumption, and the risk of metabolic syndrome: a prospective population based study

Background

The aim of this study was to investigate whether two variants of the TCF7L2 (rs7903146 and rs12255372) modify the association between nut consumption and the risk of metabolic syndrome (MetS). Additionally, the modifying effect of weight change during follow-up on these associations was investigated.

Material and methods

We prospectively studied 1423 participants of the Tehran Lipid and Glucose study aged 19–74 years who were followed-up for dietary assessment using a validated, semi-quantitative food frequency questionnaire. Multivariable-adjusted Cox regression was used to estimate hazard ratios (HRs) for MetS events. Genotyping was performed by Human Omni Express-24-v1-0 chip.

Results

Over a median 8.9 years of follow-up, 415 new cases of MetS were documented. The median nut consumption was 20.0 g/week (Interquartile Range (IQR): 8.6–38.9 g/week). Regarding the rs7903146 genotype, in carriers of T allele (CT + TT), highest tertile of nut consumption was associated with a reduced risk of MetS after adjusting for confounders (HR: 0.67 (0.50–0.91)). Regarding the rs12255372 genotype, highest versus lowest tertile of nut consumption in participants with T allele (GT + TT) resulted in 34% reduction of MetS risk after adjustment for confounders (HR: 0.66 (0.49–0.69)). After stratification by weigh change (< 7% or ≥ 7% weight gain), in individuals with ≥ 7% weight gain, highest tertile of nut consumption was associated with reduced risk of MetS among the risk allele of rs7903146. In the risk allele of rs12255372, among individuals with < 7% weight gain, third tertile of nuts intake reduced the risk of MetS, after adjustment for confounders.

Conclusion

Higher consumption of nuts may reduces the risk of MetS in T-risk allele of the TCF7L2 rs7903146 and rs12255372 variants and weight change may modify this association.

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.

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.

Reduction in saturated fat intake for cardiovascular disease

BACKGROUND

Reducing saturated fat reduces serum cholesterol, but effects on other intermediate outcomes may be less clear. Additionally, it is unclear whether the energy from saturated fats eliminated from the diet are more helpfully replaced by polyunsaturated fats, monounsaturated fats, carbohydrate or protein.

OBJECTIVES

To assess the effect of reducing saturated fat intake and replacing it with carbohydrate (CHO), polyunsaturated (PUFA), monounsaturated fat (MUFA) and/or protein on mortality and cardiovascular morbidity, using all available randomised clinical trials.

SEARCH METHODS

We updated our searches of the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (Ovid) and Embase (Ovid) on 15 October 2019, and searched Clinicaltrials.gov and WHO International Clinical Trials Registry Platform (ICTRP) on 17 October 2019.

SELECTION CRITERIA

Included trials fulfilled the following criteria: 1) randomised; 2) intention to reduce saturated fat intake OR intention to alter dietary fats and achieving a reduction in saturated fat; 3) compared with higher saturated fat intake or usual diet; 4) not multifactorial; 5) in adult humans with or without cardiovascular disease (but not acutely ill, pregnant or breastfeeding); 6) intervention duration at least 24 months; 7) mortality or cardiovascular morbidity data available.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed inclusion, extracted study data and assessed risk of bias. We performed random-effects meta-analyses, meta-regression, subgrouping, sensitivity analyses, funnel plots and GRADE assessment.

MAIN RESULTS

We included 15 randomised controlled trials (RCTs) (16 comparisons, 56,675 participants), that used a variety of interventions from providing all food to advice on reducing saturated fat. The included long-term trials suggested that reducing dietary saturated fat reduced the risk of combined cardiovascular events by 17% (risk ratio (RR) 0.83; 95% confidence interval (CI) 0.70 to 0.98, 12 trials, 53,758 participants of whom 8% had a cardiovascular event, I² = 67%, GRADE moderate-quality evidence). Meta-regression suggested that greater reductions in saturated fat (reflected in greater reductions in serum cholesterol) resulted in greater reductions in risk of CVD events, explaining most heterogeneity between trials. The number needed to treat for an additional beneficial outcome (NNTB) was 56 in primary prevention trials, so 56 people need to reduce their saturated fat intake for ~four years for one person to avoid experiencing a CVD event. In secondary prevention trials, the NNTB was 53. Subgrouping did not suggest significant differences between replacement of saturated fat calories with polyunsaturated fat or carbohydrate, and data on replacement with monounsaturated fat and protein was very limited. We found little or no effect of reducing saturated fat on all-cause mortality (RR 0.96; 95% CI 0.90 to 1.03; 11 trials, 55,858 participants) or cardiovascular mortality (RR 0.95; 95% CI 0.80 to 1.12, 10 trials, 53,421 participants), both with GRADE moderate-quality evidence. There was little or no effect of reducing saturated fats on non-fatal myocardial infarction (RR 0.97, 95% CI 0.87 to 1.07) or CHD mortality (RR 0.97, 95% CI 0.82 to 1.16, both low-quality evidence), but effects on total (fatal or non-fatal) myocardial infarction, stroke and CHD events (fatal or non-fatal) were all unclear as the evidence was of very low quality. There was little or no effect on cancer mortality, cancer diagnoses, diabetes diagnosis, HDL cholesterol, serum triglycerides or blood pressure, and small reductions in weight, serum total cholesterol, LDL cholesterol and BMI. There was no evidence of harmful effects of reducing saturated fat intakes.

AUTHORS' CONCLUSIONS

The findings of this updated review suggest that reducing saturated fat intake for at least two years causes a potentially important reduction in combined cardiovascular events. Replacing the energy from saturated fat with polyunsaturated fat or carbohydrate appear to be useful strategies, while effects of replacement with monounsaturated fat are unclear. The reduction in combined cardiovascular events resulting from reducing saturated fat did not alter by study duration, sex or baseline level of cardiovascular risk, but greater reduction in saturated fat caused greater reductions in cardiovascular events.

Change in Weight, BMI, and Body Composition in a Population-Based Intervention Versus Genetic-Based Intervention: The NOW Trial

OBJECTIVE

The aim of this study was to compare changes in body fat percentage (BFP), weight, and BMI between a standard intervention and a nutrigenomics intervention.

METHODS

The Nutrigenomics, Overweight/Obesity and Weight Management (NOW) trial is a parallel-group, pragmatic, randomized controlled clinical trial incorporated into the Group Lifestyle Balance^TM (GLB) Program. Statistical analyses included two-way ANOVA and split-plot ANOVA. Inclusion criteria consisted of: BMI ≥ 25.0 kg/m² , ≥18 years of age, English speaking, willing to undergo genetic testing, having internet access, and not seeing another health care provider for weight-loss advice outside of the study. Pregnancy and lactation were exclusion criteria. GLB groups were randomly assigned 1 to 1 (N = 140) so that participants received either the standard 12-month GLB program or a modified 12-month program (GLB plus nutrigenomics), which included the provision of nutrigenomics information and advice for weight management. The primary outcome was percent change in BFP. Secondary outcomes were change in weight and BMI.

RESULTS

The GLB plus nutrigenomics group experienced significantly (P < 0.05) greater reductions in percent and absolute BFP at the 3-month follow-up and percent BFP at the 6-month follow-up compared with the standard GLB group.

CONCLUSIONS

The nutrigenomics intervention used in the NOW trial can optimize change in body composition up to 6 months.

Reduction in saturated fat intake for cardiovascular disease

BACKGROUND

Reducing saturated fat reduces serum cholesterol, but effects on other intermediate outcomes may be less clear. Additionally, it is unclear whether the energy from saturated fats eliminated from the diet are more helpfully replaced by polyunsaturated fats, monounsaturated fats, carbohydrate or protein.

OBJECTIVES

To assess the effect of reducing saturated fat intake and replacing it with carbohydrate (CHO), polyunsaturated (PUFA), monounsaturated fat (MUFA) and/or protein on mortality and cardiovascular morbidity, using all available randomised clinical trials.

SEARCH METHODS

We updated our searches of the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (Ovid) and Embase (Ovid) on 15 October 2019, and searched Clinicaltrials.gov and WHO International Clinical Trials Registry Platform (ICTRP) on 17 October 2019.

SELECTION CRITERIA

Included trials fulfilled the following criteria: 1) randomised; 2) intention to reduce saturated fat intake OR intention to alter dietary fats and achieving a reduction in saturated fat; 3) compared with higher saturated fat intake or usual diet; 4) not multifactorial; 5) in adult humans with or without cardiovascular disease (but not acutely ill, pregnant or breastfeeding); 6) intervention duration at least 24 months; 7) mortality or cardiovascular morbidity data available.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed inclusion, extracted study data and assessed risk of bias. We performed random-effects meta-analyses, meta-regression, subgrouping, sensitivity analyses, funnel plots and GRADE assessment.

MAIN RESULTS

We included 15 randomised controlled trials (RCTs) (16 comparisons, ~59,000 participants), that used a variety of interventions from providing all food to advice on reducing saturated fat. The included long-term trials suggested that reducing dietary saturated fat reduced the risk of combined cardiovascular events by 21% (risk ratio (RR) 0.79; 95% confidence interval (CI) 0.66 to 0.93, 11 trials, 53,300 participants of whom 8% had a cardiovascular event, I² = 65%, GRADE moderate-quality evidence). Meta-regression suggested that greater reductions in saturated fat (reflected in greater reductions in serum cholesterol) resulted in greater reductions in risk of CVD events, explaining most heterogeneity between trials. The number needed to treat for an additional beneficial outcome (NNTB) was 56 in primary prevention trials, so 56 people need to reduce their saturated fat intake for ~four years for one person to avoid experiencing a CVD event. In secondary prevention trials, the NNTB was 32. Subgrouping did not suggest significant differences between replacement of saturated fat calories with polyunsaturated fat or carbohydrate, and data on replacement with monounsaturated fat and protein was very limited. We found little or no effect of reducing saturated fat on all-cause mortality (RR 0.96; 95% CI 0.90 to 1.03; 11 trials, 55,858 participants) or cardiovascular mortality (RR 0.95; 95% CI 0.80 to 1.12, 10 trials, 53,421 participants), both with GRADE moderate-quality evidence. There was little or no effect of reducing saturated fats on non-fatal myocardial infarction (RR 0.97, 95% CI 0.87 to 1.07) or CHD mortality (RR 0.97, 95% CI 0.82 to 1.16, both low-quality evidence), but effects on total (fatal or non-fatal) myocardial infarction, stroke and CHD events (fatal or non-fatal) were all unclear as the evidence was of very low quality. There was little or no effect on cancer mortality, cancer diagnoses, diabetes diagnosis, HDL cholesterol, serum triglycerides or blood pressure, and small reductions in weight, serum total cholesterol, LDL cholesterol and BMI. There was no evidence of harmful effects of reducing saturated fat intakes.

AUTHORS' CONCLUSIONS

The findings of this updated review suggest that reducing saturated fat intake for at least two years causes a potentially important reduction in combined cardiovascular events. Replacing the energy from saturated fat with polyunsaturated fat or carbohydrate appear to be useful strategies, while effects of replacement with monounsaturated fat are unclear. The reduction in combined cardiovascular events resulting from reducing saturated fat did not alter by study duration, sex or baseline level of cardiovascular risk, but greater reduction in saturated fat caused greater reductions in cardiovascular events.

A Nutrigenetic Approach to Investigate the Relationship between Metabolic Traits and Vitamin D Status in an Asian Indian Population

Studies in Asian Indians have examined the association of metabolic traits with vitamin D status. However, findings have been quite inconsistent. Hence, we aimed to explore the relationship between metabolic traits and 25-hydroxyvitamin D [25(OH)D] concentrations. We investigate whether this relationship was modified by lifestyle factors using a nutrigenetic approach in 545 Asian Indians randomly selected from the Chennai Urban Rural Epidemiology Study (219 normal glucose tolerant individuals, 151 with pre-diabetes and 175 individuals with type 2 diabetes). A metabolic genetic risk score (GRS) was developed using five common metabolic disease-related genetic variants. There was a significant interaction between metabolic GRS and carbohydrate intake (energy%) on 25(OH)D (Pinteraction = 0.047). Individuals consuming a low carbohydrate diet (≤62%) and those having lesser number of metabolic risk alleles (GRS ≤ 1) had significantly higher levels of 25(OH)D (p = 0.033). Conversely, individuals consuming a high carbohydrate diet despite having lesser number of risk alleles did not show a significant increase in 25(OH)D (p = 0.662). In summary, our findings show that individuals carrying a smaller number of metabolic risk alleles are likely to have higher 25(OH)D levels if they consume a low carbohydrate diet. These data support the current dietary carbohydrate recommendations of 50%-60% energy suggesting that reduced metabolic genetic risk increases 25(OH)D.

Mediterranean Diet Adherence Modulates Anthropometric Measures by TCF7L2 Genotypes among Puerto Rican Adults

BACKGROUND

Transcription factor 7-like 2 (TCF7L2) genetic variants that predispose individuals to type 2 diabetes (T2D) show inconsistent associations with anthropometric traits. Interaction between TCF7L2 genotypes and dietary factors may help explain these observations.

OBJECTIVE

We aimed to examine the potential modulation of TCF7L2-rs7903146 and rs12255372 on anthropometric markers by a Mediterranean diet (MedDiet).

METHODS

Cross-sectional analysis was conducted in 1120 participants (aged 45-75 y) of the Boston Puerto Rican Health Study. Anthropometric variables were measured, and polymorphisms were genotyped using standardized protocols. Diet was assessed using a validated FFQ. The MedDiet was defined based on adherence to 9 food and nutrient components using sex-specific population-based median cut-offs; high adherence was defined as meeting ≥4 components. Haplotypes were tested for association with obesity traits, independently and via interaction with the MedDiet.

RESULTS

TCF7L2-rs7903146 showed significant interaction with the MedDiet influencing BMI, weight, and waist circumference. The T risk-allele carriers (CT + TT) with a high MedDiet score had lower weight (77.3 ± 1.0 compared with CC 80.9 ± 1.0 kg; P = 0.013) and waist circumference (99.2 ± 0.9 compared with CC 102.2 ± 0.9 cm; P = 0.021), when compared with CC participants. A low MedDiet score resulted in no significant differences between genotypes. For TCF7L2-rs12255372, we found significant interactions with the MedDiet for weight (P-interaction = 0.034) and BMI (P-interaction = 0.036). The T allele carriers with a higher MedDiet score showed a trend of lower but no significant differences when compared with CC participants for BMI (P = 0.19), weight (P = 0.09), and waist circumference (P = 0.11). We found significant interactions between the 2 risk-carrying haplotypes and the MedDiet compared with the common haplotype (GC), with lower BMI (β ± SE, TT: -1.53 ± 0.68; P-interaction = 0.024), weight (TT: -4.16 ± 1.77; P-interaction = 0.019), and waist circumference (GT: -5.07 ± 2.50; P-interaction = 0.042) at a high MedDiet score.

CONCLUSION

Puerto Ricans with the TCF7L2-rs7903146 and rs12255372 T2D risk genotypes, although still high, had better anthropometric profiles when adhering to a MedDiet, suggesting that this diet may offset unfavorable genetic predisposition.

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.

Gene-Environment Interactions on Body Fat Distribution

The prevalence of obesity has been increasing markedly in the U.S. and worldwide in the past decades; and notably, the obese populations are signified by not only the overall elevated adiposity but also particularly harmful accumulation of body fat in the central region of the body, namely, abdominal obesity. The profound shift from “traditional” to “obesogenic” environments, principally featured by the abundance of palatable, energy-dense diet, reduced physical activity, and prolonged sedentary time, promotes the obesity epidemics and detrimental body fat distribution. Recent advances in genomics studies shed light on the genetic basis of obesity and body fat distribution. In addition, growing evidence from investigations in large cohorts and clinical trials has lent support to interactions between genetic variations and environmental factors, e.g., diet and lifestyle factors, in relation to obesity and body fat distribution. This review summarizes the recent discoveries from observational studies and randomized clinical trials on the gene–environment interactions on obesity and body fat distribution.

Study protocol of a pragmatic randomized controlled trial incorporated into the Group Lifestyle Balance™ program: the nutrigenomics, overweight/obesity and weight management trial (the NOW trial)

BACKGROUND

The nutrigenomics, overweight/obesity and weight management trial (NOW Trial) is a pragmatic randomized controlled trial of community-dwelling adults recruited from the Group Lifestyle Balance™ (GLB™) Program. The GLB™ Program (formerly referred to as the Diabetes Prevention Program) is an evidence-based, intensive weight management program, which was offered to overweight/obese patients (BMI ≥ 25.0 kg/m2) in a rural Ontario community.

METHODS

Patients enrolled in the GLB™ Program were invited to participate in this study. GLB™ groups were randomized 1:1 to receive either the standard GLB™ program + population-based lifestyle advice for weight management, or a modified GLB™ program + personalized, genetic-based lifestyle advice for weight management. The purpose of this study is to determine if the provision of genetic-based lifestyle guidelines is superior to the provision of population-based guidelines in a pragmatic clinical setting to promote changes in: body composition, weight, body mass index, dietary and physical activity habits, as well as attitudes, subjective norms, and behavioural control. The 12-month intervention protocol consists of 23 group-based sessions and 4 one-on-one sessions. Data collection time points include baseline in addition to 3, 6, and 12-month follow up. The comprehensive study design is described in the present manuscript, using both the extended CONSORT checklist for reporting pragmatic trials and the SPIRIT checklist as guidance during manuscript development.

DISCUSSION

Overall, this study seeks to pragmatically determine if the provision of DNA-based lifestyle advice leads to improved health and lifestyle outcomes compared to the provision of standard, population-based lifestyle advice. The results of this trial can be used to inform clinical and community nutrition practice guidelines.

TRIAL REGISTRATION

This study was registered with clinicaltrials.gov : NCT03015012 on January 9, 2017.

Targeted deletion of Tcf7l2 in adipocytes promotes adipocyte hypertrophy and impaired glucose metabolism

OBJECTIVE

Activation of the Wnt-signaling pathway is known to inhibit differentiation in adipocytes. However, there is a gap in our understanding of the transcriptional network regulated by components of the Wnt-signaling pathway during adipogenesis and in adipocytes during postnatal life. The key intracellular effectors of the Wnt-signaling pathway occur through TCF transcription factors such as TCF7L2 (transcription factor-7-like 2). Several genetic variants in proximity to TCF7L2 have been linked to type 2 diabetes through genome-wide association studies in various human populations. Our work aims to functionally characterize the adipocyte specific gene program regulated by TCF7L2 and understand how this program regulates metabolism.

METHODS

We generated Tcf7l2^F/F mice and assessed TCF7L2 function in isolated adipocytes and adipose specific knockout mice. ChIP-sequencing and RNA-sequencing was performed on the isolated adipocytes with control and TCF7L2 knockout cells. Adipose specific TCF7L2 knockout mice were challenged with high fat diet and assessed for body weight, glucose tolerance, and lipolysis.

RESULTS

Here we report that TCF7L2 regulates adipocyte size, endocrine function, and glucose metabolism. Tcf7l2 is highly expressed in white adipose tissue, and its expression is suppressed in genetic and diet-induced models of obesity. Genome-wide distribution of TCF7L2 binding and gene expression analysis in adipocytes suggests that TCF7L2 directly regulates genes implicated in cellular metabolism and cell cycle control. When challenged with a high-fat diet, conditional deletion of TCF7L2 in adipocytes led to impaired glucose tolerance, impaired insulin sensitivity, promoted weight gain, and increased adipose tissue mass. This was accompanied by reduced expression of triglyceride hydrolase, reduced fasting-induced free fatty acid release, and adipocyte hypertrophy in subcutaneous adipose tissue.

CONCLUSIONS

Together our studies support that TCF7L2 is a central transcriptional regulator of the adipocyte metabolic program by directly regulating the expression of genes involved in lipid and glucose metabolism.

Sport Nutrigenomics: Personalized Nutrition for Athletic Performance

An individual's dietary and supplement strategies can influence markedly their physical performance. Personalized nutrition in athletic populations aims to optimize health, body composition, and exercise performance by targeting dietary recommendations to an individual's genetic profile. Sport dietitians and nutritionists have long been adept at placing additional scrutiny on the one-size-fits-all general population dietary guidelines to accommodate various sporting populations. However, generic "one-size-fits-all" recommendations still remain. Genetic differences are known to impact absorption, metabolism, uptake, utilization and excretion of nutrients and food bioactives, which ultimately affects a number of metabolic pathways. Nutrigenomics and nutrigenetics are experimental approaches that use genomic information and genetic testing technologies to examine the role of individual genetic differences in modifying an athlete's response to nutrients and other food components. Although there have been few randomized, controlled trials examining the effects of genetic variation on performance in response to an ergogenic aid, there is a growing foundation of research linking gene-diet interactions on biomarkers of nutritional status, which impact exercise and sport performance. This foundation forms the basis from which the field of sport nutrigenomics continues to develop. We review the science of genetic modifiers of various dietary factors that impact an athlete's nutritional status, body composition and, ultimately athletic performance.

The Interaction between Genetic Polymorphisms in FTO and TCF7L2 Genes and Dietary Intake with Regard to Body Mass and Composition: An Exploratory Study

In contrast to the large number of genetic studies on obesity, there has been significantly less nutrigenetics investigation of the interaction between diet and single nucleotide polymorphisms (SNPs) in obesity, especially within Eastern Mediterranean populations. The aim of this study was to evaluate the potential interactions between three candidate SNPs, namely, rs1558902 and rs9939609 in the fat mass and obesity (FTO) gene and the rs7903146 variant of the Transcription factor 7 like 2 (TCF7L2) gene, and macronutrient intake with regard to obesity, body fat, and muscle composition. Three hundred and eight healthy Lebanese adults were included in this study. Data collection included a questionnaire for demographics and lifestyle in addition to a detailed dietary assessment using a culture-specific 80-item semi-quantitative food frequency questionnaire. This was coupled with anthropometric measurements and peripheral blood withdrawal for DNA and genotyping using Taqman allele discrimination assays. The two FTO candidate SNPs were not associated with risk of obesity in this population sample, yet there was a trend, though not a significant one, towards lower muscle mass among carriers of the risk allele of either FTO SNPs. To our knowledge, these results have not been previously reported. As for the TCF7L2rs7903146 variant, results were congruent with the literature, given that individuals who were homozygous for the risk allele had significantly higher body mass index (BMI) and body fat despite lower intakes of saturated fat. Similar interactions, though not significant, were shown with muscle mass, whereby individuals who were homozygous for the risk allele had lower muscle mass with higher intakes of saturated fat, a result that, to our knowledge, has not been previously reported.

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.

Daily Yogurt Consumption Improves Glucose Metabolism and Insulin Sensitivity in Young Nondiabetic Japanese Subjects with Type-2 Diabetes Risk Alleles

This study investigated whether the association between postprandial plasma glucose (PPG) is affected by five type 2 diabetes mellitus (T2DM) susceptibility genes, and whether four weeks of yogurt consumption would affect these responses. We performed a single-arm intervention study in young nondiabetic Japanese participants, who consumed 150 g yogurt daily for four weeks, after which a rice test meal containing 50 g carbohydrate was administered. PPG and postprandial serum insulin (PSI) were measured between 0 and 120 mins at baseline and after the intervention. Genetic risk was evaluated by weighted genetic risk score (GRS) according to published methodology, and participants were assigned to one of two groups (n = 17: L-GRS group and n = 15: H-GRS group) according to the median of weighted GRS. At baseline, the H-GRS group had higher glucose area under the curve_{0–120 min} after intake of the test meal than the L-GRS group (2175 ± 248 mg/dL.min vs. 1348 ± 199 mg/dL.min, p < 0.001), but there were no significant differences after the yogurt intervention. However, there was an improvement in PSI in the H-GRS group compared with baseline. These results suggest that habitual yogurt consumption may improve glucose and insulin responses in nondiabetic subjects who have genetically higher PPG.

Wnt/β-Catenin Signaling and Obesity

Obesity has become epidemic worldwide, which triggers several obesity-associated complications. Obesity is characterized by excess fat storage mainly in the visceral white adipose tissue (vWAT), subcutaneous WAT (sWAT), and other tissues. Myriad studies have demonstrated the crucial role of canonical Wnt/β-catenin cascade in the development of organs and physiological homeostasis, whereas recent studies show that genetic variations/mutations in the Wnt/β-catenin pathway are associated with human metabolic diseases. In this review, we highlight the regulation of updated Wnt/β-catenin signaling in obesity, especially the distinctly depot-specific roles between subcutaneous and visceral adipose tissue under high-fed diet stimulation and WAT browning process.

Nutritional Genomics and Direct-to-Consumer Genetic Testing: An Overview

The increasing prevalence in polygenic diseases, such as obesity, cardiovascular disease, and type 2 diabetes, observed over the past few decades is more likely linked to a rapid transition in lifestyle rather than to changes in the sequence of the nuclear genome. In the new era of precision medicine, nutritional genomics holds the promise to be translated into tailored nutritional strategies to prevent and manage polygenic diseases more effectively. Nutritional genomics aims to prevent, treat, and manage polygenic diseases through targeted therapies formulated from individuals' genetic makeup and dietary intake. Direct-to-consumer genetic testing (DTC-GT) has become commercially available to equip individuals with information on their genetic vulnerability to different diseases. This information may potentially prompt behavioral changes against adverse factors. However, scientific evidence behind the clinical recommendations is a matter of continuous debate, and behavioral modifications after disclosing genetic information remain inconclusive. In this review, we provide an overview of nutritional genomics and related nutritional DTC-GT services and discuss whether available data are sufficient to be translated into clinical recommendations and public health initiatives. Overall, the scientific evidence supporting the dissemination of genomic information for nutrigenomic purposes remains sparse. Therefore, additional knowledge needs to be generated, particularly for polygenic traits.

Penetrance of Polygenic Obesity Susceptibility Loci across the Body Mass Index Distribution

A growing number of single-nucleotide polymorphisms (SNPs) have been associated with body mass index (BMI) and obesity, but whether the effects of these obesity-susceptibility loci are uniform across the BMI distribution remains unclear. We studied the effects of 37 BMI-associated SNPs in 75,230 adults of European ancestry across BMI percentiles by using conditional quantile regression (CQR) and meta-regression (MR) models. The effects of nine SNPs (24%)-rs1421085 (FTO; p = 8.69 × 10-15), rs6235 (PCSK1; p = 7.11 × 10-6), rs7903146 (TCF7L2; p = 9.60 × 10-6), rs11873305 (MC4R; p = 5.08 × 10-5), rs12617233 (FANCL; p = 5.30 × 10-5), rs11672660 (GIPR; p = 1.64 × 10-4), rs997295 (MAP2K5; p = 3.25 × 10-4), rs6499653 (FTO; p = 6.23 × 10-4), and rs3824755 (NT5C2; p = 7.90 × 10-4)-increased significantly across the sample BMI distribution. We showed that such increases stemmed from unadjusted gene interactions that enhanced the effects of SNPs in persons with a high BMI. When 125 height-associated SNPs were analyzed for comparison, only one (<1%), rs6219 (IGF1, p = 1.80 × 10-4), showed effects that varied significantly across height percentiles. Cumulative gene scores of these SNPs (GS-BMI and GS-height) showed that only GS-BMI had effects that increased significantly across the sample distribution (BMI: p = 7.03 × 10-37; height: p = 0.499). Overall, these findings underscore the importance of gene-gene and gene-environment interactions in shaping the genetic architecture of BMI and advance a method for detecting such interactions by using only the sample outcome distribution.

Interaction between TCF7L2 polymorphism and dietary fat intake on high density lipoprotein cholesterol

Recent evidence suggests that lifestyle factors influence the association between the Melanocortin 4 receptor (MC4R) and Transcription Factor 7-Like 2 (TCF7L2) gene variants and cardio-metabolic traits in several populations; however, the available research is limited among the Asian Indian population. Hence, the present study examined whether the association between the MC4R single nucleotide polymorphism (SNP) (rs17782313) and two SNPs of the TCF7L2 gene (rs12255372 and rs7903146) and cardio-metabolic traits is modified by dietary factors and physical activity. This cross sectional study included a random sample of normal glucose tolerant (NGT) (n = 821) and participants with type 2 diabetes (T2D) (n = 861) recruited from the urban part of the Chennai Urban Rural Epidemiology Study (CURES). A validated food frequency questionnaire (FFQ) was used for dietary assessment and self-reported physical activity measures were collected. The threshold for significance was set at P = 0.00023 based on Bonferroni correction for multiple testing [(0.05/210 (3 SNPs x 14 outcomes x 5 lifestyle factors)]. After Bonferroni correction, there was a significant interaction between the TCF7L2 rs12255372 SNP and fat intake (g/day) (P_interaction = 0.0001) on high-density lipoprotein cholesterol (HDL-C), where the ‘T’ allele carriers in the lowest tertile of total fat intake had higher HDL-C (P = 0.008) and those in the highest tertile (P = 0.017) had lower HDL-C compared to the GG homozygotes. In a secondary analysis of SNPs with the subtypes of fat, there was also a significant interaction between the SNP rs12255372 and polyunsaturated fatty acids (PUFA, g/day) (P_interaction<0.0001) on HDL-C, where the minor allele carriers had higher HDL-C in the lowest PUFA tertile (P = 0.024) and those in the highest PUFA tertile had lower HDL-C (P = 0.028) than GG homozygotes. In addition, a significant interaction was also seen between TCF7L2 SNP rs12255372 and fibre intake (g/day) on HDL-C (P_interaction<0.0001). None of the other interactions between the SNPs and lifestyle factors were statistically significant after correction for multiple testing. Our findings indicate that the association between TCF7L2 SNP rs12255372 and HDL-C may be modified by dietary fat intake in this Asian Indian population.

Starch Digestion-Related Amylase Genetic Variant Affects 2-Year Changes in Adiposity in Response to Weight-Loss Diets: The POUNDS Lost Trial

Salivary and pancreatic amylases (encoded by AMY1 and AMY2 genes, respectively) are responsible for digesting starchy foods. AMY1 and AMY2 show copy number variations that affect differences in amylase amount and activity, and AMY1 copies have been associated with adiposity. We investigated whether genetic variants determining amylase gene copies are associated with 2-year changes in adiposity among 692 overweight and obese individuals who were randomly assigned to diets varying in macronutrient content. We found that changes in body weight (BW) and waist circumference (WC) were significantly different according to the AMY1-AMY2 rs11185098 genotype. Individuals carrying the A allele (indicating higher amylase amount and activity) showed a greater reduction in BW and WC at 6, 12, 18, and 24 months than those without the A allele (P < 0.05 for all). The association was stronger for long-term changes compared with short-term changes of these outcomes. The genetic effects on these outcomes did not significantly differ across diet groups. In conclusion, the genetic variant determining starch metabolism influences the response to weight-loss dietary intervention. Overweight and obese individuals carrying the AMY1-AMY2 rs11185098 genotype associated with higher amylase activity may have greater loss of adiposity during low-calorie diet interventions.

Genetic endowments, parental resources and adult health: Evidence from the Young Finns Study

This paper uses longitudinal survey data linked to administrative registers to examine socioeconomic gradients in health, particularly whether the effects of genetic endowments interact with the socioeconomic resources of the parental household. We find that genetic risk scores contribute to adult health measured by biomarkers. This result is consistent with the findings from genome-wide association studies. Socioeconomic gradients in health differ based on biomarker and resource measures. Family education is negatively related to obesity and the waist-hip ratio, and family income is negatively related to low-density lipoprotein cholesterol and triglyceride levels. Parental resources do not modify the effects of genetic endowment on adult health. However, there is evidence for gene-family income interactions for triglyceride levels, particularly among women.

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.

Genetics of fat intake in the determination of body mass

Body mass and fat intake are multifactorial traits that have genetic and environmental components. The gene with the greatest effect on body mass is FTO (fat mass and obesity-associated), but several studies have shown that the effect of FTO (and of other genes) on body mass can be modified by the intake of nutrients. The so-called gene–environment interactions may also be important for the effectiveness of weight-loss strategies. Food choices, and thus fat intake, depend to some extent on individual preferences. The most important biological component of food preference is taste, and the role of fat sensitivity in fat intake has recently been pointed out. Relatively few studies have analysed the genetic components of fat intake or fatty acid sensitivity in terms of their relation to obesity. It has been proposed that decreased oral fatty acid sensitivity leads to increased fat intake and thus increased body mass. One of the genes that affect fatty acid sensitivity is CD36 (cluster of differentiation 36). However, little is known so far about the genetic component of fat sensing. We performed a literature review to identify the state of knowledge regarding the genetics of fat intake and its relation to body-mass determination, and to identify the priorities for further investigations.

Association between dietary fat intake and insulin resistance in Chinese child twins

Dietary fat intake is correlated with increased insulin resistance (IR). However, it is unknown whether gene-diet interaction modulates the association. This study estimated heritability of IR measures and the related genetic correlations with fat intake, and tested whether dietary fat intake modifies the genetic influence on type 2 diabetes (T2D)-related traits in Chinese child twins. We included 622 twins aged 7-15 years (n 311 pairs, 162 monozygotic (MZ), 149 dizygotic (DZ)) from south-eastern China. Dietary factors were measured using FFQ. Structural equation models were fit using Mx statistical package. The intra-class correlation coefficients for all traits related to T2D were higher for MZ twins than for DZ twins. Dietary fat and fasting serum insulin (additive genetic correlation (r A) 0·20; 95 % CI 0·08, 0·43), glucose (r A 0·12; 95 % CI 0·01, 0·40), homoeostasis model of assessment-insulin resistance (Homa-IR) (r A 0·22; 95 % CI 0·10, 0·50) and the quantitative insulin sensitivity check index (Quicki) (r A -0·22; 95 % CI -0·40, 0·04) showed strong genetic correlations. Heritabilities of dietary fat intake, fasting glucose and insulin were estimated to be 52, 70 and 70 %, respectively. More than 70 % of the phenotypic correlations between dietary fat and insulin, glucose, Homa-IR and the Quicki index appeared to be mediated by shared genetic influence. Dietary fat significantly modified additive genetic effects on these quantitative traits associated with T2D. Analysis of Chinese twins yielded high estimates of heritability of dietary fat intake and IR. Genetic factors appear to contribute to a high proportion of the variance for both insulin sensitivity and IR. Dietary fat intake modifies the genetic influence on blood levels of insulin and glucose, Homa-IR and the Quicki index.

Analysis of the interaction between transcription factor 7-like 2 genetic variants with nopal and wholegrain fibre intake: effects on anthropometric and metabolic characteristics in type 2 diabetes patients

The transcription factor 7-like 2 (TCF7L2) genetic variants have shown differential effect on low-fat and high-fat diet in obese subjects. Nopal is a Mexican variety of cactus that is a traditional food and has been used in the treatment of diabetes. Its hypoglycaemic effect may be because of its soluble fibre (mucopolysaccharide) content. This study analysed the effects of the rs7903146 and rs12255372 TCF7L2 variants on anthropometric, metabolic and hormonal parameters in type 2 diabetes mellitus patients who consumed fibre from either nopal tortilla or wholegrain bread for 8 weeks. We followed-up seventy-four patients who consumed an individualised isoenergetic diet that included nopal tortilla (Diet 1) and sixty-three patients with a diet that included wholegrain bread (Diet 2). Anthropometric, metabolic and hormonal measures were collected at baseline and final intervention. The size effect and carry-over effect were estimated. To assess the interaction of genotype and diets, we used a general linear model repeated-measures analysis. Minor allele frequency of rs7903146T was 0·27 and for rs12255372T it was 0·13. At 8 weeks after Diet 1 intake, weight, BMI, waist and hip circumference decreased (P=0·00015) in rs7903146CC and rs12255372GG genotypes. In particular, patients carrying of the rs7903146CC and consuming Diet 1 showed a reduction in waist circumference of more than 2·5 cm compared with Diet 2 (P<0·001). No significant interaction between rs7903146 or rs12255372 and diet was seen in this study. In conclusion, in the carriers of the rs7903146CC and rs12255372GG wild types, significant changes in all anthropometric measures were observed, and had better response to both diets.

Association between the rs7903146 Polymorphism in the TCF7L2 Gene and Parameters Derived with Continuous Glucose Monitoring in Individuals without Diabetes

BACKGROUND

The rs7903146-T allele in the transcription factor 7-like 2 (TCF7L2) gene has been associated with impaired pancreatic insulin secretion, enhanced liver glucose production, and an increased risk of type 2 diabetes. Nevertheless, the impact of rs7903146 on daily glucose trajectories remains unclear. Continuous glucose monitoring (CGM) can estimate glycemia and glycemic variability based on consecutive glucose measurements collected over several days. The purpose of the present study was to investigate the associations of rs7903146 with glycemia and glycemic variability in middle-aged participants without diabetes.

METHODS

Complete data from 235 participants without diabetes from the Leiden Longevity Study were available. Participants were divided into two groups based on rs7903146 genotype; rs7903146-CC genotype carriers (N = 123) and rs7903146-CT/TT genotype carriers (N = 112). Validated parameters of glycemia (e.g., mean 24h glucose level) and glycemic variability (e.g., 24h standard deviation) were derived from data collected with a CGM system for a 72-hour period.

RESULTS

The study population was on average 64.7 years old (standard deviation = 5.9) and composed of 49.8% of women. Compared with rs7903146-CC carriers, rs7903146-CT/TT carriers exhibited a trend towards a higher mean 24-hour glucose level (5.21 versus 5.32 mmol/L; p-value = 0.15) and a significantly higher mean nocturnal glucose (3:00am- 6:00am; 4.48 versus 4.67 mmol/L; p-value = 0.03) that was explained for 34.6% by body weight and percentage body fat. No differences in measures of glycemic variability between the genotype groups were observed.

CONCLUSION

Despite limited sample size, our study indicates that the rs7903146-T allele in TCF7L2 was associated with a higher mean nocturnal glucose dependent on body composition, which might suggest that rs7902146 affects liver-specific aspects of glucose metabolism.