Role of TCF7L2 risk variant and dietary fibre intake on incident type 2 diabetes

Healthy dietary pattern is associated with lower glycemia independently of the genetic risk of type 2 diabetes: a cross-sectional study in Finnish men

PURPOSE

Hyperglycemia is affected by lifestyle and genetic factors. We investigated if dietary patterns associate with glycemia in individuals with high or low genetic risk for type 2 diabetes (T2D).

METHODS

Men (n = 1577, 51-81 years) without T2D from the Metabolic Syndrome in Men (METSIM) cohort filled a food-frequency questionnaire and participated in a 2-hour oral glucose tolerance test. Polygenetic risk score (PRS) including 76 genetic variants was used to stratify participants into low or high T2D risk groups. We established two data-driven dietary patterns, termed healthy and unhealthy, and investigated their association with plasma glucose concentrations and hyperglycemia risk.

RESULTS

Healthy dietary pattern was associated with lower fasting and 2-hour plasma glucose, glucose area under the curve, and better insulin sensitivity (Matsuda insulin sensitivity index) and insulin secretion (disposition index) in unadjusted and adjusted models, whereas the unhealthy pattern was not. No interaction was observed between the patterns and PRS on glycemic measures. Healthy dietary pattern was negatively associated with the risk for hyperglycemia in an adjusted model (OR 0.69, 95% CI 0.51-0.95, in the highest tertile), whereas unhealthy pattern was not (OR 1.08, 95% CI 0.79-1.47, in the highest tertile). No interaction was found between diet and PRS on the risk for hyperglycemia (p = 0.69 for healthy diet, p = 0.54 for unhealthy diet).

CONCLUSION

Our findings suggest that healthy diet is associated with lower glucose concentrations and lower risk for hyperglycemia in men with no interaction with the genetic risk.

Genotype-based precision nutrition strategies for the prediction and clinical management of type 2 diabetes mellitus

Globally, type 2 diabetes mellitus (T2DM) is one of the most common metabolic disorders. T2DM physiopathology is influenced by complex interrelationships between genetic, metabolic and lifestyle factors (including diet), which differ between populations and geographic regions. In fact, excessive consumptions of high fat/high sugar foods generally increase the risk of developing T2DM, whereas habitual intakes of plant-based healthy diets usually exert a protective effect. Moreover, genomic studies have allowed the characterization of sequence DNA variants across the human genome, some of which may affect gene expression and protein functions relevant for glucose homeostasis. This comprehensive literature review covers the impact of gene-diet interactions on T2DM susceptibility and disease progression, some of which have demonstrated a value as biomarkers of personal responses to certain nutritional interventions. Also, novel genotype-based dietary strategies have been developed for improving T2DM control in comparison to general lifestyle recommendations. Furthermore, progresses in other omics areas (epigenomics, metagenomics, proteomics, and metabolomics) are improving current understanding of genetic insights in T2DM clinical outcomes. Although more investigation is still needed, the analysis of the genetic make-up may help to decipher new paradigms in the pathophysiology of T2DM as well as offer further opportunities to personalize the screening, prevention, diagnosis, management, and prognosis of T2DM through precision nutrition.

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.

A low-inflammatory diet is associated with a lower incidence of diabetes: role of diabetes-related genetic risk

BACKGROUND

Whether a low-inflammatory diet relates to type 2 diabetes risk remains unclear. We examined the association between a low-inflammatory diet and risk of type 2 diabetes among normoglycemic and prediabetic participants. We also explored whether a low-inflammatory diet modifies genetic risk for type 2 diabetes.

METHODS

Among 142,271 diabetes-free UK Biobank participants (aged 39-72 years), 126,203 were normoglycemic and 16,068 were prediabetic at baseline. Participants were followed for up to 15 years to detect incident type 2 diabetes. At baseline, dietary intake was assessed with a 24-h dietary record. An inflammatory diet index (IDI) was generated based on high-sensitivity C-reactive protein levels and was a weighted sum of 34 food groups (16 anti-inflammatory and 18 pro-inflammatory). Participants were grouped into tertiles corresponding to inflammatory level (low, moderate, and high) based on IDI scores. Prediabetes at baseline was defined as HbA1c 5.7-6.4% in diabetes-free participants. Incident type 2 diabetes and age of onset were ascertained according to the earliest recorded date of type 2 diabetes in the Primary Care and Hospital inpatient data. A diabetes-related genetic risk score (GRS) was calculated using 424 single-nucleotide polymorphisms. Data were analyzed using Cox regression and Laplace regression.

RESULTS

During follow-up (median 8.40 years, interquartile range 6.89 to 11.02 years), 3348 (2.4%) participants in the normoglycemia group and 2496 (15.5%) in the prediabetes group developed type 2 diabetes. Type 2 diabetes risk was lower in normoglycemic (hazard ratio [HR] = 0.71, 95% confidence interval [CI] 0.65, 0.78) and prediabetic (HR = 0.81, 95% CI 0.73, 0.89) participants with low IDI scores compared to those with high IDI scores. A low-inflammatory diet may prolong type 2 diabetes onset by 2.20 (95% CI 1.67, 2.72) years among participants with normoglycemia and 1.11 (95% CI 0.59, 1.63) years among participants with prediabetes. In joint effect analyses, normoglycemic or prediabetes participants with low genetic predisposition to type 2 diabetes and low IDI scores had a significant 74% (HR = 0.26, 95% CI 0.21, 0.32) or 51% (HR = 0.49, 95% CI 0.40, 0.59) reduction in type 2 diabetes risk compared to those with high genetic risk plus high IDI scores. There were significant additive and multiplicative interactions between IDI and GRS in relation to type 2 diabetes risk in the normoglycemia group.

CONCLUSIONS

A low-inflammatory diet is associated with a decreased risk of type 2 diabetes and may delay type 2 diabetes onset among participants with normal blood glucose or prediabetes. A low-inflammatory diet might significantly mitigate the risk of genetic factors on type 2 diabetes development.

Obesity-related parameters in carriers of some BDNF genetic variants may depend on daily dietary macronutrients intake

Some common single-nucleotide polymorphisms of the brain-derived neurotrophic factor (BDNF) gene have been associated not only with the neurodegenerative diseases but also with some eating disorders. The aim of this study was to assess the possible differences in the obesity-related and glucose metabolism parameters between some BDNF genotypes', that may depend on the daily energy and macronutrients intake. In 484 adult participants we performed the anthropometric measurements, body composition analysis, and body fat distribution. The daily dietary intake was assessed using the 3-day food intake diaries. Blood glucose and insulin concentrations were measured at fasting and during oral glucose tolerance tests. Moreover, the visceral adipose tissue/subcutaneous adipose tissue (VAT/SAT) ratio and homeostatic model assessment of insulin resistance were calculated. We noted that participants carrying the GG genotype had lower skeletal muscle mass and fat free mass (FFM) when carbohydrate intake was > 48%, whereas they presented higher fat-free mass (FFM), and surprisingly higher total cholesterol and LDL-C concentrations when daily fiber intake was > 18 g. Moreover, in these subjects we noted higher waist circumference, BMI, and fasting glucose and insulin concentrations, when > 18% of total daily energy intake was delivered from proteins, and higher VAT content and HDL-C concentrations when > 30% of energy intake was derived from dietary fat. Our results suggest that glucose homeostasis and obesity-related parameters in carriers of some common variants of BDNF gene, especially in the GG (rs10835211) genotype carriers, may differ dependently on daily energy, dietary macronutrients and fiber intake.

The role of cereal soluble fiber in the beneficial modulation of glycometabolic gastrointestinal hormones

According to cohort studies, cereal fiber, and whole-grain products might decrease risk for type 2 diabetes (T2DM), inflammatory processes, cancer, and cardiovascular diseases. These associations, mainly affect insoluble, but not soluble cereal fiber. In intervention studies, soluble fiber elicit anti-hyperglycemic and anti-inflammatory short-term effects, partially explained by fermentation to short-chain fatty acids, which acutely counteract insulin resistance and inflammation. ß-glucans lower cholesterol levels and possibly reduce liver fat. Long-term benefits are not yet shown, maybe caused by T2DM heterogeneity, as insulin resistance and fatty liver disease - the glycometabolic points of action of soluble cereal fiber - are not present in every patient. Thus, only some patients might be susceptive to fiber. Also, incretin action in response to fiber could be a relevant factor for variable effects. Thus, this review aims to summarize the current knowledge from human studies on the impact of soluble cereal fiber on glycometabolic gastrointestinal hormones. Effects on GLP-1 appear to be highly contradictory, while these fibers might lower GIP and ghrelin, and increase PYY and CCK. Even though previous results of specific trials support a glycometabolic benefit of soluble fiber, larger acute, and long-term mechanistic studies are needed in order to corroborate the results.

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.

Estimating the Direct Effect between Dietary Macronutrients and Cardiometabolic Disease, Accounting for Mediation by Adiposity and Physical Activity

Assessing the causal effects of individual dietary macronutrients and cardiometabolic disease is challenging because distinguish direct effects from those mediated or confounded by other factors is difficult. To estimate these effects, intake of protein, carbohydrate, sugar, fat, and its subtypes were obtained using food frequency data derived from a Swedish population-based cohort (n~60,000). Data on clinical outcomes (i.e., type 2 diabetes (T2D) and cardiovascular disease (CVD) incidence) were obtained by linking health registry data. We assessed the magnitude of direct and mediated effects of diet, adiposity and physical activity on T2D and CVD using structural equation modelling (SEM). To strengthen causal inference, we used Mendelian randomization (MR) to model macronutrient intake exposures against clinical outcomes. We identified likely causal effects of genetically predicted carbohydrate intake (including sugar intake) and T2D, independent of adiposity and physical activity. Pairwise, serial- and parallel-mediational configurations yielded similar results. In the integrative genomic analyses, the candidate causal variant localized to the established T2D gene TCF7L2. These findings may be informative when considering which dietary modifications included in nutritional guidelines are most likely to elicit health-promoting effects.

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.

Effect of Diet Quality and Genetic Predisposition on Hemoglobin A1c and Type 2 Diabetes Risk: Gene-Diet Interaction Analysis of 357,419 Individuals

OBJECTIVE

To assess the interactions between diet quality and genetic predisposition to incident type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

Between 2006 and 2010, 357,419 participants with genetic and complete dietary data from the UK Biobank were enrolled and prospectively followed up to 2017. The genetic risk score (GRS) was calculated on the basis of 424 variants associated with T2D risk, and a higher GRS indicates a higher genetic predisposition to T2D. The adherence to a healthy diet was assessed by a diet quality score comprising 10 important dietary components, with a higher score representing a higher overall diet quality.

RESULTS

There were 5,663 incident T2D cases documented during an average of 8.1 years of follow-up. A significant negative interaction was observed between the GRS and the diet quality score. After adjusting for major risk factors, per SD increment in the GRS and the diet quality score was associated with a 54% higher and a 9% lower risk of T2D, respectively. A simultaneous increment of 1 SD in both the diet quality score and GRS was additionally associated with a 3% lower T2D risk due to the antagonistic interaction. In categorical analyses, a sharp reduction of 23% in T2D risk associated with a 1-SD increment in the diet quality score was detected among participants in the extremely high GRS group (GRS >95%). We also observed a strong negative interaction between the GRS and the diet quality score on the blood HbA1c level at baseline (P < 0.001).

CONCLUSIONS

The adherence to a healthy diet was associated with more reductions in blood HbA1c levels and subsequent T2D risk among individuals with a higher genetic risk. Our findings support tailoring dietary recommendations to an individual's genetic makeup for T2D prevention.

Genetic susceptibility, family history of diabetes and healthy lifestyle factors in relation to diabetes: A gene-environment interaction analysis in Chinese adults

AIMS/INTRODUCTION

To analyze the associations and interactions of the genetic susceptibility and family history of diabetes with lifestyle factors in relation to diabetes among Chinese adults.

MATERIALS AND METHODS

We constructed a genetic risk score of 34 single-nucleotide polymorphisms in 11,596 participants from Songnan and Youyi communities, Baoshan District, Shanghai, China. We determined a healthy lifestyle by a normal body mass index (<24 kg/m2 ), adequate fruit and vegetable intake (≥4.5 cups/day), never smoked or quit smoking >1 year prior, sufficient physical activity (≥600 metabolic equivalent minutes per week), and a sleep duration of ≥6 to ≤8 h/day. Logistic regression models were used to examine the associations and interactions between heritability and lifestyle on diabetes.

RESULTS

A healthier lifestyle was associated with a lower prevalence of diabetes within any heritable risk groups categorized by the genetic risk score and family history of diabetes. In the combined communities, the odds ratio (95% confidence interval) for diabetes associated with each additional healthy lifestyle factor was 0.83 (0.77-0.89) among participants with a low genetic risk score and 0.86 (0.81-0.91) among participants with a high genetic risk score (Pinteraction  = 0.66). Similar interaction patterns of family history (Pinteraction  = 0.15) and the combination of family history and the genetic risk score with healthy lifestyle (Pinteraction  = 0.55) on diabetes were observed.

CONCLUSIONS

A healthier lifestyle was associated with a significantly lower prevalence of diabetes regardless of heritable risk groups, highlighting the importance of adhering to a healthy lifestyle for diabetes prevention among the entire population.

A review on interplay between obesity, lipoprotein profile and nutrigenetics with selected candidate marker genes of type 2 diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus, a rapidly growing epidemic, and its frequently related complications demand global attention. The two factors commonly attributed to the epidemic are genetic factors and environmental factors. Studies indicate that the genetic makeup at an individual level and the environmental aspects influence the occurrence of the disease. However, there is insufficiency in understanding the mechanisms through which the gene mutations and environmental components individually lead to T2DM. Also, discrepancies have often been noted in the association of gene variants and type 2 diabetes when the gene factor is examined as a sole attribute to the disease.

STUDY

In this review initially, we have focused on the proposed ways through which CAPN10, FABP2, GLUT2, TCF7L2, and ENPP1 variants lead to T2DM along with the inconsistencies observed in the gene-disease association. The article also emphasizes on obesity, lipoprotein profile, and nutrition as environmental factors and how they lead to T2DM. Finally, the main objective is explored, the environment-gene-disease association i.e. the influence of each environmental factor on the aforementioned specific gene-T2DM relationship to understand if the disease-causing capability of the gene variants is exacerbated by environmental influences.

CONCLUSION

We found that environmental factors may influence the gene-disease relationship. Reciprocally, the genetic factors may alter the environment-disease relationship. To precisely conclude that the two factors act synergistically to lead to T2DM, more attention has to be paid to the combined influence of the genetic variants and environmental factors on T2DM occurrence instead of studying the influence of the factors separately.

Association of dietary fiber intake with newly-diagnosed type 2 diabetes mellitus in middle-aged Chinese population

BACKGROUND

Epidemiological evidence concerning dietary fiber on newly-diagnosed type 2 diabetes mellitus (T2DM) is sparse. Therefore, the purpose of this study was to investigate the relationship between dietary fiber intake and newly-diagnosed T2DM in a middle-aged Chinese population.

METHODS

Using data from the Hangzhou Nutrition and Health Survey collected between June 2015 and December 2016, we investigated the associations between dietary patterns and the risk of chronic non- communicable diseases. Anthropometric measurements and samples collection for biochemical assays are conducted by the well-trained staff and nurse, respectively. Multivariable logistic regression analysis was used to analyze the effect of dietary fiber intake on the risk of newly-diagnosed T2DM in crude and adjusted models.

RESULTS

Among 3250 participants, 182 (5.6%) people were identified as newly-diagnosed T2DM. Pearson correlation coefficients revealed a significant inverse association of total dietary fiber with BMI, SBP, DBP, HbA1c and LDL-C in all participants, participants with and without T2DM (P < 0.05). Compared with the study participants in the first quartile (Q1, the lowest consumption)of dietary fiber intake, participants in the fourth quartile (Q4) had a lower prevalence of newly-diagnosed T2DM(OR = 0.70; 95%CI:0.49-1.00; P < 0.05), after adjustment for potential confounders.

CONCLUSIONS

In this middle-aged Chinese population, higher intake of dietary fiber was significantly associated with lower risk of newly-diagnosed T2DM. However, our findings need to be confirmed in future large-scale prospective studies.

Dietary Intake and TCF7L2 rs7903146 T Allele Are Associated with Elevated Blood Glucose Levels in Healthy Individuals

INTRODUCTION

Type 2 diabetes (T2D) is a leading cause of global mortality with diet and genetics being considered amongst the most significant risk factors. Recently, studies have identified a single polymorphism of the TCF7L2 gene (rs7903146) as the most important genetic contributor. However, no studies have explored this factor in a healthy population and using glycated haemoglobin (HbA1c), which is a reliable long-term indicator of glucose management. This study investigates the association of the genetic polymorphism rs7903146 and dietary intake with T2D risk in a population free of metabolic disease.

METHODS

T2D risk was assessed using HbA1c plasma concentrations and dietary intake via a validated Food Frequency Questionnaire in 70 healthy participants.

RESULTS

T allele carriers had higher HbA1c levels than the CC group (32.4 ± 7.2 mmol/mol vs. 30.3 ± 7.6 mmol/mol, p = 0.005). Multiple regression reported associations between diet, genotype and HbA1c levels accounting for 37.1% of the variance in HbA1c (adj. R2 = 0.371, p < 0.001). The following macronutrients, expressed as a median percentage of total energy intake (TEI) in the risk group, were positively associated with HbA1c concentration: carbohydrate (≥39% TEI, p < 0.005; 95% CI 0.030/0.130) protein (≥21% TEI, p < 0.005, 95% CI 0.034/0.141), monounsaturated (≥15% TEI p < 0.05, 95% CI 0.006/0.163) and saturated fatty acids (≥13% TEI; p < 0.05, 95% CI 0.036/0.188).

CONCLUSION

Carriers of the T allele showed significantly higher levels of HbA1c compared to non-carriers. Dietary intake affected T2D risk to a greater extent than genetic effects of TCF7L2rs7903146 genotype in a healthy population. The study focus on healthy individuals is beneficial due to the applicability of findings for T2D screening.

Fruit intake, genetic risk and type 2 diabetes: a population-based gene-diet interaction analysis

PURPOSE

Whether the association between fruit and type 2 diabetes (T2D) is modified by the genetic predisposition of T2D was yet elucidated. The current study is meant to examine the gene-dietary fruit intake interactions in the risk of T2D and related glycemic traits.

METHODS

We performed a cross-sectional study in 11,657 participants aged ≥ 40 years from a community-based population in Shanghai, China. Fruit intake information was collected by a validated food frequency questionnaire by asking the frequency of consumption of typical food items over the previous 12 months. T2D-genetic risk score (GRS) was constructed by 34 well established T2D common variants in East Asians. The risk of T2D, fasting, 2 h-postprandial plasma glucose, and glycated hemoglobin A1c associated with T2D-GRS and each individual single nucleotide polymorphisms (SNPs) were tested.

RESULTS

The risk of T2D associated with each 1-point of T2D-GRS was gradually decreased from the lower fruit intake level (< 1 times/week) [the odds ratio (OR) and 95% confidence interval (CI) was 1.10 (1.07-1.13)], to higher levels (1-3 and > 3 times/week) [the corresponding ORs and 95% CIs were 1.08 (1.05-1.10) and 1.07 (1.05-1.08); P for interaction = 0.04]. Analyses for associations with fasting, 2 h-postprandial plasma glucose and glycated hemoglobin A1c demonstrated consistent tendencies (all P for interaction ≤ 0.03). The inverse associations of fruit intake with risk of T2D and glucose traits were more prominent in the higher T2D-GRS tertile.

CONCLUSIONS

Fruit intakes interact with the genetic predisposition of T2D on the risk of diabetes and related glucose metabolic traits. Fruit intake alleviates the association between genetic predisposition of T2D and the risk of diabetes; the association of fruit intake with a lower risk of diabetes was more prominent in population with a stronger genetic predisposition of T2D.

A Preliminary Study Showing the Impact of Genetic and Dietary Factors on GC-MS-Based Plasma Metabolome of Patients with and without PROX1-Genetic Predisposition to T2DM up to 5 Years Prior to Prediabetes Appearance

Risk factors for type 2 diabetes mellitus (T2DM) consist of a combination of an unhealthy, imbalanced diet and genetic factors that may interact with each other. Single nucleotide polymorphism (SNP) in the prospero homeobox 1 (PROX1) gene is a strong genetic susceptibility factor for this metabolic disorder and impaired β-cell function. As the role of this gene in T2DM development remains unclear, novel approaches are needed to advance the understanding of the mechanisms of T2DM development. Therefore, in this study, for the first time, postprandial changes in plasma metabolites were analysed by GC–MS in nondiabetic men with different PROX1 genotypes up to 5 years prior to prediabetes appearance. Eighteen contestants (12 with high risk (HR) and 6 with low risk (LR) genotype) participated in high-carbohydrate (HC) and normo-carbohydrate (NC) meal-challenge tests. Our study concluded that both meal-challenge tests provoked changes in 15 plasma metabolites (amino acids, carbohydrates, fatty acids and others) in HR, but not LR genotype carriers. Postprandial changes in the levels of some of the detected metabolites may be a source of potential specific early disturbances possibly associated with the future development of T2DM. Thus, accurate determination of these metabolites can be important for the early diagnosis of this metabolic disease.

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.

The role of transcription factor 7-like 2 in metabolic disorders

Transcription factor 7-like 2 (TCF7L2), a member of the T cell factor/lymphoid enhancer factor family, generally forms a complex with β-catenin to regulate the downstream target genes as an effector of the canonical Wnt signalling pathway. TCF7L2 plays a vital role in various biological processes and functions in many organs and tissues, including the liver, islet and adipose tissues. Further, TCF7L2 down-regulates hepatic gluconeogenesis and promotes lipid accumulation. In islets, TCF7L2 not only affects the insulin secretion of the β-cells but also has an impact on other cells. In addition, TCF7L2 influences adipogenesis in adipose tissues. Thus, an out-of-control TCF7L2 expression can result in metabolic disorders. The TCF7L2 gene is composed of 17 exons, generating 13 different transcripts, and has many single-nucleotide polymorphisms (SNPs). The discovery that these SNPs have an impact on the risk of type 2 diabetes (T2D) has attracted thorough investigations in the study of TCF7L2. Apart from T2D, TCF7L2 SNPs are also associated with type 1, posttransplant and other types of diabetes. Furthermore, TCF7L2 variants affect the progression of other disorders, such as obesity, cancers, metabolic syndrome and heart diseases. Finally, the interaction between TCF7L2 variants and diet also needs to be investigated.

Whole Genome Interpretation for a Family of Five

Although best practices have emerged on how to analyse and interpret personal genomes, the utility of whole genome screening remains underdeveloped. A large amount of information can be gathered from various types of analyses via whole genome sequencing including pathogenicity screening, genetic risk scoring, fitness, nutrition, and pharmacogenomic analysis. We recognize different levels of confidence when assessing the validity of genetic markers and apply rigorous standards for evaluation of phenotype associations. We illustrate the application of this approach on a family of five. By applying analyses of whole genomes from different methodological perspectives, we are able to build a more comprehensive picture to assist decision making in preventative healthcare and well-being management. Our interpretation and reporting outputs provide input for a clinician to develop a healthcare plan for the individual, based on genetic and other healthcare data.

Genetically Guided Mediterranean Diet for the Personalized Nutritional Management of Type 2 Diabetes Mellitus

The current consensus for the prevention and management of type 2 diabetes mellitus (T2DM) is that high-quality diets and adherence to a healthy lifestyle provide significant health benefits. Remarkably, however, there is little agreement on the proportions of macronutrients in the diet that should be recommended to people suffering from pre-diabetes or T2DM. We herein discuss emerging evidence that underscores the importance of gene-diet interactions in the improvement of glycemic biomarkers in T2DM. We propose that we can achieve better glycemic control in T2DM patients by coupling Mediterranean diets to genetic information as a predictor for optimal diet macronutrient composition in a personalized manner. We provide evidence to support this concept by presenting a case study of a T2DM patient who achieved rapid glycemic control when adhered to a personalized, genetically-guided Mediterranean Diet.

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.

Interactive associations of the INAFM2 rs67839313 variant and egg consumption with type 2 diabetes mellitus and fasting blood glucose in a Chinese population: A family-based study

BACKGROUND

INAFM2 rs67839313 was associated with type 2 diabetes (T2DM) in Japanese populations but not in other populations. We aimed to validate the association of rs67839313 with T2DM and explore interactive associations of INAFM2 rs67839313 and egg consumption with T2DM and fasting blood glucose (FBG) in a Chinese population.

METHODS

In total, 7175 participants (4202 T2DM cases) from 3980 families were included and categorized into two groups (<4 and ≥4 eggs/week) according to the median egg consumption. Multilevel logistic regression and linear regression models were performed to estimate the genetic associations of rs67839313 with T2DM and FBG, respectively. The crossproduct term between the variant and egg was included in the models for interaction analysis.

RESULTS

We found that rs67839313_T was associated with an increased risk of T2DM (1.22 [95% CI: 1.17-1.27], P < 0.001). Among individuals with the rs67839313_T genotype, those with egg consumption <4/week (1.37 [1.25-1.51]) had a higher T2DM risk than those with egg consumption ≥4/week (1.17 [1.11-1.23]). A significant interactive effect between rs67839313_T and egg consumption on T2DM risk was identified (P = 0.008). Moreover, among participants without T2DM, rs67839313_T was associated with FBG, with a 0.188 mmol/l increase and a 0.152 mmol/l decrease among those consuming <4 eggs/week and ≥4 eggs/week, respectively. The interaction between rs67839313_T and egg consumption was observed to be significantly associated with FBG (P = 0.003).

CONCLUSIONS

INAFM2 rs67839313_T was associated with increased T2DM risk and FBG levels in Chinese individuals, and consuming more eggs may eliminate the associated genetic risk. This finding has important implications for understanding the genetic pathogenesis of T2DM and for the precision nutrition management of T2DM.

TCF7L2 rs7903146 polymorphism modulates the association between adherence to a Mediterranean diet and the risk of gestational diabetes mellitus

OBJECTIVE

There is sparse evidence for the impact of gene-diet interaction on gestational diabetes mellitus (GDM) onset. Recent findings have shown that late first-trimester high adherence to a Mediterranean diet (MedDiet) pattern is associated with a GDM risk reduction. The aim of this study was to investigate if this effect could be modulated by TCF7L2 rs7903146 polymorphism.Research design and methods: A total of 874 pregnant women participants in the St Carlos GDM prevention study, were stratified into three groups defined as "High,5-6 on targets", "Moderate, 2-4 on targets" or "Low, 0-1 on targets" adherence to Mediterranean diet according to late first-trimester compliance with six food targets: >12 servings/week of vegetables, >12 pieces/week of fruits, <2 servings/week of juice, >3 servings/week of nuts, >6 days/week and >40 mL/day consumption of extra virgin olive oil. All patients were genotyped for rs7903146 using Taqman technology.

RESULTS

Logistic regression analysis revealed that the risk of developing GDM in those with high adherence versus low adherence was significantly reduced only in carriers of the T-allele (CT + TT), with an adjusted odds ratio of 0.15 (95% CI:0.05-0.48). This effect was not observed in CC carriers. Interaction analysis yielded significant rs7903146-MedDiet interaction in GDM risk (p < 0.03).

CONCLUSIONS

Women carrying the rs7903146 T-allele who highly adhere to a MedDiet early in pregnancy have lower risk of developing GDM than CC carriers. This reinforces the importance of identifying patients at risk of GDM who would be especially sensitive to nutritional interventions based on their genetic characteristics.

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.

The Role of Nutrition in the Prevention and Intervention of Type 2 Diabetes

Type 2 diabetes (T2D) is a rapidly growing epidemic, which leads to increased mortality rates and health care costs. Nutrients (namely, carbohydrates, fat, protein, mineral substances, and vitamin), sensing, and management are central to metabolic homeostasis, therefore presenting a leading factor contributing to T2D. Understanding the comprehensive effects and the underlying mechanisms of nutrition in regulating glucose metabolism and the interactions of diet with genetics, epigenetics, and gut microbiota is helpful for developing new strategies to prevent and treat T2D. In this review, we discuss different mechanistic pathways contributing to T2D and then summarize the current researches concerning associations between different nutrients intake and glucose homeostasis. We also explore the possible relationship between nutrients and genetic background, epigenetics, and metagenomics in terms of the susceptibility and treatment of T2D. For the specificity of individual, precision nutrition depends on the person’s genotype, and microbiota is vital to the prevention and intervention of T2D.

A comparison of a ketogenic diet with a LowGI/nutrigenetic diet over 6 months for weight loss and 18-month follow-up

BACKGROUND

Obesity and its related metabolic disturbances represent a huge health burden on society. Many different weight loss interventions have been trialled with mixed efficacy, as demonstrated by the large number of individuals who regain weight upon completion of such interventions. There is evidence that the provision of genetic information may enhance long-term weight loss, either by increasing dietary adherence or through underlying biological mechanisms.

METHODS

The investigators followed 114 overweight and obese subjects from a weight loss clinic in a 2-stage process. 1) A 24-week dietary intervention. The subjects self-selected whether to follow a standardized ketogenic diet (n = 53), or a personalised low-glycemic index (GI) nutrigenetic diet utilising information from 28 single nucleotide polymorphisms (n = 61). 2) After the 24-week diet period, the subjects were monitored for an additional 18 months using standard guidelines for the Keto group vs standard guidelines modified by nutrigenetic advice for the low-Glycaemic Index nutrigenetic diet (lowGI/NG) group.

RESULTS

After 24 weeks, the keto group lost more weight: - 26.2 ± 3.1 kg vs - 23.5 ± 6.4 kg (p = 0.0061). However, at 18-month follow up, the subjects in the low-GI nutrigenetic diet had lost significantly more weight (- 27.5 ± 8.9 kg) than those in the ketogenic diet who had regained some weight (- 19.4 ± 5.0 kg) (p < 0.0001). Additionally, after the 24-week diet and 18-month follow up the low-GI nutrigenetic diet group had significantly greater (p < 0.0001) improvements in total cholesterol (ketogenic - 35.4 ± 32.2 mg/dl; low-GI nutrigenetic - 52.5 ± 24.3 mg/dl), HDL cholesterol (ketogenic + 4.7 ± 4.5 mg/dl; low-GI nutrigenetic + 11.9 ± 4.1 mg/dl), and fasting glucose (ketogenic - 13.7 ± 8.4 mg/dl; low-GI nutrigenetic - 24.7 ± 7.4 mg/dl).

CONCLUSIONS

These findings demonstrate that the ketogenic group experienced enhanced weight loss during the 24-week dietary intervention. However, at 18-month follow up, the personalised nutrition group (lowGI/NG) lost significantly more weight and experienced significantly greater improvements in measures of cholesterol and blood glucose. This suggests that personalising nutrition has the potential to enhance long-term weight loss and changes in cardiometabolic parameters.

TRIAL REGISTRATION

NCT04330209, Registered 01/04/2020, retrospectively registered.

Genes and Diet in the Prevention of Chronic Diseases in Future Generations

Nutrition is a modifiable key factor that is able to interact with both the genome and epigenome to influence human health and fertility. In particular, specific genetic variants can influence the response to dietary components and nutrient requirements, and conversely, the diet itself is able to modulate gene expression. In this context and the era of precision medicine, nutrigenetic and nutrigenomic studies offer significant opportunities to improve the prevention of metabolic disturbances, such as Type 2 diabetes, gestational diabetes, hypertension, and cardiovascular diseases, even with transgenerational effects. The present review takes into account the interactions between diet, genes and human health, and provides an overview of the role of nutrigenetics, nutrigenomics and epigenetics in the prevention of non-communicable diseases. Moreover, we focus our attention on the mechanism of intergenerational or transgenerational transmission of the susceptibility to metabolic disturbances, and underline that the reversibility of epigenetic modifications through dietary intervention could counteract perturbations induced by lifestyle and environmental factors.

Gene-lifestyle interaction on risk of type 2 diabetes: A systematic review

The pathophysiological influence of gene-lifestyle interactions on the risk to develop type 2 diabetes (T2D) is currently under intensive research. This systematic review summarizes the evidence for gene-lifestyle interactions regarding T2D incidence. MEDLINE, EMBASE, and Web of Science were systematically searched until 31 January 2019 to identify publication with (a) prospective study design; (b) T2D incidence; (c) gene-diet, gene-physical activity, and gene-weight loss intervention interaction; and (d) population who are healthy or prediabetic. Of 66 eligible publications, 28 reported significant interactions. A variety of different genetic variants and dietary factors were studied. Variants at TCF7L2 were most frequently investigated and showed interactions with fiber and whole grain on T2D incidence. Further gene-diet interactions were reported for, eg, a western dietary pattern with a T2D-GRS, fat and carbohydrate with IRS1 rs2943641, and heme iron with variants of HFE. Physical activity showed interaction with HNF1B, IRS1, PPARγ, ADRA2B, SLC2A2, and ABCC8 variants and weight loss interventions with ENPP1, PPARγ, ADIPOR2, ADRA2B, TNFα, and LIPC variants. However, most findings represent single study findings obtained in European ethnicities. Although some interactions have been reported, their conclusiveness is still low, as most findings were not yet replicated across multiple study populations.

Gene-diet quality interactions on haemoglobin A1c and type 2 diabetes risk: The Airwave Health Monitoring Study

INTRODUCTION

Type 2 diabetes (T2D) is multifactorial involving lifestyle, environmental and genetic risk factors. This study aims to investigate the impact of genetic interactions with alcohol and diet quality on glycated haemoglobin A1c (HbA1c) independent of obesity, in a British population.

METHODS

Cross-sectional study of 14 089 white British participants from Airwave Health Monitoring Study and a subsample of 3733 participants with dietary data. A T2D genetic risk score (GRS) was constructed, and its interactions with diet on HbA1c were assessed.

RESULTS

GRS was associated with a higher HbA1c% (β = 0.03, P < 0.0001) and a higher risk of prediabetes (OR = 1.09, P < 0.0001) and T2D (OR = 1.14, P = 0.006). The genetic effect on HbA1c% was significantly higher in obese participants (β = 1.88, P interaction = 0.03). A high intake of wholegrain attenuated the effect on HbA1c% in high-risk individuals P interaction = 0.04.

CONCLUSION

The genetic effect on HbA1c was almost doubled in obese individuals, compared with those with a healthy weight, and independent of weight, there was a modest offset on HbA1c in high-genetic-risk individuals consuming a diet high in wholegrain. This supports the importance of a healthy diet high in wholegrains and along with maintaining a healthy weight in controlling HbA1c among high-genetic-risk groups.

Nutrigenetics, epigenetics and gestational diabetes: consequences in mother and child

Gestational Diabetes Mellitus (GDM) is the most common metabolic condition during pregnancy and may result in short- and long-term complications for both mother and offspring. The complexity of phenotypic outcomes seems influenced by genetic susceptibility, nutrient-gene interactions and lifestyle interacting with clinical factors. There is strong evidence that not only the adverse genetic background but also the epigenetic modifications in response to nutritional and environmental factors could influence the maternal hyperglycemia in pregnancy and the foetal metabolic programming. In this view, the correlation between epigenetic modifications and their transgenerational effects represents a very interesting field of study. The present review gives insight into the role of gene variants and their interactions with nutrients in GDM. In addition, we provide an overview of the epigenetic changes and their role in the maternal-foetal transmission of chronic diseases. Overall, the knowledge of epigenetic modifications induced by an adverse intrauterine and perinatal environment could shed light on the potential pathophysiological mechanisms of long-term disease development in the offspring and provide useful tools for their prevention.

Dietary and genetic risk scores and incidence of type 2 diabetes

Background

Both lifestyle and genetic predisposition determine the development of type 2 diabetes (T2D), and studies have indicated interactions between specific dietary components and individual genetic variants. However, it is unclear whether the importance of overall dietary habits, including T2D-related food intakes, differs depending on genetic predisposition to T2D. We examined interaction between a genetic risk score for T2D, constructed from 48 single nucleotide polymorphisms identified in genome-wide association studies, and a diet risk score of four foods consistently associated with T2D in epidemiological studies (processed meat, sugar-sweetened beverages, whole grain and coffee). In total, 25,069 individuals aged 45–74 years with genotype information and without prevalent diabetes from the Malmö Diet and Cancer cohort (1991–1996) were included. Diet data were collected with a modified diet history method.

Results

During 17-year follow-up, 3588 incident T2D cases were identified. Both the diet risk score (HR in the highest risk category 1.40; 95% CI 1.26, 1.58; P trend = 6 × 10⁻¹⁰) and the genetic risk score (HR in the highest tertile of the genetic risk score 1.67; 95% CI 1.54, 1.81; P trend = 7 × 10⁻³⁵) were associated with increased incidence of T2D. No significant interaction between the genetic risk score and the diet risk score (P = 0.83) or its food components was observed. The highest risk was seen among the 6% of the individuals with both high genetic and dietary risk scores (HR 2.49; 95% CI 2.06, 3.01).

Conclusions

The findings thus show that both genetic heredity and dietary habits previously associated with T2D add to the risk of T2D, but they seem to act in an independent fashion, with the consequence that all individuals, whether at high or low genetic risk, would benefit from favourable food choices.

Electronic supplementary material

The online version of this article (10.1186/s12263-018-0599-1) contains supplementary material, which is available to authorized users.

Reversing the tide - diagnosis and prevention of T2DM in populations of African descent

Populations of African descent are at the forefront of the worldwide epidemic of type 2 diabetes mellitus (T2DM). The burden of T2DM is amplified by diagnosis after preventable complications of the disease have occurred. Earlier detection would result in a reduction in undiagnosed T2DM, more accurate statistics, more informed resource allocation and better health. An underappreciated factor contributing to undiagnosed T2DM in populations of African descent is that screening tests for hyperglycaemia, specifically, fasting plasma glucose and HbA_1c, perform sub-optimally in these populations. To offset this problem, combining tests or adding glycated albumin (a nonfasting marker of glycaemia), might be the way forward. However, differences in diet, exercise, BMI, environment, gene-environment interactions and the prevalence of sickle cell trait mean that neither diagnostic tests nor interventions will be uniformly effective in individuals of African, Caribbean or African-American descent. Among these three populations of African descent, intensive lifestyle interventions have been reported in only the African-American population, in which they have been found to provide effective primary prevention of T2DM but not secondary prevention. Owing to a lack of health literacy and poor glycaemic control in Africa and the Caribbean, customized lifestyle interventions might achieve both secondary and primary prevention. Overall, diagnosis and prevention of T2DM requires innovative strategies that are sensitive to the diversity that exists within populations of African descent.

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.

Lifestyle precision medicine: the next generation in type 2 diabetes prevention?

The driving force behind the current global type 2 diabetes epidemic is insulin resistance in overweight and obese individuals. Dietary factors, physical inactivity, and sedentary behaviors are the major modifiable risk factors for obesity. Nevertheless, many overweight/obese people do not develop diabetes and lifestyle interventions focused on weight loss and diabetes prevention are often ineffective. Traditionally, chronically elevated blood glucose concentrations have been the hallmark of diabetes; however, many individuals will either remain 'prediabetic' or regress to normoglycemia. Thus, there is a growing need for innovative strategies to tackle diabetes at scale. The emergence of biomarker technologies has allowed more targeted therapeutic strategies for diabetes prevention (precision medicine), though largely confined to pharmacotherapy. Unlike most drugs, lifestyle interventions often have systemic health-enhancing effects. Thus, the pursuance of lifestyle precision medicine in diabetes seems rational. Herein, we review the literature on lifestyle interventions and diabetes prevention, describing the biological systems that can be characterized at scale in human populations, linking them to lifestyle in diabetes, and consider some of the challenges impeding the clinical translation of lifestyle precision medicine.

Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes: systematic review and findings from European Prospective Investigation into Cancer (EPIC)-InterAct

Background: Gene-diet interactions have been reported to contribute to the development of type 2 diabetes (T2D). However, to our knowledge, few examples have been consistently replicated to date.Objective: We aimed to identify existing evidence for gene-macronutrient interactions and T2D and to examine the reported interactions in a large-scale study.Design: We systematically reviewed studies reporting gene-macronutrient interactions and T2D. We searched the MEDLINE, Human Genome Epidemiology Network, and WHO International Clinical Trials Registry Platform electronic databases to identify studies published up to October 2015. Eligibility criteria included assessment of macronutrient quantity (e.g., total carbohydrate) or indicators of quality (e.g., dietary fiber) by use of self-report or objective biomarkers of intake. Interactions identified in the review were subsequently examined in the EPIC (European Prospective Investigation into Cancer)-InterAct case-cohort study (n = 21,148, with 9403 T2D cases; 8 European countries). Prentice-weighted Cox regression was used to estimate country-specific HRs, 95% CIs, and P-interaction values, which were then pooled by random-effects meta-analysis. A primary model was fitted by using the same covariates as reported in the published studies, and a second model adjusted for additional covariates and estimated the effects of isocaloric macronutrient substitution.Results: Thirteen observational studies met the eligibility criteria (n < 1700 cases). Eight unique interactions were reported to be significant between macronutrients [carbohydrate, fat, saturated fat, dietary fiber, and glycemic load derived from self-report of dietary intake and circulating n-3 (ω-3) polyunsaturated fatty acids] and genetic variants in or near transcription factor 7-like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) (P-interaction < 0.05). We found no evidence of interaction when we tried to replicate previously reported interactions. In addition, no interactions were detected in models with additional covariates.Conclusions: Eight gene-macronutrient interactions were identified for the risk of T2D from the literature. These interactions were not replicated in the EPIC-InterAct study, which mirrored the analyses undertaken in the original reports. Our findings highlight the importance of independent replication of reported interactions.

Gene-Diet Interactions in Type 2 Diabetes: The Chicken and Egg Debate

Consistent evidence from both experimental and human studies indicates that Type 2 diabetes mellitus (T2DM) is a complex disease resulting from the interaction of genetic, epigenetic, environmental, and lifestyle factors. Nutrients and dietary patterns are important environmental factors to consider in the prevention, development and treatment of this disease. Nutritional genomics focuses on the interaction between bioactive food components and the genome and includes studies of nutrigenetics, nutrigenomics and epigenetic modifications caused by nutrients. There is evidence supporting the existence of nutrient-gene and T2DM interactions coming from animal studies and family-based intervention studies. Moreover, many case-control, cohort, cross-sectional cohort studies and clinical trials have identified relationships between individual genetic load, diet and T2DM. Some of these studies were on a large scale. In addition, studies with animal models and human observational studies, in different countries over periods of time, support a causative relationship between adverse nutritional conditions during in utero development, persistent epigenetic changes and T2DM. This review provides comprehensive information on the current state of nutrient-gene interactions and their role in T2DM pathogenesis, the relationship between individual genetic load and diet, and the importance of epigenetic factors in influencing gene expression and defining the individual risk of T2DM.

Investigation of gene-diet interactions in the incretin system and risk of type 2 diabetes: the EPIC-InterAct study

AIMS/HYPOTHESIS

The gut incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) have a major role in the pathophysiology of type 2 diabetes. Specific genetic and dietary factors have been found to influence the release and action of incretins. We examined the effect of interactions between seven incretin-related genetic variants in GIPR, KCNQ1, TCF7L2 and WFS1 and dietary components (whey-containing dairy, cereal fibre, coffee and olive oil) on the risk of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct study.

METHODS

The current case-cohort study included 8086 incident type 2 diabetes cases and a representative subcohort of 11,035 participants (median follow-up: 12.5 years). Prentice-weighted Cox proportional hazard regression models were used to investigate the associations and interactions between the dietary factors and genes in relation to the risk of type 2 diabetes.

RESULTS

An interaction (p = 0.048) between TCF7L2 variants and coffee intake was apparent, with an inverse association between coffee and type 2 diabetes present among carriers of the diabetes risk allele (T) in rs12255372 (GG: HR 0.99 [95% CI 0.97, 1.02] per cup of coffee; GT: HR 0.96 [95% CI 0.93, 0.98]); and TT: HR 0.93 [95% CI 0.88, 0.98]). In addition, an interaction (p = 0.005) between an incretin-specific genetic risk score and coffee was observed, again with a stronger inverse association with coffee in carriers with more risk alleles (0-3 risk alleles: HR 0.99 [95% CI 0.94, 1.04]; 7-10 risk alleles: HR 0.95 [95% CI 0.90, 0.99]). None of these associations were statistically significant after correction for multiple testing.

CONCLUSIONS/INTERPRETATION

Our large-scale case-cohort study provides some evidence for a possible interaction of TCF7L2 variants and an incretin-specific genetic risk score with coffee consumption in relation to the risk of type 2 diabetes. Further large-scale studies and/or meta-analyses are needed to confirm these interactions in other populations.

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.

Putting the Genome in Context: Gene-Environment Interactions in Type 2 Diabetes

The genome is often the conduit through which environmental exposures convey their effects on health and disease. Whilst not all diseases act by directly perturbing the genome, the phenotypic responses are often genetically determined. Hence, whilst diseases are often defined has having differing degrees of genetic determination, genetic and environmental factors are, with few exceptions, inseparable features of most diseases, not least type 2 diabetes. It follows that to optimize diabetes, prevention and treatment will require that the etiological roles of genetic and environmental risk factors be jointly considered. As we discuss here, studies focused on quantifying gene-environment and gene-treatment interactions are gathering momentum and may eventually yield data that helps guide health-related choices and medical interventions for type 2 diabetes and other complex diseases.

Several type 2 diabetes-associated variants in genes annotated to WNT signaling interact with dietary fiber in relation to incidence of type 2 diabetes

Background

TCF7L2 is a central transcription factor in the canonical wingless-type MMTV integration site (WNT) signaling pathway, and genetic variants in TCF7L2 have been found to interact with dietary fiber intake on type 2 diabetes risk. Here, we investigate whether other type 2 diabetes genes could be involved in the WNT signaling pathway and whether variants in such genes might interact with dietary fiber on type 2 diabetes incidence.

Results

We included 26,905 individuals without diabetes from the Malmö Diet and Cancer Study cohort. Diet data was collected at baseline using a food frequency questionnaire, a 7-day food record, and an interview. Altogether, 51 gene loci were analyzed for putative links to WNT signaling. Over a mean follow-up period of 14.7 years, 3132 incident cases of type 2 diabetes were recorded. Seven genes (nine single nucleotide polymorphisms (SNPs)) were annotated as involved in WNT signaling including TCF7L2 (rs7903146 and rs12255372), HHEX (rs1111875), HNF1A (rs7957197), NOTCH2 (rs10923931), TLE4 (rs13292136), ZBED3 (rs4457053), and PPARG (rs1801282 and rs13081389). SNPs in TCF7L2, NOTCH2, and ZBED3 showed significant interactions with fiber intake on type 2 diabetes incidence (P_interaction = 0.034, 0.005, 0.017, and 0.002, respectively). The magnitude of the association between the TCF7L2 risk allele and incident type 2 diabetes increased from the lowest to the highest quintiles of fiber intake. Higher fiber associated with lower type 2 diabetes risk only among risk allele carriers of the NOTCH2 variant and homozygotes of the risk allele of the ZBED3 variant.

Conclusions

Our results suggest that several type 2 diabetes susceptibility SNPs in genes involved in WNT signaling may interact with dietary fiber intake on type 2 diabetes incidence.

Electronic supplementary material

The online version of this article (doi:10.1186/s12263-016-0524-4) contains supplementary material, which is available to authorized users.

Contribution of ENPP1, TCF7L2, and FTO polymorphisms to type 2 diabetes in mixed ancestry ethnic population of South Africa

BACKGROUND

Transcription factor 7-like 2 gene (TCF7L2), fat mass and obesity-associated gene (FTO), and ectonucleotide pyrophosphatase/phosphodiesterase gene (ENPP1) are known risk loci for type 2 diabetes (T2DM) mostly in European populations.

OBJECTIVES

To assess the association of these genes with T2DM risk in a South African mixed-ancestry population.

METHODS

Five hundred and sixty six participants were genotyped for ENPP1-rs997509 and -rs1044498, FTO-9941349 and -rs3751812, TCF7L2-rs12255372 and -rs7903146 polymorphisms using Taqman genotyping assays and validated by automated sequencing to assess the association of the polymorphisms with cardiometabolic traits.

RESULTS

In logistic regression models adjusted for age, sex, body mass index (BMI) and insulin resistance, minor allele of rs997509 was associated with a higher risk of prevalent T2DM under a recessive model [odd ratio 4.60 (95% confidence interval: 1.07 to 19.86); p = 0.040].Under additive model, the rs7903146 [1.43 (1.00 to 2.04); p= 0.053] and rs9941349 [1.43 (1.00 to 2.04); p = 0.052] minor alleles showed marginally significant associations with a high risk of T2DM. However, only the rs7903146 alleles (p=0.011) and genotypes (p=0.025) distributions were statistically significantly different between diabetic and non-diabetic individuals.

CONCLUSION

Our findings demonstrate that ENPP1, TCF7L2, and FTO may predispose to T2DM in the mixed-ancestry population.

Do personality traits moderate the manifestation of type 2 diabetes genetic risk?

OBJECTIVE

To test whether personality traits moderate type 2 diabetes (T2D) genetic risk.

METHODS

Using a large community-dwelling sample (n=837, Mage=69.59±0.85years, 49% males) we fitted a series of linear regression models predicting glycated haemoglobin (HbA1c) from T2D polygenic risk - aggregation of small individual effects of a large number of single nucleotide polymorphisms (SNPs) - and five personality traits. We tested the main effects of personality traits and their interactions with T2D polygenic risk score, controlling for age and sex. The models in the final set were adjusted for cognitive ability, highest educational qualification, and occupational class.

RESULTS

Lower levels of openness were associated with heightened levels of HbA1c (β=-0.014, p=.032). There was a significant interaction between T2D polygenic risk score and agreeableness: lower agreeableness was related to a stronger association between T2D polygenic risk and HbA1c (β=-0.08, p=.021). In the model adjusted for cognitive ability, the main effect of openness was not significant (β=-0.08, p=.057). The interaction between agreeableness and T2D polygenic risk was still present after controlling for cognitive ability and socioeconomic status indicators, and the interaction between conscientiousness and polygenic risk score was also significant: lower conscientiousness was associated with a stronger association between T2D polygenic risk and HbA1c levels (β=0.09, p=.04).

CONCLUSIONS

Personality may be associated with markers of diabetes, and may moderate the expression of its genetic risk.

TCF7L2 type 2 diabetes risk variant, lifestyle factors, and incidence of prostate cancer

BACKGROUND

Variation in transcription factor 7-like 2 (TCF7L2), the strongest genetic risk factor for type 2 diabetes (T2D), may play a role in prostate cancer (PCa) depending on lifestyle factors. The aims of this study were to determine if TCF7L2 rs7903146 is associated with risk of PCa and if the association is modified by lifestyle factors independently of T2D status.

METHODS

We prospectively followed 8,558 men in the Malmö Diet and Cancer Study from baseline 1991-1996 until end of 2009. Cox regression models were used to assess the association between rs7903146 T2D-risk allele (T) and PCa. Effect modification by incident T2D status, fasting glucose levels, dietary, and lifestyle risk factors were tested.

RESULTS

During follow-up 855 incident PCa cases were registered. We observed a non-significant tendency for the TCF7L2 variant to associate with higher risk of PCa, which was unaffected by adjustment for incident T2D (HR = 1.24; 95% CI: 0.96, 1.60; P = 0.079) but more pronounced among subjects who developed T2D (HR = 1.91, 95% CI: 0.88, 4.14; P = 0.064). In a sub-sample of hyperglycemic men we observed an increased risk of PCa among T-allele carriers (HR = 2.72, 95% CI: 1.22, 6.04; P = 0.014; P(interaction)  = 0.056). T-allele carriers with higher number of lifestyle risk factors had an increased risk of PCa (P(interaction)  = 0.006).

CONCLUSIONS

We found no independent association between TCF7L2 rs7903146 and PCa risk. However, among hyperglycemic men we observed that the risk allele may increase risk of PCa. The association between rs7903146 and PCa risk may also be modified by lifestyle factors.

Gene-carbohydrate and gene-fiber interactions and type 2 diabetes in diverse populations from the National Health and Nutrition Examination Surveys (NHANES) as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study

Background

Both environmental and genetic factors impact type 2 diabetes (T2D). To identify such modifiers, we genotyped 15 T2D-associated variants from genome-wide association studies (GWAS) in 6,414 non-Hispanic whites, 3,073 non-Hispanic blacks, and 3,633 Mexican American participants from the National Health and Nutrition Examination Surveys (NHANES) and evaluated interactions between these variants and carbohydrate intake and fiber intake.

Results

We calculated a genetic risk score (GRS) with the 15 SNPs. The odds ratio for T2D with each GRS point was 1.10 (95% CI: 1.05-1.14) for non-Hispanic whites, 1.07 (95% CI: 1.02-1.13) for non-Hispanic blacks, and 1.11 (95% CI: 1.06-1.17) for Mexican Americans. We identified two gene-carbohydrate interactions (P < 0.05) in non-Hispanic whites (with CDKAL1 rs471253 and FTO rs8050136), two in non-Hispanic blacks (with IGFBP2 rs4402960 and THADA rs7578597), and two in Mexican Americans (with NOTCH2 rs1092398 and TSPAN8-LGRS rs7961581). We found three gene-fiber interactions in non-Hispanic whites (with ADAMT59 rs4607103, CDKN2A/2B rs1801282, and FTO rs8050136), two in non-Hispanic blacks (with ADAMT59 rs4607103 and THADA rs7578597), and two in Mexican Americans (with THADA rs7578597 and TSPAN8-LGRS rs796158) at the P < 0.05 level. Interactions between the GRS and nutrients failed to reach significance in all the racial/ethnic groups.

Conclusion

Our results suggest that dietary carbohydrates and fiber may modify T2D-associated variants, highlighting the importance of dietary nutrients in predicting T2D risk.

Gene-lifestyle interaction and type 2 diabetes: the EPIC interact case-cohort study

BACKGROUND

Understanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention.

METHODS AND FINDINGS

The InterAct study includes 12,403 incident T2D cases and a representative sub-cohort of 16,154 individuals from a cohort of 340,234 European participants with 3.99 million person-years of follow-up. We studied the combined effects of an additive genetic T2D risk score and modifiable and non-modifiable risk factors using Prentice-weighted Cox regression and random effects meta-analysis methods. The effect of the genetic score was significantly greater in younger individuals (p for interaction  = 1.20×10-4). Relative genetic risk (per standard deviation [4.4 risk alleles]) was also larger in participants who were leaner, both in terms of body mass index (p for interaction  = 1.50×10-3) and waist circumference (p for interaction  = 7.49×10-9). Examination of absolute risks by strata showed the importance of obesity for T2D risk. The 10-y cumulative incidence of T2D rose from 0.25% to 0.89% across extreme quartiles of the genetic score in normal weight individuals, compared to 4.22% to 7.99% in obese individuals. We detected no significant interactions between the genetic score and sex, diabetes family history, physical activity, or dietary habits assessed by a Mediterranean diet score.

CONCLUSIONS

The relative effect of a T2D genetic risk score is greater in younger and leaner participants. However, this sub-group is at low absolute risk and would not be a logical target for preventive interventions. The high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.