Saturated fat intake modulates the association between an obesity genetic risk score and body mass index in two US populations

The utility of obesity polygenic risk scores from research to clinical practice: A review

Obesity represents a major public health emergency worldwide, and its etiology is shaped by a complex interplay of environmental and genetic factors. Over the last decade, polygenic risk scores (PRS) have emerged as a promising tool to quantify an individual's genetic risk of obesity. The field of PRS in obesity genetics is rapidly evolving, shedding new lights on obesity mechanisms and holding promise for contributing to personalized prevention and treatment. Challenges persist in terms of its clinical integration, including the need for further validation in large-scale prospective cohorts, ethical considerations, and implications for health disparities. In this review, we provide a comprehensive overview of PRS for studying the genetics of obesity, spanning from methodological nuances to clinical applications and challenges. We summarize the latest developments in the generation and refinement of PRS for obesity, including advances in methodologies for aggregating genome-wide association study data and improving PRS predictive accuracy, and discuss limitations that need to be overcome to fully realize its potential benefits of PRS in both medicine and public health.

A genome-wide association study on growth traits of Korean commercial pig breeds using Bayesian methods

OBJECTIVE

This study aims to identify the significant regions and candidate genes of growth-related traits (adjusted backfat thickness [ABF], average daily gain [ADG], and days to 90 kg [DAYS90]) in Korean commercial GGP pig (Duroc, Landrace, and Yorkshire) populations.

METHODS

A genome-wide association study (GWAS) was performed using single-nucleotide polymorphism (SNP) markers for imputation to Illumina PorcineSNP60. The BayesB method was applied to calculate thresholds for the significance of SNP markers. The identified windows were considered significant if they explained ≥1% genetic variance.

RESULTS

A total of 28 window regions were related to genetic growth effects. Bayesian GWAS revealed 28 significant genetic regions including 52 informative SNPs associated with growth traits (ABF, ADG, DAYS90) in Duroc, Landrace, and Yorkshire pigs, with genetic variance ranging from 1.00% to 5.46%. Additionally, 14 candidate genes with previous functional validation were identified for these traits.

CONCLUSION

The identified SNPs within these regions hold potential value for future markerassisted or genomic selection in pig breeding programs. Consequently, they contribute to an improved understanding of genetic architecture and our ability to genetically enhance pigs. SNPs within the identified regions could prove valuable for future marker-assisted or genomic selection in pig breeding programs.

Assessment of the impact of a personalised nutrition intervention in impaired glucose regulation over 26 weeks: a randomised controlled trial

Dietary interventions can reduce progression to type 2 diabetes mellitus (T2DM) in people with non-diabetic hyperglycaemia. In this study we aimed to determine the impact of a DNA-personalised nutrition intervention in people with non-diabetic hyperglycaemia over 26 weeks. ASPIRE-DNA was a pilot study. Participants were randomised into three arms to receive either (i) Control arm: standard care (NICE guidelines) (n = 51), (ii) Intervention arm: DNA-personalised dietary advice (n = 50), or (iii) Exploratory arm: DNA-personalised dietary advice via a self-guided app and wearable device (n = 46). The primary outcome was the difference in fasting plasma glucose (FPG) between the Control and Intervention arms after 6 weeks. 180 people were recruited, of whom 148 people were randomised, mean age of 59 years (SD = 11), 69% of whom were female. There was no significant difference in the FPG change between the Control and Intervention arms at 6 weeks (- 0.13 mmol/L (95% CI [- 0.37, 0.11]), p = 0.29), however, we found that a DNA-personalised dietary intervention led to a significant reduction of FPG at 26 weeks in the Intervention arm when compared to standard care (- 0.019 (SD = 0.008), p = 0.01), as did the Exploratory arm (- 0.021 (SD = 0.008), p = 0.006). HbA1c at 26 weeks was significantly reduced in the Intervention arm when compared to standard care (- 0.038 (SD = 0.018), p = 0.04). There was some evidence suggesting prevention of progression to T2DM across the groups that received a DNA-based intervention (p = 0.06). Personalisation of dietary advice based on DNA did not result in glucose changes within the first 6 weeks but was associated with significant reduction of FPG and HbA1c at 26 weeks when compared to standard care. The DNA-based diet was effective regardless of intervention type, though results should be interpreted with caution due to the low sample size. These findings suggest that DNA-based dietary guidance is an effective intervention compared to standard care, but there is still a minimum timeframe of adherence to the intervention before changes in clinical outcomes become apparent.Trial Registration: www.clinicaltrials.gov.uk Ref: NCT03702465.

Potential Mechanisms of Precision Nutrition-Based Interventions for Managing Obesity

Precision nutrition (PN) considers multiple individual-level and environmental characteristics or variables to better inform dietary strategies and interventions for optimizing health, including managing obesity and metabolic disorders. Here, we review the evidence on potential mechanisms-including ones to identify individuals most likely to respond-that can be leveraged in the development of PN interventions addressing obesity. We conducted a review of the literature and included laboratory, animal, and human studies evaluating biochemical and genetic data, completed and ongoing clinical trials, and public programs in this review. Our analysis describes the potential mechanisms related to 6 domains including genetic predisposition, circadian rhythms, physical activity and sedentary behavior, metabolomics, the gut microbiome, and behavioral and socioeconomic characteristics, i.e., the factors that can be leveraged to design PN-based interventions to prevent and treat obesity-related outcomes such as weight loss or metabolic health as laid out by the NIH 2030 Strategic Plan for Nutrition Research. For example, single nucleotide polymorphisms can modify responses to certain dietary interventions, and epigenetic modulation of obesity risk via physical activity patterns and macronutrient intake have also been demonstrated. Additionally, we identified limitations including questions of equitable implementation across a limited number of clinical trials. These include the limited ability of current PN interventions to address systemic influences such as supply chains and food distribution, healthcare systems, racial or cultural inequities, and economic disparities, particularly when designing and implementing PN interventions in low- and middle-income communities. PN has the potential to help manage obesity by addressing intra- and inter-individual variation as well as context, as opposed to "one-size fits all" approaches though there is limited clinical trial evidence to date.

Plant-based dietary patterns and genetic susceptibility to obesity in the CARTaGENE cohort

OBJECTIVE

The study's objective was to examine whether adherence to three plant-based dietary indices (PDIs) mediated or moderated genetic susceptibility to obesity.

METHODS

Baseline participants were 7037 adults (57% women, aged 55.6 ± 7.7 years) from the CARTaGENE cohort of Quebec adults. Two polygenic risk scores for BMI (PRS-BMI), 92 single-nucleotide polymorphisms and 2 million single-nucleotide polymorphisms, and three plant-based scores were calculated (overall, healthy, and unhealthy). Follow-up participants were 2258 adults with data on obesity outcomes, measured 6 years later. General linear models were used to examine the relationships between PRSs and PDI scores on obesity outcomes. Causal mediation analyses were conducted to assess mediation and interaction models.

RESULTS

The overall- and healthy-PDIs and PRSs were significantly associated with obesity outcomes. Adherence to PDIs did not mediate or moderate genetic susceptibility to obesity. Associations between PRSs and obesity outcomes were partly mediated by meat intake cross-sectionally and whole grains intake among males both cross-sectionally and longitudinally. Higher meat intake had a positive association with obesity outcomes, whereas higher whole grains intake had an inverse association.

CONCLUSIONS

These findings suggest that components of a plant-based diet and a shift away from animal products, specifically meat, might be beneficial for nutrition interventions, particularly among individuals with higher genetic risk of obesity.

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.

Misalignment of Circadian Rhythms in Diet-Induced Obesity

The biological clocks of the circadian timing system coordinate cellular and physiological processes and synchronize them with daily cycles. While the central clock in the suprachiasmatic nucleus (SCN) is mainly synchronized by the light/dark cycles, the peripheral clocks react to other stimuli, including the feeding/fasting state, nutrients, sleep-wake cycles, and physical activity. During the disruption of circadian rhythms due to genetic mutations or social and occupational obligations, incorrect arrangement between the internal clock system and environmental rhythms leads to the development of obesity. Desynchronization between the central and peripheral clocks by altered timing of food intake and diet composition leads to uncoupling of the peripheral clocks from the central pacemaker and to the development of metabolic disorders. The strong coupling of the SCN to the light-dark cycle creates a situation of misalignment when food is ingested during the "wrong" time of day. Food-anticipatory activity is mediated by a self-sustained circadian timing, and its principal component is a food-entrainable oscillator. Modifying the time of feeding alone greatly affects body weight, whereas ketogenic diet (KD) influences circadian biology, through the modulation of clock gene expression. Night-eating behavior is one of the causes of circadian disruption, and night eaters have compulsive and uncontrolled eating with severe obesity. By contrast, time-restricted eating (TRE) restores circadian rhythms through maintaining an appropriate daily rhythm of the eating-fasting cycle. The hypothalamus has a crucial role in the regulation of energy balance rather than food intake. While circadian locomotor output cycles kaput (CLOCK) expression levels increase with high-fat diet-induced obesity, peroxisome proliferator-activated receptor-alpha (PPARα) increases the transcriptional level of brain and muscle aryl hydrocarbon receptor nuclear translocator (ARNT)-like 1 (BMAL1) in obese subjects. In this context, effective timing of chronotherapies aiming to correct SCN-driven rhythms depends on an accurate assessment of the SCN phase. In fact, in a multi-oscillator system, local rhythmicity and its disruption reflects the disruption of either local clocks or central clocks, thus imposing rhythmicity on those local tissues, whereas misalignment of peripheral oscillators is due to exosome-based intercellular communication.Consequently, disruption of clock genes results in dyslipidemia, insulin resistance, and obesity, while light exposure during the daytime, food intake during the daytime, and sleeping during the biological night promote circadian alignment between the central and peripheral clocks. Thus, shift work is associated with an increased risk of obesity, diabetes, and cardiovascular diseases because of unusual eating times as well as unusual light exposure and disruption of the circadian rhythm.

Association of dietary fatty acids with the risk of atherosclerotic cardiovascular disease in a prospective cohort of United States veterans

BACKGROUND

Atherosclerotic cardiovascular diseases (ASCVDs) are the leading cause of worldwide adult mortality. Although broad classes of dietary fats have been shown to alter ASCVD risk, the roles that individual dietary fatty acids play in influencing ASCVD risk are unclear.

OBJECTIVES

The aim of this prospective cohort study was to examine the relationships of the total fat classes and individual fatty acids with the risk of ASCVD.

METHODS

The Million Veteran Program is a prospective cohort whereby dietary intake of fatty acids was assessed in 158,198 participants that had enrolled between January 2011 and November 2018 and were free of ASCVD at baseline. Incident ASCVD was ascertained from the Veterans Affairs electronic health records and the National Death Index. Multivariable-adjusted hazard ratios (HRs) for the relationship between fat intake and ASCVD risk were computed using Cox regression models.

RESULTS

The mean age was 61 years, 88% were males. A total of 11,771 ASCVD events were identified during the follow-up. When compared with the lowest quintile, participants in the highest quintile of dietary trans-monounsaturated fats and conjugated linoleic acids had an increased risk (HR [95% CI]) of ASCVD events: 1.10 (1.04, 1.17) and 1.11 (1.05, 1.18), respectively. When compared with low consumers, participants in the highest quintile of total cis-polyunsaturated fatty acid intake had a lower risk of experiencing an ASCVD event 0.93 (0.87, 0.99).

CONCLUSION

Although higher intakes of specific trans-fatty acids and conjugated linoleic were associated with an increased risk of ASCVD, the same cannot be said for all other fat classes. This work suggests that care must be taken when drawing general conclusions regarding the health effects of dietary individual fatty acids.

Interaction between genetic susceptibility to obesity and food intake on BMI in Finnish school-aged children

Diet modulates the genetic risk of obesity, but the modulation has been rarely studied using genetic risk scores (GRSs) in children. Our objectives were to identify single nucleotide polymorphisms (SNPs) that drive the interaction of specific foods with obesity and combine these into GRSs. Genetic and food frequency data from Finnish Health in Teens study was utilized. In total, 1142 11-year-old subjects were genotyped on the Metabochip array. BMI-GRS with 30 well-known SNPs was computed and the interaction of individual SNPs with food items and their summary dietary scores were examined in relation to age- and sex-specific BMI z-score (BMIz). The whole BMI-GRS interacted with several foods on BMIz. We identified 7-11 SNPs responsible for each interaction and these were combined into food-specific GRS. The most predominant interaction was witnessed for pizza (p < 0.001): the effect on BMIz was b - 0.130 (95% CI - 0.23; - 0.031) in those with low-risk, and 0.153 (95% CI 0.072; 0.234) in high-risk. Corresponding, but weaker interactions were verified for sweets and chocolate, sugary juice drink, and hamburger and hotdog. In total 5 SNPs close to genes NEGR1, SEC16B, TMEM18, GNPDA2, and FTO were shared between these interactions. Our results suggested that children genetically prone to obesity showed a stronger association of unhealthy foods with BMIz than those with lower genetic susceptibility. Shared SNPs of the interactions suggest common differences in metabolic gene-diet interactions, which warrants further investigation.

Investigation of the interaction between Genetic Risk Score (GRS) and fatty acid quality indices on mental health among overweight and obese women

BACKGROUND & AIMS

Mental disorders are associated with dietary fatty acids and genome-wide association studies have found multiple risk loci robustly related to depression, anxiety, and stress. The aim of this study is to investigate the interaction of genetic risk score (GRS) and dietary fat quality indices on mental health.

METHODS

This cross-sectional study included 279 overweight and obese women for N6/N3 ratio and 378 overweight and obese women for CSI aged 18-68 years. Using reliable and verified standard protocols, body composition, anthropometric indices, blood pressure, physical activity, and dietary fat quality were measured. Serum samples were used to determine biochemical tests. A genetic risk score (GRS) was calculated using the risk alleles of the three SNPs. A generalized linear model (GLM) was applied to assess the interactions between GRS and fat quality indices. Mental health was evaluated using Depression Anxiety Stress Scales (DASS-21).

RESULTS

The mean (± SD) age and BMI of our participants were 36.48 (8.45) and 30.73 (3.72) kg/m2 respectively. There was a marginally significant mean difference among tertiles of the CSI in terms of stress (P = 0.051), DASS-21 (P = 0.078) in the crude model. After adjusting for age, energy intake, physical activity and BMI in model 1, there was a positive interaction between GRS and T3 of N6/N3 ratio on anxiety (β = 0.91, CI = 0.08,1.75, P = 0.031), depression (β = 1.05, CI = 0.06,2.04, P = 0.037), DASS-21 (β = 2.22, CI= -0.31,4.75, P = 0.086).

CONCLUSION

Our findings indicate that higher ratio of N-6 to N-3 considering genetics were predictive of mental disorder in our population.

Interactions Between Genetic Risk Score and Healthy Plant Diet Index on Cardiometabolic Risk Factors Among Obese and Overweight Women

People with higher genetic predisposition to obesity are more susceptible to cardiovascular diseases (CVDs) and healthy plant-based foods may be associated with reduced risks of obesity and other metabolic markers. We investigated whether healthy plant-foods-rich dietary patterns might have inverse associations with cardiometabolic risk factors in participants at genetically elevated risk of obesity. For this cross-sectional study, 377 obese and overweight women were chosen from health centers in Tehran, Iran. We calculated a healthy plant-based diet index (h-PDI) in which healthy plant foods received positive scores, and unhealthy plant and animal foods received reversed scores. A genetic risk score (GRS) was developed based on 3 polymorphisms. The interaction between GRS and h-PDI on cardiometabolic traits was analyzed using a generalized linear model (GLM). We found significant interactions between GRS and h-PDI on body mass index (BMI) (p = 0.02), body fat mass (p = 0.04), and waist circumference (p = 0.056). There were significant gene-diet interactions for healthful plant-derived diets and BMI-GRS on high-sensitivity C-reactive protein (p = 0.03), aspartate aminotransferase (p = 0.04), alanine transaminase (p = 0.05), insulin (p = 0.04), and plasminogen activator inhibitor 1 (p = 0.002). Adherence to h-PDI was more strongly related to decreased levels of the aforementioned markers among participants in the second or top tertile of GRS than those with low GRS. These results highlight that following a plant-based dietary pattern considering genetics appears to be a protective factor against the risks of cardiometabolic abnormalities.

Effects of gene-lifestyle interactions on obesity based on a multi-locus risk score: A cross-sectional analysis

BACKGROUND

The relationship between lifestyle and obesity is a major focus of research. Personalized nutrition, which utilizes evidence from nutrigenomics, such as gene-environment interactions, has been attracting attention in recent years. However, evidence for gene-environment interactions that can inform treatment strategies is lacking, despite some reported interactions involving dietary intake or physical activity. Utilizing gene-lifestyle interactions in practice could aid in optimizing interventions according to genetic risk.

METHODS

This study aimed to elucidate the effects of gene-lifestyle interactions on body mass index (BMI). Cross-sectional data from the Japan Multi-Institutional Collaborative Cohort Study were used. Interactions between a multi-locus genetic risk score (GRS), calculated from 76 ancestry-specific single nucleotide polymorphisms, and nutritional intake or physical activity were assessed using a linear mixed-effect model.

RESULTS

The mean (standard deviation) BMI and GRS for all participants (n = 12,918) were 22.9 (3.0) kg/m2 and -0.07 (0.16), respectively. The correlation between GRS and BMI was r(12,916) = 0.13 (95% confidence interval [CI] 0.11-0.15, P < 0.001). An interaction between GRS and saturated fatty acid intake was observed (β = -0.11, 95% CI -0.21 to -0.02). An interaction between GRS and n-3 polyunsaturated fatty acids was also observed in the females with normal-weight subgroup (β = -0.12, 95% CI -0.22 to -0.03).

CONCLUSION

Our results provide evidence of an interaction effect between GRS and nutritional intake and physical activity. This gene-lifestyle interaction provides a basis for developing prevention or treatment interventions for obesity according to individual genetic predisposition.

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.

Healthy beverages may reduce the genetic risk of abdominal obesity and related metabolic comorbidities: a gene-diet interaction study in Iranian women

BACKGROUND & AIMS

The nutrition transition in developing countries like Iran causes the increasing rise of obesity and abdominal obesity rates. However, it is not yet well proven that environmental modifications like improving the quality of beverage intake can be effective in people who have a genetic predisposition to obesity. So, in the present study, we examine the interaction between genetic predisposition and healthy beverage index (HBI) with abdominal obesity and obesity-related metabolic risk factors in overweight and obese women.

METHOD

Based on inclusion and exclusion criteria, 202 overweight or obese females were chosen for this cross-sectional study. Body composition, anthropometric measures, physical activity, and beverage intake data were collected and analyzed using recognized and trustworthy methodologies. Biochemical tests were performed on serum samples. A genetic risk score (GRS) was calculated based on the results of genetic tests. The predetermined HBI was calculated based on previous studies. A generalized linear model was used to estimate the interactions between GRS and HBI (GLM).

RESULTS

We found significant interactions between GRS and HBI on WHR (β = - 0.39, CI: -0.07 to 0.001, P = 0.05) and WC (β = - 6.18, CI: - 13.41 to 1.05, P = 0.09). Also, there were significant gene-diet interactions for HBI and GRS on HDL (β = 7.09, CI: - 0.73 to 14.92, P = 0.07) and FBS (β = - 9.07, CI: - 18.63 to 0.47, P = 0.06).

CONCLUSIONS

These findings emphasize the HBI considering genetics appears to protect against the risks of abdominal obesity and metabolic associated obesity markers.

Using Machine Learning to Predict Obesity Based on Genome-Wide and Epigenome-Wide Gene-Gene and Gene-Diet Interactions

Obesity is associated with many chronic diseases that impair healthy aging and is governed by genetic, epigenetic, and environmental factors and their complex interactions. This study aimed to develop a model that predicts an individual's risk of obesity by better characterizing these complex relations and interactions focusing on dietary factors. For this purpose, we conducted a combined genome-wide and epigenome-wide scan for body mass index (BMI) and up to three-way interactions among 402,793 single nucleotide polymorphisms (SNPs), 415,202 DNA methylation sites (DMSs), and 397 dietary and lifestyle factors using the generalized multifactor dimensionality reduction (GMDR) method. The training set consisted of 1,573 participants in exam 8 of the Framingham Offspring Study (FOS) cohort. After identifying genetic, epigenetic, and dietary factors that passed statistical significance, we applied machine learning (ML) algorithms to predict participants' obesity status in the test set, taken as a subset of independent samples (n = 394) from the same cohort. The quality and accuracy of prediction models were evaluated using the area under the receiver operating characteristic curve (ROC-AUC). GMDR identified 213 SNPs, 530 DMSs, and 49 dietary and lifestyle factors as significant predictors of obesity. Comparing several ML algorithms, we found that the stochastic gradient boosting model provided the best prediction accuracy for obesity with an overall accuracy of 70%, with ROC-AUC of 0.72 in test set samples. Top predictors of the best-fit model were 21 SNPs, 230 DMSs in genes such as CPT1A, ABCG1, SLC7A11, RNF145, and SREBF1, and 26 dietary factors, including processed meat, diet soda, French fries, high-fat dairy, artificial sweeteners, alcohol intake, and specific nutrients and food components, such as calcium and flavonols. In conclusion, we developed an integrated approach with ML to predict obesity using omics and dietary data. This extends our knowledge of the drivers of obesity, which can inform precision nutrition strategies for the prevention and treatment of obesity. Clinical Trial Registration: [www.ClinicalTrials.gov], the Framingham Heart Study (FHS), [NCT00005121].

Dietary Mediators of the Genetic Susceptibility to Obesity-Results from the Quebec Family Study

BACKGROUND

Recent studies showed that eating behaviors such as disinhibition, emotional and external eating, and snacking mediate genetic susceptibility to obesity. It remains unknown if diet quality and intake of specific food groups also mediate the genetic susceptibility to obesity.

OBJECTIVE

This study aimed to assess if diet quality and intakes of specific food groups mediate the association between a polygenic risk score (PRS) for BMI and BMI and waist circumference (WC). We hypothesized that poor diet quality, high intakes of energy-dense food groups, and low intakes of nutrient-dense food groups mediate the genetic susceptibility to obesity.

METHODS

This cross-sectional study included 750 participants (56.3% women, aged 41.5 ± 14.9 y, BMI 27.8 ± 7.5 kg/m2) from the Quebec Family Study. A PRSBMI based on >500,000 genetic variants was calculated using LDpred2. Dietary intakes were assessed with a 3-d food record from which a diet quality score (i.e. Nutrient Rich Food Index 6.3) and food groups were derived. Mediation analyses were conducted using a regression-based and bootstrapping approach.

RESULTS

The PRSBMI explained 25.7% and 19.8% of the variance in BMI and WC, respectively. The association between PRSBMI and BMI was partly mediated by poor diet quality (β = 0.33 ± 0.12; 95% CI: 0.13, 0.60), high intakes of fat and high-fat foods (β = 0.46 ± 0.16; 95% CI: 0.19, 0.79) and sugar-sweetened beverages (β = 0.25 ± 0.14; 95% CI: 0.05, 0.60), and low intakes of vegetables (β = 0.15 ± 0.08; 95% CI: 0.03, 0.32), fruits (β = 0.37 ± 0.12; 95% CI: 0.17, 0.64), and dairy products (β = 0.17 ± 0.09; 95% CI: 0.02, 0.37). The same trends were observed for WC.

CONCLUSIONS

The genetic susceptibility to obesity was partly mediated by poor diet quality and intakes of specific food groups. These results suggest that improvement in diet quality may reduce obesity risk among individuals with high genetic susceptibility and emphasize the need to intervene on diet quality among these individuals.

Healthful plant-based dietary patterns, genetic risk of obesity, and cardiovascular risk in the UK biobank study

BACKGROUND & AIMS

People with a higher genetic risk for obesity are more likely to develop cardiovascular disease (CVD), and healthy plant-based dietary patterns may be associated with decreased risks of obesity and cardiovascular events. We investigated whether adherence to healthy plant-foods-rich dietary patterns might attenuate risks of obesity and related cardiovascular abnormalities for people at genetically higher risk of obesity.

METHODS

This study included 121,799 middle-aged adults in UK Biobank who were initially free of metabolic diseases and cancer. We calculated a healthful plant-based diet index (hPDI) based on 17 major food groups as well as a genetic risk score (GRS) for obesity consisting of body mass index (BMI)-associated variants. The incidence of cardiovascular events (myocardial infarction, MI, or stroke) was prospectively followed during a mean (SD) 5.1 (0.9) years.

RESULTS

We found significant interactions between GRS and hPDI on adiposity (P_interaction <0.0001); adherence to hPDI was more strongly associated with lower levels of adiposity among participants with higher GRS than those with lower GRS. Further, we found a similar pattern of GRS-hPDI interactions on untreated hypertension (P_interaction = 0.0036). When we tested GRS-hPDI interactions on cardiovascular events, adherence to hPDI was more strongly associated with a decreased risk of MI among people with high GRS (above median) than those with low GRS (P_interaction = 0.006). Among participants with high GRS, high adherence to hPDI (the top tertile of hPDI) was associated with an HR 0.54 (95% CI: 0.39, 0.74) for MI, as compared to low adherence.

CONCLUSIONS

Adherence to healthy plant-based dietary patterns significantly attenuated risks of cardiovascular abnormalities for people at genetically higher risk of obesity. Our results support the precision medicine strategies considering genetics and dietary habits to modify cardiovascular health for people at higher risk of genetically determined obesity.

Calcium Intake Is Inversely Related to Risk of Obesity among American Young Adults over a 30-Year Follow-Up

BACKGROUND

Calcium (Ca) is an essential nutrient that may play an important role in weight maintenance through its involvement in energy or lipid metabolism. However, little is known about the long-term associations of Ca intake with obesity risk.

OBJECTIVES

We aimed to prospectively examine the association between cumulative Ca intake and the incidence of obesity among American young adults over 30 y of follow-up.

METHODS

Participants were from the CARDIA (Coronary Artery Risk Development in Young Adults) study. A total of 4097 of 5115 black and white individuals aged 18-30 y at baseline in 1985-1986 were included in the current analysis. Dietary and supplemental Ca intake was assessed by the validated interview-based CARDIA diet history at baseline and exam years 7 and 20. Incident cases of obesity were identified when BMI was ≥30 kg/m2 for the first time since baseline. A survival analysis was performed using Cox proportional hazards regression models to estimate the HRs and corresponding 95% CIs for obesity incidence during follow-up.

RESULTS

During a 30-y follow-up (mean ± SD: 20 ± 10 y), 1675 participants developed obesity. Cumulative total Ca intake (dietary plus supplemental Ca) was inversely associated with incidence of obesity in multivariable-adjusted analysis [quintile (Q)5 (highest intake) compared with Q1 (lowest intake): HR: 0.68; 95% CI: 0.56, 0.82; P-trend < 0.01]. This inverse association persisted among Ca supplement users (Q5 compared with Q1: HR: 0.53; 95% CI: 0.40, 0.70; P-trend < 0.01), but was not seen among nonusers.

CONCLUSIONS

Following a cohort of Americans from young adulthood to midlife, an inverse association between calcium intake and obesity incidence was observed. Further studies are needed to confirm our findings.

Variants in Circadian Rhythm Gene Cry1 Interacts with Healthy Dietary Pattern for Serum Leptin Levels: a Cross-sectional Study

Circadian disruption causes obesity and other metabolic disorders. There is no research considering the role of Cryptochromes (Cry) 1 body clock gene and major dietary patterns on serum leptin level and obesity. We aimed to investigate the interaction between Cry1 circadian gene polymorphisms and major dietary patterns on leptin and obesity related measurements. This study was performed on 377 overweight and obese women. Mean age and body mass index (BMI) of study subjects were 36.64 ± 9.02 years and 30.81 ± 3.8 kg/m², respectively. Dietary assessment was done using a validated 147-item food frequency questionnaire. Cry1 rs2287161 were genotyped using polymerase chain reaction-restriction fragment length polymorphism. Generalized linear models were used for interaction analysis. Healthy and unhealthy dietary pattern (HDP and UDP, respectively) were extracted using factor analysis (principal component analysis). Our study revealed a significant higher weight (p = 0.003) and BMI (p = 0.042) in women carrying CC homozygote compared with G allele carriers. Moreover, our findings showed a significant gene-diet interaction between HDP and Cry1 rs2287161 on BMI (p = 0.034) and serum leptin level (p = 0.056) in which, BMI and serum leptin level were lower in subjects with CC genotype than in those with GG genotype while following HDP. This study suggests a significant interaction between Cry1 rs2287161 polymorphisms and HDP on BMI and serum leptin and the lowering effects were apparent among C allele carriers compared to G allele ones. This data highlights the role of dietary pattern in relation of gene and obesity.

Gene-obesogenic environment interactions on body mass indices for older black and white men and women from the Health and Retirement Study

BACKGROUND

Gene-obesogenic environment interactions influence body mass index (BMI) across the life course; however, limited research examines how these interactions may differ by race and sex.

METHODS

Utilizing mixed-effects models, we examined the interaction effects of a polygenic risk score (PGS) generated from BMI-associated single-nucleotide polymorphisms, and environmental factors, including age, physical activity, alcohol intake, and childhood socioeconomic status on measured longitudinal BMI from the Health and Retirement Study (HRS). HRS is a population representative survey of older adults in the United States. This study used a subsample of genotyped Black (N = 1796) and White (N = 4925) men and women (50-70 years) with measured BMI.

RESULTS

Higher PGS was associated with higher BMI. The association between PGS and BMI weakened as individuals aged among White men (Pinteraction = 0.0383) and White women (Pinteraction = 0.0514). The mean BMI difference between the 90th and 10th PGS percentile was 4.25 kg/m2 among 50-year-old White men, and 3.11 kg/m2 among the 70 years old's, i.e., a 1.14 kg/m2 (95% CI: -0.27, 2.82) difference. The difference among 50- and 70-year-old White women was 1.34 kg/m2 (95% CI: 0.09, 2.60). In addition, the protection effect of physical activity was stronger among White women with higher PGS (Pinteraction = 0.0546). Vigorous physical activity (compared with never) was associated with 1.66 kg/m2 (95% CI: 1.06, 2.29) lower mean BMI among those in the 90th PGS percentile, compared with 0.83 kg/m2 (95% CI: 0.37, 1.29) lower among those in the 10th PGS percentile. Interactions were also observed between both PGS and alcohol intake among White men (Pinteraction = 0.0034) and women (Pinteraction = 0.0664) and Black women (Pinteraction = 0.0108), and PGS and childhood socioeconomic status among White women (Pinteraction = 0.0007).

CONCLUSIONS

Our findings reinforce the importance of physical activity among those with an elevated genetic risk; additionally, other detected interactions may underscore the influence of broader social environments on obesity-promoting genes.

Interaction between Metabolic Genetic Risk Score and Dietary Fatty Acid Intake on Central Obesity in a Ghanaian Population

Obesity is a multifactorial condition arising from the interaction between genetic and lifestyle factors. We aimed to assess the impact of lifestyle and genetic factors on obesity-related traits in 302 healthy Ghanaian adults. Dietary intake and physical activity were assessed using a 3 day repeated 24 h dietary recall and global physical activity questionnaire, respectively. Twelve single nucleotide polymorphisms (SNPs) were used to construct 4-SNP, 8-SNP and 12-SNP genetic risk scores (GRSs). The 4-SNP GRS showed significant interactions with dietary fat intakes on waist circumference (WC) (Total fat, P_interaction = 0.01; saturated fatty acids (SFA), P_interaction = 0.02; polyunsaturated fatty acids (PUFA), P_interaction = 0.01 and monounsaturated fatty acids (MUFA), P_interaction = 0.01). Among individuals with higher intakes of total fat (>47 g/d), SFA (>14 g/d), PUFA (>16 g/d) and MUFA (>16 g/d), individuals with ≥3 risk alleles had a significantly higher WC compared to those with <3 risk alleles. This is the first study of its kind in this population, suggesting that a higher consumption of dietary fatty acid may have the potential to increase the genetic susceptibility of becoming centrally obese. These results support the general dietary recommendations to decrease the intakes of total fat and SFA, to reduce the risk of obesity, particularly in individuals with a higher genetic predisposition to central obesity.

Saturated Fats and Health: A Reassessment and Proposal for Food-Based Recommendations: JACC State-of-the-Art Review

The recommendation to limit dietary saturated fatty acid (SFA) intake has persisted despite mounting evidence to the contrary. Most recent meta-analyses of randomized trials and observational studies found no beneficial effects of reducing SFA intake on cardiovascular disease (CVD) and total mortality, and instead found protective effects against stroke. Although SFAs increase low-density lipoprotein (LDL) cholesterol, in most individuals, this is not due to increasing levels of small, dense LDL particles, but rather larger LDL particles, which are much less strongly related to CVD risk. It is also apparent that the health effects of foods cannot be predicted by their content in any nutrient group without considering the overall macronutrient distribution. Whole-fat dairy, unprocessed meat, and dark chocolate are SFA-rich foods with a complex matrix that are not associated with increased risk of CVD. The totality of available evidence does not support further limiting the intake of such foods.

Assessing the effectiveness of actionable nutrigenomics and lifestyle genomics interventions for weight management in clinical practice: A critical, scoping review with directions for future research

BACKGROUND

The use of nutrigenomics and lifestyle genomics in clinical practice has the potential to optimize weight-related outcomes for patients.

AIM

A scoping review was conducted to summarize and evaluate the current body of knowledge related to the effectiveness of providing DNA-based lifestyle advice on weight-related outcomes, with the aim of providing direction for future research.

METHOD

Primary studies were included if they were written in English, evaluated weight-related and/or body mass index and/or body composition outcomes, and provided participants with an actionable genetic-based lifestyle intervention; interventions that only provided information on genetic risk for diseases/conditions were excluded. Data was extracted from each article meeting inclusion criteria (N=3) and the studies were critically appraised for methodological limitations.

RESULTS

Research in this area is promising, but limited. Specific limitations relate to study designs, the nature of the recommendations provided to participants, small (underpowered) sample sizes, the use of self-reported weight/BMI data and lack of consideration of important confounding factors.

CONCLUSIONS

Therefore, the effectiveness of nutrigenomics and lifestyle genomics interventions for weight management in clinical practice cannot yet be conclusively determined. Recommendations for future research are detailed in the present manuscript.

Contribution of macronutrients to obesity: implications for precision nutrition

The specific metabolic contribution of consuming different energy-yielding macronutrients (namely, carbohydrates, protein and lipids) to obesity is a matter of active debate. In this Review, we summarize the current research concerning associations between the intake of different macronutrients and weight gain and adiposity. We discuss insights into possible differential mechanistic pathways where macronutrients might act on either appetite or adipogenesis to cause weight gain. We also explore the role of dietary macronutrient distribution on thermogenesis or energy expenditure for weight loss and maintenance. On the basis of the data discussed, we describe a novel way to manage excessive body weight; namely, prescribing personalized diets with different macronutrient compositions according to the individual's genotype and/or enterotype. In this context, the interplay of macronutrient consumption with obesity incidence involves mechanisms that affect appetite, thermogenesis and metabolism, and the outcomes of these mechanisms are altered by an individual's genotype and microbiota. Indeed, the interactions of the genetic make-up and/or microbiota features of a person with specific macronutrient intakes or dietary pattern consumption help to explain individualized responses to macronutrients and food patterns, which might represent key factors for comprehensive precision nutrition recommendations and personalized obesity management.

Potential Interplay between Dietary Saturated Fats and Genetic Variants of the NLRP3 Inflammasome to Modulate Insulin Resistance and Diabetes Risk: Insights from a Meta-Analysis of 19 005 Individuals

SCOPE

Insulin resistance (IR) and inflammation are hallmarks of type 2 diabetes (T2D). The nod-like receptor pyrin domain containing-3 (NLRP3) inflammasome is a metabolic sensor activated by saturated fatty acids (SFA) initiating IL-1β inflammation and IR. Interactions between SFA intake and NLRP3-related genetic variants may alter T2D risk factors.

METHODS

Meta-analyses of six Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 19 005) tested interactions between SFA and NLRP3-related single-nucleotide polymorphisms (SNPs) and modulation of fasting insulin, fasting glucose, and homeostasis model assessment of insulin resistance.

RESULTS

SFA interacted with rs12143966, wherein each 1% increase in SFA intake increased insulin by 0.0063 IU mL-1 (SE ± 0.002, p = 0.001) per each major (G) allele copy. rs4925663, interacted with SFA (β ± SE = -0.0058 ± 0.002, p = 0.004) to increase insulin by 0.0058 IU mL-1 , per additional copy of the major (C) allele. Both associations are close to the significance threshold (p < 0.0001). rs4925663 causes a missense mutation affecting NLRP3 expression.

CONCLUSION

Two NLRP3-related SNPs showed potential interaction with SFA to modulate fasting insulin. Greater dietary SFA intake accentuates T2D risk, which, subject to functional validation, may be further elaborated depending on NLRP3-related genetic variants.

Reverse gene-environment interaction approach to identify variants influencing body-mass index in humans

Identifying gene-environment interactions (GxEs) contributing to human cardiometabolic disorders is challenging. Here we apply a reverse GxE candidate search by deriving candidate variants from promoter-enhancer interactions that respond to dietary fatty acid challenge through altered chromatin accessibility in human primary adipocytes. We then test all variants residing in the lipid-responsive open chromatin sites within adipocyte promoter-enhancer contacts for interaction effects between the genotype and dietary saturated fat intake on body mass index (BMI) in the UK Biobank. We discover 14 novel GxE variants in 12 lipid-responsive promoters, including well-known lipid genes (LIPE, CARM1, and PLIN2) and novel genes, such as LDB3, for which we provide further functional and integrative genomics evidence. We further identify 24 GxE variants in enhancers, totaling 38 new GxE variants for BMI in the UK Biobank, demonstrating that molecular genomics data produced in physiologically relevant contexts can discover new functional GxE mechanisms in humans.

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

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

Impact of Genes and Environment on Obesity and Cardiovascular Disease

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

Impact of Low Caloric Diet and Exercise on Atherogenic Indices in Obese Hypertensive Adults

Background and aims: The influence of a low caloric diet with exercise were studied on several biochemical parameters including the lipid profile and atherogenic indices in overweight subjects including obesity with hypertension. Material and method: The study focused on 327 patients (144 men and 183 women) aged 54-73 years selected randomly, We chose hypertensives who live in the city of Tiaret and are over 50 years old, because it is the age group most affected by hypertension in Algeria and even in the world. We invited the subjects of our study to follow a program involving a low caloric diet, which was characterized by the suppression of the consumption of sucrose and refined white flour and by the choice of low-fat products, especially dairy products. Results: We observed a decrease in the mean value of blood pressure with its two components, systolic and diastolic. Systolic blood pressure ranged from 13.06 ± 1.40 cm Hg for the overall sample to 13.01 ± 1.12 cm Hg after the six-month program. The same finding is made for diastolic pressure, which decreased by 1.58% for the study population. For biochemical parameters, we observe a decrease in the mean value of all parameters after participation in the low-calorie diet and physical activity program, with the exception of HDL-c, which experienced an increase of 6.25%. Conclusions: The hypocaloric diet with exercise that we proposed to a group of hypertensives showed its effectiveness. A healthy lifestyle including a healthy and balanced diet with physical activity therefore allow better management of the hypertensive subject and could actually prevent atherosclerosis.

Epigenomics and metabolomics reveal the mechanism of the APOA2-saturated fat intake interaction affecting obesity

Background

The putative functional variant -265T>C (rs5082) within the APOA2 promoter has shown consistent interactions with saturated fatty acid (SFA) intake to influence the risk of obesity.

Objective

The aim of this study was to implement an integrative approach to characterize the molecular basis of this interaction.

Design

We conducted an epigenome-wide scan on 80 participants carrying either the rs5082 CC or TT genotypes and consuming either a low-SFA (<22 g/d) or high-SFA diet (≥22 g/d), matched for age, sex, BMI, and diabetes status in the Boston Puerto Rican Health Study (BPRHS). We then validated the findings in selected participants in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study (n = 379) and the Framingham Heart Study (FHS) (n = 243). Transcription and metabolomics analyses were conducted to determine the relation between epigenetic status, APOA2 mRNA expression, and blood metabolites.

Results

In the BPRHS, we identified methylation site cg04436964 as exhibiting significant differences between CC and TT participants consuming a high-SFA diet, but not among those consuming low-SFA. Similar results were observed in the GOLDN Study and the FHS. Additionally, in the FHS, cg04436964 methylation was negatively correlated with APOA2 expression in the blood of participants consuming a high-SFA diet. Furthermore, when consuming a high-SFA diet, CC carriers had lower APOA2 expression than those with the TT genotype. Lastly, metabolomic analysis identified 4 pathways as overrepresented by metabolite differences between CC and TT genotypes with high-SFA intake, including tryptophan and branched-chain amino acid (BCAA) pathways. Interestingly, these pathways were linked to rs5082-specific cg04436964 methylation differences in high-SFA consumers.

Conclusions

The epigenetic status of the APOA2 regulatory region is associated with SFA intake and APOA2 -265T>C genotype, promoting an APOA2 expression difference between APOA2 genotypes on a high-SFA diet, and modulating BCAA and tryptophan metabolic pathways. These findings identify potential mechanisms by which this highly reproducible gene-diet interaction influences obesity risk, and contribute new insights to ongoing investigations of the relation between SFA and human health. This study was registered at clinicaltrials.gov as NCT03452787.

Gene-diet interaction effects on BMI levels in the Singapore Chinese population

BACKGROUND

Recent genome-wide association studies (GWAS) have identified 97 body-mass index (BMI) associated loci. We aimed to evaluate if dietary intake modifies BMI associations at these loci in the Singapore Chinese population.

METHODS

We utilized GWAS information from six data subsets from two adult Chinese population (N = 7817). Seventy-eight genotyped or imputed index BMI single nucleotide polymorphisms (SNPs) that passed quality control procedures were available in all datasets. Alternative Healthy Eating Index (AHEI)-2010 score and ten nutrient variables were evaluated. Linear regression analyses between z score transformed BMI (Z-BMI) and dietary factors were performed. Interaction analyses were performed by introducing the interaction term (diet x SNP) in the same regression model. Analysis was carried out in each cohort individually and subsequently meta-analyzed using the inverse-variance weighted method. Analyses were also evaluated with a weighted gene-risk score (wGRS) contructed by BMI index SNPs from recent large-scale GWAS studies.

RESULTS

Nominal associations between Z-BMI and AHEI-2010 and some dietary factors were identified (P = 0.047-0.010). The BMI wGRS was robustly associated with Z-BMI (P = 1.55 × 10^- 15) but not with any dietary variables. Dietary variables did not significantly interact with the wGRS to modify BMI associations. When interaction analyses were repeated using individual SNPs, a significant association between cholesterol intake and rs4740619 (CCDC171) was identified (β = 0.077, adjP_interaction = 0.043).

CONCLUSIONS

The CCDC171 gene locus may interact with cholesterol intake to increase BMI in the Singaporean Chinese population, however most known obesity risk loci were not associated with dietary intake and did not interact with diet to modify BMI levels.

Mediterranean Diet Adherence and Genetic Background Roles within a Web-Based Nutritional Intervention: The Food4Me Study

Mediterranean Diet (MedDiet) adherence has been proven to produce numerous health benefits. In addition, nutrigenetic studies have explained some individual variations in the response to specific dietary patterns. The present research aimed to explore associations and potential interactions between MedDiet adherence and genetic background throughout the Food4Me web-based nutritional intervention. Dietary, anthropometrical and biochemical data from volunteers of the Food4Me study were collected at baseline and after 6 months. Several genetic variants related to metabolic risk features were also analysed. A Genetic Risk Score (GRS) was derived from risk alleles and a Mediterranean Diet Score (MDS), based on validated food intake data, was estimated. At baseline, there were no interactions between GRS and MDS categories for metabolic traits. Linear mixed model repeated measures analyses showed a significantly greater decrease in total cholesterol in participants with a low GRS after a 6-month period, compared to those with a high GRS. Meanwhile, a high baseline MDS was associated with greater decreases in Body Mass Index (BMI), waist circumference and glucose. There also was a significant interaction between GRS and the MedDiet after the follow-up period. Among subjects with a high GRS, those with a high MDS evidenced a highly significant reduction in total carotenoids, while among those with a low GRS, there was no difference associated with MDS levels. These results suggest that a higher MedDiet adherence induces beneficial effects on metabolic outcomes, which can be affected by the genetic background in some specific markers.

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

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

The Niemann-Pick C1 gene interacts with a high-fat diet to promote weight gain through differential regulation of central energy metabolism pathways

A genome-wide association study (GWAS) reported that common variation in the human Niemann-Pick C1 gene (NPC1) is associated with morbid adult obesity. This study was confirmed using our BALB/cJ Npc1 mouse model, whereby heterozygous mice (Npc1^+/- ) with decreased gene dosage were susceptible to weight gain when fed a high-fat diet (HFD) compared with homozygous normal mice (Npc1^+/+ ) fed the same diet. The objective for our current study was to validate this Npc1 gene-diet interaction using statistical modeling with fitted growth trajectories, conduct body weight analyses for different measures, and define the physiological basis responsible for weight gain. Metabolic phenotype analysis indicated no significant difference between Npc1^+/+ and Npc1^+/- mice fed a HFD for food and water intake, oxygen consumption, carbon dioxide production, locomotor activity, adaptive thermogenesis, and intestinal lipid absorption. However, the livers from Npc1^+/- mice had significantly increased amounts of mature sterol regulatory element-binding protein-1 (SREBP-1) and increased expression of SREBP-1 target genes that regulate glycolysis and lipogenesis with an accumulation of triacylglycerol and cholesterol. Moreover, white adipose tissue from Npc1^+/- mice had significantly decreased amounts of phosphorylated hormone-sensitive lipase with decreased triacylglycerol lipolysis. Consistent with these results, cellular energy metabolism studies indicated that Npc1^+/- fibroblasts had significantly increased glycolysis and lipogenesis, in addition to significantly decreased substrate (glucose and endogenous fatty acid) oxidative metabolism with an accumulation of triacylglycerol and cholesterol. In conclusion, these studies demonstrate that the Npc1 gene interacts with a HFD to promote weight gain through differential regulation of central energy metabolism pathways.

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

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

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.

Utilizing nutritional genomics to tailor diets for the prevention of cardiovascular disease: a guide for upcoming studies and implementations

INTRODUCTION

Personalized diets based on an individual's genome to optimize the success of dietary intervention and reduce genetic cardiovascular disease (CVD) risk, is one of the challenges most frequently discussed in the scientific community. Areas covered: The authors gathered literature-based evidence on nutritional genomics and CVD phenotypes, our own results and research experience to provide a critical overview of the current situation of using nutritional genomics to tailor diets for CVD prevention and to propose guidelines for future studies and implementations. Expert commentary: Hundreds of studies on gene-diet interactions determining CVD intermediate (plasma lipids, hypertension, etc.) and final phenotypes (stroke, etc.) have furnished top-level scientific evidence for claiming that the genetic effect in cardiovascular risk is not deterministic, but can be modified by diet. However, despite the many results obtained, there are still gaps in practically applying a personalized diet design to specific genotypes. Hence, a better systemization and methodological improvement of new studies is required to obtain top-level evidence that will allow their application in the future precision nutrition/medicine. The authors propose several recommendations for tackling new approaches and applications.

Circadian Rhythms in Diet-Induced Obesity

The biological clocks of the circadian timing system coordinate cellular and physiological processes and synchronizes these with daily cycles, feeding patterns also regulates circadian clocks. The clock genes and adipocytokines show circadian rhythmicity. Dysfunction of these genes are involved in the alteration of these adipokines during the development of obesity. Food availability promotes the stimuli associated with food intake which is a circadian oscillator outside of the suprachiasmatic nucleus (SCN). Its circadian rhythm is arranged with the predictable daily mealtimes. Food anticipatory activity is mediated by a self-sustained circadian timing and its principal component is food entrained oscillator. However, the hypothalamus has a crucial role in the regulation of energy balance rather than food intake. Fatty acids or their metabolites can modulate neuronal activity by brain nutrient-sensing neurons involved in the regulation of energy and glucose homeostasis. The timing of three-meal schedules indicates close association with the plasma levels of insulin and preceding food availability. Desynchronization between the central and peripheral clocks by altered timing of food intake and diet composition can lead to uncoupling of peripheral clocks from the central pacemaker and to the development of metabolic disorders. Metabolic dysfunction is associated with circadian disturbances at both central and peripheral levels and, eventual disruption of circadian clock functioning can lead to obesity. While CLOCK expression levels are increased with high fat diet-induced obesity, peroxisome proliferator-activated receptor (PPAR) alpha increases the transcriptional level of brain and muscle ARNT-like 1 (BMAL1) in obese subjects. Consequently, disruption of clock genes results in dyslipidemia, insulin resistance and obesity. Modifying the time of feeding alone can greatly affect body weight. Changes in the circadian clock are associated with temporal alterations in feeding behavior and increased weight gain. Thus, shift work is associated with increased risk for obesity, diabetes and cardio-vascular diseases as a result of unusual eating time and disruption of circadian rhythm.

Lunch eating predicts weight-loss effectiveness in carriers of the common allele at PERILIPIN1: the ONTIME (Obesity, Nutrigenetics, Timing, Mediterranean) study

BACKGROUND

We propose that eating lunch late impairs the mobilization of fat from adipose tissue, particularly in carriers of PERILIPIN1 (PLIN1) variants.

OBJECTIVE

The aim was to test the hypothesis that PLIN1, a circadian lipid-stabilizing protein in the adipocyte, interacts with the timing of food intake to affect weight loss.

DESIGN

A total of 1287 overweight and obese subjects [229 men and 1058 women; mean ± SD body mass index (in kg/m²): 31 ± 5] who attended outpatient obesity clinics were enrolled in the ONTIME (Obesity, Nutrigenetics, Timing, Mediterranean) study. Timing of food intake was estimated with a validated questionnaire. Anthropometric variables and PLIN1 genotypes were analyzed, including 6209T>C (rs2289487), 11482G>A (rs894160), 13041A>G (rs2304795), and 14995A>T (rs1052700). The main outcomes were effectiveness of the program and weight-loss progression during 28 wk of treatment.

RESULTS

The PLIN1 locus was associated with variability in response to a weight-loss program. Specifically, carrying the minor C allele at the PLIN1 6209T>C was associated with better weight-loss response (P = 0.035). The probability of being a better responder [percentage of weight loss ≥7.5% (median)] was 33% higher among C than among TT carriers (OR: 1.32; 95% CI: 1.05, 1.67; P = 0.017). We found an interaction of PLIN1 × food timing between the 14995A>T variant and timing of lunch eating for total weight loss (P = 0.035). Among AA carriers, eating late was associated with less weight loss (P < 0.001), whereas time of eating did not influence weight loss among TT carriers (P = 0.326).

CONCLUSIONS

Variability at the PLIN1 locus is associated with variability in weight loss. Moreover, eating late is related to lower weight-loss effectiveness among carriers of the AA genotype at the PLIN1 14995A>T variant. These results contribute to our ability to implement more precise and successful obesity treatments. The ONTIME study was registered at clinicaltrials.gov as NCT02829619.

Integrative Analysis of Metabolomic, Proteomic and Genomic Data to Reveal Functional Pathways and Candidate Genes for Drip Loss in Pigs

The aim of this study was to integrate multi omics data to characterize underlying functional pathways and candidate genes for drip loss in pigs. The consideration of different omics levels allows elucidating the black box of phenotype expression. Metabolite and protein profiling was applied in Musculus longissimus dorsi samples of 97 Duroc × Pietrain pigs. In total, 126 and 35 annotated metabolites and proteins were quantified, respectively. In addition, all animals were genotyped with the porcine 60 k Illumina beadchip. An enrichment analysis resulted in 10 pathways, amongst others, sphingolipid metabolism and glycolysis/gluconeogenesis, with significant influence on drip loss. Drip loss and 22 metabolic components were analyzed as intermediate phenotypes within a genome-wide association study (GWAS). We detected significantly associated genetic markers and candidate genes for drip loss and for most of the metabolic components. On chromosome 18, a region with promising candidate genes was identified based on SNPs associated with drip loss, the protein "phosphoglycerate mutase 2" and the metabolite glycine. We hypothesize that association studies based on intermediate phenotypes are able to provide comprehensive insights in the genetic variation of genes directly involved in the metabolism of performance traits. In this way, the analyses contribute to identify reliable candidate genes.

Effect of interactions of polymorphisms in the Melanocortin-4 receptor gene with dietary factors on the risk of obesity and Type 2 diabetes: a systematic review

AIM

To perform a systematic review of the effect of interaction between Melanocortin-4 receptor (MC4R) single nucleotide polymorphisms and diet on the development of obesity and Type 2 diabetes.

BACKGROUND

Environmental factors, such as nutrient intakes or feeding behaviours, can modulate the association of polymorphism in the MC4R gene with obesity and Type 2 diabetes mellitus.

METHODS

A systematic literature search was conducted in the PubMed, Scopus and Google Scholar databases, with a combination of the following keywords: Diet*, nutr*, melanocortin receptor, melanocortin 4 receptor and MC4R. To assess the quality of observational studies, we used a 12-item quality checklist, derived from the STREGA statement.

RESULTS

A total of 14 articles were selected based on the inclusion and exclusion criteria. Consumption of highly salty foods and adherence to a Mediterranean dietary pattern can modulate the association between MC4R polymorphisms and the risk of obesity or Type 2 diabetes. Despite the highly contradictory results of intervention studies, after short-term lifestyle interventions, children with variant alleles of MC4R single nucleotide polymorphisms can lose more body weight, compared with non-carriers, although they may have difficulty in maintaining this weight loss in the long-term. To interpret the results of studies on adults, we need further studies.

CONCLUSIONS

The interaction between MC4R genes with dietary factors plays a significant role in the development of obesity or Type 2 diabetes phenotypes. Early detection of MC4R risk alleles in individuals and modification of their diet based on these results could be an efficient strategy to prevent obesity or diabetes in these subgroups.

Nutrigenomics, the Microbiome, and Gene-Environment Interactions: New Directions in Cardiovascular Disease Research, Prevention, and Treatment: A Scientific Statement From the American Heart Association

Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies investigating the relationship between genetic variants and diet in modulating cardiometabolic risk, as well as the effects of dietary components on multiple "omic" measures, including transcriptomics, metabolomics, proteomics, lipidomics, epigenetic modifications, and the microbiome. Here, we describe the current state of the field of nutrigenomics with respect to cardiometabolic disease research and outline a direction for the integration of multiple omics techniques in future nutrigenomic studies aimed at understanding mechanisms and developing new therapeutic options for cardiometabolic disease treatment and prevention.

Association between Maternal Fish Consumption and Gestational Weight Gain: Influence of Molecular Genetic Predisposition to Obesity

Background

Studies suggest that fish consumption can restrict weight gain. However, little is known about how fish consumption affects gestational weight gain (GWG), and whether this relationship depends on genetic makeup.

Objective

To examine the association between fish consumption and GWG, and whether this relationship is dependent on molecular genetic predisposition to obesity.

Design

A nested case-cohort study based on the Danish National Birth Cohort (DNBC) sampling the most obese women (n = 990) and a random sample of the remaining participants (n = 1,128). Replication of statistically significant findings was attempted in the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 4,841). We included 32 body mass index (BMI) associated single nucleotide polymorphisms (SNPs) and 5 SNPs found associated with GWG. BMI associated SNPs were combined in a genetic risk score (GRS). Associations between consumption of fish, GRS or individual variants and GWG were analysed, and interactions between fish and the GRS or individual variants were examined.

Results

In the DNBC, each portion/week (150 g) of fatty fish was associated with a higher GWG of 0.58 kg (95% CI: 0.16, 0.99, P<0.01). For total fish and lean fish, similar patterns were observed, but these associations were not statistically significant. We found no association between GRS and GWG, and no interactions between GRS and dietary fish on GWG. However, we found an interaction between the PPARG Pro12Ala variant and dietary fish. Each additional Pro12Ala G-allele was associated with a GWG of -0.83 kg (95% CI: -1.29, -0.37, P<0.01) per portion/week of dietary fish, with the same pattern for both lean and fatty fish. In ALSPAC, we were unable to replicate these findings.

Conclusion

We found no consistent evidence of association between fish consumption and GWG, and our results indicate that the association between dietary fish and GWG has little or no dependency on GRS or individual SNPs.

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

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

CardioGxE, a catalog of gene-environment interactions for cardiometabolic traits

Background

Genetic understanding of complex traits has developed immensely over the past decade but remains hampered by incomplete descriptions of contribution to phenotypic variance. Gene-environment (GxE) interactions are one of these contributors and in the guise of diet and physical activity are important modulators of cardiometabolic phenotypes and ensuing diseases.

Results

We mined the scientific literature to collect GxE interactions from 386 publications for blood lipids, glycemic traits, obesity anthropometrics, vascular measures, inflammation and metabolic syndrome, and introduce CardioGxE, a gene-environment interaction resource. We then analyzed the genes and SNPs supporting cardiometabolic GxEs in order to demonstrate utility of GxE SNPs and to discern characteristics of these important genetic variants. We were able to draw many observations from our extensive analysis of GxEs. 1) The CardioGxE SNPs showed little overlap with variants identified by main effect GWAS, indicating the importance of environmental interactions with genetic factors on cardiometabolic traits. 2) These GxE SNPs were enriched in adaptation to climatic and geographical features, with implications on energy homeostasis and response to physical activity. 3) Comparison to gene networks responding to plasma cholesterol-lowering or regression of atherosclerotic plaques showed that GxE genes have a greater role in those responses, particularly through high-energy diets and fat intake, than do GWAS-identified genes for the same traits. Other aspects of the CardioGxE dataset were explored.

Conclusions

Overall, we demonstrate that SNPs supporting cardiometabolic GxE interactions often exhibit transcriptional effects or are under positive selection. Still, not all such SNPs can be assigned potential functional or regulatory roles often because data are lacking in specific cell types or from treatments that approximate the environmental factor of the GxE. With research on metabolic related complex disease risk embarking on genome-wide GxE interaction tests, CardioGxE will be a useful resource.