Moderate to vigorous physical activity interactions with genetic variants and body mass index in a large US ethnically diverse cohort

How do lifestyle factors modify the association between genetic predisposition and obesity-related phenotypes? A 4-way decomposition analysis using UK Biobank

BACKGROUND

Obesity and central obesity are multifactorial conditions with genetic and non-genetic (lifestyle and environmental) contributions. There is incomplete understanding of whether lifestyle modifies the translation from respective genetic risks into phenotypic obesity and central obesity, and to what extent genetic predisposition to obesity and central obesity is mediated via lifestyle factors.

METHODS

This is a cross-sectional study of 201,466 (out of approximately 502,000) European participants from UK Biobank and tested for interactions and mediation role of lifestyle factors (diet quality; physical activity levels; total energy intake; sleep duration, and smoking and alcohol intake) between genetic risk for obesity and central obesity. BMI-PRS and WHR-PRS are exposures and obesity and central obesity are outcomes.

RESULTS

Overall, 42.8% of the association between genetic predisposition to obesity and phenotypic obesity was explained by lifestyle: 0.9% by mediation and 41.9% by effect modification. A significant difference between men and women was found in central obesity; the figures were 42.1% (association explained by lifestyle), 1.4% (by mediation), and 40.7% (by modification) in women and 69.6% (association explained by lifestyle), 3.0% (by mediation), and 66.6% (by modification) in men.

CONCLUSIONS

A substantial proportion of the association between genetic predisposition to obesity/central obesity and phenotypic obesity/central obesity was explained by lifestyles. Future studies with repeated measures of obesity and lifestyle would be needed to clarify causation.

Inferring Gene-by-Environment Interactions with a Bayesian Whole-Genome Regression Model

The contribution of gene-by-environment (GxE) interactions for many human traits and diseases is poorly characterized. We propose a Bayesian whole-genome regression model for joint modeling of main genetic effects and GxE interactions in large-scale datasets, such as the UK Biobank, where many environmental variables have been measured. The method is called LEMMA (Linear Environment Mixed Model Analysis) and estimates a linear combination of environmental variables, called an environmental score (ES), that interacts with genetic markers throughout the genome. The ES provides a readily interpretable way to examine the combined effect of many environmental variables. The ES can be used both to estimate the proportion of phenotypic variance attributable to GxE effects and to test for GxE effects at genetic variants across the genome. GxE effects can induce heteroskedasticity in quantitative traits, and LEMMA accounts for this by using robust standard error estimates when testing for GxE effects. When applied to body mass index, systolic blood pressure, diastolic blood pressure, and pulse pressure in the UK Biobank, we estimate that 9.3%, 3.9%, 1.6%, and 12.5%, respectively, of phenotypic variance is explained by GxE interactions and that low-frequency variants explain most of this variance. We also identify three loci that interact with the estimated environmental scores (-log10p>7.3).

The Genetic Basis of Metabolic Disease

Recent developments in genetics and genomics are providing a detailed and systematic characterization of the genetic underpinnings of common metabolic diseases and traits, highlighting the inherent complexity within systems for homeostatic control and the many ways in which that control can fail. The genetic architecture underlying these common metabolic phenotypes is complex, with each trait influenced by hundreds of loci spanning a range of allele frequencies and effect sizes. Here, we review the growing appreciation of this complexity and how this has fostered the implementation of genome-scale approaches that deliver robust mechanistic inference and unveil new strategies for translational exploitation.

A linear mixed-model approach to study multivariate gene-environment interactions

Different exposures, including diet, physical activity, or external conditions can contribute to genotype-environment interactions (G×E). Although high-dimensional environmental data are increasingly available and multiple exposures have been implicated with G×E at the same loci, multi-environment tests for G×E are not established. Here, we propose the structured linear mixed model (StructLMM), a computationally efficient method to identify and characterize loci that interact with one or more environments. After validating our model using simulations, we applied StructLMM to body mass index in the UK Biobank, where our model yields previously known and novel G×E signals. Finally, in an application to a large blood eQTL dataset, we demonstrate that StructLMM can be used to study interactions with hundreds of environmental variables.

Cardiorespiratory Fitness Attenuates the Obesity Risk in Chinese Children Who Have Parents with Overweight/Obesity

OBJECTIVE

To evaluate the impact of parental weight status and offspring cardiorespiratory fitness on the risk of obesity among Chinese children.

STUDY DESIGN

This cross-sectional study was conducted in Wuhan, China from May to June 2010. Children's height, weight, and waist circumference were measured for assessing their total and central obesity. Their cardiorespiratory fitness was determined by the 20-m shuttle-run test. We calculated parental body mass index according to self-reported height and weight, and divided it into normal weight or overweight/obesity. Multivariable logistic regression model was applied to estimate the combined relationships of cardiorespiratory fitness and parental weight status with the risk of obesity of children.

RESULTS

A total of 587 Chinese children (343 boys and 244 girls) aged 9.6 (0.7) years participated in this study. Compared with those who had low cardiorespiratory fitness and at least 1 parent with overweight/obesity, children who had high cardiorespiratory fitness and at least 1 parent with overweight/obesity reported lower risks of total obesity (OR 0.12, 95% CI .05-0.30) and central obesity (OR .09, 95% CI .04-0.20), and children who had high cardiorespiratory fitness and no parent with overweight/obesity were 89% (OR 0.11, 95% CI .05-0.24) less likely to have total obesity and 92% (OR .08, 95% CI .04-0.16) less likely to have central obesity (all P < .001).

CONCLUSIONS

High level of cardiorespiratory fitness among children could attenuate the influence of parental obesity on their offspring's weight status.

Physical activity modifies the FTO effect on body mass index change in Japanese adolescents

BACKGROUND

Evidence of the effects of fat mass and obesity-associated (FTO) variation and long-term effects of physical activity (PA) on adiposity in adolescents is largely scarce. This study therefore investigated whether PA modulates the effects of the FTO on body mass index (BMI) changes in Japanese adolescents between the ages of 13 and 18 years.

METHODS

Data on 343 subjects (156 boys; 187 girls) who were enrolled in 2006 and 2007 at schools in Shunan City, Japan, were collected. Genotyping (rs1558902) was conducted, and anthropometry and blood test results were recorded for subjects in the eighth grade. A second survey involving self-reporting of anthropometry was conducted when the subjects were in the 12th grade. PA was estimated using the International Physical Activity Questionnaire. BMI and the standard deviation score for BMI (BMI-SDS) were calculated. BMI changes and BMI-SDS changes were compared between FTO genotypes using a multivariate model.

RESULTS

The effect of the interaction between PA and the FTO genotype on BMI changes was significant in boys but not in girls. In boys, PA had a significant negative influence on BMI-SDS changes in those with the AA genotype and a significant positive influence on BMI and BMI-SDS changes in those with the TT genotype.

CONCLUSION

The influence of PA on BMI change and BMI-SDS change varies on the basis of genotype. PA modified the effect of FTO on BMI change in Japanese boys.

High birth weight modifies association between adolescent physical activity and cardiometabolic health in women and not men

Recent evidence suggests that adverse prenatal development alters physiological response to physical activity, but longitudinal epidemiologic evidence is scant. This study tested the hypothesis that lower physical activity during adolescence and young adulthood is more strongly associated with later cardiovascular disease (CVD) risk and diabetes or prediabetes (DM/PDM) in women and men who were born with high or low birth weight (HBW, LBW), compared to normal birth weight (NBW). We analyzed data from the National Longitudinal Study of Adolescent to Adult Health, a cohort study of US adolescents followed into adulthood (1994-2009). Using sex-stratified multivariable regression, 30-year CVD risk score (calculated using objective measures; n=12,775) and prevalent DM/PDM (n=15,138) at 24-32years of age were each modeled as a function of birth weight category, self-reported moderate-to-vigorous physical activity frequency in adolescence (MVPA1) and young adulthood (MVPA3), and MVPA-birth weight interactions. Greater MVPA1 was associated with lower 30-year CVD risk score and DM/PDM risk in HBW women but not NBW or LBW women. Associations between MVPA1 and 30-year CVD risk or DM/PDM were not modified by HBW in men; or by LBW in women or men. Additionally, birth weight did not modify estimated effects of MVPA3. Findings suggest that frequent MVPA in adolescence may be a particularly important cardiometabolic risk reduction strategy in girls born HBW; however, we found no evidence that birth weight and MVPA interact in cardiometabolic disease risk in men, for MVPA in adulthood, or for LBW.

From genetics and epigenetics to the future of precision treatment for obesity

Obesity has become a major global health problem, epitomized by excess accumulation of body fat resulting from an imbalance between energy intake and expenditure. The treatments for obesity range from modified nutrition and additional physical activity, to drugs or surgery. But the curative effect of each method seems to vary between individuals. With progress in the genetics and epigenetics of obesity, personalization of the clinical management of obesity may be at our doorstep. This review presents an overview of our current understanding of the genetics and epigenetics of obesity and how these findings influence responses to treatments. As bariatric surgery is the most effective long-term treatment for morbid obesity, we pay special attention to the association between genetic factors and clinical outcomes of bariatric surgery. Finally, we discuss the prospects for precision obesity treatment.

Cross-sectional and prospective impact of reallocating sedentary time to physical activity on children's body composition

BACKGROUND

The amount of time children spend in sedentary behaviours may have adverse health effects.

OBJECTIVE

To examine the substitution effects of displacing a fixed duration of sedentary time with physical activity (PA) on children's body composition.

METHODS

We included 386 children (197 boys). Outcomes were body mass index, waist circumference, total body fat mass and trunk fat mass assessed by dual-energy X-ray absorptiometry. Sedentary time and PA were measured with accelerometers. Data were analysed by isotemporal analyses estimating the effect of reallocating 15 and 30 min d^-1 of sedentary time into light (light physical activity), and moderate-to-vigorous (MVPA) PA on body composition.

RESULTS

Reallocating 15 and 30 min d^-1 of sedentary time into MVPA was negatively associated with body fatness in cross-sectional analyses. Prospectively, reallocating 30 min of sedentary time into 30 min of MVPA was negatively associated with waist circumference (β = -1.11, p < 0.05), trunk fat mass (β = -0.21, p < 0.05), and total body fat mass (β = -0.48, p < 0.05) at follow-up (20 months). The magnitude of associations was half in magnitude and remained significant (p < 0.05) when reallocating 15 min of sedentary time into MVPA. Reallocating sedentary time into light physical activity was not related (p > 0.05) with body fatness outcomes.

CONCLUSIONS

Substituting sedentary time with MVPA using isotemporal analysis is associated with positive effects on body composition.

The contribution of genetics and environment to obesity

BACKGROUND

Obesity is a global health problem mainly attributed to lifestyle changes such as diet, low physical activity or socioeconomics factors. However, several evidences consistently showed that genetics contributes significantly to the weight-gain susceptibility.

SOURCES OF DATA

A systematic literature search of most relevant original, review and meta-analysis, restricted to English was conducted in PubMed, Web of Science and Google scholar up to May 2017 concerning the contribution of genetics and environmental factors to obesity.

AREAS OF AGREEMENT

Several evidences suggest that obesogenic environments contribute to the development of an obese phenotype. However, not every individual from the same population, despite sharing the same obesogenic environment, develop obesity.

AREAS OF CONTROVERSY

After more than 10 years of investigation on the genetics of obesity, the variants found associated with obesity represent only 3% of the estimated BMI-heritability, which is around 47-80%. Moreover, genetic factors per se were unable to explain the rapid spread of obesity prevalence.

GROWING POINTS

The integration of multi-omics data enables scientists having a better picture and to elucidate unknown pathways contributing to obesity.

AREAS TIMELY FOR DEVELOPING RESEARCH

New studies based on case-control or gene candidate approach will be important to identify new variants associated with obesity susceptibility and consequently unveiling its genetic architecture. This will lead to an improvement of our understanding about underlying mechanisms involved in development and origin of the actual obesity epidemic. The integration of several omics will also provide insights about the interplay between genes and environments contributing to the obese phenotype.

Reallocating sedentary time to moderate-to-vigorous physical activity but not to light-intensity physical activity is effective to reduce adiposity among youths: a systematic review and meta-analysis

The aim of the study was to summarize the evidence of the effects of reallocating time spent in sedentary behaviours in different activity intensities on youth's adiposity. Five databases were searched. Studies that reported the effects of replacing sedentary behaviour with light-intensity physical activity (LIPA) and/or moderate-to-vigorous physical activity (MVPA) on at least one adiposity parameter. The estimated regression coefficients (β) and 95% CIs were combined and meta-analysed. Data from 7,351 youths and five studies were analysed. Pooled analysis from cross-sectional studies shows that replacing sedentary time with LIPA showed no significant associations with any adiposity-related outcomes. Replacing sedentary time with MVPA was statistically associated with total body fat percentage (β = -2.512; p = 0.003), but not with body mass index or waist circumference. In subgroup analysis, the greatest magnitude of association was observed from studies where 60 min of sedentary behaviour was reallocated to 60 min of MVPA (β = -4.535; p < 0.001). Our results highlight the importance of promoting MVPA, which may improve body composition phenotypes in young people. This information can be used to develop more effective lifestyle interventions.

The importance of gene-environment interactions in human obesity

The worldwide obesity epidemic has been mainly attributed to lifestyle changes. However, who becomes obese in an obesity-prone environment is largely determined by genetic factors. In the last 20 years, important progress has been made in the elucidation of the genetic architecture of obesity. In parallel with successful gene identifications, the number of gene-environment interaction (GEI) studies has grown rapidly. This paper reviews the growing body of evidence supporting gene-environment interactions in the field of obesity. Heritability, monogenic and polygenic obesity studies provide converging evidence that obesity-predisposing genes interact with a variety of environmental, lifestyle and treatment exposures. However, some skepticism remains regarding the validity of these studies based on several issues, which include statistical modelling, confounding, low replication rate, underpowered analyses, biological assumptions and measurement precision. What follows in this review includes (1) an introduction to the study of GEI, (2) the evidence of GEI in the field of obesity, (3) an outline of the biological mechanisms that may explain these interaction effects, (4) methodological challenges associated with GEI studies and potential solutions, and (5) future directions of GEI research. Thus far, this growing body of evidence has provided a deeper understanding of GEI influencing obesity and may have tremendous applications in the emerging field of personalized medicine and individualized lifestyle recommendations.

Association of Fat Mass and Obesity-associated Gene Variant with Lifestyle Factors and Body Fat in Indian Children

CONTEXT

Common intronic variants of the fat mass and obesity-associated (FTO) gene have been associated with obesity-related traits in humans.

AIMS

(1) The aim of this study is to study the distribution of FTO gene variants across different body mass index (BMI) categories and (2) to explore the association between FTO gene variants and lifestyle factors in obese and normal weight Indian children.

SUBJECTS AND METHODS

Fifty-six children (26 boys, mean age 10.3 ± 2.2 years) were studied. Height, weight, and waist and hip circumference were measured. Physical activity (questionnaire) and food intake (food frequency questionnaire) were assessed. Body fat percentage (%BF) was measured by dual-energy X-ray absorptiometry. FTO allelic variants at rs9939609 site were detected by SYBR Green Amplification Refractory Mutation System real-time polymerase chain reaction using allele-specific primers. Generalized linear model was used to investigate the simultaneous influence of genetic and lifestyle factors on %BF.

RESULTS

Mean height, weight, and BMI of normal and obese children were 130.6 ± 7.1 versus 143.2 ± 15.6, 24.0 ± 5.2 versus 53.1 ± 15.8, and 13.9 ± 2.1 versus 25.3 ± 3.2, respectively. The frequency of AA allele was 57% among obese children and 35% in normal weight children. Children with the AA allele who were obese had least physical activity, whereas children with AT allele and obesity had the highest intake of calories when compared to children who had AT allele and were normal. %BF was positively associated with AA alleles and junk food intake and negatively with healthy food intake and moderate physical activity.

CONCLUSIONS

Healthy lifestyle with high physical activity and diet low in calories and fat may help in modifying the risk imposed by FTO variants in children.

The interaction between physical activity and obesity gene variants in association with BMI: Does the obesogenic environment matter?

Little is known about how obesity susceptibility single nucleotide polymorphisms (SNPs) interact with moderate to vigorous physical activity (MVPA) in relation to BMI during adolescence, once obesogenic neighborhood factors are accounted for. In race stratified models, including European (EA; N=4977), African (AA; N=1726), and Hispanic Americans (HA; N=1270) from the National Longitudinal Study of Adolescent to Adult Health (1996; ages 12-21), we assessed the evidence for a SNPxMVPA interaction with BMI-for-age Z score, once accounting for obesogenic neighborhood factors including physical activity amenities, transportation and recreation infrastructure, poverty and crime. Eight SNPxMVPA interactions with suggestive significance (p<0.10; three in each EA, and AA, two in HA) were observed showing attenuation on BMI-for-age Z score in adolescents with ≥5 versus <5 bouts/week MVPA, except for rs10146997 (near NRXN3). Findings were robust to the inclusion of neighborhood-level variables as covariates. These findings suggest that any attenuation from MVPA on a genetic susceptibility to obesity during adolescence is likely not operating through obesogenic neighborhood factors.

Differences in the Association of Physical Activity and Children's Overweight and Obesity Status Among the Major Racial and Ethnic Groups of U.S. Children

OBJECTIVE

To examine the relationship of exercise with overweight and obesity among an ethnically diverse sample of U.S. children.

METHOD

Data from the 2011-2012 National Survey of Children's Health were analyzed to examine the relationship of daily exercise with children's weight status. Propensity score covariate adjustment and multivariate logistic regression with survey weights were used to control for child, home, and community characteristics.

RESULTS

Approximately 22% of all children ages 10 to 17 years engaged in daily exercise for at least 20 minutes. In the adjusted model for the entire sample, daily exercise was associated with children having a lower likelihood of being overweight or obese (odds ratio = 0.79; 95% confidence interval = 0.68-0.91). In a stratified analysis of the major racial and ethnic groups, however, while White children who exercised daily were found to have a lower odds of being overweight or obese (odds ratio = 0.70; 95% confidence interval = 0.60-0.82), this relationship was not found for most minority children.

CONCLUSIONS

Racial and ethnic minority children were not found to have the same weight status relationship with exercising daily. These findings suggest that some population-average exercise recommendations may not be as applicable to minority children.

From Genome-Wide Association Study to Phenome-Wide Association Study: New Paradigms in Obesity Research

Obesity is a condition in which excess body fat has accumulated over an extent that increases the risk of many chronic diseases. The current clinical classification of obesity is based on measurement of body mass index (BMI), waist-hip ratio, and body fat percentage. However, these measurements do not account for the wide individual variations in fat distribution, degree of fatness or health risks, and genetic variants identified in the genome-wide association studies (GWAS). In this review, we will address this important issue with the introduction of phenome, phenomics, and phenome-wide association study (PheWAS). We will discuss the new paradigm shift from GWAS to PheWAS in obesity research. In the era of precision medicine, phenomics and PheWAS provide the required approaches to better definition and classification of obesity according to the association of obese phenome with their unique molecular makeup, lifestyle, and environmental impact.

Influence of SNP*SNP interaction on BMI in European American adolescents: findings from the National Longitudinal Study of Adolescent Health

BACKGROUND

Adolescent obesity is predictive of future weight gain, obesity and adult onset severe obesity (body mass index [BMI] ≥40 kg m(-2) ). Despite successful efforts to identify Single Nucleotide Polymorphisms (SNPs) influencing BMI, <5% of the 40-80% heritability of the phenotype has been explained. Identification of gene-gene (G-G) interactions between known variants can help explain this hidden heritability as well as identify potential biological mechanisms affecting weight gain during this critical developmental period.

OBJECTIVE

We have recently shown distinct genetic effects on BMI across the life course, and thus it is important to examine the evidence for epistasis in adolescence.

METHODS

In adolescent participants of European descent from wave II of the National Longitudinal Study of Adolescent Health (Add Health, n = 5072, ages 12-21, 52.5% female), we tested 34 established BMI-related SNPs for G-G interaction effects on BMI z-score. We used mixed-effects regression, assuming multiplicative interaction models adjusting for age, sex and geographic region, with random effects for family and school.

RESULTS

For 28 G-G interactions that were nominally significant (P < 0.05), we attempted to replicate our results in an adolescent sample from the Childhood European American Cohort from Philadelphia. In the replication study, one interaction (PRKD1-FTO) was significant after correction for multiple testing.

CONCLUSIONS

Our results are suggestive of epistatic effects on BMI during adolescence and point to potentially interactive effects between genes in biological pathways important in obesity.

Discussing the putative role of obesity-associated genes in the etiopathogenesis of eating disorders

In addition to the identification of mutations clearly related to Mendelian forms of obesity; genome-wide association studies and follow-up studies have in the last years pinpointed several loci associated with BMI. These genetic alterations are located in or near genes expressed in the hypothalamus that are involved in the regulation of eating behavior. Accordingly, it seems plausible that these SNPs, or others located in related genes, could also help develop aberrant conduct patterns that favor the establishment of eating disorders should other susceptibility factors or personality dimensions be present. However, and somewhat surprisingly, with few exceptions such as BDNF, the great majority of the genes governing these pathways remain untested in patients with anorexia nervosa, bulimia nervosa or binge-eating disorder. In the present work, we review the few existing studies, but also indications and biological concepts that point to these genes in the CNS as good candidates for association studies with eating disorder patients.

Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry

Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

Genes and the hypothalamic control of metabolism in humans

Heritability of obesity and body weight variation is high. Molecular genetic studies have led to the identification of mutations in a few genes, with a major effect on obesity (major genes and monogenic forms). Analyses of these genes have helped to unravel important pathways and have created a more profound understanding of body weight regulation. For most individuals, a polygenic basis is relevant for the genetic predisposition to obesity. Small effect sizes are conveyed by the polygenic variants. Hence, only if a number of these variants is harboured, a sizeable phenotypic effect is detectable. Most, if not all, of the genes relevant to weight regulation are expressed in the hypothalamus. This underscores the major role of this region of the brain in body weight regulation.

Modification of genetic influences on adiposity between 36 and 63 years of age by physical activity and smoking in the 1946 British Birth Cohort Study

Background:

Previous studies reporting on the interaction between physical activity and genetic susceptibility on obesity have been cross-sectional and have not considered the potential influences of other lifestyle behaviours. The aim of this study was to examine modification of genetic influences on changes across age in adiposity during mid-adulthood by physical activity and smoking.

Methods:

The sample comprised 2444 participants who were genotyped for 11 obesity variants and had body mass index (BMI), waist circumference-to-height ratio (WHtR), physical activity and smoking measures at 36, 43, 53 and 60–64 years of age. A genetic risk score (GRS) comprising the sum of risk alleles was computed. Structural equation models investigated modification of the longitudinal GRS associations by physical activity (active versus inactive) and smoking (non-smoker versus smoker), using a latent linear spline to summarise BMI or WHtR (multiplied by 100) at the age of 36 years and their subsequent rates of change over age.

Results:

Physical activity at the age of 36 years attenuated the GRS associations with BMI and WHtR at the same age (P-interaction 0.009 and 0.004, respectively). Further, physical activity at the age of 53 years attenuated the GRS association with rate of change in BMI between 53 and 63 years of age (by 0.012 kg m⁻² per year (95% confidence interval (CI): 0.001, 0.024), P-interaction 0.004). Conversely, smoking at the age of 43 years showed a trend towards augmenting the GRS association with rate of change in WHtR between 43 and 63 years of age (by 0.012 (95% CI: 0.001, 0.026), P-interaction 0.07). Estimated GRS effect sizes were lowest at all ages in the healthiest group (e.g., active non-smokers).

Conclusions:

Healthy lifestyle behaviours appeared to attenuate the genetic influence on changes across age in BMI and central adiposity during mid-adulthood. An active lifestyle and not smoking may have additive effects on reducing the genetic susceptibility to obesity in adults.

Screen time behaviours may interact with obesity genes, independent of physical activity, to influence adolescent BMI in an ethnically diverse cohort

BACKGROUND

There has been little investigation of gene-by-environment interactions related to sedentary behaviour, a risk factor for obesity defined as leisure screen time (ST; i.e. television, video and computer games).

OBJECTIVE

To test the hypothesis that limiting ST use attenuates the genetic predisposition to increased body mass index (BMI), independent of physical activity.

DESIGN

Using 7642 wave II participants of the National Longitudinal Study of Adolescent Health, (Add Health; mean = 16.4 years, 52.6% female), we assessed the interaction of ST (h week(-1) ) and 41 established obesity single nucleotide polymorphisms (SNPs) with age- and sex-specific BMI Z-scores in 4788 European-American (EA), 1612 African-American (AA) and 1242 Hispanic American (HA) adolescents.

RESULTS

Nominally significant SNP*ST interaction were found for FLJ35779 in EA, GNPDA2 in AA and none in HA (EA: beta [SE] = 0.016[0.007]), AA: beta [SE] = 0.016[0.011]) per 7 h week(-1) ST and one risk allele in relation to BMI Z-score.

CONCLUSIONS

While for two established BMI loci, we find evidence that high levels of ST exacerbate the influence of obesity susceptibility variants on body mass; overall, we do not find strong evidence for interactions between the majority of established obesity loci. However, future studies with larger sample sizes, or that may build on our current study and the growing published literature, are clearly warranted.

Genotype by energy expenditure interaction with metabolic syndrome traits: the Portuguese healthy family study

Moderate-to-high levels of physical activity are established as preventive factors in metabolic syndrome development. However, there is variability in the phenotypic expression of metabolic syndrome under distinct physical activity conditions. In the present study we applied a Genotype X Environment interaction method to examine the presence of GxEE interaction in the phenotypic expression of metabolic syndrome. A total of 958 subjects, from 294 families of The Portuguese Healthy Family study, were included in the analysis. Total daily energy expenditure was assessed using a 3 day physical activity diary. Six metabolic syndrome related traits, including waist circumference, systolic blood pressure, glucose, HDL cholesterol, total cholesterol and triglycerides, were measured and adjusted for age and sex. GxEE examination was performed on SOLAR 4.3.1. All metabolic syndrome indicators were significantly heritable. The GxEE interaction model fitted the data better than the polygenic model (p<0.001) for waist circumference, systolic blood pressure, glucose, total cholesterol and triglycerides. For waist circumference, glucose, total cholesterol and triglycerides, the significant GxEE interaction was due to rejection of the variance homogeneity hypothesis. For waist circumference and glucose, GxEE was also significant by the rejection of the genetic correlation hypothesis. The results showed that metabolic syndrome traits expression is significantly influenced by the interaction established between total daily energy expenditure and genotypes. Physical activity may be considered an environmental variable that promotes metabolic differences between individuals that are distinctively active.