Peer influence on obesity: Evidence from a natural experiment of a gene-environment interaction.
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ABSTRACT:
SUBMITTER: Li Y
PROVIDER: S-EPMC8607809 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Gene × Environment interaction contributes to externalizing disorders in childhood and adolescence, but little is known about whether such effects are long lasting or present in adulthood. We examined gene-environment interplay in the concurrent and prospective associations between antisocial peer affiliation and externalizing disorders (antisocial behavior and substance use disorders) at ages 17, 20, 24, and 29. The sample included 1,382 same-sex twin pairs participating in the Minnesota Twin Family Study. We detected a Gene × Environment interaction at age 17, such that additive genetic influences on antisocial behavior and substance use disorders were greater in the context of greater antisocial peer affiliation. This Gene × Environment interaction was not present for antisocial behavior symptoms after age 17, but it was for substance use disorder symptoms through age 29 (though effect sizes were largest at age 17). The results suggest adolescence is a critical period for the development of externalizing disorders wherein exposure to greater environmental adversity is associated with a greater expression of genetic risk. This form of Gene × Environment interaction may persist through young adulthood for substance use disorders, but it appears to be limited to adolescence for antisocial behavior.
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Project description:The epidemic of obesity has become a major public health problem. Common-form obesity is underpinned by both environmental and genetic factors. Epidemiological studies have documented that increased intakes of energy and reduced consumption of high-fiber foods, as well as sedentary lifestyle, were among the major driving forces for the epidemic of obesity. Recent genome-wide association studies have identified several genes convincingly related to obesity risk, including the fat mass and obesity associated gene and the melanocortin-4 receptor gene. Testing gene-environment interaction is a relatively new field. This article reviews recent advances in identifying the genetic and environmental risk factors (lifestyle and diet) for obesity. The evidence for gene-environment interaction, especially from observational studies and randomized intervention trials, is examined specifically. Knowledge about the interplay between genetic and environmental components may facilitate the choice of more effective and specific measures for obesity prevention based on the personalized genetic make-up.
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Project description:The authors draw data from the College Roommate Study (ROOM) and the National Longitudinal Study of Adolescent Health to investigate gene-environment interaction effects on youth binge drinking. In ROOM, the environmental influence was measured by the precollege drinking behavior of randomly assigned roommates. Random assignment safeguards against friend selection and removes the threat of gene-environment correlation that makes gene-environment interaction effects difficult to interpret. On average, being randomly assigned a drinking peer as opposed to a nondrinking peer increased college binge drinking by 0.5-1.0 episodes per month, or 20%-40% the average amount of binge drinking. However, this peer influence was found only among youths with a medium level of genetic propensity for alcohol use; those with either a low or high genetic propensity were not influenced by peer drinking. A replication of the findings is provided in data drawn from Add Health. The study shows that gene-environment interaction analysis can uncover social-contextual effects likely to be missed by traditional sociological approaches.
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Project description:We explored how gene-environment correlations can result in endogenous models, how natural experiments can protect against this threat, and if unbiased estimates from natural experiments are generalizable to other contexts.We compared a natural experiment, the College Roommate Study, which measured genes and behaviors of college students and their randomly assigned roommates in a southern public university, with observational data from the National Longitudinal Study of Adolescent Health in 2008. We predicted exposure to exercising peers using genetic markers and estimated environmental effects on alcohol consumption. A mixed-linear model estimated an alcohol consumption variance that was attributable to genetic markers and across peer environments.Peer exercise environment was associated with respondent genotype in observational data, but not in the natural experiment. The effects of peer drinking and presence of a general gene-environment interaction were similar between data sets.Natural experiments, like random roommate assignment, could protect against potential bias introduced by gene-environment correlations. When combined with representative observational data, unbiased and generalizable causal effects could be estimated.
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Project description:Peer deviance (PD) strongly predicts externalizing psychopathologic conditions but has not been previously assessable in population cohorts. We sought to develop such an index of PD and to clarify its effects on risk of drug abuse (DA).To examine how strongly PD increases the risk of DA and whether this community-level liability indicator interacts with key DA risk factors at the individual and family levels.Studies of future DA registration in 1,401,698 Swedish probands born from January 1, 1970, through December 31, 1985, and their adolescent peers in?approximately 9200 small community areas. Peer deviance was defined as the proportion of individuals born within 5 years of the proband living in the same small community when the proband was 15 years old who eventually were registered for DA.Drug abuse recorded in medical, legal, or pharmacy registry records.Peer deviance was associated with future DA in the proband, with rates of DA in older and male peers more strongly predictive than in younger or female peers. The predictive power of PD was only slightly attenuated by adding measures of community deprivation, collective efficacy, or family socioeconomic status. Probands whose parents were divorced were more sensitive to the pathogenic effects of high PD environments. A robust positive interaction was also seen between genetic risk of DA (indexed by rates of DA in first-, second-, and third-degree relatives) and PD exposure.With sufficient data, PD can be measured in populations and strongly predicts DA. In a nationwide sample, risk factors at the level of the individual (genetic vulnerability), family (parental loss), and community (PD) contribute substantially to risk of DA. Individuals at elevated DA risk because of parental divorce or high genetic liability are more sensitive to the pathogenic effects of PD. Although the effect of our PD measure on DA liability cannot be explained by standard measures of community or family risk, we cannot, with available data, discriminate definitively between the effect of true peer effects and other unmeasured risk factors.
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Project description:Adolescent drinking is an important public health concern, one that is influenced by both genetic and environmental factors. The functional variant rs1229984 in alcohol dehydrogenase 1B (ADH1B) has been associated at a genome-wide level with alcohol use disorders in diverse adult populations. However, few data are available regarding whether this variant influences early drinking behaviors and whether social context moderates this effect. This study examines the interplay between rs1229984 and peer drinking in the development of adolescent drinking milestones.One thousand five hundred and fifty European and African American individuals who had a full drink of alcohol before age 18 were selected from a longitudinal study of youth as part of the Collaborative Study on the Genetics of Alcoholism (COGA). Cox proportional hazards regression, with G × E product terms in the final models, was used to study 2 primary outcomes during adolescence: age of first intoxication and age of first DSM-5 alcohol use disorder symptom.The minor A allele of rs1229984 was associated with a protective effect for first intoxication (HR = 0.56, 95% CI 0.41 to 0.76) and first DSM-5 symptom (HR = 0.45, 95% CI 0.26 to 0.77) in the final models. Reporting that most or all best friends drink was associated with a hazardous effect for first intoxication (HR = 1.81, 95% CI 1.62 to 2.01) and first DSM-5 symptom (HR = 2.17, 95% 1.88 to 2.50) in the final models. Furthermore, there was a significant G × E interaction for first intoxication (p = 0.002) and first DSM-5 symptom (p = 0.01). Among individuals reporting none or few best friends drinking, the ADH1B variant had a protective effect for adolescent drinking milestones, but for those reporting most or all best friends drinking, this effect was greatly reduced.Our results suggest that the risk factor of best friends drinking attenuates the protective effect of a well-established ADH1B variant for 2 adolescent drinking behaviors. These findings illustrate the interplay between genetic and environmental factors in the development of drinking milestones during adolescence.
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Project description:PurposeExisting evidence on relationships between school food environments and children's in-school purchases, dietary behaviors, and body composition is based on observational studies that are vulnerable to residential selection bias.MethodsThis study leveraged exogenous variation in school environments generated by the natural experiment due to military parents' assignment to installations. We analyzed 1,010 child-wave observations from the Military Teenagers Environments, Exercise, and Nutrition Study collected during 2013-2015. Using multiple linear and logistic regression, we examined whether the number of competitive food and beverage (CF&B) items available for purchase in school, overall and by type (unhealthy, healthy, neutral), was associated with in-school food purchases, dietary behaviors, and body mass index (BMI) outcomes. Covariates included child and family characteristics and the healthiness of the home food environment.ResultsUnhealthy item availability was positively associated with purchasing any sweets (adjusted odds ratio [AOR], 1.30; p < .01), snacks (AOR, 1.23; p < .01), and sugar-sweetened beverages (AOR, 1.19; p = .01). However, there were no significant associations with overall food and beverage intake (e.g., sweets, soda) nor BMI outcomes. The home food environment was significantly associated with all outcomes.ConclusionsAccess to unhealthy CF&B items may influence in-school purchases but does not appear to influence overall dietary behaviors and BMI outcomes. Substitution of caloric intake across locations within versus outside of school may play a role in explaining why purchases were associated with unhealthy CF&B availability but overall diet and downstream BMI were not.
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Project description:The differential susceptibility model states that a given genetic variant is associated with an increased risk of pathology in negative environments but greater than average resilience in enriched ones. While this theory was first implemented in psychiatric-genetic research, it may also help us to unravel the complex ways that genes and environments interact to influence feeding behavior and obesity. We reviewed evidence on gene vs. environment interactions that influence obesity development, aiming to support the applicability of the differential susceptibility model for this condition, and propose that various environmental "layers" relevant for human development should be considered when bearing the differential susceptibility model in mind. Mother-child relationship, socioeconomic status and individual's response are important modifiers of BMI and food intake when interacting with gene variants, "for better and for worse". While only a few studies to date have investigated obesity outcomes using this approach, we propose that the differential susceptibility hypothesis is in fact highly applicable to the study of genetic and environmental influences on feeding behavior and obesity risk.
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Project description:The growing sample size of genome-wide association studies has facilitated the discovery of gene-environment interactions (GxE). Here we propose a maximum likelihood method to estimate the contribution of GxE to continuous traits taking into account all interacting environmental variables, without the need to measure any. Extensive simulations demonstrate that our method provides unbiased interaction estimates and excellent coverage. We also offer strategies to distinguish specific GxE from general scale effects. Applying our method to 32 traits in the UK Biobank reveals that while the genetic risk score (GRS) of 376 variants explains 5.2% of body mass index (BMI) variance, GRSxE explains an additional 1.9%. Nevertheless, this interaction holds for any variable with identical correlation to BMI as the GRS, hence may not be GRS-specific. Still, we observe that the global contribution of specific GRSxE to complex traits is substantial for nine obesity-related measures (including leg impedance and trunk fat-free mass).
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Project description:Gene-environment interactions have the potential to shed light on biological processes leading to disease and to improve the accuracy of epidemiological risk models. However, relatively few such interactions have yet been confirmed. In part this is because genetic markers such as tag SNPs are usually studied, rather than the causal variants themselves. Previous work has shown that this leads to substantial loss of power and increased sample size when gene and environment are independent. However, dependence between gene and environment can arise in several ways including mediation, pleiotropy, and confounding, and several examples of gene-environment interaction under gene-environment dependence have recently been published. Here we show that under gene-environment dependence, a statistical interaction can be present between a marker and environment even if there is no interaction between the causal variant and the environment. We give simple conditions under which there is no marker-environment interaction and note that they do not hold in general when there is gene-environment dependence. Furthermore, the gene-environment dependence applies to the causal variant and cannot be assessed from marker data. Gene-gene interactions are susceptible to the same problem if two causal variants are in linkage disequilibrium. In addition to existing concerns about mechanistic interpretations, we suggest further caution in reporting interactions for genetic markers.
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