Heritability Of Body Mass Index Research Articles

Heritability of Body Mass Index Among Familial Generations

Heritability of Body Mass Index Among Familial Generations

Heritability of body mass index and physical activity in Ukrainian adolescents

The article analyzed the lifestyle and physical development of Ukrainian adolescents and their parents and estimated the familial aggregation and heritability of body mass index and physical activity. 408 nuclear families were examined (1216 people with complete information). Anthropometric measures such as weight, height were measured following standardized procedures of WHO. Questionnaires were used to estimate the levels of physical activity. The method of genetic epidemiology research was used to explore heritability (h2) and family aggregation (ρ). Analysis was performed using the software product S.A.G.E. The study showed that 12.0±1.6% of children were overweight or obese, 6.4±1.2% were underweight and 81.6±1.9% with normal weight. It was found that among adolescents aged 12-15 years, 17.5±3.1% of boys and 32.7±2.9% of girls were physically inactive. Body mass index values higher than 25.0 kg/m2 were found in 34.3±2.4 mothers and in 70.6±2.3% of fathers. The proportion of physically inactive persons was 45.7±2.5% among mothers and 51.1±2.7% among fathers. Heritability values were significant for both body mass index (h2 =0.41±0.09; p<0.001) and physical activity (h2 =0.23±0.07; p<0.001). Significant familial correlations were obtained between parents-offspring for physical activity (ρ=0.20±0.04; p<0.001) and body mass index (ρ=0.25±0.03; p<0.001). The study estimated that the familial correlations for physical activity between mother-son and mother-daughter pairs were higher than in father-son and father-daughter pairs. The highest is the mother-daughter aggregation (ρ = 0.29 ± 0.06; p <0.001), the lowest is the father-son (ρ=0.19±0.08; p<0.05) by body mass index. As physical inactivity and overweight increase the risk of non-communicable diseases development, the data obtained should be taken into account while planning preventive measures.

Exploring the Genetic Association between Obesity and Serum Lipid Levels Using Bivariate Methods.

It is crucial to understand the genetic mechanisms and biological pathways underlying the relationship between obesity and serum lipid levels. Structural equation models (SEMs) were constructed to calculate heritability for body mass index (BMI), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and the genetic connections between BMI and the four classes of lipids using 1197 pairs of twins from the Chinese National Twin Registry (CNTR). Bivariate genomewide association studies (GWAS) were performed to identify genetic variants associated with BMI and lipids using the records of 457 individuals, and the results were further validated in 289 individuals. The genetic background affecting BMI may differ by gender, and the heritability of males and females was 71% (95% CI [.66, .75]) and 39% (95% CI [.15, .71]) respectively. BMI was positively correlated with TC, TG and LDL-C in phenotypic and genetic correlation, while negatively correlated with HDL-C. There were gender differences in the correlation between BMI and lipids. Bivariate GWAS analysis and validation stage found 7 genes (LOC105378740, LINC02506, CSMD1, MELK, FAM81A, ERAL1 and MIR144) that were possibly related to BMI and lipid levels. The significant biological pathways were the regulation of cholesterol reverse transport and the regulation of high-density lipoprotein particle clearance (p < .001). BMI and blood lipid levels were affected by genetic factors, and they were genetically correlated. There might be gender differences in their genetic correlation. Bivariate GWAS analysis found MIR144 gene and its related biological pathways may influence obesity and lipid levels.

Sex-specific epigenetic development in the mouse hypothalamic arcuate nucleus pinpoints human genomic regions associated with body mass index.

Recent genome-wide association studies corroborate classical research on developmental programming indicating that obesity is primarily a neurodevelopmental disease strongly influenced by nutrition during critical ontogenic windows. Epigenetic mechanisms regulate neurodevelopment; however, little is known about their role in establishing and maintaining the brain’s energy balance circuitry. We generated neuron and glia methylomes and transcriptomes from male and female mouse hypothalamic arcuate nucleus, a key site for energy balance regulation, at time points spanning the closure of an established critical window for developmental programming of obesity risk. We find that postnatal epigenetic maturation is markedly cell type and sex specific and occurs in genomic regions enriched for heritability of body mass index in humans. Our results offer a potential explanation for both the limited ontogenic windows for and sex differences in sensitivity to developmental programming of obesity and provide a rich resource for epigenetic analyses of developmental programming of energy balance.

The heritability of BMI varies across the range of BMI-a heritability curve analysis in a twin cohort.

The heritability of traits such as body mass index (BMI), a measure of obesity, is generally estimated using family and twin studies, and increasingly by molecular genetic approaches. These studies generally assume that genetic effects are uniform across all trait values, yet there is emerging evidence that this may not always be the case. This paper analyzes twin data using a recently developed measure of heritability called the heritability curve. Under the assumption that trait values in twin pairs are governed by a flexible Gaussian mixture distribution, heritability curves may vary across trait values. The data consist of repeated measures of BMI on 1506 monozygotic (MZ) and 2843 like-sexed dizygotic (DZ) adult twin pairs, gathered from multiple surveys in older Finnish Twin Cohorts. The heritability curve and BMI value-specific MZ and DZ pairwise correlations were estimated, and these varied across the range of BMI. MZ correlations were highest at BMI values from 21 to 24, with a stronger decrease for women than for men at higher values. Models with additive and dominance effects fit best at low and high BMI values, while models with additive genetic and common environmental effects fit best in the normal range of BMI. We demonstrate that twin and molecular genetic studies need to consider how genetic effects vary across trait values. Such variation may reconcile findings of traits with high heritability and major differences in mean values between countries or over time.

Heritability and genetic correlation of body mass index and coronary heart disease in Chinese adult twins

Objective: To examine the heritability of body mass index (BMI) and coronary heart disease (CHD), and to explore whether genetic factors can explain their correlation. Methods: Participants were from 11 provinces/municipalities reqistered in the Chinese National Twin Registry (CNTR) from 2010 to 2018. Participants data were collected from face-to-face questionnaire survey. Bivariate structure equation model was used to estimate the heritability and the genetic correlation of BMI and CHD. Results: A total of 20 340 pairs of same-sex twins aged ≥25 years were included in this study. After adjusting for age and gender, the heritability of BMI and CHD was 0.52 (95%CI: 0.49-0.55) and 0.76 (95%CI: 0.69-0.81), respectively. Further, a genetic correlation was identified between BMI and CHD (rA=0.10, 95%CI:0.02-0.17). Conclusion: In Chinese adult twin population, BMI and CHD are affected by genetic factors, and their correlation can be attributed to the common genetic basis.

Heritability of body mass index based on twin studies: a Meta-analysis

Objective: To use Meta analysis to understand the prevalence of the heritability of body mass index (BMI) in twins. Methods: All studies on the heritability of the twins' BMI published before December 31, 2020 were retrieved through the China National Knowledge Network, Wanfang, VIP, PubMed and Web of Science databases. The literature quality was evaluated by using Joanna Briggs Institute Critical Appraisal tools. Stata 16.0 was used to perform subgroup analysis on the outcome indicators (heritability, 95%CI) to explore the source of heterogeneity. The local weighted regression method was used to fit the trend of heritability with age. The publication bias test and the sensitivity analysis of included literatures were also performed by using Stata 16.0. Results: A total of 10 articles meeting the inclusion and exclusion criteria were included with 79 twins' independent estimates of heritability for BMI. Meta-analysis showed that the combined value of BMI heritability was 0.69 (95%CI: 0.65-0.71), the combined value of BMI (0.68, 95%CI: 0.65-0.70) in males was lower than that (0.70, 95%CI: 0.68-0.72) in females. The heritability of BMI (0.72, 95%CI: 0.68-0.76) in childhood and adolescence was higher than that (0.68, 95%CI: 0.66-0.70) in adulthood. The gender specific difference in BMI heritability in twins ≤18 years old was even greater, which was lower in males (0.68, 95%CI: 0.61-0.76) than in females (0.75, 95%CI: 0.69-0.81). The heritability increased with age in childhood, reached peak at about 18 years old, and then slowly decreased with age. Conclusions: The heritability of BMI varied with population characteristics, especially age and gender. In view of the high estimated value of BMI heritability in female children and adolescents, more attention should be paid to the start time of health intervention.

Genetic mapping of etiologic brain cell types for obesity

The underlying cell types mediating predisposition to obesity remain largely obscure. Here, we integrated recently published single-cell RNA-sequencing (scRNA-seq) data from 727 peripheral and nervous system cell types spanning 17 mouse organs with body mass index (BMI) genome-wide association study (GWAS) data from >457,000 individuals. Developing a novel strategy for integrating scRNA-seq data with GWAS data, we identified 26, exclusively neuronal, cell types from the hypothalamus, subthalamus, midbrain, hippocampus, thalamus, cortex, pons, medulla, pallidum that were significantly enriched for BMI heritability (p<1.6×10-4). Using genes harboring coding mutations associated with obesity, we replicated midbrain cell types from the anterior pretectal nucleus and periaqueductal gray (p<1.2×10-4). Together, our results suggest that brain nuclei regulating integration of sensory stimuli, learning and memory are likely to play a key role in obesity and provide testable hypotheses for mechanistic follow-up studies.

Associations Between Physical Fitness and Brain Structure in Young Adulthood.

A comprehensive analysis of associations between physical fitness and brain structure in young adulthood is lacking, and further, it is unclear the degree to which associations between physical fitness and brain health can be attributed to a common genetic pathway or to environmental factors that jointly influences physical fitness and brain health. This study examined genotype-confirmed monozygotic and dizygotic twins, along with non-twin full-siblings to estimate the contribution of genetic and environmental factors to variation within, and covariation between, physical fitness and brain structure. Participants were 1,065 young adults between the ages of 22 and 36 from open-access Young Adult Human Connectome Project (YA-HCP). Physical fitness was assessed by submaximal endurance (2-min walk test), grip strength, and body mass index. Brain structure was assessed using magnetic resonance imaging on a Siemens 3T customized ‘Connectome Skyra’ at Washington University in St. Louis, using a 32-channel Siemens head coil. Acquired T1-weighted images provided measures of cortical surface area and thickness, and subcortical volume following processing by the YA-HCP structural FreeSurfer pipeline. Diffusion weighted imaging was acquired to assess white matter tract integrity, as measured by fractional anisotropy, following processing by the YA-HCP diffusion pipeline and tensor fit. Following correction for multiple testing, body mass index was negatively associated with fractional anisotropy in various white matter regions of interest (all | z| statistics > 3.9) and positively associated with cortical thickness within the right superior parietal lobe (z statistic = 4.6). Performance-based measures of fitness (i.e., endurance and grip strength) were not associated with any structural neuroimaging markers. Behavioral genetic analysis suggested that heritability of white matter integrity varied by region, but consistently explained >50% of the phenotypic variation. Heritability of right superior parietal thickness was large (∼75% variation). Heritability of body mass index was also fairly large (∼60% variation). Generally, to of the correlation between brain structure and body mass index could be attributed to heritability effects. Overall, this study suggests that greater body mass index is associated with lower white matter integrity, which may be due to common genetic effects that impact body composition and white matter integrity.

Genetics of Obesity in East Asians.

Obesity has become a public health problem worldwide. Compared with Europe, people in Asia tend to suffer from type 2 diabetes with a lower body mass index (BMI). Genome-wide association studies (GWASs) have identified over 750 loci associated with obesity. Although the majority of GWAS results were conducted in individuals of European ancestry, a recent GWAS in individuals of Asian ancestry has made a significant contribution to the identification of obesity susceptibility loci. Indeed, owing to the multifactorial character of obesity with a strong environmental component, the revealed loci may have distinct contributions in different ancestral genetic backgrounds and in different environments as presented through diet and exercise among other factors. Uncovering novel, yet unrevealed genes in non-European ancestries may further contribute to explaining the missing heritability for BMI. In this review, we aimed to summarize recent advances in obesity genetics in individuals of Asian ancestry. We therefore compared proposed mechanisms underlying susceptibility loci for obesity associated with individuals of European and Asian ancestries and discussed whether known genetic variants might explain ethnic differences in obesity risk. We further acknowledged that GWAS implemented in individuals of Asian ancestries have not only validated the potential role of previously specified obesity susceptibility loci but also exposed novel ones, which have been missed in the initial genetic studies in individuals of European ancestries. Thus, multi-ethnic studies have a great potential not only to contribute to a better understanding of the complex etiology of human obesity but also potentially of ethnic differences in the prevalence of obesity, which may ultimately pave new avenues in more targeted and personalized obesity treatments.

Genetic mapping of etiologic brain cell types for obesity

The underlying cell types mediating predisposition to obesity remain largely obscure. Here, we integrated recently published single-cell RNA-sequencing (scRNA-seq) data from 727 peripheral and nervous system cell types spanning 17 mouse organs with body mass index (BMI) genome-wide association study (GWAS) data from >457,000 individuals. Developing a novel strategy for integrating scRNA-seq data with GWAS data, we identified 26, exclusively neuronal, cell types from the hypothalamus, subthalamus, midbrain, hippocampus, thalamus, cortex, pons, medulla, pallidum that were significantly enriched for BMI heritability (p<1.6×10-4). Using genes harboring coding mutations associated with obesity, we replicated midbrain cell types from the anterior pretectal nucleus and periaqueductal gray (p<1.2×10-4). Together, our results suggest that brain nuclei regulating integration of sensory stimuli, learning and memory are likely to play a key role in obesity and provide testable hypotheses for mechanistic follow-up studies.

Unpacking the heritability of body mass index and other ratios.

Ratios of weight to height, especially body mass index (BMI = kg/m2 ), are often used in epidemiological and genetic studies of health, but the limitations of quantitative genetic analysis of ratios are not widely known. The heritability of these ratios can be closely approximated from a bivariate quantitative genetic model of weight and height which clarifies how BMI heritabilities change. I explored this bivariate approximation and alternative measures through simulated datasets fit with linear mixed models. Simulated data were based on published heritabilities and other statistics for BMI and related anthropometric dimensions from four human samples. Inspection of the bivariate approximation and analysis of simulated data show the heritability of weight/height crucially depends on the phenotypic (rP ) and genetic correlations (rA ) between weight and height. Changes in these correlations can have dramatic effects on the heritability of BMI. For example, when rP ≪ rA heritability of BMI is reduced to 35-50% of its value when the correlations are equal. Increasing adiposity likely decreases the phenotypic correlations more than the genetic correlation resulting in reduced heritability of the ratio. This contrasts with the commonly reported stability or increase of BMI heritability and implies it may result from increased genetic variance in weight in obesogenic environments. The bivariate model offers other advantages over ratios, including estimating the conditional genetic variance or heritability of weight that is unassociated with height, which may prove useful in quantitative and molecular genetic studies.

Variation in the Heritability of Child Body Mass Index by Obesogenic Home Environment

The early obesogenic home environment is consistently identified as a key influence on child weight trajectories, but little research has examined the mechanisms of that influence. Such research is essential for the effective prevention and treatment of overweight and obesity. To test behavioral susceptibility theory's hypothesis that the heritability of body mass index (BMI) is higher among children who live in more obesogenic home environments. This study was a gene-environment interaction twin study that used cross-sectional data from 925 families (1850 twins) in the Gemini cohort (a population-based prospective cohort of twins born in England and Wales between March and December 2007). Data were analyzed from July to October 2013 and in June 2018. Parents completed the Home Environment Interview, a comprehensive measure of the obesogenic home environment in early childhood. Three standardized composite scores were created to capture food, physical activity, and media-related influences in the home; these were summed to create an overall obesogenic risk score. The 4 composite scores were split on the mean, reflecting higher-risk and lower-risk home environments. Quantitative genetic model fitting was used to estimate heritability of age-adjusted and sex-adjusted BMI (BMI SD score, estimated using British 1990 growth reference data) for children living in lower-risk and higher-risk home environments. Among 1850 twins (915 [49.5%] male and 935 [50.5%] female; mean [SD] age, 4.1 [0.4] years), the heritability of BMI SD score was significantly higher among children living in overall higher-risk home environments (86%; 95% CI, 68%-89%) compared with those living in overall lower-risk home environments (39%; 95% CI, 21%-57%). The findings were similar when examining the heritability of BMI in the separate food and physical activity environment domains. These findings support the hypothesis that obesity-related genes are more strongly associated with BMI in more obesogenic home environments. Modifying the early home environment to prevent weight gain may be particularly important for children genetically at risk for obesity.

ACEt: An R Package for Estimating Dynamic Heritability and Comparing Twin Models.

Estimating dynamic effects of age on the genetic and environmental variance components in twin studies may contribute to the investigation of gene-environment interactions, and may provide more insights into more accurate and powerful estimation of heritability. Existing parametric models for estimating dynamic variance components suffer from various drawbacks such as limitation of predefined functions. We present ACEt, an R package for fast estimating dynamic variance components and heritability that may change with respect to age or other moderators. Building on the twin models using penalized splines, ACEt provides a unified framework to incorporate a class of ACE models, in which each component can be modeled independently and is not limited by a linear or quadratic function. We demonstrate that ACEt is robust against misspecification of the number of spline knots, and offers a refined resolution of dynamic behavior of the genetic and environmental components and thus a detailed estimation of age-specific heritability. Moreover, we develop resampling methods for testing twin models with different variance functions including splines, log-linearity and constancy, which can be easily employed to verify various model assumptions. We evaluated the type I error rate and statistical power of the proposed hypothesis testing procedures under various scenarios using simulated datasets. Potential numerical issues and computational cost were also assessed through simulations. We applied the ACEt package to a Finnish twin cohort to investigate age-specific heritability of body mass index and height. Our results show that the age-specific variance components of these two traits exhibited substantially different patterns despite of comparable estimates of heritability. In summary, the ACEt R package offers a useful tool for the exploration of age-dependent heritability and model comparison in twin studies.

Association between birth cohort and the heritability of body mass index

Objective: To investigate the varying variances of the genetic components in birth cohorts. Methods: Twin samples used in the current study were collected from the Chinese National Twin Registry and a two-wave study was conducted, in Qingdao and Lishui regions. Samples were broken down by birth cohort to create four subgroups: -1958, 1959-1961, 1962-1970 and 1970-. Structural equation models were fitted in each subgroup to estimate the genetic and environmental variances. Results: From each birth cohort, weight and body mass index in 2012 appeared higher than those in 2001. Twins of 1971- cohort subgroup showed lower weight than in the other cohort subgroups. Except for the 1959-1961 cohort subgroup, the later birth cohorts were inversely related to the body mass indexes. Genetic factors might explain 54%-76% of the total variations on the body mass index. Heritability of body mass index of twins born during 1959-1961 was increasing along with age. Conclusion: Genetic factors might explain the main portion which related to the phenotypic variance of body mass index. Effects of genetic factors on body mass index of twins born during 1959-1961 might have increased along with age.

Genotype-covariate interaction effects and the heritability of adult body mass index.

Obesity is a worldwide epidemic, with major health and economic costs. Here we estimate heritability for body mass index (BMI) in 172,000 sibling pairs and 150,832 unrelated individuals and explore the contribution of genotype-covariate interaction effects at common SNP loci. We find evidence for genotype-age interaction (likelihood ratio test (LRT) = 73.58, degrees of freedom (df) = 1, P = 4.83 × 10-18), which contributed 8.1% (1.4% s.e.) to BMI variation. Across eight self-reported lifestyle factors, including diet and exercise, we find genotype-environment interaction only for smoking behavior (LRT = 19.70, P = 5.03 × 10-5 and LRT = 30.80, P = 1.42 × 10-8), which contributed 4.0% (0.8% s.e.) to BMI variation. Bayesian association analysis suggests that BMI is highly polygenic, with 75% of the SNP heritability attributable to loci that each explain <0.01% of the phenotypic variance. Our findings imply that substantially larger sample sizes across ages and lifestyles are required to understand the full genetic architecture of BMI.

Detection of gene-environment interaction in pedigree data using genome-wide genotypes.

Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include moderation of (total and SNP-based) genetic and environmental variance components by a measured moderator. By means of data simulation, we demonstrated that the type 1 error rates of the proposed test are correct and parameter estimates are accurate. As an application, we considered the moderation by age or year of birth of variance components associated with body mass index (BMI), height, attention problems (AP), and symptoms of anxiety and depression. The genetic variance of BMI was found to increase with age, but the environmental variance displayed a greater increase with age, resulting in a proportional decrease of the heritability of BMI. Environmental variance of height increased with year of birth. The environmental variance of AP increased with age. These results illustrate the assessment of moderation of environmental and genetic effects, when estimating heritability from combined SNP and family data. The assessment of moderation of genetic and environmental variance will enhance our understanding of the genetic architecture of complex traits.

Association of FTO rs9939609 SNP with Obesity and Obesity- Associated Phenotypes in a North Indian Population.

Obesity is a common disorder that has a significant impact on morbidity and mortality. Twin and adoption studies support the genetic influence on variation of obesity, and the estimates of the heritability of body mass index (BMI) is significantly high (30 to 70%). Variants in the fat mass and obesity-associated (FTO) gene have been associated with obesity and obesity-related phenotypes in different populations. The aim of this study was to examine the association of FTO rs9939609 with obesity and related phenotypes in North Indian subjects. . Gene variants were investigated for association with obesity in 309 obese and 333 non-obese patients. Genotyping of the FTO rs9939609 single nucleotide polymorphism (SNP) was analyzed using Restriction Fragment Length Polymorphism Analysis of PCR-Amplified Fragments. We also measured participants fasting glucose and insulin levels, lipid profile, percentage body fat, fat mass and fat free mass. . Waist to hip ratio, systolic blood pressure, diastolic blood pressure, percentage body fat, fat mass, insulin concentration, and homeostasis model assessment index (HOMA-Index) showed a significant difference between the study groups. Significant associations were found for FTO rs9939609 SNP with obesity and obesity-related phenotypes. The significant associations were observed between the rs9939609 SNP and blood pressure, fat mass, insulin, and HOMA-index under a different model. . This study presents significant association between FTO rs9939609 and obesity defined by BMI and also established the strong association with several measures of obesity in North Indian population.

Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models.

Twin studies have been adopted for decades to disentangle the relative genetic and environmental contributions for a wide range of traits. However, heritability estimation based on the classical twin models does not take into account dynamic behavior of the variance components over age. Varying variance of the genetic component over age can imply the existence of gene-environment (G×E) interactions that general genome-wide association studies (GWAS) fail to capture, which may lead to the inconsistency of heritability estimates between twin design and GWAS. Existing parametricG×Einteraction models for twin studies are limited by assuming a linear or quadratic form of the variance curves with respect to a moderator that can, however, be overly restricted in reality. Here we propose spline-based approaches to explore the variance curves of the genetic and environmental components. We choose the additive genetic, common, and unique environmental variance components (ACE) model as the starting point. We treat the component variances as variance functions with respect to age modeled by B-splines or P-splines. We develop an empirical Bayes method to estimate the variance curves together with their confidence bands and provide an R package for public use. Our simulations demonstrate that the proposed methods accurately capture dynamic behavior of the component variances in terms of mean square errors with a data set of >10,000 twin pairs. Using the proposed methods as an alternative and major extension to the classical twin models, our analyses with a large-scale Finnish twin data set (19,510 MZ twins and 27,312 DZ same-sex twins) discover that the variances of the A, C, and E components for body mass index (BMI) change substantially across life span in different patterns and the heritability of BMI drops to ∼50% after middle age. The results further indicate that the decline of heritability is due to increasing unique environmental variance, which provides more insights into age-specific heritability of BMI and evidence ofG×Einteractions. These findings highlight the fundamental importance and implication of the proposed models in facilitating twin studies to investigate the heritability specific to age and other modifying factors.

Genetic and environmental contributions to body mass index in a Spanish adolescent twin sample

Background and objectiveTwin and family studies support large genetic influences on variability in body mass index (BMI), with heritability estimates ranging from 47% to over 90%. Our objective was to study the relative contributions of genetics and environment to BMI, evaluating sex differences, in an adolescent twin sample from Valencia, Spain. Material and methodsFive hundred eighty-four pairs of adolescent twins between 13 and 18 years of age completed the study (82 monozygotic [MZ] and 87 dizygotic [DZ] pairs of male twins, 118 MZ and 102 DZ pairs of female twins, and 195 opposite-sex pairs of DZ twins). To determine zygosity, teachers responded a questionnaire on physical similarity. They also measured the participant's height and weight. BMI was calculated and weight status was determined according to age. We used twin models to assess genetic and environmental (common and unique) factors affecting BMI. ResultsThere was a 7.1% frequency of overweight and 2.8% of obesity. The estimated heritability of BMI was 88.0% in boys and 72.1% in girls, with the remaining variance attributable to non-shared environment in boys (12.0%) and 8.8% in girls. It was only in girls that common environment had an effect on BMI. ConclusionsGenetics appears to play an important role in explaining the variability in BMI in the adolescence, with slight variations between boys and girls. Common environmental factors exert their influence on BMI only in girls.