Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children

Ong KK (2011) Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children. PLoS ONE 6(4): e19057. doi:10.1371/journal.pone.0019057 Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children Andreas Beyerlein 0 Ru diger von Kries 0 Andrew R. Ness 0 Ken K. Ong 0 Julian Little, University of Ottawa, Canada 0 1 Institute of Social Paediatrics and Adolescent Medicine, Ludwig-Maximilians University of Munich , Munich, Germany , 2 School of Oral and Dental Science , Bristol , United Kingdom , 3 MRC Epidemiology Unit, Institute of Metabolic Science , Cambridge , United Kingdom Background: Genetic factors are important determinants of overweight. We examined whether there are differential effect sizes depending on children's body composition. Methods: We analysed data of n = 4,837 children recorded in the Avon Longitudinal Study of Parents and Children (ALSPAC), applying quantile regression with sex- and age-specific standard deviation scores (SDS) of body mass index (BMI) or with body fat mass index and fat-free mass index at 9 years as outcome variables and an ''obesity-risk-allele score'' based on eight genetic variants known to be associated with childhood BMI as the explanatory variable. Results: The quantile regression coefficients increased with increasing child's BMI-SDS and fat mass index percentiles, indicating larger effects of the genetic factors at higher percentiles. While the associations with BMI-SDS were of similar size in medium and high BMI quantiles (40th percentile and above), effect sizes with fat mass index increased over the whole fat mass index distribution. For example, the fat mass index of a normal-weight (50th percentile) child was increased by 0.13 kg/m2 (95% confidence interval (CI): 0.09, 0.16) per additional allele, compared to 0.24 kg/m2 per allele (95% CI: 0.15, 0.32) in children at the 90th percentile. The genetic associations with fat-free mass index were weaker and the quantile regression effects less pronounced than those on fat mass index. Conclusions: Genetic risk factors for childhood overweight appear to have greater effects on fatter children. Interaction of known genetic factors with environmental or unknown genetic factors might provide a potential explanation of these findings. - Increasing prevalence of childhood overweight has been reported worldwide [1]. Genetic factors are important determinants of the overweight risk as has been shown in adoption and twin studies [2,3] and in observational studies pointing to the important role of maternal body mass index (BMI) in the development of overweight in children [4,5]. Recent genome-wide association (GWA) studies allowed identifying several genetic factors associated with childhood and adult obesity, such as variants of the FTO and MC4R genes [6,7]. Members of our study group recently combined eight genetic variants (which had shown individual associations with childhood BMI in previous studies) to a so-called obesity-risk-allele score and found strong statistical evidence for positive associations of this score with mean BMI and body fat mass at the age of 9 years [8]. Similarly, shifts in mean BMI have been observed for environmental factors which, upon more detailed scrutiny, were mainly caused by shifts in the upper tail of the distribution [9,10]. For example, we found that, while the middle part of the BMI distribution was similar at the age of 56 years in formerly breastfed and formula fed children, the lower tail showed higher values in breastfed children, and the upper tail lower values [11]. These analyses were performed with the use of quantile regression [12,13], a statistical method that offers a more comprehensive approach than the widely used linear regression. While linear regression focuses on shifts of the mean, quantile regression allows differentiating shifts in different parts of the distribution. We therefore hypothesized that effect sizes of genetic risk factors for overweight might be stronger in children with high compared to children with normal or low BMI or fat mass. In order to answer this question, we assessed BMI and fat mass dependent associations of genetic risk factors for childhood obesity by quantile regression. Materials and Methods Data The Avon Longitudinal Study of Parents and Children (ALSPAC) is a longitudinal birth cohort study of the determinants of development, health, and disease during childhood and beyond and has been described in more detail elsewhere [14]. Initially, 14,541 pregnant women with an expected date of delivery between April 1991 and December 1992 were enrolled; 13,971 of their children formed the original cohort at 1 y of age. Detailed information has been collected using self-administered questionnaires, data extraction from medical notes, and linkage to routine information systems and at research clinics. Ethical approval for the study was obtained from the ALSPAC Law and Ethics Committee and Local Research Ethics Committees. Publication of the final paper has been approved by the ALSPAC board. The Ethics Committee of the Physicians Chamber of Bavaria waived the need for consent, since this study was based on analyses of anonymized data. Childhood weight and height was measured annually between ages 7 and 11 y at dedicated ALSPAC Focus clinics by a trained research team. Height was measured to the nearest 0.1 cm using a Leicester Height Measure (Holtain Crosswell, Dyfed) and weight while wearing underwear was measured to the nearest 0.1 kg using Tanita electronic scales. Fat mass and fat-free mass was assessed (only) at the 9-year-old research clinic visit (at which 7,725 of the children were seen) by whole body dual energy X-ray absorptiometry (DXA) (Prodigy scanner, Lunar Radiation Corp, Madison, Wisconsin, US). We calculated BMI as weight/height2 (kg/m2). To adjust for sex and age, we transformed the observed BMI values to sex- and agespecific standard deviation scores (SDS) established by the World Health Organisation (WHO, available at: http://www.who.int/ growthref/en/) using the LMS method [15]. The position of childrens BMI values within the distribution (the quantile) did not change considerably by the age- and sex-adjusted transformation to BMI-SDS. For descriptive analyses, we defined overweight and obesity according to BMI reference values of the International Obesity Task Force (IOTF) [16]. We calculated fat and fat-free mass indices for each child from DXA measurements at age 9 y by dividing fat mass and fat-free mass (kg) by height squared (m2) [17]. Genotype information was available for 7,333 children with respect to six GWA-obesity variants previously reported to show association with BMI or obesity in children [6,7,18]; these variants were: rs9939609 (in/near to FTO); rs17782313 (MC4R), rs6548238 (TMEM18), rs10938397 (GNPDA2), rs368794 (KCTD15), rs2568958 (N (...truncated)