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

Genetic factors are important determinants of overweight. We examined whether there are differential effect sizes depending on children's body composition. 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. 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/m(2) (95% confidence interval (CI): 0.09, 0.16) per additional allele, compared to 0.24 kg/m(2) 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. 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

The Tecton Concept Library

Tecton is an algebraic specification language. This report contains a considerable body of Tecton concepts which evolved over a long time. The concepts serve as a test bed for a Tecton translator and are a formal base for declarations occurring in algorithms from all areas of programming but in particular from computer algebra

Applying Linear Quantifier Elimination

The linear quantifier elimination algorithm for ordered fields in [15] is applicable to a wide range of..