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

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), apply...

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Autores principales: Beyerlein, Andreas, von Kries, Rüdiger, Ness, Andrew R., Ong, Ken K.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3078148/
https://www.ncbi.nlm.nih.gov/pubmed/21526213
http://dx.doi.org/10.1371/journal.pone.0019057
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author Beyerlein, Andreas
von Kries, Rüdiger
Ness, Andrew R.
Ong, Ken K.
author_facet Beyerlein, Andreas
von Kries, Rüdiger
Ness, Andrew R.
Ong, Ken K.
author_sort Beyerlein, Andreas
collection PubMed
description 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/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. 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.
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spelling pubmed-30781482011-04-27 Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children Beyerlein, Andreas von Kries, Rüdiger Ness, Andrew R. Ong, Ken K. PLoS One Research Article 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/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. 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. Public Library of Science 2011-04-15 /pmc/articles/PMC3078148/ /pubmed/21526213 http://dx.doi.org/10.1371/journal.pone.0019057 Text en Beyerlein et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Beyerlein, Andreas
von Kries, Rüdiger
Ness, Andrew R.
Ong, Ken K.
Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children
title Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children
title_full Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children
title_fullStr Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children
title_full_unstemmed Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children
title_short Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children
title_sort genetic markers of obesity risk: stronger associations with body composition in overweight compared to normal-weight children
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3078148/
https://www.ncbi.nlm.nih.gov/pubmed/21526213
http://dx.doi.org/10.1371/journal.pone.0019057
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