Polygenic risk for obesity and its interaction with lifestyle and sociodemographic factors in European children and adolescents

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Hüls , A , Wright , M N , Bogl , L H , Kaprio , J , Lissner , L , Molnar , D , Moreno , L A , Stefaan De Henauw , Siani , A , Veidebaum , T , Ahrens , W , Pigeot , I & Foraita , R 2021 , ' Polygenic risk for obesity and its interaction with lifestyle and sociodemographic factors in European children and adolescents ' , International Journal of Obesity , vol. 45 , no. 6 , pp. 1321-1330 . https://doi.org/10.1038/s41366-021-00795-5

Title: Polygenic risk for obesity and its interaction with lifestyle and sociodemographic factors in European children and adolescents
Author: Hüls, Anke; Wright, Marvin N.; Bogl, Leonie H.; Kaprio, Jaakko; Lissner, Lauren; Molnar, Denes; Moreno, Luis A.; Stefaan De Henauw; Siani, Alfonso; Veidebaum, Toomas; Ahrens, Wolfgang; Pigeot, Iris; Foraita, Ronja
Contributor organization: Institute for Molecular Medicine Finland
Department of Public Health
University of Helsinki
Date: 2021-06
Language: eng
Number of pages: 10
Belongs to series: International Journal of Obesity
ISSN: 0307-0565
DOI: https://doi.org/10.1038/s41366-021-00795-5
URI: http://hdl.handle.net/10138/340334
Abstract: Background Childhood obesity is a complex multifaceted condition, which is influenced by genetics, environmental factors, and their interaction. However, these interactions have mainly been studied in twin studies and evidence from population-based cohorts is limited. Here, we analyze the interaction of an obesity-related genome-wide polygenic risk score (PRS) with sociodemographic and lifestyle factors for BMI and waist circumference (WC) in European children and adolescents. Methods The analyses are based on 8609 repeated observations from 3098 participants aged 2-16 years from the IDEFICS/I.Family cohort. A genome-wide polygenic risk score (PRS) was calculated using summary statistics from independent genome-wide association studies of BMI. Associations were estimated using generalized linear mixed models adjusted for sex, age, region of residence, parental education, dietary intake, relatedness, and population stratification. Results The PRS was associated with BMI (beta estimate [95% confidence interval (95%-CI)] = 0.33 [0.30, 0.37], r(2) = 0.11, p value = 7.9 x 10(-81)) and WC (beta [95%-CI] = 0.36 [0.32, 0.40], r(2) = 0.09, p value = 1.8 x 10(-71)). We observed significant interactions with demographic and lifestyle factors for BMI as well as WC. Children from Southern Europe showed increased genetic liability to obesity (BMI: beta [95%-CI] = 0.40 [0.34, 0.45]) in comparison to children from central Europe (beta [95%-CI] = 0.29 [0.23, 0.34]), p-interaction = 0.0066). Children of parents with a low level of education showed an increased genetic liability to obesity (BMI: beta [95%-CI] = 0.48 [0.38, 0.59]) in comparison to children of parents with a high level of education (beta [95%-CI] = 0.30 [0.26, 0.34]), p-interaction = 0.0012). Furthermore, the genetic liability to obesity was attenuated by a higher intake of fiber (BMI: beta [95%-CI] interaction = -0.02 [-0.04,-0.01]) and shorter screen times (beta [95%-CI] interaction = 0.02 [0.00, 0.03]). Conclusions Our results highlight that a healthy childhood environment might partly offset a genetic predisposition to obesity during childhood and adolescence.
Subject: 3121 General medicine, internal medicine and other clinical medicine
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion


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