46Objectives: To investigate the degree by which the inherited susceptibility to obesity is modified 47 by environmental factors during childhood and adolescence.
48Design: Cohort study with repeated measurements of diet, lifestyle factors and anthropometry. 49 Setting: The pan-European IDEFICS/I.Family cohort 50 Participants: 8,609 repeated observations from 3,098 children aged 2 to 16 years, examined 51 between 2007 and 2014.52 Main outcome measures: Body mass index (BMI) and waist circumference. Genome-wide 53 polygenic risk scores (PRS) to capture the inherited susceptibility of obesity were calculated 54 using summary statistics from independent genome-wide association studies of BMI. Gene-55 environment interactions of the PRS with sociodemographic (European region, socioeconomic 56 status) and lifestyle factors (diet, screen time, physical activity) were estimated.
57Results: The PRS was strongly associated with BMI (r 2 = 0.11, p-value = 7.9 x 10 -81 ) and waist 58 circumference (r 2 = 0.09, p-value = 1.8 x 10 -71 ) in our cohort. The associations with BMI 59 increased from r 2 =0.03 in 3-year olds to r 2 =0.18 in 14-year olds and associations with waist 60 circumference from r 2 =0.03 to r 2 =0.14. Being in the top decile of the PRS distribution was 61 associated with 3.63 times higher odds for obesity (95% confidence interval (CI): [2.57, 5.14]).
62We observed significant interactions with demographic and lifestyle factors for BMI as well as 63 waist circumference. The risk of becoming obese among those with higher genetic 64 susceptibility was ~38% higher in children from Southern Europe (BMI: p-interaction = 0.0066,
65Central vs. Southern Europe) and ~61% higher in children with a low parental education (BMI: 66 p-interaction = 0.0012, low vs. high). Furthermore, the risk was attenuated by a higher intake 67 of dietary fiber (BMI: p-interaction=0.0082) and shorter screen times (BMI: p-68 interaction=0.018).
69Conclusions: Our results highlight that a healthy childhood environment might partly offset a 70 genetic predisposition to obesity during childhood and adolescence. 71 72 73 4 74 activity, screen time, socio-demographic factors, polygenic risk score, waist circumference 75 83With the advent of genome-wide association studies (GWAS), it was shown that multiple 84 genetic loci increase the susceptibility to obesity [3,4]. However, genome-wide significant 85 variants identified in the first large-scale GWAS on body mass index (BMI) only account for a 86 small portion of BMI variation (~2.7%) [3]. A more recent genome-wide meta-analysis extended 87 the number of individuals from ~300,000 [3] to ∼700,000 [4], which consequently increased 88 the number of genome-wide significant SNPs from 97 to 751. Even these 751 genome-wide 89 significant SNPs account for only ∼6.0% of the variance of BMI [4]. However, genome-wide 90 estimates suggest that common variation accounts for >20% of BMI variation [3], which 91 highlights the polygenic architecture of BMI. More recently, whole genome data even increased 92 ...