BACKGROUND: Obesity is a multifactorial condition influenced by both genetics and lifestyle. The aim of this study was to investigate whether the association between a validated genetic profile risk score for obesity (GPRS-obesity) and body mass index (BMI) or waist circumference (WC) was modified by macronutrient intake in a large general population study. METHODS: This study included cross-sectional data from 48 170 white European adults, aged 37-73 years, participating in the UK Biobank. Interactions between GPRS-obesity and macronutrient intake (including total energy, protein, fat, carbohydrate and dietary fibre intake) and its effects on BMI and WC were investigated. RESULTS: The 93-single-nucleotide polymorphism (SNP) GPRS was associated with a higher BMI (β: 0.57 kg m-2 per s.d. increase in GPRS (95% confidence interval: 0.53-0.60); P=1.9 × 10-183) independent of major confounding factors. There was a significant interaction between GPRS and total fat intake (P(interaction)=0.007). Among high-fat-intake individuals, BMI was higher by 0.60 (0.52, 0.67) kg m-2 per s.d. increase in GPRS-obesity; the change in BMI with GPRS was lower among low-fat-intake individuals (β: 0.50 (0.44, 0.57) kg m-2). Significant interactions with similar patterns were observed for saturated fat intake (high β: 0.66 (0.59, 0.73) versus low β: 0.49 (0.42, 0.55) kg m-2, P(interaction)=2 × 10-4) and for total energy intake (high β: 0.58 (0.51, 0.64) versus low β: 0.49 (0.42, 0.56) kg m-2, P(interaction)=0.019), but not for protein intake, carbohydrate intake and fibre intake (P(interaction) >0.05). The findings were broadly similar using WC as the outcome. CONCLUSIONS: These data suggest that the benefits of reducing the intake of fats and total energy intake may be more important in individuals with high genetic risk for obesity.
BACKGROUND:Obesity is a multifactorial condition influenced by both genetics and lifestyle. The aim of this study was to investigate whether the association between a validated genetic profile risk score for obesity (GPRS-obesity) and body mass index (BMI) or waist circumference (WC) was modified by macronutrient intake in a large general population study. METHODS: This study included cross-sectional data from 48 170 white European adults, aged 37-73 years, participating in the UK Biobank. Interactions between GPRS-obesity and macronutrient intake (including total energy, protein, fat, carbohydrate and dietary fibre intake) and its effects on BMI and WC were investigated. RESULTS: The 93-single-nucleotide polymorphism (SNP) GPRS was associated with a higher BMI (β: 0.57 kg m-2 per s.d. increase in GPRS (95% confidence interval: 0.53-0.60); P=1.9 × 10-183) independent of major confounding factors. There was a significant interaction between GPRS and total fat intake (P(interaction)=0.007). Among high-fat-intake individuals, BMI was higher by 0.60 (0.52, 0.67) kg m-2 per s.d. increase in GPRS-obesity; the change in BMI with GPRS was lower among low-fat-intake individuals (β: 0.50 (0.44, 0.57) kg m-2). Significant interactions with similar patterns were observed for saturated fat intake (high β: 0.66 (0.59, 0.73) versus low β: 0.49 (0.42, 0.55) kg m-2, P(interaction)=2 × 10-4) and for total energy intake (high β: 0.58 (0.51, 0.64) versus low β: 0.49 (0.42, 0.56) kg m-2, P(interaction)=0.019), but not for protein intake, carbohydrate intake and fibre intake (P(interaction) >0.05). The findings were broadly similar using WC as the outcome. CONCLUSIONS: These data suggest that the benefits of reducing the intake of fats and total energy intake may be more important in individuals with high genetic risk for obesity.
Authors: K M Livingstone; C Celis-Morales; J Lara; A W Ashor; J A Lovegrove; J A Martinez; W H Saris; M Gibney; Y Manios; I Traczyk; C A Drevon; H Daniel; E R Gibney; L Brennan; J Bouwman; K A Grimaldi; J C Mathers Journal: Obes Rev Date: 2015-05-28 Impact factor: 9.213
Authors: Carlos Celis-Morales; Donald M Lyall; Yibing Guo; Lewis Steell; Daniel Llanas; Joey Ward; Daniel F Mackay; Stephany M Biello; Mark Es Bailey; Jill P Pell; Jason Mr Gill Journal: Am J Clin Nutr Date: 2017-03-01 Impact factor: 7.045
Authors: Jessica Tyrrell; Andrew R Wood; Ryan M Ames; Hanieh Yaghootkar; Robin N Beaumont; Samuel E Jones; Marcus A Tuke; Katherine S Ruth; Rachel M Freathy; George Davey Smith; Stéphane Joost; Idris Guessous; Anna Murray; David P Strachan; Zoltán Kutalik; Michael N Weedon; Timothy M Frayling Journal: Int J Epidemiol Date: 2017-04-01 Impact factor: 7.196
Authors: Qibin Qi; Audrey Y Chu; Jae H Kang; Jinyan Huang; Lynda M Rose; Majken K Jensen; Liming Liang; Gary C Curhan; Louis R Pasquale; Janey L Wiggs; Immaculata De Vivo; Andrew T Chan; Hyon K Choi; Rulla M Tamimi; Paul M Ridker; David J Hunter; Walter C Willett; Eric B Rimm; Daniel I Chasman; Frank B Hu; Lu Qi Journal: BMJ Date: 2014-03-19
Authors: Juan de Toro-Martín; Frédéric Guénard; Claude Bouchard; Angelo Tremblay; Louis Pérusse; Marie-Claude Vohl Journal: Front Genet Date: 2019-10-10 Impact factor: 4.599
Authors: María D Martínez-Martínez; Hugo Mendieta-Zerón; Luis Celis; Cristian F Layton-Tovar; Rocío Torres-García; Laura E Gutiérrez-Pliego; Eneida Camarillo-Romero; José D Garduño-García; María D Camarillo-Romero Journal: Sultan Qaboos Univ Med J Date: 2018-12-19