4.5 Article

Dietary fat and total energy intake modifies the association of genetic profile risk score on obesity: evidence from 48170 UK Biobank participants

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INTERNATIONAL JOURNAL OF OBESITY
卷 41, 期 12, 页码 1761-1768

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SPRINGERNATURE
DOI: 10.1038/ijo.2017.169

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资金

  1. Wellcome Trust
  2. Medical Research Council
  3. Department of Health, Scottish Government
  4. Northwest Regional Development Agency
  5. Welsh Assembly Government
  6. British Hcart Foundation
  7. Medical Research Council [MC_qA137853, MR/N015177/1] Funding Source: researchfish
  8. MRC [MR/N015177/1] Funding Source: UKRI

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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 (beta: 0.57 kg m(-2) per s.d. increase in GPRS (95% confidence interval: 0.53-0.60); P = 1.9 x 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 beta:0.50 (0.44, 0.57) kg m(-2)). Significant interactions with similar patterns were observed for saturated fat intake (high beta: 0.66 (0.59, 0.73) versus low beta: 0.49 (0.42, 0.55) kg m(-2) P-(interaction) = 2 x 10(-4)) and for total energy intake (high beta:0.58 (0.51, 0.64) versus low beta: 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.

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