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Assessing gene-environment interaction effects of FTO, MC4R and lifestyle factors on obesity using an extreme phenotype sampling design: Results from the HUNT study

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ABSTRACT

Background: Our aim was to assess the influence of age, gender and lifestyle factors on the effect of the obesity-promoting alleles of FTO and MCR4.

Methods: The HUNT study comprises health information on the population of Nord-Trøndelag county, Norway. Extreme phenotype participants (gender-wise lower and upper quartiles of waist-hip-ratio and BMI ≥ 35 kg/m2) in the third survey, HUNT3 (2006–08), were genotyped for the single-nucleotide polymorphisms rs9939609 (FTO) and rs17782313 (MC4R); 25686 participants were successfully genotyped. Extreme sampling was chosen to increase power to detect genetic and gene-environment effects on waist-hip-ratio and BMI. Statistical inference was based on linear regression models and a missing-covariate likelihood approach for the extreme phenotype sampling design. Environmental factors were physical activity, diet (artificially sweetened beverages) and smoking. Longitudinal analysis was performed using material from HUNT2 (1995–97).

Results: Cross-sectional and longitudinal genetic effects indicated stronger genetic associations with obesity in young than in old, as well as differences between women and men. We observed larger genetic effects among physically inactive compared to active individuals. This interaction was age-dependent and seen mainly in 20–40 year olds. We observed a greater FTO effect among men with a regular intake of artificially sweetened beverages, compared to non-drinkers. Interaction analysis of smoking was mainly inconclusive.

Conclusions: In a large all-adult and area-based population survey the effects of obesity-promoting minor-alleles of FTO and MCR4, and interactions with life style factors are age- and gender-related. These findings appear relevant when designing individualized treatment for and prophylaxis against obesity.

No MeSH data available.


Over-all genetic effects.Over-all effects of FTO and MC4R with 95% confidence intervals, for men and women in three age groups. Asterisk indicates FDR-adjusted p-value below 0.05 for testing H0: βSNP = 0 against H1: βSNP ≠ 0.
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pone.0175071.g001: Over-all genetic effects.Over-all effects of FTO and MC4R with 95% confidence intervals, for men and women in three age groups. Asterisk indicates FDR-adjusted p-value below 0.05 for testing H0: βSNP = 0 against H1: βSNP ≠ 0.

Mentions: Relevant sample sizes for our analysis are presented in Table 1. The age and gender groups varied in size between 3000 and 8000 participants, the largest being the 40–60 years age group. Estimates of βFTO and βMC4R in the over-all effects Model (1) and longitudinal effects Model (2) are presented Figs 1 and 2 and in S1 and S2 Tables. In S1 and S2 Tables we also report FDR-adjusted p-values for the hypothesis tests H0: βFTO = 0 against H1: βFTO ≠ 0, and H0: βMC4R = 0 against H1: βMC4R ≠ 0. Estimates of GEIs in Model (3), and adjusted p-values for the hypothesis tests H0: βFTO*ENV = 0 and H0: βMC4R*ENV = 0 are presented in Table 2 (physical activity), Table 3 (artificially sweetened beverages) and Table 4 (pack years of smoking). Out of the 120 tests for association that we performed, 24 tests had FDR-adjusted p-values below 0.05. Thus, by controlling the false discovery rate at a 0.05 significance level we have 24 findings. Below we summarize main findings based on both estimated effect sizes and significance of test results.


Assessing gene-environment interaction effects of FTO, MC4R and lifestyle factors on obesity using an extreme phenotype sampling design: Results from the HUNT study
Over-all genetic effects.Over-all effects of FTO and MC4R with 95% confidence intervals, for men and women in three age groups. Asterisk indicates FDR-adjusted p-value below 0.05 for testing H0: βSNP = 0 against H1: βSNP ≠ 0.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5383228&req=5

pone.0175071.g001: Over-all genetic effects.Over-all effects of FTO and MC4R with 95% confidence intervals, for men and women in three age groups. Asterisk indicates FDR-adjusted p-value below 0.05 for testing H0: βSNP = 0 against H1: βSNP ≠ 0.
Mentions: Relevant sample sizes for our analysis are presented in Table 1. The age and gender groups varied in size between 3000 and 8000 participants, the largest being the 40–60 years age group. Estimates of βFTO and βMC4R in the over-all effects Model (1) and longitudinal effects Model (2) are presented Figs 1 and 2 and in S1 and S2 Tables. In S1 and S2 Tables we also report FDR-adjusted p-values for the hypothesis tests H0: βFTO = 0 against H1: βFTO ≠ 0, and H0: βMC4R = 0 against H1: βMC4R ≠ 0. Estimates of GEIs in Model (3), and adjusted p-values for the hypothesis tests H0: βFTO*ENV = 0 and H0: βMC4R*ENV = 0 are presented in Table 2 (physical activity), Table 3 (artificially sweetened beverages) and Table 4 (pack years of smoking). Out of the 120 tests for association that we performed, 24 tests had FDR-adjusted p-values below 0.05. Thus, by controlling the false discovery rate at a 0.05 significance level we have 24 findings. Below we summarize main findings based on both estimated effect sizes and significance of test results.

View Article: PubMed Central - PubMed

ABSTRACT

Background: Our aim was to assess the influence of age, gender and lifestyle factors on the effect of the obesity-promoting alleles of FTO and MCR4.

Methods: The HUNT study comprises health information on the population of Nord-Trøndelag county, Norway. Extreme phenotype participants (gender-wise lower and upper quartiles of waist-hip-ratio and BMI ≥ 35 kg/m2) in the third survey, HUNT3 (2006–08), were genotyped for the single-nucleotide polymorphisms rs9939609 (FTO) and rs17782313 (MC4R); 25686 participants were successfully genotyped. Extreme sampling was chosen to increase power to detect genetic and gene-environment effects on waist-hip-ratio and BMI. Statistical inference was based on linear regression models and a missing-covariate likelihood approach for the extreme phenotype sampling design. Environmental factors were physical activity, diet (artificially sweetened beverages) and smoking. Longitudinal analysis was performed using material from HUNT2 (1995–97).

Results: Cross-sectional and longitudinal genetic effects indicated stronger genetic associations with obesity in young than in old, as well as differences between women and men. We observed larger genetic effects among physically inactive compared to active individuals. This interaction was age-dependent and seen mainly in 20–40 year olds. We observed a greater FTO effect among men with a regular intake of artificially sweetened beverages, compared to non-drinkers. Interaction analysis of smoking was mainly inconclusive.

Conclusions: In a large all-adult and area-based population survey the effects of obesity-promoting minor-alleles of FTO and MCR4, and interactions with life style factors are age- and gender-related. These findings appear relevant when designing individualized treatment for and prophylaxis against obesity.

No MeSH data available.