Genetic predisposition to higher waist-to-hip ratio predicts diabetes and coronary heart disease
Genetic Association of Waist-to-Hip Ratio With Cardiometabolic Traits, Type 2 Diabetes, and Coronary Heart Disease
Literature - Emdin CA, Khera AV, Natarajan P, et al. - JAMA. 2017;317(6):626Main results
A 48-SNP polygenic risk score for WHR adjusted for BMI was a strong instrumental variable (F = 1713), statistically accounting for 1.5% of variance in WHR adjusted for BMI. 1-SD increase in WHR adjusted for BMI due to the polygenic risk score was associated with:
- 1 point decrease in BMI (95% CI: 0.87-1.1)
- 2 cm increase in waist circumference (95% CI: 1.5-2.4)
- 4.1 cm decrease in hip circumference (95% CI: 3.8-4.4)
- increase of 0.068 in WHR (95% CI: 0.066-0.070)
- higher total cholesterol levels (5.6 mg/dL; 95% CI: 3.9-7.3 mg/dL; 0.15 mmol/L; 95% CI: 0.10-0.19 mmol/L)
- higher LDL-C levels (5.7 mg/dL; 95% CI: 4.1-7.2 mg/dL; 0.15 mmol/L; 95% CI: 0.11-0.19 mmol/L)
- higher triglyceride levels (27 mg/dL; 95% CI: 25-30 mg/dL; 0.31 mmol/L; 95% CI: 0.28-0.34 mmol/L)
- lower HDL-C levels (6.0 mg/dL; 95% CI: 5.3-6.6 mg/dL; 0.16 mmol/L; 95% CI: 0.14-0.17 mmol/L)
- higher log-transformed fasting insulin levels (0.07; 95% CI: 0.05-0.08 log[pmol/L])
- higher 2-hour glucose levels (4.1 mg/dL; 95% CI: 1.6-6.5 mg/dL; 0.23 mmol/L; 95% CI: 0.09-0.36 mmol/L)
- higher systolic blood pressure (2.1 mm Hg; 95% CI: 1.2-3.0 mm Hg)
- higher risk of T2DM (OR: 1.77; 95% CI: 1.57-2.00; absolute risk increase per 1000 participant-years: 6.0; 95% CI: 4.4-7.8; P = 7.30 × 10−21; number of participants with T2DM outcome: 40 530)
- higher risk of CHD (OR: 1.46; 95% CI: 1.32-1.62; absolute risk increase per 1000 participant-years: 1.8; 95% CI: 1.3-2.4; P = 9.90 × 10−14; number of participants with CHD outcome: 66 440)
Conclusion
In a mendelian randomisation study, genetic predisposition to higher WHR adjusted for BMI was associated with an increased risk of T2DM and CHD. These findings support a causal association between abdominal adiposity and these outcomes.
Editorial comment
In their editorial article [6], Smith, Paternoster and Relton discuss the mendelian randomisation methodology, its application in the Emdin et al study and its relevance to clinical practice. They conclude: ‘Mendelian randomization is slowly beginning to generate data of clear clinical and public health relevance. Attention to mendelian randomization data could have helped avoid several very expensive late-stage clinical trial failures and might improve prediction of what randomized controlled trials (RCTs) will show. Indeed, the adoption of mendelian randomization to prioritize (or deprioritize) major investment in RCTs before their inception should be actively encouraged.’ The conclusion from the first extended presentation of mendelian randomization 15 years ago is still apposite: ‘it is probably fair to say that the method offers a more robust approach to understanding the effect of some modifiable exposures on health outcomes than does much conventional observational epidemiology. Where possible RCTs remain the final arbiter of the effects of interventions intended to influence health, however.’
Share this page with your colleagues and friends: