Marilyn C. Cornelis, PhD; Lu Qi, MD, PhD; Cuilin Zhang, MD, PhD; Peter Kraft, PhD; JoAnn Manson, MD, DPH; Tianxi Cai, PhD; David J. Hunter, MBBS, ScD; Frank B. Hu, MD, PhD
Cornelis MC, Qi L, Zhang C, Kraft P, Manson J, Cai T, et al. Joint Effects of Common Genetic Variants on the Risk for Type 2 Diabetes in U.S. Men and Women of European Ancestry. Ann Intern Med. 2009;150:541-550. doi: 10.7326/0003-4819-150-8-200904210-00008
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Published: Ann Intern Med. 2009;150(8):541-550.
Genome-wide association studies have identified novel type 2 diabetes loci, each of which has a modest impact on risk.
To examine the joint effects of several type 2 diabetes risk variants and their combination with conventional risk factors on type 2 diabetes risk in 2 prospective cohorts.
Nested caseâ€“control study.
2809 patients with type 2 diabetes and 3501 healthy control participants of European ancestry from the Health Professionals Follow-up Study and Nurses' Health Study.
A genetic risk score (GRS) was calculated on the basis of 10 polymorphisms in 9 loci.
After adjustment for age and body mass index (BMI), the odds ratio for type 2 diabetes with each point of GRS, corresponding to 1 risk allele, was 1.19 (95% CI, 1.14 to 1.24) and 1.16 (CI, 1.12 to 1.20) for men and women, respectively. Persons with a BMI of 30 kg/m2 or greater and a GRS in the highest quintile had an odds ratio of 14.06 (CI, 8.90 to 22.18) compared with persons with a BMI less than 25 kg/m2 and a GRS in the lowest quintile after adjustment for age and sex. Persons with a positive family history of diabetes and a GRS in the highest quintile had an odds ratio of 9.20 (CI, 5.50 to 15.40) compared with persons without a family history of diabetes and with a GRS in the lowest quintile. The addition of the GRS to a model of conventional risk factors improved discrimination by 1% (PÂ < 0.001).
The study focused only on persons of European ancestry; whether GRS is associated with type 2 diabetes in other ethnic groups remains unknown.
Although its discriminatory value is currently limited, a GRS that combines information from multiple genetic variants might be useful for identifying subgroups with a particularly high risk for type 2 diabetes.
National Institutes of Health.
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Cardiology, Coronary Risk Factors, Diabetes, Endocrine and Metabolism.
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