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Previous Volume 359:2208-2219 November 20, 2008 Number 21 Next

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ABSTRACT

Background Multiple genetic loci have been convincingly associated with the risk of type 2 diabetes mellitus. We tested the hypothesis that knowledge of these loci allows better prediction of risk than knowledge of common phenotypic risk factors alone.

Methods We genotyped single-nucleotide polymorphisms (SNPs) at 18 loci associated with diabetes in 2377 participants of the Framingham Offspring Study. We created a genotype score from the number of risk alleles and used logistic regression to generate C statistics indicating the extent to which the genotype score can discriminate the risk of diabetes when used alone and in addition to clinical risk factors.

Results There were 255 new cases of diabetes during 28 years of follow-up. The mean (±SD) genotype score was 17.7±2.7 among subjects in whom diabetes developed and 17.1±2.6 among those in whom diabetes did not develop (P<0.001). The sex-adjusted odds ratio for diabetes was 1.12 per risk allele (95% confidence interval, 1.07 to 1.17). The C statistic was 0.534 without the genotype score and 0.581 with the score (P=>0.01). In a model adjusted for sex and self-reported family history of diabetes, the C statistic was 0.595 without the genotype score and 0.615 with the score (P=0.11). In a model adjusted for age, sex, family history, body-mass index, fasting glucose level, systolic blood pressure, high-density lipoprotein cholesterol level, and triglyceride level, the C statistic was 0.900 without the genotype score and 0.901 with the score (P=0.49). The genotype score resulted in the appropriate risk reclassification of, at most, 4% of the subjects.

Conclusions A genotype score based on 18 risk alleles predicted new cases of diabetes in the community but provided only a slightly better prediction of risk than knowledge of common risk factors alone.

Source Information

From the General Medicine Division (J.B. Meigs, P.S.), the Department of Medicine (J.B. Meigs, P.S., J.C.F.), and the Center for Human Genetic Research and Diabetes Unit, Department of Medicine (J.B. McAteer, J.C.F.), Massachusetts General Hospital, Boston; the Department of Biostatistics, Boston University School of Public Health, Boston (L.M.S., J.D., A.K.M., L.A.C.); the Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA (J.B. McAteer, J.C.F.); the Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women's Hospital, Harvard Medical School, Boston (C.S.F.); the National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA (C.S.F.); the Emory Program in Cardiovascular Outcomes Research and Epidemiology, Emory University School of Medicine, Atlanta (P.W.F.W); and the Mathematics and Statistics Department, Boston University, Boston (R.B.D.).

Address reprint requests to Dr. Meigs at the General Medicine Division, Massachusetts General Hospital, 50 Staniford St., 9th Fl., Boston, MA 02114, or at jmeigs{at}partners.org.

Full Text of this Article

Related Letters:

Clinical Risk Factors, DNA Variants, and the Development of Type 2 Diabetes
Narayan K.M. V., Weber M. B., Gulcher J., Stefansson K., Lyssenko V., Nilsson P., Groop L.
Extract | Full Text | PDF  
N Engl J Med 2009; 360:1360-1361, Mar 26, 2009. Correspondence

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