Literature DB >> 19020323

Genotype score in addition to common risk factors for prediction of type 2 diabetes.

James B Meigs1, Peter Shrader, Lisa M Sullivan, Jarred B McAteer, Caroline S Fox, Josée Dupuis, Alisa K Manning, Jose C Florez, Peter W F Wilson, Ralph B D'Agostino, L Adrienne Cupples.   

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. 2008 Massachusetts Medical Society

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Year:  2008        PMID: 19020323      PMCID: PMC2746946          DOI: 10.1056/NEJMoa0804742

Source DB:  PubMed          Journal:  N Engl J Med        ISSN: 0028-4793            Impact factor:   91.245


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