title: Genotype score in addition to common risk factors for prediction of type 2 diabetes.
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.
authors.affiliation: General Medicine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA. jmeigs@partners.org
authors.forename: James B
authors.initials: JB
authors.lastname: Meigs
authors.forename: Peter
authors.initials: P
authors.lastname: Shrader
authors.forename: Lisa M
authors.initials: LM
authors.lastname: Sullivan
authors.forename: Jarred B
authors.initials: JB
authors.lastname: McAteer
authors.forename: Caroline S
authors.initials: CS
authors.lastname: Fox
authors.forename: Josée
authors.initials: J
authors.lastname: Dupuis
authors.forename: Alisa K
authors.initials: AK
authors.lastname: Manning
authors.forename: Jose C
authors.initials: JC
authors.lastname: Florez
authors.forename: Peter W F
authors.initials: PW
authors.lastname: Wilson
authors.forename: Ralph B
authors.initials: RB
authors.lastname: D'Agostino
authors.forename: L Adrienne
authors.initials: LA
authors.lastname: Cupples
mesh_terms: D000328:Adult; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics*; D005260:Female; D005500:Follow-Up Studies; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease; D005838:Genotype; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D012307:Risk Factors