title: Assessing the combined impact of 18 common genetic variants of modest effect sizes on type 2 diabetes risk.
abstract: OBJECTIVE
  Genome-wide association studies have dramatically increased the number of common genetic variants that are robustly associated with type 2 diabetes. A possible clinical use of this information is to identify individuals at high risk of developing the disease, so that preventative measures may be more effectively targeted. Here, we assess the ability of 18 confirmed type 2 diabetes variants to differentiate between type 2 diabetic case and control subjects.
  
  
  METHODS
  We assessed index single nucleotide polymorphisms (SNPs) for the 18 independent loci in 2,598 control subjects and 2,309 case subjects from the Genetics of Diabetes Audit and Research Tayside Study. The discriminatory ability of the combined SNP information was assessed by grouping individuals based on number of risk alleles carried and determining relative odds of type 2 diabetes and by calculating the area under the receiver-operator characteristic curve (AUC).
  
  
  RESULTS
  Individuals carrying more risk alleles had a higher risk of type 2 diabetes. For example, 1.2% of individuals with >24 risk alleles had an odds ratio of 4.2 (95% CI 2.11-8.56) against the 1.8% with 10-12 risk alleles. The AUC (a measure of discriminative accuracy) for these variants was 0.60. The AUC for age, BMI, and sex was 0.78, and adding the genetic risk variants only marginally increased this to 0.80.
  
  
  CONCLUSIONS
  Currently, common risk variants for type 2 diabetes do not provide strong predictive value at a population level. However, the joint effect of risk variants identified subgroups of the population at substantially different risk of disease. Further studies are needed to assess whether individuals with extreme numbers of risk alleles may benefit from genetic testing.
authors.affiliation: Genetics of Complex Traits, Institute of Biomedical and Clinical Science, Peninsula Medical School, Exeter, UK.
authors.forename: Hana
authors.initials: H
authors.lastname: Lango
authors.forename: Colin N A
authors.initials: CN
authors.lastname: Palmer
authors.forename: Andrew D
authors.initials: AD
authors.lastname: Morris
authors.forename: Eleftheria
authors.initials: E
authors.lastname: Zeggini
authors.forename: Andrew T
authors.initials: AT
authors.lastname: Hattersley
authors.forename: Mark I
authors.initials: MI
authors.lastname: McCarthy
authors.forename: Timothy M
authors.initials: TM
authors.lastname: Frayling
authors.forename: Michael N
authors.initials: MN
authors.lastname: Weedon
mesh_terms: D000367:Age Factors; D000368:Aged; D015992:Body Mass Index; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics* / Q000473:pathology / Q000517:prevention & control; D005260:Female; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005838:Genotype; D006801:Humans; D008297:Male; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide; D012372:ROC Curve