title: Evaluating the discriminative power of multi-trait genetic risk scores for type 2 diabetes in a northern Swedish population.
abstract: OBJECTIVE
  We determined whether single nucleotide polymorphisms (SNPs) previously associated with diabetogenic traits improve the discriminative power of a type 2 diabetes genetic risk score.
  
  
  METHODS
  Participants (n = 2,751) were genotyped for 73 SNPs previously associated with type 2 diabetes, fasting glucose/insulin concentrations, obesity or lipid levels, from which five genetic risk scores (one for each of the four traits and one combining all SNPs) were computed. Type 2 diabetes patients and non-diabetic controls (n = 1,327/1,424) were identified using medical records in addition to an independent oral glucose tolerance test.
  
  
  RESULTS
  Model 1, including only SNPs associated with type 2 diabetes, had a discriminative power of 0.591 (p < 1.00 x 10(-20) vs null model) as estimated by the area under the receiver operator characteristic curve (ROC AUC). Model 2, including only fasting glucose/insulin SNPs, had a significantly higher discriminative power than the null model (ROC AUC 0.543; p = 9.38 x 10(-6) vs null model), but lower discriminative power than model 1 (p = 5.92 x 10(-5)). Model 3, with only lipid-associated SNPs, had significantly higher discriminative power than the null model (ROC AUC 0.565; p = 1.44 x 10(-9)) and was not statistically different from model 1 (p = 0.083). The ROC AUC of model 4, which included only obesity SNPs, was 0.557 (p = 2.30 x 10(-7) vs null model) and smaller than model 1 (p = 0.025). Finally, the model including all SNPs yielded a significant improvement in discriminative power compared with the null model (p < 1.0 x 10(-20)) and model 1 (p = 1.32 x 10(-5)); its ROC AUC was 0.626.
  
  
  CONCLUSIONS
  Adding SNPs previously associated with fasting glucose, insulin, lipids or obesity to a genetic risk score for type 2 diabetes significantly increases the power to discriminate between people with and without clinically manifest type 2 diabetes compared with a model including only conventional type 2 diabetes loci.
authors.affiliation: Department of Nutrition Sciences, University of Ottawa, Ottawa, ON, Canada.
authors.forename: B
authors.initials: B
authors.lastname: Fontaine-Bisson
authors.forename: F
authors.initials: F
authors.lastname: Renström
authors.forename: O
authors.initials: O
authors.lastname: Rolandsson
authors.forename: F
authors.initials: F
authors.lastname: Payne
authors.forename: G
authors.initials: G
authors.lastname: Hallmans
authors.forename: I
authors.initials: I
authors.lastname: Barroso
authors.forename: P W
authors.initials: PW
authors.lastname: Franks
mesh_terms: D019540:Area Under Curve; D001786:Blood Glucose; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics*; D005260:Female; D020022:Genetic Predisposition to Disease; D005838:Genotype; D005951:Glucose Tolerance Test; D006801:Humans; D007328:Insulin / Q000235:genetics; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D016017:Odds Ratio; D020641:Polymorphism, Single Nucleotide; D011237:Predictive Value of Tests; D012372:ROC Curve; D012307:Risk Factors; D013548:Sweden; D044465:White People / Q000235:genetics*
chemical_list: D001786:Blood Glucose; D007328:Insulin