Evaluating the discriminative power of multi-trait genetic risk scores for type 2 diabetes in a northern Swedish population

Diabetologia. 2010 Oct;53(10):2155-62. doi: 10.1007/s00125-010-1792-y. Epub 2010 Jun 23.

Abstract

Aims/hypothesis: 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/interpretation: 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Area Under Curve
  • Blood Glucose
  • Diabetes Mellitus, Type 2 / genetics*
  • Female
  • Genetic Predisposition to Disease*
  • Genotype
  • Glucose Tolerance Test
  • Humans
  • Insulin / genetics
  • Male
  • Middle Aged
  • Models, Biological
  • Odds Ratio
  • Polymorphism, Single Nucleotide
  • Predictive Value of Tests*
  • ROC Curve
  • Risk Factors
  • Sweden
  • White People / genetics*

Substances

  • Blood Glucose
  • Insulin