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

摘要

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??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?×?10?6 vs null model), but lower discriminative power than model 1 (p?=?5.92?×?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?×?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?×?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??20) and model 1 (p?=?1.32?×?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.