A multigenic model to predict risk of ischemic stroke in subjects with type 2 diabetes

Abstract

We have previously demonstrated that genetic profiles determined by the combination of five functionally significant single nucleotide polymorphisms (SNPs) of genes encoding prototypical inflammatory molecules (rs1800795, rs5498, rs5361, rs1024611, rs679620) are associated with history of ischemic stroke. In this study, we tested the ability of this multigenic model to predict stroke risk in a large population-based prospective cohort of subjects with type 2 diabetes (T2D), participating to the Go-DARTS Study. This prospective study includes genetic and clinical information of patients with diabetes within the Tayside region of Scotland, UK. The above mentioned inflammatory SNPs were investigated in 2,182 Go-DARTS participants. We created an Inflammatory Risk Score (IRS), ranging from 0 to 5, according to the number of "at risk"genotypes concomitantly carried by a given individual. The primary outcome was the occurrence of fatal or non fatal stroke of any kind. Mean follow-up was 6.2+/-1.1 years. We found that the incidence of stroke increased accordingly to the IRS. The IRS was significantly and independently associated with increased stroke risk after adjustment for conventional risk factors (HR 1.34, 95% CI 1.1-1.7, P = 0.009). The highest hazard ratio for stroke was found in subjects concomitantly carrying >3 pro-inflammatory variations and in subjects without previous cardiovascular diseases. In conclusion, this large prospective cohort study provides evidence that SNPs of genes encoding prototypical inflammatory molecules may be used to create multigenic models that predict stroke risk in subjects with T2D.