Combining Information from Common Type 2 Diabetes Risk Polymorphisms Improves Disease Prediction

Abstract

Combining information from several known common risk polymorphisms allows the identification of population subgroups with markedly differing risks of developing type 2 diabetes compared to those obtained using single polymorphisms. This approach may have a role in future preventative measures for common, polygenic diseases.