Incorporating polygenic risk into the Leicester Risk Assessment score for 10-year risk prediction of type 2 diabetes.

We evaluated whether incorporating information on ethnic background and polygenic risk enhanced the Leicester Risk Assessment (LRA) score for predicting 10-year risk of type 2 diabetes. The sample included 202,529 UK Biobank participants aged 40–69 years. We computed the LRA score , and developed two new risk scores using training data (80% sample): LRArev , which incorporated additional information on ethnic background, and LRAprs , which incorporated polygenic risk for type 2 diabetes. We assessed discriminative and reclassification performance in a test set (20% sample). Type 2 diabetes was ascertained using primary care, hospital inpatient and death registry records. Over 10 years, 7,476 participants developed type 2 diabetes. The Harrell's C indexes were 0.796 (95% Confidence Interval [CI] 0.785, 0.806), 0.802 (95% CI 0.792, 0.813), and 0.829 (95% CI 0.820, 0.839) for the LRA , LRArev and LRAprs scores, respectively. The LRAprs score significantly improved the overall reclassification compared to the LRA (net reclassification index [NRI] = 0.033, 95% CI 0.015, 0.049) and LRArev (NRI = 0.040, 95% CI 0.024, 0.055) scores. Polygenic risk moderately improved the performance of the existing LRA score for 10-year risk prediction of type 2 diabetes. • The original LRA score performed well at predicting risk of type 2 diabetes. • Incorporation of polygenic risk resulted in a moderate improvement of type 2 diabetes risk prediction. • The LRA score with polygenic risk performed better at correctly classifying future cases. • Conversely, the LRA score with polygenic risk classified a higher proportion of non-cases during follow-up as high-risk. [ABSTRACT FROM AUTHOR]