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

Xiaonan Liu; Thomas J Littlejohns; Jelena Bešević; Fiona Bragg; Lei Clifton; Jennifer A Collister; Eirini Trichia; Laura J Gray; Kamlesh Khunti; David J Hunter

doi:10.1016/j.dsx.2024.102996

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

Diabetes Metab Syndr. 2024 Mar 29;18(4):102996. doi: 10.1016/j.dsx.2024.102996. Online ahead of print.

Authors

Affiliations

¹ Nuffield Department of Population Health, University of Oxford, Oxford, UK.
² Nuffield Department of Population Health, University of Oxford, Oxford, UK. Electronic address: thomas.littlejohns@ndph.ox.ac.uk.
³ Nuffield Department of Population Health, University of Oxford, Oxford, UK; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
⁴ Department of Population Health Sciences, University of Leicester, UK.
⁵ Diabetes Research Centre, University of Leicester, Leicester, UK.
⁶ Nuffield Department of Population Health, University of Oxford, Oxford, UK; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, USA.

PMID: 38608567
DOI: 10.1016/j.dsx.2024.102996

Abstract

Aims: 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.

Methods: 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.

Results: 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.

Conclusions: Polygenic risk moderately improved the performance of the existing LRA score for 10-year risk prediction of type 2 diabetes.

Keywords: Leicester Risk Assessment; Polygenic risk score; Risk prediction; Type 2 diabetes; UK Biobank.