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

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posted on 2024-04-09, 12:26 authored by Xiaonan Liu, Thomas J Littlejohns, Jelena Bešević, Fiona Bragg, Lei Clifton, Jennifer A Collister, Eirini Trichia, Laura J Gray, Kamlesh Khunti, David J Hunter

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, 7476 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.

Funding

Cancer Research UK (grant no C16077/A29186)

National Institute for Health and Care Research (NIHR) Applied Research Collaboration East Midlands (ARC EM) and Leicester NIHR Biomedical Research Centre (BRC)

Nuffield Department of Population Health, Oxford University

History

Author affiliation

College of Life Sciences/Population Health Sciences

Version

  • AM (Accepted Manuscript)

Published in

Diabetes & Metabolic Syndrome: Clinical Research & Reviews

Pagination

102996 - 102996

Publisher

Elsevier BV

issn

1871-4021

Copyright date

2024

Available date

2024-04-09

Language

en

Deposited by

Professor Laura Gray

Deposit date

2024-04-05

Data Access Statement

This research has been conducted using the UK Biobank Resource under Application Number 33952. The data reported in this paper are available via application directly to the UK Biobank, https://www.ukbiobank.ac.uk. All code used to set up and run the statistical analyses are available at https://github.com/xiaonanl1996/LRArevprs.

Rights Retention Statement

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