Calibration of polygenic risk scores is required prior to clinical implementation: results of three common cancers in UKB. Issue 3 (21st December 2020)

• Record Type: Journal Article
• Authors: Wei, Jun; Shi, Zhuqing; Na, Rong; Resurreccion, W Kyle; Wang, Chi-Hsiung; Duggan, David; Zheng, S Lilly; Hulick, Peter J; Helfand, Brian T; Xu, Jianfeng
• Is Part Of: Journal of medical genetics. Volume 59:Issue 3(2022)
• Page Start: 243
• Page End: 247
• Publication Date: 2020-12-21
• Subjects: genetic predisposition to disease -- genetics -- genetic testing -- medical oncology -- clinical decision-making; Medical genetics -- Periodicals; 616.042
• DOI: 10.1136/jmedgenet-2020-107286
• Languages: English
• ISSNs: 1468-6244

Abstract

Abstract : Background: SNP-based polygenic risk scores have recently been adopted in the clinic for risk assessment of some common diseases. Their validity is supported by a consistent trend between their percentile rank and disease risk in populations. However, for clinical use at the individual level, the reliability of score values is necessary considering they are directly used to calculate remaining lifetime risk. Objectives: We assessed the reliability of polygenic score values to estimate prostate cancer (PCa), breast cancer (BCa) and colorectal cancer (CRC) risk in three incident cohorts from the UK Biobank (n>500 000). Methods: Cancer-specific Genetic Risk Score (GRS), a well-established population-standardised polygenic risk score, was calculated. Results: A systematic bias was found between estimated risks (GRS values) and observed risks; β (95% CI) was 0.67 (0.58–0.76), 0.74 (0.65–0.84) and 0.82 (0.75–0.89), respectively, for PCa, BCa and CRC, all significantly lower than 1.00 (perfect calibration), p<0.001. After applying a correction factor derived from a training data set, the β for corrected GRS values in an independent testing data set were 1.09 (1.05–1.13), 1.00 (0.88–1.12) and 1.08 (0.96–1.21), respectively, for PCa, BCa and CRC. Conclusion: Assessing the calibration of polygenic risk scores is necessary and feasible to ensure their reliability prior to clinical implementation.