Literature DB >> 33443076

Calibration of polygenic risk scores is required prior to clinical implementation: results of three common cancers in UKB.

Jun Wei1, Zhuqing Shi1, Rong Na1, W Kyle Resurreccion1, Chi-Hsiung Wang1, David Duggan2, S Lilly Zheng1, Peter J Hulick3, Brian T Helfand1, Jianfeng Xu4.   

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. © Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  clinical decision-making; genetic predisposition to disease; genetic testing; genetics; medical oncology

Mesh:

Year:  2020        PMID: 33443076     DOI: 10.1136/jmedgenet-2020-107286

Source DB:  PubMed          Journal:  J Med Genet        ISSN: 0022-2593            Impact factor:   6.318


  2 in total

Review 1.  Inherited risk assessment and its clinical utility for predicting prostate cancer from diagnostic prostate biopsies.

Authors:  Jianfeng Xu; W Kyle Resurreccion; Zhuqing Shi; Jun Wei; Chi-Hsiung Wang; S Lilly Zheng; Peter J Hulick; Ashley E Ross; Christian P Pavlovich; Brian T Helfand; William B Isaacs
Journal:  Prostate Cancer Prostatic Dis       Date:  2022-03-28       Impact factor: 5.455

2.  Canalization of the Polygenic Risk for Common Diseases and Traits in the UK Biobank Cohort.

Authors:  Sini Nagpal; Raghav Tandon; Greg Gibson
Journal:  Mol Biol Evol       Date:  2022-04-11       Impact factor: 16.240

  2 in total

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