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The Predictive Utility of Polygenic Risk Scores

Research collaboration between RGA and King’s College London shows potential of genetic predisposition in predicting common diseases
Polygenetic long

A research study produced by RGA and King’s College London, titled “Multifactorial disorders and polygenic risk scores: predicting common diseases and the possibility of adverse selection in life and protection insurance” has been published in the November 2021 issue of the Annals of Actuarial Science.

 
The research collaboration explored data from the UK Biobank, a remarkable database offering the opportunity to research mortality and morbidity outcomes using genetic and environmental risk factors for 500,000 individuals across the U.K. Results of the study suggest that genetic predisposition significantly contributes to risk prediction for multifactorial diseases such as breast cancer and coronary artery disease above and beyond typical underwriting risk factors. The study also investigates the potential for adverse selection that could result from consumers armed with genetic information about multifactorial disorders not available to insurers.

The paper’s abstract is re-printed here with permission. To read the full study, visit the Annals of Actuarial Science.

Abstract

During the past decade, genetics research has allowed scientists and clinicians to explore the human genome in detail and reveal many thousands of common genetic variants associated with disease. Genetic risk scores, known as polygenic risk scores (PRSs), aggregate risk information from the most important genetic variants into a single score that describes an individual’s genetic predisposition to a given disease. This article reviews recent developments in the predictive utility of PRSs in relation to a person’s susceptibility to breast cancer and coronary artery disease. Prognostic models for these disorders are built using data from the UK Biobank, controlling for typical clinical and underwriting risk factors. Furthermore, we explore the possibility of adverse selection where genetic information about multifactorial disorders is available for insurance purchasers but not for underwriters. We demonstrate that prediction of multifactorial diseases, using PRSs, provides population risk information additional to that captured by normal underwriting risk factors. This research using the UK Biobank is in the public interest as it contributes to our understanding of predicting risk of disease in the population. Further research is imperative to understand how PRSs could cause adverse selection if consumers use this information to alter their insurance purchasing behavior. 

Committed to staying abreast of the latest research and new developments, RGA’s Global Data and Analytics associates are actively investigating the potential impact of genetics on insurance and other future-focused issues. Contact us for more information. 
 

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The Authors

  • Richard Russell
    Lead Health Data Scientist
    Global Data and Analytics
    RGA
  • Peter Banthorpe
    Managing Director
    RGA UK
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  • Cathryn Lewis
    Professor of Genetic
    Epidemiology and Statistics
    Statistical Genetics Unit

    King's College London
  • Jessye Maxwell

    PhD Research Student
    Social, Genetic & Developmental Psychiatry Centre
    King’s College London

  • Paul O’Reilly
    Associate Professor in Statistical Genetics
    Department of Genetics and Genomic Sciences

    Icahn School of Medicine at Mount Sinai NYC
  • Natasha Sharapova
    PhD Research Student
    Department of Medical & Molecular Genetics

    King’s College London
  • Hei Man Wu
    Postdoctoral Research Fellow
    Department of Genetics and Genomic Sciences

    Icahn School of Medicine at Mount Sinai NYC

Summary

A research study produced by RGA and King’s College London suggests that genetic predisposition significantly contributes to risk prediction for multifactorial diseases such as breast cancer and coronary artery disease above and beyond typical underwriting risk factors. The study also investigates the potential for adverse selection that could result from consumers armed with genetic information about multifactorial disorders not available to insurers.
  • actuarial
  • actuarial science
  • adverse selection
  • annals of actuarial science
  • anti-selection
  • breast cancer
  • Cardiovascular disease
  • cardiovascular risk
  • Cathryn Lewis
  • genetic evidence
  • genetic information
  • genetic predisposition
  • genetic risk prediction
  • genetic risk score life insurance
  • genetics
  • Hei Man Wu
  • human genome
  • Jessye Maxwell
  • multifactorial
  • multifactorial diseases
  • Natasha Sharapova
  • Paul O’Reilly
  • Peter Banthorpe
  • polygenetic risk scores
  • polygenetic score
  • polygenetic score insurance
  • PRS
  • Richard Russell
  • Risk prediction
  • UK Biobank
  • Underwriting
  • underwriting evidence