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.
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.