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Multifactorial disorders and polygenic risk scores: predicting common diseases and the possibility of adverse selection in life and protection insurance
Annals of Actuarial Science Pub Date : 2020-08-14 , DOI: 10.1017/s1748499520000226
Jessye M. Maxwell , Richard A. Russell , Hei Man Wu , Natasha Sharapova , Peter Banthorpe , Paul F O’Reilly , Cathryn M Lewis

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 behaviour.

中文翻译:

多因素疾病和多基因风险评分:预测常见疾病和人寿和保障保险中逆向选择的可能性

在过去的十年中,遗传学研究使科学家和临床医生能够详细探索人类基因组,并揭示与疾病相关的数千种常见遗传变异。遗传风险评分,称为多基因风险评分 (PRS),将来自最重要的遗传变异的风险信息汇总为一个评分,该评分描述了个体对特定疾病的遗传易感性。本文回顾了 PRS 与人对乳腺癌和冠状动脉疾病易感性相关的预测效用的最新进展。这些疾病的预后模型是使用来自英国生物银行的数据建立的,控制了典型的临床和承保风险因素。此外,我们探讨了逆向选择的可能性,其中关于多因素疾病的遗传信息可供保险购买者获得,但不提供给承保人。我们证明,使用 PRS 预测多因素疾病可以提供除正常承保风险因素捕获的信息之外的人口风险信息。这项使用英国生物银行的研究符合公众利益,因为它有助于我们了解预测人群中的疾病风险。如果消费者使用这些信息来改变他们的保险购买行为,进一步的研究是必要的,以了解 PRS 如何导致逆向选择。提供除由正常承保风险因素捕获的信息之外的人口风险信息。这项使用英国生物银行的研究符合公众利益,因为它有助于我们了解预测人群中的疾病风险。如果消费者使用这些信息来改变他们的保险购买行为,进一步的研究是必要的,以了解 PRS 如何导致逆向选择。提供除由正常承保风险因素捕获的信息之外的人口风险信息。这项使用英国生物银行的研究符合公众利益,因为它有助于我们了解预测人群中的疾病风险。如果消费者使用这些信息来改变他们的保险购买行为,进一步的研究是必要的,以了解 PRS 如何导致逆向选择。
更新日期:2020-08-14
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