Life insurance: genomic stratification and risk classification

Y. Joly*, H. Burton, B.M. Knoppers, I. Ngueng Feze, T. Dent, N. Pashayan, S. Chowdhury, W. Foulkes, A. Hall, P. Hamet, N. Kirwan, A. Macdonald, J. Simard, I. van Hoyweghen

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

With the development and increasing accessibility of new genomic tools such as next-generation sequencing, genome-wide association studies, and genomic stratification models, the debate on genetic discrimination in the context of life insurance became even more complex, requiring a review of current practices and the exploration of new scenarios. In this perspective, a multidisciplinary group of international experts representing different interests revisited the genetics and life insurance debate during a 2-day symposium 'Life insurance: breast cancer research and genetic risk prediction seminar' held in Quebec City, Canada on 24 and 25 September 2012. Having reviewed the current legal, social, and ethical issues on the use of genomic information in the context of life insurance, the Expert Group identified four main questions: (1) Have recent developments in genomics and related sciences changed the contours of the genetics and life insurance debate? (2) Are genomic results obtained in a research context relevant for life insurance underwriting? (3) Should predictive risk assessment and risk stratification models based on genomic data also be used for life insurance underwriting? (4) What positive actions could stakeholders in the debate take to alleviate concerns over the use of genomic information by life insurance underwriters? This paper presents a summary of the discussions and the specific action items recommended by the Expert Group. published online 16 October 2013

Original languageEnglish
Pages (from-to)575-579
Number of pages5
JournalEuropean Journal of Human Genetics
Volume22
Issue number5
Early online date16 Oct 2013
DOIs
Publication statusPublished - May 2014

Keywords

  • GENETIC DISCRIMINATION
  • BREAST-CANCER
  • SUSCEPTIBILITY
  • INFORMATION
  • PREVENTION
  • PREDICTION
  • SOLIDARITY
  • DISEASE
  • MODELS
  • IMPACT

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