Public attitudes toward genetic risk scoring in medicine and beyond. (April 2021) - Zhang, Simone; Johnson, Rebecca A.; Novembre, John; Freeland, Edward; Conley, Dalton
Abstract: Advances in genomics research have led to the development of polygenic risk scores, which numerically summarize genetic predispositions for a wide array of human outcomes. Initially developed to characterize disease risk, polygenic risk scores can now be calculated for many non-disease traits and social outcomes, with the potential to be used not only in health care but also other institutional domains. In this study, we draw on a nationally-representative survey of U.S. adults to examine three sets of lay attitudes toward the deployment of genetic risk scores in a variety of medical and non-medical domains: 1. abstract belief about whether people should be judged on the basis of genetic predispositions; 2. concrete attitudes about whether various institutions should be permitted to use genetic information; and 3. personal willingness to provide genetic information to various institutions. Results demonstrate two striking differences across these three sets of attitudes. First, despite almost universal agreement that people should not be judged based on genetics, there is support, albeit varied, for institutions being permitted to use genetic information, with support highest for disease outcomes and in reproductive decision-making. We further find significant variation in personal willingness to provide such information, with a majority of respondents expressing willingness to provide information to health care providers and relative finder services, but less than a quarter expressing willingness to do so for an array of other institutions and services. Second, while there are no demographic differences in respondents' abstract beliefs about judging based on genetics, demographic differences emerge in permissibility ratings and personal willingness. Our results should inform debates about the deployment of polygenic scores in domains within and beyond medicine. Highlights: Polygenic risk scores can now be calculated for many non-disease traits and social outcomes. Genetic prediction is now possible in a range of domains from schools to fertility clinics. Strong majorities think genetic prediction is permissible in select domains. Support is strongest for disease outcomes and weakest for physical traits like skin tone. Willingness to personally provide samples varies across institutions and services.