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Review
September 30, 2020

From Basic Science to Clinical Application of Polygenic Risk Scores: A Primer

Author Affiliations
  • 1Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
  • 2Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
  • 3Departments of Psychiatry and Medical Genetics, The University of British Columbia, Vancouver, British Columbia, Canada
  • 4BC Mental Health and Substance Use Services Research Institute, Vancouver, British Columbia, Canada
  • 5Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Wacol, Queensland, Australia
  • 6National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
  • 7Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
  • 8Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, England
  • 9Department of Psychiatry, University of Cambridge, Cambridge, England
JAMA Psychiatry. 2021;78(1):101-109. doi:10.1001/jamapsychiatry.2020.3049
Abstract

Importance  Polygenic risk scores (PRS) are predictors of the genetic susceptibilities of individuals to diseases. All individuals have DNA risk variants for all common diseases, but genetic susceptibility differences between people reflect the cumulative burden of these. Polygenic risk scores for an individual are calculated as weighted counts of thousands of risk variants that they carry, where the risk variants and their weights have been identified in genome-wide association studies. Here, we review the underlying basic science of PRS, providing a foundation for understanding the potential clinical utility and limitations of PRS.

Observations  Polygenic risk scores can be calculated for a wide range of diseases from a saliva or blood sample using genotyping technologies that are inexpensive. While genotyping only needs to be done once for each individual in their lifetime, the PRS can be recalculated as identification of risk variants improves. On their own, PRS will never be able to establish or definitively predict future diagnoses of common complex conditions because genetic factors only contribute part of the risk, and PRS will only ever capture part of the genetic contributions. Nonetheless, just as clinical medicine uses a multitude of other predictive measures, PRS either on their own or as part of multivariable predictive algorithms could play a role.

Conclusions and Relevance  Utility of PRS in clinical medicine and ethical issues related to their use should be evaluated in the context of realistic expectations of what PRS can and cannot deliver. For different diseases, PRS could have utility in community settings (stratification to better triage people into established screening programs) or could contribute to clinical decision-making for those presenting with symptoms but where formal diagnosis is unclear. In principle, PRS could contribute to treatment choices, but more data are needed to allow development of PRS in this context.

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