Clinical Polygenic Risk Scores

The Potential of Genomics in the Clinic

That genomics has incredible potential to help diagnose and treat disease is not a matter for debate any longer. As exemplified by NHS England Chief Medical Officer Dame Sally Davies in her ‘generation genome’ report [[1]], genomics has the potential to transform the clinic in a number of ways, ranging from diagnosis and treatment of rare diseases and cancer, to development of new targeted drugs and therapies, as well as planning for future health. While efforts to apply genomics to sick people in the clinic have been established in some advanced economies (with Britain leading the way), their application to prevention of disease is still in its infancy. In its infancy because the genetic causes of leading ‘old age’ diseases in the developed world are extremely complex to identify. Many of these complex diseases develop as a consequence of thousands (if not millions) of tiny contributions (i.e., genetic markers) spread throughout the genome. Therefore, the sample sizes required to identify such tiny contributions require big enough sample sizes for statistical power and controlled population stratification, unachievable until recently. It is only now that big enough genetic data samples have become available, in part due to the decreasing costs associated with the sequencing of a genome. The UK has again paved the way with sampling of substantial population-size cohorts such as the UK Biobank [[2]], which has allowed the analysis and validation of uncommon genetic markers that contribute tiny amounts to complex diseases. 

Based on the UK Biobank, there have been a number of validated polygenic risk scores such as atrial fibrillation, breast cancer or diabetes type 2 [[3]]. What this means in practice is that we are now in a position to apply informative genetic scores in pre-symptomatic individuals, and for some diseases, we can use them independent of a family history of the condition [[4]]. It is thus a matter of time that these tools will be incorporated as a standard practice for preventative clinical care.

A clinical intervention based on genetic risk scores could provide significant advantages before symptoms arise. For some diseases, such as breast cancer, the provision of a mammography before the normally indicated age might be an appropriate clinical intervention to consider. For other diseases, such as those with currently no treatment (e.g., some neurodegenerative diseases), genetic risk scores might provide an incentive to prepare early. In any case, such genetic tests should be integrated with the appropriate standard of care and not as independent health diagnoses. It is thus fundamental that expert interpretation of genetic results is contextualised with the many other factors affecting health management. 

The preventative use of genetic information may indeed be an additional piece of the puzzle for health management, but how we communicate and act upon such information is not to be taken lightly. First and foremost, genetics is only part of the health picture: most diseases are a combination of genetics and the environment, with family clinical histories playing a determinant role. Non-experts are thus ill-equipped to deal with the information that may originate as a consequence of a genetic test, with implications that go beyond the individual (e.g., family relatives). 

We are all related to each other and yet the small genetic differences that we harbour may condition us in different ways. It is indeed a very personal journey that inextricably unites us to our biology, our ancestors, our species and the planet. By no means we are close to leverage the power of the genome in our lives, yet tremendous advances in genetics have transformed the medicine of the XXI century. How we handle, relate and consider its implications will have tremendous impact on how we live our lives.


[1] https://www.gov.uk/government/publications/chief-medical-officer-annual-report-2016-generation-genome

[2] https://www.nature.com/articles/s41586-018-0579-z

[3] https://www.nature.com/articles/s41588-018-0183-z

[4] https://www.medrxiv.org/content/10.1101/2020.05.20.20108217v1

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