Predicting risk of cancer, heart attacks and other diseases using DNA
The human genome (the complete set of genetic information in an individual) has transformed health research, allowing us to uncover the changes in our genetic make-up that make us susceptible or resistant to common diseases.
We can now create scores, called polygenic scores, which quantify risks for more than 100 common diseases. Polygenic scores are driving a new generation of disease risk models which can guide earlier screening, preventative treatment and diagnostics.
Cambridge BRC investigators have been at the forefront of these efforts, particularly for breast/ovarian cancer1 and cardiovascular disease2. Developed together with clinicians and patients, CanRisk is a powerful web-based prediction tool which identifies women at especially high risk of breast and ovarian cancer, and guides preventive actions. Endorsed by NICE in the UK, American Cancer Society and other major bodies, it is used thousands of times daily in more than 90 countries, supporting women, clinicians and genetic counsellors.
CanRisk supports hundreds of thousands of women each year in making decisions about risk reducing medications and surgery (e.g. mastectomy). CanRisk contributes to lower numbers of women diagnosed with cancer, fewer deaths, improved quality of life and reduced costs. A major recent advance of CanRisk has been incorporation of polygenic scores. CanRisk has gained regulatory approval for use as a medical device in the UK and EEA.
Researchers have designed and deployed the world’s main publicly-available resource for polygenic scores, the Polygenic Score Catalog3.
Each polygenic score in the Catalog is annotated with relevant information, including how the score was developed and applied, evaluation of how well they identify people at high risk, and how equitable they are. The team have developed a reporting framework needed for researchers and clinicians to interpret and evaluate polygenic risk scores around the world, and thus promote best practice and translation into clinical care4.
The team are now implementing a prototype patient management system for primary care which uses all our knowledge and tools for polygenic risk scores for early disease detection on 24 million UK individuals.
This will be developed into a fully implemented system usable by clinicians to help make more personalised clinical decisions; bringing the benefits of our research to many underserved and disadvantaged communities.
1 Genetics in Medicine 2019 PMID:30643217
2 PLOS Medicine 2021 PMID:334443
3 Nat Genet 2021 PMID:33692568
4 Nature 2021 PMID:33692554