Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction

In a new study, researchers from the International Agency for Research on Cancer (IARC) and the University of California, San Francisco, USA, evaluated the extent to which genetic information, in the form of polygenic risk scores, can be used to more accurately identify individuals at high risk of developing cancer. Polygenic risk scores are calculated by combining the levels of risk of known genetic risk factors into a single, integrated measure of an individual’s genetic predisposition.

The research, published in Nature Communications, is the first comprehensive study demonstrating the potential of using polygenic risk scores together with information on modifiable risk factors to predict the risk of developing 16 individual cancer types.

The main finding was that incorporating polygenic risk scores can improve the accuracy of cancer risk prediction compared with predictions based on information on modifiable and demographic risk factors. The study also demonstrated that individual changes in modifiable risk factors, such as smoking or body mass index, can meaningfully reduce the risk of most cancer types regardless of genetic predisposition.

The authors created an animation describing the main findings and the implications of their work.

Kachuri L, Graff RE, Smith-Byrne K, Meyers TJ, Rashkin SR, Ziv E, et al.
Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction
Nat Commun, Published online 27 November 2020;
https://doi.org/10.1038/s41467-020-19600-4

Read the article

Watch the animation