Vast quantities of human DNA have been sequenced for biomedical research and clinicians, researchers and innovators are now beginning to focus on the next phase of the genomic revolution: translating these data into tools that aim to make a difference in the real world.

New insights into breast cancer risk

What’s more, tests for BRCA mutations are only really prescribed (and reimbursed by medical insurers) for the small subset of the population where prior information, such as a family history of early onset breast or ovarian cancer, points towards these gene variants having a putative role in the disease. (Angelina Jolie, who famously had a mastectomy following a positive test for a BRCA mutation, knew beforehand that her mother had died from ovarian cancer caused by a BRCA mutation.) Many others with BRCA mutations but who don’t have a family history of disease will not have the opportunity to be tested. So, whilst BRCA genes has been transformative for defining risk in families, as a general assay for disease risk, such tests have limited broad-scale utility.

Polygenic architecture

A separate study focused on understanding the polygenic nature of so called estrogen-receptor (ER) negative breast cancer. This is a breast cancer that, unlike the much more common ER positive version, does not respond to hormone therapies. Again, multiple variants, 125 in this case, were found to be associated with breast cancer, underlining the polygenic nature of breast cancer risk.

Towards a greater personalisation of breast cancer risk

The researchers explored different methodologies for generating PRS using different numbers of variants and validated their scores on independent datasets to produce a PRS using 313 independent variants. Whilst this used a larger number of variants than previous attempts for a breast cancer PRS, it didn’t contain the thousands mentioned above because not all of these previously identified variants provided predictive power. The researchers found that individuals with the highest 1% of scores had a four times greater lifetime risk of developing breast cancer than those in the middle of the PRS distribution, equating to an absolute lifetime risk for these individuals of about one in three.

Combining monogenic and polygenic risk

For breast cancer, using polygenic information provides further discrimination of risk for BRCA mutation carriers. Those carriers with the highest polygenic risk had an almost 80% risk of getting breast cancer by age 75, compared to around 30% risk for those with the highest polygenic scores who weren’t also carrying a BRCA mutation. This has real world impact. Knowing that your have a four out of five lifetime chance of getting breast cancer may lead you to have annual mammograms, or even choose — like Angelina Jolie — to have an elective mastectomy.

Don’t forget the environment

At Allelica we are building risk prediction models incorporating information on non-genetic factors. Our PRS for breast cancer implements an improved algorithm that outperforms the predictive power of the PRS outlined above. Users can request a demo here of the software we used to build and compute the new breast cancer PRS.

Originally published at on January 29, 2020.

Allelica is a Software Genomics Company developing algorithms and digital tools to accelerate the integration of Polygenic Risk Score in the clinical practice