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Approved Research

Targeting Interventions using Genetic Analysis for Breast Cancer prevention(TAIGA-BC): identifying genetic variants whose effects are reduced by intervening on health behaviours

Principal Investigator: Dr Jeremy Labrecque
Approved Research ID: 73728
Approval date: July 27th 2022

Lay summary

For some women, their genes place them at a higher risk of breast cancer. Genetic testing for breast cancer risk is now common place among women with a family history of breast cancer. By knowing her genetic risk of breast cancer, a woman can make important choices regarding how to prevent breast cancer or how to detect it early. Having information specific to women at high genetic risk helps these women make these difficult decisions. For example, it is known that mammography and ultrasound are not as good at detecting breast cancer in women with high-risk versions of the BRCA1 and/or BRCA2 genes when compared to women who do not have these high-risk versions. Therefore, women who have these high-risk versions are advised to be screened for breast cancer using MRI additionally. Breast cancer risk can also be reduced through changes in health behaviours such as quitting smoking, drinking less alcohol or losing weight but there is no evidence tailored toward women who are at a high genetic risk of breast cancer to help them make these decisions. This project aims to produce exactly this type of information. For example, this project will look at whether quitting smoking might have a bigger impact on reducing breast cancer among women at high genetic risk of breast cancer than women at lower risk. This information, in combination with being at high genetic risk of breast cancer might make a woman choose to quit smoking. Without the information specific to women at high genetic risk, she may have made a different decision. This project will produce this type of information for smoking, alcohol and weight loss. It will also produce similar information but for policy makers about how much breast cancer rates might be reduced if, for example, the number of people smoking decreased by half. Finally, this project will lay the statistical groundwork so that other researchers can make the same type of information for people at higher genetic risks of other diseases.