Death rates from breast cancer remain disproportionately high among women of African ancestry, often due to existing genetic models’ failure to accurately predict risk, higher rates of aggressive tumor subtypes, and later-stage diagnoses. Researchers at the University of Chicago Medicine have now developed polygenic risk score models that significantly improve breast cancer risk prediction for this historically underserved population.
Most current genetic tools for breast cancer risk prediction were developed using data from white women of European ancestry. These models perform well for that group but often fail to provide accurate predictions for African American women, particularly for aggressive subtypes like triple-negative breast cancer.
Using genetic data from more than 36,000 women through the African Ancestry Breast Cancer Genetics Consortium, which includes women from the US, the Caribbean and Sub-Saharan Africa, researchers created the most comprehensive breast cancer prediction tool for women of African ancestry. The new models showed significant improvement, with accuracy scores ranging from 0.61 to 0.64 compared to earlier models scoring 0.56 to 0.58.
Dezheng Huo, professor of public health sciences and senior author of the study, explained that polygenic risk scores worked well for European Americans but weren’t accurate for African American women due to smaller sample size and greater genetic diversity. By forming a large consortium combining data from 20 institutions, the team significantly improved prediction accuracy.
Women in the top 1 percent of risk scores had a 25.7 percent lifetime risk of developing breast cancer. The findings suggest high-risk women could benefit from screening as early as age 32, rather than waiting until the current recommendation of age 40 or 45.
See: “New genetic tools offer more accurate breast cancer prediction for women of African ancestry” (February 2, 2026)
