Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition

• DOI: 10.1200/po.22.00084
• Publication Date: 2022-11-03T19:59:36Z
• Authors: Elisha Hughes; Susanne Wagner; Dmitry Pruss; Ryan Bernhisel; Braden Probst; Victor Abkevich; Timothy Simmons; Brooke Hullinger; Thaddeus Judkins; Eric Rosenthal; Benjamin Roa; Susan M. Domchek; Charis Eng; Judy Garber; Monique Gary; Jennifer Klemp; Semanti Mukherjee; Kenneth Offit; Olufunmilayo I. O...; Joseph Vijai; Jeffrey N. Weitzel; Pat Whitworth; Lamis Yehia; Ora Gordon; Holly Pederson; Allison Kurian; Thomas P. Slavin; Alexander Gutin; Jerry S. Lanchbury
• Keywords: 0301 basic medicine; Multifactorial Inheritance; 03 medical and health sciences; Risk Factors; Humans; Female; Breast Neoplasms; Genetic Predisposition to Disease; ORIGINAL REPORTS; Genome-Wide Association Study; 3. Good health

PURPOSE Polygenic risk scores (PRSs) for breast cancer (BC) risk stratification have been developed primarily in women of European ancestry. Their application to women of non-European ancestry has lagged because of the lack of a formal approach to incorporate genetic ancestry and ancestry-dependent variant frequencies and effect sizes. Here, we propose a multiple-ancestry PRS (MA-PRS) that addresses these issues and may be useful in the development of equitable PRSs across other cancers and common diseases. MATERIALS AND METHODS Women referred for hereditary cancer testing were divided into consecutive cohorts for development (n = 189,230) and for independent validation (n = 89,126). Individual genetic composition as fractions of three reference ancestries (African, East Asian, and European) was determined from ancestry-informative single-nucleotide polymorphisms. The MA-PRS is a combination of three ancestry-specific PRSs on the basis of genetic ancestral composition. Stratification of risk was evaluated by multivariable logistic regression models controlling for family cancer history. Goodness-of-fit analysis compared expected with observed relative risks by quantiles of the MA-PRS distribution. RESULTS In independent validation, the MA-PRS was significantly associated with BC risk in the full cohort (odds ratio, 1.43; 95% CI, 1.40 to 1.46; P = 8.6 × 10–308) and within each major ancestry. The top decile of the MA-PRS consistently identified patients with two-fold increased risk of developing BC. Goodness-of-fit tests showed that the MA-PRS was well calibrated and predicted BC risk accurately in the tails of the distribution for both European and non-European women. CONCLUSION The MA-PRS uses genetic ancestral composition to expand the utility of polygenic risk prediction to non-European women. Inclusion of genetic ancestry in polygenic risk prediction presents an opportunity for more personalized treatment decisions for women of varying and mixed ancestries.