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Polygenic Score Distribution Differences Across European Ancestry Populations: Implications for Breast Cancer Risk Prediction

Overview
Specialty Oncology
Date 2024 Dec 29
PMID 39734228
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Abstract

Background: The 313-variant polygenic risk score (PRS) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS across different European populations which could influence risk estimation has not been performed.

Methods: We explored the distribution of PRS across European populations using genotype data from 94,072 females without breast cancer diagnosis, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 223,316 females without breast cancer diagnosis from the UK Biobank. The mean PRS was calculated by country in the BCAC dataset and by country of birth in the UK Biobank. We explored different approaches to reduce the observed heterogeneity in the mean PRS across the countries, and investigated the implications of the distribution variability in risk prediction.

Results: The mean PRS differed markedly across European countries, being highest in individuals from Greece and Italy and lowest in individuals from Ireland. Using the overall European PRS distribution to define risk categories, leads to overestimation and underestimation of risk in some individuals from these countries. Adjustment for principal components explained most of the observed heterogeneity in the mean PRS. The mean estimates derived when using an empirical Bayes approach were similar to the predicted means after principal component adjustment.

Conclusions: Our results demonstrate that PRS distribution differs even within European ancestry populations leading to underestimation or overestimation of risk in specific European countries, which could potentially influence clinical management of some individuals if is not appropriately accounted for. Population-specific PRS distributions may be used in breast cancer risk estimation to ensure predicted risks are correctly calibrated across risk categories.

Citing Articles

Polygenic risk scores stratify breast cancer risk among women with benign breast disease.

Sherman M, Winham S, Vierkant R, McCauley B, Scott C, Schrup S J Natl Cancer Inst. 2024; 117(3):456-464.

PMID: 39412492 PMC: 11884851. DOI: 10.1093/jnci/djae255.

References
1.
Ho W, Tan M, Mavaddat N, Tai M, Mariapun S, Li J . European polygenic risk score for prediction of breast cancer shows similar performance in Asian women. Nat Commun. 2020; 11(1):3833. PMC: 7395776. DOI: 10.1038/s41467-020-17680-w. View

2.
Lee A, Mavaddat N, Cunningham A, Carver T, Ficorella L, Archer S . Enhancing the BOADICEA cancer risk prediction model to incorporate new data on , , updates to tumour pathology and cancer incidence. J Med Genet. 2022; 59(12):1206-1218. PMC: 9691826. DOI: 10.1136/jmedgenet-2022-108471. View

3.
Ho W, Tai M, Dennis J, Shu X, Li J, Ho P . Polygenic risk scores for prediction of breast cancer risk in Asian populations. Genet Med. 2021; 24(3):586-600. PMC: 7612481. DOI: 10.1016/j.gim.2021.11.008. View

4.
Pashayan N, Morris S, Gilbert F, Pharoah P . Cost-effectiveness and Benefit-to-Harm Ratio of Risk-Stratified Screening for Breast Cancer: A Life-Table Model. JAMA Oncol. 2018; 4(11):1504-1510. PMC: 6230256. DOI: 10.1001/jamaoncol.2018.1901. View

5.
Li S, Milne R, Nguyen-Dumont T, Wang X, English D, Giles G . Prospective Evaluation of the Addition of Polygenic Risk Scores to Breast Cancer Risk Models. JNCI Cancer Spectr. 2021; 5(3). PMC: 8099999. DOI: 10.1093/jncics/pkab021. View