Evaluating mammographic density polygenic risk score for contralateral breast cancer risk prediction

Survivors of breast cancer face a substantially increased risk of developing contralateral breast cancer (CBC). We assessed whether risk prediction models for CBC are improved by integrating mammographic density (MD) and polygenic risk scores (PRS). We analyzed data from 399 European-ancestry breast cancer survivors in the WECARE Study, an international, population-based case-control study. Cases were women who developed CBC, and controls were women with unilateral breast cancer (UBC). All participants had genome-wide genotyping and MD measurements at three intensity levels (Cumulus, Altocumulus, and Cirrocumulus) using the CUMULUS software. A weighted PRS was constructed comprised of 64 previously identified genome-wide significant single nucleotide polymorphisms (SNPs) associated with MD (PRS_MD). Linear and logistic regression models were used to assess the associations between PRS_MD, MD measurements, and CBC risk, adjusting for potential confounders. PRS_MD was significantly associated with Cumulus and Altocumulus densities, but not Cirrocumulus. In multivariable-adjusted predictive models, the inclusion of PRS_MD improved adjusted R-squared values for Cumulus (from 20.6% to 22.8%) and Altocumulus (22.7% to 24.7%). However, for Cirrocumulus the PRS_MD was not a significant predictor of CBC risk, with an effect estimate of 0.27 (95% CI: -0.9,1.4; P = 0.69). PRS_MD was not independently associated with CBC risk and adding it to MD models resulted in only small, non‑significant gains in AUC. Exploratory interaction analyses did not indicate that PRS_MD modified the association between MD and CBC risk. MD remains a robust independent predictor of CBC risk. Although PRS_MD captures inherited predisposition to MD, the current PRS explains only a small fraction of MD variance and does not enhance CBC risk prediction beyond measured MD. Further research is needed to elucidate the genetic underpinnings of MD and their relevance to CBC susceptibility.

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Publication Details

Journal
Scientific Reports
Published
2026-03-04
DOI
https://doi.org/10.1038/s41598-026-42365-7
Primary Topic
Digital Radiography and Breast Imaging
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluating mammographic density polygenic risk score for contralateral breast cancer risk prediction

Tuong L. Nguyen, Andriy Derkach, Elnaz Naderi, Xiang Shu et al.
Scientific Reports
Digital Radiography and Breast Imaging
article

Evaluating mammographic density polygenic risk score for contralateral breast cancer risk prediction

Tuong L. Nguyen, Andriy Derkach, Elnaz Naderi, Xiang Shu, Meghan Woods, Jung Hun Oh, Malcolm C. Pike, Jonine L. Bernstein, Esther M. John, Kathleen E. Malone, Gordon P. Watt, Charles F. Lynch, Julia A. Knight
article en

Abstract

Survivors of breast cancer face a substantially increased risk of developing contralateral breast cancer (CBC). We assessed whether risk prediction models for CBC are improved by integrating mammographic density (MD) and polygenic risk scores (PRS). We analyzed data from 399 European-ancestry breast cancer survivors in the WECARE Study, an international, population-based case-control study. Cases were women who developed CBC, and controls were women with unilateral breast cancer (UBC). All participants had genome-wide genotyping and MD measurements at three intensity levels (Cumulus, Altocumulus, and Cirrocumulus) using the CUMULUS software. A weighted PRS was constructed comprised of 64 previously identified genome-wide significant single nucleotide polymorphisms (SNPs) associated with MD (PRS_MD). Linear and logistic regression models were used to assess the associations between PRS_MD, MD measurements, and CBC risk, adjusting for potential confounders. PRS_MD was significantly associated with Cumulus and Altocumulus densities, but not Cirrocumulus. In multivariable-adjusted predictive models, the inclusion of PRS_MD improved adjusted R-squared values for Cumulus (from 20.6% to 22.8%) and Altocumulus (22.7% to 24.7%). However, for Cirrocumulus the PRS_MD was not a significant predictor of CBC risk, with an effect estimate of 0.27 (95% CI: -0.9,1.4; P = 0.69). PRS_MD was not independently associated with CBC risk and adding it to MD models resulted in only small, non‑significant gains in AUC. Exploratory interaction analyses did not indicate that PRS_MD modified the association between MD and CBC risk. MD remains a robust independent predictor of CBC risk. Although PRS_MD captures inherited predisposition to MD, the current PRS explains only a small fraction of MD variance and does not enhance CBC risk prediction beyond measured MD. Further research is needed to elucidate the genetic underpinnings of MD and their relevance to CBC susceptibility.

Scientific Reports
University of Iowa (US), Memorial Sloan Kettering Cancer Center (US), The University of Melbourne (AU), University of Toronto (CA), Lunenfeld-Tanenbaum Research Institute (CA), The Netherlands Cancer Institute (NL), Fred Hutch Cancer Center (US), Public Health Ontario (CA), Stanford University (US)
National Cancer Institute
Good health and well-being
Openalex Percentile: Top 33%
Digital Radiography and Breast Imaging
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