Polygenic Risk for Cardiometabolic and Cardiovascular Disease in a Multiethnic Cohort of Breast Cancer Survivors

BACKGROUND: Because of cancer treatment-related cardiotoxicities, women with histories of breast cancer are at increased risk for cardiovascular disease (CVD). Many polygenic scores (PGS) have been developed for predicting risk for CVD-related conditions in the general population, but their performance in breast cancer patients remains largely unexplored. OBJECTIVES: The aim of this study was to examine the performance of PGS for CVD-related traits to predict incident cardiometabolic disorder (CMD) and CVD in women with histories of breast cancer. METHODS: In a prospective multiethnic cohort of 3,620 breast cancer survivors, 27 PGS for CVD-related traits were we computed, and their associations with 12 incident CMD and CVD events were examined. The performance of these PGS was compared relative to clinical covariates-only models and by cardiotoxic cancer treatment. RESULTS: Twenty-three significant associations were identified after Bonferroni correction between PGS and CMD or CVD events in breast cancer patients. Although the model performance of PGS and multi-PGS added to or combined with clinical models for CMD and CVD risk prediction was numerically greater, these were not statistically significant. For some outcomes, PGS performed worse among patients who received cardiotoxic cancer treatments. CONCLUSIONS: Although there may be potential value of PGS in predicting the risk for CMD and CVD events in women with histories of breast cancer, current PGS performance is limited. This work highlights the need to develop de novo PGS in breast cancer patients and to include ancestrally diverse patient populations.