Abstract 3462: Mendelian randomization analysis of 27 cardiometabolic trait related polygenic scores identifies genetic risk for cardiometabolic and cardiovascular events in a large prospective study of breast cancer survivors
Authors: Peter N. Fiorica, Haiyang Sheng, Cecile A. Laurent, Janise M. Roh, Valerie S. Lee, Alexa Zimbalist, Isaac J. Ergas, Qianqian Zhu, Richard K. Cheng, Eileen Rillamas-Sun, Carlos Iribarren, Jamal S. Rana, Mai Nguyen-Huynh, Dawn L. Hershman, Lawrence H. Kushi, Christine B. Ambrosone, Marilyn L. Kwan, Heather Greenlee, Song Yao
Journal: Cancer Research (2024)

Abstract Background: CVD is the most common cause of non-cancer death in breast cancer patients. Due to cancer treatment-related cardiotoxicities, breast cancer survivors are at increased risk of cardiometabolic disease (CMD) and cardiovascular disease (CVD). In addition to treatment-related factors, behavioral risk factors such as diet, smoking, and obesity are shared between CVD and breast cancer. While clinical factors influencing the risk of CVD in breast cancer patients are well studied, the effects of genetic factors are less known. Methods: To investigate genetic factors contributing to risk of CMD and CVD in women with a history of breast cancer, we performed a Mendelian randomization analysis to explore the relationships between 27 polygenic scores (PGS) for CMD and CVD phenotypes selected from the PGS Catalog and literature and 13 incident CMD and CVD events in a large prospective cohort of 3,699 breast cancer survivors in the Pathways Study. Fine-Gray sub-distribution hazard ratios (HRs) and 95% confidence intervals (CIs) associated with one standard deviation of PGS were derived with adjustment for epidemiologic, clinical, and treatment factors. The time scale was defined as time since date of breast cancer diagnosis to first of incident event, health plan disenrollment, death, or end of study (12/31/2019). The proportional hazards assumption was tested using Schoenfeld residuals, and no violation was found. Results: We identified 19 PGS-CMD/CVD associations that met Bonferroni significance (P&amp;lt;1.17 × 10−4). Five PGS were associated with increased risk of dyslipidemia: apolipoprotein B (HR=1.52, 95% CI,1.38-1.65), LDL cholesterol (1.49, 1.36-1.63), total cholesterol (1.43, 1.31-1.56), triglyceride levels (1.24, 1.14-1.34), and coronary artery disease (1.22, 1.13-1.33). Four PGS were associated with increased risk of hypertension: systolic blood pressure (1.36, 1.25-1.48), diastolic blood pressure (1.21, 1.11-1.32), fasting glucose adjusted for BMI (1.19, 1.09-1.30), and hypertension (1.41, 1.29-1.54). PGS for atrial fibrillation was associated with increased risk of arrhythmia (1.40, 1.25-1.57) and any cardiovascular disease (1.22, 1.12-1.32). PGS for coronary artery disease and myocardial infarction were both associated with increased risk of ischemic heart disease (1.43, 1.21-1.70 and 1.38, 1.17-1.62, respectively). Conclusion: Our study provides strong evidence for the potential use of PGS to predict the risk of CVD and CMD in women with a history of breast cancer. Future studies may explore the use of PGS to identify women with breast cancer at high risk of CVD-related outcomes and strategies to mitigate this risk. Citation Format: Peter N. Fiorica, Haiyang Sheng, Cecile A. Laurent, Janise M. Roh, Valerie S. Lee, Alexa Zimbalist, Isaac J. Ergas, Qianqian Zhu, Richard K. Cheng, Eileen Rillamas-Sun, Carlos Iribarren, Jamal S. Rana, Mai Nguyen-Huynh, Dawn L. Hershman, Lawrence H. Kushi, Christine B. Ambrosone, Marilyn L. Kwan, Heather Greenlee, Song Yao. Mendelian randomization analysis of 27 cardiometabolic trait related polygenic scores identifies genetic risk for cardiometabolic and cardiovascular events in a large prospective study of breast cancer survivors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3462.