Exploring Pre- and Postmenopausal Breast Cancer Risk Factors through Metabolomics and Risk Prediction Modeling
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Brantley, Kristen Donelle
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CitationBrantley, Kristen Donelle. 2021. Exploring Pre- and Postmenopausal Breast Cancer Risk Factors through Metabolomics and Risk Prediction Modeling. Doctoral dissertation, Harvard University Graduate School of Arts and Sciences.
AbstractEvidence suggests that breast cancer, long recognized as a hormonal disease, also has a metabolic component influencing its development. However, etiologic mechanisms of breast cancer, including those related to metabolism, remain elusive given its heterogenous nature. Investigation of metabolomics can provide information on biochemical processes key to breast cancer development. Further, because some breast cancer risk factors differ by menopausal status at diagnosis, evaluating metabolomics and risk factors by menopausal groups is important to capture underlying disease mechanisms. Research into risk factors with opposing associations with pre- vs. postmenopausal breast cancers will allow better understanding of the biologic development of this disease.
In this dissertation, I explore potential etiologic mechanisms for pre- and postmenopausal breast cancer through metabolomics and examine differences in risk factor profiles based on menopausal status at diagnosis. In Chapter 1 I took an agnostic approach to examine metabolite associations with breast cancer risk in a nested matched case-control study (N cases=939, N controls=939) in the Nurses’ Health Study (NHS). I uncovered several metabolite groups associated with risk of breast cancer, including cholesteryl esters (inversely associated with risk), triacylglycerols (TAGS) with double bonds (positively associated with risk), and TAGs with ≥ 3 double bonds (inversely associated with risk). I noted changing associations between metabolite groups and breast cancer risk dependent on timing of measurement. In Chapter 2, I took a closer look at adiposity as a risk factor for pre- and postmenopausal breast cancer and evaluated metabolomic profiles for adiposity measures. I found that metabolomic scores were often more informative than self-reported measures for adiposity in determining breast cancer risk, suggesting metabolic dysregulation as a key etiologic component to breast cancer. I also found that metabolite profiles for adiposity measures were similar by menopausal status, though associations with risk were opposite. In Chapter 3, I developed a risk prediction model for premenopausal breast cancer to identify risk factors important to development of this disease. I found that many risk factors identified as significant in primarily postmenopausal cohorts were similarly important for premenopausal breast cancer, including premenopausal duration, ever having a birth, time from menarche to first birth, height, alcohol use, BMI in young adulthood, family history of breast cancer, and history of benign breast disease.
Overall, this dissertation suggests that mechanisms of metabolic dysregulation are key components for breast cancer development. Differences seen in risk of pre- vs. postmenopausal breast cancer with respect to certain risk factors, such as adiposity, may be explained by differential action of metabolic dysregulation across the life-course. Discovery that most reproductive and hormonal risk factors for premenopausal breast cancer align with those for postmenopausal breast cancer supports the notion that metabolic dysregulation may be a key element to distinguish the two diseases. Evaluation of the factors of metabolic dysregulation that may be responsible for differences in pre-vs. postmenopausal breast cancer risk can enhance knowledge about etiologic mechanisms for development of breast cancer over time.
Citable link to this pagehttps://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37370116
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