Eleanor Watts

D.Phil., M.P.H.

National Cancer Institute

Postdoctoral Fellow

PLCO (Learn more about this study)

PLCO-1287

Aug 8, 2023

Metabolomic markers of physical activity and associations with breast cancer

Being physically active is associated with lower risks of breast cancer (HR for high vs low physical activity, 0.90; 95% CI, 0.87-0.93)1. However, the mechanisms through which physical activity conveys this health benefit is less established. The development of high throughput metabolomics offers a novel opportunity to investigate these mechanisms. Previous metabolomic studies, based on self-reported leisure time activity, have reported that physical activity levels are associated with some amino acids, lipids, and triglycerides2. Nested case control studies have also observed associations for some of these metabolite classes with breast cancer risk3. However, precise techniques to measure physical activity are expensive and time consuming for studies to administer. Consequently, there are limited high quality data for physical activity, metabolites, and breast cancer, impeding our understanding of these relationships.
The IDATA study used gold standard methods to assess physical activity and also collected metabolite concentrations in participants4. The PLCO has previously measured serum metabolites in a nested case control breast cancer study3. This provides a unique opportunity to investigate the relationships of metabolomic markers of physical activity with breast cancer risk.
We anticipate that the proposed analysis will lead to the discovery of novel biomarkers of physical activity and improve our understanding the biological mechanisms underpinning the physical activity and breast cancer relationship.

Methods
Metabolites associated with physical activity will be identified using the IDATA Study (Metabolon platform).
In PLCO, serum metabolites were measured by the Metabolon platform (N postmenopausal breast cancer cases=621, N controls=621)3. For each of the physical activity associated metabolites, we will investigate associations with risk of breast cancer using conditional logistic regression, conditioned on the matching factors. All models will be adjusted for age, sex, racial/ethnic group, body mass index and detailed smoking history.

References
1. Moore SC, Lee I-M, Weiderpass E, et al. Association of Leisure-Time Physical Activity With Risk of 26 Types of Cancer in 1.44 Million Adults. JAMA Internal Medicine. 2016;176(6):816-825. doi:10.1001/jamainternmed.2016.1548
2. Kelly RS, Kelly MP, Kelly P. Metabolomics, physical activity, exercise and health: A review of the current evidence. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 2020/12/01/ 2020;1866(12):165936. doi:https://doi.org/10.1016/j.bbadis.2020.165936
3. Moore SC, Playdon MC, Sampson JN, et al. A Metabolomics Analysis of Body Mass Index and Postmenopausal Breast Cancer Risk. J Natl Cancer Inst. Jun 1 2018;110(6):588-597. doi:10.1093/jnci/djx244
4. Matthews CE, Kozey Keadle S, Moore SC, et al. Measurement of Active and Sedentary Behavior in Context of Large Epidemiologic Studies. Med Sci Sports Exerc. Feb 2018;50(2):266-276. doi:10.1249/mss.0000000000001428