Kristen D Brantley1, Oana A Zeleznik2, Barbra A Dickerman3, Raji Balasubramanian4, Clary B Clish5, Julian Avila-Pacheco5, Bernard Rosner2,6, Rulla M Tamimi7, A Heather Eliassen3,2. 1. Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA. kbrantley@g.harvard.edu. 2. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. 3. Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA. 4. Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA. 5. Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA. 6. Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA. 7. Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
Abstract
BACKGROUND: Adiposity is consistently positively associated with postmenopausal breast cancer and inversely associated with premenopausal breast cancer risk, though the reasons for this difference remain unclear. METHODS: In this nested case-control study of 1649 breast cancer cases and 1649 matched controls from the Nurses' Health Study (NHS) and the NHSII, we selected lipid and polar metabolites correlated with BMI, waist circumference, weight change since age 18, or derived fat mass, and developed a metabolomic score for each measure using LASSO regression. Logistic regression was used to investigate the association between this score and breast cancer risk, adjusted for risk factors and stratified by menopausal status at blood draw and diagnosis. RESULTS: Metabolite scores developed among only premenopausal or postmenopausal women were highly correlated with scores developed in all women (r = 0.93-0.96). Higher metabolomic adiposity scores were generally inversely related to breast cancer risk among premenopausal women. Among postmenopausal women, significant positive trends with risk were observed (e.g., metabolomic waist circumference score OR Q4 vs. Q1 = 1.47, 95% CI = 1.03-2.08, P-trend = 0.01). CONCLUSIONS: Though the same metabolites represented adiposity in pre- and postmenopausal women, breast cancer risk associations differed suggesting that metabolic dysregulation may have a differential association with pre- vs. postmenopausal breast cancer.
BACKGROUND: Adiposity is consistently positively associated with postmenopausal breast cancer and inversely associated with premenopausal breast cancer risk, though the reasons for this difference remain unclear. METHODS: In this nested case-control study of 1649 breast cancer cases and 1649 matched controls from the Nurses' Health Study (NHS) and the NHSII, we selected lipid and polar metabolites correlated with BMI, waist circumference, weight change since age 18, or derived fat mass, and developed a metabolomic score for each measure using LASSO regression. Logistic regression was used to investigate the association between this score and breast cancer risk, adjusted for risk factors and stratified by menopausal status at blood draw and diagnosis. RESULTS: Metabolite scores developed among only premenopausal or postmenopausal women were highly correlated with scores developed in all women (r = 0.93-0.96). Higher metabolomic adiposity scores were generally inversely related to breast cancer risk among premenopausal women. Among postmenopausal women, significant positive trends with risk were observed (e.g., metabolomic waist circumference score OR Q4 vs. Q1 = 1.47, 95% CI = 1.03-2.08, P-trend = 0.01). CONCLUSIONS: Though the same metabolites represented adiposity in pre- and postmenopausal women, breast cancer risk associations differed suggesting that metabolic dysregulation may have a differential association with pre- vs. postmenopausal breast cancer.
Authors: A Heather Eliassen; Shelley S Tworoger; Christos S Mantzoros; Michael N Pollak; Susan E Hankinson Journal: Cancer Epidemiol Biomarkers Prev Date: 2007-01 Impact factor: 4.254
Authors: Libby M Morimoto; Emily White; Z Chen; Rowan T Chlebowski; Jennifer Hays; Lewis Kuller; Ana Marie Lopez; JoAnn Manson; Karen L Margolis; Paola C Muti; Marcia L Stefanick; Anne McTiernan Journal: Cancer Causes Control Date: 2002-10 Impact factor: 2.506
Authors: Kristy A Brown; Neil M Iyengar; Xi Kathy Zhou; Ayca Gucalp; Kotha Subbaramaiah; Hanhan Wang; Dilip D Giri; Monica Morrow; Domenick J Falcone; Nils K Wendel; Lisle A Winston; Michael Pollak; Anneloor Dierickx; Clifford A Hudis; Andrew J Dannenberg Journal: J Clin Endocrinol Metab Date: 2017-05-01 Impact factor: 5.958
Authors: Shelley S Tworoger; A Heather Eliassen; Stacey A Missmer; Heather Baer; Janet Rich-Edwards; Karin B Michels; Robert L Barbieri; Mitch Dowsett; Susan E Hankinson Journal: Cancer Epidemiol Biomarkers Prev Date: 2006-12 Impact factor: 4.254
Authors: Juhua Luo; Xiwei Chen; JoAnn E Manson; Aladdin H Shadyab; Jean Wactawski-Wende; Mara Vitolins; Thomas E Rohan; Ting-Yuan D Cheng; Zhenzhen Zhang; Lihong Qi; Michael Hendryx Journal: Int J Cancer Date: 2019-10-18 Impact factor: 7.396
Authors: Krithika Srikanthan; Andrew Feyh; Haresh Visweshwar; Joseph I Shapiro; Komal Sodhi Journal: Int J Med Sci Date: 2016-01-01 Impact factor: 3.738