A metabolomic analysis of adiposity measures and pre- and postmenopausal breast cancer risk in the Nurses’ Health Studies View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2022-06-18

AUTHORS

Kristen D. Brantley, Oana A. Zeleznik, Barbra A. Dickerman, Raji Balasubramanian, Clary B. Clish, Julian Avila-Pacheco, Bernard Rosner, Rulla M. Tamimi, A. Heather Eliassen

ABSTRACT

BackgroundAdiposity is consistently positively associated with postmenopausal breast cancer and inversely associated with premenopausal breast cancer risk, though the reasons for this difference remain unclear.MethodsIn 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.ResultsMetabolite 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).ConclusionsThough 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. More... »

PAGES

1-10

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41416-022-01873-9

DOI

http://dx.doi.org/10.1038/s41416-022-01873-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1148779330

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/35717425


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