scholarly journals A dietary pattern based on estrogen metabolism is associated with breast cancer risk in a prospective cohort of postmenopausal women

2018 ◽  
Vol 143 (3) ◽  
pp. 580-590 ◽  
Author(s):  
Mark A. Guinter ◽  
Alexander C. McLain ◽  
Anwar T. Merchant ◽  
Dale P. Sandler ◽  
Susan E. Steck
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Postmenopausal Women ◽  
Dietary Pattern ◽  
Prospective Cohort ◽  
Estrogen Metabolism

scholarly journals Estrogen metabolism and breast cancer risk among postmenopausal women: a case–cohort study within B~FIT

2013 ◽  
Vol 35 (2) ◽  
pp. 346-355 ◽  
Author(s):  
Cher M. Dallal ◽  
Jeffrey A. Tice ◽  
Diana S.M. Buist ◽  
Douglas C. Bauer ◽  
James V. Lacey ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cohort Study ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Postmenopausal Women ◽  
Estrogen Metabolism

scholarly journals Association of Estrogen Metabolism with Breast Cancer Risk in Different Cohorts of Postmenopausal Women

2016 ◽  
Vol 77 (4) ◽  
pp. 918-925 ◽  
Author(s):  
Joshua N. Sampson ◽  
Roni T. Falk ◽  
Catherine Schairer ◽  
Steven C. Moore ◽  
Barbara J. Fuhrman ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Postmenopausal Women ◽  
Estrogen Metabolism

scholarly journals Depression, Antidepressant Use, and Breast Cancer Risk in Pre- and Postmenopausal Women: A Prospective Cohort Study

2017 ◽  
Vol 27 (3) ◽  
pp. 306-314 ◽  
Author(s):  
Katherine W. Reeves ◽  
Olivia I. Okereke ◽  
Jing Qian ◽  
Rulla M. Tamimi ◽  
A. Heather Eliassen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cohort Study ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Postmenopausal Women ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Antidepressant Use

Antiplatelet drug use and breast cancer risk in a prospective cohort of postmenopausal women.

2021 ◽  
pp. cebp.EPI-20-1292-E.2020
Author(s):  
Manon Cairat ◽  
Marie Al Rahmoun ◽  
Marc J. Gunter ◽  
Gianluca Severi ◽  
Laure Dossus ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Drug Use ◽  
Cancer Risk ◽  
Postmenopausal Women ◽  
Prospective Cohort ◽  
Antiplatelet Drug

Cynical distrust increases breast cancer risk: Evidence from a prospective cohort study

2002 ◽  
Author(s):  
A. R. Aro ◽  
H. J. de Koning ◽  
K. Vehkalahti ◽  
P. Absetz ◽  
M. Schreck ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cohort Study ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Prospective Cohort Study ◽  
Prospective Cohort

scholarly journals Discovery of breast cancer risk genes and establishment of a prediction model based on estrogen metabolism regulation

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Feng Zhao ◽  
Zhixiang Hao ◽  
Yanan Zhong ◽  
Yinxue Xu ◽  
Meng Guo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Healthy Subjects ◽  
Metabolic Enzyme ◽  
Estrogen Metabolism ◽  
Polygenic Risk Score ◽  
Risk Genes ◽  
Polygenic Risk ◽  
Enzyme Gene

Abstract Background Multiple common variants identified by genome-wide association studies have shown limited evidence of the risk of breast cancer in Chinese individuals. In this study, we aimed to uncover the relationship between estrogen levels and the genetic polymorphism of estrogen metabolism-related enzymes in breast cancer (BC) and establish a risk prediction model composed of estrogen-metabolizing enzyme genes and GWAS-identified breast cancer-related genes based on a polygenic risk score. Methods Unrelated BC patients and healthy subjects were recruited for analysis of estrogen levels and single nucleotide polymorphisms (SNPs) in genes encoding estrogen metabolism-related enzymes. The polygenic risk score (PRS) was used to explore the combined effect of multiple genes, which was calculated using a Bayesian approach. An independent sample t-test was used to evaluate the differences between PRS scores of BC and healthy subjects. The discriminatory accuracy of the models was compared using the area under the receiver operating characteristic (ROC) curve. Results The estrogen homeostasis profile was disturbed in BC patients, with parent estrogens (E1, E2) and carcinogenic catechol estrogens (2/4-OHE1, 2-OHE2, 4-OHE2) significantly accumulating in the serum of BC patients. We then established a PRS model to evaluate the role of SNPs in multiple genes. PRS model 1 (M1) was established from SNPs in 6 GWAS-identified high risk genes. On the basis of M1, we added SNPs from 7 estrogen metabolism enzyme genes to establish PRS model 2 (M2). The independent sample t-test results showed that there was no difference between BC and healthy subjects in M1 (P = 0.17); however, there was a significant difference between BC and healthy subjects in M2 (P = 4.9*10− 5). The ROC curve results showed that the accuracy of M2 (AUC = 62.18%) in breast cancer risk identification was better than that of M1 (AUC = 54.56%). Conclusion Estrogen and related metabolic enzyme gene polymorphisms are closely related to BC. The model constructed by adding estrogen metabolic enzyme gene SNPs has a good predictive ability for breast cancer risk, and the accuracy is greatly improved compared with that of the PRS model that only includes GWAS-identified gene SNPs.

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