title: Genetic variation in multiple biologic pathways, flavonoid intake, and breast cancer.
abstract: OBJECTIVE
  We previously reported an inverse association between flavonoid intake and breast cancer incidence, which has been confirmed by others, but no studies have considered simultaneously potential interactions of flavonoids with multiple genetic polymorphisms involved in biologically relevant pathways (oxidative stress, carcinogen metabolism, DNA repair, and one-carbon metabolism).
  
  
  METHODS
  To estimate interaction effects between flavonoids and 13 polymorphisms in these four pathways on breast cancer risk, we used population-based data (n = 875 cases and 903 controls) and several statistical approaches, including conventional logistic regression and semi-Bayesian hierarchical modeling (incorporating prior information on the possible biologic functions of genes), which also provides biologic pathway-specific effect estimates.
  
  
  RESULTS
  Compared to the standard multivariate model, the results from the hierarchical model indicate that gene-by-flavonoid interaction estimates are attenuated, but more precise. In the hierarchical model, the average effect of the deleterious versus beneficial gene, controlling for average flavonoid intake in the DNA repair pathway, and adjusted for the three other biologically relevant pathways (oxidative stress, carcinogen metabolism, and one-carbon metabolism), resulted in a 27 % increase risk for breast cancer [odds ratio = 1.27; 95 % confidence interval (CI) = 0.70, 2.29]. However, the CI was wide.
  
  
  CONCLUSIONS
  Based on results from the semi-Bayesian model, breast cancer risk may be influenced jointly by flavonoid intake and genes involved in DNA repair, but our findings require confirmation.
authors.affiliation: Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA, khankari@email.unc.edu.
authors.forename: Nikhil K
authors.initials: NK
authors.lastname: Khankari
authors.forename: Patrick T
authors.initials: PT
authors.lastname: Bradshaw
authors.forename: Lauren E
authors.initials: LE
authors.lastname: McCullough
authors.forename: Susan L
authors.initials: SL
authors.lastname: Teitelbaum
authors.forename: Susan E
authors.initials: SE
authors.lastname: Steck
authors.forename: Brian N
authors.initials: BN
authors.lastname: Fink
authors.forename: Xinran
authors.initials: X
authors.lastname: Xu
authors.forename: Jiyoung
authors.initials: J
authors.lastname: Ahn
authors.forename: Christine B
authors.initials: CB
authors.lastname: Ambrosone
authors.forename: Katherine D
authors.initials: KD
authors.lastname: Crew
authors.forename: Mary Beth
authors.initials: MB
authors.lastname: Terry
authors.forename: Alfred I
authors.initials: AI
authors.lastname: Neugut
authors.forename: Jia
authors.initials: J
authors.lastname: Chen
authors.forename: Regina M
authors.initials: RM
authors.lastname: Santella
authors.forename: Marilie D
authors.initials: MD
authors.lastname: Gammon
mesh_terms: D000368:Aged; D001499:Bayes Theorem; D001943:Breast Neoplasms / Q000097:blood / Q000453:epidemiology* / Q000235:genetics*; D016022:Case-Control Studies; D004273:DNA, Neoplasm / Q000097:blood / Q000235:genetics; D005260:Female; D005419:Flavonoids / Q000008:administration & dosage*; D059647:Gene-Environment Interaction; D020022:Genetic Predisposition to Disease; D005838:Genotype; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D011110:Polymorphism, Genetic; D012307:Risk Factors; D011795:Surveys and Questionnaires; D014481:United States / Q000453:epidemiology
chemical_list: D004273:DNA, Neoplasm; D005419:Flavonoids