title: Genetic ancestry and risk factors for breast cancer among Latinas in the San Francisco Bay Area.
abstract: BACKGROUND
  Genetic association studies using case-control designs are susceptible to false-positive and false-negative results if there are differences in genetic ancestry between cases and controls. We measured genetic ancestry among Latinas in a population-based case-control study of breast cancer and tested the association between ancestry and known breast cancer risk factors. We reasoned that if genetic ancestry is associated with known breast cancer risk factors, then the results of genetic association studies would be confounded.
  
  
  METHODS
  We used 44 ancestry informative markers to estimate individuals' genetic ancestry in 563 Latina participants. To test whether ancestry is a predictor of hormone therapy use, parity, and body mass index (BMI), we used multivariate logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (95% CI) associated with a 25% increase in Indigenous American ancestry, adjusting for age, education, and the participant's and grandparents' place of birth.
  
  
  RESULTS
  Hormone therapy use was significantly less common among women with higher Indigenous American ancestry (OR, 0.78; 95% CI, 0.63-0.96). Higher Indigenous American ancestry was also significantly associated with overweight (BMI, 25-29.9 versus <25) and obesity (BMI, > or =30 versus <25), but only among foreign-born Latina women (OR, 3.44; 95% CI, 1.97-5.99 and OR, 1.95; 95% CI, 1.24-3.06, respectively).
  
  
  CONCLUSIONS
  Some breast cancer risk factors are associated with genetic ancestry among Latinas in the San Francisco Bay Area. Therefore, case-control genetic association studies for breast cancer should directly measure genetic ancestry to avoid potential confounding.
authors.affiliation: Division of General Internal Medicine, University of California San Francisco, Box 1732, San Francisco, CA 94143, USA. elad.ziv@ucsf.edu
authors.forename: Elad
authors.initials: E
authors.lastname: Ziv
authors.forename: Esther M
authors.initials: EM
authors.lastname: John
authors.forename: Shweta
authors.initials: S
authors.lastname: Choudhry
authors.forename: Jennifer
authors.initials: J
authors.lastname: Kho
authors.forename: Wendy
authors.initials: W
authors.lastname: Lorizio
authors.forename: Eliseo J
authors.initials: EJ
authors.lastname: Perez-Stable
authors.forename: Esteban Gonzalez
authors.initials: EG
authors.lastname: Burchard
mesh_terms: D000328:Adult; D001741:Black or African American / Q000235:genetics; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000208:ethnology* / Q000209:etiology* / Q000235:genetics; D016022:Case-Control Studies; D004641:Emigration and Immigration; D005260:Female; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease / Q000208:ethnology; D005838:Genotype; D006630:Hispanic or Latino / Q000235:genetics* / Q000706:statistics & numerical data; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D015999:Multivariate Analysis; D009765:Obesity / Q000150:complications / Q000208:ethnology; D011159:Population Surveillance; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors; D012495:San Francisco / Q000453:epidemiology; D044465:White People / Q000235:genetics
chemical_list: D005819:Genetic Markers