title: Estimating single nucleotide polymorphism associations using pedigree data: applications to breast cancer.
abstract: BACKGROUND
  Pedigrees with multiple genotyped family members have been underutilised in breast cancer (BC) genetic-association studies. We developed a pedigree-based analytical framework to characterise single-nucleotide polymorphism (SNP) associations with BC risk using data from 736 BC families ascertained through multiple affected individuals. On average, eight family members had been genotyped for 24 SNPs previously associated with BC.
  
  
  METHODS
  Breast cancer incidence was modelled on the basis of SNP effects and residual polygenic effects. Relative risk (RR) estimates were obtained by maximising the retrospective likelihood (RL) of observing the family genotypes conditional on all disease phenotypes. Models were extended to assess parent-of-origin effects (POEs).
  
  
  RESULTS
  Thirteen SNPs were significantly associated with BC under the pedigree RL approach. This approach yielded estimates consistent with those from large population-based studies. Logistic regression models ignoring pedigree structure generally gave larger RRs and association P-values. SNP rs3817198 in LSP1, previously shown to exhibit POE, yielded maternal and paternal RR estimates that were similar to those previously reported (paternal RR=1.12 (95% confidence interval (CI): 0.99-1.27), P=0.081, one-sided P=0.04; maternal RR=0.94 (95% CI: 0.84-1.06), P=0.33). No other SNP exhibited POE.
  
  
  CONCLUSIONS
  Our pedigree-based methods provide a valuable and efficient tool for characterising genetic associations with BC risk or other diseases and can complement population-based studies.
authors.affiliation: Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK.
authors.forename: D R
authors.initials: DR
authors.lastname: Barnes
authors.forename: D
authors.initials: D
authors.lastname: Barrowdale
authors.forename: J
authors.initials: J
authors.lastname: Beesley
authors.forename: X
authors.initials: X
authors.lastname: Chen
authors.forename: P A
authors.initials: PA
authors.lastname: James
authors.forename: J L
authors.initials: JL
authors.lastname: Hopper
authors.forename: D
authors.initials: D
authors.lastname: Goldgar
authors.forename: G
authors.initials: G
authors.lastname: Chenevix-Trench
authors.forename: A C
authors.initials: AC
authors.lastname: Antoniou
authors.forename: G
authors.initials: G
authors.lastname: Mitchell
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000175:diagnosis / Q000453:epidemiology / Q000235:genetics*; D016022:Case-Control Studies; D005260:Female; D056726:Genetic Association Studies / Q000379:methods*; D020022:Genetic Predisposition to Disease; D006801:Humans; D008297:Male; D008875:Middle Aged; D010051:Ovarian Neoplasms / Q000175:diagnosis / Q000453:epidemiology / Q000235:genetics; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide; D012307:Risk Factors; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods; D055815:Young Adult