title: An evaluation of inflammatory gene polymorphisms in sibships discordant for premature coronary artery disease: the GRACE-IMMUNE study.
abstract: BACKGROUND
  Inflammatory cytokines play a crucial role in coronary artery disease (CAD). We investigated the association between 48 coding and three non-coding single nucleotide polymorphisms (SNPs) from 35 inflammatory genes and the development of CAD, using a large discordant sibship collection (2699 individuals in 891 families).
  
  
  METHODS
  Family-based association tests (FBAT) and conditional logistic regression (CLR) were applied to single SNPs and haplotypes and, in CLR, traditional risk factors of CAD were adjusted for.
  
  
  RESULTS
  An association was observed between CAD and a common three-locus haplotype in the interleukin one (IL-1) cluster with P = 0.006 in all CAD cases, P = 0.01 in myocardial infarction (MI) cases and P = 0.0002 in young onset CAD cases (<50 years). The estimated odds ratio (OR) per copy of this haplotype is 1.21 (95% confidence interval [95CI] = 1.04 - 1.40) for CAD; 1.30 (95CI = 1.09 - 1.56) for MI and 1.50 (95CI = 1.22 - 1.86) for young onset CAD. When sex, smoking, hypertension and hypercholesterolaemia were adjusted for, the haplotype effect remained nominally significant (P = 0.05) in young onset CAD cases, more so (P = 0.002) when hypercholesterolaemia was excluded. As many as 82% of individuals affected by CAD had hypercholesterolaemia compared to only 29% of those unaffected, making the two phenotypes difficult to separate.
  
  
  CONCLUSIONS
  Despite the multiple hypotheses tested, the robustness of family design to population confoundings and the consistency with previous findings increase the likelihood of true association. Further investigation using larger data sets is needed in order for this to be confirmed. See the related commentary by Keavney: http://www.biomedcentral.com/1741-7015/8/6.
authors.affiliation: Leeds Institute of Genetics, Health and Therapeutics (LIGHT), University of Leeds, UK.
authors.forename: Benjamin D
authors.initials: BD
authors.lastname: Brown
authors.forename: Jérémie
authors.initials: J
authors.lastname: Nsengimana
authors.forename: Jennifer H
authors.initials: JH
authors.lastname: Barrett
authors.forename: Richard A
authors.initials: RA
authors.lastname: Lawrence
authors.forename: Lori
authors.initials: L
authors.lastname: Steiner
authors.forename: Suzanne
authors.initials: S
authors.lastname: Cheng
authors.forename: D Timothy
authors.initials: DT
authors.lastname: Bishop
authors.forename: Nilesh J
authors.initials: NJ
authors.lastname: Samani
authors.forename: Stephen G
authors.initials: SG
authors.lastname: Ball
authors.forename: Anthony J
authors.initials: AJ
authors.lastname: Balmforth
authors.forename: Alistair S
authors.initials: AS
authors.lastname: Hall
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D003324:Coronary Artery Disease / Q000235:genetics*; D016207:Cytokines / Q000235:genetics*; D005190:Family; D005260:Female; D020022:Genetic Predisposition to Disease; D006239:Haplotypes; D006801:Humans; D007375:Interleukin-1 / Q000235:genetics; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide; D012307:Risk Factors
chemical_list: D016207:Cytokines; D007375:Interleukin-1