Recurrence risk modelling of the genetic susceptibility to ankylosing spondylitis
- aSpondyloarthritis Research Group, Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Headington, OX3 7BN, UK, bRoyal National Hospital for Rheumatic Diseases, Upper Borough Walls, Bath, BA1 1RL, UK
- Dr Brown
- Accepted 10 April 2000
OBJECTIVES It has long been suspected that susceptibility to ankylosing spondylitis (AS) is influenced by genes lying distant to the major histocompatibility complex. This study compares genetic models of AS to assess the most likely mode of inheritance, using recurrence risk ratios in relatives of affected subjects.
METHODS Recurrence risk ratios in different degrees of relatives were determined using published data from studies specifically designed to address the question. The methods of Risch were used to determine the expected recurrence risk ratios in different degrees of relatives, assuming equal first degree relative recurrence risk between models. Goodness of fit was determined by χ2 comparison of the expected number of affected subjects with the observed number, given equal numbers of each type of relative studied.
RESULTS The recurrence risks in different degrees of relatives were: monozygotic (MZ) twins 63% (17/27), first degree relatives 8.2% (441/5390), second degree relatives 1.0% (8/834), and third degree relatives 0.7% (7/997). Parent-child recurrence risk (7.9%, 37/466) was not significantly different from the sibling recurrence risk (8.2%, 404/4924), excluding a significant dominance genetic component to susceptibility. Poor fitting models included single gene, genetic heterogeneity, additive, two locus multiplicative, and one locus and residual polygenes (χ2 >32 (two degrees of freedom), p<10−6for all models). The best fitting model studied was a five locus model with multiplicative interaction between loci (χ2=1.4 (two degrees of freedom), p=0.5). Oligogenic multiplicative models were the best fitting over a range of population prevalences and first degree recurrence risk rates.
CONCLUSIONS This study suggests that of the genetic models tested, the most likely model operating in AS is an oligogenic model with predominantly multiplicative interaction between loci.
This study was funded by the Arthritis Research Campaign. Steven Laval is funded by the Oliver Bird Fund, Nuffield Foundation; Sinead Brophy by the Colonel WW Pilkington Charitable Trust; and Dr Andrei Calin by the Royal National Hospital for Rheumatic Diseases NHS Trust.