Modeling the Effect of Susceptibility Factors (HLA and PTPN22) in Rheumatoid Arthritis

Numerous genome-wide analyses on common multifactorial diseases have been recently published in providing, for each associated Single Nucleotide Polymorphism (SNP), an Odds Ratio (OR), either for one of the susceptibility variant allele versus none, or for two copies of it versus one copy. Besides the poor information attached to these measures, it is a simplistic idea to reduce the effect of a gene to the one of an allele or of an haplotype. It is a far cry from detecting a signal indicating the presence of a causative factor in a genomic region to its identification and the important task of estimating the disease risk due to it. The contrast between cases and controls may be used for the estimation of the genotype relative risks. However, the same population distribution of a marker can be coupled with different modes of inheritance of the trait, and hence different risk estimates. Other sources of information, in particular at familial level must be used and can be crucial in discriminating the genotypes according to the disease risk. Illustration is given on two susceptibility factors to Rheumatoid Arthritis: HLA and PTPN22. In both cases, thanks to the sharing of parental alleles in affected sibs, a refining of the modeling was obtained. Tezenas du Montcel et al. (Arthritis Rheum 52:1063–1068, 2005) show that six HLA genotypes can be distinguished with different RA risks. One HLA genotype confers a risk 6.6-fold higher than another HLA genotype. For PTPN22, Bourgey et al. (BMC Proc 1 (Suppl 1):S37, 2007) show that observed data is not explained by a single variant as initially reported and that using the information on 3 SNPs discriminates the genotypic relative risks (GRRs) from 1 to 4.7.