Approaches to identifying genetic predictors of clinical outcome in rheumatoid arthritis.

Abstract

Predicting which patients with rheumatoid arthritis (RA), at presentation, are likely to suffer a severe disease course based on genotype data would be a major clinical advance. It would ensure that patients at highest risk of a severe outcome could be targeted with early aggressive therapies. With a better understanding of interactions between genotype and drug response it would be possible to prescribe treatments most likely to be efficacious and safe for specific patient subgroups. While a clear genetic component has been demonstrated in RA severity, the identification of genetic factors poses a challenge to researchers in the field. Initiatives such as the SNP Consortium and advances in genotyping technology have facilitated the investigation of genetic factors in both disease susceptibility and severity. However, several other factors, such as the availability of suitable longitudinal cohorts, definition of outcome measures, study design, selection of genetic markers, and statistical power, will all contribute to the likely success of genetic studies. Several strategies that have been applied in the pursuit of genetic predictors of clinical outcome in RA. While some encouraging results have been generated, it has so far been difficult to quantify the predictive value of genetic markers and extrapolate the results from genetic studies to clinic patients. Establishing high quality prospective inception cohorts, a more systemic approach to defining suitable outcome measures, and understanding the effects of treatment, will be critical to the eventual identification of good predictive genetic markers.