Genetic data: The new challenge of personalized medicine, insights for rheumatoid arthritis patients

• Progress in the identification of genetic variants of clinical significance has been made over the past few years.
• Many factors shape the future use of genetic information in personalized medicine, ranging from the discovery of disease-associated variants to the resulting insights into disease biology.
• Developments in genomics, including NGS technologies, are expected to enable a more personalized approach to clinical care, with improved risk stratification and treatment selection.
• By incorporating gene expression as a biological output related to the genetic variation, it is possible that eQTL methods could enhance pharmacogenomic efforts in RA.

Rapid advances in genotyping technology, analytical methods, and the establishment of large cohorts for population genetic studies have resulted in a large new body of information about the genetic basis of human rheumatoid arthritis (RA). Improved understanding of the root pathogenesis of the disease holds the promise of improved diagnostic and prognostic tools based upon this information. In this review, we summarize the nature of new genetic findings in human RA, including susceptibility loci and gene–gene and gene–environment interactions, as well as genetic loci associated with sub-groups of patients and those associated with response to therapy. Possible uses of these data are discussed, such as prediction of disease risk as well as personalized therapy and prediction of therapeutic response and risk of adverse events. While these applications are largely not refined to the point of clinical utility in RA, it seems likely that multi-parameter datasets including genetic, clinical, and biomarker data will be employed in the future care of RA patients.