Genetics and epigenetics of rheumatoid arthritis

Abstract

Investigators have made key advances in rheumatoid arthritis (RA) genetics in the past 10 years. Although genetic studies have had limited influence on clinical practice and drug discovery, they are currently generating testable hypotheses to explain disease pathogenesis. Firstly, we review here the major advances in identifying RA genetic susceptibility markers both within and outside of the MHC. Understanding how genetic variants translate into pathogenic mechanisms and ultimately into phenotypes remains a mystery for most of the polymorphisms that confer susceptibility to RA, but functional data are emerging. Interplay between environmental and genetic factors is poorly understood and in need of further investigation. Secondly, we review current knowledge of the role of epigenetics in RA susceptibility. Differences in the epigenome could represent one of the ways in which environmental exposures translate into phenotypic outcomes. The best understood epigenetic phenomena include post-translational histone modifications and DNA methylation events, both of which have critical roles in gene regulation. Epigenetic studies in RA represent a new area of research with the potential to answer unsolved questions.

Figure 1

Antigen-binding groove HLA amino acid substitutions and influence on susceptibility to RA. a | Three-dimensional ribbon models for the MHC class I molecule HLA-B and for the MHC class II molecules HLA-DRβ1 and HLA-DPβ1. Direct views of the peptide-binding groove are presented, showing key amino acid positions identified in an association analysis by Raychaudhuri, S. et al. Nat. Genet. 44, 291–296 (2012). © NPG b | The odds ratio for association with RA depends on which amino acid is substituted at positions 11, 71 and 74 of HLA-DRβ1, at position 9 of HLA-B or at position 9 of HLA-DPβ1. Abbreviation: RA, rheumatoid arthritis.

Figure 2

RA genetic susceptibility loci identified to date, and cumulative proportion of observed variance in disease susceptibility explained thus far. As of 2012, approximately 16% of phenotypic variance has been accounted for genetically. Odds ratios^,,,, for RA genetic susceptibility loci are presented in the approximate chronological order of discovery (blue and orange bars). Only susceptibility loci in white cohorts (blue) were included in calculating the proportion of phenotypic variance explained. Loci validated only in east-Asian populations are shown in orange; although the loci identified by Okada et al. were published a few months before the Immunochip study, they are presented at the far right of the plot for graphical convenience. Shared loci across different populations are shown at the time of their discovery in white cohorts. A 0.5% disease prevalence was assumed for calculations. For simplification, every locus is represented once, even if multiple independent effects were identified (except for TNFAIP3). The cumulative percent variance explained by the loci is indicated by the red line. Abbreviation: RA, rheumatoid arthritis.

Figure 3

Mapping of 11 RA susceptibility loci to pathways involved in the ‘T-cell–dendritic-cell dialogue’. The gene products (blue) of several RA susceptibility loci are implicated in the three pathways represented here—the TCR, TNF and CD40 signalling pathways. To avoid overloading the picture and to represent pathways as linear and chronological successions of molecular interactions, several membrane-associated factors are schematically represented in the cytosol and many key molecules or interactions have been omitted (for example, the p38 and JNK pathways, CD28 co-stimulation, and adhesion mediated by CD2 and CD58). NF κB is a homodimer or heterodimer containing 2 of the following subunits: RelA, RelB, c-Rel, NF κB1, NF κB2. Only c-Rel is associated with RA. CD45 and PKC-θ are encoded by PTPRC and PRKCQ respectively; both of these genes are within RA susceptibility loci. Abbreviations: NF κB, nuclear factor κB; PTPN22, tyrosine-protein phosphatase non-receptor type 22; TCR, T-cell receptor; TNFR1: TNF receptor 1; TNFAIP3, TNF-induced protein 3.

Figure 4

Network analysis to infer functional characteristics of genetic variants implicated in RA susceptibility. Analysis of RA susceptibility genes using protein–protein interaction databases shows the extent of potential physical interaction between their protein products. This network has been built using RA candidate genes and comprises major and minor network nodes (large and small circles respectively), both representing proteins. Several confirmed RA suceptibiltiy loci can be recognized among major nodes. The lines indicate physical interactions. Reproduced from Rossin, E. J. et al. PLoS Genet. 2011 Jan; 7(1): e1001273, which is published under an open-access license under the terms of the Creative Commons Attribution License.