Genome-wide analysis of methotrexate pharmacogenomics in rheumatoid arthritis shows multiple novel risk variants and leads for TYMS regulation.

OBJECTIVE

Methotrexate (MTX) is the drug of first choice for the treatment of rheumatoid arthritis (RA), but is effective only in around 60% of the patients. Identification of genetic markers to predict response is essential for effective treatment within a critical window period of 6 months after diagnosis, but have been hitherto elusive. In this study, we used genome-wide genotype data to identify the potential risk variants associated with MTX (poor)response in a north Indian RA cohort.

MATERIALS AND METHODS

Genome-wide genotyping data for a total of 457 RA patients [297 good (DAS28-3≤3.2) and 160 poor (DAS28-3≥5.1) responders] on MTX monotherapy were tested for association using an additive model. Support vector machine and genome-wide pathway analysis were used to identify additional risk variants and pathways. All risk loci were imputed to fine-map the association signals and identify causal variant(s) of therapeutic/diagnostic relevance.

RESULTS

Seven novel suggestive loci from genome-wide (P≤5×10(-5)) and three from support vector machine analysis were associated with MTX (poor)response. The associations of published candidate genes namely DHFR (P=0.014), FPGS (P=0.035), and TYMS (P=0.005) and purine and nucleotide metabolism pathways were reconfirmed. Imputation, followed by bioinformatic analysis indicated possible interaction between two reversely oriented overlapping genes namely ENOSF1 and TYMS at the post-transcriptional level.

CONCLUSION

In this first ever genome-wide analysis on MTX treatment response in RA patients, 10 new risk loci were identified. These preliminary findings warrant replication in independent studies. Further, TYMS expression at the post-transcriptional level seems to be probably regulated through an antisense-RNA involving the 6-bp ins/del marker in the overlapping segment at 3'UTR of TYMS-ENOSF1, a finding with impending pharmacogenetic applications.