Genetic predictors of response to methotrexate in patients with rheumatoid arthritis

Abstract

Abstract The University of Manchester, Sally-Anne Owen, PhD, Genetic predictors of response to methotrexate in patients with rheumatoid arthritis, 2012.Background: Methotrexate (MTX) is the cornerstone of treatment for inflammatory arthritis. However inadequate response occurs in approximately 30% of patients treated. The main determinants of MTX response in rheumatoid arthritis (RA) remain unclear although evidence suggests that part of this variability is genetic. Aim: The aim of this thesis was to identify genetic predictors of MTX response, first by validating previously published pharmacogenetic indices, second, by testing novel single nucleotide polymorphisms (SNPs) in genes encoding enzymes important in the metabolism of MTX, third by testing SNPs previously confirmed to be associated with RA susceptibility and finally by incorporating meta-analytic techniques to test associations in genes where previous research findings were controversial. A new study was also established to explore genetic predictors of MTX induced pneumonitis.Method: Subjects included a retrospectively collected cohort of 309 RA patients with response to MTX defined as (i) good responders (n=147) (ii) inefficacy failures (n=101) and (iii) adverse event (AE) failures (n=61). Genes and polymorphisms were chosen based on previous reports from the literature; pharmacogenetic indices: (ATIC, RFC, TYMS, AMPD1 MTHFR & SHMT1 and 5 SNPs), importance in the MTX metabolic pathway (AMPD1, ATIC, DHFR, FPGS, GGH, ITPA, MTHFD1, SHMT1, SLC19A1/RFC, TYMS, MTHFR and 138 SNPs) and those previously associated with RA susceptibility in cohorts tested by our group and others (35 genes and 52 SNPs). The meta-analysis was performed on two key variants (677C/T and 1298A/C) located in the MTHFR gene. A tagging SNP approach was adopted to ensure maximum gene coverage and interesting findings were investigated further using bioinformatics analysis to identify the most plausible functional candidate. Result: The pharmacogenetic indices did not validate in our UK patient cohort. In the MTX metabolic pathway, 16 associations in 5 genes were detected with either efficacy or AEs (p-trend smaller or equal to 0.05). From these data, SNPs in the ATIC (rs12995526), SLC19A1/RFC (rs11702425) and GGH (rs12681874) genes showed possible independent association with efficacy. Furthermore, three effects in the DHFR gene (rs12517451, rs10072026 & rs12517451) and one independent effect in the FPGS (rs1054774) gene were associated with AEs. Interpretation of data retrieved from bioinformatics databases prioritised 1 SNP in the ATIC gene (rs12995526), 3 SNPs in the SLC19A1/RFC gene region, (rs117002425, rs7499 & rs12482346) and a single SNP in the DHFR gene (rs1650697). Investigation of 52 SNPs within 35 RA disease susceptibility loci revealed 5 gene regions and 6 SNPs that were associated with either MTX efficacy (PRKCQ: rs4750316I, PTPN2: rs7234029) or AEs (REL: rs13031237/rs13017599, CCR6: rs2301436, IL2RA: rs2104286) and combinational analysis showed an association with an increased genetic risk score for carriage of RA susceptibility alleles and MTX inefficacy (OR= 1.40 (95% CI 1.06 - 1.86) p=0.01). Results from the meta-analysis suggested that the MTHFR 677C/T and 1298A/C gene polymorphisms are not reliable predictors of response to MTX. The pneumonitis study has enrolled 24 sites, 8 currently recruiting patients, with 16 sites currently undergoing governance reviews or reviewing the protocol.Conclusion: The results suggest that genetic variations in several genes may influence response to MTX in RA patients. Further studies will be required to validate these findings and if confirmed these results could contribute towards a better understanding of and ability to predict MTX response in RA.

Date of Award	1 Aug 2013
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Wendy Thomson (Supervisor) & Anne Barton (Supervisor)