Genome-wide Association Study of Methotrexate-Induced Liver Injury in Rheumatoid Arthritis Patients.

Hepatotoxicity is a serious adverse drug reaction related to methotrexate (MTX). However, the cause of drug-induced liver injury (DILI) is still unclear and unpredictable. Genetic risk factors may predispose for MTX-DILI. Therefore, we conducted a nested case-control genome-wide association study to explore genetic risk factors associated with MTX-DILI. Seven international groups contributed blood samples and data of patients with rheumatoid arthritis who used MTX. MTX-DILI was defined as an alanine aminotransferase (ALT) level of at least three times the upper limit of normal (ULN), to increase contrast controls ALT levels did not raise above two times the ULN. Per study site, control subjects and patients with MTX-DILI (ratio 3:1) were matched for age, gender, and duration of MTX use. Patients were genotyped using Illumina GSA MD-24v1-0 and data were imputed using the 1000 Genomes reference panel. Single-nucleotide polymorphisms (SNPs) were analyzed using an additive genetic model, corrected for sex, country, and age. A P-value of ≤ 5 × 10-8 was considered significant, whereas a  P-value of ≤ 5 × 10-6 was considered suggestive. A total of 108 MTX-DILI cases and 311 controls were included for association analysis. None of the SNPs were significantly associated with MTX-DILI. However, we found seven suggestive genetic variants associated with MTX-DILI (P-values 7.43 × 10-8 to 4.86 × 10-6 ). Of those, five SNPs were in the intronic protein-coding regions of FTCDNL1, BCOR, FGF14, RBMS3, and PFDN4/DOK5. Investigation of candidates SPATA9 (rs72783407), PLCG2 (rs60427389), RAVER2 (rs72675408), JAK1 (rs72675451), PTPN2 (rs2476601), MTHFR C677T (rs1801133), and into the HLA region did not show significant findings. No genetic variants associated with MTX-DILI were found, whereas suggestive SNPs need further investigation.

Predictive genetic biomarkers for the efficacy of methotrexate in rheumatoid arthritis: a systematic review.

Multiple pharmacogenetic studies investigated the effectiveness of methotrexate. However, due to the use of nonvalidated outcomes, lack of validation or conflicting results it remains unclear if genetic markers can help to predict response to MTX treatment. Therefore, a systematic review was performed. PubMed was searched for articles reporting potential pharmacogenetic biomarkers associated (p < 0.05) with MTX efficacy using the validated endpoints DAS(28), EULAR, or ACR response criteria. The PICO method was used for study selection, and PRISMA guidelines to prepare the report. Thirty-five studies met the inclusion criteria, providing 39 potential genetic biomarkers in 19 genes. After Bonferroni correction, six genetic biomarkers were associated with the efficacy of MTX: ATIC rs7563206; SLC19A1 rs1051266; DHFR rs836788; TYMS rs2244500, rs2847153, and rs3786362 in at least one study. Only SLC19A1 rs1051266 was replicated in an independent cohort and promising for predicting methotrexate efficacy.

Validation of a clinical pharmacogenetic model to predict methotrexate nonresponse in rheumatoid arthritis patients.

AIM: To study the performance of a clinical pharmacogenetic model for the prediction of nonresponse in rheumatoid arthritis (RA) patients treated with methotrexate (MTX) in combination with other synthetic or biologic disease-modifying anti-rheumatic drugs . This prediction model includes gender, smoking status, rheumatoid factor positivity and four genetic variants in AMPD1 (rs17602729), ATIC (rs2372536), ITPA (rs1127354) and MTHFD1 (rs17850560). METHODS: A total of 314 RA patients from three Dutch studies were retrospectively included. Eligible patients were adults diagnosed with RA and had a treatment duration with MTX and follow-up for at least two study evaluation visits. Prediction model risk scores at the first and second evaluation were calculated and compared with the actual nonresponse (disease activity score >2.4). Regression and receiver operating characteristic curve analyses of the prediction model were performed. Also, the sensitivity, specificity and the positive and negative predictive values (PPV and NPV) were determined. RESULTS: The receiver operating characteristic area under the curve was 75% at first and 70% after second evaluation. At the second evaluation, prediction nonresponse had a sensitivity of 67% (CI: 54-78%), specificity of 69% (CI: 60-77%), PPV of 52% (CI: 45-60%) and NPV of 80% (CI: 73-85%). CONCLUSIONS: This study demonstrates that the clinical pharmacogenetic model has an inadequate performance for the prediction of nonresponse to MTX in RA patients treated with combination therapies.

SLC04A1, SLC22A2 and SLC28A2 variants not related to methotrexate efficacy or toxicity in rheumatoid arthritis patients.

AIM: A third of rheumatoid arthritis patients discontinue methotrexate treatment due to inefficacy or toxic side effects. Recently, an association between SLC04A1 rs2236553, SLC22A2 rs624249 and rs316019, and SLC28A2 rs10519020 and rs1060896 with the efficacy and toxicity of methotrexate was reported. This study aims to replicate these findings in an independent cohort (n = 324). METHODS: Regression analyses tested the associations between genotype and methotrexate response or toxicity. RESULTS: In the discovery study, there was a significant association between toxicity and rs624249, and rs1060896. These associations were not replicated in the independent cohort. Neither study observed an association between methotrexate efficacy and SLC04A1, SLC22A2 or SLC28A2 variants. CONCLUSION: Current evidence does not support associations between variants in SLC04A1, SLC22A2 and SLC28A2 with methotrexate efficacy or toxicity.

Pathway analysis to identify genetic variants associated with efficacy of adalimumab in rheumatoid arthritis.

AIM: About 30% of rheumatoid arthritis patients have no clinical benefit from TNF inhibitors. Genome-wide association (GWA) and candidate gene studies tested several putative genetic variants for TNF inhibitor efficacy with inconclusive results. Therefore, this study applied a systematic pathway analysis. PATIENTS & METHODS: A total of 325 rheumatoid arthritis patients treated with adalimumab were genotyped for 223 SNPs. We tested the association between SNPs and European League Against Rheumatism response and remission at 14 weeks under the additive genetic model using logistic regression. RESULTS: A total of 3 SNPs located in CD40LG (rs1126535), TANK (rs1267067) and VEGFA (rs25648) showed association with both end points. TNFAIP3 (rs2230926) had the strongest effect related to European League Against Rheumatism response. CONCLUSION: This exploratory study suggests that TNFAIP3, CD40LG, TANK and VEGFA play a role in the response to adalimumab treatment.