No abstract

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.

Current evidence does not support associations between variants in SLC04A1, SLC22A2 and SLC28A2 with methotrexate efficacy or toxicity.

This exploratory study suggests that TNFAIP3, CD40LG, TANK and VEGFA play a role in the response to adalimumab treatment.

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.