Predicting treatment response to methotrexate: are we closer to solving the enigma?

This editorial refers to ‘Genome-wide investigaiton of persistence of treatment with methotrexate in early rheumatoid arthritis’, by Öberg Sysoev et al., 2024;63:1221–29.

Methotrexate (MTX) is the most common initial DMARD for RA. Up to 60% of patients respond inadequately to MTX, requiring therapy intensification and/or discontinuation of MTX within 3–5 years due to side effects, while lack of success with the first DMARD associates with poor long-term outcomes [1]. Previous studies implicating RA susceptibility genes as well as genes from folate and adenosine metabolic pathways with response to MTX have been inconsistent and did not replicate well in independent cohorts. Early identification of patients who will succeed on MTX treatment is an unmet need.

In this issue of the journal, Öberg Sysoev et al. present results of one of the largest genome-wide association studies (GWAS) thus far on persistence to treatment with MTX, leveraging genetic data of 3268 patients with a new diagnosis of RA on MTX monotherapy included in the Epidemiological Investigation of RA (EIRA) or the Swedish Rheumatology Quality Register’s (SRQ) biobank [2]. The authors evaluated whether a polygenic risk score consisting of single nucleotide polymorphisms (SNPs) associated with the risk of RA can predict persistence with MTX, adjusting for age, sex and genetic ancestry. They also evaluated SNP-based heritability of MTX treatment persistence. The outcome of persistence with MTX was chosen as a proxy to both treatment response and medication tolerance, with estimated 65% and 44% persistence at 1 year and 3 years, respectively, concordant with existing literature [1].

Despite the large dataset and a homogeneous population, there were no genome-wide significant associations (at threshold of P < 5 × 10⁻⁸) and no significant polygenic component for MTX persistence at the prespecified time points (i.e. 1 and 3 years). Notably, the authors report lower MTX persistence in individuals with greater genetic predisposition towards RA: adjusted heritability h² of 0.46 (95% CI 0.15, 0.78) at 1 year. These associations were more prominent in patients who were ACPA positive and/or RF positive, and attenuated toward the null in patients who were negative for ACPA and RF. This may reflect the more aggressive course of seropositive RA, with the need for escalation of immunosuppression beyond MTX monotherapy. This observation also aligns with knowledge of distinct genetics of seropositive and seronegative RA and is consistent with findings of an association between shared epitope alleles and response to MTX monotherapy replicated in several populations worldwide, while positivity for shared epitope alleles associates strongly with ACPA-positive RA [3, 4].

The overall lack of genome-wide significant associations in this study echoes similar previous studies on the genomics of MTX response, including the second largest GWAS of 1424 patients with RA [5], and highlights the overall challenge of identifying biomarkers of treatment response for RA as a polygenic and highly heterogeneous disease. The lack of clinically useful biomarkers for prediction of response to MTX following decades of research in this area is disheartening.

Emerging approaches for improved prediction of MTX treatment response include multi-omics, as well as evaluating biomarker dynamics (e.g. changes in peripheral blood T cell populations, molecular profile, cell-specific DNA methylation) that occur soon after the medication exposure and can vary from person to person [6, 7]. Longitudinal monitoring of drug response at multi-omics level using peripheral blood of persons with RA suggests that biologics normalize molecular profiles more efficiently than MTX at transcriptome, protein and cell level, and there are molecular signatures resistant to treatment with MTX and biologics [8]. Leveraging the growing knowledge of the pathogenesis of RA, i.e. identifying synovial pathotypes, specific synovial tissue biomarkers and related gene interaction networks, is very promising for identifying patient subsets with differential treatment responses and connecting the knowledge of treatment response based on peripheral blood biomarkers and synovial biomarkers [9]. Biomarker predictions can be further improved by adding comprehensive clinical phenotype data and controlling for important clinical confounders. Finally, machine learning has been increasingly used to dissect the heterogeneity of treatment response and has shown promise in prediction of MTX response in RA when combining clinical and genomic data [10].

Aside from the biologic factors affecting MTX response, several clinical practice issues can influence tolerance and effectiveness and may convolute the prediction of MTX persistence, i.e. dosing, rate of dose escalation, administration route and supplementation with folic acid. Could MTX persistence be improved if the dose was maximized to 25 mg/week, using the subcutaneous route for improved bioavailability, and consistently supplementing with folic acid to reduce the adverse effects? Nearly 70% of patients in the study by Öberg Sysoev et al. used oral MTX and only 67% had folic acid supplementation. These numbers possibly reflect the wide study time frame (1996–2020), during which rheumatology practice has changed dramatically. Indeed, before the 2000s MTX was essentially the only option, which may have affected patients’ and doctors’ decisions to stay on the medication. Similarly, MTX dosing for RA has changed over time with lower doses used in the earlier years vs recent years. Practice in use of folic acid also varied.

Studies from the USA showed underutilization and underdosing of MTX even in the late 2000s, with only 37% of patients receiving MTX ≥15 mg/week at the time of adding or switching to a biologic, and only 13% of patients switching from oral to subcutaneous MTX [11]. The impact of suboptimal utilization on the lack of MTX persistence can be difficult to discern from a retrospective study. Öberg Sysoev et al. report that 87% of patients had a non-MTX DMARD added and 35% discontinued MTX in the first year of use, suggesting non-response was the primary reason for non-persistence. However, a third of discontinuations in the SQR cohort were due to side effects, while the rest were essentially unknown and not necessarily genetically explained (e.g. non-adherence), possibly reducing the chance for significant genetic associations in the study.

In summary, despite a growing body of research, there are currently no clinically useful validated prediction models that allow early identification of MTX efficacy and safety in an individual patient. It is becoming clear that genetic biomarkers alone may not be the ideal solution and the use of alternative biomarkers, e.g. synovial tissue biomarkers or a combination of both peripheral biomarkers and tissue biomarkers, capturing the dynamic changes in the ‘omics’ profile with treatment, may help optimize prediction of response to MTX, ideally yielding a replicable, cost-effective and feasible model. Without a doubt, optimizing medication adherence and administration regimen are keys to successful treatment response and should be prioritized for each patient.

Data availability

No new data were analysed or generated in support of this article.

Funding

The author is supported by grants from the National Institutes of Health, NIA (R01 AG068192, K24 AG078179). The content is solely the responsibility of the author and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in the study design; collection, analysis, or interpretation of data; or writing or submitting of the manuscript.

Disclosure statement: The author has declared no conflicts of interest.