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Profiling of Gene Expression Biomarkers as a Classifier of Methotrexate Nonresponse in Patients With Rheumatoid
Darren Plant1, Mateusz Maciejewski2, Samantha Smith3
1Manchester University NHS Foundation Trust, Manchester, UK.
Objective:
Approximately 30-40% of rheumatoid arthritis (RA) patients who are initially started on low-dose methotrexate (MTX) will not benefit from the treatment. To date, no reliable biomarkers of MTX inefficacy in RA have been identified. The aim of this study was to analyze whole blood samples from RA patients at 2 time points (pretreatment and 4 weeks following initiation of MTX), to identify gene expression biomarkers of the MTX response.
Methods:
RA patients who were about to commence treatment with MTX were selected from the Rheumatoid Arthritis Medication Study. Using European League Against Rheumatism (EULAR) response criteria, 42 patients were categorized as good responders and 43 as nonresponders at 6 months following the initation of MTX treatment. Data on whole blood transcript expression were generated, and supervised machine learning methods were used to predict a EULAR nonresponse. Models in which transcript levels were included were compared to models in which clinical covariates alone (e.g., baseline disease activity, sex) were included. Gene network and ontology analysis was also performed.
Results:
Based on the ratio of transcript values (i.e., the difference in log2 -transformed expression values between 4 weeks of treatment and pretreatment), a highly predictive classifier of MTX nonresponse was developed using L2-regularized logistic regression (mean ± SEM area under the receiver operating characteristic [ROC] curve [AUC] 0.78 ± 0.11). This classifier was superior to models that included clinical covariates (ROC AUC 0.63 ± 0.06). Pathway analysis of gene networks revealed significant overrepresentation of type I interferon signaling pathway genes in nonresponders at pretreatment (P = 2.8 × 10-25 ) and at 4 weeks after treatment initiation (P = 4.9 × 10-28 ).
Conclusion:
Testing for changes in gene expression between pretreatment and 4 weeks post-treatment initiation may provide an early classifier of the MTX treatment response in RA patients who are unlikely to benefit from MTX over 6 months. Such patients should, therefore, have their treatment escalated more rapidly, which would thus potentially impact treatment pathways. These findings emphasize the importance of a role for early treatment biomarker monitoring in RA patients started on MTX.
Insights
Early gene expression changes in rheumatoid arthritis (RA) patients predict methotrexate (MTX) nonresponse, enabling faster treatment adjustments. This discovery offers a new biomarker for MTX efficacy in RA.
Area of Science:
- Genomics and Bioinformatics
- Rheumatology and Immunology
Background:
- A significant portion of rheumatoid arthritis (RA) patients do not respond to initial low-dose methotrexate (MTX) therapy.
- Currently, reliable biomarkers to predict MTX inefficacy in RA are lacking.
Purpose of the Study:
- To identify gene expression biomarkers in whole blood that predict MTX response in RA patients.
- To analyze gene expression at pretreatment and 4 weeks post-MTX initiation.
Main Methods:
- Whole blood transcript expression data were analyzed from RA patients categorized by EULAR response criteria.
- Supervised machine learning, specifically L2-regularized logistic regression, was employed to predict MTX nonresponse.
- Gene network and ontology analysis were performed to identify biological pathways associated with treatment response.
Main Results:
- A gene expression-based classifier achieved a high predictive accuracy (ROC AUC 0.78 ± 0.11) for MTX nonresponse, outperforming clinical covariates alone (ROC AUC 0.63 ± 0.06).
- Significant overrepresentation of type I interferon signaling pathway genes was observed in nonresponders.
- This predictive classifier was based on the ratio of transcript values at 4 weeks versus pretreatment.
Conclusions:
- Changes in gene expression between pretreatment and 4 weeks post-MTX initiation can serve as an early classifier for MTX treatment response in RA.
- Early identification of nonresponders can facilitate more rapid treatment escalation, potentially improving patient outcomes.
- These findings highlight the importance of early biomarker monitoring for RA patients commencing MTX therapy.
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