ArticleArthritis & rheumatology (Hoboken, N.J.)2019
Profiling of Gene Expression Biomarkers as a Classifier of Methotrexate Nonresponse in Patients With Rheumatoid Arthritis.
Article in Arthritis & rheumatology (Hoboken, N.J.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
- Artificial intelligence in immunotherapy: revolutionizing diagnostic and therapeutic applications in cancer and autoimmune diseases.Clinical and experimental medicine · 2026Review
- [Interferon scores in the management of rheumatic systemic diseases].Zeitschrift fur Rheumatologie · 2026Review
- Predictive biomarkers for precision treatment in rheumatoid arthritis: are we there yet?Frontiers in pharmacology · 2026Review
- Identifying Predictive Biomarkers of Response in Patients With Rheumatoid Arthritis Treated With Adalimumab Using Machine Learning Analysis of Whole-Blood Transcriptomics Data.Arthritis & rheumatology (Hoboken, N.J.) · 2025Article
- Artificial intelligence to predict treatment response in rheumatoid arthritis and spondyloarthritis: a scoping review.Rheumatology international · 2025Article
- Rheumatoid Factor: Diagnostic and Prognostic Performance and Therapeutic Implications in Rheumatoid Arthritis.Journal of clinical medicine · 2025Review
- Application of artificial intelligence in rheumatic disease: a bibliometric analysis.Clinical and experimental medicine · 2024Article
- Elevated Serum Levels of YKL-40, YKL-39, and SI-CLP in Patients with Treatment Failure to DMARDs in Patients with Rheumatoid Arthritis.Biomedicines · 2024Article
- Role of IFN-α in Rheumatoid Arthritis.Current rheumatology reports · 2024Review
- Advancing precision rheumatology: applications of machine learning for rheumatoid arthritis management.Frontiers in immunology · 2024Review
- Artificial intelligence for predicting treatment responses in autoimmune rheumatic diseases: advancements, challenges, and future perspectives.Frontiers in immunology · 2024Review
- Towards Personalized Medicine in Rheumatoid Arthritis.Open access rheumatology : research and reviews · 2024Review
- Differences in IDO1Frontiers in immunology · 2024Article
- Molecular signature of methotrexate response among rheumatoid arthritis patients.Frontiers in medicine · 2023Article
- Diagnosing growing pains in children by using machine learning: a cross-sectional multicenter study.Medical & biological engineering & computing · 2022Article
- Pre-defined gene co-expression modules in rheumatoid arthritis transition towards molecular health following anti-TNF therapy.Rheumatology (Oxford, England) · 2022Article
- Artificial Intelligence in Rheumatoid Arthritis: Current Status and Future Perspectives: A State-of-the-Art Review.Rheumatology and therapy · 2022Review
- Interferon-α-mediated therapeutic resistance in early rheumatoid arthritis implicates epigenetic reprogramming.Annals of the rheumatic diseases · 2022Article
- Does persistence to methotrexate treatment in early rheumatoid arthritis have a familial component?Arthritis research & therapy · 2022Article
- Gene Expression Profiles of Treatment Response and Non-Response in Children With Juvenile Dermatomyositis.ACR open rheumatology · 2022Article
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Authors and funding
9 authors.
Funding
Abstract
objectiveApproximately 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.
methodsRA 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.
resultsBased on the ratio of transcript values (i.e., the difference in log
conclusionTesting 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.
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