ArticleArthritis & rheumatology (Hoboken, N.J.)2015
Modular analysis of peripheral blood gene expression in rheumatoid arthritis captures reproducible gene expression changes in tumor necrosis factor responders.
Article in Arthritis & rheumatology (Hoboken, N.J.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Molecular profiling of rheumatoid arthritis patients reveals an association between innate and adaptive cell populations and response to anti-tumor necrosis factor.Arthritis research & therapy · 2019Trial
- 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
- Single-cell RNA sequencing of circulating immune cells supports inhibition ofFrontiers in immunology · 2025Article
- Article
- An ElevatedCurrent issues in molecular biology · 2024Article
- Towards Personalized Medicine in Rheumatoid Arthritis.Open access rheumatology : research and reviews · 2024Review
- Peripheral blood cellular dynamics of rheumatoid arthritis treatment informs about efficacy of response to disease modifying drugs.Scientific reports · 2023Article
- Profiling the peripheral immune response to ex vivo TNF stimulation in untreated juvenile idiopathic arthritis using single cell RNA sequencing.Pediatric rheumatology online journal · 2023Article
- Pre-defined gene co-expression modules in rheumatoid arthritis transition towards molecular health following anti-TNF therapy.Rheumatology (Oxford, England) · 2022Article
- -Omic Approaches and Treatment Response in Rheumatoid Arthritis.Pharmaceutics · 2022Review
- Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data.Nature communications · 2021Article
- Potential clinical biomarkers in rheumatoid arthritis with an omic approach.Auto- immunity highlights · 2021Review
- Bayesian approach for predicting responses to therapy from high-dimensional time-course gene expression profiles.BMC bioinformatics · 2021Article
- Comparative Analysis on Abnormal Methylome of Differentially Expressed Genes and Disease Pathways in the Immune Cells of RA and SLE.Frontiers in immunology · 2021Article
- Toward Overcoming Treatment Failure in Rheumatoid Arthritis.Frontiers in immunology · 2021Review
- MultiPLIER: A Transfer Learning Framework for Transcriptomics Reveals Systemic Features of Rare Disease.Cell systems · 2019Article
- Multi-omics monitoring of drug response in rheumatoid arthritis in pursuit of molecular remission.Nature communications · 2018Article
- The mechanistic implications of gene expression studies in SSc: Insights from Systems Biology.Current treatment options in rheumatology · 2017Article
- Transcriptional profiling of leukocytes from rheumatoid arthritis patients before and after anti-tumor necrosis factor therapy: A comparison of anti-nuclear antibody positive and negative subsets.Experimental and therapeutic medicine · 2017Article
- Increased pretreatment serum IFN-β/α ratio predicts non-response to tumour necrosis factor α inhibition in rheumatoid arthritis.Annals of the rheumatic diseases · 2016Article
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Funding
Abstract
objectiveTo establish whether the analysis of whole-blood gene expression is useful in predicting or monitoring response to anti-tumor necrosis factor (anti-TNF) therapy in patients with rheumatoid arthritis (RA).
methodsWhole-blood RNA (using a PAXgene system to stabilize whole-blood RNA in the collection tube) was obtained at baseline and at 14 weeks from 3 independent cohorts, consisting of a combined total of 240 RA patients who were beginning therapy with anti-TNF. We used an approach to gene expression analysis that is based on modular patterns of gene expression, or modules.
resultsGood and moderate responders according to the European League Against Rheumatism criteria exhibited highly significant and consistent changes in multiple gene expression modules after 14 weeks of therapy, as demonstrated by hypergeometric analysis. Strikingly, nonresponders exhibited very little change in any modules, despite exposure to TNF blockade. These patterns of change were highly consistent across all 3 cohorts, indicating that immunologic changes after TNF treatment are specific to the combination of both drug exposure and responder status. In contrast, modular patterns of gene expression did not exhibit consistent differences between responders and nonresponders at baseline in the 3 study cohorts.
conclusionThese data provide evidence that using gene expression modules related to inflammatory disease may provide a valuable method for objective monitoring of the response of RA patients who are treated with TNF inhibitors.
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