ArticleRheumatology (Oxford, England)2026
T-cell subset biomarkers across the rheumatoid arthritis disease continuum: from clinical utility to adoption in daily practice.
Article in Rheumatology (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveThe biomarker potential of CD4+ T-cell subsets [naive, regulatory (Treg), inflammation-related cells (IRC)] in patients with rheumatoid arthritis (RA) has been described.This article investigates the dynamic changes in these biomarkers across the RA disease continuum from at-risk to drug-induced remission.
methodsT-cell subset biomarker data were acquired using flow cytometry. Multiple group comparisons were performed using ANOVA test (with Bonferroni correction).
resultsIn individuals at risk of RA, longitudinal analysis showed that IRC frequencies increased just prior to onset of clinical synovitis, while naive T-cell frequencies reduced in those progressing to clinical synovitis, but increased in non-progressors. The use of naive/IRC data improved the accuracy of RA classification, especially in ACPA-negative patients. A distinct T-cell biomarker signature was observed in late-onset RA (>60 years old vs <59). In untreated RA, the predictive value of naive T-cell frequencies for methotrexate response was confirmed. For patients on methotrexate, naive T cells increased only between 6 and 12 months and only when in remission. IRC and Treg showed no consistent change. In patients treated with TNF inhibitors, naive T-cell frequency increased independently of response, whilst sustained IRC reductions and Treg increases were seen in remission. Once in stable clinical remission, only naive frequencies increased with the length of remission on conventional synthetic disease-modifying anti-rheumatic drugs (csDMARDs), whilst only Treg increased over time in TNF inhibitor-induced remission.
conclusionThese studies validated that T-cell subset measurements are independent from other currently used biomarkers, highlighting differences in the impact of drug modes of action on the three T-cell subsets. There is still an unmet need for biomarkers to predict response to TNF inhibition in early RA.
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