Ex vivo JAK and TNF inhibitor-modulated immune signatures guide first-line therapy selection in rheumatoid arthritis.

BACKGROUND

Rheumatoid arthritis (RA) is a heterogeneous autoimmune disease for which selecting the most appropriate first targeted therapy remains challenging. We integrated ex vivo immune-cell functional assays, targeted proteomics, clinical outcomes, and a three-dimensional (3D) synovial model to identify treatment-associated molecular signatures and evaluate their relationship with subsequent response to Janus kinase inhibitors (JAKi) or tumour necrosis factor inhibitors (TNFi).

METHODS

Peripheral blood mononuclear cells and neutrophils from 48 b/tsDMARDs-naïve RA patients were cultured with autologous serum and treated ex vivo with Baricitinib or Etanercept to assess proliferation, adhesion, NETosis, and 92 inflammation-related proteins. The resulting JAKi- and TNFi-modulated protein signatures were subsequently evaluated in pretreatment serum from four independent RA treatment cohorts (n = 223; naïve and non-naïve). Unsupervised clustering was used to identify molecular subgroups, which were related to longitudinal DAS28-CRP outcomes at 3, 6, and 12 months. Logistic regression, neural network, and random forest models were evaluated using repeated nested cross-validation in naïve patients to discriminate treatment-specific 6-month remission outcomes. In a subset of naïve remission achievers, paired baseline and 6-month sera were applied to a 3D synovial micromass model.

RESULTS

Ex vivo JAKi and TNFi comparably modulated immune cell functions but induced distinct protein signatures with limited overlap. When evaluated in pretreatment baseline serum, these signatures stratified b/tsDMARD-naïve patients into clusters with different baseline inflammatory profiles and treatment-specific ΔDAS28-CRP. High baseline expression of a drug-specific signature was associated with remission with the corresponding therapy and failure to achieve remission with the alternative treatment. Under repeated nested cross-validation, logistic regression showed the highest mean discrimination among the models, with an AUC of 0.70 (SD, 0.03; empirical 2.5th-97.5th percentile, 0.65-0.75) for distinguishing treatment-specific remission outcomes in b/tsDMARD-naïve RA. In remission achievers, 6-month sera from either therapy significantly reduced synovial lining thickness in 3D micromasses versus baseline.

CONCLUSION

Ex vivo-derived JAKi- and TNFi-associated immune-related protein signatures, integrated within a machine-learning framework, showed moderate discriminatory ability for treatment-specific remission patterns in b/tsDMARD-naïve RA and, together with complementary evidence of reduced synovial lining thickness in remission achievers, support further investigation of biomarker-informed selection between JAKi and TNFi as first targeted therapies.