Abraham, Y. | Search bioRxiv

bioRxiv2026

Persistent circulating autoreactive PD1⁺TIGIT⁺ peripheral helper T cells reflect synovial lymphoid activity and poor response to conventional disease-modifying anti-rheumatic drugs in early rheumatoid arthritis

ObjectiveIn the first year after onset of the autoimmune disease RA (RA), 40-60% do not achieve remission on conventional synthetic disease-modifying anti-rheumatic drugs (csDMARDs). To understand how autoreactive T cells may contribute to unstable or non-remission, we studied CD4+ T cells, including those recognising citrullinated (Cit) vimentin in participants with RA. MethodsTwo cohorts of drug-naive new-onset participants with RA were treated with csDMARDs. Disease activity score (DAS28-CRP) and peripheral blood (PB) mononuclear cells were collected longitudinally. In HLA-DR-shared epitope+ cohort 1 (n=21), T cells were assessed with a 17-marker spectral flow panel, incorporating HLA-DRB1*04:01/01:01- VimentinCit6459-71 or HLA-DRB1*04:04-VimentinCit7166-78 tetramers. Changes in T cell subsets over time were assessed in remitting and non-remitting participants using a generalized linear mixed model with a negative binomial distribution. In cohort 2 (n=26), the transcriptome of disaggregated synovial tissue (ST) and PB CD4+ T cells were analysed at baseline, and ST biopsy spatial proteomics at baseline and 6 months. ResultsCD4CXCR5-PD1+ peripheral helper T cells (Tph), including Cit-vimentin-reactive Tph, CD4CCR7+CXCR5-PD1+ stem-like Tph and TIGIT+PD1+ Tph were increased with moderate/high DAS28-CRP at any time point. Remission outcome was associated with low CD4 follicular helper T cell (Tfh) and Cit-vimentin-reactive Tfh. In non-remitting participants, Tph/fh infiltrated germinal-centre-like ST aggregates. This decreased in remission. Circulating TIGIT+ Tph genes reflected B lymphoid activation and lymph node egress, while in ST they reflected local differentiation. ConclusionPersistently high circulating TIGIT+ Tph and Tfh, including Cit-vimentin specificities, reflecting antigen-presenting B-cell interactions, are associated with reduced response to csDMARDs in recent-onset RA. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LITph and Tfh cells interacting with B cells are implicated in active ACPA+ RA C_LIO_LICitrullinated (Cit)-vimentin is an important neutrophil extracellular trap-derived target of ACPA C_LI What this study addsO_LIHigh circulating TIGIT+ Tph, Cit-vimentin-autoreactive Tph and Tfh associate with failure to reach remission on conventional synthetic DMARDs within the first year in early HLA-DR shared-epitope+ RA C_LIO_LITph/Tfh and adjacent regulatory T cells surround follicular B-cells in lymphoid aggregates in synovial tissue in non-remission C_LIO_LICirculating TIGIT+ Tph bear a transcriptional signature of lymphoid tissue expansion and lymph node egress as compared to functional differentiation and antigen experience in synovial tissue C_LI How this study might affect research, practice or policyO_LIWhen a remission target is not achieved in HLA-DR shared-epitope+ RA patients during the first year of treatment, high circulating TIGIT+ Tph implicate autoreactive T-B-lymphoid expansion in synovial tissue. C_LI

immunology↗

bioRxiv2026

TwinCell: Large Causal Cell Model for Reliable and Interpretable Therapeutic Target Prioritisation

Drug discovery is impeded by the difficulty of translating targets from preclinical models to patients. In this work, we present TwinCell, a Large Causal Cell Model for target identification that, trained on in vitro cancer cell line perturbation data, generalises to patient-derived cell types while providing biologically meaningful interpretations of its predictions. Rather than predicting perturbation outcomes, TwinCell identifies the upstream regulators most likely to drive the transition between two cell states, such as diseased and healthy, by decomposing target probability over signalling paths through a multiomics interactome conditioned on single-cell foundation model embeddings. To validate this approach, we introduce TwinBench, a benchmarking framework that evaluates virtual cell models using recommendation system metrics while correcting for mode collapse through empirical p-value estimation. On both in vitro zero-shot scenarios and in clinico validation across five therapeutic areas, TwinCell outperforms not only state-of-the-art virtual cell models but also linear baselines and network-based methods, classically used to perform target identification. When applied to patient data, TwinCell recovers clinically approved drug targets and reconstructs known disease mechanisms, such as the type I interferon signalling cascade in Systemic Lupus Erythematosus, without any disease-specific supervision. These results demonstrate that constraining learned perturbation patterns to a biological interactome enables cross-tissue, cross-disease target identification with mechanistic interpretability, bridging the gap between high-throughput in vitro experiments and clinical insights.

systems biology↗