Synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (PEAC)

Abstract

ObjectiveTo establish whether synovial pathobiology improves current clinical classification and prognostic algorithms in early inflammatory arthritis and identify predictors of subsequent biological therapy requirement.Methods200 treatment-naïve patients with early arthritis were classified as fulfilling RA1987 American College of Rheumatology (ACR) criteria (RA1987) or as undifferentiated arthritis (UA) and patients with UA further classified into those fulfilling RA2010 ACR/European League Against Rheumatism (EULAR) criteria. Treatment requirements at 12 months (Conventional Synthetic Disease Modifying Antirheumatic Drugs (csDMARDs) vs biologics vs no-csDMARDs treatment) were determined. Synovial tissue was retrieved by minimally invasive, ultrasound-guided biopsy and underwent processing for immunohistochemical (IHC) and molecular characterisation. Samples were analysed for macrophage, plasma-cell and B-cells and T-cells markers, pathotype classification (lympho-myeloid, diffuse-myeloid or pauci-immune) by IHC and gene expression profiling by Nanostring.Results128/200 patients were classified as RA1987, 25 as RA2010 and 47 as UA. Patients classified as RA1987 criteria had significantly higher levels of disease activity, histological synovitis, degree of immune cell infiltration and differential upregulation of genes involved in B and T cell activation/function compared with RA2010 or UA, which shared similar clinical and pathobiological features. At 12-month follow-up, a significantly higher proportion of patients classified as lympho-myeloid pathotype required biological therapy. Performance of a clinical prediction model for biological therapy requirement was improved by the integration of synovial pathobiological markers from 78.8% to 89%–90%.ConclusionThe capacity to refine early clinical classification criteria through synovial pathobiological markers offers the potential to predict disease outcome and stratify therapeutic intervention to patients most in need.

A Review of the Prevalence and Unmet Needs in the Management of Rheumatoid Arthritis in Africa and the Middle East

“…Multiple attempts have been made to establish RA patient registries in Saudi Arabia, the most recent being the Rheumatoid Arthritis Saudi Database (RASD), from which data are beginning to emerge [ 35 , 36 ]. Where available, registries such as the Kuwait Registry for Rheumatic Diseases [KRRD] and the Dubai Private Database, facilitate our understanding of patient characteristics, such as the mean age at diagnosis (49 years), prevalence of family history of rheumatic autoimmune disease (13%), the women:men ratio (3:1) [ 37 ], and main reasons for discontinuation of biologics (loss of efficacy and patient choice) [ 38 ].…”

Paired Rheumatoid Arthritis Synovial Biopsies From Small and Large Joints Show Similar Global Transcriptomic Patterns With Enrichment of Private Specificity TCRB and TCR Signaling Pathways

“…Several studies were performed in order to understand the mechanisms driving heterogeneity in histological, cellular and molecular changes in rheumatoid synovitis and investigate whether synovial cellular and molecular patterns can be linked to clinical outcomes (5)(6)(7)(8)(9)(10)(11). Thus, clinical variables such as disease activity, disease duration, ACPA status or response to specific therapies were associated with variations in cellular populations and molecular profiles in RA synovial biopsies (12).…”

“…In addition to the effects of extrinsic factors, evidence also indicates that intrinsic variations in synovial architecture determine the organization of RA synovitis. Synovial pathotypes (lympho-myeloid, myeloid or pauciimmune) were defined based on the relative enrichment of cell populations and gene expression profiles (9,10). The stability of these pathotypes over time, and whether they reflect the presence of distinct endotypes (i.e.…”

Insights Into Leukocyte Trafficking in Inflammatory Arthritis – Imaging the Joint

“…The era of precision medicine for inflammatory arthritis is fast approaching (reviewed by Aletaha, 2020 ; Miyagawa and Tanaka, 2020 ) with “big data” providing insights into different patient populations and further subgrouping patients according to their underlying process driven pathology – yet imaging remains crucial for initial discoveries and confirming outputs of omics analysis (e.g., Lewis et al, 2019 ). Indeed, the use of synovial tissue signatures improves the prediction that a patient will require biological therapy 12 months after diagnosis ( Lliso-Ribera et al, 2019 ). Furthermore, advances in spatial transcriptomics now enables mapping of gene expression profiles onto images of tissues, providing for the first-time spatial context to gene expression data ( Burgess, 2019 ).…”