Lymphocyte subset phenotyping for the prediction of progression to inflammatory arthritis in anti-citrullinated-peptide antibody-positive at-risk individuals.

Objectives Inflammatory arthritis (IA) is considered the last stage of a disease continuum, where features of systemic autoimmunity can appear years before clinical synovitis. Time to progression to IA varies considerably between at-risk individuals, therefore the identification of biomarkers predictive of progression is of major importance. We previously reported on the value of three CD4+T cell subsets as biomarkers of progression. Here, we aim to establish the value of 18 lymphocyte subsets (LS) for predicting progression to IA. Methods Participants were recruited based on a new musculoskeletal complaint and being positive for anti-citrullinated-peptide antibody. Progression (over 10 years) was defined as the development of clinical synovitis. LS analysis was performed for lymphocyte lineages, naive/memory subsets, inflammation-related cells (IRC) and regulatory cells (Treg/B-reg). Modelling used logistic/Cox regressions. Results Of 210 patients included, 93 (44%) progressed to IA, 41/93 (44%) within 12 months (rapid progressors). A total of 5/18 LS were associated with progression [Treg/CD4-naïve/IRC (adjusted P  < 0.0001), CD8 (P  = 0.021), B-reg (P  = 0.015)] and three trends (NK-cells/memory-B-cells/plasmablasts). Unsupervised hierarchical clustering using these eight subsets segregated three clusters of patients, one cluster being enriched [63/109(58%)] and one poor [10/45(22%)] in progressors. Combining all clinical and LS variables, forward logistic regression predicted progression with accuracy = 85.7% and AUC = 0.911, selecting smoking/rheumatoid-factor/HLA-shared-epitope/tender-joint-count-78 and Treg/CD4-naive/CD8/NK-cells/B-reg/plasmablasts. To predict rapid progression, a Cox regression was performed resulting in a model combining smoking/rheumatoid factor and IRC/CD4-naive/Treg/NK-cells/CD8+T cells (AUC = 0.794). Conclusion Overall, progression was predicted by specific LS, suggesting potential triggers for events leading to the development of IA, while rapid progression was associated with a different set of subsets. [ABSTRACT FROM AUTHOR]