A small-scale preliminary study utilizing mass cytometry to distinguish two forms of arthritis.

OBJECTIVES

Spondyloarthritis (SpA) and rheumatoid arthritis (RA) are hallmarked by immune cell infiltration in synovial joints. Although, in general, different sites are affected, misclassification or delayed diagnosis due to overlapping clinical manifestations is not uncommon. Here, we investigated the diagnostic potential of mass cytometry (MC) in early peripheral SpA (pSpA) and RA patients in a small pilot study.

METHODS

Peripheral blood and synovial fluid mononuclear cells (PBMC and SFMC) of 4 pSpA, 7 RA, and 1 undifferentiated arthritis (UA) patient(s) were evaluated using a 37-marker MC panel. Data were analyzed through Visualyte services, including dimension reduction, clustering, and Cytofast workflow.

RESULTS

PBMC data indicated naive CD4 T cell, B cell, and monocyte subsets to be differentially present in RA as compared with SpA. CD4 + Tem cell and NK cell subsets appeared more prominently present in pSpA SFMC. Merged PBMC and SFMC data showed overlapping immune profiles of an UA patient with pSpA patients. These results were in accordance with the formal clinical pSpA diagnosis the UA patient received after this study.

CONCLUSIONS

Utilizing MC, several differences in immune cell composition in both SFMC and PBMC between RA and pSpA patients were observed. Combining PBMC and SFMC data in an unsupervised analysis resulted in the correct classification of the UA patient as pSpA patient prior to formal clinical pSpA diagnosis. This pilot study provides an example of how deep phenotyping with MC aids in differentiating arthritis patients and offers a rationale to further explore these findings.

KEY POINTS

•Due to overlapping symptoms and the absence of disease-specific biomarkers, the clinical diagnosis of peripheral spondyloarthritis (pSpA) and rheumatoid arthritis (RA) can be difficult. •Visualizing immune cell profiles of peripheral blood (PB) and synovial fluid (SF) by mass cytometry (MC) suggests differences in immune cell composition between pSpA and RA patients. •Based on immune profiles of combined PB and SF data, we could correctly predict the formal clinical pSpA diagnosis of an undifferentiated arthritis (UA) patient received later. •This pilot study gives an example of how MC might contribute to faster clinical diagnosis of pSpA patients in the absence of biomarkers.