RESUMO
OBJECTIVE: Identify autoantibodies in anti-Ro/SS-A negative primary Sjögren's syndrome (SS). METHODS: This is a proof-of-concept, case-control study of SS, healthy (HC) and other disease (OD) controls. A discovery dataset of plasma samples (n=30 SS, n=15 HC) was tested on human proteome arrays containing 19 500 proteins. A validation dataset of plasma and stimulated parotid saliva from additional SS cases (n=46 anti-Ro+, n=50 anti-Ro-), HC (n=42) and OD (n=54) was tested on custom arrays containing 74 proteins. For each protein, the mean+3 SD of the HC value defined the positivity threshold. Differences from HC were determined by Fisher's exact test and random forest machine learning using 2/3 of the validation dataset for training and 1/3 for testing. Applicability of the results was explored in an independent rheumatology practice cohort (n=38 Ro+, n=36 Ro-, n=10 HC). Relationships among antigens were explored using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) interactome analysis. RESULTS: Ro+ SS parotid saliva contained autoantibodies binding to Ro60, Ro52, La/SS-B and muscarinic receptor 5. SS plasma contained 12 novel autoantibody specificities, 11 of which were detected in both the discovery and validation datasets. Binding to ≥1 of the novel antigens identified 54% of Ro- SS and 37% of Ro+ SS cases, with 100% specificity in both groups. Machine learning identified 30 novel specificities showing receiver operating characteristic area under the curve of 0.79 (95% CI 0.64 to 0.93) for identifying Ro- SS. Sera from Ro- cases of an independent cohort bound 17 of the non-canonical antigens. Antigenic targets in both Ro+ and Ro- SS were part of leukaemia cell, ubiquitin conjugation and antiviral defence pathways. CONCLUSION: We identified antigenic targets of the autoantibody response in SS that may be useful for identifying up to half of Ro seronegative SS cases.