Autoantibodies identify primary Sjögren's syndrome in patients lacking serum IgG specific for Ro/SS-A and La/SS-B

Abstract

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.

Keywords: Sjogren's syndrome; autoantibodies; autoimmune diseases.

Figure 1. Binding of novel and canonical antigens by plasma Ig of anti-Ro positive and anti-Ro negative cases from the discovery dataset.

Heatmap indicates specificities with normalized intensity values above the positive threshold (mean+3SD of HC values, green), identified in significant number of cases (≥4 cases/group, p<0.1, Fisher’s exact test, gene symbols used to refer to protein products).

Figure 2. (A-B) Binding of novel and canonical antigens by plasma and saliva Ig of anti-Ro positive and anti-Ro negative cases of validation dataset.

(A) Plasma, (B) Stimulated parotid saliva. Green indicates specificities with normalized intensity values above the positive threshold (mean+3SD) of HC values. Gray indicates saliva samples not available or excluded due to high background. In each figure, upper panels indicate specificities significantly bound by SS cases, lower panels indicate specificities significantly bound by OD controls only (p<0.1, Fisher’s exact test, gene symbols used to refer to protein products).

Figure 3. Capillary western blot of plasma IgG binding SOX5, FUT8, and GMNN.

Binding of patient IgG antibodies to select proteins (yeast expressed, CDI). Commercial monoclonal (SOX5) or polyclonal (FUT8, GMNN) antibodies were used as positive controls (PC). Capillaries were loaded with 0.2µg/mL (SOX5) or 10µg/mL (FUT8, GMNN) protein solutions. Subject IDs and plasma dilutions listed at the top of each panel. HC=healthy control. Gene symbols used to refer to protein products.

Figure 4. (A-B) Receiver Operating Curves including (A) and excluding (B) canonical Ro and La autoantigen proteome array binding data.

Machine learning predicted specificities that distinguished the Ro^– SS case group from the Ro⁺ SS case group, Healthy controls (HC) , and Other Disease (OD) controls. Areas under the curve (AUC) and 95% confidence intervals are shown.

Figure 5. Binding of novel and canonical antigens by plasma Ig of anti-Ro positive and anti-Ro negative cases from an independent rheumatology practice cohort.

Heatmap indicates specificities with normalized intensity values above the positive threshold (mean+3SD of HC values, green).

Figure 6. (A-C) Clinical correlations with non-canonical antibody specificities.

SS validation cohort patients with plasma Ig binding to at least 1 of 30 antigens identified by machine learning (see Fig 4B and SI Table 6B) exhibit increased serum IgM levels which were found to be elevated in Ro^– patients (A), but not in Ro⁺ patients (B). Ro⁺ SS patients with Ig binding to MR5 exhibited more severe SS by multiple measures (C). (Mann-Whitney or Fisher’s exact tests, p<0.05).