Novel autoantibodies help diagnose anti-SSA antibody negative Sjögren disease and predict abnormal labial salivary gland pathology

Objectives: Sjögren disease (SjD) diagnosis often requires either positive anti-SSA antibodies or a labial salivary gland biopsy with a positive focus score (FS). One-third of patients with SjD lack anti-SSA antibodies (SSA-), requiring a positive FS for diagnosis. Our objective was to identify novel autoantibodies to diagnose 'seronegative' SjD.

Methods: IgG binding to a high-density whole human peptidome array was quantified using sera from SSA- SjD cases and matched non-autoimmune controls. We identified the highest bound peptides using empirical Bayesian statistical filters, which we confirmed in an independent cohort comprising SSA- SjD (n=76), sicca-controls without autoimmunity (n=75) and autoimmune-feature controls (SjD features but not meeting SjD criteria; n=41). In this external validation, we used non-parametric methods for binding abundance and controlled false discovery rate in group comparisons. For predictive modelling, we used logistic regression, model selection methods and cross-validation to identify clinical and peptide variables that predict SSA- SjD and FS positivity.

Results: IgG against a peptide from D-aminoacyl-tRNA deacylase (DTD2) bound more in SSA- SjD than sicca-controls (p=0.004) and combined controls (sicca-controls and autoimmune-feature controls combined; p=0.003). IgG against peptides from retroelement silencing factor-1 and DTD2 were bound more in FS-positive than FS-negative participants (p=0.010; p=0.012). A predictive model incorporating clinical variables showed good discrimination between SjD versus control (area under the curve (AUC) 74%) and between FS-positive versus FS-negative (AUC 72%).

Conclusion: We present novel autoantibodies in SSA- SjD that have good predictive value for SSA- SjD and FS positivity.