Background
Skin conditions are among the most prevalent manifestations of autoimmune diseases. While certain autoimmune diseases like pemphigus vulgaris have well established autoantibodies that bind proteins in the skin to initiate blistering, the immunopathology of many other autoimmune skin diseases is poorly understood. For example, hypocomplementemia urticarial vasculitis syndrome (HUVS) is defined by recurrent and chronic urticarial rash and immune-complex-mediated injury is a predominant mechanism however, the autoantibody specificity involved is unknown. In contrast, the autoantibodies responsible for cryoglobulinemic vasculitis are rheumatoid factors, which are among the most common autoantibodies detected in autoimmune disease. However, cryoglobulinemia is a rare manifestation in patients with rheumatoid factors and identifying patients at risk is a challenge.
Aims
The purpose of this research was to molecularly characterise autoantibodies responsible for HUVS and cryoglobulinemia and determine how the B cells that produce pathogenic autoantibodies respond to treatment.
Methods
Pathogenic B cell clones were identified in patients with HUVS and cryoglobulinemic vasculitis using massively parallel immunoglobulin sequencing combined with mass spectrometry peptide sequencing of serum autoantibody. A flow cytometry assay was developed to track B cells producing autoantibody in peripheral blood over time, before and after treatment. Single cell sequencing enabled production of recombinant monoclonal autoantibodies from patients to study function.
Results
A novel autoantibody that fixed complement was identified in patients with HUVS. Serially tracking B cells producing autoantibodies provided a more sensitive method for monitoring patient flares and response to treatment than traditional B cell quantitation in the diagnostic laboratory. Importantly, B cell clonal tracking enabled treatment of a patient prior to disease flare.
Conclusion
The ability to detect pathogenic B cell clones in patient peripheral blood represents an opportunity to measure response to treatment and potentially predict and interfere with the development of severe skin disease.