Development of new automated technology for the detection and analysis of pathogenic autoantibodies in autoimmune disease — ASN Events
  1. Schedule
  2. Poster Session 1
  3. Development of new automated technology for the detection and analysis of pathogenic autoantibodies in autoimmune disease

Development of new automated technology for the detection and analysis of pathogenic autoantibodies in autoimmune disease (#219)

Betsy Barnes 1 , Di Feng 2 , Rivka Stone 3
  1. Rutgers Biomedical and Health Sciences, Newark, NJ, United States
  2. Boehringer Ingelheim, Ridgefield
  3. University of Miami, Miami

Anti-nuclear antibodies (ANA) are considered a hallmark of autoimmune rheumatic diseases.  An ANA test is routinely performed on serum from patients presenting with symptoms of autoimmune diseases such as systemic lupus erythematosus (SLE), autoimmune hepatitis, rheumatoid arthritis, polymyositis/dermatomyositis, mixed connective tissue disease, Sjögren’s syndrome, and systemic sclerosis.  The standard method for ANA detection is the indirect immunofluorescence (IIF) assay on human epithelial-2 (HEp-2) cells (ANA-HEp-2 test).  This assay is a slide-based microscopic analysis that allows for the detection of clinically relevant autoantibodies generated against cytoplasmic and nuclear antigens in patient serum.  One of the major issues with the ANA-HEp-2 test lies in the subjective evaluation of HEp-2 slides that complicates standardization and reproducibility.  We have developed a new high-throughput process of ANA testing that eliminates the subjectivity of data interpretation, and capitalizes on the properties of imaging flow cytometry to accurately localize, detect and quantify multiple autoantibodies in a single run.  The method was initially developed using anti-nuclear antibody (ANA) reference sera, prepared by the Arthritis Foundation and the Centers for Disease Control, that contains nuclear components useful in the diagnosis and classification of autoimmune diseases.  Samples were run on an Amnis Imagestream and algorithms that distinguish between individual staining patterns using masks and features provided in Amnis IDEAS® software were generated.  The method was then tested using complex sera from patients with SLE and data compared to the clinical standard ANA-HEp-2 test.  We obtained 100% replication of the standard ANA-HEp-2 assay with much greater sensitivity and detection of potentially new pathogenic autoantibodies.  The detection of such new and known autoantibodies is of significant clinical diagnostic value since it allows for not only the identification of severe autoimmune disorders but also helps to make predictions about their course and prognosis.