title: Analysis of the IgG autoantibody repertoire in endocrine ophthalmopathy using the MegaBlot technique.
abstract: OBJECTIVE
  Normal sera contain a large number of naturally-occurring autoantibodies which can complicate the differentiation of disease-associated autoantibodies from the complex background of "autoimmune noise" (i.e. naturally-occurring autoantibodies). The aim of this study was to analyze the human IgG autoantibody repertoire of sera from patients suffering from endocrine ophthalmopathy and to compare those to sera from healthy subjects using the recently developed MegaBlot technique. This new method allows the simultaneous global and quantitative screening for reactivities of antibodies with a large number of antigens.
  
  
  METHODS
  Sera (n = 17: endocrine ophthalmopathy; n = 10: healthy subjects) were tested against Western blots of SDS-PAGE preparations of proteins from human extraorbital eye muscle. Digital image analysis was performed (ScanPacK, Biometra, Germany). The blots were subsequently analyzed by our new MegaBlot technique.
  
  
  RESULTS
  Both the sera of patients suffering from endocrine ophthalmopathy and the sera of healthy subjects revealed reactivities of antibodies against eye muscle proteins (up to 15 bands/blot). The MegaBlot procedure could differentiate between the banding patterns of patients suffering from endocrine ophthalmopathy and healthy subjects. The staining patterns of both groups were significantly different (p < 0.02). A 64 kDa protein was recognized by autoantibodies in the sera of both healthy subjects and patients suffering from endocrine ophthalmopathy.
  
  
  CONCLUSIONS
  This study shows that naturally-occurring antibodies in sera of healthy subjects recognize many antigenic proteins, but despite that, the MegaBlot technique can differentiate between the complex staining patterns of both groups. Our new method can be a valuable tool in the evaluation of autoantibody repertoires in autoimmune diseases such as endocrine ophthalmopathy and can help to find and to identify the disease-associated autoantibodies.
authors.affiliation: Department of Ophthalmology, University of Bonn, Germany. 100024.1664@compuserve.com
authors.forename: F H
authors.initials: FH
authors.lastname: Grus
authors.forename: A J
authors.initials: AJ
authors.lastname: Augustin
mesh_terms: D000328:Adult; D001323:Autoantibodies / Q000032:analysis*; D015153:Blotting, Western / Q000379:methods; D004591:Electrophoresis, Polyacrylamide Gel; D000939:Epitopes / Q000276:immunology; D005136:Eye Proteins / Q000276:immunology*; D005260:Female; D006111:Graves Disease / Q000276:immunology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007074:Immunoglobulin G / Q000032:analysis*; D008297:Male; D008875:Middle Aged; D009124:Muscle Proteins / Q000276:immunology*; D009801:Oculomotor Muscles / Q000276:immunology*
chemical_list: D001323:Autoantibodies; D000939:Epitopes; D005136:Eye Proteins; D007074:Immunoglobulin G; D009124:Muscle Proteins