Autoantibodies in patients with glaucoma: a comparison of IgG serum antibodies against retinal, optic nerve, and optic nerve head antigens

  • Stephanie C. Joachim
  • Norbert Pfeiffer
  • Franz H. GrusEmail author
Laboratory Investigation



The aim of this study was to analyze and compare the entire IgG autoantibody patterns against different ocular antigens (retina, optic nerve, and optic nerve head) in sera of glaucoma patients and healthy subjects.


Sixty-six patients were included in this study: healthy volunteers without any ocular disorders (CO, n=30), patients with primary open-angle glaucoma (POAG, n=19), and patients with normal-tension glaucoma (NTG, n=17). The sera were tested for antibodies against retinal, optic nerve, and optic nerve head tissues. Immunodetection was performed using 4-chloro-1-naphthol staining. The autoantibody patterns were digitized and subsequently analyzed by multivariate statistical techniques.


All patients showed a complex repertoire of IgG antibodies against retinal, optic nerve, and optic nerve head antigens. The analysis of discriminance revealed a statistically significant differences between the patterns of all three groups. Our multivariate approach could quantify the differences in immunoreactivities of patient sera against the three antigens. The POAG group had the most significant difference against retinal antigens (P=0.0021) compared with the other antigens. In the NTG group the highest reactivity appeared against optic nerve head (P=0.00053) and optic nerve (P=0.0025).


All groups showed different and complex antibody patterns against the three ocular tissues. These autoantibodies are highly specific for each patient group. The analysis of these patterns could provide further information about possible autoimmune mechanisms in the pathogenesis of glaucoma.


Glaucoma Optic Nerve Optic Nerve Head Glaucoma Patient Normal Tension Glaucoma 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • Stephanie C. Joachim
    • 1
  • Norbert Pfeiffer
    • 1
  • Franz H. Grus
    • 1
    Email author
  1. 1.Department of OphthalmologyUniversity of MainzMainzGermany

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