Identification of two autoantigens recognised by circulating autoantibodies as potential biomarkers for diagnosing

Elisa Pesce1, Mauro Bombaci2, Stefania Croci3

  • 1Dipartimento di Scienze Cliniche e di Comunità, Dipartimento di Eccellenza 2023-2027, University of Milan, and Istituto Nazionale Genetica Molecolare, Milan, Italy.

Insights

Researchers identified two new autoantibodies, VSIG10L and DCBLD1, as potential biomarkers for diagnosing giant cell arteritis (GCA). These findings could lead to non-invasive diagnostic tools for this serious inflammatory condition.

Area of Science:

  • Immunology
  • Rheumatology
  • Vascular Biology

Background:

  • Giant cell arteritis (GCA) is a prevalent vasculitis in individuals over 50, causing inflammation in large/medium vessels.
  • Complications include vision loss, stroke, and aortic aneurysms, necessitating early diagnosis.
  • Current diagnostic methods like temporal artery biopsy and ultrasound have limitations; existing biomarkers lack specificity.

Purpose of the Study:

  • To identify novel serum autoantibodies as diagnostic biomarkers for GCA.
  • To explore the potential of autoantibodies in improving GCA diagnosis beyond current methods.

Main Methods:

  • Sera from GCA patients, Takayasu arteritis patients, and healthy controls were profiled using human protein arrays.
  • Candidate autoantigens were purified and specific autoantibodies were quantified using ELISA.

Main Results:

  • Autoantibodies against VSIG10L and DCBLD1 were identified and associated with GCA.
  • These autoantibodies showed high specificity and a combined prevalence of 43-57% in GCA patients.
  • Control groups (Takayasu arteritis, healthy controls) tested negative for these antibodies.

Conclusions:

  • The identified GCA-specific autoantibodies may provide a new, non-invasive diagnostic tool.
  • This research highlights the potential role of humoral immune responses in GCA pathogenesis.
  • Further investigation into these autoantibodies could enhance diagnostic accuracy for GCA.
Abstract