Article Text

SAT0425 Serum Autoantibody Profiling in Rheumatic Diseases by Nucleid Acid Programmable Protein Arrays
  1. L. Lourido1,
  2. J. Fernandez-Tajes1,
  3. V. Calamia1,
  4. C. Fernández1,
  5. B. Rocha1,
  6. M. Fuentes2,
  7. F.J. Blanco1,
  8. C. Ruiz-Romero1
  1. 1Rheumatology Division, Proteomics Group-ProteoRed/ISCIII, Inibic-CHUac, A Coruña
  2. 2Centro de Investigaciόn del Cáncer/IBMCC (USAL/CIC), IBSAL, Departamento de Medicina, Unidad de Proteomica Servicio general de Citometría, Universidad de Salamanca, Salamanca, Spain


Background Osteoarthritis (OA) is characterized by the loss of structural components from the extracelullar matrix (ECM) of articular cartilage. The progressive release of proteins from the tissue and an abnormal metabolic activity can be specifically detected by the immune system, leading to a humoral immune response producing immunoglobulins against these proteins (autoantibodies). Autoantibodies are stable circulating proteins, easily measurable in serum, and may be the signature before clinical manifestations of the disease. Protein microarrays have emerged providing a tool for the identification of disease immunosignatures.

Objectives The aim of this study was to detect the presence of autoantibodies in OA serum samples and compare these results with those obtained from healthy (CTRL) and rheumatoid arthritis (RA) sera.

Methods Antibodies were detected using an specific Nucleic Acid Protein Programmable Array (NAPPA) designed and constructed as previously described by Ramachandran et al. 2008, containing 80 sequence-verified full-length human genes obtained from the Center for Personalized Diagnostics at the Arizona State University ( Once protein was displayed by in situ protein expression system, NAPPA arrays were incubated in optimized conditions with 20 OA, 20 RA and 18 CTRL serum samples. The autoantibodies were detected by anti-human IgG-HRP and fluorescence dye. Array images were obtained and processed by Genepix4000B and GenePix Software 6.0. For data analysis, background correction was performed by subtraction of the first quartile of non-DNA spots intensity and then divided the excess intensity by the median of spots without DNA across arrays.

Results Significantly (p<0.05) 4 different expression of autoantibodies against four different proteins has been observed between OA and CTRL serum samples. Of note, 2 of these proteins are related to the metabolism of ECM; the others are associated to cell adhesion (1) and bone mineralization (1). Most interestingly, this approach allowed the differential classification of RA and OA patients by the detection of 3 specific autoantibodies against proteins involved in cell proliferation and bone mineralization processes; one of these proteins also distinguishing between CTRL and RA subjects.

Conclusions We have identified the presence of specific autoantibodies in OA allowing to distinguish between OA and CTRL patients and most interestingly, between OA and RA patients. These autoantibodies released to the serum might have a biomarker value to more accurate early diagnosis and prognosis of OA patients in clinical routine.

Disclosure of Interest None declared

DOI 10.1136/annrheumdis-2014-eular.5015

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