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Abstract Number: 982

Identification of Potential SERUM Autoantibody Biomarkers in Rheumatic Diseases Using a New Generation of Protein Arrays

Lucia Lourido1, Juan Fernandez-Tajes1, Valentina Calamia1, Carolina Fernandez-Costa1,2, Beatriz Rocha1, Patricia Fernandez-Puente1, Jesus Mateos1, Carlos Fernandez-Lopez1, Natividad Oreiro-Villar1, Manuel Fuentes3, Francisco J. Blanco Garcia1 and Cristina Ruiz-Romero1, 1Grupo de Proteomica-PBR2-ProteoRed/ISCIII-Servicio de Reumatologia. Instituto de Investigación Biomédica de A Coruña (INIBIC), Complexo Hospitalario Universitario de A Coruña (CHUAC), Sergas. Universidade da Coruña (UDC). As Xubias, 15006., A Coruña, Spain, 2Grupo de Proteomica-PBR2-ProteoRed/ISCIII-Servicio de Reumatologia. Instituto de Investigación Biomédica de A Coruña (INIBIC), Complexo Hospitalario Universitario de A Coruña (CHUAC), Sergas. Universidade da Coruña (UDC). As Xubias, 15006., A coruña, Spain, 3Centro de Investigación del Cáncer/IBMCC (USAL/CIC), IBSAL, Departamento de Medicina, Unidad de Proteomica Servicio general de Citometría, Universidad de Salamanca, Salamanca, SPAIN., Salamanca, Spain

Meeting: 2014 ACR/ARHP Annual Meeting

Keywords: autoantibodies, Biomarkers, osteoarthritis and serologic tests

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Session Information

Title: B cell Biology and Targets in Autoimmune Disease: Rheumatoid Arthritis and Related Diseases

Session Type: Abstract Submissions (ACR)

Background/Purpose

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. 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 using nucleic acid programmable protein arrays (NAPPA).

Methods

Antibodies were detected using NAPPA 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 (www.dnasu.org) and selected by their possible relevance in OA disease. Once the 80 different proteins were 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 using an antibody against human IgGs fluorescently labelled. Array images were obtained and processed by Genepix4000B and GenePix Software 6.0. For data analysis, normalization across all the arrays was performed.

Results

Significantly (p<0.05) 4 different autoantibodies against four different proteins have been observed to be higher in OA compared to CTRL samples.  Of note, 2 of these proteins are related to the metabolism of ECM (CHST14, PCOLCE); the others are associated to cell adhesion (CD44) and bone mineralization (LEP). We also observed that IL6 autoantibody levels distinguish RA and CTRL samples. 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 (IGFBP4, IGFBP6); and bone mineralization processes (LEP) whose levels are increased in OA compared to RA, one of these proteins (LEP) also distinguishing between CTRL and OA subjects.

Conclusion

We have identified the presence of specific autoantibodies in OA allowing to characterize differential autoantibody profiles 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 diagnosis and prognosis of OA patients in clinical routine.


Disclosure:

L. Lourido,
None;

J. Fernandez-Tajes,
None;

V. Calamia,
None;

C. Fernandez-Costa,
None;

B. Rocha,
None;

P. Fernandez-Puente,
None;

J. Mateos,
None;

C. Fernandez-Lopez,
None;

N. Oreiro-Villar,
None;

M. Fuentes,
None;

F. J. Blanco Garcia,
None;

C. Ruiz-Romero,
None.

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