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Clin Proteomics. 2013 Sep 6;10(1):11. doi: 10.1186/1559-0275-10-11.

A multilectin affinity approach for comparative glycoprotein profiling of rheumatoid arthritis and spondyloarthropathy.

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Institute of Bioinformatics, International Technology Park, Bangalore 560066, India.
Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam 690525, India.
Department of Neurochemistry, National Institute of Mental Health and Neuro Sciences, Bangalore 560029, India.
Department of Biotechnology, Kuvempu University, Shankaraghatta 577451, India.
Department of Internal Medicine, Armed Forces Medical College, Pune 411040, India.
Manipal University, Madhav Nagar, Manipal 576104, India.
Centre of Excellence in Bioinformatics, Bioinformatics Centre, School of Life Sciences, Pondicherry University, Puducherry 605 014, India.
Department of Rheumatology, Fortis Hospital, Bangalore 560076, India.
McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA.
Department of Biological Chemistry, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA.
Department of Pathology, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA.
Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.
Contributed equally



Arthritis refers to inflammation of joints and includes common disorders such as rheumatoid arthritis (RA) and spondyloarthropathies (SpAs). These diseases differ mainly in terms of their clinical manifestations and the underlying pathogenesis. Glycoproteins in synovial fluid might reflect the disease activity status in the joints affected by arthritis; yet they have not been systematically studied previously. Although markers have been described for assisting in the diagnosis of RA, there are currently no known biomarkers for SpA.


We sought to determine the relative abundance of glycoproteins in RA and SpA by lectin affinity chromatography coupled to iTRAQ labeling and LC-MS/MS analysis. We also used ELISA to validate the overexpression of VCAM-1, one of the candidate proteins identified in this study, in synovial fluid from RA patients.


We identified proteins that were previously reported to be overexpressed in RA including metalloproteinase inhibitor 1 (TIMP1), myeloperoxidase (MPO) and several S100 proteins. In addition, we discovered several novel candidates that were overexpressed in SpA including Apolipoproteins C-II and C-III and the SUN domain-containing protein 3 (SUN3). Novel molecules found overexpressed in RA included extracellular matrix protein 1 (ECM1) and lumican (LUM). We validated one of the candidate biomarkers, vascular cell adhesion molecule 1 (VCAM1), in 20 RA and SpA samples using ELISA and confirmed its overexpression in RA (p-value <0.01). Our quantitative glycoproteomic approach to study arthritic disorders should open up new avenues for additional proteomics-based discovery studies in rheumatological disorders.

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