Chronically inflamed synovium from spondyloarthropathy and rheumatoid arthritis investigated by protein expression profiling followed by tandem mass spectrometry

Proteomic biomarkers for autoimmune disease

Autoimmune diseases affect 3% of the world population, yet the diagnosis and classification of autoimmune diseases remain based on clinical examination combined with traditional laboratory tests and imaging studies. The development of genomic and proteomic technologies provides an unprecedented ability to identify novel biosignatures to diagnose, classify, and guide therapeutic decision making in patients with autoimmune disease. In this article, we review recent advances in proteomics technologies and their application to autoimmune disease.

Proteomic analysis of cartilage- and bone-associated samples

The skeleton of the human body is built of cartilage and bone, which are tissues that contain extensive amounts of extracellular matrix (ECM). In bone, inorganic mineral hydroxyapatite forms 50-70% of the whole weight of the tissue. Although the organic matrix of bone consists of numerous proteins, 90% of it is composed of type I collagen. In cartilage, ECM forms a major fraction of the tissue, type II collagen and aggrecans being the most abundant macromolecules. It is obvious that the high content of ECM components causes analytical problems in the proteomic analysis of cartilage and bone, analogous to those in the analysis of low-abundance proteins present in serum. The massive contents of carbohydrates present in cartilage proteoglycans, and hydroxyapatite in bone, further complicate the situation. However, the development of proteomic tools makes them more and more tempting also for research of musculoskeletal tissues. Application of proteomic techniques to the research of chondrocytes, osteoblasts, osteocytes, and osteoclasts in cell cultures can immediately benefit from the present knowledge. Here we make an overview to previous proteomic research of cartilage- and bone-associated samples and evaluate the future prospects of applying proteomic techniques to investigate key events, such as cellular signal transduction, in cartilage- and bone-derived cells.

Proteomic Analysis of Recurrent Joint Inflammation in Juvenile Idiopathic Arthritis

The synovial fluid proteome in juvenile idiopathic arthritis was investigated to isolate joint-specific biomarkers that are expressed in patients displaying recurrent joint inflammation. To identify the synovial specific proteome, matched synovial fluid and plasma samples were subjected to protein separation by 2-dimension electrophoresis (2DE). Forty-three protein spots, overexpressed in the joint, were identified. Synovial fluids from children with single-event knee joint inflammation were then compared with a group with recurrent knee disease. Nine synovial specific proteins were significantly differentially expressed in the recurrent group. Proteolytic fragments of collagen X, fibrin beta-chain, and T-cell receptor alpha-region have been identified among this protein cluster. Putative biomarkers, overexpressed in the joint and differentially expressed in children with recurrent joint inflammation, have been identified. These proteins may play a significant role determining the pathological state within the chronically inflamed joint and influence disease progression in JIA. This is the first study of the synovial proteome in children.

Synovial biomarkers in the spondylarthropathies

PURPOSE OF THE REVIEW

To explore the concept of a biomarker, or surrogate endpoint, to enhance early diagnosis or predict the response to therapeutic intervention in patients with spondylarthropathy.

RECENT FINDINGS

Immunopathologic studies have suggested that the features of spondylarthropathy are distinctive, supporting a prominent role for innate immune cells, and can be consistently differentiated from rheumatoid arthritis. Successful treatment of spondylarthropathy synovitis resulted in rapid and sustained decrease in infiltration by macrophage populations and neutrophils, and decreased expression of many proinflammatory mediators. Consistent with studies in rheumatoid arthritis, significant correlations between the effects of both methotrexate and infliximab on disease activity and sublining macrophage populations were reported. These observations highlight the possibility that macrophage populations may be a synovial tissue biomarker of therapeutic intervention in spondylarthropathy. Preliminary studies have evaluated advanced genomic and proteomic methodologies in spondylarthropathy.

SUMMARY

Defining the immunopathology of spondylarthropathy has been associated with identifying potential biomarkers of the clinical response to therapeutic intervention. A surrogate marker of arthritis activity in spondylarthropathy could profoundly enhance screening for efficacy and optimization of dose ranges in early-phase randomized clinical trials.

Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach

OBJECTIVE

To identify serum protein biomarkers specific for rheumatoid arthritis (RA), using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology.

METHODS

A total of 103 serum samples from patients and healthy controls were analyzed. Thirty-four of the patients had a diagnosis of RA, based on the American College of Rheumatology criteria. The inflammation control group comprised 20 patients with psoriatic arthritis (PsA), 9 with asthma, and 10 with Crohn's disease. The noninflammation control group comprised 14 patients with knee osteoarthritis and 16 healthy control subjects. Serum protein profiles were obtained by SELDI-TOF-MS and compared in order to identify new biomarkers specific for RA. Data were analyzed by a machine learning algorithm called decision tree boosting, according to different preprocessing steps.

RESULTS

The most discriminative mass/charge (m/z) values serving as potential biomarkers for RA were identified on arrays for both patients with RA versus controls and patients with RA versus patients with PsA. From among several candidates, the following peaks were highlighted: m/z values of 2,924 (RA versus controls on H4 arrays), 10,832 and 11,632 (RA versus controls on CM10 arrays), 4,824 (RA versus PsA on H4 arrays), and 4,666 (RA versus PsA on CM10 arrays). Positive results of proteomic analysis were associated with positive results of the anti-cyclic citrullinated peptide test. Our observations suggested that the 10,832 peak could represent myeloid-related protein 8.

CONCLUSION

SELDI-TOF-MS technology allows rapid analysis of many serum samples, and use of decision tree boosting analysis as the main statistical method allowed us to propose a pattern of protein peaks specific for RA.

Rheumatology: a close encounter with proteomics

Proteomics is a fast-growing discipline in biomedicine that can be defined as the large-scale characterization of the entire protein complement of a cell, tissue or organism. Because protein levels and function may be critically dependent upon post-transcriptional mechanisms (e.g. post-translational modifications), there has been significant interest in directly examining protein structure and function. It is now clear that proteomics studies may unmask previously unknown functions of proteins or protein interactions. However, proteomics in the field of rheumatology is still in its infancy. This review guides the reader through the consecutive steps of a proteomics study and provides an outline of the applications in the field of rheumatology, which may range from proteome analyses of biological fluids of rheumatic diseases to identify possible new diagnostic tools, towards more pathophysiological studies on target tissues, such as synovial tissue or articular cartilage. Proteomics has great potential in the field of rheumatology and will no doubt have a great impact on our molecular understanding of these complex diseases.