Proteomics: applications to the study of rheumatoid arthritis and osteoarthritis

Proteomics perspectives in rotator cuff research: a systematic review of gene expression and protein composition in human tendinopathy

BACKGROUND

Rotator cuff tendinopathy including tears is a cause of significant morbidity. The molecular pathogenesis of the disorder is largely unknown. This review aimed to present an overview of the literature on gene expression and protein composition in human rotator cuff tendinopathy and other tendinopathies, and to evaluate perspectives of proteomics--the comprehensive study of protein composition--in tendon research.

MATERIALS AND METHODS

We conducted a systematic search of the literature published between 1 January 1990 and 18 December 2012 in PubMed, Embase, and Web of Science. We included studies on objectively quantified differential gene expression and/or protein composition in human rotator cuff tendinopathy and other tendinopathies as compared to control tissue.

RESULTS

We identified 2199 studies, of which 54 were included; 25 studies focussed on rotator cuff or biceps tendinopathy. Most of the included studies quantified prespecified mRNA molecules and proteins using polymerase chain reactions and immunoassays, respectively. There was a tendency towards an increase of collagen I (11 of 15 studies) and III (13 of 14), metalloproteinase (MMP)-1 (6 of 12), -9 (7 of 7), -13 (4 of 7), tissue inhibitor of metalloproteinase (TIMP)-1 (4 of 7), and vascular endothelial growth factor (4 of 7), and a decrease in MMP-3 (10 of 12). Fourteen proteomics studies of tendon tissues/cells failed inclusion, mostly because they were conducted in animals or in vitro.

CONCLUSIONS

Based on methods, which only allowed simultaneous quantification of a limited number of prespecified mRNA molecules or proteins, several proteins appeared to be differentially expressed/represented in rotator cuff tendinopathy and other tendinopathies. No proteomics studies fulfilled our inclusion criteria, although proteomics technologies may be a way to identify protein profiles (including non-prespecified proteins) that characterise specific tendon disorders or stages of tendinopathy. Thus, our results suggested an untapped potential for proteomics in tendon research.

The Predicted Proteomic Network Associated with the Antiarthritic Action of Qingfu Guanjieshu in Collagen-II-Induced Arthritis in Rats

Qingfu Guanjieshu (QFGJS) is an herbal preparation for treating rheumatoid arthritis (RA). Previous studies revealed that QFGJS significantly inhibited experimental arthritis and acute inflammation, accompanied by reduction of proinflammatory cytokines and elevation of anti-inflammatory cytokines. This study aims to identify the targeted proteins and predict the proteomic network associated with the drug action of QFGJS by using 2D gel and MALDI-TOF-MS/MS techniques. Thirty female Wistar rats were evenly grouped as normal and vehicle- and QFGJS-treated CIA rats. The antiarthritic effect of QFGJS was examined with a 19-day treatment course, and the knee synovial tissues of animals from each group were obtained for 2D gel and MALDI-TOF-MS/MS analysis. Results showed that QFGJS significantly ameliorated collagen II-induced arthritis when administrated at 2.8 g/kg body weight for 19 days. 2D gel image analysis revealed 89 differentially expressed proteins in the synovial tissues among the normal and vehicle- and QFGJS-treated CIA rats from over 1000 proteins of which 63 proteins were identified by MALDI-TOF-MS/MS analysis, and 32 proteins were included for classification of functions using Gene Ontology (GO) method. Finally, 14 proteins were analyzed using bioinformatics, and a predicted proteomic network related to the anti-arthritic effect of QFGJS was established, and Pgk1 plays a central role.

Identification of proteins with increased expression in rheumatoid arthritis synovial tissues

OBJECTIVE

A proteomic approach was applied to discover novel rheumatoid arthritis (RA)-specific proteins by comparing the expression profiles of synovial membranes from patients with RA, osteoarthritis (OA), and ankylosing spondylitis (AS).

METHODS

Synovial tissues were collected from patients with RA (n = 10), OA (n = 10), or AS (n = 6), and healthy controls matched for age and sex. Proteins were separated by 2-dimensional polyacrylamide gel electrophoresis, and the proteins with significantly increased expression in the RA samples were subject to matrix-assisted laser adsorption-ionization time-of-flight spectrometry. Results were verified using Western blot and immunohistochemistry. Levels of the candidate proteins were measured within plasma and synovial fluids from the RA patients (n = 30), who had disease duration of 3-7 years, using ELISA. Levels were also measured within plasma from unmedicated RA patients (n = 41), who had disease duration of 1-6 months.

RESULTS

Compared with the OA and AS tissue samples, the proteins Ig-kappa light-chain C region, PRDX4, SOD2, TPI, and TXNDC5 were found with increased expression in synovial tissues of RA patients. PRDX4, SOD2, TPI, and TXNDC5 had 2-fold or more increase in expression in some of the early RA plasma samples (58.55%, 31.7%, 26.8%, and 36.6%, respectively) as compared with the early OA samples and control samples. TXNDC5 had 2-fold or more increase in expression in 53.3% of blood samples and 73.3% of synovial fluid samples from patients with long disease duration of RA as compared with samples from OA and AS patients.

CONCLUSION

Functional classification indicated that these identified proteins were related with cell differentiation, glycol metabolism, immunoactivation, and endogenous antioxidant reaction.

[Toward a non-empirical treatment for rheumatoid arthritis based on its molecular pathology]

Rheumatoid arthritis (RA) is a chronic, disabbling disease that affects individuals during the productive years of their lives. Modern treatment for RA includes the so called "biologic" therapy, which is based on recombinant proteins that modify the biologic processes. These agents have potent therapeutic effects and different mechanisms of action. Nevertheless, therapeutic failure still prevails. Treatment that prevents disability in RA must be started in an early manner, before the development of complications and, ideally, with a minimum possibility of therapeutic failure. As yet, there are no clinical or laboratory criteria to identify those patients with a higher probability of responding to particular types of therapy, delaying control of RA ad affecting the prevention of incapacity. Research into gene diversity through single-nucleotide polymorphisms (SNPs) by means of microarray systems, allows the detailed analysis of gene factors associated to a given disease. SNPs have been recently applied to the study of RA, where the major polymorphisms associated to RA occur primarily in genes that code for proteins related to the initiation of an immune response and/or the control of cellular activity in the immune system, in addition to genes related to tissue repair. The specific meaning of these findings is in its initial stages of research. On the other hand, proteomics relate to the analysis of protein expression profiles at multiple levels. Both types of studies will contribute to the knowledge of patterns of gene expression in RA compared to the general population, and will allow an understanding of the pathogenesis of RA. Moreover, proteomic and genomic profiles can be employed to designs probes that identify individuals with the risk of developing RA, individually predict the response to different therapeutic modalities (pharmacogenomics) and for the follow-up of the biologic response to therapy.

An inflammatory arthritis-associated metabolite biomarker pattern revealed by 1H NMR spectroscopy

Rheumatoid arthritis, a debilitating, systemic inflammatory joint disease, is likely accompanied by alterations in circulating metabolites. Here, an 1H NMR spectroscopy-based metabolomics approach was developed to establish a metabolic 'biomarker pattern' in a model of rheumatoid arthritis, the K/BxN transgenic mouse. Sera obtained from arthritic K/BxN mice (N = 15) and a control population (N = 19) having the same genetic background, but lacking the arthritogenic T-cell receptor KRN transgene, were compared by 1H NMR spectroscopy. A unique method was developed by combining technologies such as ultrafiltration to remove proteins from serum samples, quantitative 'targeted profiling' of known metabolites, pseudo-quantitative profiling of unknown resonances, a supervised O-PLS-DA pattern recognition analysis, and a metabolic-pathway based network analysis for interpretation of results. In total, 88 spectral features were profiled (59 metabolites and 28 unknown resonances). A highly significant subset of 18 spectral features (15 known compounds and 3 unknown resonances) was identified (p = 0.00075 using MANOVA) that we term a 'metabolic bioprofile'. We identified metabolites relating to nucleic acid, amino acid, and fatty acid metabolism, as well as lipolysis, reactive oxygen species generation, and methylation. Pathway analysis suggested a shift from metabolites involved in numerous reactions (hub-metabolites) toward intermediates and metabolic endpoints associated with arthritis. The results attest to the metabolic complexity of systemic inflammation and to the power of the experimental approach for identifying a wide variety of disease-associated marker candidates. The diagnostic and prognostic implications of monitoring a spectrum of metabolic events simultaneously using serum samples is discussed with respect to the potential for individualized medicine.