Chondrocyte genomics: implications for disease modification in osteoarthritis

Poor Clearance of Free Hemoglobin Due to Lower Active Haptoglobin Availability is Associated with Osteoarthritis Inflammation

Introduction

Circulating plasma proteins play an important role in various diseases, and analysis of the plasma proteome has led to the discovery of various disease biomarkers. Osteoarthritis (OA) is the most common chronic joint disease, mostly affecting people of older age. OA typically starts as a focal disease (in a single compartment, typically treated with unicompartmental knee replacement), and then progresses to the other compartments (if not treated in time, typically treated with total knee replacement). For this, identification of differential proteins was carried out in plasma samples of OA cases and compared with healthy controls. The aim of this study was to identify circulatory differentially expressed proteins (DEPs) in knee-OA patients undergoing total knee replacement or unicompartmental knee replacement compared to healthy controls and assess their role, in order to have better understanding of the etiology behind OA pathophysiology.

Methods

DEPs were identified with two-dimensional gel electrophoresis (2DE) and isobaric tags for relative and absolute quantification (iTRAQ), followed by liquid chromatography with tandem mass spectrometry. Validation of DEPs was carried out using Western blot and ELISA. Posttranslational modifications were checked after running native gel using purified protein from patients, followed by detection of autoantibodies.

Results

In total, 52 DEPs were identified, among which 45 were distinct DEPs. Haptoglobin (Hp) was identified as one of the most significantly upregulated proteins in OA (P=0.005) identified by both 2DE and iTRAQ. Decreased levels of Hp tetramers and increased levels of autoantibodies against Hpβ were observed in OA plasma.

Conclusion

Our data suggest that poor clearance of free hemoglobin and low levels of Hp tetramers may be associated with OA pathogenesis and inflammation.

Interleukin-4/interleukin-4 receptor gene polymorphisms in hand osteoarthritis

OBJECTIVE

IL-13/IL-4/IL-4R system has strong chondroprotective activity. We investigated polymorphisms in these genes as potential hand osteoarthritis (OA) susceptibility loci by performing a case-control association study.

METHODS

Eighteen common single nucleotide polymorphisms (SNPs) (nine in IL-4R, five in IL-4 and four in IL-13) were genotyped in 403 patients (380 females) with hand OA and 322 healthy controls (308 females).

RESULTS

Two SNPs (rs1805013 and rs1805015), mapping to the IL-4R gene, were associated with P-values of 0.0116 and 0.0305 respectively in the whole sample. As far as the non-erosive hand OA group (n=159) is concerned, the significance level of association of SNP rs1805013 is increased. After correction for multiple testing (correction for the 54 tests) the significance was not retained. None of the IL-13 SNPs analyzed showed association with hand OA. Some of the analyzed SNP within the IL-4 gene showed significant association with hand OA only when considering subgroups of patients. With respect to the CMC1 OA group, two SNPs in IL-4 (rs2243250 and rs2243274) showed association with a P-value of 0.027 and 0.018 respectively. None of these associations remained after correction for multiple testing.

CONCLUSIONS

The present study shows a trend to an association between non-erosive hand OA in Caucasian population and a genetic variant in the coding region of IL-4R gene. Our results, in keeping with previous data on hip OA, confirm the suggestion that IL-4/IL-4R system plays a role in OA pathogenesis. Further confirmation studies on different populations are necessary.

Proteomics role in the search for improved diagnosis, prognosis and treatment of osteoarthritis

OBJECTIVE

Osteoarthritis (OA) is the most common rheumatic pathology. It is related to aging and is characterized primarily by cartilage degradation. Despite its high prevalence, the diagnostic methods currently available are limited and lack sensitivity. The focus of this review is the application of proteomic technologies in the search of new biomarkers for improved diagnosis, prognosis and treatment of OA.

METHODS

This review focuses on the utilization of proteomics in OA biomarker research to enable early diagnosis, improved prognosis and the application of tailored treatments.

RESULTS

New diagnostic tests for OA are urgently needed and would also promote the development of alternative therapeutic strategies. Considering that OA involves different tissues and complex biological processes, the most promising diagnostic approach would be the study of combinations of biomarkers. New experimental approaches for the identification and validation of OA biomarkers have recently emerged and include proteomic technologies. These techniques allow the simultaneous analysis of multiple markers and become a very powerful tool for both biomarker discovery and validation.

CONCLUSIONS

Improvements in proteomics technology will undoubtedly lead to advances in characterizing new OA biomarkers and developing alternative therapies. Even so, further work is required to enhance the performance and reproducibility of proteomics tools before they can be routinely used in clinical trials and practice.

Genetics in osteoarthritis

Osteoarthritis is a degenerative articular disease with complex pathogeny because diverse factors interact causing a process of deterioration of the cartilage. Despite the multifactorial nature of this pathology, from the 50's it s known that certain forms of osteoarthritis are related to a strong genetic component. The genetic bases of this disease do not follow the typical patterns of mendelian inheritance and probably they are related to alterations in multiple genes. The identification of a high number of candidate genes to confer susceptibility to the development of the osteoarthritis shows the complex nature of this disease. At the moment, the genetic mechanisms of this disease are not known, however, which seems clear is that expression levels of several genes are altered, and that the inheritance will become a substantial factor in future considerations of diagnosis and treatment of the osteoarthritis.

[Genetics in osteoarthritis]

Osteoarthritis is a degenerative articular pathology with complex pathogeny because diverse factors interact causing a process of deterioration of the cartilage. In spite of the multifactorial nature of this pathology, from years 50 one knows that certain forms of osteoarthritis are related to a strong genetic component. The genetic bases of this disease do not follow the typical patterns of mendelian inheritance and probably they are related to alterations in multiple genes. The identification of a high number of candidates genes to confer susceptibility to the development of the osteoarthritis shows the complex nature of this disease. At the moment, the genetic mechanisms of this pathology are not known, however, which seems clear is that levels of expression of several genes are altered, and that the inheritance will become a substantial factor in future considerations of diagnosis and treatment of the osteoarthitis.

Gene expression profiling of chondrocytes from a porcine impact injury model

OBJECTIVE

To identify differentially expressed genes between axially impacted and control articular cartilage taken from porcine patellae maintained in organ culture for 14 days.

METHODS

Porcine patellae were impacted perpendicular to the articular surface to create an impact injury. Intact patellae (control and impacted) were maintained in culture for 14 days. Total RNA was then extracted from the articular cartilage beneath the impaction and used to prepare two Serial Analysis of Gene Expression (SAGE) libraries. Approximately 42,500 SAGE long tags were sequenced from the libraries. The expression of select genes was confirmed by quantitative real-time PCR analysis.

RESULTS

Thirty-nine SAGE tags were significantly differentially expressed in the impacted and control libraries, representing 30 different annotated pig genes. These genes represented gene products associated with matrix molecules, iron and phosphate transport, protein biosynthesis, skeletal development, cell proliferation, lipid metabolism and the inflammatory response. Twenty-three of the 30 genes were down-regulated in the impacted library and five were up-regulated in the impacted library. Quantitative real-time PCR follow-up of four genes supported the results found with SAGE.

CONCLUSION

We have identified 30 putative genes differentially expressed in a porcine impact injury model and validated these findings for four of these genes using real-time PCR. Results using this impact injury model have contributed further evidence that damaged chondrocytes may de-differentiate into fibroblast-like cells and proliferate in an attempt to repair themselves. Additional work is underway to study these genes in further detail at earlier time points to provide a more complete story about the fate of chondrocytes in articular cartilage following an injury.