Analysis of synovial fluid in knee joint of osteoarthritis:5 proteome patterns of joint inflammation based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Correlation of synovial tissue protein abundance with menopause in osteoarthritis

BACKGROUND

Osteoarthritis (OA) is a common articular disorder. Epidemiologic surveys show a higher prevalence of OA in women than men and that morbidity is higher during menopause. We aimed to explore whether menopause influences the clinical recovery of a knee joint following OA and injury, and identify associated mechanisms by analyzing the proteomic profile of synovial tissue (ST) samples.

METHODS

Routine blood examination and hormone level tests were conducted before surgery. ST samples from eight participants were collected intraoperatively for proteomic analysis. One day before and one month after the surgery, we assessed various aspects of function in the affected knee including the with Visual Analog Score (VAS), Lysholm, The Western Ontario, and McMaster Universities Osteoarthritis Index (WOMAC) scores. The relationships between proteomic data, estrogen levels, and affected knee function were compared and analyzed. This was a retrospective study.

RESULT

Menopause was associated with the clinical outcomes of knee OA and knee injuries. ST proteomic data identified that 80 proteins in premenopausal OA females were significantly different from menopausal OA females. In addition, 100 proteins were significantly different between premenopausal OA females and premenopausal injured females.

CONCLUSIONS

Age and menopause showed a positive correlation with the protein profile of ST from OA or knee injury female patients, indicating that the protein components might be affected by menopause. Postoperative clinical outcomes were affected by menopause. We conclude that menopause may, in part, regulate knee joint function by altering ST protein expression.

Soluble biological markers in osteoarthritis

In recent years, markers research has focused on the structural components of cartilage matrix. Specifically, a second generation of degradation markers has been developed against type II collagen neoepitopes generated by specific enzymes. A particular effort has been made to measure the degradation of minor collagens III and X of the cartilage matrix. However, because clinical data, including longitudinal controlled studies, are very scarce, it remains unclear whether they will be useful as an alternative to or in combination with current more established collagen biological markers to assess patients with osteoarthritis (OA). In addition, new approaches using high-throughput technologies allowed to detect new types of markers and improve the knowledge about the metabolic changes linked to OA. The relative advances coming from phenotype research are a first attempt to classify the heterogeneity of OA, and several markers could improve the phenotype characterization. These phenotypes could improve the selection of patients in clinical trials limiting the size of the studies by selecting patients with OA characteristics corresponding to the metabolic pathway targeted by the molecules evaluated. In addition, the inclusion of rapid progressors only in clinical trials would facilitate the demonstration of efficacy of the investigative drug to reduce joint degradation. The combination of selective biochemical markers appears as a promising and cost-effective approach to fulfill this unmet clinical need. Among the various potential roles of biomarkers in OA, their ability to monitor drug efficacy is probably one of the most important, in association with clinical and imaging parameters. Biochemical markers have the unique property to detect changes in joint tissue metabolism within a few weeks.

Identification of tissue-dependent proteins in knee OA synovial fluid

OBJECTIVE

For many proteins from osteoarthritic synovial fluid, their intra-articular tissue of origin remains unknown. In this study we performed comparative proteomics to identify osteoarthritis-specific and joint tissue-dependent secreted proteins that may serve as candidates for osteoarthritis biomarker development on a tissue-specific basis.

DESIGN

Protein secretomes of cartilage, synovium, Hoffa's fat pad and meniscus from knee osteoarthritis patients were determined using liquid chromatography tandem mass spectrometry, followed by label-free quantification. Validation of tissue-dependent protein species was conducted by ELISA on independent samples. Differential proteomes of osteoarthritic and non-osteoarthritic knee synovial fluids were obtained via similar proteomics approach, followed by ELISA validation.

RESULTS

Proteomics revealed 64 proteins highly secreted from cartilage, 94 from synovium, 37 from Hoffa's fat pad and 21 from meniscus. Proteomic analyses of osteoarthritic vs non-osteoarthritic knee synovial fluid revealed 70 proteins with a relatively higher abundance and 264 proteins with a relatively lower abundance in osteoarthritic synovial fluid. Of the 70 higher abundance proteins, 23 were amongst the most highly expressed in the secretomes of a specific intra-articular tissue measured. Tissue-dependent release was validated for SLPI, C8, CLU, FN1, RARRES2, MATN3, MMP3 and TNC. Abundance in synovial fluid of tissue-dependent proteins was validated for IGF2, AHSG, FN1, CFB, KNG and C8.

CONCLUSIONS

We identified proteins with a tissue-dependent release from intra-articular human knee OA tissues. A number of these proteins also had an osteoarthritis-specific abundance in knee synovial fluid. These proteins may serve as novel candidates for osteoarthritis biomarker development on a tissue-specific basis.

Proteomic analysis of synovial fluid: current and potential uses to improve clinical outcomes

INTRODUCTION

Synovial fluid (SF) is in close proximity to tissues which are primarily altered during articular disease and has significant potential to better understand the underlying disease pathogeneses of articular pathologies and biomarker discovery. Although development of mass spectrometry-based methods has allowed faster and higher sensitivity techniques, interrogation of the SF proteome has been hindered by its large protein concentration dynamic range, impeding quantification of lower abundant proteins. Areas covered: Recent advances have developed methodologies to reduce the large protein concentration dynamic range of SF and subsequently allow deeper exploration of the SF proteome. This review concentrates on methods to overcome biofluid complexity, mass spectrometry proteomics methodologies, extracellular vesicles proteomics and the application of advances within the field in clinical disease, including osteoarthritis, rheumatoid arthritis, spondyloarthritis and juvenile arthritis. A narrative review was conducted with articles searched using PubMed, 1991-2018. Expert opinion: The SF proteomics field faces various challenges, including the requirement for rigorous and standardised methods of sample collection/storage, the sensitivity and specificity of proteomic assays, techniques to combat the large protein concentration dynamic range and comprehensive data analysis to reduce falsely identified markers. Additionally, there are challenges in developing multi 'omic' integration techniques, with computational integration enhancing analysis.

Two independent proteomic approaches provide a comprehensive analysis of the synovial fluid proteome response to Autologous Chondrocyte Implantation

Background

Autologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be fully understood why. Biomarkers are needed that can pre-operatively predict in which patients it is likely to fail, so that alternative or individualised therapies can be offered. We previously used label-free quantitation (LF) with a dynamic range compression proteomic approach to assess the synovial fluid (SF) of ACI responders and non-responders. However, we were able to identify only a few differentially abundant proteins at baseline. In the present study, we built upon these previous findings by assessing higher-abundance proteins within this SF, providing a more global proteomic analysis on the basis of which more of the biology underlying ACI success or failure can be understood.

Methods

Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomic analysis was used to assess SF from ACI responders (mean Lysholm improvement of 33; n = 14) and non-responders (mean Lysholm decrease of 14; n = 13) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins in iTRAQ and combined iTRAQ and LF datasets were investigated using pathway and network analyses.

Results

iTRAQ proteomic analysis confirmed our previous finding that there is a marked proteomic shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥ 2.0-fold change and p < 0.05 between stages I and II in responders and non-responders, respectively). Further, it highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, which were not found in the LF study, 16 of which were altered at baseline. The differential expression of two proteins (complement C1s subcomponent and matrix metalloproteinase 3) was confirmed biochemically. Combination of the iTRAQ and LF proteomic datasets generated in-depth SF proteome information that was used to generate interactome networks representing ACI success or failure. Functional pathways that are dysregulated in ACI non-responders were identified, including acute-phase response signalling.

Conclusions

Several candidate biomarkers for baseline prediction of ACI outcome were identified. A holistic overview of the SF proteome in responders and non-responders to ACI  has been profiled, providing a better understanding of the biological pathways underlying clinical outcome, particularly the differential response to cartilage harvest in non-responders.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1573-4) contains supplementary material, which is available to authorized users.

Identification of candidate biomarker mass (m/z) ranges in serous ovarian adenocarcinoma using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling

OBJECTIVE

To differentiate plasma from ovarian cancer and healthy individuals using MALDI-TOF mass spectroscopy.

MATERIALS AND METHODS

MALDI-TOF was used to generate profiles of immuno-depleted plasma samples (89 cancers and 199 healthy individuals) that were fractionated using three types of magnetic beads (HIC8, WCX and IMAC-Cu).

RESULTS

Differentially expressed mass ranges showing >1.5-2-fold change in expression from HIC8 (30), WCX (12) and IMAC-Cu (6) fractions were identified. Cross validation and recognition capability scores for the models indicated discrimination between the classes.

CONCLUSIONS

Spectral profiles can differentiate plasma samples of ovarian cancer patients from healthy individuals.

Lessons from the proteomic study of osteoarthritis

Osteoarthritis is the most common rheumatic pathology and one of the leading causes of disability worldwide. It is a very complex disease whose etiopathogenesis is not fully understood. Furthermore, there are serious limitations for its management, since it lacks specific and sensitive biomarkers for early diagnosis, prognosis and therapeutic monitoring. Proteomic approaches performed in the last few decades have contributed to the knowledge on the molecular mechanisms that participate in this pathology and they have also led to interesting panels of putative biomarker candidates. In the next few years, further efforts should be made for translating these findings into the clinical routines. It is expected that targeted proteomics strategies will be highly valuable for the verification and qualification of biomarkers of osteoarthritis.

Subchondral bone proteomics in osteoarthritis: Current status and perspectives

Osteoarthritis (OA) is the most common degenerative joint disorder. OA was conceived as a “wear and tear” problem of articular cartilage, yet there is a lack of treatment options to delay or rescue articular cartilage degeneration once it is established. Actually, the degradation of articular cartilage is related to a complex network of biochemical pathways involving the diffusion of catabolic factors within and between different joint tissues and particularly bone and cartilage. Advanced proteomics technology provides a powerful tool to allow us to build up a library of such factors. Factors that govern the bone-cartilage interplay could be the candidate diagnostic biomarkers and therapeutic targets for OA. Currently, a growing body of proteomic studies has been done to unveil a number of inflammatory cytokines, proteases, and cartilaginous matrix cleavages in the blood serum, synovial fluid, and articular cartilage from OA patients. Little information is available regarding the protein profiles of disturbances at subchondral bone in the pathophysiology of OA. The technical difficulties in protein extraction from tissues particularly bone and quantitative analyses of protein profile are discussed; cellular proteomics of the defective osteoblasts and secretomics for the osteoblasts–chondrocytes crosstalk are proposed to supplement the information obtained from the bone tissue proteomics.

Delineating the synovial fluid proteome: recent advancements and ongoing challenges in biomarker research

There is an urgent need for identifying novel serum biomarkers that can be used to improve diagnosis, predict disease progression or response to therapy, or serve as therapeutic targets for rheumatic diseases. Synovial fluid (SF) is secreted by and remains in direct contact with the synovial membrane, and can reflect the biochemical state of the joint under different physiological and pathological conditions. Therefore, SF is regarded as an excellent source for identifying biomarkers of rheumatologic diseases. The use of high-throughput and/or quantitative proteomics and sophisticated computational software applied to analyze the protein content of SF has been well-adopted as an approach to finding novel arthritis biomarkers. This review will focus on some of the potential pitfalls of biomarker studies using SF, summarize the status of the field of SF proteomics in general, as well as discuss some of the most promising biomarker study approaches using proteomics. A brief status of the biomarker discovery efforts in rheumatoid arthritis, osteoarthritis and juvenile idiopathic arthritis is also provided.

Osteoarthritis year 2012 in review: biomarkers

PURPOSE

Biomarkers provide useful diagnostic information by detecting cartilage degradation in osteoarthritis (OA), reflecting disease-relevant biological activity and predicting the course of disease progression. They also serve as surrogate endpoints in the drug discovery process. The aim of this narrative review was to focus on OA biomarker-related papers published between the osteoarthritis research society international (OARSI) 2011 meeting in San Diego and the OARSI 2012 meeting in Barcelona.

METHODS

The PubMed/MEDLINE and SciVerse Scopus bibliographic databases were searched using the keywords: 'biomarker' and 'osteoarthritis' and/or 'biomarker' and 'proteomics'.

RESULTS

Ninety-eight papers were found with the keywords 'biomarker' and 'osteoarthritis'. Fifteen papers were found with the keywords 'biomarker' and 'proteomics'. Review articles were also included. The most relevant published studies focused on extracellular matrix (ECM) molecules in body fluids. Enrichment of the deamidated epitope of cartilage oligomeric matrix protein (D-COMP) suggests that OA disease progression is associated with post-translational modifications that may show specificity for particular joint sites. Fibulin-3 peptides (Fib3-1 and Fib3-2) have been proposed as potential biomarkers of OA along with follistatin-like protein 1 (FSTL1), a new serum biomarker with the capacity to reflect the severity of joint damage. The 'membrane attack complex' (MAC) component of complement has also been implicated in OA.

CONCLUSION

Novel OA biomarkers are needed for sub-clinical disease diagnosis. Proteomic techniques are beginning to yield useful data and deliver new OA biomarkers in serum and urine. Combining biochemical markers with tissue and cell imaging techniques and bioinformatics (i.e., machine learning, clustering, data visualization) may facilitate the development of biomarker combinations enabling earlier detection of OA.

The fate of acutely inflamed joints with a negative synovial fluid culture

PURPOSE

The purpose of this study was to evaluate the management and fate of acutely inflamed joints with a negative synovial fluid culture.

METHODS

Between January and December 2009, all the patients who presented to our institution with an acutely inflamed joint and were subjected to microbiological assessment of their synovial fluid, were included in the study. Patients with a positive synovial fluid culture, a prosthetic joint replacement in situ and where an aspirate was obtained for a rheumatological diagnosis were excluded. This cohort was then divided into two groups depending on whether a diagnosis could be established through the course of their treatment. Group I included patients in whom a diagnosis could be established and group II included patients in whom a diagnosis could not be established. A thorough review of the patients' medical records and the hospital database was performed. Following this, a database consisting of the patient demographics, clinical features, investigations, treatment and outcome was created.

RESULTS

A total of 144 patients met the inclusion criteria (group I: 95, group II: 49). The most commonly affected joint in both the groups was the knee. The average time to presentation was shorter in group II. Clinical findings at presentation were comparable in both groups. However, inflammatory markers were more likely to be raised in group II in comparison with group I. Eighty-two percent of group II required antibiotic treatment compared with 15% of group I. The mean duration of antibiotic treatment in group I was ten days and in group II was 26 days. Mean hospital stay differed significantly between the two groups, with group II being more than twice as long as compared with group I (p=0.001). The rate of mortality was also higher in group II (8.2%, p=0.03).

CONCLUSION

Our study shows that patients presenting with an acutely inflamed joint and a negative synovial fluid culture in whom a diagnosis cannot be established during their hospital stay have a longer hospital stay and an increased rate of mortality as compared with patients in whom a diagnosis can be established.

Contributions of mass spectrometry-based proteomics to defining cellular mechanisms and diagnostic markers for systemic lupus erythematosus

Systematic lupus erythematosus (SLE) is a complex disease for which molecular diagnostics are limited and pathogenesis is not clearly understood. Important information is provided in this regard by identification and characterization of more specific molecular and cellular targets in SLE immune cells and target tissue and markers of early-onset and effective response to treatment of SLE complications. In recent years, advances in proteomic technologies and applications have facilitated such discoveries. Here we provide a review of insights into SLE pathogenesis, diagnosis and treatment that have been provided by mass spectrometry-based proteomic approaches.

Differential protein profiling of synovial fluid from rheumatoid arthritis and osteoarthritis patients using LC-MALDI TOF/TOF

The purpose of this study was to identify those proteins relatively more abundant in the synovial fluid (SF) of patients suffering from rheumatoid arthritis (RA) and osteoarthritis (OA) using high performance liquid chromatography coupled to mass spectrometry. 20 individual SF samples from each disease were pooled into two groups (RA and OA) to reduce the contribution of extreme individual values. Prior to the proteomic analysis, samples were immunodepleted from the top 20 most abundant plasma proteins, to enrich the lower-abundance protein fractions. Then, they were subjected to protein size fractioning and in-gel digestion, followed by reversed-phase peptide separation in a nano-LC system and subsequent peptide identification by MALDI-TOF/TOF. This strategy led to the identification of 136 different proteins in SF, which is the largest number of SF proteins described up to date by proteomics. A relative quantification of the proteins between RA and OA was carried out by spectral counting analysis. In RA, our results show a greater relative abundance of proteins related to complement activation, inflammation and the immune response, such as the major matrix metalloproteinases and several neutrophil-related proteins. In OA, we detected an increase in proteins involved in the formation and remodeling of the extracellular matrix (ECM), such as fibronectin, kininogen-1, cartilage acidic protein 1 and cartilage oligomeric matrix protein. The results obtained for MMP-1, BGH3, fibronectin and gelsolin were verified by immunoblotting analyses. Some of the novel proteins identified in this work might be relevant not only for increasing knowledge on the etiopathogenesis of RA and OA processes, but also as putative disease biomarkers, as their presence in SF is a prior step to their dilution in serum. This article is part of a Special Issue entitled: Proteomics: The clinical link.