Synovial fluid-derived extracellular vesicles - potential biomarkers of osteoarthritis
DOI: https://doi.org/10.47184/tev.2022.01.05Osteoarthritis (OA) is a degenerative disease of the musculoskeletal system affecting millions of people around the world. Therefore, research focusing on the correct diagnostics and effective treatment of OA represents a major society-wide challenge. Extracellular vesicles (EVs) as extracellular products of cells containing nucleic acids, proteins and lipids provide intercellular communication and affect the biological activity of cells. This work describes the pathogenesis of OA and the current nomenclature, composition and potential function of EVs associated with this degenerative disease. Investigation of EVs function in OA will help to elucidate the pathogenesis and investigate other new potential biomarkers of this disease.
Keywords: Extracellular vesicles, synovial fluid, biomarkers, osteoarthritis
Introduction
Osteoarthritis (OA) of the joint is one of the most common diseases of the musculoskeletal system. It is accompanied by various types of manifestations from pain, synovial membrane inflammation (synovitis) and cartilage degeneration to enlargement (hyperplasia) of the subchondral bone [1]. OA has long been thought to be a disease caused primarily by mechanical wear of cartilage. The basic pillar of this theory was the fact that cartilage is made up of a single type of cell - chondrocytes, which have low metabolic activity and therefore are unable to regenerate damaged cartilage. In addition, this type of tissue is not physiologically innervated and vascularized, which also reduces regenerative capacity. However, with increasing scientific knowledge, this theory has been abandoned and replaced by the so-called inflammatory environment theory. This is based on the action of molecules such as cytokines and prostaglandins, which significantly affect the production of matrix metalloproteinases by chondrocytes, and thus contribute to the gradual degradation of articular cartilage [2]. Cytokines are secreted by chondrocytes, synovial cells and a number of other cells present in the joint and are detectable in synovial fluid (SF) in OA patients. Studies from previous years have confirmed the significant effect of the synovial membrane on pathological cartilage changes through the autoimmune system, leading to the progression of OA [3]. Extracellular vesicles (EVs) are particles naturally released from the cells that are bounded by a lipid bilayer and cannot replicate, i. e. they do not contain a functional nucleus. They are produced by a number of cells types and can be found in several body fluids (plasma, serum, urine, cerebrospinal fluid and SF). In the past, EVs were considered to be waste products of cell metabolism. Today, studies have shown that they have a number of important functions. EVs contain biologically active molecules such as non-coding RNA (ncRNA), proteins, microRNA (miRNA), messenger RNA (mRNA), etc. Due to the specific "cargo", EVs are thought to be able to affect the microenvironment and provide intercellular communication [4]. Activated synovial fibroblasts have been shown to have the ability to directly affect OA pathology through these small transporters. There are several methods by which EVs can be separated/isolated, either from conditioned media from cells, tissues or from biofluids [5]. Such methods include: differential centrifugation, density gradient centrifugation, particle size chromatography, filtration, precipitation, and immunomagnetic separation.
Basics in characterisation and classification of EVs
In recent decades, the study of EVs has expanded into several areas of research [6,7]. Therefore, it was necessary to propose a general uniform nomenclature and categorization of these particles. Researchers studying EVs have taken on this role and developed a manual called: Minimum experimental requirements for the definition of extracellular vesicles and their functions in 2014 [8]. According to current recommendations, EVs should therefore be named either according to size (small EVs <200nm, large EVs ˃200nm), density (low, medium, high), biochemical composition (expression of surface markers), or according to the source of the cells from which they originate (e. g. mesenchymal stem cell-derived EVs) [8]. In 2018, the original criteria were supplemented and another manual called: Minimal Information for Studies of Extracellular Vesicles 2018 - MISEV2018 was published [4]. In addition to the nomenclature of EVs, the criteria contain a wealth of information on the various options for separating and characterizing EVs. For each experiment, the number of cultured cells must be reported, the total initial volume of biofluid or weight/volume/tissue size at the time of collection. The presence of at least three positive EVs protein markers (at least one of the transmembrane – CD9, CD63, CD81, CD82 and cytosolic – TSG101, FLOT1/2, ALIX, HSC70) must be confirmed using either Western blot or flow cytometry (FACS). One negative protein marker (APOB100, albumin etc.) must also be analysed to demonstrate the nature of the EVs and the degree of purity of the EVs preparation. Visualization of individual EVs can be achieved using atomic force microscopy (AFM) or transmission electron microscopy (TEM). Using these methods, it is possible to determine the shape and amount of EVs. The methods used to determine the number and average size of EVs are based on the principle of measurement by resistive pulse sensing, light scattering properties (NTA) or fluorescence properties (FCS, FACS) [4]. By adhering to these basic rules, the results can be compared between individual laboratories without misinterpretation or inconsistency in the presented research results in the field of EVs.
Synovial fluid - source of EVs
Since blood plasma is a source of information from the whole organism and it is not possible to determine exactly where the information from plasma-derived EVs comes from, ways are being sought for a more accurate diagnosis of OA [9]. Nowadays, the diagnostics of OA itself takes place on the basis of visualization techniques (e. g. X-ray, MRI, USG) and the patient's clinical history, which does not always correlate exactly with the symptoms themselves (pain, stiffness, swelling and others) [10]. One of the possibilities is a diagnostic method based on the analysis of SF and EVs isolated from it. SF is a suitable source of information in monitoring the pathogenesis of OA, because it directly connects the tissues present in the joint capsule, such as the synovial membrane, cartilage or Hoff's fat pad [11]. The advantage of SF is that changes in the OA process are more pronounced in it than in other biological fluids [12]. Compared to visualization methods, aspiration of SF is an invasive diagnostic tool. In healthy joints, physiological soft cartilage and SF work together to create as little friction as possible within the connective tissue. The fluid itself provides mechanical shock absorption, lubrication and cartilage nutrition [13]. SF is produced by the inner membrane of the joint (synovial membrane) and contains mainly serum albumin, hyaluronan, lubricin and globulin [14]. During friction, which occurs in the joint during physiological movement, there are changes in the composition of the SF. A naturally thin layer of homogeneous fluid changes into a rough heterogeneous mixture of fluid and precipitates by frictional forces [15]. Current research is focused on the characterization of proteins and miRNAs as potential biomarkers of OA present in SF [9]. Since SF is in direct contact with OA tissues, it is expected that a potential biomarker can be detected in it, which could ideally correlate with its plasma levels. Thus, based on SF-derived biomarker research, we would reach the stage of less invasive diagnostics of OA (from an ordinary blood sample).
miRNA and lncRNA as a diagnostic biomarker of OA
The key assumption for successful treatment of most diseases is their early diagnosis. EVs provide potential information in the form of microRNA (miRNA), long non-coding RNA (lncRNA), mRNA, etc. [16]. These could be used in the diagnosis of OA or in determining the specific degree of the disease [17]. Only a small part of the transcriptome encodes proteins and the rest belongs to the so-called non-coding RNA (ncRNA), which is not translated into proteins in the translation process [18]. One of many types of such ncRNA molecules are miRNAs composed of 19-23 nucleotides. These molecules can bind partially complementarily to the 3'UTR of the target mRNA and thus regulate many biochemical reactions involved in the pathogenesis of several diseases [19]. The heterogeneity of lncRNA molecules is due to their size, which ranges from several hundred to several thousand nucleotides [20]. They play an important regulatory role in the processes of cell development, differentiation, proliferation, apoptosis and metabolism [21]. However, it seems that not their size but their secondary and tertiary structure are essential for the proper performance of the functions of these molecules. In recent years, miRNAs and lncRNAs have been among the most studied molecules in EVs in association with the research of potential diagnostic biomarkers of OA [20]. A recent study compared EV-associated miRNAs from serum and SF in OA patients [22]. There were observed 31 "upregulated" and 33 "downregulated" EV-associated miRNAs in SF compared to serum (Fig.1).
Confirmation of the theory that serum EVs do not copy SF-derived EVs is of great importance for the correct optimization of OA diagnostics in the future. Xie et al. demonstrated significantly higher levels of free miR-210 in the SF of OA patients compared to the control sample regardless of disease stage [23]. The analysis of miR-210 revealed an association of this miRNA with VEGF. Supported angiogenesis may be a potential mechanism by which miR-210 contributes to the development of OA. Therefore, miR-210 appears to be a potential diagnostic biomarker in the early stages of OA [23]. Levels of six miRNAs (miR-23a-3p, miR-24-3p, miR-27b-3p, miR-29c-3p, miR-34a-5p and miR-186-5p) were significantly higher in SF of patients with late OA compared to patients with early-stage OA, regardless of age, gender and BMI. In contrast, some miRNAs (miR-27a-5p, miR-329, miR-655, miR-708-3p and miR-934) were significantly lower at end-stage OA compared to early OA [24]. It is also interesting that changes in miRNA in OA patients also occur depending on the patient's gender. Women have a significantly higher risk of formation and development of OA compared to men [25]. The estrogen signaling pathway is known to be directly involved in the pathogenesis of OA in women [26]. Levels of some EV-associated miRNAs (miR-181d-3p, miR-155-3p, miR-185-5p, miR-3940-3p, miR-4532, miR-7107-5p, miR-504-3p, miR-320d, miR- 19b-3p and miR-22-3p) were increased in SF in female OA patients [27]. After the estrogen treatment process, the levels of these miRNAs decreased. On the other hand, the levels of some miRNAs (miR-24-3p, miR-26a-5p, miR-200a-3p) increased after this treatment. Results show that the hormone estrogen has a significant effect on the composition of EV-associated miRNAs in SF. As estrogen levels in postmenopausal women drop significantly, the composition of miRNAs in EVs is significantly affected, which increases the chance of OA formation and development [27]. miRNAs and lncRNAs are involved in the regulation of expression of downstream genes [17]. The interaction between these two types of RNA plays an important role in the development of OA (Fig. 1). Studies have confirmed the presence of significantly higher levels of EVs in the early and late phases of OA compared to controls [28]. At the same time, they also revealed significantly higher expression of EV-associated lncRNA PCGEM1 in the late OA phase compared to early OA and also the higher expression of this lncRNA in early OA compared to the control group [28]. Work that sought to elucidate the functions of non-coding RNAs in the pathogenesis of OA confirmed higher expression of 52 lncRNAs and lower expression of 144 lncRNAs derived from SF EVs of OA patients compared to controls [29]. lncRNA FOXD2-AS1 promotes chondrocyte proliferation and inhibits OA development via the miR-27a / TLR4 pathway [30]. Wang et al. confirmed that the level of this lncRNA was low in OA patients, suggesting its inhibitory effect in the OA process [30]. lncRNA CIR promotes apoptosis via the miR-130a / Bim pathway and inhibits miR-27b expression, thereby degrading the extracellular matrix. Regulation of miR-149 expression is provided by PVT1 lncRNA. The process of regulating the expression of this miRNA affects the degradation of the extracellular matrix, the inflammatory response and apoptosis [31]. The diagnostic potential of these molecules is obvious, but it needs to be verified by several studies that would confirm their ability to accurately distinguish between a pathological condition and a healthy individual.
Cytokines present in SF
The presence and level of cytokines also vary with the duration and degree of OA [33]. Cytokines enter anabolic and catabolic processes, especially in tissues that are subject to high mechanical stress. As a result of the imbalance of these processes, there is a progressive degeneration of the articular cartilage, which plays a key role in the biomechanics of each joint. This leads to the development of a difficult-to-interrupt disease process, which involves inflammatory, degradation and production processes, which together lead to a gradual loss of joint function and pain [34]. Due to the effect that cytokines have within OA, they are divided into pro-inflammatory and anti-inflammatory. Inflammation has been reported to activate macrophages, which regulates the secretion of pro-inflammatory cytokines and enzymes [35]. EVs isolated from the SF of the affected joint of OA patients are able to stimulate macrophages to produce inflammatory cytokines, chemokines and metalloproteinases causing cartilage degradation. This ability indicates the crucial regulatory role of EVs in the OA process. Thus, they are a potential tool in the effort to alter the inflammatory microenvironment that occurs in OA. Fell and Jubb first confirmed in vitro that certain metabolites (at which time they could not determine exactly) were likely to act as regulators of chondrocyte function. They did this by co-cultivating a healthy synovial membrane with parts of the cartilage. They observed the degradation of the extracellular matrix by the products of the respective chondrocytes and, based on these findings, considered that the synovial membrane was likely to produce a factor that causes this degradation [36]. It is now known that elevated levels of cytokines (IL-1, TNF-α, IL-6, etc.) disrupt joint homeostasis in OA [37]. Up to date, it is not known exactly which cell type is the specific source of the cytokine IL-1, considered to be one of the strongest initiator of cartilage degradation in the OA process. Together with other cytokines, they are found in the SF of OA patients as well as in the synovial membrane at the early stage of OA. The mechanism of action of IL-1 in chondrocytes is that its precursor is transferred from the cytoplasm to the cell nucleus, where it activates the transcription of pro-inflammatory genes. The release of intracellular IL-1 into the extracellular space occurs after chondrocyte death. IL-1 is thus able to affect the activity of the same chondrocyte (autocrine) or adjacent chondrocytes (paracrine). Another pro-inflammatory cytokine involved in cartilage degradation in OA is the tumor necrosis factor α (TNFα). It has similar effects on chondrocytes as IL-1. It stimulates the production of cartilage matrix-degrading proteinases and suppresses the synthesis of proteoglycans and collagen type II. Interestingly, while IL-1 alone is much more effective in initiating cartilage destruction compared to TNFα, the synergy of these two cytokines results in much more extensive tissue damage [38]. TNFα can affect the production of other cytokines, such as interleukin-6 (IL-6). IL-6 is a pro-inflammatory cytokine whose levels increase in several inflammatory diseases. It is produced by several cell types (T and B cells, monocytes, fibroblasts, osteoblasts and Hoff's fat adipocytes). It stimulates synoviocyte proliferation and osteoclast activation, leading to the production of matrix metalloproteinases responsible for chondral tissue destruction [39].
Cytokines are not only found in SF as free ly detectable molecules (free cytokines) but are also widely present in EVs (EV-associated cytokines). The levels of free cytokines IL-1β, IL-17, IL-10 and INF-γ present in the SF of patients in late-stage OA were significantly higher compared to the levels of cytokines in patients in early stage OA. The profile of EV-associated cytokines had a similar level trend depending on the stage of OA [40]. SF-derived EVs can "induce" inflammatory cells and have a negative effect on the formation of chondral tissue, thus directly contributing to the degeneration of articular cartilage.
Conclusion
Although the diagnostic of OA (including visualization methods and subjective evidence of pain by the patient) is a standard and common process, it is necessary to present the patient with a form of more accurate and especially early diagnostic of this disease. OA is a disease of the whole joint that affects the cartilage, subchondral bone and synovium. The microenvironment in such a pathological joint is full of inflammatory cells, which also communicate with each other through signaling nanoparticles - EVs. This process affects adjacent tissues and cells and disrupts the integrity of the whole joint. Nucleic acids (miRNA or lncRNA) and proteins (cytokines, chemokines, enzymes) of SF-derived EVs have potential regulatory effects in the pathogenesis of OA and presumably participate in the basic mechanisms of disease development and reflect the severity of the disease. These properties predispose EVs as a source of early and reliable diagnostic biomarkers in monitoring OA progression. However, for better management of patients with OA, further research efforts and clinical studies are needed to gain a deeper understanding of the function and composition of SF biomarkers.
Acknowledgements
This publication is the result of the project implementation: “Open scientific community for modern interdisciplinary research in medicine (OPENMED)”, ITMS2014+: 313011V455 supported by the Operational Programme Integrated Infrastructure, funded by the ERDF. This research was also supported by the Slovak Research and Development Agency under the contract No. APVV-17-0118.
Funding
This publication is the result of the project implementation: “Open scientific community for modern interdisciplinary research in medicine (OPENMED)”, ITMS2014+: 313011V455 supported by the Operational Programme Integrated Infrastructure, funded by the ERDF. This research was also supported by the Slovak Research and Development Agency under the contract No. APVV-17-0118 and the Internal Scientific Grant System VUaVP35 UPJŠ No. vvgs-2022-2186.