Current Models for Development of Disease-Modifying Osteoarthritis Drugs

Abstract

Osteoarthritis (OA) is a painful and disabling disease that affects millions of people worldwide. Symptom-alleviating treatments exist, although none with long-term efficacy. Furthermore, there are currently no disease-modifying OA drugs (DMOADs) with demonstrated efficacy in OA patients, which is, in part, attributed to a lack of full understanding of the pathogenesis of OA. The inability to translate findings from basic research to clinical applications also highlights the deficiencies in the available OA models at simulating the clinically relevant pathologies and responses to treatments in humans. In this review, the current status in the development of DMOADs will be first presented, with special attention to those in Phase II–IV clinical trials. Next, current in vitro, ex vivo, and in vivo OA models are summarized and the respective advantages and disadvantages of each are highlighted. Of note, the development and application of microphysiological or tissue-on-a-chip systems for modeling OA in humans are presented and the issues that need to be addressed in the future are discussed. Microphysiological systems should be given serious consideration for their inclusion in the DMOAD development pipeline, both for their ability to predict drug safety and efficacy in human clinical trials at present, as well as for their potential to serve as a test platform for personalized medicine.

Impact statement

At present, no disease-modifying osteoarthritis (OA) drugs (DMOADs) have been approved for widespread clinical use by regulatory bodies. The failure of developing effective DMOADs is likely owing to multiple factors, not the least of which are the intrinsic differences between the intact human knee joint and the preclinical models. This work summarizes the current OA models for the development of DMOADs, discusses the advantages/disadvantages of each, and then proposes future model development to aid in the discovery of effective and personalized DMOADs. The review also highlights the microphysiological systems, which are emerging as a new platform for drug development.

Burden of Osteoarthritis

Osteoarthritis (OA) is a progressive and debilitating disease that is a major cause of disability and reduced quality of life for patients worldwide.¹ According to the Centers for Disease Control (2015), there are currently 32.5 million adults in the United States who suffer from OA. The majority of these cases occur in adults over the age of 45, with women at higher risk²; these numbers are expected to increase because of the aging population and prevalence of obesity.³ Around 85% of reported cases occur in the knee, but the hip, hands, feet, and ankle exhibit OA as well.^2,4 OA not only limits physical activity, but can increase social isolation, adding to psychological stress and resulting in depression.^5,6 Furthermore, memory loss can occur in conjunction with pain related to OA.^7,8 As OA progresses, so does the economic impact associated with health care costs and decreases in productivity.^2,9

Symptom management strategies primarily target pain and include topical and oral nonsteroidal anti-inflammatory drugs, intra-articular corticosteroid and hyaluronate injections, and ultimately oral opioid analgesics. However, these drugs do not slow the progression of OA, and all are associated with potential side effects.¹⁰ This leaves surgery, in the form of total joint arthroplasty (TJA), as the only long-term solution for most patients. The challenge with TJA is that it involves a significant surgical procedure associated with a relatively long recovery trajectory. The artificial joints have a finite lifespan, and revision joint replacement is often more complicated than the initial TJA. In addition, up to 20% of patients undergoing knee TJA are still in pain 1 year after surgery.¹¹ Thus, there is an urgent need for disease-modifying osteoarthritis drugs (DMOADs). In Table 1, agents in Phase II–IV OA trials listed in clinicaltrials.gov are presented, including symptom-alleviating compounds and potential DMOADs. Some of the agents, in particular Lorecivivint (SM04690, a selective Wnt pathway inhibitor) and Spriferimin (fibroblast growth factor 18), have recently shown some efficacy in treating OA in Phase II studies.^12–14 However, at this time, no DMOADs have been approved for widespread clinical use by regulatory bodies in either the United States or Europe. The aim of this review was to summarize the current models of OA, discuss the advantages/disadvantages of each, and then propose future model development to aid in the discovery of effective DMOADs.

Table 1.

Potential Disease-Modifying Osteoarthritis Drugs That Are Recently in Phase II–IV Clinical Trials (Data from clinicaltrials.gov, Up To September 30, 2020)

Drug name	Function/Target	Phase	Reference
AS902330	Anabolic factor	2	NCT01919164
Oral salmon calcitonin	Anabolic factor	3	NCT00704847¹⁵
Cingal	Anabolic factor	3	NCT04231318
Spironolactone	Anti-pro-inflammatory cytokines	4	NCT02046668
Artrodar	Anti-inflammatory agent	3	NCT04318041
Colchicine	Anti-inflammatory agent	4	NCT03913442
Resveratrol	Anti-inflammatory or anti-ageing agent	3	NCT02905799
ABT-981	Ant-IL-1α/β	2	NCT02384538¹⁶
metHuIL-1ra	Anti-IL-1α	4	NCT00111410
Canakinumab	Anti-IL-1β	3	NCT02396212^17,18
Tocilizumab	Anti-IL-6R	3	NCT02477059
Curcumin	Anti-inflammatory agent	3	NCT03715140
Crocin	Anti-IL-1β, 4, 10, 17	3	NCT03375814
Adalimumab	Anti-TNF-α	2/3	CT200600092571¹⁹
LY3016859	Anti-TNF-α	2	NCT04456686
GLPG1972	ADAMTS-5 inhibitor	2	NCT03595618
Doxycycline	MMP inhibitor	2/3	NCT03115177²⁰
BAY129566	MMP-13 inhibitor	2
MK0822	Anti-CatK	3	NCT01803607
MIV-711	Anti-CatK	2	NCT03037489
SM04690	Wnt pathway inhibitor	2	NCT02536833¹²
Strontium ranelate	Bone resorption inhibitor	2	NCT0393751²¹
SD-6010	iNOS inhibitor	3	NCT00565812²²
CNTX-4975-05	TRPV1 receptor	4	NCT03576508
LY2951742	Anti-CGRP	2	NCT02192190²³
GW842166	Cannabinoid receptor 2 agonist	2	NCT00479427
AF-219	P2X3R antagonist	2	NCT01554579
PF-04457845	FAAH inhibitor	2	NCT00981357
Sprifermin	Recombinant FGF-18	2	NCT01919164^13,14
Duloxetine	CNS reuptake inhibitor	2	NCT04224584

The studies that were completed in recent 10 years are also included.

ADAMTS5, a disintegrin and metalloproteinase with thrombospondin motifs 5; CatK, cathepsin K; CGRP, calcitonin gene-related peptide; CNS, central nervous system; FAAH, fatty acid amide hydrolase; FGF, fibroblast growth factor; IL, interleukin; IL-1(6)R, interleukin-1 (6) receptor; iNOS, inducible nitric oxide synthase; MMP, matrix metallopeptidase; P2X3R, purinergic P2X3 receptors; TNF-α, tumor necrosis factor-alpha; TRPV1, transient receptor potential cation channel, subfamily V, member 1.

Pathology of OA in Knee Joints

The knee joint is a complex organ system composed of multiple tissue elements that together contribute to its overall functionality. The dynamic interactions between the tissue elements support the concept that OA is a “whole joint disease.”^24,25 There are at least six main tissue components within the knee joint: articular cartilage, subchondral bone, synovium, ligaments, menisci, and the infrapatellar fat pad (IPFP).^26,27 Of these, pathological changes in cartilage, bone, and synovium have received the most intensive study. These joint components are also the primary targets for current DMOAD delivery (Fig. 1).

FIG. 1.

OA-associated histopathological changes in joint elements, and representative agents that target different pathological issues. OA, osteoarthritis. Color images are available online.

Cartilage is a hyaline, aneural, and avascular tissue with chondrocytes embedded in abundant extracellular matrix (ECM) consisting of type II collagen and sulfated proteoglycans.²⁸ The cartilage ECM functions to maintain frictionless contact of the synovial joint and supports mechanical loads and forces to which the knee is subjected.²⁸ Chondrocytes are the primary cell type of the cartilage that regulate its architecture and biochemical composition.^24,29 In a healthy joint, chondrocytes are in a quiescent state and maintain the homeostasis of cartilage.^25,30 However, under OA-like conditions, chondrocytes are “activated,” leading to the secretion of cytokines including interleukin (IL)-1, IL-4, IL-9, IL-13, and tumor necrosis factor-alpha (TNF-α),¹⁰ which are accompanied by degradative enzymes including disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS), and collagenases/matrix metalloproteinases (MMPs).^25,31 The degradation of cartilage represents the most critical sign of OA.

Another essential component of the knee is the synovium. This fluid-secreting capsular tissue functions to lubricate and nourish the cartilage it encases.³² The intra-articular side of the synovium surface is primarily composed of two types of synoviocytes: fibroblast- and macrophage-like cells.^26,32 The fibroblast-like synoviocytes produce proteoglycans of the synovial ECM, such as hyaluronan (HA), which help to maintain synovial health.^32,33 The macrophage-like synoviocytes remove tissue debris and are involved in the innate immune activation of the synovium during inflammation.^32,33 In particular, cartilage degradation products can stimulate the synovium and induce the activation and migration of inflammatory cells, which produce and release cytokines and other substances mentioned previously.^32,34 As inflammation within the synovium (synovitis) progresses, vascular endothelial growth factor is secreted by synovial macrophages and stimulates increased vascularization within the synovium and potentially vascular invasion of the cartilage.^33,34 This increased vascularization also occurs in the subchondral bone as well and will be discussed later.

The synovium also plays a role in the structure and function of the IPFP, by forming the lining of the IPFP.³² There is increasing evidence that the IPFP might also play a role in the progression of OA through the release of adipokines and cytokines from adipocytes that drive inflammation, a process presumably exacerbated in obese OA patients.³⁵ The level of inflammation observed in the IPFP and in the synovium are indicators of disease progression and are often used as a predictor of pain.²⁶

The subchondral bone is a distinct and essential component of the knee that is integrated with cartilage to form the osteochondral unit. With a mineralized ECM composed primarily of type I collagen, the subchondral bone has a distinct separation point with the cartilage called the tidemark, which delineates the calcified cartilage from the noncalcified cartilage.^33,36 During OA, the tidemark moves into the noncalcified zone.³³ In addition, subchondral bone remodeling occurs between the calcified cartilage and the subchondral bone resulting in the formation of bone spurs, also known as osteophytes.^24,31 These osteophytes play a role in the increase of pain caused by OA owing to the innervation of the bone.³⁷ In addition, the development of cysts and bone marrow lesions/edema, a clinical finding on magnetic resonance imaging (MRI), occurs in the subchondral bone. These sources of fluid buildup are thought to be a significant source of pain and are a central feature of OA.³⁷

The meniscus has an integral role in mechanical loading and shock absorption of the knee. Like cartilage, the meniscal ECM contains water, multiple collagen types, specifically type I collagen, and proteoglycans.³⁸ Prior trauma to the meniscus can lead to the onset of OA and is considered a significant risk factor for OA.³⁹ However, in OA patients, damage to the meniscus can result in degradation because of the release of inflammatory cytokines produced by the synovium and cartilage.⁴⁰ If mechanical trauma causes meniscal ECM degradation, such as loss of collagen, the resulting forces are then allocated to the cartilage owing to the loss of meniscal integrity; this in turn causes chondrocytes to produce inflammatory factors that result in further destruction of the meniscus, thus leading to the potential onset of OA.^27,40

In addition to the tissues already discussed, other joint components, including muscle, intra-articular ligaments, and tendons also contribute to normal joint function, physiology, and OA pathogenesis. For example, trauma to the ligaments can cause bleeding, tissue degradation, and structural instability resulting in inflammation; these injuries are predisposing factors for OA.⁴¹ Furthermore, these tissues have major biomechanical functions and their injuries, caused by abnormal mechanical loading, can eventually impact cartilage and bone, leading to joint diseases.⁴²

Current OA Models

There are a variety of models currently used to develop drugs for the treatment of OA.⁴³ In this section, we briefly describe the most common models and focus on how they are used for OA pharmaceutical development. It should be noted that treatment with IL-1β, commonly 10 ng/mL, is the most widely used method to generate OA-like phenotypes in various cell and explant cultures. However, it has been shown that in the OA knee joint, the average level of IL-1β is ∼20–30 pg/mL,⁴⁴ which is markedly lower than that used in many in vitro studies. Furthermore, most of the conventional OA in vitro and ex vivo models focus solely on cartilage, which fails to recapitulate the whole-joint nature of this disease. Therefore, any data generated with these models usually need to be re-evaluated in more physiologically relevant models, such as in vivo animal models or in vitro microphysiological systems (MPSs), which will be elaborated hereunder.

In addition, different in vitro culture methods result in different cell morphology, which has been shown to directly regulate chondrocyte phenotype. Typically, cells in monolayer culture and in the peripheral area of micromass cultures display a flat and well-extended shape, whereas in the center area of micromass culture, pellet culture and in-scaffold culture, cells adopted a sphere morphology. At present, it has been demonstrated that forcing chondrocytes to become round shape, such as in-agarose culture, can promote the expression of chondrogenic genes, which may function through modulating RhoA pathway and changing cytoskeletal structure.^45–48

Monolayer cultures

Monolayer or two-dimensional (2D) culture cultures allow for the most convenient testing of therapeutics. The advantages of 2D culture include easy handling, need of a relatively low number of cells, and convenient experimental endpoints and analysis. Regarding the culture of chondrocytes, 2D culture was the first method used to study this cell type >50 years ago.⁴⁹ Overall, monolayer cultures of chondrocytes have greatly facilitated the understanding of chondrocyte phenotype, differentiation, the effects of cytokines and inflammation, and the alterations caused by exposure to growth factors.⁵⁰ For example, the 2D culture of chondrocytes permits the top surface of the cells to be exposed to inflammatory cytokines, such as IL-1β, in an effort to understand the consequences of their associated downstream inflammatory pathways on cartilage.⁵¹ Koshy et al. used monolayer culture to pinpoint degradative mediators of cartilage degradation,⁵² whereas Pearson et al. used this method to observe and clarify the differences in IL-6-mediated inflammation in obese versus nonobese OA patients.⁵³ Other research groups have used monolayer culture methods to study the role of synovium in OA.^54,55

Two-dimensional cultures have been used to investigate plant extract-derived polyphenols to assess their anti-inflammatory potential in treating OA.^56,57 For example, curcumin displayed anti-inflammatory activity in liposaccharide treated chondrocyte cultures.⁵⁸ Zheng et al. found that the administration of plumbagin, a compound that can be extracted from the roots of herbal therapeutics, to human chondrocytes in vitro successfully inhibited IL-1β inflammatory effects through the suppression of nuclear factor kappa beta (NF-κβ),⁵⁶ an inflammatory transcription factor responsive to the cytokines IL-1β and TNF-α.⁵⁹ More recently, curcumin, resveratrol, and epigallocatechin-3-gallate were shown to inhibit the production of reactive oxygen species and nitric oxide in the 2D culture of bovine and human chondrocytes, which implied their potential therapeutic values for OA clinical application.⁶⁰ A small-molecule inhibitor of the Wnt pathway was examined in 2D chondrocyte culture and it was shown to enhance chondrocyte differentiation and suppress degradation.⁶¹ These results suggested that this compound might function as a novel DMOAD. Numerous miRNAs have also been studied using monolayer cultures to test their ability to inhibit inflammation.⁶²

Although monolayer culture protocols have aided with the testing of new DMOADs and the analysis of mechanistic pathways, there are significant disadvantages with their application for the study of OA. The knee is constantly subjected to loads and mechanical forces, which are nearly impossible to simulate in most monolayer cultures.⁶³ Cyclic tensile strain (CTS), a process that stretches the cell body through deforming the culture substate, has been explored to overcome this limitation. For example, Du et al. applied CTS on chondrocyte monolayer cultures and found that TRPV4-mediated Ca²⁺ signaling played a central role in the response of chondrocytes to physiologic levels of strain (3% and 8% of strain), whereas Piezo2-mediated Ca²⁺ signaling was central to injurious levels of strain (18% of strain).⁶⁴ In addition, CTS has been used to investigate diacerein, a potential DMOAD, on monolayered cultured OA chondrocytes, as well as explore its interaction with mechanotransduction pathways.⁶⁵

Chondrocytes in monolayer cultures also undergo dedifferentiation, resulting in the loss of type II collagen and aggrecan, and an increase of type I collagen and versican, thus altering the composition and natural structure of the ECM.^63,66 Proteoglycans are also decreased with the dedifferentiation.^67,68 The degradation of the natural ECM in the synovial joint is a primary factor in the progression of OA, and an accurate model of ECM degradation is imperative for the proper formulation of anti-inflammatory therapeutics.⁶⁹ Another issue with monolayer culture is the technical challenge of replicating the interaction of different cell types. Therefore, modeling OA in 2D cultures alone is inadequate to elucidate the interactions of different tissues of the joint.

Micromass culture

Micromass is a three-dimensional (3D), high-density culture system consisting of cell aggregates formed by seeding cells in droplets.^70,71 Chondrocytes cultured as micromasses maintain higher levels of chondrogenesis⁷² and produce an ECM that is rich in cartilage-associated proteoglycans and collagen, compared with 2D cultures of the same cell types.⁷³ Researchers have determined that the micromass-derived cartilage constructs were more extensive, more homogenous, and had less hypertrophic and fibrous features compared with pellet cultures formed by centrifugation of a cell suspension (see Pellet culture section).⁷⁴ Thus, micromass culture has been widely applied for studying chondrocyte cell physiology, pathophysiological mechanisms, and cartilage degradation.^75,76 For example, Sun et al. recently used micromass culture to detect the effects of phosphocitrate, a potential DMOAD, on ECM production by OA chondrocytes.⁷⁷ A reliable assay system using micromass cultures of human chondrocyte line C-28/I2 was established by Greco et al. to demonstrate the modulatory functions of various pharmacological agents.⁷⁸

Although micromass is a classic in vitro culture model to generate cartilage tissue, it also has limitations. For example, chondrocyte micromass cultures maintained a differentiated phenotype up to 3 weeks, but culture durations longer than 6 weeks led to progressive dedifferentiation that should be considered during long-term evaluation.⁷⁹ In addition, the inability to study cell–cell and tissue–tissue interactions limits the application of the micromass culture system for understanding the pathogenesis of OA. These limitations call for more complex in vitro models.

Pellet culture

Another common method to create cartilage in vitro is the formation of chondrospheres or 3D cell pellets. Typically, these spheroids are generated by pelleting cells with centrifugation.^49,80 In contrast to monolayer or micromass culture, 3D pellets allow cells to proliferate in all directions to better mimic the native environment of cartilage. Pellet cultures result in more robust chondrocyte formation, as indicated by higher glycosaminoglycan (GAG)/DNA ratios compared with the monolayer cultures.⁸¹ The pellet culture model also allows the study of the cell–cell and cell–matrix interactions.^66,82

Cartilage tissue generated from pellet cultures has been widely used in assessing potential DMOADs. Ziadlou et al. used the pellet model to test plant-based anti-inflammatory and NF-κβ pathway inhibiting drugs.⁸³ Specifically, they introduced 34 traditional Chinese medicine compounds to pellet cultures of human OA chondrocytes and investigated their influence on the ECM production and the expression of MMPs. Several of these compounds were shown to elevate ECM production. In particular, epimedin C enhanced the expression of type II collagen and aggrecan, potentially restoring the matrix loss in OA cartilage.⁸³ Another study tested the effects of a traditional Persian material known as Mummy, recognized for its ability to reduce joint inflammation. Polymerase chain reaction analysis determined that upon treatment with Mummy, OA pellets exposed to IL-1β had increased gene expression of type II collagen and downregulated expression of proinflammatory factors.⁸⁴

Although many studies have shown that the application of 3D pellet cultures can generate data that 2D models cannot, such as the study of ECM abundance and composition, this method also has its limitations. For example, pellets cannot be subjected to physiologically relevant mechanical forces precluding the ability of using this natural stimulus to study the progression of OA.^82,85 Further engineering is thus needed to overcome some of these limitations of pellet cultures.

Three-dimensional scaffold cultures

Natural and synthetic materials have been used to construct 3D scaffolds for the engineering of different tissues. Hydrogels are commonly used to create cartilage tissue because of their inherent ability to retain the water, support cell proliferation and differentiation, and mimic native soft tissue.⁸⁶ Scaffold-based cultures may not only promote chondrogenesis, but also facilitate higher quality cartilage formation. For example, alginate beads were shown to yield more robust chondrogenesis compared with monolayer and pellet culture.⁸⁰ Chondrocytes derived from human mesenchymal stem cells (MSCs) displayed lower expression of hypertrophic and osteogenic genes in a hyaluronic acid hydrogel than in pellet culture.⁸⁷ Aside from maintaining chondrocyte phenotype, this culture method was also utilized to investigate the paracrine interactions between cells. For example, chondrocytes and macrophages were encapsulated in poly(ethylene glycol) diacrylate hydrogels, to better understand how macrophages alter the phenotypes of chondrocytes. In this study, the hydrogel network was tethered with the integrin-binding peptide, arginine–glycine–aspartic acid, to allow for cell–ECM crosstalk.⁸⁸ The use of scaffolds can also be used to simulate the physical properties of cartilage and thereby allow the assessment of the effects of DMOADs on the mechanobiological characteristics of cartilage.

Studies have used 3D culture of chondrocytes followed by the induction of OA for drug screening. Sun et al. successfully created a silk-based 3D engineered cartilage system and introduced inflammatory factors such as TNF-α and IL-1β to simulate an OA environment.⁸⁹ They have subsequently used this model for screening potential therapeutics. A collagen matrix laden with chondrocytes was used in another study that enabled the authors to assess the impact of incorporating platelet-rich plasma (PRP) on the inhibition of ECM loss.⁹⁰ The authors then used the same neo-cartilage to test the effects of hyaluronic acid and PRP on chondrocytes challenged with IL-1β.⁹¹ Other researchers have used this model to monitor changes in OA-related gene expression after drug treatment,⁹² to understand the effects of small molecule inhibitors on common cartilage degrading proteases (MMPs and ADAMTS),^93,94 and to determine how growth factors aid in the proliferation of chondrocytes in vitro.⁹⁵ 3D models have also been routinely used to assess the basis for the therapeutic efficacy of drugs such as FK506, originally thought to be a T cell suppressor, in the treatment of OA.^96,97

Scaffolds can also be used to deliver candidate drugs, thereby avoiding complications associated with repeated intra-articular injections. For example, a poly(lactic-co-glycolic acid) scaffold was used to encapsulate rapamycin, which allowed for a controlled release of rapamycin for several days.⁹⁸ This study also reported the first successful administration of rapamycin in microparticle form for the prevention of senescence and OA changes in chondrocytes exposed to an induced oxidative stress microenvironment.⁹⁸

A major disadvantage of the most widely used scaffold cultures is that they fail to fully simulate the biological cues of the native cartilage ECM to support chondrogenesis. In addition, cell–cell interaction is often lacking. These limitations require the further development of chondrosupportive biomaterials, as well as the optimization of cell encapsulation methods. For example, HA hydrogels, which were functionalized with N-cadherin mimetic peptides, promoted a more robust chondrogenesis of MSCs and cartilage matrix production, compared with HA hydrogels in which a scrambled peptide was included.⁹⁹ Attempts to increase the cell–cell interaction in scaffolds have also been reported. For example, Rogan et al. generated an MSC-based μPellet (∼100 cells/pellet) before encapsulating them into a scaffold. However, this approach resulted in less chondrogenesis than when single cells were encapsulated into a scaffold.¹⁰⁰

Explant cultures

Also known as ex vivo cultures, tissue explants are considered the most natural DMOAD model compared with other in vitro cultures. Tissue explants are composed of tissue-specific cells that reside within the native ECM. They have therefore been used to study the cell–cell and cell–matrix interactions that occur within the native cartilage tissue.^66,101 More importantly, explant cultures largely retain the native mechanical properties of tissues, and therefore are particularly useful in studying the role of mechanical loads in OA onset and progression. However, tissue explants tend to have a short life span, exhibiting tissue death along the outer edge of the explant, likely owing to the injury from the harvesting process.^82,85 Therefore, they are not ideal for long-term studies. Potentially more problematic is that once removed from the donor, cell phenotypes start to change.⁸⁵ Furthermore, although this model might be inexpensive, access to tissue donors can be difficult and there may be considerable variability among different donor sites and donors.^82,85

Knee joint components are known to respond to mechanical cues, and therefore explant cultures are commonly subjected to different loading protocols to determine how mechanical load affects the physiology of the knee.⁸⁵ Both static and dynamic compression methods are used.¹⁰² For example, the drop-tower protocol, in which a free weight is released at a specific height and dropped onto the tissue to simulate a single impact load, has been used, and other methods such as hydraulic loading chambers have also been used to apply load in a cyclic manner.⁸⁵ Alexander et al. developed a spring-loaded system with spherical impact geometry to assess the effects of mechanical injury on the cell–cell interactions, ECM formation, and overall cell viability.¹⁰³ Dolzani et al. used a compression-inducing bioreactor to simulate physiological mechanical forces encountered by joint tissues. In this study, cartilage explants were loaded between two compression plates. A pressurized air system was used to reduce the distance between the plates, thus applying an unconfined compression to the explants.¹⁰⁴ Finally, Cutcliffe and DeFrate used explants to determine whether or not unloading/recovery response of cartilage after mechanical load could be used to replace the load response when used in in vivo models using MRI.¹⁰⁵ Thus, the use of explants for mechanical loading provides valuable information on how native cartilage responds to physical damage.

Explants of other knee joint elements have also been used to study their interaction with cartilage. Osteochondral explants from OA donors might be valuable for testing DMOADs. Geurts et al. observed that human explant specimens were capable of maintaining viability and undergoing an inflammatory response after TLR4 agonist exposure.¹⁰⁶ Nishimuta et al. showed that healthy IPFP explants promoted GAG production in cartilage explants.¹⁰⁷ In another study, He et al. demonstrated that conditioned medium from IPFP (FP-CM) aggravated GAG release in mechanically traumatized cartilage but did not significantly affect healthy cartilage.¹⁰⁸ FP-CM also enhanced the gene expression of cyclooxygenase-2, inducible nitric oxide synthase, and IL-6 in traumatized cartilage explants, compared with the nonconditioned medium. Of importance, they found that IL-6 was a crucial tissue degeneration mediator.

Synovium explants have also been used to research the pathophysiology of OA and test potential therapies. Synovial explants collected from OA patients have been used to test the anti-inflammatory and anti-catabolic, paracrine effects of MSCs.¹⁰⁹ When mechanically injured bovine cartilage was cocultured with bovine synovium/joint capsule (SJC) explants, the presence of SJC resulted in earlier aggrecan proteolysis and the release of additional types of aggrecan fragments, indicating the involvement of synovium-secreted molecules in the cleavage of cartilage aggrecan.¹¹⁰ Beekhuizen et al. cocultured synovium and cartilage from OA donors and evaluated several outcome parameters, such as GAG release and content, MMP activity, and cytokine production.¹¹¹ This model was proposed to assess the effect of potential OA therapies. In fact, a bovine synovium–cartilage coculture model has been used to study the possible protective effects of IL-1 receptor antagonist (IL-1Ra) against catabolic activities in the cartilage explants induced by the proinflammatory cytokine IL-1α.¹¹² Of interest, cartilage catabolism could be more effectively suppressed by IL-1Ra addition in the presence of synovial explants.¹¹² In human articular cartilage–synovium cocultures, IL-1β-induced degradation of cartilage proteoglycans could be blocked by the selective cyclooxygenase 2 inhibitor, SC-236, suggesting the potential of this small molecule to inhibit cartilage degeneration.¹¹³

The meniscus has a key biomechanical role of load distribution and shock absorption, and meniscal damage is frequently observed in osteoarthritic knee joints.¹¹⁴ To understand the involvement of traumatic meniscus injury in OA pathogenesis, Nishimuta and Levenston¹¹⁵ applied confined compressive overload on bovine meniscus explants and observed biological damage of the tissue even without obvious macroscopic injury. The authors also established a meniscus–IPFP coculture model, where the IPFP displayed a modulatory role in the metabolism of GAGs in the meniscus explants.¹⁰⁷ Gupta et al.^116,117 stimulated porcine menisci with pathological overloading, which was found to upregulate the expression of major inflammatory and degenerative genes and increase the release of nitric oxide and GAGs. Models involving meniscus explants have been used to test several potential therapies for joint diseases, such as PRP,¹¹⁸ insulin-like growth factor-I,¹¹⁹ transforming tissue growth factor β3 (TGF-β3),^120,121 TGF-β1,¹¹⁹ basic fibroblast growth factor,¹¹⁹ connective tissue growth factor,¹²⁰ and platelet-derived growth factor-AB.¹¹⁹ What is clear from these studies is that the clinical relevance of meniscus explant-based in vitro models used to study joint pathophysiology is highly dependent on the recapitulation of tissue crosstalk between the meniscus and other joint components such as the articular cartilage, IPFP, and synovium. Future in vitro studies using meniscus explants would benefit from including multiple joint tissues.¹²²

Animal models

Given that the complex physiology of the knee joint has not been fully recapitulated in vitro, researchers often use in vivo animal models of OA. The stifle is the primary joint targeted for OA studies in animal models.^40,123 A number of models are widely used and have yielded valuable information regarding the onset, signs, and progression of OA.¹²⁴ These models are also widely used to investigate the safety and efficacy of therapeutic interventions of OA.¹²⁵ There are a variety of small and large animal models of OA. Small animals such as rodents (mice and rats), rabbits, and guinea pigs are used because of their ready procurement, rapid OA progression, and ease of handling.^43,126 However, these models may not accurately recapitulate the anatomy or physiology of the human knee joint. Although large animals such as dogs, horses, and sheep are used to address this issue, they are more expensive, difficult to work with, and tend to develop OA more slowly than the small animal models.⁴³

As summarized in Table 2, several methods are commonly used to create OA in animals. Surgical methods are commonly used to create mechanical instability and induce OA development and progression.^123,124,127 Vincent suggested that research in surgical preclinical OA models aligns well with findings in clinical trials.¹²⁸ Destabilization of medial meniscus is one of the most studied methods to create OA in rodents.¹²⁹ In these models, the meniscus is surgically injured, although the surrounding ligaments can also be damaged.¹²³ Another model that is commonly used is anterior cruciate ligament (ACL) transection, in which the ACL is transected and causes instability of the joint.¹³⁰ Injury to the joint stimulates OA onset by the effect of inflammatory factors.

Table 2.

Current Osteoarthritis Animal Models

Methods	Examples	Animal model used	Advantages	Disadvantages
Surgical	Meniscal tear, total meniscectomy, DMM, ovariectomy, ACL transection, articular groove^126,137	Mouse, rat, guinea pig, rabbit, dog, horse	It allows for rapid disease induction and there is less phenotypic variability. These show mechanical onset of OA rather than a genetic change of OA^123,126	Not an optimal technique for the study of the pathogenesis of OA¹²³
Chemical	MIA, papain, collagenases.¹²⁶	Mouse, rat, guinea pig, rabbit, dog, horse	MIA is commonly used to study pain.¹²⁷ Intra-articular injection is less invasive and allows for rapid progression of OA^123,137	Injection of these chemicals does not properly recreate the pathogenic effects of naturally occurring OA in humans^123,137
Spontaneous (genetic)	Occurring naturally in the animal¹²⁷	Dog, guinea pig, mouse^{124–127,138}	This type of model allows for the observation of OA progression from the onset to the final stages^126,137	This model can be time-consuming and expensive.^123,126,137 The variation among animals can be large
High-fat diet	Exposure of animals to a high-fat diet, to study the metabolic profile of the synovial joint^139,140	Mouse, rat,¹⁴⁰ rabbit¹⁴¹	High-fat diets provide information about how the metabolic effects of obesity contribute to OA¹⁴¹	Most high-fat models focus on small animals, and are thus physiologically different from humans
Noninvasive loading	Noninvasive models use surgical techniques to induce a mechanical load	Rabbit, mouse¹⁴²	Noninvasive injury models are aseptic and useful for the avoidance of contamination. These models are used for studying the initiation of OA¹³⁶	Microsurgery is necessary for this technique, which requires the ability to perform surgical measures on small animals¹⁴²

ACL, anterior cruciate ligament; DMM, destabilization of medial meniscus; MIA, monosodium iodoacetate; OA, osteoarthritis.

Chemical induction of OA is also widely used, where chemicals are introduced to the intra-articular surface that impact the homeostasis of the joint, leading to the release of inflammatory cytokines.¹²⁷ Common chemicals used include monosodium iodoacetate (MIA), papain, and collagenases.^123,126 MIA inhibits chondrocyte function by halting the process of glycolysis, leading to chondrocyte apoptosis, inflammation, and the onset of OA.^123,127 In addition, there are spontaneous cases of OA, owing to the genetics of the animal; this is common in dogs and guinea pigs. Recently, inspired by the link between obesity and OA,¹³¹ high-fat diet-induced OA models have also been developed. The contribution of adipose tissue to OA has been shown in animal models.^132–134 Serum levels of adipose-derived cytokines are elevated in OA patients, suggesting that metabolic disruption of adipose tissue may play a role in the severity and progression of OA.¹³⁵ Finally, to avoid the confounding effects because of the surgical/invasive injury procedure itself, noninvasive injury methods through mechanically inducing a joint injury externally have also been used in creating OA models.¹³⁶ This type of model facilitates the study of early adaptive processes at the time of injury, thus may be more representative of post-traumatic OA in humans.

The choice of an animal model and method of creating OA is based on the specific etiology and the purpose of the study.⁴³ Although there are numerous animal models to choose to study therapeutic efficacy and OA progression, it is still difficult to ascertain whether these models accurately simulate OA in human joints.

MPSs to simulate knee joint in vitro

MPSs, also called tissue/organ-on-a-chip, are emerging as a new platform for drug development.^143,144 The primary endpoint for tissue-on-a-chip technology is to offer a system that simulates the in vivo microenvironment characterized by diverse cellular composition, tissue-specific ECM, and interactive physiological biochemical and physical signals.¹⁴⁵ By using human cells and integrating multiple tissues, it may be possible to partially overcome the limitations of current animal models and in vitro culture assays.^49,146 Therefore, researchers are attempting to develop MPS that replicates the knee joint using human cells.

Although the “joint-on-a-chip” concept has been coined,^1,49,146 the successful generation of such systems has not yet been reported. As mentioned previously, OA is considered a whole joint disease.¹ The multiple tissue types involved in the synovial joint require the creation of a microenvironment that is able to mimic the joint as a whole. Given the unique anatomical structure of the knee joint and its complex mechanical motion, in vitro knee joint simulation poses a technical challenge. Many MPS models are in the early stages of development, focusing on a single cell type. However, a few MPS that incorporate multiple cell lines have been developed.¹ In 2014, our team constructed, for the first time, an osteochondral tissue chip derived from human MSCs,¹⁴⁷ which has recently been expanded by using induced pluripotent stem cells as the constituent cell source.¹⁴⁸ Recently, the development of a polydimethylsiloxane-based cartilage-one-a-chip by Occhetta et al. focused on the mechanical compression of chondrocytes for simulating the effects of mechanical loading.¹⁴⁹

Although joint-on-a-chip technology holds tremendous promise, there are still several conceptual and technical barriers. For example, it is unclear how best to model the local and systemic influences on tissue properties, including physical and chemical signals (Fig. 2). Nevertheless, similar to the development of other tissue/organ chips,^149–152 engineering a knee joint to fully recapitulate the native counterpart may not be necessary. That is, it may only be necessary to recapitulate select essential aspects of the organ physiology and diseases, and then use this model to generate new information on the screening of new drugs for safety and efficacy in humans.¹⁵¹

FIG. 2.

Generation of knee joint MPS through integrating individual tissue modules. Each tissue is perfused with the tissue-specific medium on one side and the “synovial fluid” on the other side, which is shared by all tissues except bone. The flow of the “synovial fluid” is bi-directional so that it can be conditioned and sensed by all tissues, simulating their crosstalk in the native knee joint. The inclusion of patient-specific cells allows the generation of personalized chip and the development of personalized DMOADs. The biomarkers in the “synovial fluid” are used to assess the types and severity of OA, as well as inform the treatment efficacy. DMOAD, disease-modifying osteoarthritis drug; MPS, microphysiological system. Color images are available online.

In summary, despite the multiple clinical trials that have been reported to date, many of the drugs that showed promising results in preclinical models have failed to demonstrate efficacy in OA patients. This failure rate is likely because of multiple factors, not the least of which are the intrinsic differences between the intact human knee joint and the preclinical models used to identify putative therapeutic targets and screen for efficacy.¹⁵³ The significance of these deficiencies was succinctly stated by Malfait and Little, who concluded that current preclinical OA models were poor predictors of the outcomes of clinical trials.¹³⁸ Therefore, identification of a relevant preclinical model would facilitate a clearer understanding of the drug mechanisms, safety and efficacy in OA before human studies and could potentially minimize the loss of valuable time and costly resources.

Conclusion and Future Perspectives

The current lack of robust, scalable, and physiologically relevant models of the human knee joint represents a significant impediment for the elucidation of the pathogenesis of OA and the discovery and development of DMOADs. OA can be caused by numerous factors including heredity, obesity, trauma, congenital or developmental anomalies, and other factors.¹⁵⁴ It is, thus, not surprising that there is extensive heterogeneity in disease presentation and progression in different OA patients, suggesting that patients should benefit from personalized medicine. Therefore, a more realistic goal may be to classify OA patients based on some validated common features, and then use models that most closely recapitulate OA to develop the DMOADs for this subgroup of OA patients (Fig. 3). In addition, comprehensive patient-specific efficacy/toxicity prediction models must be developed.

FIG. 3.

The DMOAD development pipeline that enables precision medicine. In traditional drug development, the potential agents are created (Step 1) and then tested in 2D or 3D disease models (Step 2). The candidates that show efficacy without cytotoxicity are further screened in animal models (Step 3) before one to two drugs finally enter human clinical trial (Step 4). In general, the conventional models for drug testing lack the personalized features of participants in the clinical trials. In the future, as the first step toward “personalized OA medicine,” validated biomarkers will be used to first classify patients into different groups (endotypes or phenotypes). By studying the specific etiologies and pathologies, drug candidates and testing models will be developed for the different patient groups. Next, by using patient-derived cells and simulating the specific disease features of the patient, the personalized models will be applied to develop candidate therapeutics for the specific patient. With the capability of using human cells, including differentiated cells, MSCs, and/or induced pluripotent stem cells, and recapitulating relevant human physiological parameters, MPS represent a potentially high-utility system in the development of personalized DMOADs. In particular, the observations derived from the two physiological models, that is, MPS and animals, can be cross-checked and validated to further enhance the prediction of drug efficacy and toxicity in humans. 2D, two-dimensional; 3D, three-dimensional; MSC, mesenchymal stem cell. Color images are available online.

In that regard, OA-specific and sensitive biomarkers will be critical for the accurate classification of the phenotype of each patient to aid in the prediction of appropriate interventions. This approach will encompass the key principles of personalized medicine for OA treatment. Although several molecules, such as urinary excreted CTX-II (C-terminal cross-linked telopeptide of type II collagen) and serum COMP (cartilage oligomeric protein) have been proposed as predictive OA biomarkers, biomarker(s) that can precisely distinguish the etiologies/pathologies of different subgroups of OA patients or determine treatment efficacy have not been established. This represents a major obstacle to the development of personalized OA models and the future development of DMOADs. Recently, mass spectrometry, a technology that can examine candidate proteins without being limited by the availability of antibodies, has been used to profile metabolomics in human OA synovial fluid.^155,156 In these studies, different metabolomic phenotypes were found within healthy, early, and late OA cohorts, and several pathways, such as those related to keratan sulfate and N-glycan degradation, may provide new information in developing biomarkers of OA. It should be noted that while obtaining a blood or urine sample is less invasive than synovial fluid, molecules from the diseased joint must gain entrance to the synovium before entering the systemic circulation. The efficiency of such penetration is unknown. In addition, the molecules are diluted significantly and subjected to potential degradation in the blood. Therefore, synovial fluid remains the most relevant sample for the isolation of biomarkers.

Extensive evidence has demonstrated that cell–cell crosstalk is a primary contributor to OA pathogenesis. It is expected that such communication will also play a key role in the prevention or reversal of OA after treatment. For example, the physiological models with multiple tissues, such as MPSs and animal models, should provide more power in terms of predicting the toxicity and efficacy of drugs in clinical trials. As demonstrated in Figure 3, these two types of models can be complementary. For example, MPSs can be used to exclude the drugs that may be toxic to human cells, thus reducing animal use. In addition, the drugs that are screened in animal studies can be further validated in the MPSs and inform the patient subpopulations that may benefit from the drugs. Also, to enable personalized medicine, the new OA models need to be versatile with the capacity to readily generate different types of pathological changes.

Moreover, more comprehensive tools are needed to further assess the OA models, as well as the effect of treatments. Currently, most studies use limited parameters, such as MMP-13 expression, GAG loss, and the presence of proinflammatory cytokines, to indicate the disease state. However, at least 1500 genes are found to be differentially expressed in chondrocytes isolated from the intact and damaged areas.^157,158 Therefore, “omic”-based methods, such as mass spectrometry mentioned previously, will facilitate future studies. The comprehensive characterization of models not only improves the classification of patients and indicates the fidelity of modeling, but also may reveal potential adverse or beneficial effects of treatments that cannot be identified through analysis of the “known” targets alone. At present, such “omic” studies are rarely seen in the testing of DMOADs.

Finally, to further validate the models to enable the prediction of the efficacy of novel therapeutic interventions in humans, it is important to first assess the impact of agents with known clinical efficacy. This validation step will justify moving forward to screen for new drugs. Ideally, one should start with the “gold standard,” that is, a drug with well-recognized treatment efficacy. However, to date, there are no FDA-approved DMOADs, and numerous late-stage clinical trials have failed to demonstrate effectiveness.¹⁵⁴ We may examine the effect of these failed drugs in the OA models and compare the results with clinical observations. Ideally, the efficacious models should be capable of reproducing the deficiencies of the failed drug.

In conclusion, clinically relevant and personalized models of OA are urgently needed to enhance our understanding of the pathogenesis of joint diseases in humans and facilitate the discovery and development of novel drug treatments.¹ In Figure 3, we summarize the current models and demonstrate their utilities in the DMOAD development pipeline. With the development of efficacious biomarkers and “true” MPS, we will finally be able to apply precision medicine in the treatment of OA. In particular, the inclusion of MPSs will increase the predictive power in the discovery phase, reduce animal numbers in the preclinical stage, and predict the efficacy and toxicity of compounds before human clinical trials.

Footnotes

Disclosure Statement

No competing financial interests exist.

Funding Information

This work is supported by the NIH (UH3TR002136, UG3TR003090).

References

, Li

, Alexander

P.G.

, et al. Pathogenesis of osteoarthritis: risk factors, regulatory pathways in chondrocytes, and experimental models. Biology (Basel), 9, 194, 2020.

Hunter

D.J.

, and Bierma-Zeinstra

Osteoarthritis. Lancet, 393, 1745, 2019.

Hootman

J.M.

, Helmick

C.G.

, Barbour

K.E.

, Theis

K.A.

, and Boring

M.A.

Updated projected prevalence of self-reported doctor-diagnosed arthritis and arthritis-attributable activity limitation among US adults, 2015–2040. Arthritis Rheumatol, 68, 1582, 2016.

Litwic

, Edwards

M.H.

, Dennison

E.M.

, and Cooper

Epidemiology and burden of osteoarthritis. Br Med Bull, 105, 185, 2013.

Veronese

, Stubbs

, Solmi

, et al. Association between lower limb osteoarthritis and incidence of depressive symptoms: data from the osteoarthritis initiative. Age Ageing, 46, 470, 2017.

Kye

S.Y.

, and Park

Suicidal ideation and suicidal attempts among adults with chronic diseases: a cross-sectional study. Compr Psychiatry, 73, 160, 2017.

Innes

K.E.

, and Sambamoorthi

The association of perceived memory loss with osteoarthritis and related joint pain in a large appalachian population. Pain Med, 19, 1340, 2018.

Vina

E.R.

, and Kwoh

C.K.

Epidemiology of osteoarthritis: literature update. Curr Opin Rheumatol, 30, 160, 2018.

Kloppenburg

, and Berenbaum

Osteoarthritis year in review 2019: epidemiology and therapy. Osteoarthritis Cartilage, 28, 242, 2020.

10.

Watt

F.E.

, and Gulati

New drug treatments for osteoarthritis: what is on the horizon? Eur Med J Rheumatol, 2, 50, 2017.

11.

Healy

W.L.

, Della Valle

C.J.

, Iorio

, et al. Complications of total knee arthroplasty: standardized list and definitions of the knee society. Clin Orthop Relat Res, 471, 215, 2013.

12.

Yazici

, McAlindon

T.E.

, Gibofsky

, et al. Lorecivivint, a novel intraarticular CDC-like kinase 2 and dual-specificity tyrosine phosphorylation-regulated kinase 1A inhibitor and wnt pathway modulator for the treatment of knee osteoarthritis: a phase II randomized trial. Arthritis Rheum, 72, 1694, 2020.

13.

Eckstein

, Kraines

J.L.

, Aydemir

, Wirth

, Maschek

, and Hochberg

M.C.

Intra-articular sprifermin reduces cartilage loss in addition to increasing cartilage gain independent of location in the femorotibial joint: post-hoc analysis of a randomised, placebo-controlled phase II clinical trial. Ann Rheum Dis, 79, 525, 2020.

14.

Hochberg

M.C.

, Guermazi

, Guehring

, et al. Effect of intra-articular sprifermin vs placebo on femorotibial joint cartilage thickness in patients with osteoarthritis: the forward randomized clinical trial. JAMA, 322, 1360, 2019.

15.

Karsdal

M.A.

, Byrjalsen

, Alexandersen

, et al. Treatment of symptomatic knee osteoarthritis with oral salmon calcitonin: results from two phase 3 trials. Osteoarthritis Cartilage, 23, 532, 2015.

16.

Kloppenburg

, Peterfy

, Haugen

I.K.

, et al. Phase IIa, placebo-controlled, randomised study of lutikizumab, an anti-interleukin-1α and anti-interleukin-1β dual variable domain immunoglobulin, in patients with erosive hand osteoarthritis. Ann Rheum Dis, 78, 413, 2019.

17.

Wang

S.X.

, Abramson

S.B.

, Attur

, et al. Safety, tolerability, and pharmacodynamics of an anti-interleukin-1α/β dual variable domain immunoglobulin in patients with osteoarthritis of the knee: a randomized phase 1 study. Osteoarthritis Cartilage, 25, 1952, 2017.

18.

Nishimura

, Hara

, Umebayashi

, et al. Efficacy and safety of canakinumab in systemic juvenile idiopathic arthritis: 48-week results from an open-label phase III study in Japanese patients. Mod Rheumatol, 31, 226, 2021.

19.

Verbruggen

, Wittoek

, Vander Cruyssen

, and Elewaut

Tumour necrosis factor blockade for the treatment of erosive osteoarthritis of the interphalangeal finger joints: a double blind, randomised trial on structure modification. Ann Rheum Dis, 71, 891, 2012.

20.

Leff

R.L.

, Elias

, Ionescu

, Reiner

, and Poole

A.R.

Molecular changes in human osteoarthritic cartilage after 3 weeks of oral administration of BAY 12-9566, a matrix metalloproteinase inhibitor. J Rheumatol, 30, 544, 2003.

21.

Reginster

J.Y.

, Badurski

, Bellamy

, et al. Efficacy and safety of strontium ranelate in the treatment of knee osteoarthritis: results of a double-blind, randomised placebo-controlled trial. Ann Rheum Dis, 72, 179, 2013.

22.

Hellio le Graverand

M.P.

, Clemmer

R.S.

, Redifer

, et al. A 2-year randomised, double-blind, placebo-controlled, multicentre study of oral selective iNOS inhibitor, cindunistat (SD-6010), in patients with symptomatic osteoarthritis of the knee. Ann Rheum Dis, 72, 187, 2013.

23.

Jin

, Smith

, Monteith

, et al. CGRP blockade by galcanezumab was not associated with reductions in signs and symptoms of knee osteoarthritis in a randomized clinical trial. Osteoarthritis Cartilage, 26, 1609, 2018.

24.

Glyn-Jones

, Palmer

A.J.

, Agricola

, et al. Osteoarthritis. Lancet, 386, 376, 2015.

25.

Loeser

R.F.

, Goldring

S.R.

, Scanzello

C.R.

, and Goldring

M.B.

Osteoarthritis: a disease of the joint as an organ. Arthritis Rheum, 64, 1697, 2012.

26.

Belluzzi

, Stocco

, Pozzuoli

, et al. Contribution of infrapatellar fat pad and synovial membrane to knee osteoarthritis pain. Biomed Res Int, 2019, 6390182, 2019.

27.

Favero

, Belluzzi

, Trisolino

, et al. Inflammatory molecules produced by meniscus and synovium in early and end-stage osteoarthritis: a coculture study. J Cell Physiol, 234, 11176, 2019.

28.

Guilak

, Nims

R.J.

, Dicks

, Wu

C.L.

, and Meulenbelt

Osteoarthritis as a disease of the cartilage pericellular matrix. Matrix Biol, 71–72, 40, 2018.

29.

Mueller

M.B.

, and Tuan

R.S.

Anabolic/catabolic balance in pathogenesis of osteoarthritis: identifying molecular targets. PM R, 3, S3, 2011.

30.

Rim

Y.A.

, Nam

, and Ju

J.H.

The role of chondrocyte hypertrophy and senescence in osteoarthritis initiation and progression. Int J Mol Sci, 21, 2358, 2020.

31.

Kim

J.R.

, Yoo

J.J.

, and Kim

H.A.

Therapeutics in osteoarthritis based on an understanding of its molecular pathogenesis. Int J Mol Sci, 19, 674, 2018.

32.

Mathiessen

, and Conaghan

P.G.

Synovitis in osteoarthritis: current understanding with therapeutic implications. Arthritis Res Ther, 19, 18, 2017.

33.

Hugle

, and Geurts

What drives osteoarthritis?-Synovial versus subchondral bone pathology. Rheumatology (Oxford), 56, 1461, 2017.

34.

Lopes

E.B.P.

, Filiberti

, Husain

S.A.

, and Humphrey

M.B.

Immune contributions to osteoarthritis. Curr Osteoporos Rep, 15, 593, 2017.

35.

Jiang

L.F.

, Fang

J.H.

, and Wu

L.D.

Role of infrapatellar fat pad in pathological process of knee osteoarthritis: future applications in treatment. World J Clin Cases, 7, 2134, 2019.

36.

Aho

O.M.

, Finnila

, Thevenot

, Saarakkala

, and Lehenkari

Subchondral bone histology and grading in osteoarthritis. PLoS One, 12, e0173726, 2017.

37.

O'Neill

T.W.

, and Felson

D.T.

Mechanisms of osteoarthritis (OA) pain. Curr Osteoporos Rep, 16, 611, 2018.

38.

Bilgen

, Jayasuriya

C.T.

, and Owens

B.D.

Current concepts in meniscus tissue engineering and repair. Adv Healthc Mater, 7, e1701407, 2018.

39.

Eijgenraam

S.M.

, Bovendeert

F.A.T.

, Verschueren

, et al. T2 mapping of the meniscus is a biomarker for early osteoarthritis. Eur Radiol, 29, 5664, 2019.

40.

Kuyinu

E.L.

, Narayanan

, Nair

L.S.

, and Laurencin

C.T.

Animal models of osteoarthritis: classification, update, and measurement of outcomes. J Orthop Res, 11, 19, 2016.

41.

Schulze-Tanzil

Intraarticular ligament degeneration is interrelated with cartilage and bone destruction in osteoarthritis. Cells, 8, 990, 2019.

42.

Gregory

M.H.

, Capito

, Kuroki

, Stoker

A.M.

, Cook

J.L.

, and Sherman

S.L.

A review of translational animal models for knee osteoarthritis. Arthritis, 2012, 764621, 2012.

43.

Samvelyan

H.J.

, Hughes

, Stevens

, and Staines

K.A.

Models of osteoarthritis: relevance and new insights. Calcif Tissue Int, 2020. [Epub ahead of print]; DOI: 10.1007/s00223-020-00670-x.

44.

Westacott

C.I.

, Whicher

J.T.

, Barnes

I.C.

, Thompson

, Swan

A.J.

, and Dieppe

P.A.

Synovial fluid concentration of five different cytokines in rheumatic diseases. Ann Rheum Dis, 49, 676, 1990.

45.

Sasazaki

, Seedhom

B.B.

, and Shore

Morphology of the bovine chondrocyte and of its cytoskeleton in isolation and in situ: are chondrocytes ubiquitously paired through the entire layer of articular cartilage? Rheumatology (Oxford), 47, 1641, 2008.

46.

Hall

A.C.

The role of chondrocyte morphology and volume in controlling phenotype-implications for osteoarthritis, cartilage repair, and cartilage engineering. Curr Rheumatol Rep, 21, 38, 2019.

47.

Kim

M.J.

, Kim

, Jin

E.J.

, and Sonn

J.K.

Inhibition of RhoA but not ROCK induces chondrogenesis of chick limb mesenchymal cells. Biochem Biophys Res Commun, 418, 500, 2012.

48.

Rottmar

, Mhanna

, Guimond-Lischer

, Vogel

, Zenobi-Wong

, and Maniura-Weber

Interference with the contractile machinery of the fibroblastic chondrocyte cytoskeleton induces re-expression of the cartilage phenotype through involvement of PI3K, PKC and MAPKs. Exp Cell Res, 320, 175, 2014.

49.

Alexander

P.G.

, Gottardi

, Lin

, Lozito

T.P.

, and Tuan

R.S.

Three-dimensional osteogenic and chondrogenic systems to model osteochondral physiology and degenerative joint diseases. Exp Biol Med (Maywood), 239, 1080, 2014.

50.

Marlovits

, Hombauer

, Truppe

, Vecsei

, and Schlegel

Changes in the ratio of type-I and type-II collagen expression during monolayer culture of human chondrocytes. J Bone Joint Surg Br, 86, 286, 2004.

51.

Zhou

, Thornhill

T.S.

, Meng

, Xie

, Wright

, and Glowacki

Influence of osteoarthritis grade on molecular signature of human cartilage. J Orthop Res, 34, 454, 2016.

52.

Koshy

P.J.

, Lundy

C.J.

, Rowan

A.D.

, et al. The modulation of matrix metalloproteinase and ADAM gene expression in human chondrocytes by interleukin-1 and oncostatin M: a time-course study using real-time quantitative reverse transcription-polymerase chain reaction. Arthritis Rheum, 46, 961, 2002.

53.

Pearson

M.J.

, Herndler-Brandstetter

, Tariq

M.A.

, et al. IL-6 secretion in osteoarthritis patients is mediated by chondrocyte-synovial fibroblast cross-talk and is enhanced by obesity. Sci Rep, 7, 3451, 2017.

54.

Nair

, Kanda

, Bush-Joseph

, et al. Synovial fluid from patients with early osteoarthritis modulates fibroblast-like synoviocyte responses to toll-like receptor 4 and toll-like receptor 2 ligands via soluble CD14. Arthritis Rheum, 64, 2268, 2012.

55.

Ribel-Madsen

, Bartels

E.M.

, Stockmarr

, et al. A synoviocyte model for osteoarthritis and rheumatoid arthritis: response to Ibuprofen, betamethasone, and ginger extract-a cross-sectional in vitro study. Arthritis, 2012, 505842, 2012.

56.

Zheng

, Tao

, Chen

, et al. Plumbagin prevents IL-1beta-induced inflammatory response in human osteoarthritis chondrocytes and prevents the progression of osteoarthritis in mice. Inflammation, 40, 849, 2017.

57.

Lee

S.A.

, Moon

S.M.

, Han

S.H.

, et al. Chondroprotective effects of aqueous extract of Anthriscus sylvestris leaves on osteoarthritis in vitro and in vivo through MAPKs and NF-kappaB signaling inhibition. Biomed Pharmacother, 103, 1202, 2018.

58.

D'Ascola

, Irrera

, Ettari

, et al. Exploiting curcumin synergy with natural products using quantitative analysis of dose-effect relationships in an experimental in vitro model of osteoarthritis. Front Pharmacol, 10, 1347, 2019.

59.

Lawrence

The nuclear factor NF-kappaB pathway in inflammation. Cold Spring Harb Perspect Biol, 1, a001651, 2009.

60.

Yagi

, Ulici

, and Tuan

R.S.

Polyphenols suppress inducible oxidative stress in human osteoarthritic and bovine chondrocytes. Osteparitis Cartilage Open, 2, 100064, 2020.

61.

Deshmukh

, Hu

, Barroga

, et al. A small-molecule inhibitor of the Wnt pathway (SM04690) as a potential disease modifying agent for the treatment of osteoarthritis of the knee. Osteoarthritis Cartilage, 26, 18, 2018.

62.

Al-Modawi

R.N.

, Brinchmann

J.E.

, and Karlsen

T.A.

Multi-pathway protective effects of microRNAs on human chondrocytes in an in vitro model of osteoarthritis. Mol Ther Nucleic Acids, 17, 776, 2019.

63.

Stewart

M.C.

, Saunders

K.M.

, Burton-Wurster

, and Macleod

J.N.

Phenotypic stability of articular chondrocytes in vitro: the effects of culture models, bone morphogenetic protein 2, and serum supplementation. J Bone Miner Res, 15, 166, 2000.

64.

, Li

, Zhang

, et al. Roles of TRPV4 and piezo channels in stretch-evoked Ca(2+) response in chondrocytes. Exp Biol Med (Maywood), 245, 180, 2020.

65.

Lohberger

, Kaltenegger

, Weigl

, et al. Mechanical exposure and diacerein treatment modulates integrin-FAK-MAPKs mechanotransduction in human osteoarthritis chondrocytes. Cell Signal, 56, 23, 2019.

66.

Bicho

, Pina

, Oliveira

J.M.

, and Reis

R.L.

In vitro mimetic models for the bone-cartilage interface regeneration. Adv Exp Med Biol, 1059, 373, 2018.

67.

Lin

, Fitzgerald

J.B.

, Xu

, et al. Gene expression profiles of human chondrocytes during passaged monolayer cultivation. J Orthop Res, 26, 1230, 2008.

68.

Mao

, Block

, Singh-Varma

, et al. Extracellular matrix derived from chondrocytes promotes rapid expansion of human primary chondrocytes in vitro with reduced dedifferentiation. Acta Biomater, 85, 75, 2019.

69.

Sokolove

, Lepus

C.M.

Role of inflammation in the pathogenesis of osteoarthritis: latest findings and interpretations. Ther Adv Musculoskelet Dis, 5, 77, 2013.

70.

Zuliani

C.C.

, Bombini

M.F.

, de Andrade

K.C.

, Mamoni

, Pereira

A.H.

, and Coimbra

I.B.

Micromass cultures are effective for differentiation of human amniotic fluid stem cells into chondrocytes. Clinics (Sao Paulo), 73, e268, 2018.

71.

DeLise

A.M.

, Stringa

, Woodward

W.A.

, Mello

M.A.

, and Tuan

R.S.

Embryonic limb mesenchyme micromass culture as an in vitro model for chondrogenesis and cartilage maturation. Methods Mol Biol, 137, 359, 2000.

72.

Honorati

M.C.

, Cattini

, and Facchini

VEGF production by osteoarthritic chondrocytes cultured in micromass and stimulated by IL-17 and TNF-α. Connect Tissue Res, 48, 239, 2007.

73.

Handschel

J.G.K.

, Depprich

R.A.

, Kübler

N.R.

, Wiesmann

H.-P.

, Ommerborn

, and Meyer

Prospects of micromass culture technology in tissue engineering. Head Face Med, 3, 4, 2007.

74.

Zhang

, Su

, Xu

, Yang

, Yu

, and Huang

Chondrogenic differentiation of human mesenchymal stem cells: a comparison between micromass and pellet culture systems. Biotechnol Lett, 32, 1339, 2010.

75.

Alini

, Carey

, Hirata

, Grynpas

M.D.

, Pidoux

, and Poole

A.R.

Cellular and matrix changes before and at the time of calcification in the growth plate studied in vitro: arrest of type X collagen synthesis and net loss of collagen when calcification is initiated. J Bone Miner Res, 9, 1077, 1994.

76.

Battistelli

, Salucci

, Olivotto

, et al. Cell death in human articular chondrocyte: a morpho-functional study in micromass model. Apoptosis, 19, 1471, 2014.

77.

Sun

, Franklin

A.M.

, Mauerhan

D.R.

, and Hanley

E.N.

Biological effects of phosphocitrate on osteoarthritic articular chondrocytes. J Rheumatol, 11, 62, 2017.

78.

Greco

K.V.

, Iqbal

A.J.

, Rattazzi

, et al. High density micromass cultures of a human chondrocyte cell line: a reliable assay system to reveal the modulatory functions of pharmacological agents. Biochem Pharmacol, 82, 1919, 2011.

79.

Dehne

, Schenk

, Perka

, et al. Gene expression profiling of primary human articular chondrocytes in high-density micromasses reveals patterns of recovery, maintenance, re- and dedifferentiation. Gene, 462, 8, 2010.

80.

Caron

M.M.

, Emans

P.J.

, Coolsen

M.M.

, et al. Redifferentiation of dedifferentiated human articular chondrocytes: comparison of 2D and 3D cultures. Osteoarthritis Cartilage, 20, 1170, 2012.

81.

Khurshid

, Mulet-Sierra

, Adesida

, and Sen

Osteoarthritic human chondrocytes proliferate in 3D co-culture with mesenchymal stem cells in suspension bioreactors. J Tissue Eng Regen Med, 12, e1418, 2018.

82.

Cope

P.J.

, Ourradi

, Li

, and Sharif

Models of osteoarthritis: the good, the bad and the promising. Osteoarthritis Cartilage, 27, 230, 2019.

83.

Ziadlou

, Barbero

, Stoddart

M.J.

, et al. Regulation of inflammatory response in human osteoarthritic chondrocytes by novel herbal small molecules. Int J Mol Sci, 20, 5745, 2019.

84.

Morrovati

, Karimian Fathi

, Soleimani Rad

, and Montaseri

Mummy prevents IL-1beta-induced inflammatory responses and cartilage matrix degradation via inhibition of NF-B subunits gene expression in pellet culture system. Adv Pharm Bull, 8, 283, 2018.

85.

Johnson

C.I.

, Argyle

D.J.

, and Clements

D.N.

In vitro models for the study of osteoarthritis. Vet J, 209, 40, 2016.

86.

Mantha

, Pillai

, Khayambashi

, et al. Smart hydrogels in tissue engineering and regenerative medicine. Materials (Basel), 12, 2019.

87.

Deng

, Lei

, Lin

, Yang

, Lin

, and Tuan

R.S.

Engineering hyaline cartilage from mesenchymal stem cells with low hypertrophy potential via modulation of culture conditions and Wnt/beta-catenin pathway. Biomaterials, 192, 569, 2019.

88.

Samavedi

, Diaz-Rodriguez

, Erndt-Marino

J.D.

, and Hahn

M.S.

A three-dimensional chondrocyte-macrophage coculture system to probe inflammation in experimental osteoarthritis. Tissue Eng Part A, 23, 101, 2017.

89.

Sun

, Wang

, and Kaplan

D.L.

A 3D cartilage—inflammatory cell culture system for the modeling of human osteoarthritis. Biomaterials, 32, 5581, 2011.

90.

C.C.

, Chen

W.H.

, Zao

, et al. Regenerative potentials of platelet-rich plasma enhanced by collagen in retrieving pro-inflammatory cytokine-inhibited chondrogenesis. Biomaterials, 32, 5847, 2011.

91.

Chen

W.H.

, Lo

W.C.

, Hsu

W.C.

, et al. Synergistic anabolic actions of hyaluronic acid and platelet-rich plasma on cartilage regeneration in osteoarthritis therapy. Biomaterials, 35, 9599, 2014.

92.

Peck

, Ng

L.Y.

, Goh

J.Y.

, Gao

, and Wang

D.A.

A three-dimensionally engineered biomimetic cartilaginous tissue model for osteoarthritic drug evaluation. Mol Pharm, 11, 1997, 2014.

93.

Kjelgaard-Petersen

C.F.

, Sharma

, Kayed

, et al. Tofacitinib and TPCA-1 exert chondroprotective effects on extracellular matrix turnover in bovine articular cartilage ex vivo. Biochem Pharmacol, 165, 91, 2019.

94.

Chanalaris

, Doherty

, Marsden

B.D.

, et al. Suramin inhibits osteoarthritic cartilage degradation by increasing extracellular levels of chondroprotective tissue inhibitor of metalloproteinases 3. Mol Pharm, 92, 459, 2017.

95.

Muller

, Lindemann

, and Gigout

Effects of sprifermin, IGF1, IGF2, BMP7, or CNP on bovine chondrocytes in monolayer and 3D culture. J Orthop Res, 38, 653, 2020.

96.

Siebelt

, van der Windt

A.E.

, Groen

H.C.

, et al. FK506 protects against articular cartilage collagenous extra-cellular matrix degradation. Osteoarthritis Cartilage, 22, 591, 2014.

97.

Kang

S.W.

, Kim

, and Shin

D.Y.

Inhibition of senescence and promotion of the proliferation of chondrocytes from articular cartilage by CsA and FK506 involves inhibition of p38MAPK. Mech Ageing Dev, 153, 7, 2016.

98.

Dhanabalan

K.M.

, Gupta

V.K.

, and Agarwal

Rapamycin-PLGA microparticles prevent senescence, sustain cartilage matrix production under stress and exhibit prolonged retention in mouse joints. Biomater Sci, 8, 4308, 2020.

99.

Bian

, Guvendiren

, Mauck

R.L.

, and Burdick

J.A.

Hydrogels that mimic developmentally relevant matrix and N-cadherin interactions enhance MSC chondrogenesis. Proc Natl Acad Sci U S A, 110, 10117, 2013.

100.

Rogan

, Ilagan

, and Yang

Comparing single cell versus pellet encapsulation of mesenchymal stem cells in three-dimensional hydrogels for cartilage regeneration. Tissue Eng Part A, 25, 1404, 2019.

101.

Jimenez

, Lopez-Ruiz

, Antich

, Chocarro-Wrona

, and Marchal

J.A.

Models of disease. Adv Exp Med Biol, 1059, 331, 2018.

102.

Haltmayer

, Ribitsch

, Gabner

, et al. Co-culture of osteochondral explants and synovial membrane as in vitro model for osteoarthritis. PLoS One, 14, e0214709, 2019.

103.

Alexander

P.G.

, Song

, Taboas

J.M.

, et al. Development of a spring-loaded impact device to deliver injurious mechanical impacts to the articular cartilage surface. Cartilage, 4, 52, 2013.

104.

Dolzani

, Assirelli

, Pulsatelli

, Meliconi

, Mariani

, and Neri

Ex vivo physiological compression of human osteoarthritis cartilage modulates cellular and matrix components. PLoS One, 14, e0222947, 2019.

105.

Cutcliffe

H.C.

, and DeFrate

L.E.

Comparison of cartilage mechanical properties measured during creep and recovery. Sci Rep, 10, 1547, 2020.

106.

Geurts

, Juric

, Muller

, Scharen

, and Netzer

Novel ex vivo human osteochondral explant model of knee and spine osteoarthritis enables assessment of inflammatory and drug treatment responses. Int J Mol Sci, 19, 1314, 2018.

107.

Nishimuta

J.F.

, Bendernagel

M.F.

, and Levenston

M.E.

Co-culture with infrapatellar fat pad differentially stimulates proteoglycan synthesis and accumulation in cartilage and meniscus tissues. Connect Tissue Res, 58, 447, 2017.

108.

, Jiang

, Alexander

P.G.

, et al. Infrapatellar fat pad aggravates degeneration of acute traumatized cartilage: a possible role for interleukin-6. Osteoarthritis Cartilage, 25, 138, 2017.

109.

van Buul

G.M.

, Villafuertes

, Bos

P.K.

, et al. Mesenchymal stem cells secrete factors that inhibit inflammatory processes in short-term osteoarthritic synovium and cartilage explant culture. Osteoarthritis Cartilage, 20, 1186, 2012.

110.

Swärd

, Wang

, Hansson

, Lohmander

L.S.

, Grodzinsky

A.J.

, and Struglics

Coculture of bovine cartilage with synovium and fibrous joint capsule increases aggrecanase and matrix metalloproteinase activity. Arthritis Res Ther, 19, 157, 2017.

111.

Beekhuizen

, Bastiaansen-Jenniskens

Y.M.

, Koevoet

, et al. Osteoarthritic synovial tissue inhibition of proteoglycan production in human osteoarthritic knee cartilage: establishment and characterization of a long-term cartilage-synovium coculture. Arthritis Rheum, 63, 1918, 2011.

112.

Mehta

, Akhtar

, Porter

R.M.

, Önnerfjord

, and Bajpayee

A.G.

Interleukin-1 receptor antagonist (IL-1Ra) is more effective in suppressing cytokine-induced catabolism in cartilage-synovium co-culture than in cartilage monoculture. Arthritis Res Ther, 21, 238, 2019.

113.

Hardy

M.M.

, Seibert

, Manning

P.T.

, et al. Cyclooxygenase 2-dependent prostaglandin E2 modulates cartilage proteoglycan degradation in human osteoarthritis explants. Arthritis Rheum, 46, 1789, 2002.

114.

Englund

, Roemer

F.W.

, Hayashi

, Crema

M.D.

, and Guermazi

Meniscus pathology, osteoarthritis and the treatment controversy. Nat Rev Rheumatol, 8, 412, 2012.

115.

Nishimuta

J.F.

, and Levenston

M.E.

Response of cartilage and meniscus tissue explants to in vitro compressive overload. Osteoarthritis Cartilage, 20, 422, 2012.

116.

Gupta

, Zielinska

, McHenry

, Kadmiel

, and Haut Donahue

T.L.

IL-1 and iNOS gene expression and NO synthesis in the superior region of meniscal explants are dependent on the magnitude of compressive strains. Osteoarthritis Cartilage, 16, 1213, 2008.

117.

Zielinska

, Killian

, Kadmiel

, Nelsen

, and Haut Donahue

T.L.

Meniscal tissue explants response depends on level of dynamic compressive strain. Osteoarthritis Cartilage, 17, 754, 2009.

118.

Kisiday

J.D.

, McIlwraith

C.W.

, Rodkey

W.G.

, Frisbie

D.D.

, and Steadman

J.R.

Effects of platelet-rich plasma composition on anabolic and catabolic activities in equine cartilage and meniscal explants. Cartilage, 3, 245, 2012.

119.

Imler

S.M.

, Doshi

A.N.

, and Levenston

M.E.

Combined effects of growth factors and static mechanical compression on meniscus explant biosynthesis. Osteoarthritis Cartilage, 12, 736, 2004.

120.

Tarafder

, Gulko

, Kim

, et al. Effect of dose and release rate of CTGF and TGFβ3 on avascular meniscus healing. J Orthop Res, 37, 1555, 2019.

121.

Sasaki

, Rothrauff

B.B.

, Alexander

P.G.

, et al. In vitro repair of meniscal radial tear with hydrogels seeded with adipose stem cells and TGF-β3. Am J Sports Med, 46, 2402, 2018.

122.

Tarafder

, Park

, and Lee

C.H.

Explant models for meniscus metabolism, injury, repair, and healing. Connect Tissue Res, 61, 292, 2020.

123.

Lampropoulou-Adamidou

, Lelovas

, Karadimas

E.V.

, et al. Useful animal models for the research of osteoarthritis. Eur J Orthop Surg Traumatol, 24, 263, 2014.

124.

Poulet

Models to define the stages of articular cartilage degradation in osteoarthritis development. Int J Exp Pathol, 98, 120, 2017.

125.

Poole

, Blake

, Buschmann

, et al. Recommendations for the use of preclinical models in the study and treatment of osteoarthritis. Osteoarthritis Cartilage, 18(Suppl 3), S10, 2010.

126.

Thysen

, Luyten

F.P.

, and Lories

R.J.

Targets, models and challenges in osteoarthritis research. Dis Model Mech, 8, 17, 2015.

127.

Miller

R.E.

, and Malfait

A.M.

Osteoarthritis pain: what are we learning from animal models? Best Pract Res Clin Rheumatol, 31, 676, 2017.

128.

Vincent

T.L.

Of mice and men: converging on a common molecular understanding of osteoarthritis. Lancet Rheumatol, 2, e633, 2020.

129.

Culley

K.L.

, Singh

, Lessard

, et al. Mouse models of osteoarthritis: surgical model of post-traumatic osteoarthritis induced by destabilization of the medial meniscus. Methods Mol Biol, 2221, 223, 2021.

130.

Mittelstaedt

, Kahn

, and Xia

Detection of early osteoarthritis in canine knee joints 3 weeks post ACL transection by microscopic MRI and biomechanical measurement. J Orthop Surg (Hong Kong), 26, 2309499018778357, 2018.

131.

Pottie

, Presle

, Terlain

, Netter

, Mainard

, and Berenbaum

Obesity and osteoarthritis: more complex than predicted!. Ann Rheum Dis, 65, 1403, 2006.

132.

Tang

, Harasymowicz

N.S.

, Wu

C.-L.

, et al. Gene therapy for follistatin mitigates systemic metabolic inflammation and post-traumatic arthritis in high-fat diet–induced obesity. Sci Adv, 6, eaaz7492, 2020.

133.

Donovan

E.L.

, Lopes

E.B.P.

, Batushansky

, Kinter

, and Griffin

T.M.

Independent effects of dietary fat and sucrose content on chondrocyte metabolism and osteoarthritis pathology in mice. Dis Model Mech, 11, dmm034827, 2018.

134.

Stannus

O.P.

, Jones

, Quinn

S.J.

, Cicuttini

F.M.

, Dore

, and Ding

The association between leptin, interleukin-6, and hip radiographic osteoarthritis in older people: a cross-sectional study. Arthritis Res Ther, 12, R95, 2010.

135.

de Boer

T.N.

, van Spil

W.E.

, Huisman

A.M.

, et al. Serum adipokines in osteoarthritis; comparison with controls and relationship with local parameters of synovial inflammation and cartilage damage. Osteoarthritis Cartilage, 20, 846, 2012.

136.

Christiansen

B.A.

, Guilak

, Lockwood

K.A.

, et al. Non-invasive mouse models of post-traumatic osteoarthritis. Osteoarthritis Cartilage, 23, 1627, 2015.

137.

Ameye

L.G.

, and Young

M.F.

Animal models of osteoarthritis: lessons learned while seeking the “Holy Grail”. Curr Opin Rheumatol, 18, 537, 2006.

138.

Malfait

A.M.

, and Little

C.B.

On the predictive utility of animal models of osteoarthritis. Arthritis Res Ther, 17, 225, 2015.

139.

Berenbaum

, Griffin

T.M.

, and Liu-Bryan

Review: metabolic regulation of inflammation in osteoarthritis. Arthritis Rheumatol, 69, 9, 2017.

140.

Datta

, Zhang

, Parousis

, et al. High-fat diet-induced acceleration of osteoarthritis is associated with a distinct and sustained plasma metabolite signature. Sci Rep, 7, 8205, 2017.

141.

Brunner

A.M.

, Henn

C.M.

, Drewniak

E.I.

, et al. High dietary fat and the development of osteoarthritis in a rabbit model. Osteoarthritis Cartilage, 20, 584, 2012.

142.

Poulet

Non-invasive loading model of murine osteoarthritis. Curr Rheumatol Rep, 18, 40, 2016.

143.

Mittal

, Woo

F.W.

, Castro

C.S.

, et al. Organ-on-chip models: implications in drug discovery and clinical applications. J Cell Physiol, 234, 8352, 2019.

144.

Wang

, Li

, Xu

, and Qin

Bioinspired engineering of organ-on-chip devices. Adv Exp Med Biol, 1174, 401, 2019.

145.

Bhatia

S.N.

, and Ingber

D.E.

Microfluidic organs-on-chips. Nat Biotechnol, 32, 760, 2014.

146.

Piluso

, Li

, Abinzano

, et al. Mimicking the articular joint with in vitro models. Trends Biotechnol, 37, 1063, 2019.

147.

Lin

, Lozito

T.P.

, Alexander

P.G.

, Gottardi

, and Tuan

R.S.

Stem cell-based microphysiological osteochondral system to model tissue response to interleukin-1beta. Mol Pharm, 11, 2203, 2014.

148.

Lin

, Li

E.N.

, et al. Osteochondral tissue chip derived from iPSCs: modeling OA pathologies and testing drugs. Front Bioeng Biotechnol, 7, 411, 2019.

149.

Occhetta

, Mainardi

, Votta

, et al. Hyperphysiological compression of articular cartilage induces an osteoarthritic phenotype in a cartilage-on-a-chip model. Nat Biomed Eng, 3, 545, 2019.

150.

Zhao

, Rafatian

, Feric

N.T.

, et al. A platform for generation of chamber-specific cardiac tissues and disease modeling. Cell, 176, 913, 2019.

151.

Ronaldson-Bouchard

, and Vunjak-Novakovic

Organs-on-a-chip: a fast track for engineered human tissues in drug development. Cell Stem Cell, 22, 310, 2018.

152.

Chou

D.B.

, Frismantas

, Milton

, et al. On-chip recapitulation of clinical bone marrow toxicities and patient-specific pathophysiology. Nat Biomed Eng, 4, 394, 2020.

153.

Antoni

, Burckel

, Josset

, and Noel

Three-dimensional cell culture: a breakthrough in vivo. Int J Mol Sci, 16, 5517, 2015.

154.

Karsdal

M.A.

, Michaelis

, Ladel

, et al. Disease-modifying treatments for osteoarthritis (DMOADs) of the knee and hip: lessons learned from failures and opportunities for the future. Osteoarthritis Cartilage, 24, 2013, 2016.

155.

Carlson

A.K.

, Rawle

R.A.

, Adams

, Greenwood

M.C.

, Bothner

, and June

R.K.

Application of global metabolomic profiling of synovial fluid for osteoarthritis biomarkers. Biochem Biophys Res Commun, 499, 182, 2018.

156.

Carlson

A.K.

, Rawle

R.A.

, Wallace

C.W.

, et al. Characterization of synovial fluid metabolomic phenotypes of cartilage morphological changes associated with osteoarthritis. Osteoarthritis Cartilage, 27, 1174, 2019.

157.

Dunn

S.L.

, Soul

, Anand

, Schwartz

J.M.

, Boot-Handford

R.P.

, and Hardingham

T.E.

Gene expression changes in damaged osteoarthritic cartilage identify a signature of non-chondrogenic and mechanical responses. Osteoarthritis Cartilage, 24, 1431, 2016.

158.

, Yang

H.H.

, Sun

Z.G.

, Tang

H.B.

, and Min

J.K.

Whole-transcriptome sequencing of knee joint cartilage from osteoarthritis patients. Bone Joint Res, 8, 290, 2019.