Molecular taxonomy of osteoarthritis for patient stratification, disease management and drug development: biochemical markers associated with emerging clinical phenotypes and molecular endotypes

Transformative approaches for effective clinical trials to reduce the disease burden of osteoarthritis

Osteoarthritis (OA) is a leading cause of disability and morbidity that has eluded development of effective disease modifying drugs and therapies. While established OA in the form of symptomatic radiographic disease is a recognizable final common pathway, OA development encompasses a broad spectrum of pathological changes, susceptibilities, and etiological pathways that cannot be considered a single disease process. Beginning with preclinical disease where radiographs are normal, the concept of pre-osteoarthritis (pre-OA) offers a systems-based approach to OA prevention by targeting reduction of OA risk prior to the onset of definable OA. Early OA ensues when cellular, molecular, and joint tissue changes begin to overlap that of OA, a process that can begin before the onset of definitive symptoms or radiographic changes. A myriad of pathways and crossroads of pre-OA and early OA eventually leads to poorly irreversible symptomatic radiographic OA. With increasing recognition of pre-OA and early OA markers, pathways and subtypes, opportunities arise to address these new therapeutic targets. The current status of clinical trials in OA was identified as a critical barrier to progress by the 2022 National Institute of Arthritis, Musculoskeletal, and Skin Diseases (NIAMS) Roundtable on "Cartilage Preservation and Restoration in Knee Osteoarthritis: Challenges, Gaps, and Opportunities". This manuscript summarizes the recommendations of the work group established from the Roundtable to address this issue. The work group recommends that clinical trial design and endpoints evolve to effectively evaluate new treatment approaches suitable for pre-osteoarthritis and early OA by different criteria than what has been set for symptomatic radiographic OA. While symptomatic improvement is the primary goal for palliation of irreversible established OA, important goals for treating earlier disease states include disease modification and prevention, with the potential to alter the natural history of progressive OA. Because symptoms may not correlate with structural changes in pre-OA and early OA, the primary outcomes in these trials need to match the intended mechanistic target and the therapeutic goal for the disease state being treated. The purpose of this manuscript is to transform the approach to clinical trials in OA by establishing a new benchmark of identifying critical outcomes that are appropriate for the joint disease states and subtypes of the target patient population, and the therapeutic or mechanistic target of the intervention being tested. By shifting the approach from using standardized outcomes based on established OA towards customizing clinical trials according to these principles, new precision medicine strategies to address the full spectrum of disease from pre-OA to OA can be more readily advanced into clinical practice.

Differential Responses of Articular Chondrocytes from Diabetic and Non-Diabetic Rats to Glucose Conditions and Inflammatory Stimuli: Influence of a Vitamin K2 Enriched Diet

ObjectiveMeanwhile, the association between osteoarthritis (OA) and type 2 diabetes mellitus (T2DM) is well known. However, it remains unclear whether vitamin K2 (vit.K2) could exert chondroprotective effects. Hence, this study investigates the interrelation between OA and T2DM under the influence of vit.K2 in chondrocytes.MethodsUsing an in vitro OA/T2DM model, articular chondrocytes were harvested from adult male Zucker diabetic fatty (ZDF) Leptfa/Crl rats, categorized as non-diabetic (heterozygous: fa/+) or diabetic (homozygous: fa/fa). Based on vit.K2 supplementation of the rats, four groups arose: control without or with vit.K2 and diabetic without or with vit.K2 supplementation. Inflammatory conditions simulating OA were induced by exposing chondrocytes to tumor necrosis factor alpha (TNFα) and C5a. Chondrocyte response was analyzed using proliferation, metabolic and wound healing assays, immunolabeling, as well as gene expression analyses.ResultsThe proliferation of chondrocytes from control rats with vit.K2 supplementation was significantly higher than those without vit.K2 feeding, under both normoglycemic (NG) and hyperglycemic (HG) conditions. The wound closure ability of chondrocytes was significantly higher in the non-diabetic compared with the diabetic chondrocyte donor group. TNFα and C5a exerted catabolic effects under HG conditions by significantly inducing Tnfα gene activity in chondrocytes of control rats without vit.K2 supplementation and a significant reduction of collagen type 2 gene expression in those cells of control rats with vit.K2 supplementation.ConclusionsThe response of chondrocytes derived from non-diabetic and diabetic donors differed. The vit.K2 supply of chondrocyte donor rats exerted anabolic effects on chondrocytes.

Rethinking Osteoarthritis Management: Synergistic Effects of Chronoexercise, Circadian Rhythm, and Chondroprotective Agents

Osteoarthritis (OA) is a chronic and debilitating joint disease characterized by progressive cartilage degeneration for which no definitive cure exists. Conventional management approaches often rely on fragmented and poorly coordinated pharmacological and non-pharmacological interventions that are inconsistently applied throughout the disease course. Persistent controversies regarding the clinical efficacy of chondroprotective agents, frequently highlighted by pharmacovigilance agencies, underscore the need for a structured evidence-based approach. Emerging evidence suggests that synchronizing pharmacotherapy and exercise regimens with circadian biology may optimize therapeutic outcomes by addressing early pathological processes, including low-grade inflammation, oxidative stress, and matrix degradation. Recognizing the influence of the chondrocyte clock on these processes, this study proposes a 'prototype' for a novel framework that leverages the circadian rhythm-aligned administration of traditional chondroprotective agents along with tailored, accessible exercise protocols to mitigate cartilage breakdown and support joint function. In addition, this model-based framework emphasizes the interdependence between cartilage chronobiology and time-of-day-dependent responses to exercise, where strategically timed joint activity enhances nutrient and waste exchange, mitigates mitochondrial dysfunction, supports cellular metabolism, and promotes tissue maintenance, whereas nighttime rest promotes cartilage rehydration and repair. This time-sensitive, comprehensive approach aims to slow OA progression, reduce structural damage, and delay invasive procedures, particularly in weight-bearing joints such as the knee and hip. However, significant challenges remain, including inter-individual variability in circadian rhythms, a lack of reliable biomarkers for pharmacotherapeutic monitoring, and limited clinical evidence supporting chronoexercise protocols. Future large-scale, longitudinal trials are critical to evaluate the efficacy and scalability of this rational integrative strategy, paving the way for a new era in OA management.

[Biomarkers and Their Role in Understanding Osteoarthritis]

Osteoarthritis (OA) is a degenerative joint disease characterized by progressive damage and loss of articular cartilage with concomitant structural and functional changes in the joint. It is the most common cause of joint pain globally and the resulting productivity loss to the economy. The clinical symptoms of osteoarthritis are mostly determined by the difficulties of patients related to the development of articular degenerative changes, which secondarily lead to joint stiffness and functional limitation. The diagnosis of this disease is currently based on typical clinical symptoms and radiographic findings (e.g. joint space narrowing, osteophytes, subchondral sclerosis, etc.). These parameters, however, are difficult to detect in the early stages of the disease and are most often recognized in the advanced stages. For these reasons, the diagnosis of osteoarthritis is often delayed until irreversible destruction of joint tissue occurs and conservative treatment is less effective. Despite recent scientific progress in understanding the genetic and molecular principles of joint degeneration, currently there is no reliable causal therapy for OA. This review aims to summarize current knowledge of osteoarthritis and possible future directions for diagnosis and early intervention. One of such directions is the study of the so-called biomarkers. A biomarker is defined as an indicator of biological processes and can include radiographic, histological, physiological, or molecular characteristics. In particular, molecular biomarkers are widely studied in knee OA. Attention of the research community is focused on the study of biomarkers as a method of detection and prediction of the early stages of osteoarthritis before irreversible joint damage occurs. Biomarkers help develop more effective and, above all, personalized treatment, thus improve the overall clinical approach to the patient.

Longitudinal stability of molecular endotypes of knee osteoarthritis patients

OBJECTIVE

To assess the longitudinal stability of biomarker-based molecular endotypes of knee osteoarthritis (KOA) participants from APPROACH and to evaluate the consistency of findings in an independent KOA population.

METHODS

Nineteen biomarkers were measured longitudinally in 295 KOA participants from the APPROACH cohort. K-means clustering was used to identify the structural damage, inflammation, and low tissue turnover endotypes at the six-, 12-, and 24-month follow-ups. Endotype stability was defined as having the same independent endotype assignment longitudinally for patients with complete data (n = 226). Clinical and biochemical characteristics were compared between participants with longitudinally stable and unstable endotypes. The presence and longitudinal stability of the endotypes were evaluated in a different KOA population from the placebo arm of the oral salmon calcitonin trials.

RESULTS

An average overall longitudinal endotype stability of 55% (Fleiss' Kappa of 0.53; 95% confidence interval [CI]: 0.46, 0.60) was demonstrated. An average stability of 59% (range: 54-59%) was observed for the structural damage endotype (Fleiss' Kappa 0.52; 95% CI: 0.45, 0.60), 54% (52-56%) for the inflammatory (Fleiss' Kappa 0.61; 95% CI: 0.53, 0.68), and 50% (49-52%) for the low tissue turnover endotype (Fleiss' Kappa 0.46; 95% CI: 0.39, 0.54). Participants with longitudinally unstable endotypes exhibited molecular properties of more than one endotype, which were detectable already at the first visit.

CONCLUSIONS

Our study showed for the first time that more than half of KOA participants exhibited a longitudinally stable endotype, highlighting the applicability of biomarker-based endotyping in a clinical trial setting.

Multi-centre modified Delphi exercise to identify candidate items for classifying early-stage symptomatic knee osteoarthritis

OBJECTIVE

To generate a list of candidate items potentially useful for discriminating individuals with Early-stage Symptomatic Knee Osteoarthritis (EsSKOA) from those with other conditions and from established osteoarthritis (OA), and to reduce this list based on expert consensus.

DESIGN

We conducted a three-round online international modified Delphi exercise with OA clinicians and researchers ("OA experts"). In Round 1, participants reviewed 84 candidate items and nominated additional item(s) potentially useful for EsSKOA classification; those nominated by ≥3 participants were added. In Round 2, participants rated perceived usefulness of 108 items (1 [not at all useful] to 9 [extremely useful]). In Round 3, participants could revise their ratings after reviewing Round 2 group median and quartiles. Following Round 3, we retained items with a median usefulness score >5 and ≥33.3% of participants categorised the item as useful (7 to 9), overall and in subgroup analysis by clinician field.

RESULTS

There were 128 participants in Round 1 and 113 (88%) completed all rounds. We retained 77 items that spanned multiple domains (demographics, symptoms, physical exam, performance-based measures, imaging, laboratory investigations, and gross inspection/arthroscopy). Highly rated items included (median usefulness score): prior knee joint injury (8), diagnosis of OA in a different joint (7), and activity-related knee pain (7). The interquartile range was most often 3.

CONCLUSION

We identified 77 items that OA experts consider potentially useful for EsSKOA classification. The results highlight experts' uncertainty around item usefulness. Next, candidate items will be further assessed and reduced using data-driven and multicriteria decision analysis methods.

Development of methodology to support molecular endotype discovery from synovial fluid of individuals with knee osteoarthritis: The STEpUP OA consortium

OBJECTIVES

To develop a protocol for largescale analysis of synovial fluid proteins, for the identification of biological networks associated with subtypes of osteoarthritis.

METHODS

Synovial Fluid To detect molecular Endotypes by Unbiased Proteomics in Osteoarthritis (STEpUP OA) is an international consortium utilising clinical data (capturing pain, radiographic severity and demographic features) and knee synovial fluid from 17 participating cohorts. 1746 samples from 1650 individuals comprising OA, joint injury, healthy and inflammatory arthritis controls, divided into discovery (n = 1045) and replication (n = 701) datasets, were analysed by SomaScan Discovery Plex V4.1 (>7000 SOMAmers/proteins). An optimised approach to standardisation was developed. Technical confounders and batch-effects were identified and adjusted for. Poorly performing SOMAmers and samples were excluded. Variance in the data was determined by principal component (PC) analysis.

RESULTS

A synovial fluid standardised protocol was optimised that had good reliability (<20% co-efficient of variation for >80% of SOMAmers in pooled samples) and overall good correlation with immunoassay. 1720 samples and >6290 SOMAmers met inclusion criteria. 48% of data variance (PC1) was strongly correlated with individual SOMAmer signal intensities, particularly with low abundance proteins (median correlation coefficient 0.70), and was enriched for nuclear and non-secreted proteins. We concluded that this component was predominantly intracellular proteins, and could be adjusted for using an 'intracellular protein score' (IPS). PC2 (7% variance) was attributable to processing batch and was batch-corrected by ComBat. Lesser effects were attributed to other technical confounders. Data visualisation revealed clustering of injury and OA cases in overlapping but distinguishable areas of high-dimensional proteomic space.

CONCLUSIONS

We have developed a robust method for analysing synovial fluid protein, creating a molecular and clinical dataset of unprecedented scale to explore potential patient subtypes and the molecular pathogenesis of OA. Such methodology underpins the development of new approaches to tackle this disease which remains a huge societal challenge.

Targeting FAP-positive chondrocytes in osteoarthritis: a novel lipid nanoparticle siRNA approach to mitigate cartilage degeneration

BACKGROUND

Osteoarthritis (OA) is a common joint disease that leads to chronic pain and functional limitations. Recent research has revealed soluble fibroblast activation protein (FAP) secreted from OA synovium could degrade type II collagen (Col2) in cartilage to promote the progression of OA. This study aimed to reveal the role of FAP from chondrocytes in OA and develop a novel lipid nanoparticle (LNP)-FAP siRNA delivery system for OA treatment.

METHODS

The expression of FAP in the cartilage of knee OA patients was investigated using [68 Ga]Ga-FAPI-04 PET in vivo and immunofluorescence, western blotting, and RT-qPCR in vitro. Cell senescence was determined by senescence-associated β-galactosidase (SA-β-Gal) assay after FAP overexpressing or knockdown in chondrocytes. An OA model with chondrocyte-specific FAP knockout mice was applied to investigate the role of FAP in chondrocyte senescence and OA development. The therapeutic effects of lipid nanoparticle (LNP) @FAP siRNA on cartilage degeneration were evaluated in the rat OA model.

RESULTS

Our study found that higher [68 Ga]Ga-FAPI-04 uptake was detected in knee OA patients by PET/CT scan. FAP mRNA and protein levels were highly expressed in OA-damaged cartilage. Moreover, we found that overexpression of FAP promotes chondrocyte senescence, and the genetic knockout of FAP in chondrocytes alleviates OA. Knockdown FAP by siRNA could alleviate chondrocyte senescence and suppress the NF-κB pathway to reduce the senescence-associated secretory phenotype (SASP). In the rat model of OA, intraarticular injection of LNP@FAP siRNA can reduce senescent cells and ameliorate cartilage destruction.

CONCLUSION

FAP-positive chondrocytes play a significant role in the pathogenesis of OA. Targeting these cells selectively has the potential to mitigate the progression of the disease. Our study provides valuable insights into the intraarticular injection of LNP@FAP siRNA as a promising strategy for the treatment of OA.

Prospects of Disease-Modifying Osteoarthritis Drugs

Osteoarthritis (OA) causes a massive disease burden with a global prevalence of nearly 23% in 2020 and an unmet need for adequate treatment, given a lack of disease-modifying drugs (DMOADs). The author reviews the prospects of active DMOAD candidates in the phase 2/3 clinical trials of drug development pipeline based on key OA pathogenetic mechanisms directed to inflammation-driven, bone-driven, and cartilage-driven endotypes. The challenges and possible research opportunities are stated in terms of the formulation of a research question known as the PICO approach: (1) population, (2) interventions, (3) comparison or placebo, and (4) outcomes.

The efficacy and safety of a fixed-dose combination of apocynin and paeonol, APPA, in symptomatic knee OA: A double-blind, randomized, placebo-controlled, clinical trial

OBJECTIVE

Apocynin (AP) and paeonol (PA) are low molecular weight phenolic compounds with a broad array of anti-inflammatory and immunoregulatory effects. This study assessed of a fixed-dose combination of APPA in people with symptomatic knee osteoarthritis (OA).

METHODS

A multi-center, randomized, placebo-controlled, double-blind phase 2a trial enrolled participants with radiographic knee OA (Kellgren-Lawrence, KL, grades 2-3) and pain ≥40/100 on WOMAC pain subscale, and evaluated the efficacy and safety of oral APPA over a 28-day period. APPA 800 mg or matching placebo was administered twice daily in a 1:1 ratio. Post-hoc analyses explored the response to APPA in sub-groups with more severe pain and structural severity.

RESULTS

The two groups were comparable at baseline; 152 subjects were enrolled and 148 completed the trial. There was no statistically significant difference between groups with respect to the primary outcome, WOMAC pain (mean difference between groups was -0.89, 95% CI: -5.62, 3.84, p = 0.71), nor WOMAC function or WOMAC total. However, predefined subgroup analyses of subjects with symptoms compatible with nociplastic/neuropathic pain features showed a statistically significant effect of APPA compared to placebo. Adverse events (mainly gastrointestinal) were mild to moderate.

CONCLUSION

Treatment with APPA 800 mg twice daily for 28 days in subjects with symptomatic knee OA was not associated with significant symptom improvement compared to placebo. The treatment was well-tolerated and safe. While the study was not powered for such analysis, pre-planned subgroup analyses showed a significant effect of APPA in subjects with nociplastic pain/severe OA, indicating that further research in the effects of APPA in appropriate patients is warranted.

Prognostic value of B-score for predicting joint replacement in the context of osteoarthritis phenotypes: Data from the osteoarthritis initiative

Objective

Developing new therapies for knee osteoarthritis (KOA) requires improved prediction of disease progression. This study evaluated the prognostic value of clinical clusters and machine-learning derived quantitative 3D bone shape B-score for predicting total and partial knee replacement (KR).

Design

This retrospective study used longitudinal data from the Osteoarthritis Initiative. A previous study used patients' clinical profiles to delineate phenotypic clusters. For these clusters, the distribution of B-scores was assessed (employing Tukey's method). The value of both cluster allocation and B-score for KR-prediction was then evaluated using multivariable Cox regression models and Kaplan-Meier curves for time-to-event analyses. The impact of using B-score vs. cluster was evaluated using a likelihood ratio test for the multivariable Cox model; global performances were assessed by concordance statistics (Harrell's C-index) and time dependent receiver operating characteristic (ROC) curves.

Results

B-score differed significantly for the individual clinical clusters (p ​< ​0.001). Overall, 9.4% of participants had a KR over 9 years, with a shorter time to event in clusters with high B-score at baseline. Those clusters were characterized clinically by a high rate of comorbidities and potential signs of inflammation. Both phenotype and B-score independently predicted KR, with better prediction if combined (P ​< ​0.001). B-score added predictive value in groups with less pain and radiographic severity but limited physical activity.

Conclusions

B-scores correlated with phenotypes based on clinical patient profiles. B-score and phenotype independently predicted KR surgery, with higher predictive value if combined. This can be used for patient stratification in drug development and potentially risk prediction in clinical practice.

Potential therapeutic strategies for osteoarthritis via CRISPR/Cas9 mediated gene editing

Osteoarthritis (OA) is an incapacitating and one of the most common physically degenerative conditions with an assorted etiology and a highly complicated molecular mechanism that to date lacks an efficient treatment. The capacity to design biological networks and accurately modify existing genomic sites holds an apt potential for applications across medical and biotechnological sciences. One of these highly specific genomes editing technologies is the CRISPR/Cas9 mechanism, referred to as the clustered regularly interspaced short palindromic repeats, which is a defense mechanism constituted by CRISPR associated protein 9 (Cas9) directed by small non-coding RNAs (sncRNA) that bind to target DNA through Watson-Crick base pairing rules where subsequent repair of the target DNA is initiated. Up-to-date research has established the effectiveness of the CRISPR/Cas9 mechanism in targeting the genetic and epigenetic alterations in OA by suppressing or deleting gene expressions and eventually distributing distinctive anti-arthritic properties in both in vitro and in vivo osteoarthritic models. This review aims to epitomize the role of this high-throughput and multiplexed gene editing method as an analogous therapeutic strategy that could greatly facilitate the clinical development of OA-related treatments since it's reportedly an easy, minimally invasive technique, and a comparatively less painful method for osteoarthritic patients.

Pain-phenotyping in osteoarthritis: Current concepts, evidence, and considerations towards a comprehensive framework for assessment and treatment

Objectives

Pain as central symptom of osteoarthritis (OA) needs to be addressed as part of successful treatment. The assessment of pain as feature of disease or outcome in clinical practice and drug development remains a challenge due to its multidimensionality and the plethora of confounders. This article aims at providing insights into our understanding of OA pain-phenotypes and suggests a framework for systematic and comprehensive assessments.

Methods

This narrative review is based on a search of current literature for various combinations of the search terms "pain-phenotype" and "knee OA" and summarizes current knowledge on OA pain-phenotypes, putting OA pain and its assessment into perspective of current research efforts.

Results

Pain is a complex phenomenon, not necessarily associated with tissue damage. Various pain-phenotypes have been described in knee OA. Among those, a phenotype with high pain levels not necessarily matching structural changes and a phenotype with low pain levels and impact are relatively consistent. Further subgroups can be differentiated based on patient reported outcome measures, assessments of comorbidities, anxiety and depression, sleep, activity and objective measures such as quantitative sensory testing.

Conclusions

The complexity of both OA as disease and pain in OA prompt the definition of a set of variables that facilitate assessments comparable across studies to maximize our understanding of pain, as central concern for the patient.

Association of biochemical markers with bone marrow lesion changes on imaging-data from the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium

BACKGROUND

To assess the prognostic value of short-term change in biochemical markers as it relates to bone marrow lesions (BMLs) on MRI in knee osteoarthritis (OA) over 24 months and, furthermore, to assess the relationship between biochemical markers involved with tissue turnover and inflammation and BMLs on MRI.

METHODS

Data from the Foundation for the National Institutes of Health OA Biomarkers Consortium within the Osteoarthritis Initiative (n = 600) was analyzed. BMLs were measured according to the MRI Osteoarthritis Knee Score (MOAKS) system (0-3), in 15 knee subregions. Serum and urinary biochemical markers assessed were as follows: serum C-terminal crosslinked telopeptide of type I collagen (CTX-I), serum crosslinked N-telopeptide of type I collagen (NTX-I), urinary CTX-Iα and CTX-Iβ, urinary NTX-I, urinary C-terminal cross-linked telopeptide of type II collagen (CTX-II), serum matrix metalloproteinase (MMP)-degraded type I, II, and III collagen (C1M, C2M, C3M), serum high sensitivity propeptide of type IIb collagen (hsPRO-C2), and matrix metalloproteinase-generated neoepitope of C-reactive protein (CRPM). The association between change in biochemical markers over 12 months and BMLs over 24 months was examined using regression models adjusted for covariates. The relationship between C1M, C2M, C3M, hsPRO-C2, and CRPM and BMLs at baseline and over 24 months was examined.

RESULTS

Increases in serum CTX-I and urinary CTX-Iβ over 12 months were associated with increased odds of changes in the number of subregions affected by any BML at 24 months. Increase in hsPRO-C2 was associated with decreased odds of worsening in the number of subregions affected by any BML over 24 months. C1M and C3M were associated with BMLs affected at baseline.

CONCLUSIONS

Short-term changes in serum CTX-I, hsPRO-C2, and urinary CTX-Iβ hold the potential to be prognostic of BML progression on MRI. The association of C1M and C3M with baseline BMLs on MRI warrants further investigation.

Specific-cytokine associations with outcomes in knee osteoarthritis subgroups: breaking down disease heterogeneity with phenotyping

BACKGROUND

Despite existing extensive literature, a comprehensive and clinically relevant classification system for osteoarthritis (OA) has yet to be established. In this study, we aimed to further characterize four knee OA (KOA) inflammatory phenotypes (KOIP) recently proposed by our group, by identifying the inflammatory factors associated with KOA severity and progression in a phenotype-specific manner.

METHODS

We performed an analysis within each of the previously defined four KOIP groups, to assess the association between KOA severity and progression and a panel of 13 cytokines evaluated in the plasma and synovial fluid of our cohort's patients. The cohort included 168 symptomatic female KOA patients with persistent joint effusion.

RESULTS

Overall, our analyses showed that associations with KOA outcomes were of higher magnitude within the KOIP groups than for the overall patient series (all p-values < 1.30e-16) and that several of the cytokines showed a KOIP-specific behaviour regarding their associations with KOA outcomes.

CONCLUSION

Our study adds further evidence supporting KOA as a multifaceted syndrome composed of multiple phenotypes with differing pathophysiological pathways, providing an explanation for inconsistencies between previous studies focussed on the role of cytokines in OA and the lack of translational results to date. Our findings also highlight the potential clinical benefits of accurately phenotyping KOA patients, including improved patient stratification, tailored therapies, and the discovery of novel treatments.

From biochemical markers to molecular endotypes of osteoarthritis: a review on validated biomarkers

INTRODUCTION

Osteoarthritis (OA) affects over 500 million people worldwide. OA patients are symptomatically treated, and current therapies exhibit marginal efficacy and frequently carry safety-risks associated with chronic use. No disease-modifying therapies have been approved to date leaving surgical joint replacement as a last resort. To enable effective patient care and successful drug development there is an urgent need to uncover the pathobiological drivers of OA and how these translate into disease endotypes. Endotypes provide a more precise and mechanistic definition of disease subgroups than observable phenotypes, and a panel of tissue- and pathology-specific biochemical markers may uncover treatable endotypes of OA.

AREAS COVERED

We have searched PubMed for full-text articles written in English to provide an in-depth narrative review of a panel of validated biochemical markers utilized for endotyping of OA and their association to key OA pathologies.

EXPERT OPINION

As utilized in IMI-APPROACH and validated in OAI-FNIH, a panel of biochemical markers may uncover disease subgroups and facilitate the enrichment of treatable molecular endotypes for recruitment in therapeutic clinical trials. Understanding the link between biochemical markers and patient-reported outcomes and treatable endotypes that may respond to given therapies will pave the way for new drug development in OA.

Machine Learning Approaches to the Prediction of Osteoarthritis Phenotypes and Outcomes

PURPOSE OF REVIEW

Osteoarthritis (OA) is a complex heterogeneous disease with no effective treatments. Artificial intelligence (AI) and its subfield machine learning (ML) can be applied to data from different sources to (1) assist clinicians and patients in decision making, based on machine-learned evidence, and (2) improve our understanding of pathophysiology and mechanisms underlying OA, providing new insights into disease management and prevention. The purpose of this review is to improve the ability of clinicians and OA researchers to understand the strengths and limitations of AI/ML methods in applications to OA research.

RECENT FINDINGS

AI/ML can assist clinicians by prediction of OA incidence and progression and by providing tailored personalized treatment. These methods allow using multidimensional multi-source data to understand the nature of OA, to identify different OA phenotypes, and for biomarker discovery. We described the recent implementations of AI/ML in OA research and highlighted potential future directions and associated challenges.

PSD95 as a New Potential Therapeutic Target of Osteoarthritis: A Study of the Identification of Hub Genes through Self-Contrast Model

Osteoarthritis (OA) is a worldwide joint disease. However, the precise mechanism causing OA remains unclear. Our primary aim was to identify vital biomarkers associated with the mechano-inflammatory aspect of OA, providing potential diagnostic and therapeutic targets for OA. Thirty OA patients who underwent total knee arthroplasty were recruited, and cartilage samples were obtained from both the lateral tibial plateau (LTP) and medial tibial plateau (MTP). GO and KEGG enrichment analyses were performed, and the protein-protein interaction (PPI) assessment was conducted for hub genes. The effect of PSD95 inhibition on cartilage degeneration was also conducted and analyzed. A total of 1247 upregulated and 244 downregulated DEGs were identified. Significant differences were observed between MTP and LTP in mechanical stress-related genes and activated sensory neurons based on a self-contrast model of human knee OA. Cluster analysis identified DLG4 as the hub gene. Cyclic loading stress increased PSD95 (encoded by DLG4) expression in LTP cartilage, and PSD95 inhibitors could alleviate OA progression. This study suggests that inhibiting PSD95 could be a potential therapeutic strategy for preventing articular cartilage degradation.

Osteomodulin downregulation is associated with osteoarthritis development

Abnormal subchondral bone remodeling leading to sclerosis is a main feature of osteoarthritis (OA), and osteomodulin (OMD), a proteoglycan involved in extracellular matrix mineralization, is associated with the sclerotic phenotype. However, the functions of OMD remain poorly understood, specifically in vivo. We used Omd knockout and overexpressing male mice and mutant zebrafish to study its roles in bone and cartilage metabolism and in the development of OA. The expression of Omd is deeply correlated with bone and cartilage microarchitectures affecting the bone volume and the onset of subchondral bone sclerosis and spontaneous cartilage lesions. Mechanistically, OMD binds to RANKL and inhibits osteoclastogenesis, thus controlling the balance of bone remodeling. In conclusion, OMD is a key factor in subchondral bone sclerosis associated with OA. It participates in bone and cartilage homeostasis by acting on the regulation of osteoclastogenesis. Targeting OMD may be a promising new and personalized approach for OA.

Menstrual Blood-Derived Stem Cell Paracrine Factors Possess Stimulatory Effects on Chondrogenesis In Vitro and Diminish the Degradation of Articular Cartilage during Osteoarthritis

Articular cartilage is an avascular tissue with a limited capacity for self-regeneration, leading the tissue to osteoarthritis (OA). Mesenchymal stem cells (MSCs) are promising for cartilage tissue engineering, as they are capable of differentiating into chondrocyte-like cells and secreting a number of active molecules that are important for cartilage extracellular matrix (ECM) synthesis. The aim of this study was to evaluate the potential of easily accessible menstrual blood-derived MSC (MenSC) paracrine factors in stimulating bone marrow MSC (BMMSCs) chondrogenic differentiation and to investigate their role in protecting cartilage from degradation in vitro. MenSCs and BMMSCs chondrogenic differentiation was induced using four different growth factors: TGF-β3, activin A, BMP-2, and IGF-1. The chondrogenic differentiation of BMMSCs was stimulated in co-cultures with MenSCs and cartilage explants co-cultured with MenSCs for 21 days. The chondrogenic capacity of BMMSCs was analyzed by the secretion of four growth factors and cartilage oligomeric matrix protein, as well as the release and synthesis of cartilage ECM proteins, and chondrogenic gene expression in cartilage explants. Our results suggest that MenSCs stimulate chondrogenic response in BMMSCs by secreting activin A and TGF-β3 and may have protective effects on cartilage tissue ECM by decreasing the release of GAGs, most likely through the modulation of activin A related molecular pathway. In conclusion, paracrine factors secreted by MenSCs may turn out to be a promising therapeutical approach for cartilage tissue protection and repair.

Biomarkers for osteoarthritis: Current status and future prospects

Osteoarthritis (OA) is the most common form of arthritis globally and a major cause of pain, physical disability, and loss of economic productivity, with currently no causal treatment available. This review article focuses on current research on OA biomarkers and the potential for using biomarkers in future clinical practice and clinical trials of investigational drugs. We discuss how biomarkers, specifically soluble ones, have a long path to go before reaching clinical standards of care. We also discuss how biomarkers can help in phenotyping and subtyping to achieve enhanced stratification and move toward better-designed clinical trials. We also describe how biomarkers can be used for molecular endotyping and for determining the clinical outcomes of investigational cell-based therapies. Biomarkers have the potential to be developed as surrogate end points in clinical trials and help private-public consortia and the biotechnology and pharmaceutical industries develop more effective and targeted personalized treatments and enhance clinical care for patients with OA.

Strategic application of imaging in DMOAD clinical trials: focus on eligibility, drug delivery, and semiquantitative assessment of structural progression

Despite decades of research efforts and multiple clinical trials aimed at discovering efficacious disease-modifying osteoarthritis (OA) drugs (DMOAD), we still do not have a drug that shows convincing scientific evidence to be approved as an effective DMOAD. It has been suggested these DMOAD clinical trials were in part unsuccessful since eligibility criteria and imaging-based outcome evaluation were solely based on conventional radiography. The OA research community has been aware of the limitations of conventional radiography being used as a primary imaging modality for eligibility and efficacy assessment in DMOAD trials. An imaging modality for DMOAD trials should be able to depict soft tissue and osseous pathologies that are relevant to OA disease progression and clinical manifestations of OA. Magnetic resonance imaging (MRI) fulfills these criteria and advances in technology and increasing knowledge regarding imaging outcomes likely should play a more prominent role in DMOAD clinical trials. In this perspective article, we will describe MRI-based tools and analytic methods that can be applied to DMOAD clinical trials with a particular emphasis on knee OA. MRI should be the modality of choice for eligibility screening and outcome assessment. Optimal MRI pulse sequences must be chosen to visualize specific features of OA.

The Effect of CaV1.2 Inhibitor Nifedipine on Chondrogenic Differentiation of Human Bone Marrow or Menstrual Blood-Derived Mesenchymal Stem Cells and Chondrocytes

Cartilage is an avascular tissue and sensitive to mechanical trauma and/or age-related degenerative processes leading to the development of osteoarthritis (OA). Therefore, it is important to investigate the mesenchymal cell-based chondrogenic regenerating mechanisms and possible their regulation. The aim of this study was to investigate the role of intracellular calcium (iCa2+) and its regulation through voltage-operated calcium channels (VOCC) on chondrogenic differentiation of mesenchymal stem/stromal cells derived from human bone marrow (BMMSCs) and menstrual blood (MenSCs) in comparison to OA chondrocytes. The level of iCa2+ was highest in chondrocytes, whereas iCa2+ store capacity was biggest in MenSCs and they proliferated better as compared to other cells. The level of CaV1.2 channels was also highest in OA chondrocytes than in other cells. CaV1.2 antagonist nifedipine slightly suppressed iCa2+, Cav1.2 and the proliferation of all cells and affected iCa2+ stores, particularly in BMMSCs. The expression of the CaV1.2 gene during 21 days of chondrogenic differentiation was highest in MenSCs, showing the weakest chondrogenic differentiation, which was stimulated by the nifedipine. The best chondrogenic differentiation potential showed BMMSCs (SOX9 and COL2A1 expression); however, purposeful iCa2+ and VOCC regulation by blockers can stimulate a chondrogenic response at least in MenSCs.

NOTCH1: A Novel Player in the Molecular Crosstalk Underlying Articular Chondrocyte Protection by Oleuropein and Hydroxytyrosol

Osteoarthritis (OA) is the most common joint disease, but no effective and safe disease-modifying treatment is available. Risk factors such as age, sex, genetics, injuries and obesity can concur to the onset of the disease, variably triggering the loss of maturational arrest of chondrocytes further sustained by oxidative stress, inflammation and catabolism. Different types of nutraceuticals have been studied for their anti-oxidative and anti-inflammatory properties. Olive-derived polyphenols draw particular interest due to their ability to dampen the activation of pivotal signaling pathways in OA. Our study aims to investigate the effects of oleuropein (OE) and hydroxytyrosol (HT) in in vitro OA models and elucidate their possible effects on NOTCH1, a novel therapeutic target for OA. Chondrocytes were cultured and exposed to lipopolysaccharide (LPS). Detailed analysis was carried out about the OE/HT mitigating effects on the release of ROS (DCHF-DA), the increased gene expression of catabolic and inflammatory markers (real time RT-PCR), the release of MMP-13 (ELISA and Western blot) and the activation of underlying signaling pathways (Western blot). Our findings show that HT/OE efficiently attenuates LPS-induced effects by firstly reducing the activation of JNK and of the NOTCH1 pathway downstream. In conclusion, our study provides molecular bases supporting the dietary supplementation of olive-derived polyphenols to revert/delay the progression of OA.

The application of machine learning in early diagnosis of osteoarthritis: a narrative review

Osteoarthritis (OA) is the commonest musculoskeletal disease worldwide, with an increasing prevalence due to aging. It causes joint pain and disability, decreased quality of life, and a huge burden on healthcare services for society. However, the current main diagnostic methods are not suitable for early diagnosing patients of OA. The use of machine learning (ML) in OA diagnosis has increased dramatically in the past few years. Hence, in this review article, we describe the research progress in the application of ML in the early diagnosis of OA, discuss the current trends and limitations of ML approaches, and propose future research priorities to apply the tools in the field of OA. Accurate ML-based predictive models with imaging techniques that are sensitive to early changes in OA ahead of the emergence of clinical features are expected to address the current dilemma. The diagnostic ability of the fusion model that combines multidimensional information makes patient-specific early diagnosis and prognosis estimation of OA possible in the future.

Network-based modelling of mechano-inflammatory chondrocyte regulation in early osteoarthritis

Osteoarthritis (OA) is a debilitating joint disease characterized by articular cartilage degradation, inflammation and pain. An extensive range of in vivo and in vitro studies evidences that mechanical loads induce changes in chondrocyte gene expression, through a process known as mechanotransduction. It involves cascades of complex molecular interactions that convert physical signals into cellular response(s) that favor either chondroprotection or cartilage destruction. Systematic representations of those interactions can positively inform early strategies for OA management, and dynamic modelling allows semi-quantitative representations of the steady states of complex biological system according to imposed initial conditions. Yet, mechanotransduction is rarely integrated. Hence, a novel mechano-sensitive network-based model is proposed, in the form of a continuous dynamical system: an interactome of a set of 118 nodes, i.e., mechano-sensitive cellular receptors, second messengers, transcription factors and proteins, related among each other through a specific topology of 358 directed edges is developed. Results show that under physio-osmotic initial conditions, an anabolic state is reached, whereas initial perturbations caused by pro-inflammatory and injurious mechanical loads leads to a catabolic profile of node expression. More specifically, healthy chondrocyte markers (Sox9 and CITED2) are fully expressed under physio-osmotic conditions, and reduced under inflammation, or injurious loadings. In contrast, NF-κB and Runx₂, characteristic of an osteoarthritic chondrocyte, become activated under inflammation or excessive loading regimes. A literature-based evaluation shows that the model can replicate 94% of the experiments tested. Sensitivity analysis based on a factorial design of a treatment shows that inflammation has the strongest influence on chondrocyte metabolism, along with a significant deleterious effect of static compressive loads. At the same time, anti-inflammatory therapies appear as the most promising ones, though the restoration of structural protein production seems to remain a major challenge even in beneficial mechanical environments. The newly developed mechano-sensitive network model for chondrocyte activity reveals a unique potential to reflect load-induced chondroprotection or articular cartilage degradation in different mechano-chemical-environments.

Unsupervised machine-learning algorithms for the identification of clinical phenotypes in the osteoarthritis initiative database

OBJECTIVES

Osteoarthritis (OA) is a complex disease comprising diverse underlying patho-mechanisms. To enable the development of effective therapies, segmentation of the heterogenous patient population is critical. This study aimed at identifying such patient clusters using two different machine learning algorithms.

METHODS

Using the progression and incident cohorts of the Osteoarthritis Initiative (OAI) dataset, deep embedded clustering (DEC) and multiple factor analysis with clustering (MFAC) approaches, including 157 input-variables at baseline, were employed to differentiate specific patient profiles.

RESULTS

DEC resulted in 5 and MFAC in 3 distinct patient phenotypes. Both identified a "comorbid" cluster with higher body mass index (BMI), relevant burden of comorbidity and low levels of physical activity. Both methods also identified a younger and physically more active cluster and an elderly cluster with functional limitations, but low disease impact. The additional two clusters identified with DEC were subgroups of the young/physically active and the elderly/physically inactive clusters. Overall pain trajectories over 9 years were stable, only the numeric rating scale (NRS) for pain showed distinct increase, while physical activity decreased in all clusters. Clusters showed different (though non-significant) trajectories of joint space changes over the follow-up period of 8 years.

CONCLUSION

Two different clustering approaches yielded similar patient allocations primarily separating complex "comorbid" patients from healthier subjects, the latter divided in young/physically active vs elderly/physically inactive subjects. The observed association to clinical (pain/physical activity) and structural progression could be helpful for early trial design as strategy to enrich for patients who may specifically benefit from disease-modifying treatments.

Osteoarthritis, an old wine in a new bottle!

Osteoarthritis (OA) is the most common form of arthritis that has a major impact on patient morbidity and health care services. Despite its prevalence and impact, we do not have any effective management strategy to prevent or control their manifestations. Several decades of pharmacological development have failed to deliver a disease-modifying solution to OA. This editorial article outlines the lacunae in the research efforts of the past, the challenges that we are facing at present, and the exciting opportunities we have in the future for the management of OA. OA research has to be made more personalized concerning the phenotypic and endotypic disease variants. To begin with, robust disease classification criteria need to be defined for early OA, and biomarkers to detect such early diseases to aid in patient stratification. We also need to refine our clinical research design to make them more objective to meet the demands of the patient and the regulatory agencies. Embracing the current technologies such as artificial intelligence along with the use of genomic profiling from the omics platforms, the future of OA is more promising in developing appropriate management of OA.

An integrated in silico-in vitro approach for identifying therapeutic targets against osteoarthritis

BACKGROUND

Without the availability of disease-modifying drugs, there is an unmet therapeutic need for osteoarthritic patients. During osteoarthritis, the homeostasis of articular chondrocytes is dysregulated and a phenotypical transition called hypertrophy occurs, leading to cartilage degeneration. Targeting this phenotypic transition has emerged as a potential therapeutic strategy. Chondrocyte phenotype maintenance and switch are controlled by an intricate network of intracellular factors, each influenced by a myriad of feedback mechanisms, making it challenging to intuitively predict treatment outcomes, while in silico modeling can help unravel that complexity. In this study, we aim to develop a virtual articular chondrocyte to guide experiments in order to rationalize the identification of potential drug targets via screening of combination therapies through computational modeling and simulations.

RESULTS

We developed a signal transduction network model using knowledge-based and data-driven (machine learning) modeling technologies. The in silico high-throughput screening of (pairwise) perturbations operated with that network model highlighted conditions potentially affecting the hypertrophic switch. A selection of promising combinations was further tested in a murine cell line and primary human chondrocytes, which notably highlighted a previously unreported synergistic effect between the protein kinase A and the fibroblast growth factor receptor 1.

CONCLUSIONS

Here, we provide a virtual articular chondrocyte in the form of a signal transduction interactive knowledge base and of an executable computational model. Our in silico-in vitro strategy opens new routes for developing osteoarthritis targeting therapies by refining the early stages of drug target discovery.

Curcuma longa and Boswellia serrata Extracts Modulate Different and Complementary Pathways on Human Chondrocytes In Vitro: Deciphering of a Transcriptomic Study

Objectives:Curcuma longa (CL) and Boswellia serrata (BS) extracts are used to relieve osteoarthritis symptoms. The aim of this in vitro study was to investigate their mechanisms of action at therapeutic plasmatic concentrations on primary human osteoarthritic (OA) chondrocytes.

Methods: BS (10–50 μg/ml) and CL (0.4–2 μg/ml corresponding to 1–5 µM of curcumin) were evaluated separately or in combination on primary chondrocytes isolated from 17 OA patients and cultured in alginate beads. Ten patients were used for RNA-sequencing analysis. Proteomic confirmation was performed either by immunoassays in the culture supernatant or by flow cytometry for cell surface markers after 72 h of treatment.

Results: Significant gene expression modifications were already observed after 6 h of treatment at the highest dose of CL (2 μg/ml) while BS was significantly effective only after 24 h of treatment irrespective of the concentration tested. The most over-expressed genes by CL were anti-oxidative, detoxifying, and cytoprotective genes involved in the Nrf2 pathway. Down-regulated genes were principally pro-inflammatory cytokines and chemokines. Inversely, BS anti-oxidant/detoxifying activities were related to the activation of Nrf1 and PPARα pathways. BS anti-inflammatory effects were associated with the increase in GDF15, decrease in cholesterol cell intake and fatty acid metabolism-involved genes, and down-regulation of Toll-like receptors (TLRs) activation. Similar to CL, BS down-regulated ADAMTS1, 5, and MMP3, 13 genes expression. The combination of both CL and BS was significantly more effective than CL or BS alone on many genes such as IL-6, CCL2, ADAMTS1, and 5.

Conclusion: BS and CL have anti-oxidative, anti-inflammatory, and anti-catabolic activities, suggesting a protective effect of these extracts on cartilage. Even if they share some mechanism of action, the two extracts act mainly on distinct pathways, and with different time courses, justifying their association to treat osteoarthritis.

An improved diagnostic tool to predict cartilage formation in an osteoarthritic joint environment

Osteoarthritis (OA) is a degenerative joint disease with progressive articular cartilage loss. Due to the chondrogenic potential of human mesenchymal stromal cells (MSCs), MSC-based therapies are promising treatment strategies for cartilage loss. However, the local joint microenvironment has a great impact on the success of cartilage formation by MSCs. This local joint environment is different between patients and therefore the outcome of MSC therapies is uncertain. We previously developed gene promoter-based reporter assays as a novel tool to predict the effect of a patient's OA joint microenvironment on the success of MSC-based cartilage formation. Here we describe an improved version of this molecular tool with increased prediction accuracy. For this, we generated fourteen stable cell lines using transcription factor (TF) binding elements (AP1, ARE, CRE, GRE, ISRE, NFAT5, NFκB, PPRE, SBE, SIE, SOX9, SRE, SRF, TCF/LEF) to drive luciferase reporter gene expression, and evaluated the cell lines for their responsiveness to an osteoarthritic microenvironment by stimulation with OA synovium-conditioned medium (OAs-cm; n=31). To study the effect of this OA microenvironment on MSC-based cartilage formation, MSCs were cultured in a three-dimensional pellet culture model while stimulated with OAs-cm. Cartilage formation was assessed histologically and by quantifying sulfated glycosaminoglycan (sGAG) production. Six TF reporters correlated significantly with the effect of OAs-cm on cartilage formation. We validated the predictive value of these TF reporters with an independent cohort of OAs-cm (n=22) and compared the prediction accuracy between our previous and the current new tool. Furthermore, we investigated which combination of reporters could predict the effect of the OA microenvironment on cartilage repair with the highest accuracy. A combination between the TF (NFκB) and the promoter-based (IL6) reporter proved to reach a more accurate prediction compared to the tools separately. These developments are an important step towards a diagnostic tool that can be used for personalized cartilage repair strategies for OA patients.

Nanomedicine and regenerative medicine approaches in osteoarthritis therapy

Osteoarthritis (OA), the most common chronic joint disease, is a degenerative disease that affects 7% of the worldwide population, more than 500 million people all over the world. OA is the main factor of disability in elderly people which decreases the quality of life of patients. It is characterized by joint pain, low bone density, and deterioration of the joint structure. Despite ongoing novel advances in drug discovery and drug delivery, OA therapy is still a big challenge since there is no available effective treatment and the existing therapies mainly focus on pain and symptomatic management rather than improving and/or suppressing its progression. This review aims to summarize the currently available and novel emerging therapies for OA including regenerative medicine and nanotechnology-based materials and formulations at the clinical and experimental levels. Applications of regenerative medicine and novel technologies such as nanotechnology in OA treatments have opened a new window to support OA patients by offering treatments that could halt or delay OA progression satisfactorily or provide an effective cure in near future. Nanomedicine and regenerative medicine suggest novel alternatives in the regeneration of cartilage, repair of bone damage, and control of chronic pain in OA therapy.

Biclustering reveals potential knee OA phenotypes in exploratory analyses: Data from the Osteoarthritis Initiative

Objective

To apply biclustering, a methodology originally developed for analysis of gene expression data, to simultaneously cluster observations and clinical features to explore candidate phenotypes of knee osteoarthritis (KOA) for the first time.

Methods

Data from the baseline Osteoarthritis Initiative (OAI) visit were cleaned, transformed, and standardized as indicated (leaving 6461 knees with 86 features). Biclustering produced submatrices of the overall data matrix, representing similar observations across a subset of variables. Statistical validation was determined using the novel SigClust procedure. After identifying biclusters, relationships with key outcome measures were assessed, including progression of radiographic KOA, total knee arthroplasty, loss of joint space width, and worsening Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores, over 96 months of follow-up.

Results

The final analytic set included 6461 knees from 3330 individuals (mean age 61 years, mean body mass index 28 kg/m², 57% women and 86% White). We identified 6 mutually exclusive biclusters characterized by different feature profiles at baseline, particularly related to symptoms and function. Biclusters represented overall better (#1), similar (#2, 3, 6), and poorer (#4, 5) prognosis compared to the overall cohort of knees, respectively. In general, knees in biclusters #4 and 5 had more structural progression (based on Kellgren-Lawrence grade, total knee arthroplasty, and loss of joint space width) but tended to have an improvement in WOMAC pain scores over time. In contrast, knees in bicluster #1 had less incident and progressive KOA, fewer total knee arthroplasties, less loss of joint space width, and stable pain scores compared with the overall cohort.

Significance

We identified six biclusters within the baseline OAI dataset which have varying relationships with key outcomes in KOA. Such biclusters represent potential phenotypes within the larger cohort and may suggest subgroups at greater or lesser risk of progression over time.

Repurposed and investigational disease-modifying drugs in osteoarthritis (DMOADs)

In spite of a major public health burden with increasing prevalence, current osteoarthritis (OA) management is largely palliative with an unmet need for effective treatment. Both industry and academic researchers have invested a vast amount of time and financial expense to discover the first diseasing-modifying osteoarthritis drugs (DMOADs), with no regulatory success so far. In this narrative review, we discuss repurposed drugs as well as investigational agents which have progressed into phase II and III clinical trials based on three principal endotypes: bone-driven, synovitis-driven and cartilage-driven. Then, we will briefly describe the recent failures and lessons learned, promising findings from predefined post hoc analyses and insights gained, novel methodologies to enhance future success and steps underway to overcome regulatory hurdles.

Dexamethasone: Insights into Pharmacological Aspects, Therapeutic Mechanisms, and Delivery Systems

Dexamethasone (DEX) has been widely used to treat a variety of diseases, including autoimmune diseases, allergies, ocular disorders, cancer, and, more recently, COVID-19. However, DEX usage is often restricted in the clinic due to its poor water solubility. When administered through a systemic route, it can elicit severe side effects, such as hypertension, peptic ulcers, hyperglycemia, and hydro-electrolytic disorders. There is currently much interest in developing efficient DEX-loaded nanoformulations that ameliorate adverse disease effects inhibiting advancements in scientific research. Various nanoparticles have been developed to selectively deliver drugs without destroying healthy cells or organs in recent years. In the present review, we have summarized some of the most attractive applications of DEX-loaded delivery systems, including liposomes, polymers, hydrogels, nanofibers, silica, calcium phosphate, and hydroxyapatite. This review provides our readers with a broad spectrum of nanomedicine approaches to deliver DEX safely.

Osteoarthritis endotype discovery via clustering of biochemical marker data

OBJECTIVES

Osteoarthritis (OA) patient stratification is an important challenge to design tailored treatments and drive drug development. Biochemical markers reflecting joint tissue turnover were measured in the IMI-APPROACH cohort at baseline and analysed using a machine learning approach in order to study OA-dominant phenotypes driven by the endotype-related clusters and discover the driving features and their disease-context meaning.

METHOD

Data quality assessment was performed to design appropriate data preprocessing techniques. The k-means clustering algorithm was used to find dominant subgroups of patients based on the biochemical markers data. Classification models were trained to predict cluster membership, and Explainable AI techniques were used to interpret these to reveal the driving factors behind each cluster and identify phenotypes. Statistical analysis was performed to compare differences between clusters with respect to other markers in the IMI-APPROACH cohort and the longitudinal disease progression.

RESULTS

Three dominant endotypes were found, associated with three phenotypes: C1) low tissue turnover (low repair and articular cartilage/subchondral bone turnover), C2) structural damage (high bone formation/resorption, cartilage degradation) and C3) systemic inflammation (joint tissue degradation, inflammation, cartilage degradation). The method achieved consistent results in the FNIH/OAI cohort. C1 had the highest proportion of non-progressors. C2 was mostly linked to longitudinal structural progression, and C3 was linked to sustained or progressive pain.

CONCLUSIONS

This work supports the existence of differential phenotypes in OA. The biomarker approach could potentially drive stratification for OA clinical trials and contribute to precision medicine strategies for OA progression in the future.

TRIAL REGISTRATION NUMBER

NCT03883568.

Gender-Related Aspects in Osteoarthritis Development and Progression: A Review

Osteoarthritis (OA) is a common degenerative joint disease treated mostly symptomatically before approaching its definitive treatment, joint arthroplasty. The rapidly growing prevalence of OA highlights the urgent need for a more efficient treatment strategy and boosts research into the mechanisms of OA incidence and progression. As a multifactorial disease, many aspects have been investigated as contributors to OA onset and progression. Differences in gender appear to play a role in the natural history of the disease, since female sex is known to increase the susceptibility to its development. The aim of the present review is to investigate the cues associated with gender by analyzing various hormonal, anatomical, molecular, and biomechanical parameters, as well as their differences between sexes. Our findings reveal the possible implications of gender in OA onset and progression and provide evidence for gaps in the current state of art, thus suggesting future research directions.

Overcoming barriers for intra-articular delivery of disease-modifying osteoarthritis drugs

Despite four decades of research in intra-articular drug delivery systems (DDS) and two decades of advances in disease-modifying osteoarthritis drugs (DMOADs), there is still no clinically available disease-modifying therapy for osteoarthritis (OA). Multiple barriers compromise intra-articular DMOAD delivery. Although multiple exciting approaches have been developed to overcome these barriers, there are still outstanding questions. We make several recommendations that can help in fully overcoming these barriers. Considering OA heterogeneity, we also propose a patient-centered, bottom-up workflow to guide preclinical development of DDS-based intra-articular DMOAD therapies. Overall, we expect this review to inspire paradigm-shifting innovations for developing next-generation DDS that can enable clinical translation of intra-articular DMOADs.

Osteoarthritis: Mechanistic Insights, Senescence, and Novel Therapeutic Opportunities

Osteoarthritis (OA) is the most common joint disease. In the last years, the research community has focused on understanding the molecular mechanisms that led to the pathogenesis of the disease, trying to identify different molecular and clinical phenotypes along with the discovery of new therapeutic opportunities. Different types of cell-to-cell communication mechanisms have been proposed to contribute to OA progression, including mechanisms mediated by connexin43 (Cx43) channels or by small extracellular vesicles. Furthermore, changes in the chondrocyte phenotype such as cellular senescence have been proposed as new contributors of the OA progression, changing the paradigm of the disease. The use of different drugs able to restore chondrocyte phenotype, to reduce cellular senescence and senescence-associated secretory phenotype components, and to modulate ion channel activity or Cx43 appears to be promising therapeutic strategies for the different types of OA. In this review, we aim to summarize the current knowledge in OA phenotypes related with aging and tissue damage and the new therapeutic opportunities currently available.

Osteoarthritis in year 2021: biochemical markers

OBJECTIVE

To summarize recent scientific advances in protein-derived soluble biomarkers of osteoarthritis.

DESIGN

A systematic search on the PubMed electronic database of clinical studies on protein-derived soluble biochemical markers of osteoarthritis in humans that were published between January 1st 2020 and March 31th 2021. The studies were selected on the basis of objective criteria and summarized in a table. Then they were described in a narrative review.

RESULTS

Out of 1971 publications, 48 fulfilled all selection criteria and 16 were selected by the author for the narrative review. The papers were classified according their clinical significance as defined in the BIPEDS classification. Two papers investigated the "burden of disease", two were dedicated to "investigative biomarkers", four papers question the "prognosis", three the "efficacy of treatment" and five the "diagnosis and phenotyping" value of protein-derived biomarkers.

CONCLUSIONS

Currently, biomarkers research is focused on their use as tools to identify molecular endotypes and clinical phenotypes and to facilitate patient screening and monitoring in clinical trials. This approach should allow a more targeted management of patients suffering from osteoarthritis.

Investigating Molecular Signatures Underlying Trapeziometacarpal Osteoarthritis Through the Evaluation of Systemic Cytokine Expression

Purpose

Non-operative management of trapeziometacarpal osteoarthritis (TMOA) demonstrates only short-term symptomatic alleviation, and no approved disease modifying drugs exist to treat this condition. A key issue in these patients is that radiographic disease severity can be discordant with patient reported pain, illustrating the need to identify molecular mediators of disease. This study characterizes the biochemical profile of TMOA patients to elucidate molecular mechanisms driving TMOA progression.

Methods

Plasma from patients with symptomatic TMOA undergoing surgical (n=39) or non-surgical management (n=44) with 1-year post-surgical follow-up were compared using a targeted panel of 27 cytokines. Radiographic (Eaton-Littler), anthropometric, longitudinal pain (VAS, TASD, quick DASH) and functional (key pinch, grip strength) data were used to evaluate relationships between structure, pain, and systemic cytokine expression. Principal Component Analysis was used to identify clusters of patients.

Results

Patients undergoing surgery had greater BMI as well as higher baseline quick DASH, TASD scores. Systemically, these patients could only be distinguished by differing levels of Interleukin-7 (IL-7), with an adjusted odds ratio of 0.22 for surgery for those with increased levels of this cytokine. Interestingly, PCA analysis of all patients (regardless of surgical status) identified a subset of patients with an “inflammatory” phenotype, as defined by a unique molecular signature consisting of thirteen cytokines.

Conclusion

Overall, this study demonstrated that circulating cytokines are capable of distinguishing TMOA disease severity, and identified IL-7 as a target capable of differentiating disease severity with higher levels associated with a decreased likelihood of TMOA needing surgical intervention. It also identified a cluster of patients who segregate based on a molecular signature of select cytokines.

The future of deep phenotyping in osteoarthritis: How can high throughput omics technologies advance our understanding of the cellular and molecular taxonomy of the disease?

Osteoarthritis (OA) is the most common form of musculoskeletal disease with significant healthcare costs and unmet needs in terms of early diagnosis and treatment. Many of the drugs that have been developed to treat OA failed in phase 2 and phase 3 clinical trials or produced inconclusive and ambiguous results. High throughput omics technologies are a powerful tool to better understand the mechanisms of the development of OA and other arthritic diseases. In this paper we outline the strategic reasons for increasingly applying deep phenotyping in OA for the benefit of gaining a better understanding of disease mechanisms and developing targeted treatments. This editorial is intended to launch a special themed issue of Osteoarthritis and Cartilage Open addressing the timely topic of "Advances in omics technologies for deep phenotyping in osteoarthritis". High throughput omics technologies are increasingly being applied in mechanistic studies of OA and other arthritic diseases. Applying multi-omics approaches in OA is a high priority and will allow us to gather new information on disease pathogenesis at the cellular level, and integrate data from diverse omics technology platforms to enable deep phenotyping. We anticipate that new knowledge in this area will allow us to harness the power of Big Data Analytics and resolve the extremely complex and overlapping clinical phenotypes into molecular endotypes, revealing new information about the cellular taxonomy of OA and "druggable pathways", thus facilitating future drug development.

Cartilage Biomarkers Coll2-1 and Coll2-1NO2 Are Associated with Knee OA MRI Features and Are Helpful in Identifying Patients at Risk of Disease Worsening

OBJECTIVE

To assess the cross-sectional association between serum levels of Coll2-1 and Coll2-1NO2, two cartilage degradation biomarkers; the burden of magnetic resonance imaging (MRI) features and clinical outcomes; and to evaluate the predictive value of these biomarkers on progression.

DESIGN

A total of 121 subjects with knee osteoarthritis (OA) were followed during 1 year with pain, function, and MRI assessment (PRODIGE study). Type II collagen-specific biomarker Coll2-1 and its nitrated form Coll2-1NO2 were directly measured in serum using immunoassays at baseline and after 3-, 6-, and 12-month follow-up.

RESULTS

Serum Coll2-1 and Coll2-1NO2 were correlated with several baseline knee features quantified with Whole-Organ Magnetic Resonance Imaging Score (WORMS). Coll2-1 was significantly correlated with periarticular cysts/bursitis (ρ = 0.29, P < 0.01), subarticular bone attrition (ρ = 0.25, P = 0.01), subarticular cysts (ρ = 0.24, P = 0.02), and articular cartilage integrity (ρ = 0.23, P = 0.03) WORMS subscores for the whole joint as well as with the medial femorotibial joint sum score (ρ = 0.26, P = 0.01) and medial femorotibial joint cartilage (ρ = 0.23, P = 0.02). Coll2-1NO2 correlated with WORMS total score (ρ = 0.23, P = 0.02), WORMS scores in the patellofemoral (ρ = 0.23, P = 0.02) and medial femorotibial compartments (ρ = 0.21, P = 0.03), with osteophytes scores (ρ = 0.27, P < 0.01), subarticular cysts (ρ = 0.24, P = 0.019), and intraarticular loose bodies (ρ = 0.27, P = 0.007). Baseline Coll2-1NO2 was higher in subjects with a pain worsening (426.4 pg/mL [278.04-566.95]) as compared to non-progressors (306.84 pg/mL [200.37-427.84]) over 1 year (AUC = 0.655, P = 0.015).

CONCLUSION

Serum cartilage biomarkers Coll2-1 and Coll2-1NO2 are associated with several knee OA features quantified with WORMS. Our study also shows that the baseline value of Coll2-1NO2 is positively associated with pain worsening.

Circ_SPG11 plays contributing effects on IL-1β-induced chondrocyte apoptosis and ECM degradation via miR-665 inhibition-mediated GREM1 upregulation

The dysregulation of circular RNA (circRNA) has been monitored in osteoarthritis (OA) cartilage, hinting that circRNA deregulation modulates OA progression. We thus aimed to unveil the role of circRNA spastic paraplegia 11 (circ_SPG11) in OA conditions. The upregulation of circ_SPG11 was observed in OA cartilage and IL-1β-treated chondrocytes. Knockdown of circ_SPG11 restored IL-1β-depleted cell proliferation and alleviated IL-1β-induced cell apoptosis and ECM degradation. Circ_SPG11 bound to miR-665 and negatively regulated miR-665 expression. Inhibition of miR-665 reversed the inhibitory effect on IL-1β-induced chondrocyte injury caused by circ_SPG11 knockdown. GREM1 was a target of miR-665, and circ_SPG11 knockdown depleted GREM1 expression by enriching miR-665. Overexpression of GREM1 also reversed the inhibitory effect on IL-1β-induced chondrocyte injury caused by miR-665 enrichment. Circ_SPG11 might promote IL-1β-induced chondrocyte apoptosis and ECM degradation via increasing GREM1 expression by decoying miR-665.

Emerging Concepts of Endotypes/Phenotypes in Regenerative Medicine for Osteoarthritis

Osteoarthritis (OA) represents a broad spectrum of different conditions. Our present understanding of phenotypes and endotypes can explain the differences in clinical manifestations, etiology, and underlying pathophysiology. Although this concept was first applied in choosing the right target population for clinical trials of disease-modifying osteoarthritis drugs (DMOADs), given that the regenerative medicine so far has not delivered uniformly successful results in structural improvement in OA, it merits a consideration to introduce the concept of phenotype/endotype in the regenerative medicine for OA toward an effort to find the right patients for these expensive therapeutics. A better understanding of molecular endotypes facilitates defining clinical phenotypes more clearly. Based on this knowledge, these patients may respond better to treatments that can preserve joints, including regenerative medicine. On the other hand, patients who are not expected to benefit from these treatments may receive earlier total joint replacement surgery. This will result in a reduction of healthcare costs, as well as a more effective approach to new drug development. An understanding of phenotypes/endotypes will contribute to the selection of suitable patients for regenerative treatment of OA.

Molecular-Morphological Relationships of the Scaffold Protein FKBP51 and Inflammatory Processes in Knee Osteoarthritis

Knee osteoarthritis (OA) is one of the most prevalent chronic conditions affecting the adult population. OA is no longer thought to come from a purely biomechanical origin but rather one that has been increasingly recognized to include a persistent low-grade inflammatory component. Intra-articular corticosteroid injections (IACSI) have become a widely used method for treating pain in patients with OA as an effective symptomatic treatment. However, as the disease progresses, IACSI become ineffective. FKBP51 is a regulatory protein of the glucocorticoid receptor function and have been shown to be dysregulated in several pathological scenario's including chronic inflammation. Despite of these facts, to our knowledge, there are no previous studies of the expression and possible role of FKBP51 in OA. We investigated by double and triple immunofluorescence confocal microscopy the cellular and subcellular expression of FKBP51 and its relations with inflammation factors in osteoarthritic knee joint tissues: specifically, in the tibial plateau knee cartilage, Hoffa's fat pad and suprapatellar synovial tissue of the knee. Our results show co-expression of FKBP51 with TNF-α, IL-6, CD31 and CD34 in OA chondrocytes, synovial membrane cells and adipocytes in Hoffa's fat pad. FKBP51 is also abundant in nerve fibers within the fat pad. Co-expression of FKBP51 protein with these markers may be indicative of its contribution to inflammatory processes and associated chronic pain in OA.

Hyaluronic acid synthesis, degradation, and crosslinking in equine osteoarthritis: TNF-α-TSG-6-mediated HC-HA formation

BACKGROUND

TNF-α-stimulated gene 6 (TSG-6) protein, a TNF-α-responsive hyaladherin, possesses enzymatic activity that can catalyze covalent crosslinks of the polysaccharide hyaluronic acid (HA) to another protein to form heavy chain-hyaluronic acid (HC-HA) complexes in pathological conditions such as osteoarthritis (OA). Here, we examined HA synthase and inflammatory gene expression; synovial fluid HA, TNF-α, and viscosity; and TSG-6-mediated HC-HA complex formation in an equine OA model. The objectives of this study were to (1) evaluate the TNF-α-TSG-6-HC-HA signaling pathway across multiple joint tissues, including synovial membrane, cartilage, and synovial fluid, and (2) determine the impact of OA on synovial fluid composition and biophysical properties.

METHODS

HA and inflammatory cytokine concentrations (TNF-α, IL-1β, CCL2, 3, 5, and 11) were analyzed in synovial fluid from 63 OA and 25 control joints, and HA synthase (HAS1-3), TSG-6, and hyaluronan-degrading enzyme (HYAL2, HEXA) gene expression was measured in synovial membrane and cartilage. HA molecular weight (MW) distributions were determined using agarose gel electrophoresis and solid-state nanopore measurements, and HC-HA complex formation was detected via immunoblotting and immunofluorescence. SEC-MALS was used to evaluate TSG-6-mediated HA crosslinking, and synovial fluid and HA solution viscosities were analyzed using multiple particle-tracking microrheology and microfluidic measurements, respectively.

RESULTS

TNF-α concentrations were greater in OA synovial fluid, and TSG6 expression was upregulated in OA synovial membrane and cartilage. TSG-6-mediated HC-HA complex formation was greater in OA synovial fluid and tissues than controls, and HC-HA was localized to both synovial membrane and superficial zone chondrocytes in OA joints. SEC-MALS demonstrated macromolecular aggregation of low MW HA in the presence of TSG-6 and inter-α-inhibitor with concurrent increases in viscosity.

CONCLUSIONS

Synovial fluid TNF-α concentrations, synovial membrane and cartilage TSG6 gene expression, and HC-HA complex formation were increased in equine OA. Despite the ability of TSG-6 to induce macromolecular aggregation of low MW HA with resultant increases in the viscosity of low MW HA solutions in vitro, HA concentration was the primary determinant of synovial fluid viscosity rather than HA MW or HC-HA crosslinking. The TNF-α-TSG-6-HC-HA pathway may represent a potential therapeutic target in OA.