Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration

The role of DNA methylation in chondrogenesis of human iPSCs as a stable marker of cartilage quality

BACKGROUND

Lack of insight into factors that determine purity and quality of human iPSC (hiPSC)-derived neo-cartilage precludes applications of this powerful technology toward regenerative solutions in the clinical setting. Here, we set out to generate methylome-wide landscapes of hiPSC-derived neo-cartilages from different tissues-of-origin and integrated transcriptome-wide data to identify dissimilarities in set points of methylation with associated transcription and the respective pathways in which these genes act.

METHODS

We applied in vitro chondrogenesis using hiPSCs generated from two different tissue sources: skin fibroblasts and articular cartilage. Upon differentiation toward chondrocytes, these are referred to as hFiCs and hCiC, respectively. Genome-wide DNA methylation and RNA sequencing datasets were generated of the hiPSC-derived neo-cartilages, and the epigenetically regulated transcriptome was compared to that of neo-cartilage deposited by human primary articular cartilage (hPAC).

RESULTS

Methylome-wide landscapes of neo-cartilages of hiPSCs reprogrammed from two different somatic tissues were 85% similar to that of hPACs. By integration of transcriptome-wide data, differences in transcriptionally active CpGs between hCiC relative to hPAC were prioritized. Among the CpG-gene pairs lower expressed in hCiCs relative to hPACs, we identified genes such as MGP, GDF5, and CHAD enriched in closely related pathways and involved in cartilage development that likely mark phenotypic differences in chondrocyte states. Vice versa, among the CpG-gene pairs higher expressed, we identified genes such as KIF1A or NKX2-2 enriched in neurogenic pathways and likely reflecting off target differentiation.

CONCLUSIONS

We did not find significant variation between the neo-cartilages derived from hiPSCs of different tissue sources, suggesting that application of a robust differentiation protocol such as we applied here is more important as compared to the epigenetic memory of the cells of origin. Results of our study could be further exploited to improve quality, purity, and maturity of hiPSC-derived neo-cartilage matrix, ultimately to realize introduction of sustainable, hiPSC-derived neo-cartilage implantation into clinical practice.

Unveiling inflammatory and prehypertrophic cell populations as key contributors to knee cartilage degeneration in osteoarthritis using multi-omics data integration

OBJECTIVES

Single-cell and spatial transcriptomics analysis of human knee articular cartilage tissue to present a comprehensive transcriptome landscape and osteoarthritis (OA)-critical cell populations.

METHODS

Single-cell RNA sequencing and spatially resolved transcriptomic technology have been applied to characterise the cellular heterogeneity of human knee articular cartilage which were collected from 8 OA donors, and 3 non-OA control donors, and a total of 19 samples. The novel chondrocyte population and marker genes of interest were validated by immunohistochemistry staining, quantitative real-time PCR, etc. The OA-critical cell populations were validated through integrative analyses of publicly available bulk RNA sequencing data and large-scale genome-wide association studies.

RESULTS

We identified 33 cell population-specific marker genes that define 11 chondrocyte populations, including 9 known populations and 2 new populations, that is, pre-inflammatory chondrocyte population (preInfC) and inflammatory chondrocyte population (InfC). The novel findings that make this an important addition to the literature include: (1) the novel InfC activates the mediator MIF-CD74; (2) the prehypertrophic chondrocyte (preHTC) and hypertrophic chondrocyte (HTC) are potentially OA-critical cell populations; (3) most OA-associated differentially expressed genes reside in the articular surface and superficial zone; (4) the prefibrocartilage chondrocyte (preFC) population is a major contributor to the stratification of patients with OA, resulting in both an inflammatory-related subtype and a non-inflammatory-related subtype.

CONCLUSIONS

Our results highlight InfC, preHTC, preFC and HTC as potential cell populations to target for therapy. Also, we conclude that profiling of those cell populations in patients might be used to stratify patient populations for defining cohorts for clinical trials and precision medicine.

Thyroid hormone induces ossification and terminal maturation in a preserved OA cartilage biomimetic model

OBJECTIVE

To characterize aspects of triiodothyronine (T3) induced chondrocyte terminal maturation within the molecular osteoarthritis pathophysiology using the previously established T3 human ex vivo osteochondral explant model.

DESIGNS

RNA-sequencing was performed on explant cartilage obtained from OA patients (n = 8), that was cultured ex vivo with or without T3 (10 ng/ml), and main findings were validated using RT-qPCR in an independent sample set (n = 22). Enrichment analysis was used for functional clustering and comparisons with available OA patient RNA-sequencing and GWAS datasets were used to establish relevance for OA pathophysiology by linking to OA patient genomic profiles.

RESULTS

Besides the upregulation of known hypertrophic genes EPAS1 and ANKH, T3 treatment resulted in differential expression of 247 genes with main pathways linked to extracellular matrix and ossification. CCDC80, CDON, ANKH and ATOH8 were among the genes found to consistently mark early, ongoing and terminal maturational OA processes in patients. Furthermore, among the 37 OA risk genes that were significantly affected in cartilage by T3 were COL12A1, TNC, SPARC and PAPPA.

CONCLUSIONS

RNA-sequencing results show that metabolic activation and recuperation of growth plate morphology are induced by T3 in OA chondrocytes, indicating terminal maturation is accelerated. The molecular mechanisms involved in hypertrophy were linked to all stages of OA pathophysiology and will be used to validate disease models for drug testing.

Identified senescence endotypes in aged cartilage are reflected in the blood metabolome

Heterogeneous accumulation of senescent cells expressing the senescence-associated secretory phenotype (SASP) affects tissue homeostasis which leads to diseases, such as osteoarthritis (OA). In this study, we set out to characterize heterogeneity of cellular senescence within aged articular cartilage and explored the presence of corresponding metabolic profiles in blood that could function as representative biomarkers. Hereto, we set out to perform cluster analyses, using a gene-set of 131 senescence genes (N = 57) in a previously established RNA sequencing dataset of aged articular cartilage and a generated metabolic dataset in overlapping blood samples. Using unsupervised hierarchical clustering and pathway analysis, we identified two robust cellular senescent endotypes. Endotype-1 was enriched for cell proliferating pathways, expressing forkhead box protein O4 (FOXO4), RB transcriptional corepressor like 2 (RBL2), and cyclin-dependent kinase inhibitor 1B (CDKN1B); the FOXO mediated cell cycle was identified as possible target for endotype-1 patients. Endotype-2 showed enriched inflammation-associated pathways, expressed by interleukin 6 (IL6), matrix metallopeptidase (MMP)1/3, and vascular endothelial growth factor (VEGF)C and SASP pathways were identified as possible targets for endotype-2 patients. Notably, plasma-based metabolic profiles in overlapping blood samples (N = 21) showed two corresponding metabolic clusters in blood. These non-invasive metabolic profiles could function as biomarkers for patient-tailored targeting of senescence in OA.

Mechanical stress and inflammation have opposite effects on Wnt signaling in human chondrocytes

Dysregulation of Wingless and Int-1 (Wnt) signaling has been strongly associated with development and progression of osteoarthritis (OA). Here, we set out to investigate the independent effects of either mechanical stress (MS) or inflammation on Wnt signaling in human neocartilage pellets, and to relate this Wnt signaling to OA pathophysiology. OA synovium-conditioned media (OAS-CM) was collected after incubating synovium from human end-stage OA joints for 24 h in medium. Cytokine levels in the OAS-CM were determined with a multiplex immunoassay (Luminex). Human neocartilage pellets were exposed to 20% MS, 2% OAS-CM or 1 ng/mL Interleukin-1β (IL-1β). Effects on expression levels of Wnt signaling members were determined by reverse transcription-quantitative polymerase chain reaction. Additionally, the expression of these members in articular cartilage from human OA joints was analyzed in association with joint space narrowing (JSN) and osteophyte scores. Protein levels of IL-1β, IL-6, IL-8, IL-10, tumor necrosis factor α, and granulocyte-macrophage colony-stimulating factor positively correlated with each other. MS increased noncanonical WNT5A and FOS expression. In contrast, these genes were downregulated upon stimulation with OAS-CM or IL-1β. Furthermore, Wnt inhibitors DKK1 and FRZB decreased in response to OAS-CM or IL-1β exposure. Finally, expression of WNT5A in OA articular cartilage was associated with increased JSN scores, but not osteophyte scores. Our results demonstrate that MS and inflammatory stimuli have opposite effects on canonical and noncanonical Wnt signaling in human neocartilage. Considering the extent to which MS and inflammation contribute to OA in individual patients, we hypothesize that targeting specific Wnt pathways offers a more effective, individualized approach.

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.

Understanding interleukin 11 as a disease gene and therapeutic target

Interleukin 11 (IL11) is an elusive member of the IL6 family of cytokines. While initially thought to be a haematopoietic and cytoprotective factor, more recent data show instead that IL11 is redundant for haematopoiesis and toxic. In this review, the reasons that led to the original misunderstandings of IL11 biology, which are now understandable, are explained with particular attention on the use of recombinant human IL11 in mice and humans. Following tissue injury, as part of an evolutionary ancient homeostatic response, IL11 is secreted from damaged mammalian cells to signal via JAK/STAT3, ERK/P90RSK, LKB1/mTOR and GSK3β/SNAI1 in autocrine and paracrine. This activates a program of mesenchymal transition of epithelial, stromal, and endothelial cells to cause inflammation, fibrosis, and stalled endogenous tissue repair, leading to organ failure. The role of IL11 signalling in cell- and organ-specific pathobiology is described, the large unknowns about IL11 biology are discussed and the promise of targeting IL11 signalling as a therapeutic approach is reviewed.

Metabolic and inflammatory profiles define phenotypes with clinical relevance in female knee osteoarthritis patients with joint effusion

OBJECTIVES

Osteoarthritis has been the subject of abundant research in the last years with limited translation to the clinical practice, probably due to the disease's high heterogeneity. In this study, we aimed to identify different phenotypes in knee osteoarthritis (KOA) patients with joint effusion based on their metabolic and inflammatory profiles.

METHODS

A non-supervised strategy based on statistical and machine learning methods was applied to 45 parameters measured on 168 female KOA patients with persistent joint effusion, consecutively recruited at our hospital after a monographic OA outpatient visit. Data comprised anthropometric and metabolic factors and a panel of systemic and local inflammatory markers. The resulting clusters were compared regarding their clinical, radiographic and ultrasound severity at baseline and their radiographic progression at two years.

RESULTS

Our analyses identified four KOA inflammatory phenotypes (KOIP): a group characterized by metabolic syndrome, probably driven by body fat and obesity, and by high local and systemic inflammation (KOIP-1); a metabolically healthy phenotype with mild overall inflammation (KOIP-2); a non-metabolic phenotype with high inflammation levels (KOIP-3); and a metabolic phenotype with low inflammation and cardiovascular risk factors not associated with obesity (KOIP-4). Of interest, these groups exhibited differences regarding pain, functional disability and radiographic progression, pointing to a clinical relevance of the uncovered phenotypes.

CONCLUSION

Our results support the existence of different KOA phenotypes with clinical relevance and differing pathways regarding their pathophysiology and disease evolution, which entails implications in patients' stratification, treatment tailoring and the search of novel and personalized therapies.

Identifying Muscle Function-based Phenotypes Associated With Radiographic Progression of Secondary Hip Osteoarthritis

OBJECTIVE

The purposes of our study were to (1) identify muscle function-based clinical phenotypes in patients with hip osteoarthritis (OA) and (2) determine the association between those phenotypes and radiographic progression of hip OA.

DESIGN

Prospective cohort study.

SETTING

Clinical biomechanics laboratory of a university.

PARTICIPANTS

Fifty women patients with mild-to-moderate secondary hip OA (N=50) were recruited from the orthopedic department of a single institution.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Two-step cluster analyses were performed to classify the patients, using hip flexion, extension, abduction, and external/internal rotation muscle strength (cluster analysis 1); relative hip muscle strength to total hip strength (ie, hip muscle strength balance; cluster analysis 2); and both hip muscle strength and muscle strength balance (cluster analysis 3) as variables. The association between the phenotype and hip OA progression over 12 months (indicated by joint space width [JSW] >0.5 mm) was investigated by logistic regression analyses. Hip joint morphology, hip pain, gait speed, physical activity, Harris hip score, and SF-36 scores were compared between the phenotypes.

RESULTS

Radiographic progression of hip OA was observed in 42% of the patients. The patients were classified into 2 phenotypes in each of the 3 cluster analyses. The solution in cluster analyses 1 and 3 was similar, and high-function and low-function phenotypes were identified; however, no association was found between the phenotypes and hip OA progression. The phenotype 2-1 (high-risk phenotype) extracted in cluster analysis 2, which had relative muscle weakness in hip flexion and internal rotation, was associated with subsequent hip OA progression, even after adjusting for age and minimum JSW at baseline (adjusted odds ratio [95% confidence interval], 3.60 [1.07-12.05]; P=.039).

CONCLUSION

As preliminary findings, the phenotype based on hip muscle strength balance, rather than hip muscle strength, may be associated with hip OA progression.

MSdb: An integrated expression atlas of human musculoskeletal system

The global prevalence and burden of musculoskeletal (MSK) disorders are immense. Advancements in next-generation sequencing (NGS) have generated vast amounts of data, accelerating the research of pathological mechanisms and the development of therapeutic approaches for MSK disorders. However, scattered datasets across various repositories complicate uniform analysis and comparison. Here, we introduce MSdb, a database for visualization and integrated analysis of next-generation sequencing data from human musculoskeletal system, along with manually curated patient phenotype data. MSdb provides various types of analysis, including sample-level browsing of metadata information, gene/miRNA expression, and single-cell RNA-seq dataset. In addition, MSdb also allows integrated analysis for cross-samples and cross-omics analysis, including customized differentially expressed gene/microRNA analysis, microRNA-gene network, scRNA-seq cross-sample/disease integration, and gene regulatory network analysis. Overall, systematic categorizing, standardized processing, and freely accessible knowledge features MSdb a valuable resource for MSK research community.

MicroRNA Signatures in Cartilage Ageing and Osteoarthritis

Osteoarthritis is the most common degenerative joint disorder. MicroRNAs are gene expression regulators that act post-transcriptionally to control tissue homeostasis. Microarray analysis was undertaken in osteoarthritic intact, lesioned and young intact cartilage. Principal component analysis showed that young intact cartilage samples were clustered together; osteoarthritic samples had a wider distribution; and osteoarthritic intact samples were separated into two subgroups, osteoarthritic-Intact-1 and osteoarthritic-Intact-2. We identified 318 differentially expressed microRNAs between young intact and osteoarthritic lesioned cartilage, 477 between young intact and osteoarthritic-Intact-1 cartilage and 332 between young intact and osteoarthritic-Intact-2 cartilage samples. For a selected list of differentially expressed microRNAs, results were verified in additional cartilage samples using qPCR. Of the validated DE microRNAs, four-miR-107, miR-143-3p, miR-361-5p and miR-379-5p-were selected for further experiments in human primary chondrocytes treated with IL-1β. Expression of these microRNAs decreased in human primary chondrocytes treated with IL-1β. For miR-107 and miR-143-3p, gain- and loss-of-function approaches were undertaken and associated target genes and molecular pathways were investigated using qPCR and mass spectrometry proteomics. Analyses showed that WNT4 and IHH, predicted targets of miR-107, had increased expression in osteoarthritic cartilage compared to young intact cartilage and in primary chondrocytes treated with miR-107 inhibitor, and decreased expression in primary chondrocytes treated with miR-107 mimic, suggesting a role of miR-107 in chondrocyte survival and proliferation. In addition, we identified an association between miR-143-3p and EIF2 signalling and cell survival. Our work supports the role of miR-107 and miR-143-3p in important chondrocyte mechanisms regulating proliferation, hypertrophy and protein translation.

N6-methyladenine regulator-mediated RNA methylation modification patterns in immune microenvironment regulation of osteoarthritis

Background: Osteoarthritis is a common chronic degenerative disease, and recently, an increasing number of studies have shown that immunity plays an important role in the progression of osteoarthritis, which is exacerbated by local inflammation. The role of N6-methyladenine (m⁶A) modification in immunity is being explored. However, the role of m⁶A modification in regulating the immune microenvironment of osteoarthritis remains unknown. In this study, we sought to discuss the association between the N6-methyladenine (m⁶A) modification and the immune microenvironment of osteoarthritis. Methods: First, the data and gene expression profiles of 139 samples, including 33 healthy samples and 106 osteoarthritis samples, were obtained from the Genetics osteoARthritis and Progression (GARP) study. Then the differences in m⁶A regulators between healthy individuals and osteoarthritis patients were analyzed. The correlation between m⁶A regulators and immune characteristics was also investigated by single-sample gene set enrichment analysis (ssGSEA). Principal component analysis (PCA), Gene Set Variation Analysis (GSVA) enrichment analysis, weighted gene coexpression network analysis (WGCNA), and Associated R packages were used to identify the m⁶A phenotype and its biological functions. Results: A total of 23 m⁶A regulators were involved in this study. We found a close correlation between most m⁶A regulators in all samples as well as in osteoarthritis samples. VIRMA and LRPPRC were the most highly correlated m⁶A regulators and showed a positive correlation, whereas VIRMA and RBM15B were the most negatively correlated. M⁶A regulators are associated with osteoarthritis immune characteristics. For example, MDSC cell abundance was strongly correlated with RBM15B and HNRNPC. Meanwhile, RBM15B and HNRNPC were important effectors of natural killer cell immune responses. IGFBP3 is an important regulator of cytolytic activity immune function. We performed an unsupervised consensus cluster analysis of the osteoarthritis samples based on the expression of 23 m⁶A regulators. Three different m⁶A subtypes of osteoarthritis were identified, including 27 samples in subtype C1, 21 samples in subtype C2, and 58 samples in subtype C3. Different m⁶A subtypes have unique biological pathways and play different roles in the immune microenvironment of osteoarthritis. Conclusion: The m⁶A modification plays a crucial role in the diversity and complexity of the immune microenvironment in osteoarthritis.

Mice Lacking Wnt9a or Wnt4 Are Prone to Develop Spontaneous Osteoarthritis With Age and Display Alteration in Either the Trabecular or Cortical Bone Compartment

Osteoarthritis (OA) is a common degenerative disease of the joint, with a complex multifactorial not yet fully understood etiology. Over the past years, the Wnt signaling pathway has been implicated in osteoarthritis. In a recent genomewide association study (GWAS), the chromosomal location on chromosome 1, linked to the Wnt3a-Wnt9a gene locus, was identified as the most significant locus associated with a thumb osteoarthritis endophenotype. Previously, it was shown that WNT9a is involved in maintaining synovial cell identity in the elbow joint during embryogenesis. Here, we report that the conditional loss of Wnt9a in the Prx1-Cre expressing limb mesenchyme or Prg4-CreER expressing cells predispositions the mice to develop spontaneous OA-like changes with age. In addition, the trabecular bone volume is altered in these mice. Similarly, mice with a conditional loss of Wnt4 in the limb mesenchyme are also more prone to develop spontaneously OA-like joint alterations with age. These mice display additional alterations in their cortical bone. The combined loss of Wnt9a and Wnt4 increased the likelihood of the mice developing osteoarthritis-like changes and enhanced disease severity in the affected mice. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

OA foundations - experimental models of osteoarthritis

Osteoarthritis (OA) is increasingly recognised as a disease of diverse phenotypes with variable clinical presentation, progression, and response to therapeutic intervention. This same diversity is readily apparent in the many animal models of OA. However, model selection, study design, and interpretation of resultant findings, are not routinely done in the context of the target human (or veterinary) patient OA sub-population or phenotype. This review discusses the selection and use of animal models of OA in discovery and therapeutic-development research. Beyond evaluation of the different animal models on offer, this review suggests focussing the approach to OA-animal model selection on study objective(s), alignment of available models with OA-patient sub-types, and the resources available to achieve valid and translatable results. How this approach impacts model selection is discussed and an experimental design checklist for selecting the optimal model(s) is proposed. This approach should act as a guide to new researchers and a reminder to those already in the field, as to issues that need to be considered before embarking on in vivo pre-clinical research. The ultimate purpose of using an OA animal model is to provide the best possible evidence if, how, when and where a molecule, pathway, cell or process is important in clinical disease. By definition this requires both model and study outcomes to align with and be predictive of outcomes in patients. Keeping this at the forefront of research using pre-clinical OA models, will go a long way to improving the quality of evidence and its translational value.

Insights into the molecular landscape of osteoarthritis in human tissues

PURPOSE OF REVIEW

To provide an overview of recent developments in the field of osteoarthritis research with a focus on insights gleaned from the application of different -omic technologies.

RECENT FINDINGS

We searched for osteoarthritis-relevant studies focusing on transcriptomics, epigenomics, proteomics and metabolomics, published since November of 2019. Study designs showed a trend towards characterizing the genomic profile of osteoarthritis-relevant tissues with high resolution, for example either by using single-cell technologies or by considering several -omic levels and disease stages.

SUMMARY

Multitissue interactions (cartilage-subchondral bone; cartilage-synovium) are prevalent in the pathophysiology of osteoarthritis, which is characterized by substantial matrix remodelling in an inflammatory milieu. Subtyping approaches using -omic technologies have contributed to the identification of at least two osteoarthritis endotypes. Studies using data integration approaches have provided molecular maps that are tissue-specific for osteoarthritis and pave the way for expanding these data integration approaches towards a more comprehensive view of disease aetiopathogenesis.

Assessment of Clinical, Tissue, and Cell-Level Metrics Identify Four Biologically Distinct Knee Osteoarthritis Patient Phenotypes

OBJECTIVE

Clinical heterogeneity of primary osteoarthritis (OA) is a major challenge in understanding pathogenesis and development of targeted therapeutic strategies. This study aims to (1) identify OA patient subgroups phenotypes and (2) determine predictors of OA severity and cartilage-derived stem/progenitor concentration using clinical-, tissue-, and cell- level metrics.

DESIGN

Cartilage, synovium (SYN) and infrapatellar fatpad (IPFP) were collected from 90 total knee arthroplasty patients. Clinical metrics (patient demographics, radiograph-based joint space width (JSW), Kellgren and Lawrence score (KL)), tissue metrics (cartilage histopathology grade, glycosaminoglycans (GAGs)) and cell-based metrics (cartilage-, SYN-, and IPFP-derived cell concentration ([Cell], cells/mg), connective tissue progenitor (CTP) prevalence (PCTP, CTPs/million cells plated), CTP concentration, [CTP], CTPs/mg)) were assessed using k-mean clustering and linear regression model.

RESULTS

Four patient subgroups were identified. Clusters 1 and 2 comprised of younger, high body mass index (BMI) patients with healthier cartilage, where Cluster 1 had high CTP in cartilage, SYN, and IPFP, and Cluster 2 had low [CTP] in cartilage, SYN, and IPFP. Clusters 3 and 4 comprised of older, low BMI patients with diseased cartilage where Cluster 3 had low [CTP] in SYN, IPFP but high [CTP] in cartilage, and Cluster 4 had high [CTP] in SYN, IPFP but low [CTP] in cartilage. Age (r = 0.23, P = 0.026), JSW (r = 0.28, P = 0.007), KL (r = 0.26, P = 0.012), GAG/mg cartilage tissue (r = -0.31, P = 0.007), and SYN-derived [Cell] (r = 0.25, P = 0.049) were weak but significant predictors of OA severity. Cartilage-derived [Cell] (r = 0.38, P < 0.001) and PCTP (r = 0.9, P < 0.001) were moderate/strong predictors of cartilage-derived [CTP].

CONCLUSION

Initial findings suggests the presence of OA patient subgroups that could define opportunities for more targeted patient-specific approaches to prevention and treatment.

The non-coding RNA interactome in joint health and disease

Non-coding RNAs have distinct regulatory roles in the pathogenesis of joint diseases including osteoarthritis (OA) and rheumatoid arthritis (RA). As the amount of high-throughput profiling studies and mechanistic investigations of microRNAs, long non-coding RNAs and circular RNAs in joint tissues and biofluids has increased, data have emerged that suggest complex interactions among non-coding RNAs that are often overlooked as critical regulators of gene expression. Identifying these non-coding RNAs and their interactions is useful for understanding both joint health and disease. Non-coding RNAs regulate signalling pathways and biological processes that are important for normal joint development but, when dysregulated, can contribute to disease. The specific expression profiles of non-coding RNAs in various disease states support their roles as promising candidate biomarkers, mediators of pathogenic mechanisms and potential therapeutic targets. This Review synthesizes literature published in the past 2 years on the role of non-coding RNAs in OA and RA with a focus on inflammation, cell death, cell proliferation and extracellular matrix dysregulation. Research to date makes it apparent that 'non-coding' does not mean 'non-essential' and that non-coding RNAs are important parts of a complex interactome that underlies OA and RA.

Circulating MicroRNAs Highly Correlate to Expression of Cartilage Genes Potentially Reflecting OA Susceptibility-Towards Identification of Applicable Early OA Biomarkers

Objective: To identify and validate circulating micro RNAs (miRNAs) that mark gene expression changes in articular cartilage early in osteoarthritis (OA) pathophysiology process. Methods: Within the ongoing RAAK study, human preserved OA cartilage and plasma (N = 22 paired samples) was collected for RNA sequencing (respectively mRNA and miRNA). Spearman correlation was determined for 114 cartilage genes consistently and significantly differentially expressed early in osteoarthritis and 384 plasma miRNAs. Subsequently, the minimal number of circulating miRNAs serving to discriminate between progressors and non-progressors was assessed by regression analysis and area under receiver operating curves (AUC) was calculated with progression data and plasma miRNA sequencing from the GARP study (N = 71). Results: We identified strong correlations (ρ ≥ |0.7|) among expression levels of 34 unique plasma miRNAs and 21 genes, including 4 genes that correlated with multiple miRNAs. The strongest correlation was between let-7d-5p and EGFLAM (ρ = −0.75, P = 6.9 × 10⁻⁵). Regression analysis of the 34 miRNAs resulted in a set of 7 miRNAs that, when applied to the GARP study, demonstrated clinically relevant predictive value with AUC > 0.8 for OA progression over 2 years and near-clinical value for progression over 5 years- (AUC = 0.8). Conclusions: We show that plasma miRNAs levels reflect gene expression levels in cartilage and can be exploited to represent ongoing pathophysiological processes in articular cartilage. We advocate that identified signature of 7 plasma miRNAs can contribute to direct further studies toward early biomarkers predictive for progression of osteoarthritis over 2 and 5 years.

Elucidating mechano-pathology of osteoarthritis: transcriptome-wide differences in mechanically stressed aged human cartilage explants

Background

Failing of intrinsic chondrocyte repair after mechanical stress is known as one of the most important initiators of osteoarthritis. Nonetheless, insight into these early mechano-pathophysiological processes in age-related human articular cartilage is still lacking. Such insights are needed to advance clinical development. To highlight important molecular processes of osteoarthritis mechano-pathology, the transcriptome-wide changes following injurious mechanical stress on human aged osteochondral explants were characterized.

Methods

Following mechanical stress at a strain of 65% (65%MS) on human osteochondral explants (n_65%MS = 14 versus n_control = 14), RNA sequencing was performed. Differential expression analysis between control and 65%MS was performed to determine mechanical stress-specific changes. Enrichment for pathways and protein-protein interactions was analyzed with Enrichr and STRING.

Results

We identified 156 genes significantly differentially expressed between control and 65%MS human osteochondral explants. Of note, IGFBP5 (FC = 6.01; FDR = 7.81 × 10⁻³) and MMP13 (FC = 5.19; FDR = 4.84 × 10⁻²) were the highest upregulated genes, while IGFBP6 (FC = 0.19; FDR = 3.07 × 10⁻⁴) was the most downregulated gene. Protein-protein interactions were significantly higher than expected by chance (P = 1.44 × 10⁻¹⁵ with connections between 116 out of 156 genes). Pathway analysis showed, among others, enrichment for cellular senescence, insulin-like growth factor (IGF) I and II binding, and focal adhesion.

Conclusions

Our results faithfully represent transcriptomic wide consequences of mechanical stress in human aged articular cartilage with MMP13, IGF binding proteins, and cellular senescence as the most notable results. Acquired knowledge on the as such identified initial, osteoarthritis-related, detrimental responses of chondrocytes may eventually contribute to the development of effective disease-modifying osteoarthritis treatments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-021-02595-8.

RNA Sequencing Reveals Interacting Key Determinants of Osteoarthritis Acting in Subchondral Bone and Articular Cartilage: Identification of IL11 and CHADL as Attractive Treatment Targets

OBJECTIVE

To identify key determinants of the interactive pathophysiologic processes in subchondral bone and cartilage in osteoarthritis (OA).

METHODS

We performed RNA sequencing on macroscopically preserved and lesional OA subchondral bone from patients in the Research Arthritis and Articular Cartilage study who underwent joint replacement surgery due to OA (n = 24 sample pairs: 6 hips and 18 knees). Unsupervised hierarchical clustering and differential expression analyses were conducted. Results were combined with data on previously identified differentially expressed genes in cartilage (partly overlapping samples) as well as data on recently identified OA risk genes.

RESULTS

We identified 1,569 genes that were significantly differentially expressed between lesional and preserved subchondral bone, including CNTNAP2 (fold change [FC] 2.4, false discovery rate [FDR] 3.36 × 10^-5 ) and STMN2 (FC 9.6, FDR 2.36 × 10^-3 ). Among these 1,569 genes, 305 were also differentially expressed, and with the same direction of effect, in cartilage, including the recently recognized OA susceptibility genes IL11 and CHADL. Upon differential expression analysis with stratification for joint site, we identified 509 genes that were exclusively differentially expressed in subchondral bone of the knee, including KLF11 and WNT4. These genes that were differentially expressed exclusively in the knee were enriched for involvement in epigenetic processes, characterized by, e.g., HIST1H3J and HIST1H3H.

CONCLUSION

IL11 and CHADL were among the most consistently differentially expressed genes OA pathophysiology-related genes in both bone and cartilage. As these genes were recently also identified as robust OA risk genes, they classify as attractive therapeutic targets acting on 2 OA-relevant tissues.

Experimental Therapeutics for the Treatment of Osteoarthritis

Osteoarthritis (OA) therapy remains a large challenge since no causative treatment options are so far available. Despite some main pathways contributing to OA are identified its pathogenesis is still rudimentary understood. A plethora of therapeutically promising agents are currently tested in experimental OA research to find an opportunity to reverse OA-associated joint damage and prevent its progression. Hence, this review aims to summarize novelly emerging experimental approaches for OA. Due to the diversity of strategies shown only main aspects could be summarized here including herbal medicines, nanoparticular compounds, growth factors, hormones, antibody-, cell- and extracellular vesicle (EV)-based approaches, optimized tools for joint viscosupplementation, genetic regulators such as si- or miRNAs and promising combinations. An abundant multitude of compounds obtained from plants, environmental, autologous or synthetic sources have been identified with anabolic, anti-inflammatory, -catabolic and anti-apoptotic properties. Some ubiquitous signaling pathways such as wingless and Integration site-1 (Wnt), Sirtuin, Toll-like receptor (TLR), mammalian target of rapamycin (mTOR), Nuclear Factor (NF)-κB and complement are involved in OA and addressed by them. Hyaluronan (HA) provided benefit in OA since many decades, and novel HA formulations have been developed now with higher HA content and long-term stability achieved by cross-linking suitable to be combined with other agents such as components from herbals or chemokines to attract regenerative cells. pH- or inflammation-sensitive nanoparticular compounds could serve as versatile slow-release systems of active compounds, for example, miRNAs. Some light has been brought into the intimate regulatory network of small RNAs in the pathogenesis of OA which might be a novel avenue for OA therapy in future. Attraction of autologous regenerative cells by chemokines and exosome-based treatment strategies could also innovate OA therapy.