Linking chondrocyte and synovial transcriptional profile to clinical phenotype in osteoarthritis

Sex differences in osteoarthritis prevalence, pain perception, physical function and therapeutics

OBJECTIVE

Women have a higher prevalence of osteoarthritis (OA) and worse clinical courses than men. However, the underlying factors and therapeutic outcomes of these sex-specific differences are incompletely researched. This review examines the current state of knowledge regarding sex differences in OA prevalence, risk factors, pain severity, functional outcomes, and use and response to therapeutics.

METHODS

PubMed database was used with the title keyword combinations "{gender OR sex} AND osteoarthritis" plus additional manual search of the included papers for pertinent references, yielding 212 references. Additional references were added and 343 were reviewed for appropriateness.

RESULTS

Globally, women account for 60% of people with osteoarthritis, with a greater difference after age 40. The higher risk for women may be due to differences in joint anatomy, alignment, muscle strength, hormonal influences, obesity, and/or genetics. At the same radiographic severity, women have greater pain severity than men, which may be explained by biologically distinct pain pathways, differential activation of central pain pathways, differences in pain sensitivity, perception, reporting, and coping strategies. Women have greater limitations of physical function and performance than men independent of BMI, OA severity, injury history, and amount of weekly exercise. Women also have greater use of analgesic medications than men but less use of arthroplasty and poorer prognosis after surgical interventions.

CONCLUSIONS

The recognition of sex differences in OA manifestations and management could guide tailoring of sex-specific treatment protocols, and analysis of sex as a biological variable in future research would enhance development of precision medicine.

Epigenomic differences between osteoarthritis grades in primary cartilage

OBJECTIVE

Osteoarthritis is a common and complex joint disorder that shows higher prevalence and greater disease severity in women. Here, we investigate genome-wide methylation profiles of primary chondrocytes from osteoarthritis patients.

DESIGN

We compare genome-wide methylation profiles of macroscopically intact (low-grade) and degraded (high-grade) osteoarthritis cartilage samples matched from osteoarthritis patients undergoing knee replacement surgery. We perform an epigenome-wide association study for cartilage degeneration across 170 patients and separately in 96 women and 74 men.

RESULTS

We reveal widespread epigenetic differences with enrichments of nervous system and apoptosis-related processes. We further identify substantial similarities between sexes, but also sex-specific markers and pathways.

CONCLUSIONS

Together, we provide the largest genome-wide methylation profiles of primary cartilage to date with enhanced and sex-specific insights into epigenetic processes underlying osteoarthritis progression.

Bidirectional association identified between synovitis and knee and hand osteoarthritis: a general population-based study

Background

Synovitis has long been considered a common and modifiable inflammatory feature of osteoarthritis (OA), but current disease-modifying anti-inflammatory treatments appear ineffective in OA clinical trials. Elucidating the temporal relationship between synovitis and OA could provide insight into the role of synovitis in OA.

Methods

We conducted a prospective cohort study based on the baseline and three-year follow-up data from the Xiangya Osteoarthritis (XO) Study. We assessed bidirectional associations between ultrasound-detected synovitis and radiographic and symptomatic OA at knee and hand sites using generalized estimating equations. Additionally, we performed bidirectional Mendelian randomization (MR) analyses to test these hypotheses utilising whole-genome sequencing data in the XO population. Age, sex, body mass index, smoking, alcohol consumption, educational level, physical activity, and joint injury history were adjusted for these analyses.

Findings

A total of 2211, 2420, 2280, and 2600 participants were enrolled for analyses of radiographic knee OA (RKOA), symptomatic knee OA (SKOA), radiographic hand OA (RHOA) and symptomatic hand OA (SHOA), respectively. The baseline synovitis (i.e., with synovitis vs. without synovitis) was associated with the incident RKOA (76/277 vs. 557/3674 knees), SKOA (49/387 vs. 287/4213 knees), RHOA (171/358 vs. 686/3664 hands) and SHOA (35/689 vs. 76/4327 hands), with adjusted odds ratio (aORs) of 2.2 (95% CI 1.7-3.1), 2.0 (1.3-2.9), 3.4 (2.7-4.4), and 2.4 (1.5-3.8), respectively. The baseline RKOA (with OA vs. without OA: 409/1246 vs. 481/3758 knees), SKOA (200/576 vs. 675/4356 knees), RHOA (192/778 vs. 410/3723 hands), and SHOA (41/162 vs. 548/4285 hands) were also associated with the incident synovitis, with aORs of 3.4 (95% CI 2.9-4.1), 2.7 (2.1-3.4), 2.3 (1.8-2.9) and 1.9 (1.2-2.8), respectively. These bidirectional associations were stronger when more active synovitis was compared with the reference group (all P < 0.05). MR analyses further supported bidirectional associations that synovitis significantly increased the odds of incident OA at both sites and vice versa (all ORs ranged from 1.2-1.7).

Interpretation

Our population-based cohort study found novel evidence of a bidirectional association between synovitis and OA, which was further validated through MR analysis and suggested that the bidirectional association is likely causal. Our findings indicated that synovitis is both a risk factor and a consequence of the OA rather than solely a risk factor.

Funding

The National Key Research and Development Plan, the National Natural Science Foundation of China, the Key Research and Development Program of Hunan Province, the Natural Science Foundation of Hunan Province, the Central South University Innovation-Driven Research Programme, and the Fundamental Research Funds for the Central Universities of Central South University.

Transcriptomics and metabolomics: Challenges of studying obesity in osteoarthritis

Objective

Obesity is a leading risk factor for both the incidence and progression of osteoarthritis (OA). Omic technologies, including transcriptomics and metabolomics are capable of identifying RNA and metabolite profiles in tissues and biofluids of OA patients. The objective of this review is to highlight studies using transcriptomics and metabolomics that contribute to our understanding of OA pathology in relation to obesity.

Design

We conducted a targeted search of PUBMED for articles, and GEO for datasets, published up to February 13, 2024, screening for those using high-throughput transcriptomic and metabolomic techniques to study human or pre-clinical animal model tissues or biofluids related to obesity-associated OA. We describe relevant studies and discuss challenges studying obesity as a disease-related factor in OA.

Results

Of the 107 publications identified by our search criteria, only 15 specifically used transcriptomics or metabolomics to study joint tissues or biofluids in obesity-related OA. Specific transcriptomic and metabolomic signatures associated with obesity-related OA have been defined in select local joint tissues, biofluids and other biological material. However, considerable challenges exist in understanding contributions of obesity-associated modifications of transcriptomes and metabolomes related to OA, including sociodemographic, anthropometric, dietary and molecular redundancy-related factors.

Conclusions

A number of additional transcriptomic and metabolomic studies are needed to comprehensively understand how obesity affects OA incidence, progression and outcomes. Integration of transcriptome and metabolome signatures from multiple tissues and biofluids, using network-based approaches will likely help to better define putative therapeutic targets that could enable precision medicine approaches to obese OA patients.

The Genetics and Functional Genomics of Osteoarthritis

Osteoarthritis is the most prevalent whole-joint degenerative disorder, and is characterized by the degradation of articular cartilage and the underlying bone structures. Almost 600 million people are affected by osteoarthritis worldwide. No curative treatments are available, and management strategies focus mostly on pain relief. Here, we provide a comprehensive overview of the available human genetic and functional genomics studies for osteoarthritis to date and delineate how these studies have helped shed light on disease etiopathology. We highlight genetic discoveries from genome-wide association studies and provide a detailed overview of molecular-level investigations in osteoarthritis tissues, including methylation-, transcriptomics-, and proteomics-level analyses. We review how functional genomics data from different molecular levels have helped to prioritize effector genes that can be used as drug targets or drug-repurposing opportunities. Finally, we discuss future directions with the potential to drive a step change in osteoarthritis research.

Development and Validation of Diagnostic Models for Transcriptomic Signature Genes for Multiple Tissues in Osteoarthritis

Background

Progress in research on expression profiles in osteoarthritis (OA) has been limited to individual tissues within the joint, such as the synovium, cartilage, or meniscus. This study aimed to comprehensively analyze the common gene expression characteristics of various structures in OA and construct a diagnostic model.

Methods

Three datasets were selected: synovium, meniscus, and knee joint cartilage. Modular clustering and differential analysis of genes were used for further functional analyses and the construction of protein networks. Signature genes with the highest diagnostic potential were identified and verified using external gene datasets. The expression of these genes was validated in clinical samples by Real-time (RT)-qPCR and immunohistochemistry (IHC) staining. This study investigated the status of immune cells in OA by examining their infiltration.

Results

The merged OA dataset included 438 DEGs clustered into seven modules using WGCNA. The intersection of these DEGs with WGCNA modules identified 190 genes. Using Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest algorithms, nine signature genes were identified (CDADC1, PPFIBP1, ENO2, NOM1, SLC25A14, METTL2A, LINC01089, L3HYPDH, NPHP3), each demonstrating substantial diagnostic potential (areas under the curve from 0.701 to 0.925). Furthermore, dysregulation of various immune cells has also been observed.

Conclusion

CDADC1, PPFIBP1, ENO2, NOM1, SLC25A14, METTL2A, LINC01089, L3HYPDH, NPHP3 demonstrated significant diagnostic efficacy in OA and are involved in immune cell infiltration.

Identification of eight genes associated with recurrent patellar dislocation

The inheritance of recurrent patellar dislocation (RPD) is known, but the susceptible gene remains unidentified. Here, we performed the first whole exome sequencing (WES) cohort study to identify the susceptible genes. The results showed eight genes were associated with this disease. Notably, the carboxypeptidase D (CPD) gene showed the highest relevance based on its gene function and tissue expression. Single-cell sequencing results indicate that the CPD gene is involved in the pathophysiological process of RPD through granulocytes. Implicated pathways include nuclear factor kappa B (NF-κB), mitogen-activated protein kinase (MAPK), and Wnt/β-catenin signaling, potentially influencing CPD's role in RPD pathogenesis. This study identified the susceptible gene and investigates the potential pathogenesis of RPD, which provided a new prospect for the understanding of RPD. Besides, it would offer the theoretical basis for disease prevention and genetic counseling.

PTH treatment before cyclic joint loading improves cartilage health and attenuates load-induced osteoarthritis development in mice

Osteoarthritis (OA) treatment is limited by the lack of effective nonsurgical interventions to slow disease progression. Here, we examined the contributions of the subchondral bone properties to OA development. We used parathyroid hormone (PTH) to modulate bone mass before OA initiation and alendronate (ALN) to inhibit bone remodeling during OA progression. We examined the spatiotemporal progression of joint damage by combining histopathological and transcriptomic analyses across joint tissues. The additive effect of PTH pretreatment before OA initiation and ALN treatment during OA progression most effectively attenuated load-induced OA pathology. Individually, PTH directly improved cartilage health and slowed the development of cartilage damage, whereas ALN primarily attenuated subchondral bone changes associated with OA progression. Joint damage reflected early transcriptomic changes. With both treatments, the structural changes were associated with early modulation of immunoregulation and immunoresponse pathways that may contribute to disease mechanisms. Overall, our results demonstrate the potential of subchondral bone-modifying therapies to slow the progression of OA.

Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies

OBJECTIVE

Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades.

DESIGN

We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease.

RESULTS

Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues.

CONCLUSIONS

Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions.

Articular cartilage repair biomaterials: strategies and applications

Articular cartilage injury is a frequent worldwide disease, while effective treatment is urgently needed. Due to lack of blood vessels and nerves, the ability of cartilage to self-repair is limited. Despite the availability of various clinical treatments, unfavorable prognoses and complications remain prevalent. However, the advent of tissue engineering and regenerative medicine has generated considerable interests in using biomaterials for articular cartilage repair. Nevertheless, there remains a notable scarcity of comprehensive reviews that provide an in-depth exploration of the various strategies and applications. Herein, we present an overview of the primary biomaterials and bioactive substances from the tissue engineering perspective to repair articular cartilage. The strategies include regeneration, substitution, and immunization. We comprehensively delineate the influence of mechanically supportive scaffolds on cellular behavior, shedding light on emerging scaffold technologies, including stimuli-responsive smart scaffolds, 3D-printed scaffolds, and cartilage bionic scaffolds. Biologically active substances, including bioactive factors, stem cells, extracellular vesicles (EVs), and cartilage organoids, are elucidated for their roles in regulating the activity of chondrocytes. Furthermore, the composite bioactive scaffolds produced industrially to put into clinical use, are also explicitly presented. This review offers innovative solutions for treating articular cartilage ailments and emphasizes the potential of biomaterials for articular cartilage repair in clinical translation.

APOD acts on fibroblast-like synoviocyte and chondrocyte to alleviate the process of osteoarthritis in vitro

The pathogenesis of osteoarthritis (OA) is still unclear, leading to the lack of targeted treatment. We aimed to probe into the effect of apolipoprotein D (APOD), the key gene from our previous study through bioinformatics analysis, on fibroblast-like synoviocyte (FLS) and chondrocytes in vitro to confirm its potential roles on the delay of OA progression. Primary FLS and chondrocytes were extracted from synovium and cartilage of OA patients and stimulated with interleukin 1β (IL-1β) in vitro. After APOD intervention, viability and proliferation of FLS and chondrocytes were detected. Subsequently, the inflammatory factors of the two cells were detected by quantitative reverse-transcription polymerase chain reaction, enzyme-linked immunosorbent assay, and western blot, and the apoptosis and autophagy-related substances were determined at the same time. Finally, the oxidation level in FLS and chondrocytes were detected. APOD reversed the change of gene expression stimulated by IL-1β in FLS and chondrocytes. APOD alleviated the proliferation of FLS while promoted proliferation of chondrocytes, and reduced the expression of inflammatory factors. Moreover, APOD promoted apoptosis of FLS and autography of chondrocytes, while reduced apoptosis of chondrocytes. Finally, decrease level of reactive oxygen species (ROS) in both cells were observed after APOD intervention, as well as the increased expression of antioxidant-related genes. APOD had effects on the proliferation of FLS and chondrocytes through apoptosis and autography as well as the reduction of oxidative stress, delaying the progress of OA.

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.

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.

Microscopic and transcriptomic changes in porcine synovium one year following disruption of the anterior cruciate ligament

OBJECTIVE

There is no disease-modifying treatment for posttraumatic osteoarthritis (PTOA). This may be partly due to an incomplete understanding of synovitis, which has been causally linked to PTOA progression. The microscopic and transcriptomic changes in synovium seen in early- to mid-stage PTOA were evaluated to better characterize this knowledge gap.

METHODS

Seventy-two Yucatan minipigs underwent transection of the anterior cruciate ligament (ACL). Subjects were randomized to no further intervention, ligament reconstruction, or ligament repair, followed by microscopic synovium evaluation and RNA-sequencing at 1, 4, and 52 weeks. Six additional subjects received no ligament transection and served as 1- and 4-week controls and 12 contralateral knees served as 52-week controls.

RESULTS

Synovial lining thickness, stromal cellularity, and overall microscopic synovitis reached their highest levels in the first few weeks following injury. Inflammatory infiltration continued to increase over the course of a year. Leaving the ACL transected, reconstructing the ligament, or repairing the ligament did not modulate synovitis development at 1, 4, or 52 weeks. Differential gene expression analysis of PTOA-affected synovium compared to control synovium revealed increased cell proliferation, angiogenesis, collagen breakdown, and diminished lipid metabolism at 1 and 4 weeks, and increased axonogenesis and focal adhesion with reduced immune activation at 52 weeks.

CONCLUSIONS

Synovitis was present one year after ACL injury and was not alleviated by surgical intervention. Gene expression in early synovitis was characterized by cell proliferation, angiogenesis, proteolysis, and reduced lipolysis, which was followed by nerve growth and cellular adhesion with less immune activation at 52 weeks.

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.

Extracellular matrix in synovium development, homeostasis and arthritis disease

Extracellular matrix (ECM) is a three-dimensional network entity composed of extracellular macromolecules. ECM in synovium not only supports the structural integrity of synovium, but also plays a crucial role in regulating homeostasis and damage repair response in synovium. Obvious disorders in the composition, behavior and function of synovial ECM will lead to the occurrence and development of arthritis diseases such as rheumatoid arthritis (RA), osteoarthritis (OA) and psoriatic arthritis (PsA). Based on the importance of synovial ECM, targeted regulation of the composition and structure of ECM is considered to be an effective measure for the treatment of arthritis disease. This paper reviews the current research status of synovial ECM biology, discusses the role and mechanism of synovial ECM in physiological status and arthritis disease, and summarizes the current strategies for targeting synovial ECM to provide information for the pathogenesis, diagnosis and treatment of arthritis disease.

Osteoarthritis genetic risk acting on the galactosyltransferase gene COLGALT2 has opposing functional effects in articulating joint tissues

BACKGROUND

Investigation of cartilage and chondrocytes has revealed that the osteoarthritis risk marked by the independent DNA variants rs11583641 and rs1046934 mediate  their effects by decreasing the methylation status of CpG dinucleotides in enhancers and increasing the expression of shared target gene COLGALT2. We set out to investigate if these functional effects operate in a non-cartilaginous joint tissue.

METHODS

Nucleic acids were extracted from the synovium of osteoarthritis patients. Samples were genotyped, and DNA methylation was quantified by pyrosequencing at CpGs within the COLGALT2 enhancers. CpGs were tested for enhancer effects using a synovial cell line and a reporter gene assay. DNA methylation was altered using epigenetic editing, with the impact on gene expression determined using quantitative polymerase chain reaction. In silico analysis complemented laboratory experiments.

RESULTS

The rs1046934 genotype did not associate with DNA methylation or COLGALT2 expression in the synovium, whereas the rs11583641 genotype did. Surprisingly, the effects for rs11583641 were opposite to those previously observed in cartilage. Epigenetic editing in synovial cells revealed that enhancer methylation is causally linked to COLGALT2 expression.

CONCLUSIONS

This is the first direct demonstration for osteoarthritis genetic risk of a functional link between DNA methylation and gene expression operating in opposite directions between articular joint tissues. It highlights pleiotropy in the action of osteoarthritis risk and provides a cautionary note in the application of future genetically based osteoarthritis therapies: an intervention that decreases the detrimental effect of a risk allele in one joint tissue may inadvertently increase its detrimental effect in another joint tissue.

CircRNAs in osteoarthritis: research status and prospect

Osteoarthritis (OA) is the most common joint disease globally, and its progression is irreversible. The mechanism of osteoarthritis is not fully understood. Research on the molecular biological mechanism of OA is deepening, among which epigenetics, especially noncoding RNA, is an emerging hotspot. CircRNA is a unique circular noncoding RNA not degraded by RNase R, so it is a possible clinical target and biomarker. Many studies have found that circRNAs play an essential role in the progression of OA, including extracellular matrix metabolism, autophagy, apoptosis, the proliferation of chondrocytes, inflammation, oxidative stress, cartilage development, and chondrogenic differentiation. Differential expression of circRNAs was also observed in the synovium and subchondral bone in the OA joint. In terms of mechanism, existing studies have mainly found that circRNA adsorbs miRNA through the ceRNA mechanism, and a few studies have found that circRNA can serve as a scaffold for protein reactions. In terms of clinical transformation, circRNAs are considered promising biomarkers, but no large cohort has tested their diagnostic value. Meanwhile, some studies have used circRNAs loaded in extracellular vesicles for OA precision medicine. However, there are still many problems to be solved in the research, such as the role of circRNA in different OA stages or OA subtypes, the construction of animal models of circRNA knockout, and more research on the mechanism of circRNA. In general, circRNAs have a regulatory role in OA and have particular clinical potential, but further studies are needed in the future.

Responding to ACL Injury and its Treatments: Comparative Gene Expression between Articular Cartilage and Synovium

The relationship between cartilage and synovium is a rapidly growing area of osteoarthritis research. However, to the best of our knowledge, the relationships in gene expression between these two tissues have not been explored in mid-stage disease development. The current study compared the transcriptomes of these two tissues in a large animal model one year following posttraumatic osteoarthritis induction and multiple surgical treatment modalities. Thirty-six Yucatan minipigs underwent transection of the anterior cruciate ligament. Subjects were randomized to no further intervention, ligament reconstruction, or ligament repair augmented with an extracellular matrix (ECM) scaffold, followed by RNA sequencing of the articular cartilage and synovium at 52 weeks after harvest. Twelve intact contralateral knees served as controls. Across all treatment modalities, the primary difference in the transcriptomes was that the articular cartilage had greater upregulation of genes related to immune activation compared to the synovium-once baseline differences between cartilage and synovium were adjusted for. Oppositely, synovium featured greater upregulation of genes related to Wnt signaling compared to articular cartilage. After adjusting for expression differences between cartilage and synovium seen following ligament reconstruction, ligament repair with an ECM scaffold upregulated pathways related to ion homeostasis, tissue remodeling, and collagen catabolism in cartilage relative to synovium. These findings implicate inflammatory pathways within cartilage in the mid-stage development of posttraumatic osteoarthritis, independent of surgical treatment. Moreover, use of an ECM scaffold may exert a chondroprotective effect over gold-standard reconstruction through preferentially activating ion homeostatic and tissue remodeling pathways within cartilage.

Osteoarthritis year in review: genetics, genomics and epigenetics

This "year in review" provides a summary of the research findings on the topic of genetics, genomics and epigenetics for osteoarthritis (OA) between Mar 2021-Apr 2022. A search routine of the literature in PubMed for the keyword, osteoarthritis, together with topics on genetics, genomics, epigenetics, polymorphism, DNA methylation, noncoding RNA, lncRNA, proteomics, and single cell RNA sequencing, returned key research articles and relevant reviews. Following filtering of duplicates across search routines, 695 unique research articles and 112 reviews were identified. We manually curated these articles and selected 90 as references for this review. However, we were unable to refer to all these articles, and only used selected articles to highlight key outcomes and trends. The trend in genetics is on the meta-analysis of existing cohorts with comparable genetic and phenotype characterisation of OA; in particular, clear definition of endophenotypes to enhance the genetic power. Further, many researchers are realizing the power of big data and multi-omics approaches to gain molecular insights for OA, and this has opened innovative approaches to include transcriptomics and epigenetics data as quantitative trait loci (QTLs). Given that most of the genetic loci for OA are not located within coding regions of genes, implying the impact is likely to be on gene regulation, epigenetics is a hot topic, and there is a surge in studies relating to the role of miRNA and long non-coding RNA on cartilage biology and pathology. The findings are exciting and new insights are provided in this review to summarize a year of research and the road map to capture all new innovations to achieve the desired goal in OA prevention and treatment.

Cytokine-Like Protein 1 (CYTL1) as a Key Target of M-Stage Immune Infiltration in Stomach Adenocarcinoma

Background

Stomach adenocarcinoma (STAD) has an extremely high fatality rate worldwide, and survival after metastasis is extremely poor. Cytokine-like protein 1 (CYTL1) has prognostic significance in various tumors. We aimed to explore the impact and underlying molecular mechanisms of CYTL1 in STAD through bioinformatics analysis.

Methods

We used R software to analyze CYTL1 expression in STAD samples (n = 375) and normal samples (n = 32) in The Cancer Genome Atlas database. Kaplan-Meier analysis was used to verify the relationship between CYTL1 expression and overall survival (OS) and disease-specific survival (DSS) based on the clinical characteristics and subgroups of patients with STAD. Furthermore, univariate and multivariate Cox regression analyses were used to verify the outcome variables of OS and DSS in patients with STAD. Receiver operating characteristic curves were used to test the predictive power of CYTL1. The biological functions and signaling pathways of CYTL1 were determined using gene set enrichment analysis (GSEA), and the immune infiltration patterns of CYTL1 and correlation of immune-related markers were analyzed using single-sample GSEA (ssGSEA) and an estimate algorithm.

Results

In our research, low CYTL1 expression (tumor vs. normal) was noted in patients with STAD. High CYTL1 expression was detrimental to OS and DSS and had good diagnostic performance (AUC = 0.731). In the subtype analysis of STAD, T3 and T4 stages, N0 and N1 stages, M0 stage, gender (female), and age (≤65 years) showed different performances between OS and DSS. Univariate and multivariate Cox analyses identified CYTL1 as an independent factor, and logistic regression analysis indicated that CYTL1 was associated with M stage (OR = 3.406) and sex (OR = 1.535). GSEA of the differential genes of CYTL1 showed the possible involvement of immunity. ssGSEA and estimation algorithms were used to further evaluate whether immune cells were closely related to CYTL1 expression, and many markers of immune cells also had statistical significance with the expression of CYTL1.

Conclusion

CYTL1 may, thus, act as an independent prognostic factor for STAD and regulate STAD progression by affecting the immune microenvironment.

The impact of omics research on our understanding of osteoarthritis and future treatments

PURPOSE OF REVIEW

To review recent studies using 'Omics' approaches (genomics, proteomics, metabolomics, single cell analyses) in patient populations and animal models of osteoarthritis (OA), with the goal of identifying disease-modifying mechanisms that could serve as therapeutic and diagnostic targets.

RECENT FINDINGS

The number of genes, pathways and molecules with potential roles in OA pathogenesis has grown substantially over the last 18 months. Studies have expanded from their traditional focus on cartilage and gene expression to other joint tissues, proteins and metabolites. Single cell approaches provide unprecedented resolution and exciting insights into the heterogeneity of cellular activities in OA. Functional validation and investigation of underlying mechanisms in animal models of OA, in particular genetically engineered mice, link Omics findings to pathophysiology and potential therapeutic applications.

SUMMARY

Although great progress has been made in the use of Omics approaches to OA, in both animal models and patient samples, much work remains to be done. In addition to filling gaps in data sets not yet existing, integration of data from the various approaches, mechanistic investigations, and linkage of Omics data to patient stratification remain significant challenges.

The role of the immune microenvironment in bone, cartilage, and soft tissue regeneration: from mechanism to therapeutic opportunity

Bone, cartilage, and soft tissue regeneration is a complex spatiotemporal process recruiting a variety of cell types, whose activity and interplay must be precisely mediated for effective healing post-injury. Although extensive strides have been made in the understanding of the immune microenvironment processes governing bone, cartilage, and soft tissue regeneration, effective clinical translation of these mechanisms remains a challenge. Regulation of the immune microenvironment is increasingly becoming a favorable target for bone, cartilage, and soft tissue regeneration; therefore, an in-depth understanding of the communication between immune cells and functional tissue cells would be valuable. Herein, we review the regulatory role of the immune microenvironment in the promotion and maintenance of stem cell states in the context of bone, cartilage, and soft tissue repair and regeneration. We discuss the roles of various immune cell subsets in bone, cartilage, and soft tissue repair and regeneration processes and introduce novel strategies, for example, biomaterial-targeting of immune cell activity, aimed at regulating healing. Understanding the mechanisms of the crosstalk between the immune microenvironment and regeneration pathways may shed light on new therapeutic opportunities for enhancing bone, cartilage, and soft tissue regeneration through regulation of the immune microenvironment.

Recharge of chondrocyte mitochondria by sustained release of melatonin protects cartilage matrix homeostasis in osteoarthritis

Recent evidence indicates that the mitochondrial functions of chondrocytes are impaired in the pathogenesis of osteoarthritis (OA). Melatonin can attenuate cartilage degradation through its antioxidant functions. This study aims to investigate whether melatonin could rescue the impaired mitochondrial functions of OA chondrocytes and protect cartilage metabolism. OA chondrocytes showed a compromised matrix synthesis capacity associated with mitochondrial dysfunction and aberrant oxidative stress. In vitro treatments with melatonin promoted the expression of cartilage extracellular matrix (ECM) components, improved adenosine triphosphate production, and attenuated mitochondrial oxidative stress. Mechanistically, either silencing of SOD2 or inhibition of SIRT1 abolished the protective effects of melatonin on mitochondrial functions and ECM synthesis. To achieve a sustained release effect, a melatonin-laden drug delivery system (DDS) was developed and intra-articular injection with DDS successfully improved cartilage matrix degeneration in a posttraumatic rat OA model. These findings demonstrate that melatonin-mediated recharge of mitochondria to rescue the mitochondrial functions of chondrocytes represents a promising therapeutic strategy to protect cartilage from OA.

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.

RNAseq of Osteoarthritic Synovial Tissues: Systematic Literary Review

Osteoarthritis (OA) is one of the most common causes of disability in aged people, and it is defined as a degenerative arthropathy, characterized by the disruption in joint tissue. The synovium plays a vital role in maintaining the health of the joint by supplying the nutrients to the surrounding tissues and the lubrication for joint movement. While it is well known that all the joint tissues are communicating and working together to provide a functioning joint, most studies on OA have been focused on bone and cartilage but much less about synovium have been reported. The purpose of this review was to investigate the current literature focused on RNA sequencing (RNAseq) of osteoarthritic synovial tissues to further understand the dynamic transcriptome changes occurring in this pivotal joint tissue. A total of 3 electronic databases (PubMed, CINHAL Complete, and Academic Complete) were systematically searched following PRISMA guidelines. The following criteria was used for inclusion: English language, free full text, between the period 2011–2022, size of sample (n &gt; 10), study design being either retrospective or prospective, and RNAseq data of synovial tissue from OA subjects. From the initial search, 174 articles, 5 met all of our criteria and were selected for this review. The RNAseq analysis revealed several differentially expressed genes (DEGs) in synovial tissue. These genes are related to the inflammatory pathway and regulation of the extracellular matrix. The MMP family, particularly MMP13 was identified by three of the studies, indicating its important role in OA. IL6, a key contributor in the inflammation pathway, was also identified in 3 studies. There was a total of 8 DEGs, MMP13, MMP1, MMP2, APOD, IL6, TNFAIP6, FCER1G, and IGF1 that overlapped in 4 out of the 5 studies. One study focused on microbial RNA in the synovial tissue found that the microbes were differentially expressed in OA subjects too. These differentially expressed microbes have also been linked to the inflammatory pathway. Further investigation with more clinical gene profiling in synovial tissue of OA subjects is required to reveal the causation and progression, as well as aid in the development of new treatments.

Translating osteoarthritis genetics research: challenging times ahead

The ultimate goal of molecular genetic studies of human diseases is to translate the discoveries for patient benefit. For diseases that lack licensed disease-modifying therapeutics, such as osteoarthritis (OA), the need is acute. OA is polygenic and affects older individuals, with a recent genome-wide study of over 800 000 individuals adding 52 novel association signals to those already reported on for this common arthritis. Many of the predicted effector genes of these signals encode proteins that are targets of drugs for other indications, highlighting repurposing opportunities. Here, the potential for OA genetic data to translate is discussed, including whether the developmental origin of OA will limit the application of genetic risk data for disease-modification purposes.

An osteoarthritis subtype characterized by synovial lipid metabolism disorder and fibroblast-like synoviocyte dysfunction

Background

The heterogeneity of osteoarthritis (OA) significantly limits the effectiveness of pharmacological treatments in an unselected patient population. In this context, the identification of OA subtypes is meaningful for the development of therapies that target specific types of OA pathogenesis.

Methods

Expression array profiles of 70 OA and 36 control synovial samples were extracted from the GEO database. Unsupervised consensus clustering was performed based on the most variable genes to identify OA subclusters. Next, Joint samples from OA patients were obtained. We divided the OA patient into two subpopulations according to synovial ADCY7 levels. Synovium and cartilage samples from different OA subpopulations were evaluated. In addition, we established a high-fat diet (HFD)-induced rat OA model. We evaluated OA progression, lipid metabolism, synovitis and fibroblast-like synoviocytes (FLS) function in this HFD-induced OA model.

Results

70 OA patients were categorized into three distinct subclusters. We noted that one subcluster was characterized by synovial lipid metabolism disorder GO terms. We further identified the most noticeable KEGG pathway “Regulation of lipolysis in adipocytes” in this subcluster as well as the most significantly differentially expressed gene, ADCY7. We found that the ADCY7 high expressing group (32.6%) exhibited features of synovial inflammatory lipolysis epithelial-mesenchymal transition (EMT) tendency, as well as faster join space narrowing. The HFD induced OA-like degeneration in rat joints. We observed similar synovial inflammatory lipolysis and EMT in FLS, characterized by higher proliferative and invasive activity and elevated proinflammatory and procatabolic properties. ADCY7 was highly expressed in the synovium of the HFD-OA model rats and the inhibition of ADCY7 effectively attenuated these HFD-induced degenerative changes as well as synovial inflammatory lipolysis and FLS dysfunction. In HFD-FLSs, ADCY7 promoted the phosphorylation of PKA as well as its downstream lipid droplet-associated protein PLIN1 and hormone-sensitive lipase (HSL). The inhibition of PKA largely alleviated ADCY7-mediated HFD-FLS dysfunction.

Conclusions

We described a synovial EMT and lipid metabolism disorder in the pathogenesis of OA. This novel mechanism may represent a currently undefined OA subtype. ADCY7 is a potential molecular marker of this pathomechanism.

The Translational potential of this article

Utilizing synovial samples from OA patients, we identified a subpopulation with high ADCY7 expression. This may represent a currently undefined OA subtype and explain the clinical phenomenon of more severe synovial inflammation in obese OA patients. In addition, we established an HFD-induced OA rat model and found an upregulation of ADCY7 in the synovium. We confirmed that the inhibition of ADCY7 could effectively attenuate HFD-induced degenerative changes as well as the inflammatory lipolysis and FLS dysfunction observed in the rat model. This suggests that ADCY7 and its downstream pathways are potential pharmacological targets for treating this lipid-metabolism-disorder-related OA mechanism.

Osteoarthritis year in review: genetics, genomics, epigenetics

OBJECTIVE

In this review, we have highlighted the advances over the past year in genetics, genomics and epigenetics in the field of osteoarthritis (OA).

METHODS

A literature search of PubMed was performed using the criteria: "osteoarthritis" and one of the following terms "genetic(s), genomic(s), epigenetic(s), polymorphism, noncoding ribonucleic acid (RNA), microRNA, long noncoding RNA, lncRNA, circular RNA, RNA sequencing (RNA-seq), single cell sequencing, transcriptomics, or deoxyribonucleic acid (DNA) methylation between April 01, 2020 and April 30, 2021.

RESULTS

In total we identified 765 unique publications, which eventually reduced to 380 of relevance to the field as judged by two assessors. Many of these studies included multiple search terms. We summarised advances relating to genetics, functional genetics, genomics and epigenetics, focusing on our personal key papers during the year.

CONCLUSIONS

This year few studies have identified new genetic variants contributing to OA susceptibility, but a focus has been on refining risk loci or their functional validation. The use of new technologies together with investigating the cross-talk between multiple tissue types, greater sample sizes and/or better patient classification (OA subtypes) will continue to increase our knowledge of disease mechanisms and progress towards understanding and treating OA.

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.