Widespread epigenomic, transcriptomic and proteomic differences between hip osteophytic and articular chondrocytes in osteoarthritis

Single-cell RNA sequencing in osteoarthritis

Osteoarthritis is a progressive and heterogeneous joint disease with complex pathogenesis. The various phenotypes associated with each patient suggest that better subgrouping of tissues associated with genotypes in different phases of osteoarthritis may provide new insights into the onset and progression of the disease. Recently, single-cell RNA sequencing was used to describe osteoarthritis pathogenesis on a high-resolution view surpassing traditional technologies. Herein, this review summarizes the microstructural changes in articular cartilage, meniscus, synovium and subchondral bone that are mainly due to crosstalk amongst chondrocytes, osteoblasts, fibroblasts and endothelial cells during osteoarthritis progression. Next, we focus on the promising targets discovered by single-cell RNA sequencing and its potential applications in target drugs and tissue engineering. Additionally, the limited amount of research on the evaluation of bone-related biomaterials is reviewed. Based on the pre-clinical findings, we elaborate on the potential clinical values of single-cell RNA sequencing for the therapeutic strategies of osteoarthritis. Finally, a perspective on the future development of patient-centred medicine for osteoarthritis therapy combining other single-cell multi-omics technologies is discussed. This review will provide new insights into osteoarthritis pathogenesis on a cellular level and the field of applications of single-cell RNA sequencing in personalized therapeutics for osteoarthritis in the future.

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 > 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.

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.

Human osteoblasts obtained from distinct periarticular sites demonstrate differences in biological function in vitro

AIMS

Accumulated evidence indicates that local cell origins may ingrain differences in the phenotypic activity of human osteoblasts. We hypothesized that these differences may also exist in osteoblasts harvested from the same bone type at periarticular sites, including those adjacent to the fixation sites for total joint implant components.

METHODS

Human osteoblasts were obtained from the acetabulum and femoral neck of seven patients undergoing total hip arthroplasty (THA) and from the femoral and tibial cuts of six patients undergoing total knee arthroplasty (TKA). Osteoblasts were extracted from the usually discarded bone via enzyme digestion, characterized by flow cytometry, and cultured to passage three before measurement of metabolic activity, collagen production, alkaline phosphatase (ALP) expression, and mineralization.

RESULTS

Osteoblasts from the acetabulum showed lower proliferation (p = 0.034), cumulative collagen release (p < 0.001), and ALP expression (p = 0.009), and produced less mineral (p = 0.006) than those from the femoral neck. Osteoblasts from the tibia produced significantly less collagen (p = 0.021) and showed lower ALP expression than those from the distal femur.

CONCLUSION

We have demonstrated for the first time an anatomical regional variation in the biological behaviours of osteoblasts on either side of the hip and knee joint. The lower osteoblast proliferation, matrix production, and mineralization from the acetabulum compared to those from the proximal femur may be reflected in differences in bone formation and implant fixation at these sites. Cite this article: Bone Joint Res 2021;10(9):611-618.

Chondrocyte protein co-synthesis network analysis links ECM mechanosensing to metabolic adaptation in osteoarthritis

BACKGROUND

Knee osteoarthritis (OA) is one of the most common structural OA disorders globally. Incomplete understanding of the fundamental biological aspects of osteoarthritis underlies the current lack of effective treatment or disease modifying drugs.

RESEARCH DESIGN AND METHODS

We implemented a systems approach by making use of the statistical network concepts in Weighted Gene Co-expression Analysis to reconstruct the organization of the core proteome network in chondrocytes obtained from OA patients and healthy individuals. Protein modules reflect groups of tightly co-ordinated changes in protein abundance across healthy and OA chondrocytes.

RESULTS

The unbiased systems analysis identified extracellular matrix (ECM) mechanosensing and glycolysis as two modules that are most highly correlated with ΟΑ. The ECM module was enriched in the OA genetic risk factors tenascin-C (TNC) and collagen 11A1 (COL11A1), as well as in cartilage oligomeric matrix protein (COMP), a biomarker associated with cartilage integrity. Mapping proteins that are unique to OA or healthy chondrocytes onto the core interactome, which connects microenvironment sensing and regulation of glycolysis, identified differences in metabolic and anti-inflammatory adaptation.

CONCLUSION

The interconnection between cartilage ECM remodeling and metabolism is indicative of the dynamic chondrocyte states and their significance in osteoarthritis.

MFG-E8 regulated by miR-99b-5p protects against osteoarthritis by targeting chondrocyte senescence and macrophage reprogramming via the NF-κB pathway

Milk fat globule-epidermal growth factor (EGF) factor 8 (MFG-E8), as a necessary bridging molecule between apoptotic cells and phagocytic cells, has been widely studied in various organs and diseases, while the effect of MFG-E8 in osteoarthritis (OA) remains unclear. Here, we identified MFG-E8 as a key factor mediating chondrocyte senescence and macrophage polarization and revealed its role in the pathology of OA. We found that MFG-E8 expression was downregulated both locally and systemically as OA advanced in patients with OA and in mice after destabilization of the medial meniscus surgery (DMM) to induce OA. MFG-E8 loss caused striking progressive articular cartilage damage, synovial hyperplasia, and massive osteophyte formation in OA mice, which was relieved by intra-articular administration of recombinant mouse MFG-E8 (rmMFG-E8). Moreover, MFG-E8 restored chondrocyte homeostasis, deferred chondrocyte senescence and reprogrammed macrophages to the M2 subtype to alleviate OA. Further studies showed that MFG-E8 was inhibited by miR-99b-5p, expression of which was significantly upregulated in OA cartilage, leading to exacerbation of experimental OA partially through activation of NF-κB signaling in chondrocytes. Our findings established an essential role of MFG-E8 in chondrocyte senescence and macrophage reprogramming during OA, and identified intra-articular injection of MFG-E8 as a potential therapeutic target for OA prevention and treatment.

Analysis of mRNA Expression and DNA Methylation Datasets According to the Genomic Distribution of CpG Sites in Osteoarthritis

Objectives Transcriptional changes in cartilage can impact function by causing degradation such as that which occurs during the development of osteoarthritis (OA). Epigenetic regulation may be a key factor leading to transcriptional changes in OA. In this study, we performed a combined analysis of DNA methylation and gene expression microarray datasets and identified key transcription factors (TFs) central to the regulation of gene expression in OA. Methods A DNA methylation profile dataset (GSE63106) and a gene expression profiling dataset (GSE114007) were extracted from the Gene Expression Omnibus (GEO). We used ChAMP methylation analysis and the Limma package to identify differentially methylation genes (DMGs) and differentially expressed genes (DEGs) from normal and human knee cartilage samples in OA. Function enrichment analysis of DMGs was conducted using the DAVID database. A combined analysis of DEGs and DMGs was conducted to identify key TFs in OA. We then validated the mRNA expression of selected TFs in normal and OA cartilage by RT-qPCR. Primary chondrocytes were cultured and treated with the DNA methylation inhibitor 5-Aza-2-deoxycytidine (5-Aza) for functional validation. Results We identified 2,170 differential methylation sites (DMS) containing 1005 genes and 1986 DEGs between normal human and OA cartilage. Functional analysis of DMGs revealed that focal adhesion, extracellular matrix (ECM)-receptor interactions, the PI3K-Akt signaling pathway, and the FoxO signaling pathway were involved in OA. Integrated analysis showed a subset of 17 TFs. Four TFs (ELF3, SOX11, RARA, and FOXD2) were validated. RT-qPCR results showed the mRNA expression of SOX11, RARA, and FOXD2 were consistent with the results from the mRNA expression data. However, the expression of ELF3 could not be validated. Upon 5-Aza-2'-deoxycytidine (5-Aza) treatment, the mRNA levels of ELF3 and SOX11 were down-regulated, whilst RARA was up-regulated, and FOXD2 showed no significant change in expression level. Conclusions the effect of DNA methylation on the transcriptional regulation is related to the distribution of methylated sites across the genome. Epigenetic studies on the positions of DMS in transcriptional units can inform a better understanding of the function of DNA methylation and its transcription regulation.

A molecular quantitative trait locus map for osteoarthritis

Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis.

Understanding osteoarthritis pathogenesis: a multiomics system-based approach

PURPOSE OF REVIEW

Osteoarthritis is a heterogeneous, multifactorial condition regulated by complex biological interactions at multiple levels. Comprehensive understanding of these regulatory interactions is required to develop feasible advances to improve patient outcomes. Improvements in technology have made extensive genomic, transcriptomic, epigenomic, proteomic, and metabolomic profiling possible. This review summarizes findings over the past 20 months related to omics technologies in osteoarthritis and examines how using a multiomics approach is necessary for advancing our understanding of osteoarthritis as a disease to improve precision osteoarthritis treatments.

RECENT FINDINGS

Using the search terms 'genomics' or 'transcriptomics' or 'epigenomics' or 'proteomics' or 'metabolomics' and 'osteoarthritis' from January 1, 2018 to August 31, 2019, we identified advances in omics approaches applied to osteoarthritis. Trends include untargeted whole genome, transcriptome, proteome, and metabolome analyses leading to identification of novel molecular signatures, cell subpopulations and multiomics validation approaches.

SUMMARY

To address the complexity of osteoarthritis, integration of multitissue analyses by multiomics approaches with the inclusion of longitudinal clinical data is necessary for a comprehensive understanding of the disease process, and for appropriate development of efficacious diagnostics, prognostics, and biotherapeutics.

Accelerating functional gene discovery in osteoarthritis

Osteoarthritis causes debilitating pain and disability, resulting in a considerable socioeconomic burden, yet no drugs are available that prevent disease onset or progression. Here, we develop, validate and use rapid-throughput imaging techniques to identify abnormal joint phenotypes in randomly selected mutant mice generated by the International Knockout Mouse Consortium. We identify 14 genes with functional involvement in osteoarthritis pathogenesis, including the homeobox gene Pitx1, and functionally characterize 6 candidate human osteoarthritis genes in mouse models. We demonstrate sensitivity of the methods by identifying age-related degenerative joint damage in wild-type mice. Finally, we phenotype previously generated mutant mice with an osteoarthritis-associated polymorphism in the Dio2 gene by CRISPR/Cas9 genome editing and demonstrate a protective role in disease onset with public health implications. We hope this expanding resource of mutant mice will accelerate functional gene discovery in osteoarthritis and offer drug discovery opportunities for this common, incapacitating chronic disease.

Osteoarthritis from evolutionary and mechanistic perspectives

Developmental osteogenesis and the pathologies associated with tissues that normally are mineralized are active areas of research. All of the basic cell types of skeletal tissue evolved in early aquatic vertebrates. Their characteristics, transcription factors, and signaling pathways have been conserved, even as they adapted to the challenge imposed by gravity in the transition to terrestrial existence. The response to excess mechanical stress (among other factors) can be expressed in the pathologic phenotype described as osteoarthritis (OA). OA is mediated by epigenetic modification of the same conserved developmental gene networks, rather than by gene mutations or new chemical signaling pathways. Thus, these responses have their evolutionary roots in morphogenesis. Epigenetic channeling and heterochrony, orchestrated primarily by microRNAs, maintain the sequence of these responses, while allowing variation in their timing that depends at least partly on the life history of the individual.

Role of Epigenomics in Bone and Cartilage Disease

Phenotypic variation in skeletal traits and diseases is the product of genetic and environmental factors. Epigenetic mechanisms include information-containing factors, other than DNA sequence, that cause stable changes in gene expression and are maintained during cell divisions. They represent a link between environmental influences, genome features, and the resulting phenotype. The main epigenetic factors are DNA methylation, posttranslational changes of histones, and higher-order chromatin structure. Sometimes non-coding RNAs, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), are also included in the broad term of epigenetic factors. There is rapidly expanding experimental evidence for a role of epigenetic factors in the differentiation of bone cells and the pathogenesis of skeletal disorders, such as osteoporosis and osteoarthritis. However, different from genetic factors, epigenetic signatures are cell- and tissue-specific and can change with time. Thus, elucidating their role has particular difficulties, especially in human studies. Nevertheless, epigenomewide association studies are beginning to disclose some disease-specific patterns that help to understand skeletal cell biology and may lead to development of new epigenetic-based biomarkers, as well as new drug targets useful for treating diffuse and localized disorders. Here we provide an overview and update of recent advances on the role of epigenomics in bone and cartilage diseases. © 2019 American Society for Bone and Mineral Research.