Genetic and Epigenetic Fine-Tuning of TGFB1 Expression Within the Human Osteoarthritic Joint

The methylomic landscape of human articular cartilage development contains epigenetic signatures of osteoarthritis risk

Increasing evidence is emerging to link age-associated complex musculoskeletal diseases, including osteoarthritis (OA), to developmental factors. Multiple studies have shown a functional role for DNA methylation in the genetic mechanisms of OA risk using articular cartilage samples taken from aged individuals, yet knowledge of temporal changes to the methylome during human cartilage development is limited. We quantified DNA methylation at ∼700,000 individual CpGs across the epigenome of developing human chondrocytes in 72 samples ranging from 7 to 21 post-conception weeks. We identified significant changes in 3% of all CpGs and >8,200 developmental differentially methylated regions. We further identified 24 loci at which OA genetic variants colocalize with methylation quantitative trait loci. Through integrating developmental and mature human chondrocyte datasets, we find evidence for functional effects exerted solely in development or throughout the life course. This will have profound impacts on future approaches to translating genetic pathways for therapeutic intervention.

The importance of functional genomics studies in precision rheumatology

Rheumatic diseases, those that affect the musculoskeletal system, cause significant morbidity. Among risk factors of these diseases is a significant genetic component. Recent advances in high-throughput omics techniques now allow a comprehensive profiling of patients at a genetic level through genome-wide association studies. Without functional interpretation of variants identified through these studies, clinical insight remains limited. Strategies include statistical fine-mapping that refine the list of variants in loci associated with disease, whilst colocalization techniques attempt to attribute function to variants that overlap a genetically active chromatin annotation. Functional validation using genome editing techniques can be used to further refine genetic signals and identify key pathways in cell types relevant to rheumatic disease biology. Insight gained from the combination of genetic studies and functional validation can be used to improve precision medicine in rheumatic diseases by allowing risk prediction and drug repositioning.

Comparative Analysis of Osteoarthritis Therapeutics: A Justification for Harnessing Retrospective Strategies via an Inverted Pyramid Model Approach

In this review, we seek to explore two distinct approaches to the clinical management of OA: a prospective approach, addressing primarily one's genetic predisposition to OA and generating early intervention options, and the retrospective approach, aimed at halting or reversing OA progression post-symptom onset. The clinical management of OA remains challenging, largely due to the limited availability of preventative treatments and failure of existing therapies to modify or reverse the underlying pathophysiology. The prospective approach involves the identification of genetic markers associated with OA and utilizes in vitro and in vivo models to characterize the underlying disease mechanism. Further, this approach focuses on identifying genetic predispositions and unique molecular subtypes of OA to develop individualized treatment plans based on patient genotypes. While the current literature investigating this strategy has been notable, this approach faces substantial challenges, such as extensive time burdens and utilization of extensive genetic testing that may not be economically feasible. Additionally, there is questionable justification for such extensive investigations, given OA's relatively low mortality rates and burden when contrasted with diseases like specific forms of cancer, which rely heavily on the prospective approach. Alternatively, the retrospective approach primarily focuses on intervention following symptom onset and aims to utilize novel therapeutics to slow or reverse the inflammatory cascade typically seen in disease progression. These treatments, like Hippo pathway inhibitors, have shown initial promise in halting OA progression and alleviating OA symptomology by modulating cellular processes to preserve articular cartilage. In comparison to the prospective approach, the retrospective strategy is likely more cost-effective, more widely applicable, and does not necessitate thorough and invasive genetic screening. However, this approach must still be weighed against the typical natural history of disease progression, which frequently results in total knee arthroplasty and unacceptable outcomes for 15-20% of patients. From a comparative analysis of these two approaches, this review argues that the retrospective strategy, with ideally lower time and economic burden and greater accessibility, offers a more reasonable and effective solution in the context of OA management. Using a similar approach to other management of chronic diseases, we suggest an "Inverted Pyramid" model algorithm, a structured research and development regimen that prioritizes generating widely effective therapies first, with subsequent refinement of treatments based on the development of patient resistance to these therapies. We argue that this strategy may reduce the need for total knee arthroplasty while improving patient outcomes and accessibility.

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.

Evolution and advancements in genomics and epigenomics in OA research: How far we have come

OBJECTIVE

Osteoarthritis (OA) is the most prevalent musculoskeletal disease affecting articulating joint tissues, resulting in local and systemic changes that contribute to increased pain and reduced function. Diverse technological advancements have culminated in the advent of high throughput "omic" technologies, enabling identification of comprehensive changes in molecular mediators associated with the disease. Amongst these technologies, genomics and epigenomics - including methylomics and miRNomics, have emerged as important tools to aid our biological understanding of disease.

DESIGN

In this narrative review, we selected articles discussing advancements and applications of these technologies to OA biology and pathology. We discuss how genomics, deoxyribonucleic acid (DNA) methylomics, and miRNomics have uncovered disease-related molecular markers in the local and systemic tissues or fluids of OA patients.

RESULTS

Genomics investigations into the genetic links of OA, including using genome-wide association studies, have evolved to identify 100+ genetic susceptibility markers of OA. Epigenomic investigations of gene methylation status have identified the importance of methylation to OA-related catabolic gene expression. Furthermore, miRNomic studies have identified key microRNA signatures in various tissues and fluids related to OA disease.

CONCLUSIONS

Sharing of standardized, well-annotated omic datasets in curated repositories will be key to enhancing statistical power to detect smaller and targetable changes in the biological signatures underlying OA pathogenesis. Additionally, continued technological developments and analysis methods, including using computational molecular and regulatory networks, are likely to facilitate improved detection of disease-relevant targets, in-turn, supporting precision medicine approaches and new treatment strategies for OA.

Osteoarthritis as an Enhanceropathy: Gene Regulation in Complex Musculoskeletal Disease

PURPOSE OF REVIEW

Osteoarthritis is a complex and highly polygenic disease. Over 100 reported osteoarthritis risk variants fall in non-coding regions of the genome, ostensibly conferring functional effects through the disruption of regulatory elements impacting target gene expression. In this review, we summarise the progress that has advanced our knowledge of gene enhancers both within the field of osteoarthritis and more broadly in complex diseases.

RECENT FINDINGS

Advances in technologies such as ATAC-seq have facilitated our understanding of chromatin states in specific cell types, bolstering the interpretation of GWAS and the identification of effector genes. Their application to osteoarthritis research has revealed enhancers as the principal regulatory element driving disease-associated changes in gene expression. However, tissue-specific effects in gene regulatory mechanisms can contribute added complexity to biological interpretation. Understanding gene enhancers and their altered activity in specific cell and tissue types is the key to unlocking the genetic complexity of osteoarthritis. The use of single-cell technologies in osteoarthritis research is still in its infancy. However, such tools offer great promise in improving our functional interpretation of osteoarthritis GWAS and the identification of druggable targets. Large-scale collaborative efforts will be imperative to understand tissue and cell-type specific molecular mechanisms underlying enhancer function in disease.

Epigenetic mechanisms of osteoarthritis risk in human skeletal development

The epigenome, including the methylation of cytosine bases at CG dinucleotides, is intrinsically linked to transcriptional regulation. The tight regulation of gene expression during skeletal development is essential, with ~1/500 individuals born with skeletal abnormalities. Furthermore, increasing evidence is emerging to link age-associated complex genetic musculoskeletal diseases, including osteoarthritis (OA), to developmental factors including joint shape. Multiple studies have shown a functional role for DNA methylation in the genetic mechanisms of OA risk using articular cartilage samples taken from aged patients. Despite this, our knowledge of temporal changes to the methylome during human cartilage development has been limited. We quantified DNA methylation at ~700,000 individual CpGs across the epigenome of developing human articular cartilage in 72 samples ranging from 7-21 post-conception weeks, a time period that includes cavitation of the developing knee joint. We identified significant changes in 8% of all CpGs, and >9400 developmental differentially methylated regions (dDMRs). The largest hypermethylated dDMRs mapped to transcriptional regulators of early skeletal patterning including MEIS1 and IRX1. Conversely, the largest hypomethylated dDMRs mapped to genes encoding extracellular matrix proteins including SPON2 and TNXB and were enriched in chondrocyte enhancers. Significant correlations were identified between the expression of these genes and methylation within the hypomethylated dDMRs. We further identified 811 CpGs at which significant dimorphism was present between the male and female samples, with the majority (68%) being hypermethylated in female samples. Following imputation, we captured the genotype of these samples at >5 million variants and performed epigenome-wide methylation quantitative trait locus (mQTL) analysis. Colocalization analysis identified 26 loci at which genetic variants exhibited shared impacts upon methylation and OA genetic risk. This included loci which have been previously reported to harbour OA-mQTLs (including GDF5 and ALDH1A2), yet the majority (73%) were novel (including those mapping to CHST3, FGF1 and TEAD1). To our knowledge, this is the first extensive study of DNA methylation across human articular cartilage development. We identify considerable methylomic plasticity within the development of knee cartilage and report active epigenomic mediators of OA risk operating in prenatal joint tissues.

Specific isoforms of the ubiquitin ligase gene WWP2 are targets of osteoarthritis genetic risk via a differentially methylated DNA sequence

BACKGROUND

Transitioning from a genetic association signal to an effector gene and a targetable molecular mechanism requires the application of functional fine-mapping tools such as reporter assays and genome editing. In this report, we undertook such studies on the osteoarthritis (OA) risk that is marked by single nucleotide polymorphism (SNP) rs34195470 (A > G). The OA risk-conferring G allele of this SNP associates with increased DNA methylation (DNAm) at two CpG dinucleotides within WWP2. This gene encodes a ubiquitin ligase and is the host gene of microRNA-140 (miR-140). WWP2 and miR-140 are both regulators of TGFβ signaling.

METHODS

Nucleic acids were extracted from adult OA (arthroplasty) and foetal cartilage. Samples were genotyped and DNAm quantified by pyrosequencing at the two CpGs plus 14 flanking CpGs. CpGs were tested for transcriptional regulatory effects using a chondrocyte cell line and reporter gene assay. DNAm was altered using epigenetic editing, with the impact on gene expression determined using RT-qPCR. In silico analysis complemented laboratory experiments.

RESULTS

rs34195470 genotype associates with differential methylation at 14 of the 16 CpGs in OA cartilage, forming a methylation quantitative trait locus (mQTL). The mQTL is less pronounced in foetal cartilage (5/16 CpGs). The reporter assay revealed that the CpGs reside within a transcriptional regulator. Epigenetic editing to increase their DNAm resulted in altered expression of the full-length and N-terminal transcript isoforms of WWP2. No changes in expression were observed for the C-terminal isoform of WWP2 or for miR-140.

CONCLUSIONS

As far as we are aware, this is the first experimental demonstration of an OA association signal targeting specific transcript isoforms of a gene. The WWP2 isoforms encode proteins with varying substrate specificities for the components of the TGFβ signaling pathway. Future analysis should focus on the substrates regulated by the two WWP2 isoforms that are the targets of this genetic risk.

Endothelial gene regulatory elements associated with cardiopharyngeal lineage differentiation

Endothelial cells (EC) differentiate from multiple sources, including the cardiopharyngeal mesoderm, which gives rise also to cardiac and branchiomeric muscles. The enhancers activated during endothelial differentiation within the cardiopharyngeal mesoderm are not completely known. Here, we use a cardiogenic mesoderm differentiation model that activates an endothelial transcription program to identify endothelial regulatory elements activated in early cardiogenic mesoderm. Integrating chromatin remodeling and gene expression data with available single-cell RNA-seq data from mouse embryos, we identify 101 putative regulatory elements of EC genes. We then apply a machine-learning strategy, trained on validated enhancers, to predict enhancers. Using this computational assay, we determine that 50% of these sequences are likely enhancers, some of which are already reported. We also identify a smaller set of regulatory elements of well-known EC genes and validate them using genetic and epigenetic perturbation. Finally, we integrate multiple data sources and computational tools to search for transcriptional factor binding motifs. In conclusion, we show EC regulatory sequences with a high likelihood to be enhancers, and we validate a subset of them using computational and cell culture models. Motif analyses show that the core EC transcription factors GATA/ETS/FOS is a likely driver of EC regulation in cardiopharyngeal mesoderm.

Proteome and phospholipidome interrelationship of synovial fluid-derived extracellular vesicles in equine osteoarthritis: An exploratory 'multi-omics' study to identify composite biomarkers

Osteoarthritis causes progressive joint deterioration, severe morbidity, and reduced mobility in both humans and horses. Currently, osteoarthritis is diagnosed at late stages through clinical examination and radiographic imaging, hence it is challenging to address and provide timely therapeutic interventions to slow disease progression or ameliorate symptoms. Extracellular vesicles are cell-derived vesicles that play a key role in cell-to-cell communication and are potential sources for specific composite biomarker panel discovery. We here used a multi-omics strategy combining proteomics and phospholipidomics in an integral approach to identify composite biomarkers associated to purified extracellular vesicles from synovial fluid of healthy, mildly and severely osteoarthritic equine joints. Although the number of extracellular vesicles was unaffected by osteoarthritis, proteome profiling of extracellular vesicles by mass spectrometry identified 40 differentially expressed proteins (non-adjusted p < 0.05) in osteoarthritic joints associated with 7 significant canonical pathways in osteoarthritis. Moreover, pathway analysis unveiled changes in disease and molecular functions during osteoarthritis development. Phospholipidome profiling by mass spectrometry showed a relative increase in sphingomyelin and a decrease in phosphatidylcholine, phosphatidylinositol, and phosphatidylserine in extracellular vesicles derived from osteoarthritic joints compared to healthy joints. Unsupervised data integration revealed positive correlations between the proteome and the phospholipidome. Comprehensive analysis showed that some phospholipids and their related proteins increased as the severity of osteoarthritis progressed, while others decreased or remained stable. Altogether our data show interrelationships between synovial fluid extracellular vesicle-associated phospholipids and proteins responding to osteoarthritis pathology and which could be explored as potential composite diagnostic biomarkers of disease.

Pan-cancer analysis revealing the multidimensional expression and prognostic and immunologic roles of TGFB1 in cancer

OBJECTIVE

This study aimed to perform an integrated pan-cancer analysis to characterize the expression patterns, prognostic value, genetic alterations, and immunologic roles of transforming growth factor beta 1 (TGFB1) across diverse human cancer types.

METHODS

Bioinformatics analyses were conducted using multiple public databases including The Cancer Genome Atlas, Genotype-Tissue Expression, Clinical Proteomic Tumor Analysis Consortium, TIMER2, GEPIA2, cBioPortal, StringDB, and others. Differential expression, survival, immune correlation, and protein interaction network analyses were performed.

RESULTS

TGFB1 was overexpressed in several tumor types compared with that in normal tissues. High TGFB1 expression was associated with an advanced stage and poorer prognosis in certain cancers. TGFB1 mutations occurred in 1.3% of 10,967 cases surveyed. TGFB1 expression correlated with tumor-infiltrating immune cells and immunotherapy-related genes.

CONCLUSIONS

This comprehensive multi-omics analysis revealed the complex expression and prognostic landscape of TGFB1 across cancers. TGFB1 is emerging as a potential immunotherapeutic target in certain contexts. Further research should elucidate its multifaceted tumor-promoting and tumor-suppressive mechanisms. Our pan-cancer analysis provides new insights into TGFB1 as a prognostic biomarker and immunotherapeutic target in human cancers, and our findings may guide future preclinical and clinical investigations of TGFB1-directed therapies.

Role of epigenetics and the transcription factor Sp1 in the expression of the D prostanoid receptor 1 in human cartilage

D prostanoid receptor 1 (DP1), a prostaglandin D2 receptor, plays a central role in the modulation of inflammation and cartilage metabolism. We have previously shown that activation of DP1 signaling downregulated catabolic responses in cultured chondrocytes and was protective in mouse osteoarthritis (OA). However, the mechanisms underlying its transcriptional regulation in cartilage remained poorly understood. In the present study, we aimed to characterize the human DP1 promoter and the role of DNA methylation in DP1 expression in chondrocytes. In addition, we analyzed the expression level and methylation status of the DP1 gene promoter in normal and OA cartilage. Deletion and site-directed mutagenesis analyses identified a minimal promoter region (-250/-120) containing three binding sites for specificity protein 1 (Sp1). Binding of Sp1 to the DP1 promoter was confirmed using electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation (ChIP) assays. Treatment with the Sp1 inhibitor mithramycin A reduced DP1 promoter activity and DP1 mRNA expression. Inhibition of DNA methylation by 5-Aza-2'-deoxycytidine upregulated DP1 expression, and in vitro methylation reduced the DP1 promoter activity. Neither the methylation status of the DP1 promoter nor the DP1 expression level were different between normal and OA cartilage. In conclusion, our results suggest that the transcription factor Sp1 and DNA methylation are important determinants of DP1 transcription regulation. They also suggest that the methylation status and expression level of DP1 are not altered in OA cartilage. These findings will improve our understanding of the regulatory mechanisms of DP1 transcription and may facilitate the development of intervention strategies involving DP1.

Mediation of the Same Epigenetic and Transcriptional Effect by Independent Osteoarthritis Risk-Conferring Alleles on a Shared Target Gene, COLGALT2

OBJECTIVE

Over 100 DNA variants have been associated with osteoarthritis (OA), including rs1046934, located within a linkage disequilibrium block encompassing part of COLGALT2 and TSEN15. The present study was undertaken to determine the target gene(s) and the mechanism of action of the OA locus using human fetal cartilage, cartilage from OA and femoral neck fracture arthroplasty patients, and a chondrocyte cell model.

METHODS

Genotyping and methylation array data of DNA from human OA cartilage samples (n = 87) were used to determine whether the rs1046934 genotype is associated with differential DNA methylation at proximal CpGs. Results were replicated in DNA from human arthroplasty (n = 132) and fetal (n = 77) cartilage samples using pyrosequencing. Allelic expression imbalance (AEI) measured the effects of genotype on COLGALT2 and TSEN15 expression. Reporter gene assays and epigenetic editing determined the functional role of regions harboring differentially methylated CpGs. In silico analyses complemented these experiments.

RESULTS

Three differentially methylated CpGs residing within regulatory regions were detected in the human OA cartilage array data, and 2 of these were replicated in human arthroplasty and fetal cartilage. AEI was detected for COLGALT2 and TSEN15, with associations between expression and methylation for COLGALT2. Reporter gene assays confirmed that the CpGs are in chondrocyte enhancers, with epigenetic editing results directly linking methylation with COLGALT2 expression.

CONCLUSION

COLGALT2 is a target of this OA locus. We previously characterized another OA locus, marked by rs11583641, that independently targets COLGALT2. The genotype of rs1046934, like rs11583641, mediates its effect by modulating expression of COLGALT2 via methylation changes to CpGs located in enhancers. Although the single-nucleotide polymorphisms, CpGs, and enhancers are distinct between the 2 independent OA risk loci, their effect on COLGALT2 is the same. COLGALT2 is the target of independent OA risk loci sharing a common mechanism of action.

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.

Epigenetics as a mediator of genetic risk in osteoarthritis: role during development, homeostasis, aging, and disease progression

The identification of genomic loci that are associated with osteoarthritis (OA) has provided a starting point for understanding how genetic variation activates catabolic processes in the joint. However, genetic variants can only alter gene expression and cellular function when the epigenetic environment is permissive to these effects. In this review, we provide examples of how epigenetic shifts at distinct life stages can alter the risk for OA, which we posit is critical for the proper interpretation of genome-wide association studies (GWAS). During development, intensive work on the growth and differentiation factor 5 (GDF5) locus has revealed the importance of tissue-specific enhancer activity in controlling both joint development and the subsequent risk for OA. During homeostasis in adults, underlying genetic risk factors may help establish beneficial or catabolic "set points" that dictate tissue function, with a strong cumulative effect on OA risk. During aging, methylation changes and the reorganization of chromatin can "unmask" the effects of genetic variants. The destructive function of variants that alter aging would only mediate effects after reproductive competence and thus avoid any evolutionary selection pressure, as consistent with larger frameworks of biological aging and its relationship to disease. A similar "unmasking" may occur during OA progression, which is supported by the finding of distinct expression quantitative trait loci (eQTLs) in chondrocytes depending on the degree of tissue degradation. Finally, we propose that massively parallel reporter assays (MPRAs) will be a valuable tool to test the function of putative OA GWAS variants in chondrocytes from different life stages.

The clusterin connectome: Emerging players in chondrocyte biology and putative exploratory biomarkers of osteoarthritis

Introduction

Clusterin is amoonlighting protein that hasmany functions. It is amultifunctional Q6 holdase chaperone glycoprotein that is present intracellularly and extracellularly in almost all bodily fluids. Clusterin is involved in lipid transport, cell differentiation, regulation of apoptosis, and clearance of cellular debris, and plays a protective role in ensuring cellular survival. However, the possible involvement of clusterin in arthritic disease remains unclear. Given the significant potential of clusterin as a biomarker of osteoarthritis (OA), a more detailed analysis of its complex network in an inflammatory environment, specifically in the context of OA, is required. Based on the molecular network of clusterin, this study aimed to identify interacting partners that could be developed into biomarker panels for OA.

Methods

The STRING database and Cytoscape were used to map and visualize the clusterin connectome. The Qiagen Ingenuity Pathway Analysis (IPA) software was used to analyze and study clusterinassociated signaling networks in OA. We also analyzed transcription factors known to modulate clusterin expression, which may be altered in OA.

Results

The top hits in the clusterin network were intracellular chaperones, aggregate-forming proteins, apoptosis regulators and complement proteins. Using a text-mining approach in Cytoscape, we identified additional interacting partners, including serum proteins, apolipoproteins, and heat shock proteins.

Discussion

Based on known interactions with proteins, we predicted potential novel components of the clusterin connectome in OA, including selenoprotein R, semaphorins, and meprins, which may be important for designing new prognostic or diagnostic biomarker panels.

Epigenetics as a Therapeutic Target in Osteoarthritis

Osteoarthritis (OA) is a heterogenous, complex disease affecting the integrity of diarthrodial joints that, despite its high prevalence worldwide, lacks effective treatment. In recent years it has been discovered that epigenetics may play an important role in OA. Our objective is to review the current knowledge of the three classical epigenetic mechanisms-DNA methylation, histone post-translational modifications (PTMs), and non-coding RNA (ncRNA) modifications, including microRNAs (miRNAs), circular RNAs (circRNAs), and long non-coding RNAs (lncRNAs)-in relation to the pathogenesis of OA and focusing on articular cartilage. The search for updated literature was carried out in the PubMed database. Evidence shows that dysregulation of numerous essential cartilage molecules is caused by aberrant epigenetic regulatory mechanisms, and it contributes to the development and progression of OA. This offers the opportunity to consider new candidates as therapeutic targets with the potential to attenuate OA or to be used as novel biomarkers of the disease.

Identification of TMEM129, encoding a ubiquitin-protein ligase, as an effector gene of osteoarthritis genetic risk

BACKGROUND

Osteoarthritis is highly heritable and genome-wide studies have identified single nucleotide polymorphisms (SNPs) associated with the disease. One such locus is marked by SNP rs11732213 (T > C). Genotype at rs11732213 correlates with the methylation levels of nearby CpG dinucleotides (CpGs), forming a methylation quantitative trait locus (mQTL). This study investigated the regulatory activity of the CpGs to identify a target gene of the locus.

METHODS

Nucleic acids were extracted from the articular cartilage of osteoarthritis patients. Samples were genotyped, and DNA methylation was quantified by pyrosequencing at 14 CpGs within a 259-bp interval. CpGs were tested for enhancer effects in immortalised chondrocytes using a reporter gene assay. DNA methylation at the locus was altered using targeted epigenome editing, with the impact on gene expression determined using quantitative polymerase chain reaction.

RESULTS

rs11732213 genotype correlated with DNA methylation at nine CpGs, which formed a differentially methylated region (DMR), with the osteoarthritis risk allele T corresponding to reduced levels of methylation. The DMR acted as an enhancer and demethylation of the CpGs altered expression of TMEM129. Allelic imbalance in TMEM129 expression was identified in cartilage, with under-expression of the risk allele.

CONCLUSIONS

TMEM129 is a target of osteoarthritis genetic risk at this locus. Genotype at rs11732213 impacts DNA methylation at the enhancer, which, in turn, modulates TMEM129 expression. TMEM129 encodes an enzyme involved in protein degradation within the endoplasmic reticulum, a process previously implicated in osteoarthritis. TMEM129 is a compelling osteoarthritis susceptibility target.

Epigenetic Regulation in Knee Osteoarthritis

Osteoarthritis (OA) is a complicated disease with both hereditary and environmental causes. Despite an increase in reports of possible OA risk loci, it has become clear that genetics is not the sole cause of osteoarthritis. Epigenetics, which can be triggered by environmental influences and result in transcriptional alterations, may have a role in OA pathogenesis. The majority of recent research on the epigenetics of OA has been focused on DNA methylation, histone modification, and non-coding RNAs. However, this study will explore epigenetic regulation in OA at the present stage. How genetics, environmental variables, and epigenetics interact will be researched, shedding light for future studies. Their possible interaction and control processes open up new avenues for the development of innovative osteoarthritis treatment and diagnostic techniques.

Potential Methods of Targeting Cellular Aging Hallmarks to Reverse Osteoarthritic Phenotype of Chondrocytes

Osteoarthritis (OA) is a chronic degenerative joint disease that causes pain, physical disability, and life quality impairment. The pathophysiology of OA remains largely unclear, and currently no FDA-approved disease-modifying OA drugs (DMOADs) are available. As has been acknowledged, aging is the primary independent risk factor for OA, but the mechanisms underlying such a connection are not fully understood. In this review, we first revisit the changes in OA chondrocytes from the perspective of cellular hallmarks of aging. It is concluded that OA chondrocytes share many alterations similar to cellular aging. Next, based on the findings from studies on other cell types and diseases, we propose methods that can potentially reverse osteoarthritic phenotype of chondrocytes back to a healthier state. Lastly, current challenges and future perspectives are summarized.

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.

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.