Chromatin accessibility landscape of articular knee cartilage reveals aberrant enhancer regulation in osteoarthritis

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.

Identification of therapeutic targets in osteoarthritis by combining heterogeneous transcriptional datasets, drug-induced expression profiles, and known drug-target interactions

BACKGROUND

Osteoarthritis (OA) is a multifactorial, hypertrophic, and degenerative condition involving the whole joint and affecting a high percentage of middle-aged people. It is due to a combination of factors, although the pivotal mechanisms underlying the disease are still obscure. Moreover, current treatments are still poorly effective, and patients experience a painful and degenerative disease course.

METHODS

We used an integrative approach that led us to extract a consensus signature from a meta-analysis of three different OA cohorts. We performed a network-based drug prioritization to detect the most relevant drugs targeting these genes and validated in vitro the most promising candidates. We also proposed a risk score based on a minimal set of genes to predict the OA clinical stage from RNA-Seq data.

RESULTS

We derived a consensus signature of 44 genes that we validated on an independent dataset. Using network analysis, we identified Resveratrol, Tenoxicam, Benzbromarone, Pirinixic Acid, and Mesalazine as putative drugs of interest for therapeutics in OA for anti-inflammatory properties. We also derived a list of seven gene-targets validated with functional RT-qPCR assays, confirming the in silico predictions. Finally, we identified a predictive subset of genes composed of DNER, TNFSF11, THBS3, LOXL3, TSPAN2, DYSF, ASPN and HTRA1 to compute the patient's risk score. We validated this risk score on an independent dataset with a high AUC (0.875) and compared it with the same approach computed using the entire consensus signature (AUC 0.922).

CONCLUSIONS

The consensus signature highlights crucial mechanisms for disease progression. Moreover, these genes were associated with several candidate drugs that could represent potential innovative therapeutics. Furthermore, the patient's risk scores can be used in clinical settings.

Current Status of Next-Generation Sequencing in Bone Genetic Diseases

The development of next-generation sequencing (NGS) has dramatically increased the speed and volume of genetic analysis. Furthermore, the range of applications of NGS is rapidly expanding to include genome, epigenome (such as DNA methylation), metagenome, and transcriptome analyses (such as RNA sequencing and single-cell RNA sequencing). NGS enables genetic research by offering various sequencing methods as well as combinations of methods. Bone tissue is the most important unit supporting the body and is a reservoir of calcium and phosphate ions, which are important for physical activity. Many genetic diseases affect bone tissues, possibly because metabolic mechanisms in bone tissue are complex. For instance, the presence of specialized immune cells called osteoclasts in the bone tissue, which absorb bone tissue and interact with osteoblasts in complex ways to support normal vital functions. Moreover, the many cell types in bones exhibit cell-specific proteins for their respective activities. Mutations in the genes encoding these proteins cause a variety of genetic disorders. The relationship between age-related bone tissue fragility (also called frailty) and genetic factors has recently attracted attention. Herein, we discuss the use of genomic, epigenomic, transcriptomic, and metagenomic analyses in bone genetic disorders.

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.

Analysis of RNA Polyadenylation in Healthy and Osteoarthritic Human Articular Cartilage

Polyadenylation (polyA) defines the 3' boundary of a transcript's genetic information. Its position can vary and alternative polyadenylation (APA) transcripts can exist for a gene. This causes variance in 3' regulatory domains and can affect coding sequence if intronic events occur. The distribution of polyA sites on articular chondrocyte transcripts has not been studied so we aimed to define their transcriptome-wide location in age-matched healthy and osteoarthritic knee articular cartilage. Total RNA was isolated from frozen tissue samples and analysed using the QuantSeq-Reverse 3' RNA sequencing approach, where each read runs 3' to 5' from within the polyA tail into the transcript and contains a distinct polyA site. Differential expression of transcripts was significant altered between healthy and osteoarthritic samples with enrichment for functionalities that were strongly associated with joint pathology. Subsequent examination of polyA site data allowed us to define the extent of site usage across all the samples. When comparing healthy and osteoarthritic samples, we found that differential use of polyadenylation sites was modest. However, in the genes affected, there was potential for the APA to have functional relevance. We have characterised the polyadenylation landscape of human knee articular chondrocytes and conclude that osteoarthritis does not elicit a widespread change in their polyadenylation site usage. This finding differentiates knee osteoarthritis from pathologies such as cancer where APA is more commonly observed.

A Functional Polymorphism Downstream of Vitamin A Regulator Gene CYP26B1 Is Associated with Hand Osteoarthritis

While genetic analyses have revealed ~100 risk loci associated with osteoarthritis (OA), only eight have been linked to hand OA. Besides, these studies were performed in predominantly European and Caucasian ancestries. Here, we conducted a genome-wide association study in the Han Chinese population to identify genetic variations associated with the disease. We recruited a total of 1136 individuals (n = 420 hand OA-affected; n = 716 unaffected control subjects) of Han Chinese ancestry. We carried out genotyping using Axiom Asia Precisi on Medicine Research Array, and we employed the RegulomeDB database and RoadMap DNase I Hypersensitivity Sites annotations to further narrow down our potential candidate variants. Genetic variants identified were tested in the Geisinger's hand OA cohort selected from the Geisinger MyCode community health initiative (MyCode^®). We also performed a luciferase reporter assay to confirm the potential impact of top candidate single-nucleotide polymorphisms (SNPs) on hand OA. We identified six associated SNPs (p-value = 6.76 × 10^-7-7.31 × 10^-6) clustered at 2p13.2 downstream of the CYP26B1 gene. The strongest association signal identified was rs883313 (p-value = 6.76 × 10^-7, odds ratio (OR) = 1.76), followed by rs12713768 (p-value = 1.36 × 10^-6, OR = 1.74), near or within the enhancer region closest to the CYP26B1 gene. Our findings showed that the major risk-conferring CC haplotype of SNPs rs12713768 and rs10208040 [strong linkage disequilibrium (LD); D' = 1, r² = 0.651] drives 18.9% of enhancer expression activity. Our findings highlight that the SNP rs12713768 is associated with susceptibility to and severity of hand OA in the Han Chinese population and that the suggested retinoic acid signaling pathway may play an important role in its pathogenesis.

Insights from multi-omics integration in complex disease primary tissues

Genome-wide association studies (GWAS) have provided insights into the genetic basis of complex diseases. In the next step, integrative multi-omics approaches can characterize molecular profiles in relevant primary tissues to reveal the mechanisms that underlie disease development. Here, we highlight recent progress in four examples of complex diseases generated by integrative studies: type 2 diabetes (T2D), osteoarthritis, Alzheimer's disease (AD), and systemic lupus erythematosus (SLE). High-resolution methodologies such as single-cell and spatial omics techniques will become even more important in the future. Furthermore, we emphasize the urgent need to include as yet understudied cell types and increase the diversity of studied populations.

Assay for Transposase-Accessible Chromatin Using Sequencing of Freshly Isolated Muscle Stem Cells

Actively transcribed genes harbor cis-regulatory modules with comparatively low nucleosome occupancy and few high-order structures (="open chromatin"), whereas non-transcribed genes are characterized by high nucleosome density and extensive interactions between nucleosomes (="closed chromatin"), preventing transcription factor binding. Knowledge about chromatin accessibility is crucial to understand gene regulatory networks determining cellular decisions. Several techniques are available to map chromatin accessibility, among which the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) is one of the most popular. ATAC-seq is based on a straightforward and robust protocol but requires adjustments for different cell types. Here, we describe an optimized protocol for ATAC-seq of freshly isolated murine muscle stem cells. We provide details for the isolation of MuSC, tagmentation, library amplification, double-sided SPRI bead cleanup, and library quality assessment and give recommendations for sequencing parameters and downstream analysis. The protocol should facilitate generation of high-quality data sets of chromatin accessibility in MuSCs, even for newcomers to the field.

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.

Genetics of osteoarthritis

Osteoarthritis genetics has been transformed in the past decade through the application of large-scale genome-wide association scans. So far, over 100 polymorphic DNA variants have been associated with this common and complex disease. These genetic risk variants account for over 20% of osteoarthritis heritability and the vast majority map to non-protein coding regions of the genome where they are presumed to act by regulating the expression of target genes. Statistical fine mapping, in silico analyses of genomics data, and laboratory-based functional studies have enabled the identification of some of these targets, which encode proteins with diverse roles, including extracellular signaling molecules, intracellular enzymes, transcription factors, and cytoskeletal proteins. A large number of the risk variants correlate with epigenetic factors, in particular cartilage DNA methylation changes in cis, implying that epigenetics may be a conduit through which genetic effects on gene expression are mediated. Some of the variants also appear to have been selected as humans adapted to bipedalism, suggesting that a proportion of osteoarthritis genetic susceptibility results from antagonistic pleiotropy, with risk variants having a positive role in joint formation but a negative role in the long-term health of the joint. Although data from an osteoarthritis genetic study has not yet directly led to a novel treatment, some of the osteoarthritis associated genes code for proteins that have available therapeutics. Genetic investigations are therefore revealing fascinating fundamental insights into osteoarthritis and can expose options for translational intervention.

Chromatin accessibility profiling by ATAC-seq

The assay for transposase-accessible chromatin using sequencing (ATAC-seq) provides a simple and scalable way to detect the unique chromatin landscape associated with a cell type and how it may be altered by perturbation or disease. ATAC-seq requires a relatively small number of input cells and does not require a priori knowledge of the epigenetic marks or transcription factors governing the dynamics of the system. Here we describe an updated and optimized protocol for ATAC-seq, called Omni-ATAC, that is applicable across a broad range of cell and tissue types. The ATAC-seq workflow has five main steps: sample preparation, transposition, library preparation, sequencing and data analysis. This protocol details the steps to generate and sequence ATAC-seq libraries, with recommendations for sample preparation and downstream bioinformatic analysis. ATAC-seq libraries for roughly 12 samples can be generated in 10 h by someone familiar with basic molecular biology, and downstream sequencing analysis can be implemented using benchmarked pipelines by someone with basic bioinformatics skills and with access to a high-performance computing environment.

Transcriptomic and epigenomic analyses uncovered Lrrc15 as a contributing factor to cartilage damage in osteoarthritis

In osteoarthritis (OA), articular chondrocytes display phenotypic and functional changes associated with epigenomic alterations. These changes contribute to the disease progression, which is characterized by dysregulated reparative processes and abnormal extracellular matrix remodeling leading to cartilage degradation. Recent studies using a murine model of posttraumatic OA highlighted the contribution of changes in DNA hydroxymethylation (5hmC) to OA progression. Here, we integrated transcriptomic and epigenomic analyses in cartilage after induction of OA to show that the structural progression of OA is accompanied by early transcriptomic and pronounced DNA methylation (5mC) changes in chondrocytes. These changes accumulate over time and are associated with recapitulation of developmental processes, including cartilage development, chondrocyte hypertrophy, and ossification. Our integrative analyses also uncovered that Lrrc15 is differentially methylated and expressed in OA cartilage, and that it may contribute to the functional and phenotypic alterations of chondrocytes, likely coordinating stress responses and dysregulated extracellular matrix remodeling.

Joint disease-specificity at the regulatory base-pair level

Given the pleiotropic nature of coding sequences and that many loci exhibit multiple disease associations, it is within non-coding sequence that disease-specificity likely exists. Here, we focus on joint disorders, finding among replicated loci, that GDF5 exhibits over twenty distinct associations, and we identify causal variants for two of its strongest associations, hip dysplasia and knee osteoarthritis. By mapping regulatory regions in joint chondrocytes, we pinpoint two variants (rs4911178; rs6060369), on the same risk haplotype, which reside in anatomical site-specific enhancers. We show that both variants have clinical relevance, impacting disease by altering morphology. By modeling each variant in humanized mice, we observe joint-specific response, correlating with GDF5 expression. Thus, we uncouple separate regulatory variants on a common risk haplotype that cause joint-specific disease. By broadening our perspective, we finally find that patterns of modularity at GDF5 are also found at over three-quarters of loci with multiple GWAS disease associations.

The landscape of chromatin accessibility in skeletal muscle during embryonic development in pigs

BACKGROUND

The development of skeletal muscle in pigs during the embryonic stage is precisely regulated by transcriptional mechanisms, which depend on chromatin accessibility. However, how chromatin accessibility plays a regulatory role during embryonic skeletal muscle development in pigs has not been reported. To gain insight into the landscape of chromatin accessibility and the associated genome-wide transcriptome during embryonic muscle development, we performed ATAC-seq and RNA-seq analyses of skeletal muscle from pig embryos at 45, 70 and 100 days post coitus (dpc).

RESULTS

In total, 21,638, 35,447 and 60,181 unique regions (or peaks) were found across the embryos at 45 dpc (LW45), 70 dpc (LW70) and 100 dpc (LW100), respectively. More than 91% of the peaks were annotated within - 1 kb to 100 bp of transcription start sites (TSSs). First, widespread increases in specific accessible chromatin regions (ACRs) from embryos at 45 to 100 dpc suggested that the regulatory mechanisms became increasingly complicated during embryonic development. Second, the findings from integrated ATAC-seq and RNA-seq analyses showed that not only the numbers but also the intensities of ACRs could control the expression of associated genes. Moreover, the motif screening of stage-specific ACRs revealed some transcription factors that regulate muscle development-related genes, such as MyoG, Mef2c, and Mef2d. Several potential transcriptional repressors, including E2F6, OTX2 and CTCF, were identified among the genes that exhibited different regulation trends between the ATAC-seq and RNA-seq data.

CONCLUSIONS

This work indicates that chromatin accessibility plays an important regulatory role in the embryonic muscle development of pigs and regulates the temporal and spatial expression patterns of key genes in muscle development by influencing the binding of transcription factors. Our results contribute to a better understanding of the regulatory dynamics of genes involved in pig embryonic skeletal muscle development.

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.

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

OBJECTIVE

Osteoarthritis (OA) is an age-related disease characterized by articular cartilage degeneration. It is largely heritable, and genetic screening has identified single-nucleotide polymorphisms (SNPs) marking genomic risk loci. One such locus is marked by the G>A SNP rs75621460, downstream of TGFB1. This gene encodes transforming growth factor β1, the correct expression of which is essential for cartilage maintenance. This study investigated the regulatory activity of rs75621460 to characterize its impact on TGFB1 expression in disease-relevant patient samples (n = 319) and in Tc28a2 immortalized chondrocytes.

METHODS

Articular cartilage samples from human patients were genotyped, and DNA methylation levels were quantified using pyrosequencing. Gene reporter and electrophoretic mobility shift assays were used to determine differential nuclear protein binding to the region. The functional impact of DNA methylation on TGFB1 expression was tested using targeted epigenome editing.

RESULTS

The analyses showed that SNP rs75621460 was located within a TGFB1 enhancer region, and the OA risk allele A altered transcription factor binding, with decreased enhancer activity. Protein complexes binding to A (but not G) induced DNA methylation at flanking CG dinucleotides. Strong correlations between patient DNA methylation levels and TGFB1 expression were observed, with directly opposing effects in the cartilage and the synovium at this locus. This demonstrated biologic pleiotropy in the impact of the SNP within different tissues of the articulating joint.

CONCLUSION

The OA risk SNP rs75621460 impacts TGFB1 expression by modulating the function of a gene enhancer. We propose a mechanism by which the SNP impacts enhancer function, providing novel biologic insight into one mechanism of OA genetic risk, which may facilitate the development of future pharmacologic therapies.

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.

Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles

The exploration of three-dimensional chromatin interaction and organization provides insight into mechanisms underlying gene regulation, cell differentiation and disease development. Advances in chromosome conformation capture technologies, such as high-throughput chromosome conformation capture (Hi-C) and chromatin interaction analysis by paired-end tag (ChIA-PET), have enabled the exploration of chromatin interaction and organization. However, high-resolution Hi-C and ChIA-PET data are only available for a limited number of cell lines, and their acquisition is costly, time consuming, laborious and affected by theoretical limitations. Increasing evidence shows that DNA sequence and epigenomic features are informative predictors of regulatory interaction and chromatin architecture. Based on these features, numerous computational methods have been developed for the prediction of chromatin interaction and organization, whereas they are not extensively applied in biomedical study. A systematical study to summarize and evaluate such methods is still needed to facilitate their application. Here, we summarize 48 computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles, categorize them and compare their performance. Besides, we provide a comprehensive guideline for the selection of suitable methods to predict chromatin interaction and organization based on available data and biological question of interest.

Changes in DNA methylation accompany changes in gene expression during chondrocyte hypertrophic differentiation in vitro

During osteoarthritis (OA), articular chondrocytes undergo phenotypic changes that resemble developmental patterns characteristic of growth plate chondrocytes. These phenotypic alterations lead to a hypertrophy-like phenotype characterized by altered production of extracellular matrix constituents and increased collagenase activity, which, in turn, results in cartilage destruction in OA disease. Recent studies have shown that the phenotypic instability and dysregulated gene expression in OA are associated with changes in DNA methylation patterns. Subsequent efforts have aimed to identify changes in DNA methylation with functional impact in OA disease, to potentially uncover therapeutic targets. Here, we paired an in vitro 3D/pellet culture system that mimics chondrocyte hypertrophy with RNA sequencing (RNA-Seq) and enhanced reduced representation of bisulfite sequencing (ERRBS) to identify transcriptomic and epigenomic changes in murine primary articular chondrocytes undergoing hypertrophy-like differentiation. We identified hypertrophy-associated changes in DNA methylation patterns in vitro. Integration of RNA-Seq and ERRBS datasets identified associations between changes in methylation and gene expression. Our integrative analyses showed that hypertrophic differentiation of articular chondrocytes is accompanied by transcriptomic and epigenomic changes in vitro. We believe that our integrative approaches have the potential to uncover new targets for therapeutic intervention.

Universal NicE-seq for high-resolution accessible chromatin profiling for formaldehyde-fixed and FFPE tissues

Accessible chromatin plays a central role in gene expression and chromatin architecture. Current accessible chromatin approaches depend on limited digestion/cutting and pasting adaptors at the accessible DNA, thus requiring additional materials and time for optimization. Universal NicE-seq (UniNicE-seq) is an improved accessible chromatin profiling method that negates the optimization step and is suited to a variety of mammalian cells and tissues. Addition of 5-methyldeoxycytidine triphosphate during accessible chromatin labeling and an on-bead library making step substantially improved the signal to noise ratio while protecting the accessible regions from repeated nicking in cell lines, mouse T cells, mouse kidney, and human frozen tissue sections. We also demonstrate one tube UniNicE-seq for the FFPE tissue section for direct NGS library preparation without sonication and DNA purification steps. These refinements allowed reliable mapping of accessible chromatin for high-resolution genomic feature studies.

Transcription Factors in Cartilage Homeostasis and Osteoarthritis

Osteoarthritis (OA) is the most common degenerative joint disease, and it is characterized by articular cartilage loss. In part, OA is caused by aberrant anabolic and catabolic activities of the chondrocyte, the only cell type present in cartilage. These chondrocyte activities depend on the intra- and extracellular signals that the cell receives and integrates into gene expression. The key proteins for this integration are transcription factors. A large number of transcription factors exist, and a better understanding of the transcription factors activated by the various signaling pathways active during OA can help us to better understand the complex etiology of OA. In addition, establishing such a profile can help to stratify patients in different subtypes, which can be a very useful approach towards personalized therapy. In this review, we discuss crucial transcription factors for extracellular matrix metabolism, chondrocyte hypertrophy, chondrocyte senescence, and autophagy in chondrocytes. In addition, we discuss how insight into these factors can be used for treatment purposes.

Knee Osteoarthritis: A Review of Pathogenesis and State-Of-The-Art Non-Operative Therapeutic Considerations

Being the most common musculoskeletal progressive condition, osteoarthritis is an interesting target for research. It is estimated that the prevalence of knee osteoarthritis (OA) among adults 60 years of age or older is approximately 10% in men and 13% in women, making knee OA one of the leading causes of disability in elderly population. Today, we know that osteoarthritis is not a disease characterized by loss of cartilage due to mechanical loading only, but a condition that affects all of the tissues in the joint, causing detectable changes in tissue architecture, its metabolism and function. All of these changes are mediated by a complex and not yet fully researched interplay of proinflammatory and anti-inflammatory cytokines, chemokines, growth factors and adipokines, all of which can be measured in the serum, synovium and histological samples, potentially serving as biomarkers of disease stage and progression. Another key aspect of disease progression is the epigenome that regulates all the genetic expression through DNA methylation, histone modifications, and mRNA interference. A lot of work has been put into developing non-surgical treatment options to slow down the natural course of osteoarthritis to postpone, or maybe even replace extensive surgeries such as total knee arthroplasty. At the moment, biological treatments such as platelet-rich plasma, bone marrow mesenchymal stem cells and autologous microfragmented adipose tissue containing stromal vascular fraction are ordinarily used. Furthermore, the latter two mentioned cell-based treatment options seem to be the only methods so far that increase the quality of cartilage in osteoarthritis patients. Yet, in the future, gene therapy could potentially become an option for orthopedic patients. In the following review, we summarized all of the latest and most important research in basic sciences, pathogenesis, and non-operative treatment.

Knee Osteoarthritis: A Review of Pathogenesis and State-Of-The-Art Non-Operative Therapeutic Considerations

Being the most common musculoskeletal progressive condition, osteoarthritis is an interesting target for research. It is estimated that the prevalence of knee osteoarthritis (OA) among adults 60 years of age or older is approximately 10% in men and 13% in women, making knee OA one of the leading causes of disability in elderly population. Today, we know that osteoarthritis is not a disease characterized by loss of cartilage due to mechanical loading only, but a condition that affects all of the tissues in the joint, causing detectable changes in tissue architecture, its metabolism and function. All of these changes are mediated by a complex and not yet fully researched interplay of proinflammatory and anti-inflammatory cytokines, chemokines, growth factors and adipokines, all of which can be measured in the serum, synovium and histological samples, potentially serving as biomarkers of disease stage and progression. Another key aspect of disease progression is the epigenome that regulates all the genetic expression through DNA methylation, histone modifications, and mRNA interference. A lot of work has been put into developing non-surgical treatment options to slow down the natural course of osteoarthritis to postpone, or maybe even replace extensive surgeries such as total knee arthroplasty. At the moment, biological treatments such as platelet-rich plasma, bone marrow mesenchymal stem cells and autologous microfragmented adipose tissue containing stromal vascular fraction are ordinarily used. Furthermore, the latter two mentioned cell-based treatment options seem to be the only methods so far that increase the quality of cartilage in osteoarthritis patients. Yet, in the future, gene therapy could potentially become an option for orthopedic patients. In the following review, we summarized all of the latest and most important research in basic sciences, pathogenesis, and non-operative treatment.

Comparison of differential accessibility analysis strategies for ATAC-seq data

ATAC-seq is widely used to measure chromatin accessibility and identify open chromatin regions (OCRs). OCRs usually indicate active regulatory elements in the genome and are directly associated with the gene regulatory network. The identification of differential accessibility regions (DARs) between different biological conditions is critical in determining the differential activity of regulatory elements. Differential analysis of ATAC-seq shares many similarities with differential expression analysis of RNA-seq data. However, the distribution of ATAC-seq signal intensity is different from that of RNA-seq data, and higher sensitivity is required for DARs identification. Many different tools can be used to perform differential analysis of ATAC-seq data, but a comprehensive comparison and benchmarking of these methods is still lacking. Here, we used simulated datasets to systematically measure the sensitivity and specificity of six different methods. We further discussed the statistical and signal density cut-offs in the differential analysis of ATAC-seq by applying them to real data. Batch effects are very common in high-throughput sequencing experiments. We illustrated that batch-effect correction can dramatically improve sensitivity in the differential analysis of ATAC-seq data. Finally, we developed a user-friendly package, BeCorrect, to perform batch effect correction and visualization of corrected ATAC-seq signals in a genome browser.

Patient-specific multi-omics models and the application in personalized combination therapy

The rapid advancement of high-throughput technologies and sharp decrease in cost have opened up the possibility to generate large amount of multi-omics data on an individual basis. The development of high-throughput -omics, including genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiomics, enables the application of multi-omics technologies in the clinical settings. Combination therapy, defined as disease treatment with two or more drugs to achieve efficacy with lower doses or lower drug toxicity, is the basis for the care of diseases like cancer. Patient-specific multi-omics data integration can help the identification and development of combination therapies. In this review, we provide an overview of different -omics platforms, and discuss the methods for multi-omics, high-throughput, data integration, personalized combination therapy.

Inhibition of TET1 prevents the development of osteoarthritis and reveals the 5hmC landscape that orchestrates pathogenesis

Osteoarthritis (OA) is a degenerative disease of the joint, which results in pain, loss of mobility, and, eventually, joint replacement. Currently, no disease-modifying drugs exist, partly because of the multiple levels at which cartilage homeostasis is disrupted. Recent studies have highlighted the importance of epigenetic dysregulation in OA, sparking interest in the epigenetic modulation for this disease. In our previous work, we characterized a fivefold increase in cytosine hydroxymethylation (5hmC), an oxidized derivative of cytosine methylation (5mC) associated with gene activation, accumulating at OA-associated genes. To test the role of 5hmC in OA, here, we used a mouse model of surgically induced OA and found that OA onset was accompanied by a gain of ~40,000 differentially hydroxymethylated sites before the notable histological appearance of disease. We demonstrated that ten-eleven-translocation enzyme 1 (TET1) mediates the 5hmC deposition because 98% of sites enriched for 5hmC in OA were lost in Tet1−/− mice. Loss of TET1-mediated 5hmC protected the Tet1−/− mice from OA development, including degeneration of the cartilage surface and osteophyte formation, by directly preventing the activation of multiple OA pathways. Loss of TET1 in human OA chondrocytes reduced the expression of the matrix metalloproteinases MMP3 and MMP13 and multiple inflammatory cytokines. Intra-articular injections of a dioxygenases inhibitor, 2-hydroxyglutarate, on mice after surgical induction of OA stalled disease progression. Treatment of human OA chondrocytes with the same inhibitor also phenocopied TET1 loss. Collectively, these data demonstrate that TET1-mediated 5hmC deposition regulates multiple OA pathways and can be modulated for therapeutic intervention.

Interplay between genetics and epigenetics in osteoarthritis

Research into the molecular genetics of osteoarthritis (OA) has been substantially bolstered in the past few years by the implementation of powerful genome-wide scans that have revealed a large number of novel risk loci associated with the disease. This refreshing wave of discovery has occurred concurrently with epigenetic studies of joint tissues that have examined DNA methylation, histone modifications and regulatory RNAs. These epigenetic analyses have involved investigations of joint development, homeostasis and disease and have used both human samples and animal models. What has become apparent from a comparison of these two complementary approaches is that many OA genetic risk signals interact with, map to or correlate with epigenetic mediators. This discovery implies that epigenetic mechanisms, and their effect on gene expression, are a major conduit through which OA genetic risk polymorphisms exert their functional effects. This observation is particularly exciting as it provides mechanistic insight into OA susceptibility. Furthermore, this knowledge reveals avenues for attenuating the negative effect of risk-conferring alleles by exposing the epigenome as an exploitable target for therapeutic intervention in OA.

Osteoarthritis year in review 2019: genetics, genomics and epigenetics

Although osteoarthritis (OA) aetiology is complex, genetic, genomic and epigenetic studies published within the last decade have advanced our understanding of the molecular processes underlying this common musculoskeletal disease. The purpose of this narrative review is to highlight the key research articles within the OA genetics, genomics and epigenetics fields that were published between April 2018 and April 2019. The review focuses on the identification of new OA genetic risk loci, genomics techniques that have been used for the first time in human cartilage and new publicly available databases, and datasets that will aid OA functional studies. Fifty-six new OA susceptibility loci were identified by two large scale genome wide association study meta-analyses, increasing the number of genome-wide significant risk loci to 90. OA risk variants are enriched near genes involved in skeletal development and morphology, and show genetic overlap with height, hip shape, bone area and developmental dysplasia of the hip. Several functional studies of OA loci were published, including a genome-wide analysis of genetic variation on cartilage gene expression. A specialised data portal for exploring cross-species skeletal transcriptomic datasets has been developed, and the first use of cartilage single cell RNAseq analysis reported. This year also saw the systematic identification of all microRNAs, long non-coding RNAs and circular RNAs expressed in human OA cartilage. Putative transcriptional regulatory regions have been mapped in human chondrocytes genome-wide, providing a dataset that will facilitate the prioritisation and characterisation of OA genetic and epigenetic loci.

Histone ChIP-Seq identifies differential enhancer usage during chondrogenesis as critical for defining cell-type specificity

Epigenetic mechanisms are known to regulate gene expression during chondrogenesis. In this study, we have characterized the epigenome during the in vitro differentiation of human mesenchymal stem cells (hMSCs) into chondrocytes. Chromatin immunoprecipitation followed by next‐generation sequencing (ChIP‐seq) was used to assess a range of N‐terminal posttranscriptional modifications (marks) to histone H3 lysines (H3K4me3, H3K4me1, H3K27ac, H3K27me3, and H3K36me3) in both hMSCs and differentiated chondrocytes. Chromatin states were characterized using histone ChIP‐seq and cis‐regulatory elements were identified in chondrocytes. Chondrocyte enhancers were associated with chondrogenesis‐related gene ontology (GO) terms. In silico analysis and integration of DNA methylation data with chondrogenesis chromatin states revealed that enhancers marked by histone marks H3K4me1 and H3K27ac were de‐methylated during in vitro chondrogenesis. Similarity analysis between hMSC and chondrocyte chromatin states defined in this study with epigenomes of cell‐types defined by the Roadmap Epigenomics project revealed that enhancers are more distinct between cell‐types compared to other chromatin states. Motif analysis revealed that the transcription factor SOX9 is enriched in chondrocyte enhancers. Luciferase reporter assays confirmed that chondrocyte enhancers characterized in this study exhibited enhancer activity which may be modulated by DNA methylation and SOX9 overexpression. Altogether, these integrated data illustrate the cross‐talk between different epigenetic mechanisms during chondrocyte differentiation.

DNA hypomethylation during MSC chondrogenesis occurs predominantly at enhancer regions

Regulation of transcription occurs in a cell type specific manner orchestrated by epigenetic mechanisms including DNA methylation. Methylation changes may also play a key role in lineage specification during stem cell differentiation. To further our understanding of epigenetic regulation in chondrocytes we characterised the DNA methylation changes during chondrogenesis of mesenchymal stem cells (MSCs) by Infinium 450 K methylation array. Significant DNA hypomethylation was identified during chondrogenic differentiation including changes at many key cartilage gene loci. Integration with chondrogenesis gene expression data revealed an enrichment of significant CpGs in upregulated genes, while characterisation of significant CpG loci indicated their predominant localisation to enhancer regions. Comparison with methylation profiles of other tissues, including healthy and diseased adult cartilage, identified chondrocyte-specific regions of hypomethylation and the overlap with differentially methylated CpGs in osteoarthritis. Taken together we have associated DNA methylation levels with the chondrocyte phenotype. The consequences of which has potential to improve cartilage generation for tissue engineering purposes and also to provide context for observed methylation changes in cartilage diseases such as osteoarthritis.

Insights into Gene Regulatory Networks in Chondrocytes

Chondrogenesis is a key developmental process that molds the framework of our body and generates the skeletal tissues by coupling with osteogenesis. The developmental processes are well-coordinated by spatiotemporal gene expressions, which are hardwired with gene regulatory elements. Those elements exist as thousands of modules of DNA sequences on the genome. Transcription factors function as key regulatory proteins by binding to regulatory elements and recruiting cofactors. Over the past 30 years, extensive attempts have been made to identify gene regulatory mechanisms in chondrogenesis, mainly through biochemical approaches and genetics. More recently, newly developed next-generation sequencers (NGS) have identified thousands of gene regulatory elements on a genome scale, and provided novel insights into the multiple layers of gene regulatory mechanisms, including the modes of actions of transcription factors, post-translational histone modifications, chromatin accessibility, the concept of pioneer factors, and three-dimensional chromatin architecture. In this review, we summarize the studies that have improved our understanding of the gene regulatory mechanisms in chondrogenesis, from the historical studies to the more recent works using NGS. Finally, we consider the future perspectives, including efforts to improve our understanding of the gene regulatory landscape in chondrogenesis and potential applications to the treatment of chondrocyte-related diseases.

Functional testing of thousands of osteoarthritis-associated variants for regulatory activity

To date, genome-wide association studies have implicated at least 35 loci in osteoarthritis but, due to linkage disequilibrium, the specific variants underlying these associations and the mechanisms by which they contribute to disease risk have yet to be pinpointed. Here, we functionally test 1,605 single nucleotide variants associated with osteoarthritis for regulatory activity using a massively parallel reporter assay. We identify six single nucleotide polymorphisms (SNPs) with differential regulatory activity between the major and minor alleles. We show that the most significant SNP, rs4730222, exhibits differential nuclear protein binding in electrophoretic mobility shift assays and drives increased expression of an alternative isoform of HBP1 in a heterozygote chondrosarcoma cell line, in a CRISPR-edited osteosarcoma cell line, and in chondrocytes derived from osteoarthritis patients. This study provides a framework for prioritization of GWAS variants and highlights a role of HBP1 and Wnt signaling in osteoarthritis pathogenesis.

Bevacizumab tested for treatment of knee osteoarthritis via inhibition of synovial vascular hyperplasia in rabbits

Background/objective

Osteoarthritis (OA) is the most common joint disorder. Angiogenesis and synovial hyperplasia are important factors in the development of OA. Previous studies demonstrated that bevacizumab, an antibody against vascular endothelial growth factor in angiogenesis for cancer treatment, might be a potential candidate for the treatment of OA. However, experimental studies were lacking in whether bevacizumab would be able to attenuate the severity of OA. In this study, we used normal New Zealand rabbits and a rabbit knee immobilization model of OA, to investigate the toxicity and efficacy of bevacizumab.

Methods

In the safety test of bevacizumab, sixteen rabbits were randomly divided into 2 groups: control group and bevacizumab group (n = 8 per group). We evaluated the blood chemistry and histology of normal rabbit joints after bevacizumab treatment. In the efficacy test of bevacizumab, thirty-two rabbits were used for establishing OA model and then randomly divided into 4 groups: bevacizumab group, sodium hyaluronate (SH) group, triamcinolone acetonide (TA) group and control group (n = 8 per group). We used histological evaluations and immunohistochemistry to examine the responses to bevacizumab treatment in a rabbit model of knee immobilization-induced OA.

Results

Bevacizumab treatment did not show any adverse effects histologically on normal joints. Blood tests and Mankin's score of cartilage revealed no significant difference between the bevacizumab and control groups (p > 0.05). The bevacizumab, SH, and TA groups attenuated articular cartilage degeneration and showed less synovial hyperplasia compared to the control group macroscopically and histologically, while the effect of the bevacizumab group was most obvious (p < 0.05). Immunohistochemistry revealed significantly lower vascular endothelial growth factor (VEGF) expression in the synovium and matrix metalloproteinase-1 (MMP-1) in the cartilage in the bevacizumab, SH, and TA groups compared to the control group (p < 0.05), while the expression of VEGF and MMP-1 in the bevacizumab group was the lowest among the four groups (p < 0.05).

Conclusions

Intra-articular injection of 4-mg bevacizumab in rabbit knees did not show adverse effects. The bevacizumab treatment prevented joint inflammation in terms of inhibition of reduced angiogenesis, inhibited synovial proliferation, and reduced VEGF and MMP-1 expression. Compared with SH and TA, bevacizumab protected the cartilage and produced a better therapeutic effect on primary knee OA in rabbits, which imply that bevacizumab, an anticancer drug, may become a potentially effective drug for the treatment of OA.

The translational potential of this article

Our study confirmed the therapeutic effect of bevacizumab on rabbit primary knee OA. This study demonstrated that bevacizumab may have clinical implications and contribute to the development of new OA treatments.

Recent advances in understanding the regulation of metalloproteinases

Metalloproteinases remain important players in arthritic disease, in part because members of this large enzymatic family, namely matrix metalloproteinase-1 (MMP-1) and MMP-13, are responsible for the irreversible degradation of articular cartilage collagen. Although direct inhibition of MMPs fell out of vogue with the initial clinical disappointment of the first generation of compounds, interest in other mechanisms that control these important enzymes has always been maintained. Since these enzymes are critically important for tissue homeostasis, their expression and activity are tightly regulated at many levels, not just by direct inhibition by their endogenous inhibitors the tissue inhibitors of metalloproteinases (TIMPs). Focussing on MMP-13, we discuss recent work that highlights new discoveries in the transcriptional regulation of this enzyme, from defined promoter functional analysis to how more global technologies can provide insight into the enzyme’s regulation, especially by epigenetic mechanisms, including non-coding RNAs. In terms of protein regulation, we highlight recent findings into enzymatic cascades involved in MMP-13 regulation and activation. Importantly, we highlight a series of recent studies that describe how MMP-13 activity, and in fact that of other metalloproteinases, is in part controlled by receptor-mediated endocytosis. Together, these new discoveries provide a plethora of novel regulatory mechanisms, besides direct inhibition, which with renewed vigour could provide further therapeutic opportunities for regulating the activity of this class of important enzymes.