Integrative epigenomics, transcriptomics and proteomics of patient chondrocytes reveal genes and pathways involved in osteoarthritis

Beyond symptomatic alignment: evaluating the integration of causal mechanisms in matching animal models with human pathotypes in osteoarthritis research

Osteoarthritis (OA) is a highly prevalent and disabling condition lacking curative treatments, with only symptomatic relief available. Recognizing OA as a heterogenous disorder with diverse aetiologies and molecular foundations underscores the need to classify patients by both phenotypes and molecular pathomechanisms (endotypes). Such stratification could enable the development of targeted therapies to surmount existing treatment barriers. From a scientific, economic, and ethical perspective, it is crucial to employ animal models that accurately represent the endotype of the target patient population, not merely their clinical symptoms. These models must also account for intrinsic and extrinsic factors, like age, sex, metabolic status, and comorbidities, which impact OA's pathogenesis and its clinical and molecular variability and can profoundly influence not only structural and symptomatic disease severity and progression but also the underlying molecular pathophysiology. The molecular definition of the OA subpopulation must also be reflected in the read-outs, as the traditional methods-macroscopic and histological scoring, along with limited gene expression profiling of established biomarkers for cartilage degradation, extracellular matrix (ECM) turnover, and synovial inflammation-are inadequate for discovering new, phenotype- and endotype-specific biomarkers or therapeutic targets. Thus, animal model characterisation should evolve to include both clinically and pathophysiologically pertinent measures of disease progression and response to treatment. This review evaluates the utility and accuracy of current animal models in OA research, focusing on their capacity to replicate the disease's pathophysiological processes.

Recent advances in omics and the integration of multi-omics in osteoarthritis research

Osteoarthritis (OA) is a complex disorder driven by the combination of environmental and genetic factors. Given its high global prevalence and heterogeneity, developing effective and personalized treatment methods is crucial. This requires identifying new disease mechanisms, drug targets, and biomarkers. Various omics approaches have been applied to identify OA-related genes, pathways, and biomarkers, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. These omics studies have generated vast datasets that are shaping the field of OA research. The emergence of high-resolution methodologies, such as single-cell and spatial omics techniques, further enhances our ability to dissect molecular complexities within the OA microenvironment. By integrating these multi-layered datasets, researchers can uncover central signaling hubs and disease mechanisms, ultimately facilitating the development of targeted therapies and precision medicine approaches for OA treatment.

Advances in Microfluidic Single-Cell RNA Sequencing and Spatial Transcriptomics

The development of micro- and nano-fabrication technologies has greatly advanced single-cell and spatial omics technologies. With the advantages of integration and compartmentalization, microfluidic chips are capable of generating high-throughput parallel reaction systems for single-cell screening and analysis. As omics technologies improve, microfluidic chips can now integrate promising transcriptomics technologies, providing new insights from molecular characterization for tissue gene expression profiles and further revealing the static and even dynamic processes of tissues in homeostasis and disease. Here, we survey the current landscape of microfluidic methods in the field of single-cell and spatial multi-omics, as well as assessing their relative advantages and limitations. We highlight how microfluidics has been adapted and improved to provide new insights into multi-omics over the past decade. Last, we emphasize the contributions of microfluidic-based omics methods in development, neuroscience, and disease mechanisms, as well as further revealing some perspectives for technological advances in translational and clinical medicine.

The Identification of Novel Therapeutic Biomarkers in Rheumatoid Arthritis: A Combined Bioinformatics and Integrated Multi-Omics Approach

Rheumatoid arthritis (RA) is a multifaceted autoimmune disease that is marked by a complex molecular profile influenced by an array of factors, including genetic, epigenetic, and environmental elements. Despite significant advancements in research, the precise etiology of RA remains elusive, presenting challenges in developing innovative therapeutic markers. This study takes an integrated multi-omics approach to uncover novel therapeutic markers for RA. By analyzing both transcriptomics and epigenomics datasets, we identified common gene candidates that span these two omics levels in patients diagnosed with RA. Remarkably, we discovered eighteen multi-evidence genes (MEGs) that are prevalent across transcriptomics and epigenomics, twelve of which have not been previously linked directly to RA. The bioinformatics analyses of the twelve novel MEGs revealed they are part of tightly interconnected protein-protein interaction networks directly related to RA-associated KEGG pathways and gene ontology terms. Furthermore, these novel MEGs exhibited direct interactions with miRNAs linked to RA, underscoring their critical role in the disease's pathogenicity. Overall, this comprehensive bioinformatics approach opens avenues for identifying new candidate markers for RA, empowering researchers to validate these markers efficiently through experimental studies. By advancing our understanding of RA, we can pave the way for more effective therapies and improved patient outcomes.

Clinical and omics biomarkers in osteoarthritis diagnosis and treatment

Osteoarthritis (OA) is a prevalent degenerative joint disease that significantly impacts the quality of life for hundreds of millions, and is a major cause of disability. Despite this, diagnostic and therapeutic options for OA are still limited. With advances in molecular biology, an increasing number of OA biomarkers have been identified, which not only enhances our understanding of OA pathogenesis, but also offers new approaches for OA diagnosis and treatment. This review discussed the research progress on traditional OA biomarkers, and analyzed the application of various omics, including genomics, transcriptomics, proteomics, and metabolomics, in the diagnosis and treatment of OA. Furthermore, we explored how integrating multi-omics methods can reveal interactions among different biomolecules and their roles in the development of OA. This emerging interdisciplinary approach not only provides a more comprehensive understanding of the fundamental biological characteristics of OA, but also aids in identifying new integrated biomarkers, thereby allowing for more accurate predictions of disease progression and treatment responses. The identification and development of biomarkers offer new perspectives in understanding OA, enhancing the specificity and sensitivity of biological diagnostic markers, providing a basis for the design of targeted drugs, and ultimately advancing the development of precision diagnosis and treatment strategies in clinical OA. This study provides an overview of both commonly used and emerging biomarkers of OA which is beneficial for a more accurate, timely, effective clinical diagnosis and treatment for OA.

Primary cartilage transcriptional signatures reflect cell-type-specific molecular pathways underpinning osteoarthritis

Translational efforts in osteoarthritis are hampered by a gap in our understanding of disease processes at the molecular level. Here, we present evidence of pronounced transcriptional changes in high- and low-disease-grade cartilage tissue, pointing to embryonic processes involved in disease progression. We identify shared transcriptional programs between osteoarthritis cartilage and cell populations in the human embryonic and fetal limb, pointing to increases in pre-hypertrophic chondrocytes' transcriptional programs in low-grade cartilage and increases in osteoblastic signatures in high-grade disease tissue. We find that osteoarthritis genetic risk signals are enriched in six gene co-expression modules and show that these transcriptional signatures reflect cell-type-specific expression along the endochondral ossification developmental trajectory. Using this network approach in combination with causal inference analysis, we present evidence of a causal effect on osteoarthritis risk for variants associated with the expression of ten genes that have not been previously reported as effector genes in genome-wide association studies in osteoarthritis. Our findings point to key molecular pathways as drivers of cartilage degeneration and identify high-value drug targets and repurposing opportunities.

Genetics of osteoarthritis

Osteoarthritis (OA) is the most common form of arthritis with well recognized multifactorial nature. While several environmental factors such as older age, obesity and previous joint injury are strongly associated with its development, a genetic influence on OA has been recognized for over 80 years. Identification of genes associated with OA has received considerable attention over the last two decades, aided by the rapidly evolving genotyping and sequencing technologies. More than 300 genomic loci have been identified to be associated with OA at different joints. These findings are likely to help our better understanding of the pathogenesis of OA and lead to important therapeutic and diagnostic advances in this most common disabling rheumatic disorder. This article will review the data that support the role of genetic factors in common idiopathic OA.

Epigenomic differences between osteoarthritis grades in primary cartilage

OBJECTIVE

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

DESIGN

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

RESULTS

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

CONCLUSIONS

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

A Review of Current Approaches to Pain Management in Knee Osteoarthritis with a Focus on Italian Clinical Landscape

The global cases of knee osteoarthritis (KOA) are projected to increase by 74.9% by 2050. Currently, over half of patients remain dissatisfied with their pain relief. This review addresses unmet needs for moderate-to-severe KOA pain; it offers evidence and insights for improved management. Italian experts from the fields of rheumatology, physical medicine and rehabilitation, orthopedics, primary care, and pain therapy have identified several key issues. They emphasized the need for standardized care protocols to address inconsistencies in patient management across different specialties. Early diagnosis is crucial, as cartilage responds better to early protective and structural therapies. Faster access to physiatrist evaluation and reimbursement for physical, rehabilitative, and pharmacological treatments, including intra-articular (IA) therapy, could reduce access disparities. Concerns surround the adverse effects of oral pharmacological treatments, highlighting the need for safer alternatives. Patient satisfaction with corticosteroids and hyaluronic acid-based IA therapies reduces over time and there is no consensus on the optimal IA therapy protocol. Surgery should be reserved for severe symptoms and radiographic KOA evidence, as chronic pain post-surgery poses significant societal and economic burdens. The experts advocate for a multidisciplinary approach, promoting interaction and collaboration between specialists and general practitioners, to enhance KOA care and treatment consistency in Italy.

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.

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.

ALDH1A3 promotes invasion and metastasis in triple-negative breast cancer by regulating the plasminogen activation pathway

Aldehyde dehydrogenase 1A3 (ALDH1A3) is a cancer stem cell marker that promotes metastasis. Triple-negative breast cancer (TNBC) progression has been linked to ALDH1A3-induced gene expression changes. To investigate the mechanism of ALDH1A3-mediated breast cancer metastasis, we assessed the effect of ALDH1A3 on the expression of proteases and the regulators of proteases that degrade the extracellular matrix, a process that is essential for invasion and metastasis. This revealed that ALDH1A3 regulates the plasminogen activation pathway; it increased the levels and activity of tissue plasminogen activator (tPA) and urokinase plasminogen activator (uPA). This resulted in a corresponding increase in the activity of serine protease plasmin, the enzymatic product of tPA and uPA. The ALDH1A3 product all-trans-retinoic acid similarly increased tPA and plasmin activity. The increased invasion of TNBC cells by ALDH1A3 was plasminogen-dependent. In patient tumours, ALDH1A3 and tPA are co-expressed and their combined expression correlated with the TNBC subtype, high tumour grade and recurrent metastatic disease. Knockdown of tPA in TNBC cells inhibited plasmin generation and lymph node metastasis. These results identify the ALDH1A3-tPA-plasmin axis as a key contributor to breast cancer progression.

pH-sensing G protein-coupled orphan receptor GPR68 is expressed in human cartilage and correlates with degradation of extracellular matrix during OA progression

Background

Osteoarthritis (OA) is a debilitating joints disease affecting millions of people worldwide. As OA progresses, chondrocytes experience heightened catabolic activity, often accompanied by alterations in the extracellular environment's osmolarity and acidity. Nevertheless, the precise mechanism by which chondrocytes perceive and respond to acidic stress remains unknown. Recently, there has been growing interest in pH-sensing G protein-coupled receptors (GPCRs), such as GPR68, within musculoskeletal tissues. However, function of GPR68 in cartilage during OA progression remains unknown. This study aims to identify the role of GPR68 in regulation of catabolic gene expression utilizing an in vitro model that simulates catabolic processes in OA.

Methods

We examined the expression of GPCR by analyzing high throughput RNA-Seq data in human cartilage isolated from healthy donors and OA patients. De-identified and discarded OA cartilage was obtained from joint arthroplasty and chondrocytes were prepared by enzymatic digestion. Chondrocytes were treated with GPR68 agonist, Ogerin and then stimulated IL1β and RNA isolation was performed using Trizol method. Reverse transcription was done using the cDNA synthesis kit and the expression of GPR68 and OA related catabolic genes was quantified using SYBR® green assays.

Results

The transcriptome analysis revealed that pH sensing GPCR were expressed in human cartilage with a notable increase in the expression of GPR68 in OA cartilage which suggest a potential role for GPR68 in the pathogenesis of OA. Immunohistochemical (IHC) and qPCR analyses in human cartilage representing various stages of OA indicated a progressive increase in GPR68 expression in cartilage associated with higher OA grades, underscoring a correlation between GPR68 expression and the severity of OA. Furthermore, IHC analysis of Gpr68 in murine cartilage subjected to surgically induced OA demonstrated elevated levels of GPR68 in knee cartilage and meniscus. Using IL1β stimulated in vitro model of OA catabolism, our qPCR analysis unveiled a time-dependent increase in GPR68 expression in response to IL1β stimulation, which correlates with the expression of matrix degrading proteases suggesting the role of GPR68 in chondrocytes catabolism and matrix degeneration. Using pharmacological activator of GPR68, our results further showed that GPR68 activation repressed the expression of MMPs in human chondrocytes.

Conclusions

Our results demonstrated that GPR68 was robustly expressed in human cartilage and mice and its expression correlates with matrix degeneration and severity of OA progression in human and surgical model. GPR68 activation in human chondrocytes further repressed the expression of MMPs under OA pathological condition. These results identify GPR68 as a possible therapeutic target in the regulation of matrix degradation during OA.

SGMS2 in primary osteoporosis with facial nerve palsy

Pathogenic heterozygous variants in SGMS2 cause a rare monogenic form of osteoporosis known as calvarial doughnut lesions with bone fragility (CDL). The clinical presentations of SGMS2-related bone pathology range from childhood-onset osteoporosis with low bone mineral density and sclerotic doughnut-shaped lesions in the skull to a severe spondylometaphyseal dysplasia with neonatal fractures, long-bone deformities, and short stature. In addition, neurological manifestations occur in some patients. SGMS2 encodes sphingomyelin synthase 2 (SMS2), an enzyme involved in the production of sphingomyelin (SM). This review describes the biochemical structure of SM, SM metabolism, and their molecular actions in skeletal and neural tissue. We postulate how disrupted SM gradient can influence bone formation and how animal models may facilitate a better understanding of SGMS2-related osteoporosis.

Transcriptomic and proteomic studies of condylar ossification of the temporomandibular joint in porcine embryos

BACKGROUND

The ossification mechanism of the temporomandibular joint (TMJ) condyle remains unclear in human embryo. The size and structure of TMJ, shape of articular disc and the characteristics of omnivorous chewing in the pig are similar to those of humans. The pig is an ideal animal for studying the mechanism of ossification of the TMJ condyle during the embryonic period.

METHOD

In a previous study by our group, it was found that there was no condylar ossification on embryonic day(E) 45, but the ossification of condyle occurred between E75 and E90. In this study, a total of 12 miniature pig embryos on E45 and E85 were used. Six embryos were used for tissue sections (3 in each group). The remaining six embryos were used for transcriptomic and proteomic studies to find differential genes and proteins. The differentially expressed genes in transcriptome and proteomic analysis were verified by QPCR.

RESULTS

In total, 1592 differential genes comprising 1086 up-regulated genes and 506 down-regulated genes were screened for fold changes of ≥2 to ≤0.5 between E45 and E85. In the total of 4613 proteins detected by proteomic analysis, there were 419 differential proteins including 313 up-regulated proteins and 106 down-regulated proteins screened for fold changes of ≥2 to ≤0.5 between E45 and E85. A total of 36 differential genes differing in both transcriptome and proteome analysis were found. QPCR analysis showed that 14 of 15 selected genes were consistent with transcriptome analysis.

CONCLUSION

Condylar transcriptome and proteomic analysis during the development of TMJ in miniature pigs revealed the regulatory genes/proteins of condylar ossification.

From target discovery to clinical drug development with human genetics

The substantial investments in human genetics and genomics made over the past three decades were anticipated to result in many innovative therapies. Here we investigate the extent to which these expectations have been met, excluding cancer treatments. In our search, we identified 40 germline genetic observations that led directly to new targets and subsequently to novel approved therapies for 36 rare and 4 common conditions. The median time between genetic target discovery and drug approval was 25 years. Most of the genetically driven therapies for rare diseases compensate for disease-causing loss-of-function mutations. The therapies approved for common conditions are all inhibitors designed to pharmacologically mimic the natural, disease-protective effects of rare loss-of-function variants. Large biobank-based genetic studies have the power to identify and validate a large number of new drug targets. Genetics can also assist in the clinical development phase of drugs-for example, by selecting individuals who are most likely to respond to investigational therapies. This approach to drug development requires investments into large, diverse cohorts of deeply phenotyped individuals with appropriate consent for genetically assisted trials. A robust framework that facilitates responsible, sustainable benefit sharing will be required to capture the full potential of human genetics and genomics and bring effective and safe innovative therapies to patients quickly.

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.

Prediction and analysis of osteoarthritis hub genes with bioinformatics

Background

Osteoarthritis (OA) is the most common type of arthritis. OA can cause joint pain, stiffness, and loss of function. The pathogenesis of OA is not completely clear. Moreover, there is no effective treatment, and clinical management is limited to symptomatic relief or joint surgery. This study utilized bioinformatics to analyze normal and OA articular cartilage samples to find biomarkers and therapeutic targets for OA.

Methods

The GSE169077 gene chip dataset was downloaded from the public gene chip data platform of the National Biotechnology Information Center. The dataset included 6 samples of OA tissues and 5 samples of healthy cartilage tissues. Differentially expressed genes (DEGs) were screened using the R language "limma" function package under the threshold of log2[fold change (FC)] ≥2 and a P value <0.05. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways of the target genes were enriched and analyzed using the database for annotation, visualization, and integrated discovery (DAVID), and a protein-protein interaction (PPI) network was further constructed using the search tool for the retrieval of interacting genes/proteins (STRING) database. The coexpression relationship of the genes in the module was visualized and screened with Cytoscape.

Results

A total of 27 DEGs were identified, including 9 downregulated genes and 18 upregulated genes. GO signal pathway enrichment analysis showed involvement in hypoxic response, fibrous collagen trimer, and extracellular matrix structural components. KEGG analysis demonstrated associations with protein digestion and absorption, extracellular matrix receptor interaction, and the peroxisome proliferator-activated receptor signal pathway, among several other pathways. A PPI network was obtained through STRING analysis, and the results were imported into Cytoscape software. The 27 DEGs were sequenced by the cytoHubba plug-in by various calculation methods, and 5 hub genes (COL1A1, COL1A2, POSTN, BMP1, and MMP13) were finally selected. These genes were analyzed by PPI again and annotated with GO and KEGG in different colors.

Conclusions

Bioinformatics technology effectively identified differential genes in the knee cartilage tissue of healthy controls and patients with OA, providing opportunities to further explore the mechanism and treatment of OA on a transcriptional level.

A "best-in-class" systemic biomarker predictor of clinically relevant knee osteoarthritis structural and pain progression

We aimed to identify markers in blood (serum) to predict clinically relevant knee osteoarthritis (OA) progression defined as the combination of both joint structure and pain worsening over 48 months. A set of 15 serum proteomic markers corresponding to 13 total proteins reached an area under the receiver operating characteristic curve (AUC) of 73% for distinguishing progressors from nonprogressors in a cohort of 596 individuals with knee OA. Prediction based on these blood markers was far better than traditional prediction based on baseline structural OA and pain severity (59%) or the current "best-in-class" biomarker for predicting OA progression, urinary carboxyl-terminal cross-linked telopeptide of type II collagen (58%). The generalizability of the marker set was confirmed in a second cohort of 86 individuals that yielded an AUC of 70% for distinguishing joint structural progressors. Blood is a readily accessible biospecimen whose analysis for these biomarkers could facilitate identification of individuals for clinical trial enrollment and those most in need of treatment.

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.

Performance of Colombian Silk Fibroin Hydrogels for Hyaline Cartilage Tissue Engineering

The development and evaluation of scaffolds play a crucial role in the engineering of hyaline cartilage tissue. This work aims to evaluate the performance of silk fibroin hydrogels fabricated from the cocoons of the Colombian hybrid in the in vitro regeneration of hyaline cartilage. The scaffolds were physicochemically characterized, and their performance was evaluated in a cellular model. The results showed that the scaffolds were rich in random coils and β-sheets in their structure and susceptible to various serine proteases with different degradation profiles. Furthermore, they showed a significant increase in ACAN, COL10A1, and COL2A1 expression compared to pellet culture alone and allowed GAG deposition. The soluble portion of the scaffold did not affect chondrogenesis. Furthermore, they promoted the increase in COL1A2, showing a slight tendency to differentiate towards fibrous cartilage. The results also showed that Colombian silk could be used as a source of biomedical devices, paving the way for sericulture to become a more diverse economic activity in emerging countries.

Whole-genome RNA sequencing identifies distinct transcriptomic profiles in impingement cartilage between patients with femoroacetabular impingement and hip osteoarthritis

Femoroacetabular impingement (FAI) has a strong clinical association with the development of hip osteoarthritis (OA); however, the pathobiological mechanisms underlying the transition from focal impingement to global joint degeneration remain poorly understood. The purpose of this study is to use whole-genome RNA sequencing to identify and subsequently validate differentially expressed genes (DEGs) in femoral head articular cartilage samples from patients with FAI and hip OA secondary to FAI. Thirty-seven patients were included in the study with whole-genome RNA sequencing performed on 10 gender-matched patients in the FAI and OA cohorts and the remaining specimens were used for validation analyses. We identified a total of 3531 DEGs between the FAI and OA cohorts with multiple targets for genes implicated in canonical OA pathways. Quantitative reverse transcription-polymerase chain reaction validation confirmed increased expression of FGF18 and WNT16 in the FAI samples, while there was increased expression of MMP13 and ADAMTS4 in the OA samples. Expression levels of FGF18 and WNT16 were also higher in FAI samples with mild cartilage damage compared to FAI samples with severe cartilage damage or OA cartilage. Our study further expands the knowledge regarding distinct genetic reprogramming in the cartilage between FAI and hip OA patients. We independently validated the results of the sequencing analysis and found increased expression of anabolic markers in patients with FAI and minimal histologic cartilage damage, suggesting that anabolic signaling may be increased in early FAI with a transition to catabolic and inflammatory gene expression as FAI progresses towards more severe hip OA. Clinical significance:Cam-type FAI has a strong clinical association with hip OA; however, the cellular pathophysiology of disease progression remains poorly understood. Several previous studies have demonstrated increased expression of inflammatory markers in FAI cartilage samples, suggesting the involvement of these inflammatory pathways in the disease progression. Our study further expands the knowledge regarding distinct genetic reprogramming in the cartilage between FAI and hip OA patients. In addition to differences in inflammatory gene expression, we also identified differential expression in multiple pathways involved in hip OA progression.

Integrative proteomics and m6A microarray analyses of the signatures induced by METTL3 reveals prognostically significant in gastric cancer by affecting cellular metabolism

METTL3-mediated RNA N6-methyladenosine (m6A) is the most prevalent modification that participates in tumor initiation and progression via governing the expression of their target genes in cancers. However, its role in tumor cell metabolism remains poorly characterized. In this study, m6A microarray and quantitative proteomics were employed to explore the potential effect and mechanism of METTL3 on the metabolism in GC cells. Our results showed that METTL3 induced significant alterations in the protein and m6A modification profile in GC cells. Gene Ontology (GO) enrichment indicated that down-regulated proteins were significantly enriched in intracellular mitochondrial oxidative phosphorylation (OXPHOS). Moreover, the protein-protein Interaction (PPI) network analysis found that these differentially expressed proteins were significantly associated with OXPHOS. A prognostic model was subsequently constructed based on the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, and the high-risk group exhibited a worse prognosis in GC patients. Meanwhile, Gene Set Enrichment Analysis (GSEA) demonstrated significant enrichment in the energy metabolism signaling pathway. Then, combined with the results of the m6A microarray analysis, the intersection molecules of DEPs and differential methylation genes (DMGs) were significantly correlated with the molecules of OXPHOS. Besides, there were significant differences in prognosis and GSEA enrichment between the two clusters of GC patients classified according to the consensus clustering algorithm. Finally, highly expressed and highly methylated molecules regulated by METTL3 were analyzed and three (AVEN, DAZAP2, DNAJB1) genes were identified to be significantly associated with poor prognosis in GC patients. These results signified that METTL3-regulated DEPs in GC cells were significantly associated with OXPHOS. After combined with m6A microarray analysis, the results suggested that these proteins might be implicated in cell energy metabolism through m6A modifications thus influencing the prognosis of GC patients. Overall, our study revealed that METTL3 is involved in cell metabolism through an m6A-dependent mechanism in GC cells, and indicated a potential biomarker for prognostic prediction in GC.

Expression Profile of New Gene Markers Involved in Differentiation of Canine Adipose-Derived Stem Cells into Chondrocytes

The interest in stem cell research continuously increased over the last decades, becoming one of the most important trends in the 21st century medicine. Stem cell-based therapies have a potential to become a solution for a range of currently untreatable diseases, such as spinal cord injuries, type I diabetes, Parkinson’s disease, heart disease, stroke, and osteoarthritis. Hence, this study, based on canine material, aims to investigate the molecular basis of adipose-derived stem cell (ASC) differentiation into chondrocytes, to serve as a transcriptomic reference for further research aiming to introduce ASC into treatment of bone and cartilage related diseases, such as osteoarthritis in veterinary medicine. Adipose tissue samples were harvested from a canine specimen subjected to a routine ovariohysterecromy procedure at an associated veterinary clinic. The material was treated for ASC isolation and chondrogenic differentiation. RNA samples were isolated at day 1 of culture, day 30 of culture in unsupplemented culture media, and day 30 of culture in chondrogenic differentiation media. The resulting RNA was analyzed using RNAseq assays, with the results validated by RT-qPCR. Between differentiated chondrocytes, early and late cultures, most up- and down-regulated genes in each comparison were selected for further analysis., there are several genes (e.g., MMP12, MPEG1, CHI3L1, and CD36) that could be identified as new markers of chondrogenesis and the influence of long-term culture conditions on ASCs. The results of the study prove the usefulness of the in vitro culture model, providing further molecular insight into the processes associated with ASC culture and differentiation. Furthermore, the knowledge obtained could be used as a molecular reference for future in vivo and clinical studies.

The Kinesin Gene KIF26B Modulates the Severity of Post-Traumatic Heterotopic Ossification

The formation of pathological bone deposits within soft tissues, termed heterotopic ossification (HO), is common after trauma. However, the severity of HO formation varies substantially between individuals, from relatively isolated small bone islands through to extensive soft tissue replacement by bone giving rise to debilitating symptoms. The aim of this study was to identify novel candidate therapeutic molecular targets for severe HO. We conducted a genome-wide scan in men and women with HO of varying severity following hip replacement for osteoarthritis. HO severity was dichotomized as mild or severe, and association analysis was performed with adjustment for age and sex. We next confirmed expression of the gene encoded by the lead signal in human bone and in primary human mesenchymal stem cells. We then examined the effect of gene knockout in a murine model of osseous trans-differentiation, and finally we explored transcription factor phosphorylation in key pathways perturbed by the gene. Ten independent signals were suggestively associated with HO severity, with KIF26B as the lead. We subsequently confirmed KIF26B expression in human bone and upregulation upon BMP2-induced osteogenic differentiation in primary human mesenchymal stem cells, and also in a rat tendo-Achilles model of post-traumatic HO. CRISPR-Cas9 mediated knockout of Kif26b inhibited BMP2-induced Runx2, Sp7/Osterix, Col1A1, Alp, and Bglap/Osteocalcin expression and mineralized nodule formation in a murine myocyte model of osteogenic trans-differentiation. Finally, KIF26B deficiency inhibited ERK MAP kinase activation during osteogenesis, whilst augmenting p38 and SMAD 1/5/8 phosphorylation. Taken together, these data suggest a role for KIF26B in modulating the severity of post-traumatic HO and provide a potential novel avenue for therapeutic translation.

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.

An epigenome-wide view of osteoarthritis in primary tissues

Osteoarthritis is a complex degenerative joint disease. Here, we investigate matched genotype and methylation profiles of primary chondrocytes from macroscopically intact (low-grade) and degraded (high-grade) osteoarthritis cartilage and from synoviocytes collected from 98 osteoarthritis-affected individuals undergoing knee replacement surgery. We perform an epigenome-wide association study of knee cartilage degeneration and report robustly replicating methylation markers, which reveal an etiologic mechanism linked to the migration of epithelial cells. Using machine learning, we derive methylation models of cartilage degeneration, which we validate with 82% accuracy in independent data. We report a genome-wide methylation quantitative trait locus (mQTL) map of articular cartilage and synovium and identify 18 disease-grade-specific mQTLs in osteoarthritis cartilage. We resolve osteoarthritis GWAS loci through causal inference and colocalization analyses and decipher the epigenetic mechanisms that mediate the effect of genotype on disease risk. Together, our findings provide enhanced insights into epigenetic mechanisms underlying osteoarthritis in primary tissues.

A molecular map of long non-coding RNA expression, isoform switching and alternative splicing in osteoarthritis

Osteoarthritis is a prevalent joint disease and a major cause of disability worldwide with no curative therapy. Development of disease-modifying therapies requires a better understanding of the molecular mechanisms underpinning disease. A hallmark of osteoarthritis is cartilage degradation. To define molecular events characterizing osteoarthritis at the whole transcriptome level, we performed deep RNA sequencing in paired samples of low- and high-osteoarthritis grade knee cartilage derived from 124 patients undergoing total joint replacement. We detected differential expression between low- and high-osteoarthritis grade articular cartilage for 365 genes and identified a 38-gene signature in osteoarthritis cartilage by replicating our findings in an independent dataset. We also found differential expression for 25 novel long non-coding RNA genes (lncRNAs) and identified potential lncRNA interactions with RNA-binding proteins in osteoarthritis. We assessed alterations in the relative usage of individual gene transcripts and identified differential transcript usage for 82 genes, including ABI3BP, coding for an extracellular matrix protein, AKT1S1, a negative regulator of the mTOR pathway and TPRM4, coding for a transient receptor potential channel. We further assessed genome-wide differential splicing, for the first time in osteoarthritis, and detected differential splicing for 209 genes, which were enriched for extracellular matrix, proteoglycans and integrin surface interactions terms. In the largest study of its kind in osteoarthritis, we find that isoform and splicing changes, in addition to extensive differences in both coding and non-coding sequence expression, are associated with disease and demonstrate a novel layer of genomic complexity to osteoarthritis pathogenesis.

Mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers

Background

Osteoarthritis (OA) is a slowly developing and debilitating disease, and there are no validated specific biomarkers for its early detection. To improve therapeutic approaches, identification of specific molecules/biomarkers enabling early determination of this disease is needed. This study aimed at identifying, with the use of proteomics/mass spectrometry, novel OA-specific serum biomarkers. As obesity is a major risk factor for OA, we discriminated obesity-regulated proteins to target only OA-specific proteins as biomarkers.

Methods

Serum from the Osteoarthritis Initiative cohort was used and divided into 3 groups: controls (n=8), OA-obese (n=10) and OA-non-obese (n=10). Proteins were identified and quantified from the liquid chromatography–tandem mass spectrometry analyses using MaxQuant software. Statistical analysis used the Limma test followed by the Benjamini-Hochberg method. To compare the proteomic profiles, the multivariate unsupervised principal component analysis (PCA) followed by the pairwise comparison was used. To select the most predictive/discriminative features, the supervised linear classification model sparse partial least squares regression discriminant analysis (sPLS-DA) was employed. Validation of three differential proteins was performed with protein-specific assays using plasma from a cohort derived from the Newfoundland Osteoarthritis.

Results

In total, 509 proteins were identified, and 279 proteins were quantified. PCA-pairwise differential comparisons between the 3 groups revealed that 8 proteins were differentially regulated between the OA-obese and/or OA-non-obese with controls. Further experiments using the sPLS-DA revealed two components discriminating OA from controls (component 1, 9 proteins), and OA-obese from OA-non-obese (component 2, 23 proteins). Proteins from component 2 were considered related to obesity. In component 1, compared to controls, 7 proteins were significantly upregulated by both OA groups and 2 by the OA-obese. Among upregulated proteins from both OA groups, some of them alone would not be a suitable choice as specific OA biomarkers due to their rather non-specific role or their strong link to other pathological conditions. Altogether, data revealed that the protein CRTAC1 appears to be a strong OA biomarker candidate. Other potential new biomarker candidates are the proteins FBN1, VDBP, and possibly SERPINF1. Validation experiments revealed statistical differences between controls and OA for FBN1 (p=0.044) and VDPB (p=0.022), and a trend for SERPINF1 (p=0.064).

Conclusion

Our study suggests that 4 proteins, CRTAC1, FBN1, VDBP, and possibly SERPINF1, warrant further investigation as potential new biomarker candidates for the whole OA population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-022-02801-1.

The crucial mechanism and therapeutic implication of RNA methylation in bone pathophysiology

Methylation is the most common posttranscriptional modification in cellular RNAs, which has been reported to modulate the alteration of RNA structure for initiating relevant functions such as nuclear translocation and RNA degradation. Recent studies found that RNA methylation especially N6-methyladenosine (m⁶A) regulates the dynamic balance of bone matrix and forms a complicated network in bone metabolism. The modulation disorder of RNA methylation contributes to several pathological bone diseases including osteoporosis (OP), osteoarthritis (OA), rheumatoid arthritis (RA), and so on. In the review, we will discuss advanced technologies for detecting RNA methylation, summarize RNA methylation-related biological impacts on regulating bone homeostasis and pathological bone diseases. In addition, we focus on the promising roles of RNA methylation in early diagnosis and therapeutic implications for bone-related diseases. Then, we aim to establish a theoretical basis for further investigation in this meaningful field.

Prenatal exposure to phthalates and peripheral blood and buccal epithelial DNA methylation in infants: An epigenome-wide association study

BACKGROUND

Prenatal exposure to phthalates has been associated with adverse health and neurodevelopmental outcomes. DNA methylation (DNAm) alterations may be a mechanism underlying these effects, but prior investigations of prenatal exposure to phthalates and neonatal DNAm profiles are limited to placental tissue and umbilical cord blood.

OBJECTIVE

Conduct an epigenome-wide association study (EWAS) of the associations between prenatal exposure to phthalates and DNAm in two accessible infant tissues, venous buffy coat blood and buccal epithelial cells (BECs).

METHODS

Participants included 152 maternal-infant pairs from the Alberta Pregnancy Outcomes and Nutrition (APrON) study. Maternal second trimester urine samples were analyzed for nine phthalate metabolites. Blood (n = 74) or BECs (n = 78) were collected from 3-month-old infants and profiled for DNAm using the Infinium HumanMethylation450 (450K) BeadChip. Robust linear regressions were used to investigate the associations between high (HMWPs) and low molecular weight phthalates (LMWPs) and change in methylation levels at variable Cytosine-phosphate-Guanine (CpG) sites in infant tissues, as well as the sensitivity of associations to potential confounders.

RESULTS

One candidate CpG in gene RNF39 reported by a previous study examining prenatal exposure to phthalates and cord blood DNAm was replicated. The EWAS identified 12 high-confidence CpGs in blood and another 12 in BECs associated with HMWPs and/or LMWPs. Prenatal exposure to bisphenol A (BPA) associated with two of the CpGs associated with HMWPs in BECs.

DISCUSSION

Prenatal exposure to phthalates was associated with DNAm variation at CpGs annotated to genes associated with endocrine hormone activity (i.e., SLCO4A1, TPO), immune pathways and DNA damage (i.e., RASGEF1B, KAZN, HLA-A, MYO18A, DIP2C, C1or109), and neurodevelopment (i.e., AMPH, NOTCH3, DNAJC5). Future studies that characterize the stability of these associations in larger samples, multiple cohorts, across tissues, and investigate the potential associations between these biomarkers and relevant health and neurodevelopmental outcomes are needed.

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.

The deterioration of calcified cartilage integrity reflects the severity of osteoarthritis-A structural, molecular, and biochemical analysis

The calcified cartilage zone (CCZ) is a thin interlayer between the hyaline articular cartilage and the subchondral bone and plays an important role in maintaining the joint homeostasis by providing biological and mechanical support from unmineralized cartilage to the underlying mineralized subchondral bone. The hallmark of CCZ characteristics in osteoarthritis (OA) is less well known. The aim of our study is to evaluate the structural, molecular, and biochemical composition of CCZ in tissues affected by primary knee OA and its relationship with disease severity. We collected osteochondral tissue samples stratified according to disease severity, from 16 knee OA patients who underwent knee replacement surgery. We also used meniscectomy-induced rat samples to confirm the pathophysiologic changes of human samples. We defined the characteristics of the calcified cartilage layer using a combination of morphological, biochemical, proteomic analyses on laser micro-dissected tissue. Our results demonstrated that the Calcium/Phosphate ratio is unchanged during the OA progression, but the calcium-binding protein and cadherin binding protein, as well as carbohydrate metabolism-related proteins, undergo significant changes. These changes were further accompanied by thinning of the CCZ, loss of collagen and proteoglycan content, the occurrence of the endochondral ossification, neovasculature, loss of the elastic module, loss of the collagen direction, and increase of the tortuosity indicating an altered structural and mechanical properties of the CCZ in OA. In conclusion, our results suggest that the calcified cartilage changes can reflect the disease progression.

Transcriptome Analysis Reveals Novel Genes Associated with Cartilage Degeneration in Posttraumatic Osteoarthritis Progression

OBJECTIVE

The current therapeutic strategy for posttraumatic osteoarthritis (PTOA) focuses on early intervention to attenuate disease progression, preserve joint function, and defer joint replacement timing. Sequential transcriptomic changes of articular cartilage in a rat model were investigated to explore the molecular mechanism in early PTOA progression.

DESIGN

Anterior cruciate ligament transection and medial meniscectomy (ACLT + MMx)-induced PTOA model was applied on male Wistar rats. Articular cartilages were harvested at time 0 (naïve), 2 week, and 4 weeks after surgery. Affymetrix Rat genome 230 2.0 array was utilized to analyze the gene expression changes of articular cartilages.

RESULTS

We identified 849 differentially expressed genes (DEGs) at 2 weeks and 223 DEGs at 4 weeks post-ACLT + MMx surgery compared with time 0 (naïve group). Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to gain further insights from these DEGs. 22 novel genes and 1 novel KEGG pathway (axon guidance) in cartilage degeneration of osteoarthritis were identified. Axon guidance molecules-Gnai1, Sema4d, Plxnb1, and Srgap2 commonly dysregulated in PTOA progression. Gnai1 gene showed a concordant change in protein expression by immunohistochemistry staining.

CONCLUSIONS

Our study identified 22 novel dysregulated genes and axon guidance pathway associated with articular cartilage degeneration in PTOA progression. These findings provide the potential candidates of biomarkers and therapeutic targets for further investigation.

Low-Input RNA-Sequencing in Patients with Cartilage Lesions, Osteoarthritis, and Healthy Cartilage

OBJECTIVE

To analyze and compare cartilage samples from 3 groups of patients utilizing low-input RNA-sequencing.

DESIGN

Cartilage biopsies were collected from patients in 3 groups (n = 48): Cartilage lesion (CL) patients had at least ICRS grade 2, osteoarthritis (OA) samples were taken from patients undergoing knee replacement, and healthy cartilage (HC) was taken from ACL-reconstruction patients without CLs. RNA was isolated using an optimized protocol. RNA samples were assessed for quality and sequenced with a low-input SmartSeq2 protocol.

RESULTS

RNA isolation yielded 48 samples with sufficient quality for sequencing. After quality control, 13 samples in the OA group, 9 in the HC group, and 9 in the CL group were included in the analysis. There was a high degree of co-clustering between the HC and CL groups with only 6 genes significantly up- or downregulated. OA and the combined HC/CL group clustered significantly separate from each other, yielding 659 significantly upregulated and 1,369 downregulated genes. GO-term analysis revealed that genes matched to cartilage and connective tissue development terms.

CONCLUSION

The gene expression profiles from the 3 groups suggest that there are no major differences in gene expression between cartilage from knees with a cartilage injury and knees without an apparent cartilage injury. OA cartilage, as expected, showed markedly different gene expression from the other 2 groups. The gene expression profiles resulting from this low-input RNA-sequencing study offer opportunities to discover new pathways not previously recognized that may be explored in future studies.

DNA methylation and noncoding RNA in OA: Recent findings and methodological advances

Introduction

Osteoarthritis (OA) is a chronic musculoskeletal disease characterized by progressive loss of joint function. Historically, it has been characterized as a disease caused by mechanical trauma, so-called 'wear and tear'. Over the past two decades, it has come to be understood as a complex systemic disorder involving gene-environmental interactions. Epigenetic changes have been increasingly implicated. Recent improvements in microarray and next-generation sequencing (NGS) technologies have allowed for ever more complex evaluations of epigenetic aberrations associated with the development and progression of OA.

Methods

A systematic review was conducted in the Pubmed database. We curated studies that presented the results of DNA methylation and noncoding RNA research in human OA and OA animal models since 1985.

Results

Herein, we discuss recent findings and methodological advancements in OA epigenetics, including a discussion of DNA methylation, including microarray and NGS studies, and noncoding RNAs. Beyond cartilage, we also highlight studies in subchondral bone and peripheral blood mononuclear cells, which highlight widespread and potentially clinically important alterations in epigenetic patterns seen in OA patients. Finally, we discuss epigenetic editing approaches in the context of OA.

Conclusions

Although a substantial body of literature has already been published in OA, much is still unknown. Future OA epigenetics studies will no doubt continue to broaden our understanding of underlying pathophysiology and perhaps offer novel diagnostics and/or treatments for human OA.

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.

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

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

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

BACKGROUND

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

RESEARCH DESIGN AND METHODS

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

RESULTS

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

CONCLUSION

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

Critical role of Aquaporin-1 and telocytes in infantile hemangioma response to propranolol beta blockade

Propranolol, a nonselective β-adrenergic receptor (ADRB) antagonist, is the first-line therapy for severe infantile hemangiomas (IH). Since the incidental discovery of propranolol efficacy in IH, preclinical and clinical investigations have shown evidence of adjuvant propranolol response in some malignant tumors. However, the mechanism for propranolol antitumor effect is still largely unknown, owing to the absence of a tumor model responsive to propranolol at nontoxic concentrations. Immunodeficient mice engrafted with different human tumor cell lines were treated with anti-VEGF bevacizumab to create a model sensitive to propranolol. Proteomics analysis was used to reveal propranolol-mediated protein alteration correlating with tumor growth inhibition, and Aquaporin-1 (AQP1), a water channel modulated in tumor cell migration and invasion, was identified. IH tissues and cells were then functionally investigated. Our functional protein association networks analysis and knockdown of ADRB2 and AQP1 indicated that propranolol treatment and AQP1 down-regulation trigger the same pathway, suggesting that AQP1 is a major driver of beta-blocker antitumor response. Examining AQP1 in human hemangioma samples, we found it exclusively in a perivascular layer, so far unrecognized in IH, made of telocytes (TCs). Functional in vitro studies showed that AQP1-positive TCs play a critical role in IH response to propranolol and that modulation of AQP1 in IH-TC by propranolol or shAQP1 decreases capillary-like tube formation in a Matrigel-based angiogenesis assay. We conclude that IH sensitivity to propranolol may rely, at least in part, on a cross talk between lesional vascular cells and stromal TCs.

Decellularized Porcine Cartilage Scaffold; Validation of Decellularization and Evaluation of Biomarkers of Chondrogenesis

Osteoarthritis is a major concern in the United States and worldwide. Current non-surgical and surgical approaches alleviate pain but show little evidence of cartilage restoration. Cell-based treatments may hold promise for the regeneration of hyaline cartilage-like tissue at the site of injury or wear. Cell-cell and cell-matrix interactions have been shown to drive cell differentiation pathways. Biomaterials for clinically relevant applications can be generated from decellularized porcine auricular cartilage. This material may represent a suitable scaffold on which to seed and grow chondrocytes to create new cartilage. In this study, we used decellularization techniques to create an extracellular matrix scaffold that supports chondrocyte cell attachment and growth in tissue culture conditions. Results presented here evaluate the decellularization process histologically and molecularly. We identified new and novel biomarker profiles that may aid future cartilage decellularization efforts. Additionally, the resulting scaffold was characterized using scanning electron microscopy, fluorescence microscopy, and proteomics. Cellular response to the decellularized scaffold was evaluated by quantitative real-time PCR for gene expression analysis.

Update on pain in arthritis

PURPOSE OF REVIEW

Osteoarthritis is a degenerative joint disease that features pain as a hallmark symptom. This review summarises progress and obstacles in our understanding of pain mechanisms in arthritis.

RECENT FINDINGS

Pain phenotypes in osteoarthritis are poorly characterized in clinical studies and animal studies are largely carti-centric. Different animal models incur variable disease progression patterns and activation of distinct pain pathways, but studies reporting both structural and pain outcomes permit better translational insights. In patients, classification of osteoarthritis disease severity is only based on structural integrity of the joint, but pain outcomes do not consistently correlate with joint damage. The complexity of this relationship underlines the need for pain detection in criteria for osteoarthritis classification and patient-reported outcome measures.

SUMMARY

Variable inflammatory and neuropathic components and spatiotemporal evolution underlie the heterogeneity of osteoarthritis pain phenotypes, which must be considered to adequately stratify patients. Revised classification of osteoarthritis at different stages encompassing both structural and pain outcomes would significantly improve detection and diagnosis at both early and late stages of disease. These are necessary advancements in the field that would also improve trial design and provide better understanding of basic mechanisms of disease progression and pain in osteoarthritis.

Candidates for Intra-Articular Administration Therapeutics and Therapies of Osteoarthritis

Osteoarthritis (OA) of the knee is a disease that significantly decreases the quality of life due to joint deformation and pain caused by degeneration of articular cartilage. Since the degeneration of cartilage is irreversible, intervention from an early stage and control throughout life is important for OA treatment. For the treatment of early OA, the development of a disease-modifying osteoarthritis drug (DMOAD) for intra-articular (IA) injection, which is attracting attention as a point-of-care therapy, is desired. In recent years, the molecular mechanisms involved in OA progression have been clarified while new types of drug development methods based on gene sequences have been established. In addition to conventional chemical compounds and protein therapeutics, the development of DMOAD from the new modalities such as gene therapy and oligonucleotide therapeutics is accelerating. In this review, we have summarized the current status and challenges of DMOAD for IA injection, especially for protein therapeutics, gene therapy, and oligonucleotide therapeutics.

OATargets: a knowledge base of genes associated with osteoarthritis joint damage in animals

OBJECTIVES

To collate the genes experimentally modulated in animal models of osteoarthritis (OA) and compare these data with OA transcriptomics data to identify potential therapeutic targets.

METHODS

PubMed searches were conducted to identify publications describing gene modulations in animal models. Analysed gene expression data were retrieved from the SkeletalVis database of analysed skeletal microarray and RNA-Seq expression data. A network diffusion approach was used to predict new genes associated with OA joint damage.

RESULTS

A total of 459 genes were identified as having been modulated in animal models of OA, with ageing and post-traumatic (surgical) models the most prominent. Ninety-eight of the 143 genes (69%) genetically modulated more than once had a consistent effect on OA joint damage severity. Several discrepancies between different studies were identified, providing lessons on interpretation of these data. We used the data collected along with OA gene expression data to expand existing annotations and prioritise the most promising therapeutic targets, which we validated using the latest reported associations. We constructed an online database OATargets to allow researchers to explore the collated data and integrate it with existing OA and skeletal gene expression data.

CONCLUSIONS

We present a comprehensive survey and online resource for understanding gene regulation of animal model OA pathogenesis.

Genome-wide association of phenotypes based on clustering patterns of hand osteoarthritis identify WNT9A as novel osteoarthritis gene

BACKGROUND

Despite recent advances in the understanding of the genetic architecture of osteoarthritis (OA), only two genetic loci have been identified for OA of the hand, in part explained by the complexity of the different hand joints and heterogeneity of OA pathology.

METHODS

We used data from the Rotterdam Study (RSI, RSII and RSIII) to create three hand OA phenotypes based on clustering patterns of radiographic OA severity to increase power in our modest discovery genome-wide association studies in the RS (n=8700), and sought replication in an independent cohort, the Framingham Heart Study (n=1203). We used multiple approaches that leverage different levels of information and functional data to further investigate the underlying biological mechanisms and candidate genes for replicated loci. We also attempted to replicate known OA loci at other joint sites, including the hips and knees.

RESULTS

We found two novel genome-wide significant loci for OA in the thumb joints. We identified WNT9A as a possible novel causal gene involved in OA pathogenesis. Furthermore, several previously identified genetic loci for OA seem to confer risk for OA across multiple joints: TGFa, RUNX2, COL27A1, ASTN2, IL11 and GDF5 loci.

CONCLUSIONS

We identified a robust novel genetic locus for hand OA on chromosome 1, of which WNT9A is the most likely causal gene. In addition, multiple genetic loci were identified to be associated with OA across multiple joints. Our study confirms the potential for novel insight into the genetic architecture of OA by using biologically meaningful stratified phenotypes.

A molecular quantitative trait locus map for osteoarthritis

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

Accelerating functional gene discovery in osteoarthritis

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

Identification of abnormally methylated-differentially expressed genes and pathways in osteoarthritis: a comprehensive bioinformatic study

OBJECTIVES

To investigate abnormally methylated-differentially expressed genes (DEGs) and their related pathways in osteoarthritis (OA) by comprehensive bioinformatic analysis.

METHODS

Gene expression profiles of GSE51588 and GSE114007, and a gene methylation microarray data GSE63695 were downloaded from the Gene Expression Omnibus (GEO) repository. Abnormally methylated DEGs were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of these genes were subsequently performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction (PPI) network was built from STRING. Module analysis and hub gene identification were performed by using Cytoscape. Co-expression analysis was also constructed using the CEMiTool package.

RESULTS

In total, 133 abnormally methylated DEGs were identified, including 85 hypomethylation high-expression genes and 48 hypermethylation low-expression genes. Among biological processes and KEGG pathways of abnormally methylated DEGs, collagen fibril organization was enriched most frequently, and pathways of oxidative stress and aging were enriched, including HIF-1 signaling pathway, AMPK signaling pathway, and FoxO signaling pathway. In PPI networks, the hub genes of hypomethylation high-expression genes were COL1A1, COL3A1, COL1A2, COL5A2, LUM, MMP2, SPARC, COL2A1, COL6A2, and COL7A1, and the hub genes of hypermethylation low-expression genes were VEGFA, SLC2A1, LDHA, PDK1, and BNIP3. Combined with co-expression analysis, COL3A1, LUM, and MMP2 were the critical hypomethylation high-expression hub genes in medial tibia subchondral bone.

CONCLUSIONS

Our study implied abnormally methylated DEGs and dysregulated pathways in OA. Common methylation biomarkers included COL3A1, LUM, and MMP2, and we also found that THBS2 may serve as a novel biomarker in end-stage OA. Key Points • Abnormally methylated differentially expressed genes regulate osteoarthritis. • Hypomethylation high-expression genes were related to the extracellular matrix. • Hypermethylation low-expression genes were related to oxidative stress and aging. • COL3A1, LUM, and MMP2 were potential methylation biomarkers for osteoarthritis.