Aims. Osteoporosis (OP) is a metabolic bone disease, characterized by a decrease in bone mineral density (BMD). However, the research of regulatory variants has been limited for BMD. In this study, we aimed to explore novel regulatory genetic variants associated with BMD. Methods. We conducted an integrative analysis of BMD genome-wide association study (GWAS) and regulatory single nucleotide polymorphism (rSNP) annotation information. Firstly, the
Aims. Impaired fracture repair in patients with type 2 diabetes mellitus (T2DM) is not fully understood. In this study, we aimed to characterize the local changes in gene expression (GE) associated with diabetic fracture. We used an unbiased approach to compare GE in the fracture callus of Zucker diabetic fatty (ZDF) rats relative to wild-type (WT) littermates at three weeks following femoral osteotomy. Methods. Zucker rats, WT and homozygous for leptin receptor mutation (ZDF), were fed a moderately high-fat diet to induce T2DM only in the ZDF animals. At ten weeks of age, open femoral fractures were simulated using a unilateral osteotomy stabilized with an external fixator. At three weeks post-surgery, the fractured femur from each animal was retrieved for analysis. Callus formation and the extent of healing were assessed by radiograph and histology. Bone tissue was processed for total RNA extraction and messenger RNA (mRNA) sequencing (mRNA-Seq). Results. Radiographs and histology demonstrated impaired fracture healing in ZDF rats with incomplete bony bridge formation and an influx of intramedullary inflammatory tissue. In comparison, near-complete bridging between cortices was observed in Sham WT animals. Of 13,160 genes, mRNA-Seq analysis identified 13 that were differentially expressed in ZDF rat callus, using a false
Aims. To assess the alterations in cell-specific DNA methylation associated with chondroitin sulphate response using peripheral blood collected from Kashin-Beck disease (KBD) patients before initiation of chondroitin sulphate treatment. Methods. Peripheral blood samples were collected from KBD patients at baseline of chondroitin sulphate treatment. Methylation profiles were generated using reduced representation bisulphite sequencing (RRBS) from peripheral blood. Differentially methylated regions (DMRs) were identified using MethylKit, while DMR-related genes were defined as those annotated to the gene body or 2.2-kilobase upstream regions of DMRs. Selected DMR-related genes were further validated by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) to assess expression levels. Tensor composition analysis was performed to identify cell-specific differential DNA methylation from bulk tissue. Results. This study revealed 21,060 hypermethylated and 44,472 hypomethylated DMRs, and 13,194 hypermethylated and 22,448 hypomethylated CpG islands for differential global methylation for chondroitin sulphate treatment response. A total of 12,666 DMR-related genes containing DMRs were identified in their promoter regions, such as CHL1 (false
Osteoarthritis (OA) is a chronic degenerative joint disease characterized by progressive cartilage degradation, synovial membrane inflammation, osteophyte formation, and subchondral bone sclerosis. Pathological changes in cartilage and subchondral bone are the main processes in OA. In recent decades, many studies have demonstrated that activin-like kinase 3 (ALK3), a bone morphogenetic protein receptor, is essential for cartilage formation, osteogenesis, and postnatal skeletal development. Although the role of bone morphogenetic protein (BMP) signalling in articular cartilage and bone has been extensively studied, many new
The ability to edit DNA at the nucleotide level using clustered regularly interspaced short palindromic repeats (CRISPR) systems is a relatively new investigative tool that is revolutionizing the analysis of many aspects of human health and disease, including orthopaedic disease. CRISPR, adapted for mammalian cell genome editing from a bacterial defence system, has been shown to be a flexible, programmable, scalable, and easy-to-use gene editing tool. Recent improvements increase the functionality of CRISPR through the engineering of specific elements of CRISPR systems, the
Aims. The aim of this study was to explore the genetic correlation and causal relationship between blood plasma proteins and rheumatoid arthritis (RA). Methods. Based on the genome-wide association studies (GWAS) summary statistics of RA from European descent and the GWAS summary datasets of 3,622 plasma proteins, we explored the relationship between RA and plasma proteins from three aspects. First, linkage disequilibrium score regression (LD score regression) was applied to detect the genetic correlation between RA and plasma proteins. Mendelian randomization (MR) analysis was then used to evaluate the causal association between RA and plasma proteins. Finally, GEO2R was used to screen the differentially expressed genes (DEGs) between patients with RA and healthy controls. Results. We found that seven kinds of plasma proteins had genetic correlations with RA, such as Soluble Receptor for Advanced Glycation End Products (sRAGE) (correlation coefficient = 0.2582, p = 0.049), vesicle transport protein USE1 (correlation coefficient = 0.1337, p = 0.018), and spermatogenesis-associated protein 20 (correlation coefficient = 0.3706, p = 0.018). There was a significant causal relationship between sRAGE and RA. By comparing the genes encoding seven plasma proteins, we found that only USE1 was a DEG associated with RA. Conclusion. Our study identified a set of candidate plasma proteins that showed signals correlated with RA. Since the results of this study need further experimental verification, they should be interpreted with caution. However, we hope that this paper will provide new insights for the
Objectives. Meniscal injuries are often associated with an active lifestyle. The damage of meniscal tissue puts young patients at higher risk of undergoing meniscal surgery and, therefore, at higher risk of osteoarthritis. In this study, we undertook proof-of-concept research to develop a cellularized human meniscus by using 3D bioprinting technology. Methods. A 3D model of bioengineered medial meniscus tissue was created, based on MRI scans of a human volunteer. The Digital Imaging and Communications in Medicine (DICOM) data from these MRI scans were processed using dedicated software, in order to obtain an STL model of the structure. The chosen 3D
Aim. Osteoarthritis (OA) is caused by complex interactions between genetic and environmental factors. Epigenetic mechanisms control the expression of genes and are likely to regulate the OA transcriptome. We performed integrative genomic analyses to define methylation-gene expression relationships in osteoarthritic cartilage. Patients and Methods. Genome-wide DNA methylation profiling of articular cartilage from five patients with OA of the knee and five healthy controls was conducted using the Illumina Infinium HumanMethylation450 BeadChip (Illumina, San Diego, California). Other independent genome-wide mRNA expression profiles of articular cartilage from three patients with OA and three healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Integrative pathway enrichment analysis of DNA methylation and mRNA expression profiles was performed using integrated analysis of cross-platform microarray and pathway software. Gene ontology (GO) analysis was conducted using the Database for Annotation, Visualization and Integrated
Objectives. The molecular mechanism of rheumatoid arthritis (RA) remains elusive. We conducted a protein-protein interaction network-based integrative analysis of genome-wide association studies (GWAS) and gene expression profiles of RA. Methods. We first performed a dense search of RA-associated gene modules by integrating a large GWAS meta-analysis dataset (containing 5539 RA patients and 20 169 healthy controls), protein interaction network and gene expression profiles of RA synovium and peripheral blood mononuclear cells (PBMCs). Gene ontology (GO) enrichment analysis was conducted by DAVID. The protein association networks of gene modules were generated by STRING. Results. For RA synovium, the top-ranked gene module is HLA-A, containing TAP2, HLA-A, HLA-C, TAPBP and LILRB1 genes. For RA PBMCs, the top-ranked gene module is GRB7, consisting of HLA-DRB5, HLA-DRA, GRB7, CD63 and KIT genes. Functional enrichment analysis identified three significant GO terms for RA synovium, including antigen processing and presentation of peptide antigen via major histocompatibility complex class I (false
Objectives. In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. Results. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false
The aims of this study were to identify and evaluate the current literature examining the prognostic factors which are associated with failure of total elbow arthroplasty (TEA). Electronic literature searches were conducted using MEDLINE, Embase, PubMed, and Cochrane. All studies reporting prognostic estimates for factors associated with the revision of a primary TEA were included. The risk of bias was assessed using the Quality In Prognosis Studies (QUIPS) tool, and the quality of evidence was assessed using the modified Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) framework. Due to low quality of the evidence and the heterogeneous nature of the studies, a narrative synthesis was used.Aims
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Rotator cuff tear (RCT) is the leading cause of shoulder pain, primarily associated with age-related tendon degeneration. This study aimed to elucidate the potential differential gene expressions in tendons across different age groups, and to investigate their roles in tendon degeneration. Linear regression and differential expression (DE) analyses were performed on two transcriptome profiling datasets of torn supraspinatus tendons to identify age-related genes. Subsequent functional analyses were conducted on these candidate genes to explore their potential roles in tendon ageing. Additionally, a secondary DE analysis was performed on candidate genes by comparing their expressions between lesioned and normal tendons to explore their correlations with RCTs.Aims
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To explore the novel molecular mechanisms of histone deacetylase 4 (HDAC4) in chondrocytes via RNA sequencing (RNA-seq) analysis. Empty adenovirus (EP) and a Aims
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Transcription factor nuclear factor kappa B (NF-κB) plays a major role in the pathogenesis of chronic inflammatory diseases in all organ systems. Despite its importance, NF-κB targeted drug therapy to mitigate chronic inflammation has had limited success in preclinical studies. We hypothesized that sex differences affect the response to NF-κB treatment during chronic inflammation in bone. This study investigated the therapeutic effects of NF-κB decoy oligodeoxynucleotides (ODN) during chronic inflammation in male and female mice. We used a murine model of chronic inflammation induced by continuous intramedullary delivery of lipopolysaccharide-contaminated polyethylene particles (cPE) using an osmotic pump. Specimens were evaluated using micro-CT and histomorphometric analyses. Sex-specific osteogenic and osteoclastic differentiation potentials were also investigated in vitro, including alkaline phosphatase, Alizarin Red, tartrate-resistant acid phosphatase staining, and gene expression using reverse transcription polymerase chain reaction (RT-PCR).Aims
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The metabolic variations between the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) remain largely unknown. Our study aimed to address this by conducting a comparative analysis of the metabolic profiles present in the cartilage of KBD and OA. Cartilage samples from patients with KBD (n = 10) and patients with OA (n = 10) were collected during total knee arthroplasty surgery. An untargeted metabolomics approach using liquid chromatography coupled with mass spectrometry (LC-MS) was conducted to investigate the metabolomics profiles of KBD and OA. LC-MS raw data files were converted into mzXML format and then processed by the XCMS, CAMERA, and metaX toolbox implemented with R software. The online Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate the metabolites by matching the exact molecular mass data of samples with those from the database.Aims
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This study aimed to explore the biological and clinical importance of dysregulated key genes in osteoarthritis (OA) patients at the cartilage level to find potential biomarkers and targets for diagnosing and treating OA. Six sets of gene expression profiles were obtained from the Gene Expression Omnibus database. Differential expression analysis, weighted gene coexpression network analysis (WGCNA), and multiple machine-learning algorithms were used to screen crucial genes in osteoarthritic cartilage, and genome enrichment and functional annotation analyses were used to decipher the related categories of gene function. Single-sample gene set enrichment analysis was performed to analyze immune cell infiltration. Correlation analysis was used to explore the relationship among the hub genes and immune cells, as well as markers related to articular cartilage degradation and bone mineralization.Aims
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Osteoarthritis (OA) is a common degenerative joint disease. The osteocyte transcriptome is highly relevant to osteocyte biology. This study aimed to explore the osteocyte transcriptome in subchondral bone affected by OA. Gene expression profiles of OA subchondral bone were used to identify disease-relevant genes and signalling pathways. RNA-sequencing data of a bone loading model were used to identify the loading-responsive gene set. Weighted gene co-expression network analysis (WGCNA) was employed to develop the osteocyte mechanics-responsive gene signature.Aims
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This study was designed to develop a model for predicting bone mineral density (BMD) loss of the femur after total hip arthroplasty (THA) using artificial intelligence (AI), and to identify factors that influence the prediction. Additionally, we virtually examined the efficacy of administration of bisphosphonate for cases with severe BMD loss based on the predictive model. The study included 538 joints that underwent primary THA. The patients were divided into groups using unsupervised time series clustering for five-year BMD loss of Gruen zone 7 postoperatively, and a machine-learning model to predict the BMD loss was developed. Additionally, the predictor for BMD loss was extracted using SHapley Additive exPlanations (SHAP). The patient-specific efficacy of bisphosphonate, which is the most important categorical predictor for BMD loss, was examined by calculating the change in predictive probability when hypothetically switching between the inclusion and exclusion of bisphosphonate.Aims
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Lumbar spinal stenosis (LSS) is a common skeletal system disease that has been partly attributed to genetic variation. However, the correlation between genetic variation and pathological changes in LSS is insufficient, and it is difficult to provide a reference for the early diagnosis and treatment of the disease. We conducted a transcriptome-wide association study (TWAS) of spinal canal stenosis by integrating genome-wide association study summary statistics (including 661 cases and 178,065 controls) derived from Biobank Japan, and pre-computed gene expression weights of skeletal muscle and whole blood implemented in FUSION software. To verify the TWAS results, the candidate genes were furthered compared with messenger RNA (mRNA) expression profiles of LSS to screen for common genes. Finally, Metascape software was used to perform enrichment analysis of the candidate genes and common genes.Aims
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