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
Aims. To assess the effect of physical exercise (PE) on the histological and transcriptional characteristics of proteoglycan-induced arthritis (PGIA) in BALB/c mice. Methods. Following PGIA, mice were subjected to treadmill PE for ten weeks. The tarsal joints were used for histological and genetic analysis through
Aims. This study explored the shared genetic traits and molecular interactions between postmenopausal osteoporosis (POMP) and sarcopenia, both of which substantially degrade elderly health and quality of life. We hypothesized that these motor system diseases overlap in pathophysiology and regulatory mechanisms. Methods. We analyzed
Objectives. Diabetes mellitus (DM) is known to impair fracture healing. Increasing evidence suggests that some microRNA (miRNA) is involved in the pathophysiology of diabetes and its complications. We hypothesized that the functions of miRNA and changes to their patterns of expression may be implicated in the pathogenesis of impaired fracture healing in DM. Methods. Closed transverse fractures were created in the femurs of 116 rats, with half assigned to the DM group and half assigned to the control group. Rats with DM were induced by a single intraperitoneal injection of streptozotocin. At post-fracture days five, seven, 11, 14, 21, and 28, miRNA was extracted from the newly generated tissue at the fracture site.
Objectives. MicroRNAs (miRNAs) have been reported as key regulators of bone formation, signalling, and repair. Fracture healing is a proliferative physiological process where the body facilitates the repair of a bone fracture. The aim of our study was to explore the effects of microRNA-186 (miR-186) on fracture healing through the bone morphogenetic protein (BMP) signalling pathway by binding to Smad family member 6 (SMAD6) in a mouse model of femoral fracture. Methods.
Objectives. Osteoporosis is a metabolic disease resulting in progressive loss of bone mass as measured by bone mineral density (BMD). Physical exercise has a positive effect on increasing or maintaining BMD in postmenopausal women. The contribution of exercise to the regulation of osteogenesis in osteoblasts remains unclear. We therefore investigated the effect of exercise on osteoblasts in ovariectomized mice. Methods. We compared the activity of differentially expressed genes of osteoblasts in ovariectomized mice that undertook exercise (OVX+T) with those that did not (OVX), using
Objectives. Osteoporosis is a chronic disease. The aim of this study was to identify key genes in osteoporosis. Methods.
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
Objectives. We have previously investigated an association between the genome copy number variation (CNV) and acetabular dysplasia (AD). Hip osteoarthritis is associated with a genetic polymorphism in the aspartic acid repeat in the N-terminal region of the asporin (ASPN) gene; therefore, the present study aimed to investigate whether the CNV of ASPN is involved in the pathogenesis of AD. Methods. Acetabular coverage of all subjects was evaluated using radiological findings (Sharp angle, centre-edge (CE) angle, acetabular roof obliquity (ARO) angle, and minimum joint space width). Genomic DNA was extracted from peripheral blood leukocytes. Agilent’s region-targeted high-density oligonucleotide tiling
Aims. Animal models have been developed that allow simulation of post-traumatic joint contracture. One such model involves contracture-forming surgery followed by surgical capsular release. This model allows testing of antifibrotic agents, such as rosiglitazone. Methods. A total of 20 rabbits underwent contracture-forming surgery. Eight weeks later, the animals underwent a surgical capsular release. Ten animals received rosiglitazone (intramuscular initially, then orally). The animals were sacrificed following 16 weeks of free cage mobilisation. The joints were tested biomechanically, and the posterior capsule was assessed histologically and via genetic
Objectives. The goal of this study was to determine whether intra-articular
administration of the potentially anti-fibrotic agent decorin influences
the expression of genes involved in the fibrotic cascade, and ultimately
leads to less contracture, in an animal model. Methods. A total of 18 rabbits underwent an operation on their right knees
to form contractures. Six limbs in group 1 received four intra-articular
injections of decorin; six limbs in group 2 received four intra-articular
injections of bovine serum albumin (BSA) over eight days; six limbs
in group 3 received no injections. The contracted limbs of rabbits
in group 1 were biomechanically and genetically compared with the
contracted limbs of rabbits in groups 2 and 3, with the use of a
calibrated joint measuring device and custom
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
Methods
Knee osteoarthritis (OA) involves a variety of tissues in the joint. Gene expression profiles in different tissues are of great importance in order to understand OA. First, we obtained gene expression profiles of cartilage, synovium, subchondral bone, and meniscus from the Gene Expression Omnibus (GEO). Several datasets were standardized by merging and removing batch effects. Then, we used unsupervised clustering to divide OA into three subtypes. The gene ontology and pathway enrichment of three subtypes were analyzed. CIBERSORT was used to evaluate the infiltration of immune cells in different subtypes. Finally, OA-related genes were obtained from the Molecular Signatures Database for validation, and diagnostic markers were screened according to clinical characteristics. Quantitative reverse transcription polymerase chain reaction (qRT‐PCR) was used to verify the effectiveness of markers.Aims
Methods
Long non-coding RNAs (lncRNAs) act as crucial regulators in osteoporosis (OP). Nonetheless, the effects and potential molecular mechanism of lncRNA PCBP1 Antisense RNA 1 (PCBP1-AS1) on OP remain largely unclear. The aim of this study was to explore the role of lncRNA PCBP1-AS1 in the pathogenesis of OP. Using quantitative real-time polymerase chain reaction (qRT-PCR), osteogenesis-related genes (alkaline phosphatase (ALP), osteocalcin (OCN), osteopontin (OPN), and Runt-related transcription factor 2 (RUNX2)), PCBP1-AS1, microRNA (miR)-126-5p, group I Pak family member p21-activated kinase 2 (PAK2), and their relative expression levels were determined. Western blotting was used to examine the expression of PAK2 protein. Cell Counting Kit-8 (CCK-8) assay was used to measure cell proliferation. To examine the osteogenic differentiation, Alizarin red along with ALP staining was used. RNA immunoprecipitation assay and bioinformatics analysis, as well as a dual-luciferase reporter, were used to study the association between PCBP1-AS1, PAK2, and miR-126-5p.Aims
Methods
This study aimed, through bioinformatics analysis and in vitro experiment validation, to identify the key extracellular proteins of intervertebral disc degeneration (IDD). The gene expression profile of GSE23130 was downloaded from the Gene Expression Omnibus (GEO) database. Extracellular protein-differentially expressed genes (EP-DEGs) were screened by protein annotation databases, and we used Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) to analyze the functions and pathways of EP-DEGs. STRING and Cytoscape were used to construct protein-protein interaction (PPI) networks and identify hub EP-DEGs. NetworkAnalyst was used to analyze transcription factors (TFs) and microRNAs (miRNAs) that regulate hub EP-DEGs. A search of the Drug Signatures Database (DSigDB) for hub EP-DEGs revealed multiple drug molecules and drug-target interactions.Aims
Methods
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
Methods
Osteoarthritis (OA) is a common degenerative joint disease worldwide, which is characterized by articular cartilage lesions. With more understanding of the disease, OA is considered to be a disorder of the whole joint. However, molecular communication within and between tissues during the disease process is still unclear. In this study, we used transcriptome data to reveal crosstalk between different tissues in OA. We used four groups of transcription profiles acquired from the Gene Expression Omnibus database, including articular cartilage, meniscus, synovium, and subchondral bone, to screen differentially expressed genes during OA. Potential crosstalk between tissues was depicted by ligand-receptor pairs.Aims
Methods
This study examined the relationship between obesity (OB) and osteoporosis (OP), aiming to identify shared genetic markers and molecular mechanisms to facilitate the development of therapies that target both conditions simultaneously. Using weighted gene co-expression network analysis (WGCNA), we analyzed datasets from the Gene Expression Omnibus (GEO) database to identify co-expressed gene modules in OB and OP. These modules underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction analysis to discover Hub genes. Machine learning refined the gene selection, with further validation using additional datasets. Single-cell analysis emphasized specific cell subpopulations, and enzyme-linked immunosorbent assay (ELISA), protein blotting, and cellular staining were used to investigate key genes.Aims
Methods
This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue. The gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by R software. Functional enrichment analyses were performed and protein-protein interaction networks (PPI) were constructed. Then the hub genes were screened. Biomarkers with high value for the diagnosis of early osteoarthritis (OA) were validated by GEO datasets. Finally, the CIBERSORT algorithm was used to evaluate the immune infiltration between early-stage OA and end-stage OA, and the correlation between the diagnostic marker and infiltrating immune cells was analyzed.Aims
Methods
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
Methods
