Objectives. Osteoporosis is a chronic disease. The aim of this study was to identify key genes in osteoporosis. Methods. Microarray data sets GSE56815 and GSE56814, comprising 67 osteoporosis blood samples and 62 control blood samples, were obtained from the Gene Expression Omnibus database.
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 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
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
Degenerative cervical spondylosis (DCS) is a common musculoskeletal disease that encompasses a wide range of progressive degenerative changes and affects all components of the cervical spine. DCS imposes very large social and economic burdens. However, its genetic basis remains elusive. Predicted whole-blood and skeletal muscle gene expression and genome-wide association study (GWAS) data from a DCS database were integrated, and functional summary-based imputation (FUSION) software was used on the integrated data. A transcriptome-wide association study (TWAS) was conducted using FUSION software to assess the association between predicted gene expression and DCS risk. The TWAS-identified genes were verified via comparison with differentially expressed genes (DEGs) in DCS RNA expression profiles in the Gene Expression Omnibus (GEO) (Accession Number: GSE153761). The Functional Mapping and Annotation (FUMA) tool for genome-wide association studies and Meta tools were used for gene functional enrichment and annotation analysis.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
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. 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.Objectives
Methods
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
Methods
To investigate the effects of senescent osteocytes on bone homeostasis in the progress of age-related osteoporosis and explore the underlying mechanism. In a series of in vitro experiments, we used tert-Butyl hydroperoxide (TBHP) to induce senescence of MLO-Y4 cells successfully, and collected conditioned medium (CM) and senescent MLO-Y4 cell-derived exosomes, which were then applied to MC3T3-E1 cells, separately, to evaluate their effects on osteogenic differentiation. Furthermore, we identified differentially expressed microRNAs (miRNAs) between exosomes from senescent and normal MLO-Y4 cells by high-throughput RNA sequencing. Based on the key miRNAs that were discovered, the underlying mechanism by which senescent osteocytes regulate osteogenic differentiation was explored. Lastly, in the in vivo experiments, the effects of senescent MLO-Y4 cell-derived exosomes on age-related bone loss were evaluated in male SAMP6 mice, which excluded the effects of oestrogen, and the underlying mechanism was confirmed.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
Exosomes (exo) are involved in the progression of osteoarthritis (OA). This study aimed to investigate the function of dysfunctional chondrocyte-derived exo (DC-exo) on OA in rats and rat macrophages. Rat-derived chondrocytes were isolated, and DCs induced with interleukin (IL)-1β were used for exo isolation. Rats with OA (n = 36) or macrophages were treated with DC-exo or phosphate-buffered saline (PBS). Macrophage polarization and autophagy, and degradation and chondrocyte activity of cartilage tissues, were examined. RNA sequencing was used to detect genes differentially expressed in DC-exo, followed by RNA pull-down and ribonucleoprotein immunoprecipitation (RIP). Long non-coding RNA osteoarthritis non-coding transcript (OANCT) and phosphoinositide-3-kinase regulatory subunit 5 (PIK3R5) were depleted in DC-exo-treated macrophages and OA rats, in order to observe macrophage polarization and cartilage degradation. The PI3K/AKT/mammalian target of rapamycin (mTOR) pathway activity in cells and tissues was measured using western blot.Aims
Methods
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. 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).Aims
Methods
Acquired heterotopic ossification (HO) is a debilitating disease characterized by abnormal extraskeletal bone formation within soft-tissues after injury. The exact pathogenesis of HO remains unknown. It was reported that Achilles tendon puncture (ATP) mouse model was performed on ten-week-old male C57BL/6J mice. One week after ATP procedure, the mice were given different treatments (e.g. JQ1, shMancr). Achilles tendon samples were collected five weeks after treatment for RNA-seq and real-time quantitative polymerase chain reaction (RT-qPCR) analysis; the legs were removed for micro-CT imaging and subsequent histology. Human bone marrow mesenchymal stem cells (hBMSCs) were isolated and purified bone marrow collected during surgeries by using density gradient centrifugation. After a series of interventions such as knockdown or overexpressing Aims
Methods
Osteoarthritis (OA) is the most prevalent joint disease. However, the specific and definitive genetic mechanisms of OA are still unclear. Tissue-related transcriptome-wide association studies (TWAS) of hip OA and knee OA were performed utilizing the genome-wide association study (GWAS) data of hip OA and knee OA (including 2,396 hospital-diagnosed hip OA patients versus 9,593 controls, and 4,462 hospital-diagnosed knee OA patients versus 17,885 controls) and gene expression reference to skeletal muscle and blood. The OA-associated genes identified by TWAS were further compared with the differentially expressed genes detected by the messenger RNA (mRNA) expression profiles of hip OA and knee OA. Functional enrichment and annotation analysis of identified genes was performed by the DAVID and FUMAGWAS tools.Aims
Methods
The aim of this study was to provide a comprehensive understanding of alterations in messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) in cartilage affected by osteoarthritis (OA). The expression profiles of mRNAs, lncRNAs, and circRNAs in OA cartilage were assessed using whole-transcriptome sequencing. Bioinformatics analyses included prediction and reannotation of novel lncRNAs and circRNAs, their classification, and their placement into subgroups. Gene ontology and pathway analysis were performed to identify differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs), and differentially expressed circRNAs (DECs). We focused on the overlap of DEGs and targets of DELs previously identified in seven high-throughput studies. The top ten DELs were verified by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) in articular chondrocytes, both Objectives
Methods
Rheumatoid arthritis (RA) is a systematic autoimmune disorder, characterized by synovial inflammation, bone and cartilage destruction, and disease involvement in multiple organs. Although numerous drugs are employed in RA treatment, some respond little and suffer from severe side effects. This study aimed to screen the candidate therapeutic targets and promising drugs in a novel method. We developed a module-based and cumulatively scoring approach that is a deeper-layer application of weighted gene co-expression network (WGCNA) and connectivity map (CMap) based on the high-throughput datasets.Aims
Methods
To assess the effect of physical exercise (PE) on the histological and transcriptional characteristics of proteoglycan-induced arthritis (PGIA) in BALB/c mice. Following PGIA, mice were subjected to treadmill PE for ten weeks. The tarsal joints were used for histological and genetic analysis through microarray technology. The genes differentially expressed by PE in the arthritic mice were obtained from the microarray experiments. Bioinformatic analysis in the DAVID, STRING, and Cytoscape bioinformatic resources allowed the association of these genes in biological processes and signalling pathways.Aims
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