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Aims

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.

Methods

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.


Bone & Joint Research
Vol. 13, Issue 10 | Pages 559 - 572
8 Oct 2024
Wu W Zhao Z Wang Y Liu M Zhu G Li L

Aims

This study aimed to demonstrate the promoting effect of elastic fixation on fracture, and further explore its mechanism at the gene and protein expression levels.

Methods

A closed tibial fracture model was established using 12 male Japanese white rabbits, and divided into elastic and stiff fixation groups based on different fixation methods. Two weeks after the operation, a radiograph and pathological examination of callus tissue were used to evaluate fracture healing. Then, the differentially expressed proteins (DEPs) were examined in the callus using proteomics. Finally, in vitro cell experiments were conducted to investigate hub proteins involved in this process.


Bone & Joint Research
Vol. 13, Issue 9 | Pages 474 - 484
10 Sep 2024
Liu Y Li X Jiang L Ma J

Aims

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.

Methods

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.


Bone & Joint Research
Vol. 13, Issue 5 | Pages 237 - 246
17 May 2024
Cheng B Wu C Wei W Niu H Wen Y Li C Chen P Chang H Yang Z Zhang F

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.


Bone & Joint Research
Vol. 13, Issue 2 | Pages 66 - 82
5 Feb 2024
Zhao D Zeng L Liang G Luo M Pan J Dou Y Lin F Huang H Yang W Liu J

Aims

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.

Methods

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.


Bone & Joint Research
Vol. 13, Issue 2 | Pages 52 - 65
1 Feb 2024
Yao C Sun J Luo W Chen H Chen T Chen C Zhang B Zhang Y

Aims

To investigate the effects of senescent osteocytes on bone homeostasis in the progress of age-related osteoporosis and explore the underlying mechanism.

Methods

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.


Bone & Joint Research
Vol. 12, Issue 12 | Pages 702 - 711
1 Dec 2023
Xue Y Zhou L Wang J

Aims. 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. Methods. 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. Results. C1 subtype is mainly concentrated in the development of skeletal muscle organs, C2 lies in metabolic process and immune response, and C3 in pyroptosis and cell death process. Therefore, we divided OA into three subtypes: bone remodelling subtype (C1), immune metabolism subtype (C2), and cartilage degradation subtype (C3). The number of macrophage M0 and activated mast cells of C2 subtype was significantly higher than those of the other two subtypes. COL2A1 has significant differences in different subtypes. The expression of COL2A1 is related to age, and trafficking protein particle complex subunit 2 is related to the sex of OA patients. Conclusion. This study linked different tissues with gene expression profiles, revealing different molecular subtypes of patients with knee OA. The relationship between clinical characteristics and OA-related genes was also studied, which provides a new concept for the diagnosis and treatment of OA. Cite this article: Bone Joint Res 2023;12(12):702–711


Bone & Joint Research
Vol. 12, Issue 9 | Pages 522 - 535
4 Sep 2023
Zhang G Li L Luo Z Zhang C Wang Y Kang X

Aims. This study aimed, through bioinformatics analysis and in vitro experiment validation, to identify the key extracellular proteins of intervertebral disc degeneration (IDD). Methods. 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. Results. A total of 56 EP-DEGs were identified in the differential expression analysis. EP-DEGs were enriched in the extracellular structure organization, ageing, collagen-activated signalling pathway, PI3K-Akt signalling pathway, and AGE-RAGE signalling pathway. PPI network analysis showed that the top ten hub EP-DEGs are closely related to IDD. Correlation analysis also demonstrated a significant correlation between the ten hub EP-DEGs (p<0.05), which were selected to construct TF–gene interaction and TF–miRNA coregulatory networks. In addition, ten candidate drugs were screened for the treatment of IDD. Conclusion. The findings clarify the roles of extracellular proteins in IDD and highlight their potential as promising novel therapeutic targets. Cite this article: Bone Joint Res 2023;12(9):522–535


Bone & Joint Research
Vol. 12, Issue 7 | Pages 433 - 446
7 Jul 2023
Guo L Guo H Zhang Y Chen Z Sun J Wu G Wang Y Zhang Y Wei X Li P

Aims. To explore the novel molecular mechanisms of histone deacetylase 4 (HDAC4) in chondrocytes via RNA sequencing (RNA-seq) analysis. Methods. Empty adenovirus (EP) and a HDAC4 overexpression adenovirus were transfected into cultured human chondrocytes. The cell survival rate was examined by real-time cell analysis (RTCA) and EdU and flow cytometry assays. Cell biofunction was detected by Western blotting. The expression profiles of messenger RNAs (mRNAs) in the EP and HDAC4 transfection groups were assessed using whole-transcriptome sequencing (RNA-seq). Volcano plot, Gene Ontology, and pathway analyses were performed to identify differentially expressed genes (DEGs). For verification of the results, the A289E/S246/467/632 A sites of HDAC4 were mutated to enhance the function of HDAC4 by increasing HDAC4 expression in the nucleus. RNA-seq was performed to identify the molecular mechanism of HDAC4 in chondrocytes. Finally, the top ten DEGs associated with ribosomes were verified by quantitative polymerase chain reaction (QPCR) in chondrocytes, and the top gene was verified both in vitro and in vivo. Results. HDAC4 markedly improved the survival rate and biofunction of chondrocytes. RNA-seq analysis of the EP and HDAC4 groups showed that HDAC4 induced 2,668 significant gene expression changes in chondrocytes (1,483 genes upregulated and 1,185 genes downregulated, p < 0.05), and ribosomes exhibited especially large increases. The results were confirmed by RNA-seq of the EP versus mutated HDAC4 groups and the validations in vitro and in vivo. Conclusion. The enhanced ribosome pathway plays a key role in the mechanism by which HDAC4 improves the survival rate and biofunction of chondrocytes. Cite this article: Bone Joint Res 2023;12(7):433–446


Bone & Joint Research
Vol. 12, Issue 6 | Pages 387 - 396
26 Jun 2023
Xu J Si H Zeng Y Wu Y Zhang S Shen B

Aims. 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. Methods. 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. Results. TWAS identified 295 genes with permutation p-values < 0.05 for skeletal muscle and 79 genes associated for the whole blood, such as RCHY1 (PTWAS = 0.001). Those genes were enriched in 112 gene ontology (GO) terms and five Kyoto Encyclopedia of Genes and Genomes pathways, such as ‘chemical carcinogenesis - reactive oxygen species’ (LogP value = −2.139). Further comparing the TWAS significant genes with the differentially expressed genes identified by mRNA expression profiles of LSS found 18 overlapped genes, such as interleukin 15 receptor subunit alpha (IL15RA) (PTWAS = 0.040, PmRNA = 0.010). Moreover, 71 common GO terms were detected for the enrichment results of TWAS and mRNA expression profiles, such as negative regulation of cell differentiation (LogP value = −2.811). Conclusion. This study revealed the genetic mechanism behind the pathological changes in LSS, and may provide novel insights for the early diagnosis and intervention of LSS. Cite this article: Bone Joint Res 2023;12(6):387–396


Bone & Joint Research
Vol. 12, Issue 4 | Pages 274 - 284
11 Apr 2023
Du X Jiang Z Fang G Liu R Wen X Wu Y Hu S Zhang Z

Aims

This study aimed to investigate the role and mechanism of meniscal cell lysate (MCL) in fibroblast-like synoviocytes (FLSs) and osteoarthritis (OA).

Methods

Meniscus and synovial tissue were collected from 14 patients with and without OA. MCL and FLS proteins were extracted and analyzed by liquid chromatography‒mass spectrometry (LC‒MS). The roles of MCL and adenine nucleotide translocase 3 (ANT3) in FLSs were examined by enzyme-linked immunosorbent assay (ELISA), flow cytometry, immunofluorescence, and transmission electron microscopy. Histological analysis was performed to determine ANT3 expression levels in a male mouse model.


Bone & Joint Research
Vol. 12, Issue 4 | Pages 259 - 273
6 Apr 2023
Lu R Wang Y Qu Y Wang S Peng C You H Zhu W Chen A

Aims

Osteoarthritis (OA) is a prevalent joint disorder with inflammatory response and cartilage deterioration as its main features. Dihydrocaffeic acid (DHCA), a bioactive component extracted from natural plant (gynura bicolor), has demonstrated anti-inflammatory properties in various diseases. We aimed to explore the chondroprotective effect of DHCA on OA and its potential mechanism.

Methods

In vitro, interleukin-1 beta (IL-1β) was used to establish the mice OA chondrocytes. Cell counting kit-8 evaluated chondrocyte viability. Western blotting analyzed the expression levels of collagen II, aggrecan, SOX9, inducible nitric oxide synthase (iNOS), IL-6, matrix metalloproteinases (MMPs: MMP1, MMP3, and MMP13), and signalling molecules associated with nuclear factor-kappa B (NF-κB) and mitogen-activated protein kinase (MAPK) pathways. Immunofluorescence analysis assessed the expression of aggrecan, collagen II, MMP13, and p-P65. In vivo, a destabilized medial meniscus (DMM) surgery was used to induce mice OA knee joints. After injection of DHCA or a vehicle into the injured joints, histological staining gauged the severity of cartilage damage.


Bone & Joint Research
Vol. 12, Issue 2 | Pages 147 - 154
20 Feb 2023
Jia Y Qi X Ma M Cheng S Cheng B Liang C Guo X Zhang F

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 discovery GWAS dataset and replication GWAS dataset were integrated with rSNP annotation database to obtain BMD associated SNP regulatory elements and SNP regulatory element-target gene (E-G) pairs, respectively. Then, the common genes were further subjected to HumanNet v2 to explore the biological effects. Results. Through discovery and replication integrative analysis for BMD GWAS and rSNP annotation database, we identified 36 common BMD-associated genes for BMD irrespective of regulatory elements, such as FAM3C (p. discovery GWAS. = 1.21 × 10. -25. , p. replication GWAS. = 1.80 × 10. -12. ), CCDC170 (p. discovery GWAS. = 1.23 × 10. -11. , p. replication GWAS. = 3.22 × 10. -9. ), and SOX6 (p. discovery GWAS. = 4.41 × 10. -15. , p. replication GWAS. = 6.57 × 10. -14. ). Then, for the 36 common target genes, multiple gene ontology (GO) terms were detected for BMD such as positive regulation of cartilage development (p = 9.27 × 10. -3. ) and positive regulation of chondrocyte differentiation (p = 9.27 × 10. -3. ). Conclusion. We explored the potential roles of rSNP in the genetic mechanisms of BMD and identified multiple candidate genes. Our study results support the implication of regulatory genetic variants in the development of OP. Cite this article: Bone Joint Res 2023;12(2):147–154


Bone & Joint Research
Vol. 12, Issue 2 | Pages 91 - 102
1 Feb 2023
Li Z Chen M Wang Z Fan Q Lin Z Tao X Wu J Liu Z Lin R Zhao C

Aims

Rheumatoid arthritis (RA) is a common chronic immune disease. Berberine, as its main active ingredient, was also contained in a variety of medicinal plants such as Berberaceae, Buttercup, and Rutaceae, which are widely used in digestive system diseases in traditional Chinese medicine with anti-inflammatory and antibacterial effects. The aims of this article were to explore the therapeutic effect and mechanism of berberine on rheumatoid arthritis.

Methods

Cell Counting Kit-8 was used to evaluate the effect of berberine on the proliferation of RA fibroblast-like synoviocyte (RA-FLS) cells. The effect of berberine on matrix metalloproteinase (MMP)-1, MMP-3, receptor activator of nuclear factor kappa-Β ligand (RANKL), tumour necrosis factor alpha (TNF-α), and other factors was determined by enzyme-linked immunoassay (ELISA) kit. Transcriptome technology was used to screen related pathways and the potential targets after berberine treatment, which were verified by reverse transcription-polymerase chain reaction (RT-qPCR) and Western blot (WB) technology.


Bone & Joint Research
Vol. 12, Issue 1 | Pages 80 - 90
20 Jan 2023
Xu J Si H Zeng Y Wu Y Zhang S Liu Y Li M Shen B

Aims. 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. Methods. 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. Results. The TWAS detected 420 DCS genes with p < 0.05 in skeletal muscle, such as ribosomal protein S15A (RPS15A) (PTWAS = 0.001), and 110 genes in whole blood, such as selectin L (SELL) (PTWAS = 0.001). Comparison with the DCS RNA expression profile identified 12 common genes, including Apelin Receptor (APLNR) (PTWAS = 0.001, PDEG = 0.025). In total, 148 DCS-enriched Gene Ontology (GO) terms were identified, such as mast cell degranulation (GO:0043303); 15 DCS-enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified, such as the sphingolipid signalling pathway (ko04071). Nine terms, such as degradation of the extracellular matrix (R-HSA-1474228), were common to the TWAS enrichment results and the RNA expression profile. Conclusion. Our results identify putative susceptibility genes; these findings provide new ideas for exploration of the genetic mechanism of DCS development and new targets for preclinical intervention and clinical treatment. Cite this article: Bone Joint Res 2023;12(1):80–90


Bone & Joint Research
Vol. 11, Issue 12 | Pages 843 - 853
1 Dec 2022
Cai Y Huang C Chen X Chen Y Huang Z Zhang C Zhang W Fang X

Aims. This study aimed to explore the role of small colony variants (SCVs) of Staphylococcus aureus in intraosseous invasion and colonization in patients with periprosthetic joint infection (PJI). Methods. A PJI diagnosis was made according to the MusculoSkeletal Infection Society (MSIS) for PJI. Bone and tissue samples were collected intraoperatively and the intracellular invasion and intraosseous colonization were detected. Transcriptomics of PJI samples were analyzed and verified by polymerase chain reaction (PCR). Results. SCVs can be isolated from samples collected from chronic PJIs intraoperatively. Transmission electron microscopy (TEM) and immunofluorescence (IF) showed that there was more S. aureus in bone samples collected from chronic PJIs, but much less in bone samples from acute PJIs, providing a potential mechanism of PJI. Immunofluorescence results showed that SCVs of S. aureus were more likely to invade osteoblasts in vitro. Furthermore, TEM and IF also demonstrated that SCVs of S. aureus were more likely to invade and colonize in vivo. Cluster analysis and principal component analysis (PCA) showed that there were substantial differences in gene expression profiles between chronic and acute PJI. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these differentially expressed genes were enriched to chemokine-related signal pathways. PCR also verified these results. Conclusion. Our study has shown that the S. aureus SCVs have a greater ability to invade and colonize in bone, resulting in S. aureus remaining in bone tissues long-term, thus explaining the pathogenesis of chronic PJI. Cite this article: Bone Joint Res 2022;11(12):843–853


Bone & Joint Research
Vol. 11, Issue 12 | Pages 862 - 872
1 Dec 2022
Wang M Tan G Jiang H Liu A Wu R Li J Sun Z Lv Z Sun W Shi D

Aims. 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. Methods. 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. Results. During OA, there were 626, 97, 1,060, and 2,330 differentially expressed genes in articular cartilage, meniscus, synovium, and subchondral bone, respectively. Gene Ontology enrichment revealed that these genes were enriched in extracellular matrix and structure organization, ossification, neutrophil degranulation, and activation at different degrees. Through ligand-receptor pairing and proteome of OA synovial fluid, we predicted ligand-receptor interactions and constructed a crosstalk atlas of the whole joint. Several interactions were reproduced by transwell experiment in chondrocytes and synovial cells, including TNC-NT5E, TNC-SDC4, FN1-ITGA5, and FN1-NT5E. After lipopolysaccharide (LPS) or interleukin (IL)-1β stimulation, the ligand expression of chondrocytes and synovial cells was upregulated, and corresponding receptors of co-culture cells were also upregulated. Conclusion. Each tissue displayed a different expression pattern in transcriptome, demonstrating their specific roles in OA. We highlighted tissue molecular crosstalk through ligand-receptor pairs in OA pathophysiology, and generated a crosstalk atlas. Strategies to interfere with these candidate ligands and receptors may help to discover molecular targets for future OA therapy. Cite this article: Bone Joint Res 2022;11(12):862–872


Aims. This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue. Methods. 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. Results. A total of 88 DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that DEGs were significantly enriched in leucocyte migration and interleukin (IL)-17 signalling pathways. Disease ontology (DO) indicated that DEGs were mostly enriched in rheumatoid arthritis. Six hub genes including FosB proto-oncogene, AP-1 transcription factor subunit (FOSB); C-X-C motif chemokine ligand 2 (CXCL2); CXCL8; IL-6; Jun proto-oncogene, AP-1 transcription factor subunit (JUN); and Activating transcription factor 3 (ATF3) were identified and verified by GEO datasets. ATF3 (area under the curve = 0.975) turned out to be a potential biomarker for the diagnosis of early OA. Several infiltrating immune cells varied significantly between early-stage OA and end-stage OA, such as resting NK cells (p = 0.016), resting dendritic cells (p = 0.043), and plasma cells (p = 0.043). Additionally, ATF3 was significantly correlated with resting NK cells (p = 0.034), resting dendritic cells (p = 0.026), and regulatory T cells (Tregs, p = 0.018). Conclusion. ATF3 may be a potential diagnostic marker for early diagnosis and treatment of OA, and immune cell infiltration provides new perspectives for understanding the mechanism during OA progression. Cite this article: Bone Joint Res 2022;11(9):679–689


Bone & Joint Research
Vol. 11, Issue 8 | Pages 548 - 560
17 Aug 2022
Yuan W Yang M Zhu Y

Aims. We aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism. Methods. Five datasets were obtained from the Gene Expression Omnibus database. Unsupervised consensus cluster analysis was used to determine new PMOP subtypes. To determine the central genes and the core modules related to PMOP, the weighted gene co-expression network analysis (WCGNA) was applied. Gene Ontology enrichment analysis was used to explore the biological processes underlying key genes. Logistic regression univariate analysis was used to screen for statistically significant variables. Two algorithms were used to select important PMOP-related genes. A logistic regression model was used to construct the PMOP-related gene profile. The receiver operating characteristic area under the curve, Harrell’s concordance index, a calibration chart, and decision curve analysis were used to characterize PMOP-related genes. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of the PMOP-related genes in the gene signature. Results. We identified three PMOP-related subtypes and four core modules. The muscle system process, muscle contraction, and actin filament-based movement were more active in the hub genes. We obtained five feature genes related to PMOP. Our analysis verified that the gene signature had good predictive power and applicability. The outcomes of the GSE56815 cohort were found to be consistent with the results of the earlier studies. qRT-PCR results showed that RAB2A and FYCO1 were amplified in clinical samples. Conclusion. The PMOP-related gene signature we developed and verified can accurately predict the risk of PMOP in patients. These results can elucidate the molecular mechanism of RAB2A and FYCO1 underlying PMOP, and yield new and improved treatment strategies, ultimately helping PMOP monitoring. Cite this article: Bone Joint Res 2022;11(8):548–560


Bone & Joint Research
Vol. 11, Issue 6 | Pages 362 - 370
9 Jun 2022
Zhou J He Z Cui J Liao X Cao H Shibata Y Miyazaki T Zhang J

Aims

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.

Methods

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.