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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.


Bone & Joint Open
Vol. 1, Issue 7 | Pages 330 - 338
3 Jul 2020
Ajayi B Trompeter A Arnander M Sedgwick P Lui DF

Aims

The first death in the UK caused by COVID-19 occurred on 5 March 2020. We aim to describe the clinical characteristics and outcomes of major trauma and orthopaedic patients admitted in the early COVID-19 era.

Methods

A prospective trauma registry was reviewed at a Level 1 Major Trauma Centre. We divided patients into Group A, 40 days prior to 5 March 2020, and into Group B, 40 days after.


Bone & Joint Research
Vol. 8, Issue 4 | Pages 179 - 188
1 Apr 2019
Chen M Chang C Yang L Hsieh P Shih H Ueng SWN Chang Y

Objectives

Prosthetic joint infection (PJI) diagnosis is a major challenge in orthopaedics, and no reliable parameters have been established for accurate, preoperative predictions in the differential diagnosis of aseptic loosening or PJI. This study surveyed factors in synovial fluid (SF) for improving PJI diagnosis.

Methods

We enrolled 48 patients (including 39 PJI and nine aseptic loosening cases) who required knee/hip revision surgery between January 2016 and December 2017. The PJI diagnosis was established according to the Musculoskeletal Infection Society (MSIS) criteria. SF was used to survey factors by protein array and enzyme-linked immunosorbent assay to compare protein expression patterns in SF among three groups (aseptic loosening and first- and second-stage surgery). We compared routine clinical test data, such as C-reactive protein level and leucocyte number, with potential biomarker data to assess the diagnostic ability for PJI within the same patient groups.


Bone & Joint 360
Vol. 4, Issue 6 | Pages 28 - 29
1 Dec 2015

The December 2015 Research Roundup360 looks at: Biomarkers in periprosthetic joint infection; HbA1c and complications in arthroplasty; Getting to the bottom of biofilms; Effective antibiosis for biofilms; Stem cells and avascular necrosis; Predicting LOS in total joint arthroplasty; Long-term antibiotics reduce recurrence in periprosthetic infection


Bone & Joint 360
Vol. 3, Issue 6 | Pages 10 - 12
1 Dec 2014

The December 2014 Hip & Pelvis Roundup360 looks at: Sports and total hips; topical tranexamic acid and blood conservation in hip replacement; blind spots and biases in hip research; no recurrence in cam lesions at two years; to drain or not to drain?; sonication and diagnosis of implant associated infection; and biomarkers and periprosthetic infection


Bone & Joint 360
Vol. 2, Issue 6 | Pages 2 - 8
1 Dec 2013
Jones R Wood D

This article provides an overview of the role of genomics in sarcomas and describes how new methods of analysis and comparative screening have provided the potential to progress understanding and treatment of sarcoma. This article reviews genomic techniques, the evolution of the use of genomics in cancer, the current state of genomic analysis, and also provides an overview of the medical, social and economic implications of recent genomic advances.


Bone & Joint Research
Vol. 1, Issue 7 | Pages 158 - 166
1 Jul 2012
Dean BJF Franklin SL Carr AJ

Introduction

The pathogenesis of rotator cuff disease (RCD) is complex and not fully understood. This systematic review set out to summarise the histological and molecular changes that occur throughout the spectrum of RCD.

Methods

We conducted a systematic review of the scientific literature with specific inclusion and exclusion criteria.