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Bone & Joint Research
Vol. 11, Issue 7 | Pages 426 - 438
20 Jul 2022
Luo P Wang P Xu J Hou W Xu P Xu K Liu L

Rheumatoid arthritis (RA) is an autoimmune disease that involves T and B cells and their reciprocal immune interactions with proinflammatory cytokines. T cells, an essential part of the immune system, play an important role in RA. T helper 1 (Th1) cells induce interferon-γ (IFN-γ), tumour necrosis factor-α (TNF-α), and interleukin (IL)-2, which are proinflammatory cytokines, leading to cartilage destruction and bone erosion. Th2 cells primarily secrete IL-4, IL-5, and IL-13, which exert anti-inflammatory and anti-osteoclastogenic effects in inflammatory arthritis models. IL-22 secreted by Th17 cells promotes the proliferation of synovial fibroblasts through induction of the chemokine C-C chemokine ligand 2 (CCL2). T follicular helper (Tfh) cells produce IL-21, which is key for B cell stimulation by the C-X-C chemokine receptor 5 (CXCR5) and coexpression with programmed cell death-1 (PD-1) and/or inducible T cell costimulator (ICOS). PD-1 inhibits T cell proliferation and cytokine production. In addition, there are many immunomodulatory agents that promote or inhibit the immunomodulatory role of T helper cells in RA to alleviate disease progression. These findings help to elucidate the aetiology and treatment of RA and point us toward the next steps. Cite this article: Bone Joint Res 2022;11(7):426–438


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. 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.


Bone & Joint Research
Vol. 11, Issue 1 | Pages 29 - 31
20 Jan 2022
Ma M Tan Z Li W Zhang H Liu Y Yue C


Bone & Joint Research
Vol. 11, Issue 1 | Pages 26 - 28
20 Jan 2022
Ma M Tan Z Li W Zhang H Liu Y Yue C


Bone & Joint Research
Vol. 9, Issue 8 | Pages 501 - 514
1 Aug 2020
Li X Yang Y Sun G Dai W Jie X Du Y Huang R Zhang J

Aims

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.

Methods

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.


The Bone & Joint Journal
Vol. 96-B, Issue 3 | Pages 291 - 298
1 Mar 2014
Murray IR Corselli M Petrigliano FA Soo C Péault B

The ability of mesenchymal stem cells (MSCs) to differentiate in vitro into chondrocytes, osteocytes and myocytes holds great promise for tissue engineering. Skeletal defects are emerging as key targets for treatment using MSCs due to the high responsiveness of bone to interventions in animal models. Interest in MSCs has further expanded in recognition of their ability to release growth factors and to adjust immune responses.

Despite their increasing application in clinical trials, the origin and role of MSCs in the development, repair and regeneration of organs have remained unclear. Until recently, MSCs could only be isolated in a process that requires culture in a laboratory; these cells were being used for tissue engineering without understanding their native location and function. MSCs isolated in this indirect way have been used in clinical trials and remain the reference standard cellular substrate for musculoskeletal engineering. The therapeutic use of autologous MSCs is currently limited by the need for ex vivo expansion and by heterogeneity within MSC preparations. The recent discovery that the walls of blood vessels harbour native precursors of MSCs has led to their prospective identification and isolation. MSCs may therefore now be purified from dispensable tissues such as lipo-aspirate and returned for clinical use in sufficient quantity, negating the requirement for ex vivo expansion and a second surgical procedure.

In this annotation we provide an update on the recent developments in the understanding of the identity of MSCs within tissues and outline how this may affect their use in orthopaedic surgery in the future.

Cite this article: Bone Joint J 2014;96-B:291–8.