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Bone & Joint Research
Vol. 11, Issue 9 | Pages 652 - 668
7 Sep 2022
Lv G Wang B Li L Li Y Li X He H Kuang L

Aims. 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. Methods. 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. Results. DC-exo inhibited macrophage autophagy (p = 0.002) and promoted M1 macrophage polarization (p = 0.002). DC-exo at 20 μg/ml induced collagen degradation (p < 0.001) and inflammatory cell infiltration (p = 0.023) in rats. OANCT was elevated in DC (p < 0.001) and in cartilage tissues of OA patients (p < 0.001), and positively correlated with patients’ Kellgren-Lawrence grade (p < 0.001). PIK3R5 was increased in DC-exo-treated cartilage tissues (p < 0.001), and OANCT bound to fat mass and obesity-associated protein (FTO) (p < 0.001). FTO bound to PIK3R5 (p < 0.001) to inhibit the stability of PIK3R5 messenger RNA (mRNA) (p < 0.001) and disrupt the PI3K/AKT/mTOR pathway (p < 0.001). Conclusion. Exosomal OANCT from DC could bind to FTO protein, thereby maintaining the mRNA stability of PIK3R5, further activating the PI3K/AKT/mTOR pathway to exacerbate OA. Cite this article: Bone Joint Res 2022;11(9):652–668


Bone & Joint Research
Vol. 13, Issue 7 | Pages 362 - 371
17 Jul 2024
Chang H Liu L Zhang Q Xu G Wang J Chen P Li C Guo X Yang Z Zhang F

Aims

The metabolic variations between the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) remain largely unknown. Our study aimed to address this by conducting a comparative analysis of the metabolic profiles present in the cartilage of KBD and OA.

Methods

Cartilage samples from patients with KBD (n = 10) and patients with OA (n = 10) were collected during total knee arthroplasty surgery. An untargeted metabolomics approach using liquid chromatography coupled with mass spectrometry (LC-MS) was conducted to investigate the metabolomics profiles of KBD and OA. LC-MS raw data files were converted into mzXML format and then processed by the XCMS, CAMERA, and metaX toolbox implemented with R software. The online Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate the metabolites by matching the exact molecular mass data of samples with those from the database.


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. 11, Issue 2 | Pages 61 - 72
15 Feb 2022
Luobu Z Wang L Jiang D Liao T Luobu C Qunpei L

Aims

Circular RNA (circRNA) S-phase cyclin A-associated protein in the endoplasmic reticulum (ER) (circSCAPER, ID: hsa_circ_0104595) has been found to be highly expressed in osteoarthritis (OA) patients and has been associated with the severity of OA. Hence, the role and mechanisms underlying circSCAPER in OA were investigated in this study.

Methods

In vitro cultured human normal chondrocyte C28/I2 was exposed to interleukin (IL)-1β to mimic the microenvironment of OA. The expression of circSCAPER, microRNA (miR)-140-3p, and enhancer of zeste homolog 2 (EZH2) was detected using quantitative real-time polymerase chain reaction and Western blot assays. The extracellular matrix (ECM) degradation, proliferation, and apoptosis of chondrocytes were determined using Western blot, cell counting kit-8, and flow cytometry assays. Targeted relationships were predicted by bioinformatic analysis and verified using dual-luciferase reporter and RNA immunoprecipitation (RIP) assays. The levels of phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) pathway-related protein were detected using Western blot assays.


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.