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Bone & Joint Research
Vol. 9, Issue 9 | Pages 623 - 632
5 Sep 2020
Jayadev C Hulley P Swales C Snelling S Collins G Taylor P Price A

Aims. The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA). Methods. Synovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA. Results. PLS-DA produced a streamlined biomarker model with excellent sensitivity (95%), specificity (98.4%), and reliability (97.4%). The eight-biomarker model produced a fingerprint for esOA comprising type IIA procollagen N-terminal propeptide (PIIANP), tissue inhibitor of metalloproteinase (TIMP)-1, a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS-4), monocyte chemoattractant protein (MCP)-1, interferon-γ-inducible protein-10 (IP-10), and transforming growth factor (TGF)-β3. Receiver operating characteristic (ROC) analysis demonstrated excellent discriminatory accuracy: area under the curve (AUC) being 0.970 for esOA, 0.957 for knee injury, and 1 for inflammatory arthritis. All ten validation test patients were classified correctly as esOA (accuracy 100%; reliability 100%) by the biomarker model. Conclusion. SF analysis coupled with machine learning produced a partially validated biomarker model with cohort-specific fingerprints that accurately and reliably discriminated esOA from knee injury and inflammatory arthritis with almost 100% efficacy. The presented findings and approach represent a new biomarker concept and potential diagnostic tool to stage disease in therapy trials and monitor the efficacy of such interventions. Cite this article: Bone Joint Res 2020;9(9):623–632


Bone & Joint Research
Vol. 12, Issue 9 | Pages 601 - 614
21 Sep 2023
Gu P Pu B Liu T Yue D Xin Q Li H Yang B Ke D Zheng X Zeng Z Zhang Z

Aims

Mendelian randomization (MR) is considered to overcome the bias of observational studies, but there is no current meta-analysis of MR studies on rheumatoid arthritis (RA). The purpose of this study was to summarize the relationship between potential pathogenic factors and RA risk based on existing MR studies.

Methods

PubMed, Web of Science, and Embase were searched for MR studies on influencing factors in relation to RA up to October 2022. Meta-analyses of MR studies assessing correlations between various potential pathogenic factors and RA were conducted. Random-effect and fixed-effect models were used to synthesize the odds ratios of various pathogenic factors and RA. The quality of the study was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guidelines.


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. 10, Issue 7 | Pages 459 - 466
28 Jul 2021
Yang J Zhou Y Liang X Jing B Zhao Z

Aims

Osteoarthritis (OA) is characterized by persistent destruction of articular cartilage. It has been found that microRNAs (miRNAs) are closely related to the occurrence and development of OA. The purpose of the present study was to investigate the mechanism of miR-486 in the development and progression of OA.

Methods

The expression levels of miR-486 in cartilage were determined by quantitative real-time polymerase chain reaction (qRT-PCR). The expression of collagen, type II, alpha 1 (COL2A1), aggrecan (ACAN), matrix metalloproteinase (MMP)-13, and a disintegrin and metalloproteinase with thrombospondin motifs-4 (ADAMTS4) in SW1353 cells at both messenger RNA (mRNA) and protein levels was determined by qRT-PCR, western blot, and enzyme-linked immunosorbent assay (ELISA). Double luciferase reporter gene assay, qRT-PCR, and western blot assay were used to determine whether silencing information regulator 6 (SIRT6) was involved in miR-486 induction of chondrocyte-like cells to a more catabolic phenotype.


Bone & Joint Research
Vol. 10, Issue 8 | Pages 548 - 557
25 Aug 2021
Tao Z Zhou Y Zeng B Yang X Su M

Aims

MicroRNA-183 (miR-183) is known to play important roles in osteoarthritis (OA) pain. The aims of this study were to explore the specific functions of miR-183 in OA pain and to investigate the underlying mechanisms.

Methods

Clinical samples were collected from patients with OA, and a mouse model of OA pain was constructed by surgically induced destabilization of the medial meniscus (DMM). Reverse transcription quantitative polymerase chain reaction was employed to measure the expression of miR-183, transforming growth factor α (TGFα), C-C motif chemokine ligand 2 (CCL2), proinflammatory cytokines (interleukin (IL)-6, IL-1β, and tumour necrosis factor-α (TNF-α)), and pain-related factors (transient receptor potential vanilloid subtype-1 (TRPV1), voltage-gated sodium 1.3, 1.7, and 1.8 (Nav1.3, Nav1.7, and Nav1.8)). Expression of miR-183 in the dorsal root ganglia (DRG) of mice was evaluated by in situ hybridization. TGFα, CCL2, and C-C chemokine receptor type 2 (CCR2) levels were examined by immunoblot analysis and interaction between miR-183 and TGFα, determined by luciferase reporter assay. The extent of pain in mice was measured using a behavioural assay, and OA severity assessed by Safranin O and Fast Green staining. Immunofluorescent staining was conducted to examine the infiltration of macrophages in mouse DRG.


Bone & Joint Research
Vol. 9, Issue 10 | Pages 689 - 700
7 Oct 2020
Zhang A Ma S Yuan L Wu S Liu S Wei X Chen L Ma C Zhao H

Aims

The study aimed to determine whether the microRNA miR21-5p (MiR21) mediates temporomandibular joint osteoarthritis (TMJ-OA) by targeting growth differentiation factor 5 (Gdf5).

Methods

TMJ-OA was induced in MiR21 knockout (KO) mice and wild-type (WT) mice by a unilateral anterior crossbite (UAC) procedure. Mouse tissues exhibited histopathological changes, as assessed by: Safranin O, toluidine blue, and immunohistochemistry staining; western blotting (WB); and quantitative real-time polymerase chain reaction (RT-qPCR). Mouse condylar chondrocytes were transfected with a series of MiR21 mimic, MiR21 inhibitor, Gdf5 siRNA (si-GDF5), and flag-GDF5 constructs. The effects of MiR-21 and Gdf5 on the expression of OA related molecules were evaluated by immunofluorescence, alcian blue staining, WB, and RT-qPCR.