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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. 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 1 | Pages 4 - 18
2 Jan 2024
Wang Y Wu Z Yan G Li S Zhang Y Li G Wu C

Aims

cAMP response element binding protein (CREB1) is involved in the progression of osteoarthritis (OA). However, available findings about the role of CREB1 in OA are inconsistent. 666-15 is a potent and selective CREB1 inhibitor, but its role in OA is unclear. This study aimed to investigate the precise role of CREB1 in OA, and whether 666-15 exerts an anti-OA effect.

Methods

CREB1 activity and expression of a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS4) in cells and tissues were measured by immunoblotting and immunohistochemical (IHC) staining. The effect of 666-15 on chondrocyte viability and apoptosis was examined by cell counting kit-8 (CCK-8) assay, JC-10, and terminal deoxynucleotidyl transferase-mediated dUTP nick end-labelling (TUNEL) staining. The effect of 666-15 on the microstructure of subchondral bone, and the synthesis and catabolism of cartilage, in anterior cruciate ligament transection mice were detected by micro-CT, safranin O and fast green (S/F), immunohistochemical staining, and enzyme-linked immunosorbent assay (ELISA).


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.


Bone & Joint Research
Vol. 11, Issue 4 | Pages 214 - 225
20 Apr 2022
Hao X Zhang J Shang X Sun K Zhou J Liu J Chi R Xu T

Aims

Post-traumatic osteoarthritis (PTOA) is a subset of osteoarthritis (OA). The gut microbiome is shown to be involved in OA. However, the effect of exercise on gut microbiome in PTOA remains elusive.

Methods

A total of 18 eight-week Sprague-Dawley rats were assigned into three groups: Sham/sedentary (Sham/Sed), PTOA/sedentary (PTOA/Sed), and PTOA/treadmill-walking (PTOA/TW). PTOA model was induced by transection of the anterior cruciate ligament (ACLT) and the destabilization of the medial meniscus (DMM). Treadmill-walking (15 m/min, 30 min/d, five days/week for eight weeks) was employed in the PTOA/TW group. The response of cartilage, subchondral bone, serology, and gut microbiome and their correlations were assessed.


Bone & Joint Research
Vol. 11, Issue 7 | Pages 484 - 493
13 Jul 2022
Hayer S Niederreiter B Kalkgruber M Wanic K Maißner J Smolen JS Aletaha D Blüml S Redlich K

Aims

Insufficient treatment response in rheumatoid arthritis (RA) patients requires novel treatment strategies to halt disease progression. The potential benefit of combination of cytokine-inhibitors in RA is still unclear and needs further investigation. To explore the impact of combined deficiency of two major cytokines, namely interleukin (IL)-1 and IL-6, in this study double deficient mice for IL-1αβ and IL-6 were investigated in different tumour necrosis factor (TNF)-driven inflammatory bone disorders, namely peripheral arthritis and sacroiliitis, as well as systemic bone loss.

Methods

Disease course, histopathological features of arthritis, and micro-CT (µCT) bone analysis of local and systemic bone loss were assessed in 15-week-old IL1-/-IL6-/-hTNFtg in comparison to IL1-/-hTNFtg, IL6-/-hTNFtg, and hTNFtg mice. µCT bone analysis of single deficient and wild-type mice was also performed.


Bone & Joint Research
Vol. 11, Issue 1 | Pages 12 - 22
13 Jan 2022
Zhang F Rao S Baranova A

Aims

Deciphering the genetic relationships between major depressive disorder (MDD) and osteoarthritis (OA) may facilitate an understanding of their biological mechanisms, as well as inform more effective treatment regimens. We aim to investigate the mechanisms underlying relationships between MDD and OA in the context of common genetic variations.

Methods

Linkage disequilibrium score regression was used to test the genetic correlation between MDD and OA. Polygenic analysis was performed to estimate shared genetic variations between the two diseases. Two-sample bidirectional Mendelian randomization analysis was used to investigate causal relationships between MDD and OA. Genomic loci shared between MDD and OA were identified using cross-trait meta-analysis. Fine-mapping of transcriptome-wide associations was used to prioritize putatively causal genes for the two diseases.


Bone & Joint Research
Vol. 9, Issue 11 | Pages 789 - 797
2 Nov 2020
Seco-Calvo J Sánchez-Herráez S Casis L Valdivia A Perez-Urzelai I Gil J Echevarría E

Aims

To analyze the potential role of synovial fluid peptidase activity as a measure of disease burden and predictive biomarker of progression in knee osteoarthritis (KOA).

Methods

A cross-sectional study of 39 patients (women 71.8%, men 28.2%; mean age of 72.03 years (SD 1.15) with advanced KOA (Ahlbäck grade ≥ 3 and clinical indications for arthrocentesis) recruited through the (Orthopaedic Department at the Complejo Asistencial Universitario de León, Spain (CAULE)), measuring synovial fluid levels of puromycin-sensitive aminopeptidase (PSA), neutral aminopeptidase (NAP), aminopeptidase B (APB), prolyl endopeptidase (PEP), aspartate aminopeptidase (ASP), glutamyl aminopeptidase (GLU) and pyroglutamyl aminopeptidase (PGAP).


Bone & Joint Research
Vol. 9, Issue 4 | Pages 173 - 181
1 Apr 2020
Schon J Chahla J Paudel S Manandhar L Feltham T Huard J Philippon M Zhang Z

Aims

Femoroacetabular impingement (FAI) is a potential cause of hip osteoarthritis (OA). The purpose of this study was to investigate the expression profile of matrix metalloproteinases (MMPs) in the labral tissue with FAI pathology.

Methods

In this study, labral tissues were collected from four FAI patients arthroscopically and from three normal hips of deceased donors. Proteins extracted from the FAI and normal labrums were separately applied for MMP array to screen the expression of seven MMPs and three tissue inhibitors of metalloproteinases (TIMPs). The expression of individual MMPs and TIMPs was quantified by densitometry and compared between the FAI and normal labral groups. The expression of selected MMPs and TIMPs was validated and localized in the labrum with immunohistochemistry.


Bone & Joint Research
Vol. 8, Issue 12 | Pages 582 - 592
1 Dec 2019
Sansone V Applefield RC De Luca P Pecoraro V Gianola S Pascale W Pascale V

Aims

The aim of this study was to systematically review the literature for evidence of the effect of a high-fat diet (HFD) on the onset or progression of osteoarthritis (OA) in mice.

Methods

A literature search was performed in PubMed, Embase, Web of Science, and Scopus to find all studies on mice investigating the effects of HFD or Western-type diet on OA when compared with a control diet (CD). The primary outcome was the determination of cartilage loss and alteration. Secondary outcomes regarding local and systemic levels of proteins involved in inflammatory processes or cartilage metabolism were also examined when reported.


Aims

This study aimed to uncover the hub long non-coding RNAs (lncRNAs) differentially expressed in osteoarthritis (OA) cartilage using an integrated analysis of the competing endogenous RNA (ceRNA) network and co-expression network.

Methods

Expression profiles data of ten OA and ten normal tissues of human knee cartilage were obtained from the Gene Expression Omnibus (GEO) database (GSE114007). The differentially expressed messenger RNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the edgeR package. We integrated human microRNA (miRNA)-lncRNA/mRNA interactions with DElncRNA/DEmRNA expression profiles to construct a ceRNA network. Likewise, lncRNA and mRNA expression profiles were used to build a co-expression network with the WGCNA package. Potential hub lncRNAs were identified based on an integrated analysis of the ceRNA network and co-expression network. StarBase and Multi Experiment Matrix databases were used to verify the lncRNAs.