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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).


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 2 | Pages 91 - 102
1 Feb 2023
Li Z Chen M Wang Z Fan Q Lin Z Tao X Wu J Liu Z Lin R Zhao C

Aims

Rheumatoid arthritis (RA) is a common chronic immune disease. Berberine, as its main active ingredient, was also contained in a variety of medicinal plants such as Berberaceae, Buttercup, and Rutaceae, which are widely used in digestive system diseases in traditional Chinese medicine with anti-inflammatory and antibacterial effects. The aims of this article were to explore the therapeutic effect and mechanism of berberine on rheumatoid arthritis.

Methods

Cell Counting Kit-8 was used to evaluate the effect of berberine on the proliferation of RA fibroblast-like synoviocyte (RA-FLS) cells. The effect of berberine on matrix metalloproteinase (MMP)-1, MMP-3, receptor activator of nuclear factor kappa-Β ligand (RANKL), tumour necrosis factor alpha (TNF-α), and other factors was determined by enzyme-linked immunoassay (ELISA) kit. Transcriptome technology was used to screen related pathways and the potential targets after berberine treatment, which were verified by reverse transcription-polymerase chain reaction (RT-qPCR) and Western blot (WB) technology.


Bone & Joint Research
Vol. 11, Issue 2 | Pages 134 - 142
23 Feb 2022
Luo P Cheng S Zhang F Feng R Xu K Jing W Xu P

Aims

The aim of this study was to explore the genetic correlation and causal relationship between blood plasma proteins and rheumatoid arthritis (RA).

Methods

Based on the genome-wide association studies (GWAS) summary statistics of RA from European descent and the GWAS summary datasets of 3,622 plasma proteins, we explored the relationship between RA and plasma proteins from three aspects. First, linkage disequilibrium score regression (LD score regression) was applied to detect the genetic correlation between RA and plasma proteins. Mendelian randomization (MR) analysis was then used to evaluate the causal association between RA and plasma proteins. Finally, GEO2R was used to screen the differentially expressed genes (DEGs) between patients with RA and healthy controls.


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.