Early growth response 1 reduction in peripheral blood involving condylar subchondral bone loss

High expression of transcription factor EGR1 is associated with postoperative muscle atrophy in patients with knee osteoarthritis undergoing total knee arthroplasty

BACKGROUND

Muscle atrophy is a typical affliction in patients affected by knee Osteoarthritis (KOA). This study aimed to examine the potential pathogenesis and biomarkers that coalesce to induce muscle atrophy, primarily through the utilization of bioinformatics analysis.

METHODS

Two distinct public datasets of osteoarthritis and muscle atrophy (GSE82107 and GSE205431) were subjected to differential gene expression analysis and gene set enrichment analysis (GSEA) to probe for common differentially expressed genes (DEGs) and conduct transcription factor (TF) enrichment analysis from such genes. Venn diagrams were used to identify the target TF, followed by the construction of a protein-protein interaction (PPI) network of the common DEGs governed by the target TF. Hub genes were determined through the CytoHubba plug-in whilst their biological functions were assessed using GSEA analysis in the GTEx database. To validate the study, reverse transcriptase real-time quantitative polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay (ELISA), and Flow Cytometry techniques were employed.

RESULTS

A total of 138 common DEGs of osteoarthritis and muscle atrophy were identified, with 16 TFs exhibiting notable expression patterns in both datasets. Venn diagram analysis identified early growth response gene-1 (EGR1) as the target TF, enriched in critical pathways such as epithelial mesenchymal transition, tumor necrosis factor-alpha signaling NF-κB, and inflammatory response. PPI analysis revealed five hub genes, including EGR1, FOS, FOSB, KLF2, and JUNB. The reliability of EGR1 was confirmed by validation testing, corroborating bioinformatics analysis trends.

CONCLUSIONS

EGR1, FOS, FOSB, KLF2, and JUNB are intricately involved in muscle atrophy development. High EGR1 expression directly regulated these hub genes, significantly influencing postoperative muscle atrophy progression in KOA patients.

Osteoarthritis of the Temporomandibular Joint: A Narrative Overview

Background and Objectives: This study reviewed the literature to summarize the current and recent knowledge of temporomandibular joint osteoarthritis (TMJOA). Methods: Through a literature review, this work summarizes many concepts related to TMJOA. Results: Although many signaling pathways have been investigated, the etiopathogenesis of TMJOA remains unclear. Some clinical signs are suggestive of TMJOA; however, diagnosis is mainly based on radiological findings. Treatment options include noninvasive, minimally invasive, and surgical techniques. Several study models have been used in TMJOA studies because there is no gold standard model. Conclusion: More research is needed to develop curative treatments for TMJOA, which could be tested with reliable in vitro models, and to explore tissue engineering to regenerate damaged temporomandibular joints.

PTHrP promotes subchondral bone formation in TMJ-OA

PTH-related peptide (PTHrP) improves the bone marrow micro-environment to activate the bone-remodelling, but the coordinated regulation of PTHrP and transforming growth factor-β (TGFβ) signalling in TMJ-OA remains incompletely understood. We used disordered occlusion to establish model animals that recapitulate the ordinary clinical aetiology of TMJ-OA. Immunohistochemical and histological analyses revealed condylar fibrocartilage degeneration in model animals following disordered occlusion. TMJ-OA model animals administered intermittent PTHrP (iPTH) exhibited significantly decreased condylar cartilage degeneration. Micro-CT, histomorphometry, and Western Blot analyses disclosed that iPTH promoted subchondral bone formation in the TMJ-OA model animals. In addition, iPTH increased the number of osterix (OSX)-positive cells and osteocalcin (OCN)-positive cells in the subchondral bone marrow cavity. However, the number of osteoclasts was also increased by iPTH, indicating that subchondral bone volume increase was mainly due to the iPTH-mediated increase in the bone-formation ability of condylar subchondral bone. In vitro, PTHrP treatment increased condylar subchondral bone marrow-derived mesenchymal stem cell (SMSC) osteoblastic differentiation potential and upregulated the gene and protein expression of key regulators of osteogenesis. Furthermore, we found that PTHrP-PTH1R signalling inhibits TGFβ signalling during osteoblastic differentiation. Collectively, these data suggested that iPTH improves OA lesions by enhancing osteoblastic differentiation in subchondral bone and suppressing aberrant active TGFβ signalling. These findings indicated that PTHrP, which targets the TGFβ signalling pathway, may be an effective biological reagent to prevent and treat TMJ-OA in the clinic.

Identification of transcription factors and construction of a novel miRNA regulatory network in primary osteoarthritis by integrated analysis

Backgrounds

As osteoarthritis (OA) disease-modifying therapies are not available, novel therapeutic targets need to be discovered and prioritized. Here, we aim to identify miRNA signatures in patients to fully elucidate regulatory mechanism of OA pathogenesis and advance in basic understanding of the genetic etiology of OA.

Methods

Six participants (3 OA and 3 controls) were recruited and serum samples were assayed through RNA sequencing (RNA-seq). And, RNA-seq dataset was analysed to identify genes, pathways and regulatory networks dysregulated in OA. The overlapped differentially expressed microRNAs (DEMs) were further screened in combination with the microarray dataset GSE143514. The expression levels of candidate miRNAs were further validated by quantitative real-time PCR (qRT-PCR) based on the GEO dataset (GSE114007).

Results

Serum samples were sequenced interrogating 382 miRNAs. After screening of independent samples and GEO database, the two comparison datasets shared 19 overlapped candidate micRNAs. Of these, 9 up-regulated DEMs and 10 down-regulated DEMs were detected, respectively. There were 236 target genes for up-regulated DEMs and 400 target genes for those down-regulated DEMs. For up-regulated DEMs, the top 10 hub genes were KRAS, NRAS, CDC42, GDNF, SOS1, PIK3R3, GSK3B, IRS2, GNG12, and PRKCA; for down-regulated DEMs, the top 10 hub genes were NR3C1, PPARGC1A, SUMO1, MEF2C, FOXO3, PPP1CB, MAP2K1, RARA, RHOC, CDC23, and CREB3L2. Mir-584-5p-KRAS, mir-183-5p-NRAS, mir-4435-PIK3R3, and mir-4435-SOS1 were identified as four potential regulatory pathways by integrated analysis.

Conclusions

We have integrated differential expression data to reveal putative genes and detected four potential miRNA-target gene pathways through bioinformatics analysis that represent new mediators of abnormal gene expression and promising therapeutic targets in OA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-021-04894-2.