Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Objective: The pathological mechanism of osteoporosis (OP) involves increased bone resorption mediated by osteoclasts and decreased bone formation mediated by osteoblasts, leading to an imbalance in bone homeostasis. Identifying key molecules in osteoclast-mediated OP progression is crucial for the prevention and treatment of OP.
Methods: Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed on the OP patient datasets from the GEO database. The results were intersected with the differential expression results from the osteoclast differentiation dataset to identify key genes. These key genes were then subjected to disease relevance analysis, and consensus clustering was performed on OP patient samples based on their expression profiles. The subgroups were analyzed for differences, followed by GO, KEGG, GSEA, and GSVA analyses, and immune infiltration. Finally, osteoclast differentiation model was constructed. After validating the success of the model using TRAP and F-actin staining, the differential expression of key genes was validated in vitro via Western blot.
Results: CTRL, ARHGEF5, PPAP2C, VSIG2, and PBLD were identified as key genes. These genes exhibited strong disease relevance (AUC > 0.9). Functional enrichment results also indicated their close association with OP and osteoclast differentiation. In vitro differential expression validation showed that during osteoclast differentiation, CTRL was downregulated, while ARHGEF5, PPAP2C, VSIG2, and PBLD were upregulated, with all differences being statistically significant (< 0.05).
Discussion: Currently, there are no studies on the effects of these five genes on osteoclast differentiation. Therefore, it is meaningful to design in vivo and in vitro perturbation experiments to observe the impact of each gene on osteoclast differentiation and OP progression.
Conclusion: CTRL, ARHGEF5, PPAP2C, VSIG2, and PBLD show high potential as molecular targets for basic and clinical research in osteoclast-mediated OP.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11590132 | PMC |
http://dx.doi.org/10.1177/00368504241300723 | DOI Listing |
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