Article ; Online: Transcriptomic analysis identifies diagnostic genes in polycystic ovary syndrome and periodontitis
European Journal of Medical Research, Vol 29, Iss 1, Pp 1-
2024 Volume 12
Abstract: Abstract Purpose To investigate underlying co-mechanisms of PCOS and periodontitis through transcriptomic approach. Methods PCOS and periodontitis gene expression data were downloaded from the GEO database to identify differentially expressed genes. GO ... ...
Abstract | Abstract Purpose To investigate underlying co-mechanisms of PCOS and periodontitis through transcriptomic approach. Methods PCOS and periodontitis gene expression data were downloaded from the GEO database to identify differentially expressed genes. GO and KEGG pathway enrichment analysis and random forest algorithm were used to screen hub genes. GSEA analyzed the functions of hub genes. Correlations between hub genes and immune infiltration in two diseases were examined, constructing a TF-ceRNA regulatory network. Clinical samples were gathered from PCOS and periodontitis patients and RT-qPCR was performed to verify the connection. Results There were 1661 DEGs in PCOS and 701 DEGs in periodontitis. 66 intersected genes were involved and were enriched in immune and inflammation-related biological pathways. 40 common genes were selected from the PPI network. RF algorithm demonstrated that ACSL5, NLRP12, CCRL2, and CEACAM3 were hub genes, and GSEA results revealed their close relationship with antigen processing and presentation, and chemokine signaling pathway. RT-qPCR results confirmed the upregulated gene expression in both PCOS and periodontitis. Conclusion The 4 hub genes ACSL5, NLRP12, CCRL2, and CEACAM3 may be diagnostic genes for PCOS and periodontitis. The created ceRNA network could provide a molecular basis for future studies on the association between PCOS and periodontitis. |
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Keywords | Polycystic ovary syndrome ; Periodontitis ; GSEA ; Diagnosis ; Transcriptomic analysis ; Medicine ; R |
Language | English |
Publishing date | 2024-01-01T00:00:00Z |
Publisher | BMC |
Document type | Article ; Online |
Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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