1. Elucidating common biomarkers and pathways of osteoporosis and aortic valve calcification: insights into new therapeutic targets
- Author
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Yujian Lan, Qingping Peng, Jianlin Shen, and Huan Liu
- Subjects
Osteoporosis ,Aortic valve calcification ,Bioinformatics analysis ,Machine learning ,Molecular mechanisms ,Medicine ,Science - Abstract
Abstract Background: Osteoporosis and aortic valve calcification, prevalent in the elderly, have unclear common mechanisms. This study aims to uncover them through bioinformatics analysis. Methods: Microarray data from GEO was analyzed for osteoporosis and aortic valve calcification. Differential expression analysis identified co-expressed genes. SVM-RFE and random forest selected key genes. GO and KEGG enrichment analyses were performed. Immunoinfiltration and GSEA analyses were subsequently performed. NetworkAnalyst analyzed microRNAs/TFs. HERB predicted drugs, and molecular docking assessed targeting potential. Results: Thirteen genes linked to osteoporosis and aortic valve calcification were identified. TNFSF11, KYNU, and HLA-DMB emerged as key genes. miRNAs, TFs, and drug predictions offered therapeutic insights. Molecular docking suggested 17-beta-estradiol and vitamin D3 as potential treatments. Conclusion: The study clarifies shared mechanisms of osteoporosis and aortic valve calcification, identifies biomarkers, and highlights TNFSF11, KYNU, and HLA-DMB. It also suggests 17-beta-estradiol and vitamin D3 as potential effective treatments.
- Published
- 2024
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