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  3. Developing a diagnostic model for necroptosis in osteoporosis using bioinformatics and machine learning

Developing a diagnostic model for necroptosis in osteoporosis using bioinformatics and machine learning

  • Comput Methods Biomech Biomed Engin. 2025 Dec 10:1-16. doi: 10.1080/10255842.2025.2600005.
Yan Wang 1,  Lijuan Zhang 2,  Yafei Liu 3
Affiliations

Affiliations

  • 1 Sports Rehabilitation Department, Xi'an International Medical Center Hospital, Xi'an City, Shaanxi Province, China.
  • 2 Nerve & Spine Ward of Rehabilitation Department, Honghui Hospital, Xi'an Jiaotong University, Xi'an City, Shaanxi Province, China.
  • 3 Department of Orthopedics, Honghui Hospital, Xi'an Jiaotong University, Xi'an City, Shaanxi Province, China.
PMID: 41370854 DOI: 10.1080/10255842.2025.2600005
Abstract

This study aims to explore the role of Necroptosis in osteoporosis and identify potential diagnostic biomarkers. By analyzing the GSE56815 and GSE7429 datasets, we identified 107 differentially expressed genes associated with Necroptosis. Enrichment analysis revealed that these genes were significantly enriched in Necroptosis, the NOD-like Receptor signaling pathway, and the IL-17 signaling pathway. Furthermore, through protein-protein interaction network analysis, multiple algorithms (MCC and MCODE) screening, and LASSO regression modeling, we ultimately established a diagnostic model consisting of 13 key genes. In vitro cell experiments suggest that CASP3 may serve as a potential target for Minocycline in the treatment of osteoporosis.

Keywords

Bioinformatics; diagnosis; machine learning; necroptosis; osteoporosis.

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