Developing a diagnostic model for necroptosis in osteoporosis using bioinformatics and machine learning.
Yan Wang1, Lijuan Zhang2, Yafei Liu3
1Sports Rehabilitation Department, Xi'an International Medical Center Hospital, Xi'an City, Shaanxi Province, China.
Computer Methods in Biomechanics and Biomedical Engineering
|December 10, 2025
Summary
This study identifies key genes involved in necroptosis and osteoporosis, developing a 13-gene diagnostic model. CASP3 is highlighted as a potential therapeutic target for osteoporosis treatment.
Area of Science:
- Molecular Biology
- Genomics
- Immunology
Background:
- Osteoporosis is a complex skeletal disorder.
- The role of programmed cell death, specifically necroptosis, in osteoporosis pathogenesis is not fully understood.
Purpose of the Study:
- To investigate the involvement of necroptosis in osteoporosis.
- To identify potential diagnostic biomarkers for osteoporosis.
- To develop a diagnostic model for osteoporosis based on necroptosis-related genes.
Main Methods:
- Analysis of public gene expression datasets (GSE56815, GSE7429).
- Identification of differentially expressed genes related to necroptosis.
- Enrichment analysis (necroptosis, NOD-like receptor signaling, IL-17 signaling pathways).
- Protein-protein interaction network analysis and machine learning models (LASSO regression).
Main Results:
- Identified 107 differentially expressed genes associated with necroptosis.
- Established a diagnostic model comprising 13 key genes.
- CASP3 identified as a potential therapeutic target for Minocycline in osteoporosis treatment.
Conclusions:
- Necroptosis plays a significant role in osteoporosis.
- A 13-gene signature can serve as a diagnostic biomarker for osteoporosis.
- CASP3 inhibition may be a viable therapeutic strategy for osteoporosis.
