Identification of Cystatin 3 as a Potential Diagnostic Biomarker for Osteoporosis Using Machine Learning

Dec 8, 2025Journal of inflammation research

Using Machine Learning to Find Cystatin 3 as a Possible Marker for Diagnosing Osteoporosis

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Abstract

A total of 178 differentially expressed genes were identified, with (CST3) showing excellent diagnostic efficacy for .

  • CST3 and another gene, FLJ36848, were identified as characteristic genes with an area under the ROC curve exceeding 0.9.
  • CST3 expression was confirmed to be upregulated in bone marrow mesenchymal stem cells of osteoporosis rats, while levels of other bone markers decreased.
  • CST3 interacts with 178 node genes, indicating potential involvement in various biological processes related to osteoporosis.
  • Increased proportions of immune cells, such as M2-type macrophages and NK cells, were observed in the CST3 high-expression group.
  • Findings suggest that CST3 may play a role in osteoporosis progression through mechanisms involving immune microenvironment regulation and extracellular matrix dynamics.

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Key numbers

> 0.9
Diagnostic Efficacy of
Area under the for in diagnostic tests.
178
Characterization of Genes
Total differentially expressed genes screened in the study.
8 rats
Animal Model Group Size
Total number of rats used in the model.

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