Osteoporosis Diagnostic Model Based on Disulfidoptosis-Related Genes and Immune Analysis

Gene expression data from the Gene Expression Omnibus (GEO) used to develop an osteoporosis diagnostic model. The dataset includes results from bioinformatics analyses identifying 299 disulfidoptosis-related differentially expressed genes and a model built on three hub genes (SOAT2, FOLR3, TUBA8). The data was authored by Ping Yang and last updated on 2026-05-28.

Use Cases

• Building a diagnostic classifier for osteoporosis based on the three identified hub genes (SOAT2, FOLR3, TUBA8).
• Analyzing immune infiltration patterns in osteoporosis using CIBERSORT-derived cell type proportions.
• Investigating the relationship between disulfidoptosis-related genes and osteoclast differentiation.
• Clustering osteoporosis patients into subtypes based on molecular and immune characteristics via consensus clustering.
• Validating gene expression dysregulation in an in vitro RANKL-induced osteoclast model.

Strengths

• The diagnostic model achieved high accuracy in external validation, with an AUC reported as greater than 0.9.
• Experimental validation was conducted using qPCR and Western blot, providing multi-level evidence for gene dysregulation.
• The analysis identified 299 disulfidoptosis-related differentially expressed genes, providing a substantial feature set.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is 1.4 MB, indicating a relatively small scale.

Provenance

Source

Gene Expression Omnibus (GEO)

Collection Method

Integrative bioinformatics analysis of microarray datasets, including differential expression analysis, WGCNA, and machine learning.

Freshness

Last updated 2026-05-28 06:27:10; freshness should be verified.