Table 1_Integrative analysis of hub genes for recurrent pregnancy loss with antiphospholip

Gene expression data analysis identifying potential hub genes for Recurrent Pregnancy Loss (RPL) associated with Antiphospholipid Syndrome (APS). The study, authored by Huan Zeng and last updated in June 2026, integrated datasets from the GEO database, differential expression analysis, and machine learning algorithms. It identified 10 common differentially expressed genes and three hub genes (NAA30, ARHGAP44, SUGT1) validated through computational and experimental methods.

Use Cases

• Identify diagnostic biomarkers for recurrent pregnancy loss based on hub gene expression profiles.
• Analyze immune cell infiltration in pregnancy loss samples using the CIBERSORT tool mentioned in the description.
• Validate gene function through computational models like LASSO regression and RandomForest algorithms described in the methods.
• Explore associations between hub genes and other pregnancy-related diseases using the Comparative Toxicogenomics Database.

Strengths

• Identifies 10 common differentially expressed genes (8 downregulated, 2 upregulated) from integrated GEO datasets.
• Validates three hub genes (NAA30, ARHGAP44, SUGT1) using multiple machine learning methods and experimental qPCR.
• Includes immune cell infiltration analysis and single-gene GSEA for functional insights.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 34.5 KB, indicating limited raw data scope.

Provenance

Source

Gene Expression Omnibus (GEO) database.

Collection Method

Integrated bioinformatics analysis including differential expression, WGCNA, PPI network, and machine learning (LASSO, GMM, RandomForest).

Freshness

Last updated 2026-06-04 05:47:30; freshness should be verified.