Diagnostic Gene Signatures for Immune Nephropathy Biomarkers

An eight-gene diagnostic signature (IPMK, TP53, SLC40A1, NCOA4, SLC39A7, KEAP1, TNIP1, SAT1) was identified for immune nephropathy. The dataset contains results from gene expression analysis correlating these genes with clinical parameters like eGFR and proteinuria. It was created by Chengkun Wu and published on figshare in March 2026.

Use Cases

• Validate the diagnostic accuracy of the eight-gene signature (IPMK, TP53, SLC40A1, NCOA4, SLC39A7, KEAP1, TNIP1, SAT1) for classifying immune nephropathy subtypes.
• Investigate correlations between KEAP1 and SLC40A1 expression levels and clinical proteinuria measurements.
• Analyze associations between TNIP1 and TP53 gene expression and impaired renal function metrics like estimated glomerular filtration rate (eGFR).

Strengths

• Focuses on a specific eight-gene diagnostic signature validated for immune nephropathy.
• Includes correlation analyses linking specific genes (KEAP1, SLC40A1, TNIP1, TP53) to clinical parameters like eGFR and proteinuria.
• Derived from analysis of gene expression profiles from the authoritative Gene Expression Omnibus (GEO) database.

Limitations

• The dataset is very small at 24.9 KB, indicating it contains summary results rather than raw expression data.
• No row or column counts are provided, limiting assessment of the underlying data's scale and granularity.
• The analysis is based on secondary data from GEO, so it may reflect the biases and limitations of the original source studies.

Provenance

Source

Gene Expression Omnibus (GEO) database.

Collection Method

Bioinformatic analysis of gene expression profiles using LASSO regression and support vector machine (SVM) algorithms.

Freshness

Last updated March 2026.