LCN2 and TIMP1 as Senescence-Associated Biomarkers in Sepsis-Induced AKI

Three AKI-related datasets from the Gene Expression Omnibus (GEO) database were used to construct a diagnostic model. The model, based on LCN2 and TIMP1 genes, achieved an AUC of 0.997 in the training set. The dataset, authored by Aijing Huo and last updated in June 2026, includes ELISA validation data and immune cell infiltration analysis via the CIBERSORT algorithm.

Use Cases

• Developing diagnostic models for sepsis-induced AKI based on LCN2 and TIMP1 gene expression.
• Analyzing immune cell infiltration patterns in AKI using the CIBERSORT algorithm mentioned in the description.
• Validating biomarker protein expression through ELISA data referenced in the study.

Strengths

• The optimized LCN2/TIMP1 dual-gene diagnostic model showed an AUC of 0.997 in the training set.
• Includes validation data from Enzyme-Linked Immunosorbent Assay (ELISA).

Limitations

• The description notes it is a pilot study with a small sample size.
• Row count and column-level documentation are unknown.
• The dataset is small at 889.0 KB, indicating limited scope.

Provenance

Source

Gene Expression Omnibus (GEO) database

Collection Method

Sourced experimental data and gene expression arrays.

Freshness

Last updated 2026-06-01 10:03:44.