BACKGROUND: Immune cells are key drivers of acute kidney injury (AKI) due to the complex interaction between immune cells, senescence and AKI. MATERIAL AND METHODS: Three AKI-related datasets were sourced from the Gene Expression Omnibus (GEO) database, encompassing experimental data and gene expression arrays. TIMP1 and LCN2 were used to construct the AKI diagnostic model, and the resulting nomogram and Receiver Operating Characteristic (ROC) curves exhibited significant diagnostic efficacy. Within the framework of AKI patients, the increased protein expression of LCN2 and TIMP1 was corroborated through Enzyme-Linked Immunosorbent Assay (ELISA). RESULTS: The precision of the risk predictive model's classification based on signature ARGs, was validated by ROC curves, with an area under the curve (AUC) of 0.9596 in the training cohort; the optimized LCN2/TIMP1 dual-gene diagnostic model showed an AUC of 0.997 in the training set. Utilizing the CIBERSORT algorithm, it was observed that sepsis-induced AKI models exhibited elevated levels of Macrophages M1, T cells follicular helper and so on, and sepsis-induced AKI models had lower levels of dendritic cells resting. CONCLUSIONS: The management of AKI emphasizes the senescence-association of LCN2 and TIMP1 genes with immune cells. As a pilot study with a small sample size, more prospective approaches could be considered to demonstrate this argument.
Huo et al. (Mon,) studied this question.