Urinary proteome analysis of acute kidney injury in post-cardiac surgery patients using enrichment materials with high-resolution mass spectrometry

Background: Cardiac surgery-associated acute kidney injury (CSA-AKI) may increase the mortality and incidence rates of chronic kidney disease in critically ill patients. This study aimed to investigate the underlying correlations between urinary proteomic changes and CSA-AKI. Methods: Nontargeted proteomics was performed using nano liquid chromatography coupled with Orbitrap Exploris mass spectrometry (MS) on urinary samples preoperatively and postoperatively collected from patients with CSA-AKI. Gemini C18 silica microspheres were used to separate and enrich trypsin-hydrolysed peptides under basic mobile phase conditions. Differential analysis was conducted to screen out urinary differential expressed proteins (DEPs) among patients with CSA-AKI for bioinformatics. Kyoto Encyclopedia of Genes and Genomes (KEGG) database analysis was adopted to identify the altered signal pathways associated with CSA-AKI. Results: Approximately 2000 urinary proteins were identified and quantified through data-independent acquisition MS, and 324 DEPs associated with AKI were screened by univariate statistics. According to KEGG enrichment analysis, the signal pathway of protein processing in the endoplasmic reticulum was enriched as the most up-regulated DEPs, and cell adhesion molecules were enriched as the most down-regulated DEPs. In protein-protein interaction analysis, the three hub targets in the up-regulated DEPs were alpha-1-antitrypsin, beta-2-microglobulin and angiotensinogen, and the three key down-regulated DEPs were growth arrest-specific protein 6, matrix metalloproteinase-9 and urokinase-type plasminogen activator. Conclusion: Urinary protein disorder was observed in CSA-AKI due to ischaemia and reperfusion. The application of Gemini C18 silica microspheres can improve the protein identification rate to obtain highly valuable resources for the urinary DEPs of AKI. This work provides valuable knowledge about urinary proteome biomarkers and essential resources for further research on AKI.