The Predictive Value of Soluble Urokinase-Type Plasminogen Activator Receptor in Contrast-Induced Acute Kidney Injury in Patients Undergoing Percutaneous Coronary Intervention

Clinical value of soluble urokinase-type plasminogen activator receptor in predicting sepsis-associated acute kidney injury

BACKGROUND

Sepsis-associated acute kidney injury (S-AKI) is a critical illness and is often associated with high morbidity and mortality rates. The soluble urokinase-type plasminogen activator receptor (suPAR) is an important immune mediator and is involved in kidney injury. However, its diagnostic value in S-AKI patients remains unclear. Therefore, we assessed the early predictive value of suPAR for S-AKI patients.

METHODS

We prospectively enrolled adult patients, immediately after fulfilling the sepsis-3 criteria. Plasma suPAR levels at 0-, 12-, 24-, and 48-h post-sepsis diagnosis were measured. S-AKI development was the primary outcome. S-AKI risk factors were analyzed using logistic regression, and the value of plasma suPAR for early S-AKI diagnosis was assessed using receiver operating characteristic (ROC) curves.

RESULTS

Of 179 sepsis patients, 63 (35.2%) developed AKI during hospitalization. At 12-, 24-, and 48-h post-sepsis diagnosis, plasma suPAR levels were significantly higher in patients with S-AKI than in patients without S-AKI (p < 0.05). The plasma suPAR had the highest area under the ROC curve of 0.700 (95% confidence interval (CI), 0.621-0.779) at 24-h post-sepsis diagnosis, at which the best discrimination ability for S-AKI was achieved with suPAR of ≥6.31 ng/mL (sensitivity 61.9% and specificity 71.6%). Logistic regression analysis showed that suPAR at 24-h post-sepsis diagnosis remained an independent S-AKI risk factor after adjusting for mechanical ventilation, blood urea nitrogen, and pH.

CONCLUSIONS

The findings suggest that plasma suPAR may be a potential biomarker for early S-AKI diagnosis.

New biomarkers in acute kidney injury

Acute kidney injury (AKI) is a commonly encountered clinical syndrome. Although it often complicates community acquired illness, it is more common in hospitalized patients, particularly those who are critically ill or who have undergone major surgery. Approximately 20% of hospitalized adult patients develop an AKI during their hospital care, and this rises to nearly 60% in the critically ill, depending on the population being considered. In general, AKI is more common in older adults, in those with preexisting chronic kidney disease and in those with known risk factors for AKI (including diabetes and hypertension). The development of AKI is associated with an increase in both mortality and morbidity, including the development of post-AKI chronic kidney disease. Currently, AKI is defined by a rise in serum creatinine from either a known or derived baseline value and/or oliguria or anuria. However, clinicians may fail to recognize the initial development of AKI because of a delay in the rise of serum creatinine or because of inaccurate urine output monitoring. This, in turn, delays any putative measures to treat AKI or to limit its degree. Consequently, efforts have focused on new biomarkers associated with AKI that may allow early recognition of this syndrome with the intent that this will translate into improved patient outcomes. Here we outline current biomarkers associated with AKI and explore their potential in aiding diagnosis, understanding the pathophysiology and directing therapy.

Circulating Soluble Urokinase Plasminogen Activator Receptor as a Predictive Indicator for COVID-19-Associated Acute Kidney Injury and Mortality: Clinical and Bioinformatics Analysis

Urokinase receptors regulate the interplay between inflammation, immunity, and blood clotting. The soluble urokinase plasminogen activator system is an immunologic regulator affecting endothelial function and its related receptor; the soluble urokinase plasminogen activator receptor (suPAR) has been reported to impact kidney injury. This work aims to measure serum levels of suPAR in COVID-19 patients and correlate the measurements with variable clinicolaboratory parameters and patient outcomes. In this prospective cohort study, 150 COVID-19 patients and 50 controls were included. The circulating suPAR levels were quantified by Enzyme-linked immunosorbent assay (ELISA). Routine COVID-19 laboratory assessments, including CBC, CRP, LDH, serum creatinine, and estimated glomerular filtration rates, were performed. The need for oxygen therapy, CO-RAD score, and survival rates was assessed. Bioinformatic analysis and molecular docking were run to explore the urokinase receptor structure/function and to characterize molecules as potential anti-suPAR therapeutic targets, respectively. We found higher circulating suPAR levels in COVID-19 patients vs. controls (p < 0.001). Circulating suPAR levels positively correlated with COVID-19 severity, the need for O₂ therapy, the total leukocytes count, and the neutrophils to lymphocyte ratio, while they were negatively correlated with the O₂ saturation level, albumin, blood calcium, lymphocytic count, and GFR. In addition, the suPAR levels were associated with poor prognostic outcomes such as a high incidence of acute kidney injury (AKI) and mortality rate. Kaplan-Meier curves showed a lower survival rate with higher suPAR levels. The logistic regression analysis confirmed the significant association of suPAR levels with the occurrence of AKI related to COVID-19 and with increased mortality probability within three months of COVID-19 follow-up. Some compounds that can act similarly to uPAR were discovered and tested by molecular docking to identify the possible ligand-protein interactions. In conclusion, higher circulating suPAR levels were associated with COVID-19 severity and could be considered a putative predictor of AKI development and mortality.

Predictive value of suPAR in AKI: a systematic review and meta-analysis

BACKGROUND

Some clinical trials have shown that soluble urokinase-type plasminogen activator receptor (suPAR) has good predictive value for acute kidney injury (AKI), but there is still a lack of evidence-based proof. Therefore, we conducted this systematic review and meta-analysis to evaluate the predictive value of suPAR for AKI.

METHODS

Pubmed, EMBASE, Cochrane Library, and Web of Science databases were searched until December 2021 to obtain the literature on the prediction of suPAR for AKI. The quality of the included studies was assessed using the QUADAS-2 scoring system, and a bivariate random-effect model was used for the meta-analysis. The present study has been registered on PROSPERO (Registration No. CRD42022324978).

RESULTS

Seven articles were included, involving 2,319 patients, 635 of whom were AKI patients. The meta-analysis results showed that the combined sensitivity of suPAR in predicting AKI was 0.77 (95% CI 0.67-0.84); the specificity was 0.64 (95% CI 0.53-0.75); the odds ratio of diagnosis was 6 (95% CI 3-10); the pooled positive likelihood ratio was 2.2 (95% CI 1.6-2.9); the pooled negative likelihood ratio was 0.36 (95% CI 0.26-0.52); and the area under the summary receiver-operating characteristic (SROC) curve was 0.77 (95% CI 0.12~0.99). Deek's funnel plot suggested no potential publication bias among included studies.

CONCLUSION

suPAR is a valuable biomarker for the prediction of AKI with relatively high predictive accuracy, but its clinical application needs improvements. SuPAR should be considered as an indicator in the subsequent development of more effective predictive tools for AKI.

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 α-1-antitrypsin, β-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.