Soluble Urokinase Receptor (SuPAR) in COVID-19-Related AKI

Abstract

Background: AKI commonly occurs in patients with coronavirus disease 2019 (COVID-19). Its pathogenesis is poorly understood. The urokinase receptor system is a key regulator of the intersection between inflammation, immunity, and coagulation, and soluble urokinase plasminogen activator receptor (suPAR) has been identified as an immunologic risk factor for AKI. Whether suPAR is associated with COVID-19-related AKI is unknown.

Methods: In a multinational observational study of adult patients hospitalized for COVID-19, we measured suPAR levels in plasma samples from 352 adult patients that had been collected within 48 hours of admission. We examined the association between suPAR levels and incident in-hospital AKI.

Results: Of the 352 patients (57.4% were male, 13.9% were black, and mean age was 61 years), 91 (25.9%) developed AKI during their hospitalization, of whom 25 (27.4%) required dialysis. The median suPAR level was 5.61 ng/ml. AKI incidence rose with increasing suPAR tertiles, from a 6.0% incidence in patients with suPAR <4.60 ng/ml (first tertile) to a 45.8% incidence of AKI in patients with suPAR levels >6.86 ng/ml (third tertile). None of the patients with suPAR <4.60 ng/ml required dialysis during their hospitalization. In multivariable analysis, the highest suPAR tertile was associated with a 9.15-fold increase in the odds of AKI (95% confidence interval [95% CI], 3.64 to 22.93) and a 22.86-fold increase in the odds of requiring dialysis (95% CI, 2.77 to 188.75). The association was independent of inflammatory markers and persisted across subgroups.

Conclusions: Admission suPAR levels in patients hospitalized for COVID-19 are predictive of in-hospital AKI and the need for dialysis. SuPAR may be a key component of the pathophysiology of AKI in COVID-19.

Keywords: AKI; COVID-19; CRP; SARS-CoV-2; SuPAR; acute renal failure; coronavirus; dialysis; renal replacement therapy; urokinase.

Copyright © 2020 by the American Society of Nephrology.

Figures

Graphical abstract

Figure 1.

AKI stratified by suPAR levels. Bar graphs showing (A) the percentage of patients with incident AKI stratified by suPAR tertiles, and (B) the median suPAR levels across AKI stages. Note: stages 2–3 AKI here exclude patients on dialysis, which are shown in a separate bar graph. P value is derived from the chi-squared test in (A) and Kruskal–Wallis test in (B).

Figure 2.

Percent change in creatinine throughout the hospitalization stratified by suPAR tertiles. We plotted the daily percentage creatinine change relative to admission creatinine stratified by suPAR tertiles using locally weighted smoothing. P value derived from linear mixed model examining the interaction between the creatinine slope and suPAR tertiles. Patients in second and third tertiles had steadily increasing creatinine levels compared with patients in the first suPAR tertile.

Figure 3.

SuPAR and odds of COVID-19–related AKI. (A) Bar graph depicting ORs and 95% CIs for AKI according to admission suPAR tertiles. (B) Kaplan–Meier curves showing cumulative incidence of AKI stratified by suPAR tertiles with log-rank P value. Cox regression modeling hazard ratios are reported in the accompanying table. Model 1 was unadjusted. Model 2 was adjusted for age, sex, race, diabetes mellitus, hypertension, and eGFR at the time of sample collection for suPAR. Model 3 incorporated the aforementioned variables including oxygen saturation and CRP levels. Tertile 1 was the reference (R) group in all models. **P<0.001. Data for model 3 were available in 301 participants.

Figure 4.

Addition of suPAR improves the AUC for predicting AKI. Receiver operating characteristic curve for predicting AKI. Model 0 includes age, sex, race, and creatinine-derived eGFR at the time of suPAR measurement. Model 1 includes all aforementioned characteristics in addition to suPAR as a continuous variable.

Figure 5.

SuPAR and AKI across subgroups. Forest plot depicting the risk of AKI on the basis of suPAR levels as a continuous variable according to subgroups. suPAR levels were log-transformed (base 2) given their skewed distribution. †P value for the interaction between subgroups.