Identification of Acute Kidney Injury Subphenotypes with Differing Molecular Signatures and Responses to Vasopressin Therapy

Abstract

Rationale: Currently, no safe and effective pharmacologic interventions exist for acute kidney injury (AKI). One reason may be that heterogeneity exists within the AKI population, thereby hampering the identification of specific pathophysiologic pathways and therapeutic targets.

Objective: The aim of this study was to identify and test whether AKI subphenotypes have prognostic and therapeutic implications.

Methods: First, latent class analysis methodology was applied independently in two critically ill populations (discovery [n = 794] and replication [n = 425]) with AKI. Second, a parsimonious classification model was developed to identify AKI subphenotypes. Third, the classification model was applied to patients with AKI in VASST (Vasopressin and Septic Shock Trial; n = 271), and differences in treatment response were determined. In all three populations, AKI was defined using serum creatinine and urine output.

Measurements and main results: A two-subphenotype latent class analysis model had the best fit in both the discovery (P = 0.004) and replication (P = 0.004) AKI groups. The risk of 7-day renal nonrecovery and 28-day mortality was greater with AKI subphenotype 2 (AKI-SP2) relative to AKI subphenotype 1 (AKI-SP1). The AKI subphenotypes discriminated risk for poor clinical outcomes better than the Kidney Disease: Improving Global Outcomes stages of AKI. A three-variable model that included markers of endothelial dysfunction and inflammation accurately determined subphenotype membership (C-statistic 0.92). In VASST, vasopressin compared with norepinephrine was associated with improved 90-day mortality in AKI-SP1 (27% vs. 46%, respectively; P = 0.02), but no significant difference was observed in AKI-SP2 (45% vs. 49%, respectively; P = 0.99) and the P value for interaction was 0.05.

Conclusions: This analysis identified two molecularly distinct AKI subphenotypes with different clinical outcomes and responses to vasopressin therapy. Identification of AKI subphenotypes could improve risk prognostication and may be useful for predictive enrichment in clinical trials.

Keywords: acute kidney injury; endothelial dysfunction; mortality; subphenotypes.

Figure 1.

(A and B) Heat map of the standardized values of each variable by acute kidney injury (AKI) subphenotype for the discovery (A) and replication (B) groups. The variables are sorted based on the degree of separation between AKI subphenotypes, from maximum values with AKI subphenotype 2 (AKI-SP2) at the top to maximum values for AKI-SP1 at the bottom. Variables were standardized by scaling all means to zero, with SD = 1. A variable of 1+ for the standardized variable signifies that the mean value for a given AKI subphenotype was an entire SD higher than the mean value for the population as a whole in that group (discovery or replication).