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Identification of Acute Kidney Injury Subphenotypes with Differing Molecular Signatures and Responses to Vasopressin
Pavan K Bhatraju1,2, Leila R Zelnick2, Jerald Herting3
11 Division of Pulmonary, Critical Care, and Sleep Medicine.
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.
Insights
This study identified two distinct acute kidney injury (AKI) subphenotypes. These subphenotypes predict patient outcomes and guide vasopressin therapy, offering new avenues for treatment.
Area of Science:
- Nephrology
- Critical Care Medicine
- Translational Medicine
Background:
- Acute kidney injury (AKI) lacks effective pharmacologic treatments due to population heterogeneity.
- Identifying specific pathophysiologic pathways and therapeutic targets in AKI is challenging.
Purpose of the Study:
- To identify and validate acute kidney injury (AKI) subphenotypes.
- To determine if AKI subphenotypes have prognostic and therapeutic implications.
Main Methods:
- Latent class analysis was applied to two independent critically ill populations with AKI (discovery and replication).
- A classification model was developed to identify AKI subphenotypes.
- The model was applied to patients in the Vasopressin and Septic Shock Trial (VASST) to assess treatment response differences.
Main Results:
- A two-subphenotype model demonstrated the best fit, identifying AKI subphenotype 1 (AKI-SP1) and AKI subphenotype 2 (AKI-SP2).
- AKI-SP2 was associated with a higher risk of renal nonrecovery and mortality compared to AKI-SP1.
- Subphenotypes better predicted outcomes than KDIGO stages; a three-variable model accurately classified membership.
- In VASST, vasopressin improved 90-day mortality in AKI-SP1 but not AKI-SP2, with a trend toward interaction (P=0.05).
Conclusions:
- Two molecularly distinct AKI subphenotypes with differing clinical outcomes and treatment responses were identified.
- AKI subphenotype identification can enhance risk prognostication.
- Subphenotyping may aid in predictive enrichment for future clinical trials in AKI.
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