Urinary proteomics identifies distinct immunological profiles of sepsis associated AKI sub-phenotypes

Ian B. Stanaway, Eric D. Morrell, F. Linzee Mabrey, Neha A. Sathe, Zoie Bailey, Sarah Speckmaier, Jordan Lo, Leila R. Zelnick, Jonathan Himmelfarb, Carmen Mikacenic, Laura Evans, Mark M. Wurfel, Pavan K. Bhatraju

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Patients with sepsis-induced AKI can be classified into two distinct sub-phenotypes (AKI-SP1, AKI-SP2) that differ in clinical outcomes and response to treatment. The biologic mechanisms underlying these sub-phenotypes remains unknown. Our objective was to understand the underlying biology that differentiates AKI sub-phenotypes and associations with kidney outcomes. Methods: We prospectively enrolled 173 ICU patients with sepsis from a suspected respiratory infection (87 without AKI and 86 with AKI on enrollment). Among the AKI patients, 66 were classified as AKI-SP1 and 20 as AKI-SP2 using a three-plasma biomarker classifier. Aptamer-based proteomics assessed 5,212 proteins in urine collected on ICU admission. We compared urinary protein abundances between AKI sub-phenotypes, conducted pathway analyses, tested associations with risk of RRT and blood bacteremia, and predicted AKI-SP2 class membership using LASSO. Measurement and main results: In total, 117 urine proteins were higher in AKI-SP2, 195 were higher in AKI-SP1 (FDR < 0.05). Urinary proteins involved in inflammation and chemoattractant of neutrophils and monocytes (CXCL1 and REG3A) and oxidative stress (SOD2) were abundant in AKI-SP2, while proteins involved in collagen deposition (GP6), podocyte derived (SPOCK2), proliferation of mesenchymal cells (IL11RA), anti-inflammatory (IL10RB and TREM2) were abundant in AKI-SP1. Pathways related to immune response, complement activation and chemokine signaling were upregulated in AKI-SP2 and pathways of cell adhesion were upregulated in AKI-SP1. Overlap was present between urinary proteins that differentiated AKI sub-phenotypes and proteins that differentiated risk of RRT during hospitalization. Variable correlation was found between top aptamers and ELISA based protein assays. A LASSO derived urinary proteomic model to classify AKI-SP2 had a mean AUC of 0.86 (95% CI: 0.69–0.99). Conclusion: Our findings suggest AKI-SP1 is characterized by a reparative, regenerative phenotype and AKI-SP2 is characterized as an immune and inflammatory phenotype associated with blood bacteremia. We identified shared biology between AKI sub-phenotypes and eventual risk of RRT highlighting potential therapeutic targets. Urine proteomics may be used to non-invasively classify SP2 participants.

Original languageEnglish
Article number419
JournalCritical Care
Volume28
Issue number1
DOIs
StatePublished - Dec 2024
Externally publishedYes

Keywords

  • Acute kidney injury
  • Intensive care unit
  • Sepsis
  • Urinary proteomics

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