Photo Credit: stefanamer

The following is a summary of “Complementary role of transcriptomic endotyping and protein-based biomarkers for risk stratification in sepsis-associated acute kidney injury,” published in the March 2025 issue of Critical Care by Tavris et al. 

Sepsis-associated acute kidney injury (SA-AKI) a severe complication, with diagnostic and therapeutic progress hindered by biological heterogeneity, while transcriptomic endotyping and biomarker profiling were proposed to improve risk stratification.  

Researchers conducted a retrospective study to evaluate whether combining transcriptomic endotyping with protein-based biomarkers improved risk stratification in SA-AKI.  

They analyzed data from the PredARRT-Sep-Trial, including 167 individuals with critical illness who met the Sepsis-3 criteria. A validated whole-blood gene expression classifier was used to categorize them into 3 transcriptomic endotypes—inflammopathic (IE), adaptive (AE), and coagulopathic (CE). Levels of 8 protein-based biomarkers related to kidney function, vascular integrity, and immune response were measured. The predictive performance for the primary outcome, kidney replacement therapy or death, was evaluated using receiver operating characteristic curve analysis and logistic regression models.  

The results showed that transcriptomic endotyping classified 33% as IE, 42% as AE, and 24% as CE. Disease severity was highest in IE, with 30% meeting the primary outcome, compared to 17% in AE and 10% in CE. Kidney function biomarkers increased with acute kidney injury (AKI) severity across all endotypes, while non-functional biomarkers—neutrophil gelatinase-associated lipocalin (NGAL), soluble urokinase plasminogen activator receptor (suPAR), and bioactive adrenomedullin (bio-ADM)—varied independently of AKI severity, NGAL and suPAR were disproportionately elevated in IE, indicating innate immune dysregulation, while bio-ADM was the strongest risk predictor in CE. Combining transcriptomic endotyping with protein-based biomarkers improved predictive accuracy, with the highest area under the receiver operating characteristic curve at 0.80 (95% confidence interval [CI] 0.72–0.88) for endotyping with bio-ADM and 0.85 (95% CI 0.78–0.93) for endotyping with suPAR. This combination enhanced mortality-related risk stratification.  

Investigators concluded that combining transcriptomic endotyping with protein-based biomarker profiling enhanced risk stratification in SA-AKI. 

Source: ccforum.biomedcentral.com/articles/10.1186/s13054-025-05361-3