BACKGROUND: Sepsis-associated acute kidney injury (SA-AKI) is a critical condition associated with high morbidity and mortality rates. Elucidating metabolic alterations and identifying early diagnostic biomarkers is essential for timely intervention and precise treatment. The study aims to characterize the metabolic features of SA-AKI and identify specific biomarkers for its early diagnosis.
METHOD: Using existing plasma metabolomics data from 20 healthy controls (HC group), 22 sepsis patients with acute kidney injury (AKI, AKI group), and 31 sepsis patients without AKI (N-AKI group), we performed three comparative analyses (N-AKI vs. HC, AKI vs. HC, and AKI vs. N-AKI). This approach identified the core perturbed metabolic pathways and set of shared differentially expressed metabolites (DEMs). Correlation analysis was performed between the shared DEMs and serum creatinine levels, and those demonstrating a strong correlation (r > 0.6) were selected as final diagnostic biomarkers.
RESULTS: Three pairwise comparative analyses (N-AKI vs. HC, AKI vs. HC, and AKI vs. N-AKI) revealed three core metabolic pathways: ascorbate and aldarate metabolism, glycerophospholipid metabolism, and sphingolipid metabolism. We identified 161 DEMs that were common to all comparison group. From this shared pool, five DEMs demonstrated a strong correlation with serum creatinine levels (∣r∣ > 0.6) and were selected as early diagnostic biomarkers: 3h-Indole-3-propanoic acid, α-amino- (3I3PA), lysophosphatidylcholine (LysoPC) (18:1/0:0), LPC 18:2, N-methylethanolaminium phosphate (NMEAP), and pseudouridine.
CONCLUSION: By analyzing three distinct clinical groups, this untargeted metabolomics study identified three core metabolic pathways and five potential early diagnostic biomarkers for SA-AKI. These findings provide crucial insights that could facilitate the development of early diagnoses and precise interventions for this condition.
