Abstract: FR-PO0061
Metabolomic Analysis for Biomarker Identification in Severe AKI in Critically Ill Patients
Session Information
- AKI: Epidemiology, Risk Factors, and Prevention
November 07, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Acute Kidney Injury
- 101 AKI: Epidemiology, Risk Factors, and Prevention
Authors
- Zuñiga Gonzalez, Erick Yasar, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, CDMX, Mexico
- Mercado Hernández, Yazmin Alejandra, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, CDMX, Mexico
- Del Toro-Cisneros, Noemi, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, CDMX, Mexico
- Rincon, Rodolfo, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, CDMX, Mexico
- Vega, Olynka, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, CDMX, Mexico
Background
Acute kidney injury (AKI) is a frequent complication linked to high morbidity and mortality. Metabolomics allows global metabolic profiling and is a promising tool for identifying early biomarkers of kidney dysfunction.
Methods
We prospectively enrolled 124 ICU patients without evidence of AKI on admission. Untargeted serum metabolomic profiling was performed using gas chromatography-mass spectrometry (GC/MS), identifying 53 metabolites. Principal component analysis (PCA) and volcano plots were used to explore metabolic differences between patients who developed AKI. Logistic regression models were applied to evaluate associations between specific metabolites and AKI, adjusted for SOFA and Charlson scores.
Results
PCA showed partial separation between AKI and non-AKI groups. The most discriminative metabolites were gluconic acid and valine. Volcano plot analysis showed lower levels of 1,5-anhydroglucitol and higher levels of gluconic acid, cysteine, myo-inositol, and 3,4-dihydroxybutanoic acid (log2-FC > 0.5, p < 0.05) in AKI patients. After adjusting for SOFA and Charlson scores, only gluconic acid and 3,4-dihydroxybutanoic acid remained significantly associated with AKI development (AUC 0.75, p<0.001). (Figure1)
Conclusion
Elevated gluconic acid and 3,4-dihydroxybutanoic indicate early metabolic changes linked to oxidative stress and mitochondrial dysfunction and risk of AKI, suggesting their potential as early biomarkers for risk stratification and intervention.
Figure 1. Exploratory and predictive analysis of the metabolomic profile in AKI. A. Principal component analysis (PLS-DA) of serum metabolites in patients with and without AKI. B. VIP scores showing top metabolites differentiating both groups. C. Volcano plot of significantly altered metabolites (fold change >0.5, p<0.05). D. ROC curves of key metabolites before and after adjustment for Charlson and SOFA.
Funding
- Government Support – Non-U.S.