Abstract: SA-PO0296
Metabolomic Profiling in Diabetic Nephropathy: Uncovering Biochemical Signatures
Session Information
- Diabetic Kidney Disease: Basic and Translational Science Advances - 2
November 08, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Diabetic Kidney Disease
- 701 Diabetic Kidney Disease: Basic
Authors
- Ali, Hamad, Dasman Diabetes Institute, Kuwait City, Al Asimah Governate, Kuwait
- Abu-Farha, Mohamed, Dasman Diabetes Institute, Kuwait City, Al Asimah Governate, Kuwait
- Malik, Mohammad Zubbair, Dasman Diabetes Institute, Kuwait City, Al Asimah Governate, Kuwait
- Bahbahani, Yousif, Dasman Diabetes Institute, Kuwait City, Al Asimah Governate, Kuwait
- Abubaker, Jehad, Dasman Diabetes Institute, Kuwait City, Al Asimah Governate, Kuwait
- Al-Mulla, Fahd, Dasman Diabetes Institute, Kuwait City, Al Asimah Governate, Kuwait
Background
Diabetic nephropathy (DN) is a common small blood vessel problem in people with type 2 diabetes and a main reason for kidney failure. Detecting and treating the disease early is important to slow its progress, but there are still only a few reliable biomarkers available. This study aimed to explore the plasma metabolomic signatures associated with DN and identify potential biomarkers and metabolic pathways altered during disease progression.
Methods
This cross-sectional study analyzed plasma samples from DN patients (n=18) and healthy controls (n=14) using high-resolution mass spectrometry. Multivariate analyses (PCA, PLS-DA) and random forest classification identified key differential metabolites. Hierarchical clustering and pathway enrichment were used to explore biological significance.
Results
A total of 318 metabolites were differentially abundant, with marked shifts in lipid and amino acid metabolism. Hierarchical clustering illustrated a clear transition from high to low abundance of key metabolites with disease progression. Lipid metabolism particularly involving cholesteryl esters (CE(18:2)), sphingomyelins (SM(33:1)), and triglycerides (TG(48:3)) was profoundly altered. Random forest analysis highlighted CE(18:2), SM(33:1), PC(30:2), and taurine as key discriminatory metabolites. Pathway enrichment analysis identified significant disruptions in branched-chain amino acid degradation, ether lipid metabolism, glutathione metabolism, and porphyrin metabolism, reflecting oxidative stress and altered energy metabolism in DN.
Conclusion
Our findings reveal profound metabolic reprogramming in diabetic nephropathy, with lipid and amino acid metabolites playing a central role in disease pathogenesis. These metabolites may serve as novel biomarkers for early detection and therapeutic targeting in DN.