Diabetic kidney disease hits many with type 2 diabetes and worsens steadily. KDIGO guidelines split patients into low, moderate, and high risk. Serum metabolomics might track this shift early. This study profiles changes across groups to find biomarkers for monitoring. The results were published in the Journal of Diabetes and its Complications.
Targeted Metabolomics in Risk Tiers
Researchers ran untargeted liquid chromatography–quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) on serum from 48 T2DM patients. They grouped 16 each into low, moderate, and high DKD risk per KDIGO. Picked differential metabolites by p-value, log fold change, and VIP score. Then did pathway enrichment to link findings.
Clear Metabolite Patterns by Risk
Low vs moderate risk showed five differing metabolites, moderate vs high had three, and low vs high had three. Sphinganine, arachidonic acid, and ornithine fell as risk rose. AFMK, L-arginine, lactosylceramide (LacCer), and lysophosphatidylcholine (lysoPC) climbed with higher risk. These tied to key pathways like arginine-proline metabolism, sphingolipid metabolism, glycerophospholipid metabolism, arachidonic acid metabolism, and tryptophan metabolism.
Biomarkers for Smarter DKD Care
Amino acid, lipid, and inflammation paths change step-by-step with DKD risk. Stage-specific profiles like lower sphinganine or higher lysoPC could flag progression. Use them to detect and track DKD in T2DM clinics.