Diabetic kidney disease (DKD) is the leading cause of morbidity and mortality in diabetic patients. Defining risk factors for DKD using a reductionist approach has proven challenging. Integrative omics-based systems biology tools have shed new insights in our understanding of DKD and have provided several key breakthroughs for identifying novel predictive and diagnostic biomarkers. In this review, we highlight the role of the Warburg effect in DKD and potential regulating factors such as sphingomyelin, fumarate, and pyruvate kinase muscle isozyme M2 in shifting glucose flux from complete oxidation in mitochondria to the glycolytic pathway and its principal branches. With the development of highly sensitive instruments and more advanced automatic bioinformatics tools, we believe that omics analyses and imaging techniques will focus more on singular-cell-level studies, which will allow in-depth understanding of DKD and pave the path for personalized kidney precision medicine.
Keywords: Diabetic kidney disease; aerobic glycolysis; metabolomics; mitochondrion; the Warburg effect.
Published by Elsevier Inc.