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- W2794972088 abstract "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." @default.
- W2794972088 created "2018-04-06" @default.
- W2794972088 creator A5004926290 @default.
- W2794972088 creator A5071634737 @default.
- W2794972088 creator A5088903449 @default.
- W2794972088 date "2018-03-01" @default.
- W2794972088 modified "2023-10-18" @default.
- W2794972088 title "The Warburg Effect in Diabetic Kidney Disease" @default.
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- W2794972088 doi "https://doi.org/10.1016/j.semnephrol.2018.01.002" @default.
- W2794972088 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5973839" @default.
- W2794972088 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29602394" @default.
- W2794972088 hasPublicationYear "2018" @default.
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