We live in an age of "big data." One could argue that nephrology was at the forefront of such analyses with early trials using USRDS and DOPPS data. Proteomic and metabolomic studies are representative of modern-day big-data analyses and distinct from databases such as USRDS and DOPPS. Traditional databases include data from a large number of patients over an increasing period of time, but proteomic/metabolomic studies analyze large volumes of data generated by a small number of patients in a shorter period of time. This feature makes such studies attractive for revealing patterns that may otherwise take years to uncover. One such study, by Gordin and colleagues , combines proteomic and metabolomic analyses to identify new targets for diabetic kidney disease.
They focused on glycolytic pathway enzymes (and their metabolites) and pyruvate kinase M2 (PKM2) in particular. PKM2 is upregulated in patients with diabetes who do not have chronic kidney disease (CKD). It and other upregulated enzymes are thought to play a role in protecting against diabetic kidney disease. The researchers took two approaches to identify PKM2 and other biomarkers that could provide kidney protection against diabetes. Part one entailed tissue sampling of post-mortem kidneys, and part two used proteomic and metabolomic analyses.
For the post-mortem kidney analysis, they stained for eight enzymes within glucose metabolic pathways, including PKM2. PKM2 levels were higher in patients without diabetes compared with those with diabetes, especially those with type 2 diabetes.
Figure 1.
Within the group of patients with type 2 diabetes, those without CKD had higher PKM2 levels than those with normal kidney function. The findings from this small portion of the study suggest that PKM2 levels are significantly altered in patients with diabetes and with concomitant kidney disease.
Urine and serum samples from patients enrolled in the Medalist Study were used for part two. Over 1100 proteins and nearly 60 metabolites were analyzed using a DNA aptamer-based assay and liquid chromatography, respectively. Levels of each protein and metabolite were categorized on the basis of presence or absence of CKD. PKM2, as well as 140 other proteins involved in glucose metabolism, was elevated in those without CKD compared with those with CKD. In the metabolomics portion of the study, two metabolites (one of which was pyruvate, a metabolite of PKM2) were upregulated in those without CKD.
Future Targets
Overall, this study is a welcome addition to the burgeoning data and analyses arising from proteomic and metabolomic studies. Certain proteins/metabolites are significantly altered in specific disease states; if these can be reliably identified in diabetic kidney disease, then additional studies may characterize their protective or deleterious effects and, ultimately, identify future therapeutic targets.
What proteins/metabolites do you think are most promising in diabetic kidney disease? Share your ideas (and citations) in the comments section below.
Tejas Desai is a practicing nephrologist in Charlotte, North Carolina. His academic interests include the use of social media for physician, student, and patient education. He is the founder of NOD Analytics, a free social media analytics group that serves the medical education community. He has two wonderful children and enjoys spending time with them and his wife.
Follow Dr Desai on Twitter: @nephondemand
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Any views expressed above are the author's own and do not necessarily reflect the views of WebMD or Medscape.
Cite this: Tejas P. Desai. Promising Biomarkers for Diabetic Nephropathy - Medscape - Nov 12, 2019.
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