Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease

Pena, M. J., Mischak, H. and Heerspink, H. J.L. (2016) Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease. Diabetologia, 59(9), pp. 1819-1831. (doi: 10.1007/s00125-016-4001-9) (PMID:27344310) (PMCID:PMC4969331)

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The past decade has resulted in multiple new findings of potential proteomic biomarkers of diabetic kidney disease (DKD). Many of these biomarkers reflect an important role in the (patho)physiology and biological processes of DKD. Situations in which proteomics could be applied in clinical practice include the identification of individuals at risk of progressive kidney disease and those who would respond well to treatment, in order to tailor therapy for those at highest risk. However, while many proteomic biomarkers have been discovered, and even found to be predictive, most lack rigorous external validation in sufficiently powered studies with renal endpoints. Moreover, studies assessing short-term changes in the proteome for therapy-monitoring purposes are lacking. Collaborations between academia and industry and enhanced interactions with regulatory agencies are needed to design new, sufficiently powered studies to implement proteomics in clinical practice.

Item Type:Articles
Additional Information:Work by the authors is supported by the Novo Nordisk Foundation, grant number NNF14SA0003 (Personalising Treatment of Diabetic Nephropathy, PROTON).
Glasgow Author(s) Enlighten ID:Mischak, Professor Harald
Authors: Pena, M. J., Mischak, H., and Heerspink, H. J.L.
College/School:College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
Journal Name:Diabetologia
ISSN (Online):1432-0428
Published Online:25 June 2016
Copyright Holders:Copyright © 2016 The Authors
First Published:First published in Diabetologia 59(9): 1819-1831
Publisher Policy:Reproduced under a Creative Commons license

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