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Nephrol Dial Transplant. 2015 Aug;30 Suppl 4:iv86-95. doi: 10.1093/ndt/gfv252.

Prognostic clinical and molecular biomarkers of renal disease in type 2 diabetes.

Author information

1
Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
2
BHF Glasgow Cardiovascular Research Center, University of Glasgow, Glasgow, UK Mosaiques Diagnostics GmbH, Hannover, Germany.
3
University Hospital RWTH, Institute for Molecular Cardiovascular Research, Aachen, Germany.
4
Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria KH Elisabethinen Linz and Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria.
5
Biomarker Design Forschungs GmbH, Vienna, Austria.
6
Biocrates Life Sciences AG, Innsbruck, Austria.
7
emergentec biodevelopment GmbH, Vienna, Austria.
8
Department of Internal Medicine IV (Nephrology and Hypertension), Medical University Innsbruck, Innsbruck, Austria.
9
Steno Diabetes Center, Gentofte, Denmark University of Aarhus, Aarhus, Denmark Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.

Abstract

Diabetic kidney disease occurs in ∼ 25-40% of patients with type 2 diabetes. Given the high risk of progressive renal function loss and end-stage renal disease, early identification of patients with a renal risk is important. Novel biomarkers may aid in improving renal risk stratification. In this review, we first focus on the classical panel of albuminuria and estimated glomerular filtration rate as the primary clinical predictors of renal disease and then move our attention to novel biomarkers, primarily concentrating on assay-based multiple/panel biomarkers, proteomics biomarkers and metabolomics biomarkers. We focus on multiple biomarker panels since the molecular processes of renal disease progression in type 2 diabetes are heterogeneous, rendering it unlikely that a single biomarker significantly adds to clinical risk prediction. A limited number of prospective studies of multiple biomarkers address the predictive performance of novel biomarker panels in addition to the classical panel in type 2 diabetes. However, the prospective studies conducted so far have small sample sizes, are insufficiently powered and lack external validation. Adequately sized validation studies of multiple biomarker panels are thus required. There is also a paucity of studies that assess the effect of treatments on novel biomarker panels and determine whether initial treatment-induced changes in novel biomarkers predict changes in long-term renal outcomes. Such studies can not only improve our healthcare but also our understanding of the mechanisms of actions of existing and novel drugs and may yield biomarkers that can be used to monitor drug response. We conclude that this will be an area to focus research on in the future.

KEYWORDS:

CKD; biomarker panels; metabolomics; novel biomarkers; proteomics

PMID:
26209743
DOI:
10.1093/ndt/gfv252
[Indexed for MEDLINE]

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