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Biomarkers of diabetic kidney disease.
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- Author(s): Colhoun HM;Colhoun HM; Marcovecchio ML; Marcovecchio ML
- Source:
Diabetologia [Diabetologia] 2018 May; Vol. 61 (5), pp. 996-1011. Date of Electronic Publication: 2018 Mar 08.- Publication Type:
Journal Article; Review- Language:
English - Source:
- Additional Information
- Source: Publisher: Springer Verlag Country of Publication: Germany NLM ID: 0006777 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-0428 (Electronic) Linking ISSN: 0012186X NLM ISO Abbreviation: Diabetologia Subsets: MEDLINE
- Publication Information: Original Publication: Berlin Springer Verlag
- Subject Terms: Glomerular Filtration Rate*; Albuminuria/*diagnosis ; Biomarkers/*analysis ; Diabetes Mellitus, Type 1/*complications ; Diabetes Mellitus, Type 2/*complications ; Diabetic Nephropathies/*diagnosis; Albuminuria/physiopathology ; Algorithms ; Animals ; Disease Progression ; Humans ; Kidney/metabolism ; Kidney Failure, Chronic/complications ; Metabolomics ; MicroRNAs/metabolism ; Prognosis ; Programmed Cell Death 1 Ligand 2 Protein/metabolism ; Proteomics
- Abstract: Diabetic kidney disease (DKD) remains one of the leading causes of reduced lifespan in diabetes. The quest for both prognostic and surrogate endpoint biomarkers for advanced DKD and end-stage renal disease has received major investment and interest in recent years. However, at present no novel biomarkers are in routine use in the clinic or in trials. This review focuses on the current status of prognostic biomarkers. First, we emphasise that albuminuria and eGFR, with other routine clinical data, show at least modest prediction of future renal status if properly used. Indeed, a major limitation of many current biomarker studies is that they do not properly evaluate the marginal increase in prediction on top of these routinely available clinical data. Second, we emphasise that many of the candidate biomarkers for which there are numerous sporadic reports in the literature are tightly correlated with each other. Despite this, few studies have attempted to evaluate a wide range of biomarkers simultaneously to define the most useful among these correlated biomarkers. We also review the potential of high-dimensional panels of lipids, metabolites and proteins to advance the field, and point to some of the analytical and post-analytical challenges of taking initial studies using these and candidate approaches through to actual clinical biomarker use.
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J Clin Med. 2015 Jul 17;4(7):1498-517. (PMID: 26239688) - Contributed Indexing: Keywords: Biomarker; Diabetic kidney disease; Epidemiology; Nephropathy; Review
- Accession Number: 0 (Biomarkers)
0 (MicroRNAs)
0 (PDCD1LG2 protein, human)
0 (Programmed Cell Death 1 Ligand 2 Protein) - Publication Date: Date Created: 20180310 Date Completed: 20190128 Latest Revision: 20190418
- Publication Date: 20221213
- Accession Number: PMC6448994
- Accession Number: 10.1007/s00125-018-4567-5
- Accession Number: 29520581
- Source:
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