Evidence map›Paper›PMID 26257595›Full record

ArticleClinical proteomics2015

Urinary proteomics in chronic kidney disease: diagnosis and risk of progression beyond albuminuria.

Marius A Øvrehus, Petra Zürbig, Bjørn E Vikse, Stein I Hallan

Abstract read
In one paragraph

Article in Clinical proteomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

32 citing papers in PubMed.

  1. Review
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  10. Recent ambient temperature and fine particulate matter (PMThe Science of the total environment · 2024
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  18. Urinary Peptidomic Biomarkers in Kidney Diseases.International journal of molecular sciences · 2019
    Review
  19. Observational
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Marius A ØvrehusDepartment of Nephrology, St Olav University Hospital, Trondheim, Norway ; Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway.
Petra ZürbigMosaiques Diagnostics GmbH, Hannover, Germany.
Bjørn E VikseRenal Research Group, Department of Clinical Medicine, University of Bergen, Bergen, Norway ; Department of Medicine, Haugesund Hospital, Haugesund, Norway.
Stein I HallanDepartment of Nephrology, St Olav University Hospital, Trondheim, Norway ; Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway ; Center of Renal Translational Medicine, University of California San Diego (UCSD), La Jolla, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe contrast between a high prevalence of chronic kidney disease (CKD) and the low incidence of end-stage renal disease highlights the need for new biomarkers of progression beyond albuminuria testing. Urinary proteomics is a promising method, but more studies focusing on progression rate and patients with hypertensive nephropathy are needed.

resultsWe analyzed urine samples with capillary electrophoresis coupled to a mass-spectrometer from 18 well characterized patients with CKD stage 4-5 (of whom six with hypertensive nephropathy) and 17 healthy controls. Classification scores based on a previously developed panel of 273 urinary peptides were calculated and compared to urine albumin dipstick results. Urinary proteomics classified CKD with a sensitivity of 0.95 and specificity of 1.00. Overall diagnostic accuracy (area under ROC curve) was 0.98, which was better than for albuminuria (0.85, p = 0.02). Results for hypertensive nephropathy were similar to other CKD diagnoses. Adding the proteomic score to an albuminuria model improved detection of rapid kidney function decline (>4 ml/min/1.73 m(2) per year) substantially: area under ROC curve increased from 0.762 to 0.909 (p = 0.042), and 38% of rapid progressors were correctly reclassified to a higher risk and 55% of slow progressors were correctly reclassified to a lower risk category. Reduced excretion of collagen types I-III, uromodulin, and other indicators of interstitial inflammation, fibrosis and tubular dysfunction were associated with CKD diagnosis and rapid progression. Patients with hypertensive nephropathy displayed the same findings as other types of CKD.

conclusionsUrinary proteomic analyses had a high diagnostic accuracy for CKD, including hypertensive nephropathy, and strongly improved identification of patients with rapid kidney function decline beyond albuminuria testing.

Indexed as

AlbuminuriaChronic kidney diseaseDisease progressionHypertensive nephropathyProteomicsUrine

Identifiers

PMID26257595
PMCPMC4528848

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.