Literature DB >> 23880038

Clinical value of inflammatory urinary biomarkers in overt diabetic nephropathy: a prospective study.

Jacobien C Verhave1, Josée Bouchard, Rémi Goupil, Vincent Pichette, Soumeya Brachemi, François Madore, Stéphan Troyanov.   

Abstract

AIMS: The evolution of diabetic nephropathy is incompletely accounted by current clinical tools. New biomarkers may refine patient assessment and help monitor therapy. We compared the added predictive value of 7 candidate inflammatory urinary biomarkers to known risk factors of progression.
METHODS: We prospectively followed 83 patients with overt diabetic nephropathy for a median 2.1 years and obtained repeated measurements of proteinuria, IL-1β, IL-6, IL-8, MCP-1, TNF-α, TGF-β1, and PAI-1.
RESULTS: Patients had an initial estimated glomerular filtration rate of 25 ± 9 mL/min/1.73 m(2), blood pressure of 142/69 mmHg and used a median of 4 anti-hypertensive medications over the course of the study. The observed rate of renal function decline was 2.9 ± 3.0 mL/min/1.73 m(2)/year. All urinary biomarkers levels were collinear and for each one except IL-1β, elevated levels predicted a more rapid progression. MCP-1 was the only biomarker increasing during follow-up, which also correlated with a worst outcome. Using multivariate linear regression adjusting for clinical risk factors of progression, urinary MCP-1 and TGF-β1 predicted progression independently and additively to the degree of proteinuria. We dichotomized these 3 biomarkers and observed a renal function decline with 0, 1, 2 or 3 elevated biomarkers of -0.8 ± 1.4, -2.1 ± 2.1, -4.2 ± 2.8 and -6.0 ± 2.8 mL/min/1.73 m(2)/year, respectively (p<0.001).
CONCLUSIONS: Multiple urinary biomarkers predict outcome in overt diabetic nephropathy. However, urinary MCP-1 and TGF-β1 are also independent and additive to proteinuria in predicting the rate of renal function decline and could serve as useful clinical tools in patient risk stratification.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Diabetic nephropathy; MCP-1; Proteinuria; Rate of renal function decline; TGF-β1; Urinary biomarkers

Mesh:

Substances:

Year:  2013        PMID: 23880038     DOI: 10.1016/j.diabres.2013.07.006

Source DB:  PubMed          Journal:  Diabetes Res Clin Pract        ISSN: 0168-8227            Impact factor:   5.602


  20 in total

1.  Urinary monocyte chemoattractant protein-1 and hepcidin and early diabetic nephropathy lesions in type 1 diabetes mellitus.

Authors:  Gudeta D Fufaa; E Jennifer Weil; Robert G Nelson; Robert L Hanson; William C Knowler; Brad H Rovin; Haifeng Wu; Jon B Klein; Theodore E Mifflin; Harold I Feldman; Ramachandran S Vasan; Paul L Kimmel; John W Kusek; Michael Mauer
Journal:  Nephrol Dial Transplant       Date:  2015-02-03       Impact factor: 5.992

2.  Longitudinal Changes in Measured Glomerular Filtration Rate, Renal Fibrosis and Biomarkers in a Rat Model of Type 2 Diabetic Nephropathy.

Authors:  Zhi Su; Deborah Widomski; Ji Ma; Marian Namovic; Arthur Nikkel; Laura Leys; Lauren Olson; Katherine Salte; Diana Donnelly-Roberts; Timothy Esbenshade; Steve McGaraughty
Journal:  Am J Nephrol       Date:  2016-10-14       Impact factor: 3.754

Review 3.  Urinary biomarkers for early diabetic nephropathy: beyond albuminuria.

Authors:  So-Young Lee; Mary E Choi
Journal:  Pediatr Nephrol       Date:  2014-07-25       Impact factor: 3.714

Review 4.  Role of Kidney Biopsies for Biomarker Discovery in Diabetic Kidney Disease.

Authors:  Helen C Looker; Michael Mauer; Robert G Nelson
Journal:  Adv Chronic Kidney Dis       Date:  2018-03       Impact factor: 3.620

5.  Association of Urinary Biomarkers of Inflammation, Injury, and Fibrosis with Renal Function Decline: The ACCORD Trial.

Authors:  Girish N Nadkarni; Veena Rao; Faramarz Ismail-Beigi; Vivian A Fonseca; Sudhir V Shah; Michael S Simonson; Lloyd Cantley; Prasad Devarajan; Chirag R Parikh; Steven G Coca
Journal:  Clin J Am Soc Nephrol       Date:  2016-05-17       Impact factor: 8.237

Review 6.  Cellular crosstalk of glomerular endothelial cells and podocytes in diabetic kidney disease.

Authors:  Shan Jiang; Manyu Luo; Xue Bai; Ping Nie; Yuexin Zhu; Hangxi Cai; Bing Li; Ping Luo
Journal:  J Cell Commun Signal       Date:  2022-01-18       Impact factor: 5.908

7.  A panel of novel biomarkers representing different disease pathways improves prediction of renal function decline in type 2 diabetes.

Authors:  Michelle J Pena; Andreas Heinzel; Georg Heinze; Alaa Alkhalaf; Stephan J L Bakker; Tri Q Nguyen; Roel Goldschmeding; Henk J G Bilo; Paul Perco; Bernd Mayer; Dick de Zeeuw; Hiddo J Lambers Heerspink
Journal:  PLoS One       Date:  2015-05-14       Impact factor: 3.240

Review 8.  Diabetic nephropathy: What does the future hold?

Authors:  R M Montero; A Covic; L Gnudi; D Goldsmith
Journal:  Int Urol Nephrol       Date:  2015-10-05       Impact factor: 2.370

Review 9.  Potential Role of Serum and Urinary Biomarkers in Diagnosis and Prognosis of Diabetic Nephropathy.

Authors:  Carole G Campion; Oraly Sanchez-Ferras; Sri N Batchu
Journal:  Can J Kidney Health Dis       Date:  2017-05-22

Review 10.  Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease.

Authors:  Michelle J Pena; Harald Mischak; Hiddo J L Heerspink
Journal:  Diabetologia       Date:  2016-06-25       Impact factor: 10.122

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