Literature DB >> 27528550

Urinary peptidomics provides a noninvasive humanized readout of diabetic nephropathy in mice.

Julie Klein1, Adela Ramirez-Torres2, Anette Ericsson3, Yufeng Huang4, Benjamin Breuil1, Justyna Siwy2, Harald Mischak5, Xiao-Rong Peng3, Jean-Loup Bascands6, Joost P Schanstra7.   

Abstract

Nephropathy is among the most frequent complications of diabetes and the leading cause of end-stage renal disease. Despite the success of novel drugs in animal models, the majority of the subsequent clinical trials employing those drugs targeting diabetic nephropathy failed. This lack of translational value may in part be due to an inadequate comparability of human disease and animal models that often capture only a few aspects of disease. Here we overcome this limitation by developing a multimolecular noninvasive humanized readout of diabetic nephropathy based on urinary peptidomics. The disease-modified urinary peptides of 2 type 2 diabetic nephropathy mouse models were identified and compared with previously validated urinary peptide markers of diabetic nephropathy in humans to generate a classifier composed of 21 ortholog peptides. This classifier predicted the response to disease and treatment with inhibitors of the renin-angiotensin system in mice. The humanized classifier was significantly correlated with glomerular lesions. Using a human type 2 diabetic validation cohort of 207 patients, the classifier also distinguished between patients with and without diabetic nephropathy, and their response to renin-angiotensin system inhibition. Thus, a combination of multiple molecular features common to both human and murine disease could provide a significant change in translational drug discovery research in type 2 diabetic nephropathy.
Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  albuminuria; angiotensin-converting enzyme inhibitor; diabetic nephropathy; proteomic analysis; urine

Mesh:

Substances:

Year:  2016        PMID: 27528550     DOI: 10.1016/j.kint.2016.06.023

Source DB:  PubMed          Journal:  Kidney Int        ISSN: 0085-2538            Impact factor:   18.998


  11 in total

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Authors:  Yoshitaka Isaka
Journal:  Ann Transl Med       Date:  2016-10

Review 2.  The tissue proteome in the multi-omic landscape of kidney disease.

Authors:  Markus M Rinschen; Julio Saez-Rodriguez
Journal:  Nat Rev Nephrol       Date:  2020-10-07       Impact factor: 28.314

3.  Association of kidney fibrosis with urinary peptides: a path towards non-invasive liquid biopsies?

Authors:  Pedro Magalhães; Martin Pejchinovski; Katerina Markoska; Miroslaw Banasik; Marian Klinger; Dominika Švec-Billá; Ivan Rychlík; Merita Rroji; Arianna Restivo; Giovambattista Capasso; Flaviu Bob; Adalbert Schiller; Alberto Ortiz; Maria Vanessa Perez-Gomez; Pablo Cannata; Maria Dolores Sanchez-Niño; Radomir Naumovic; Voin Brkovic; Momir Polenakovic; William Mullen; Antonia Vlahou; Petra Zürbig; Lars Pape; Franco Ferrario; Colette Denis; Goce Spasovski; Harald Mischak; Joost P Schanstra
Journal:  Sci Rep       Date:  2017-12-05       Impact factor: 4.379

4.  Urinary peptidomics analysis reveals proteases involved in diabetic nephropathy.

Authors:  Magdalena Krochmal; Georgia Kontostathi; Pedro Magalhães; Manousos Makridakis; Julie Klein; Holger Husi; Johannes Leierer; Gert Mayer; Jean-Loup Bascands; Colette Denis; Jerome Zoidakis; Petra Zürbig; Christian Delles; Joost P Schanstra; Harald Mischak; Antonia Vlahou
Journal:  Sci Rep       Date:  2017-11-09       Impact factor: 4.379

5.  Quantitative peptidomics of endogenous peptides involved in TGF-β1-induced epithelial mesenchymal transition of renal epithelial cells.

Authors:  Rattiyaporn Kanlaya; Visith Thongboonkerd
Journal:  Cell Death Discov       Date:  2018-02-06

6.  Urinary peptide-based classifier CKD273: towards clinical application in chronic kidney disease.

Authors:  Claudia Pontillo; Harald Mischak
Journal:  Clin Kidney J       Date:  2017-03-29

7.  The use of urinary proteomics in the assessment of suitability of mouse models for ageing.

Authors:  Esther Nkuipou-Kenfack; Joost P Schanstra; Seerat Bajwa; Martin Pejchinovski; Claire Vinel; Cédric Dray; Philippe Valet; Jean-Loup Bascands; Antonia Vlahou; Thomas Koeck; Melanie Borries; Hauke Busch; Wibke Bechtel-Walz; Tobias B Huber; Karl L Rudolph; Andreas Pich; Harald Mischak; Petra Zürbig
Journal:  PLoS One       Date:  2017-02-15       Impact factor: 3.240

8.  Apelin affects the mouse aging urinary peptidome with minimal effects on kidney.

Authors:  Claire Vinel; Joost P Schanstra; Franck Boizard; Ophélie Péreira; Johanna Auriau; Alizée Dortignac; Benjamin Breuil; Guylène Feuillet; Esther Nkuipou-Kenfack; Petra Zürbig; Philippe Valet; Jean-Loup Bascands; Cédric Dray; Colette Denis
Journal:  Sci Rep       Date:  2019-07-23       Impact factor: 4.379

9.  Dual mTOR/PI3K inhibition limits PI3K-dependent pathways activated upon mTOR inhibition in autosomal dominant polycystic kidney disease.

Authors:  Yang Liu; Martin Pejchinovski; Xueqi Wang; Xuebin Fu; Deborah Castelletti; Terry J Watnick; Alexandre Arcaro; Justyna Siwy; William Mullen; Harald Mischak; Andreas L Serra
Journal:  Sci Rep       Date:  2018-04-03       Impact factor: 4.379

10.  Connectivity mapping of glomerular proteins identifies dimethylaminoparthenolide as a new inhibitor of diabetic kidney disease.

Authors:  Julie Klein; Cécile Caubet; Mylène Camus; Manousos Makridakis; Colette Denis; Marion Gilet; Guylène Feuillet; Simon Rascalou; Eric Neau; Luc Garrigues; Olivier Thillaye du Boullay; Harald Mischak; Bernard Monsarrat; Odile Burlet-Schiltz; Antonia Vlahou; Jean Sébastien Saulnier-Blache; Jean-Loup Bascands; Joost P Schanstra
Journal:  Sci Rep       Date:  2020-09-10       Impact factor: 4.379

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