title: The role of urinary peptidomics in kidney disease research.
abstract: Urinary peptidomics focuses on endogenous urinary peptide content. Many studies now show the usefulness of this approach for the discovery and validation of biomarkers in kidney diseases that are as varied as chronic kidney disease, acute kidney injury, congenital anomalies of the kidney and the urinary tract, and polycystic kidney disease. Most studies focus on chronic kidney disease and demonstrate that urinary peptidome analysis can substantially contribute to early detection and stratification of patients with chronic kidney disease. A number of multicenter studies are ongoing that aim further validation in a clinical setting and broaden the applicability of urinary peptides. The association of urinary peptides with kidney disease also starts to deliver information on the pathophysiology of kidney disease with emphasis on extracellular matrix remodeling. Bioinformatic peptide centric tools have been developed that allow to model the changes in protease activity involved in kidney disease, based on the urinary peptidome content. A novel application of urinary peptidome analysis is the back-translation of results obtained in humans to animals for animal model validation and improvement of readout in these preclinical models. In conclusion, urinary peptidomics not only contribute to detection and stratification of kidney disease in the clinic, but might also create a new impulse in drug discovery through better insight in the pathophysiology of disease and optimized translatability of animal models.
authors.affiliation: Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institute of Cardiovascular and Metabolic Disease, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France.
authors.forename: Julie
authors.initials: J
authors.lastname: Klein
authors.affiliation: Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institute of Cardiovascular and Metabolic Disease, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France.
authors.forename: Jean-Loup
authors.initials: JL
authors.lastname: Bascands
authors.affiliation: Mosaiques Diagnostics and Therapeutics, Hannover, Germany; BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical, Glasgow, Scotland.
authors.forename: Harald
authors.initials: H
authors.lastname: Mischak
authors.affiliation: Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institute of Cardiovascular and Metabolic Disease, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France. Electronic address: joost-peter.schanstra@inserm.fr.
authors.forename: Joost P
authors.initials: JP
authors.lastname: Schanstra
mesh_terms: D000818:Animals; D015415:Biomarkers / Q000652:urine; D035843:Biomedical Research / Q000379:methods*; D019295:Computational Biology; D004195:Disease Models, Animal; D006801:Humans; D007674:Kidney Diseases / Q000175:diagnosis / Q000503:physiopathology / Q000628:therapy / Q000652:urine*; D009398:Nephrology / Q000379:methods*; D010455:Peptides / Q000652:urine*; D011237:Predictive Value of Tests; D011379:Prognosis; D040901:Proteomics / Q000379:methods*; D016482:Urinalysis
chemical_list: D015415:Biomarkers; D010455:Peptides
keywords: biomarkers; chronic kidney disease; pathophysiology; patient stratification; proteins and peptides; urine