Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/104805
Title: Mining the Biomarker Potential of the Urine Peptidome: From Amino Acids Properties to Proteases
Authors: Trindade, Fábio
Barros, António Sousa 
Silva, Jéssica
Vlahou, Antonia
Falcão-Pires, Inês
Guedes, Sofia
Vitorino, Carla 
Ferreira, Rita
Leite-Moreira, Adelino
Amado, Francisco 
Vitorino, Rui
Keywords: urine; peptides; proteases; peptidomics; degradomics; biomarkers; predictive, preventive and personalized (3P) medicine; molecular patterns; individualized patient profiling
Issue Date: 31-May-2021
Publisher: MDPI
Project: UIDP/00051/2020 
UIDB/04501/2020 
POCI- 01-0145-FEDER-007628 
UIDB/50006/2020 
POCI-01-0145-FEDER-016385 
FCT - SAICTPAC/0047/2015 
IF/00286/2015 
UIDP/00051/2020 
UIDB/00051/2020 
metadata.degois.publication.title: International Journal of Molecular Sciences
metadata.degois.publication.volume: 22
metadata.degois.publication.issue: 11
Abstract: Native biofluid peptides offer important information about diseases, holding promise as biomarkers. Particularly, the non-invasive nature of urine sampling, and its high peptide concentration, make urine peptidomics a useful strategy to study the pathogenesis of renal conditions. Moreover, the high number of detectable peptides as well as their specificity set the ground for the expansion of urine peptidomics to the identification of surrogate biomarkers for extra-renal diseases. Peptidomics further allows the prediction of proteases (degradomics), frequently dysregulated in disease, providing a complimentary source of information on disease pathogenesis and biomarkers. Then, what does urine peptidomics tell us so far? In this paper, we appraise the value of urine peptidomics in biomarker research through a comprehensive analysis of all datasets available to date. We have mined > 50 papers, addressing > 30 different conditions, comprising > 4700 unique peptides. Bioinformatic tools were used to reanalyze peptide profiles aiming at identifying disease fingerprints, to uncover hidden disease-specific peptides physicochemical properties and to predict the most active proteases associated with their generation. The molecular patterns found in this study may be further validated in the future as disease biomarker not only for kidney diseases but also for extra-renal conditions, as a step forward towards the implementation of a paradigm of predictive, preventive and personalized (3P) medicine.
URI: https://hdl.handle.net/10316/104805
ISSN: 1422-0067
DOI: 10.3390/ijms22115940
Rights: openAccess
Appears in Collections:FFUC- Artigos em Revistas Internacionais
I&D CQC - Artigos em Revistas Internacionais
I&D CNC - Artigos em Revistas Internacionais

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