Mining the Biomarker Potential of the Urine Peptidome: From Amino Acids Properties to Proteases

Data de publicação: 01/06/2021 Data Ahead of Print: 31/05/2021

Autores da FMUP

• António Sousa Barros

  Autor

• Inês Maria Falcão Sousa Pires Marques

  Autor

• Joaquim Adelino Correia Ferreira Leite Moreira

  Autor

Participantes de fora da FMUP

• Trindade, F
• Silva, J
• Vlahou, A
• Guedes, S
• Vitorino, C
• Ferreira, R
• Amado, F
• Vitorino, R.

Unidades de investigação

• Cirurgia e Fisiologia

• Laboratório Associado RISE- Rede de Investigação em Saúde

  

  Investigador

  Fernando Carlos De Landér Schmitt

• RISE-Health

  

  Investigador

  Fernando Carlos De Landér Schmitt

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.

Keywords

• urine; peptides; proteases; peptidomics; degradomics; biomarkers; predictive; preventive and personalized (3P) medicine; molecular patterns; individualized patient profiling