Deciphering the disease-related molecular networks using urine proteomics

作者：Dias Bastos Paulo Andre; Vlahou Antonia; Leite Moreira Adelino; Santos Lucio Lara; Ferreira Rita; Vitorino Rui

来源：TrAC-Trends in Analytical Chemistry, 2017, 94: 200-209.

DOI：10.1016/j.trac.2017.07.018

• Protein profiling
• Bioinformatics
• Cancer
• Cardiovascular diseases
• Autoimmune
• Inflammation

Despite the large number of studies focused on the impact of diseases on urine proteome, few outputs with clinical meaning were retrieved so far. The goal of this study was to identify the biological processes modulated in urine by distinct diseases to better understand disease pathogenesis and to identify urinary proteins with potential diagnosis value. We searched PubMed and SCOPUS databases for mass spectrometry-based experimental papers and pooled differentially expressed proteins by disease and target organic system.
A total of 2572 differentially expressed proteins or peptides were pooled from 89 studies focused on 57 diseases. Data analysis highlighted inflammation as a biological process modulated by all diseases. However, specific inflammatory signatures are associated with specific diseases and/or aetiologies. Moreover, specific biological processes were identified for specific groups of pathologies and unique proteins identified. Overall, integrative data analysis from urine proteomics/peptidomics reinforces the clinical potential of this body fluid for the clinical management of distinct diseases.

• 出版日期2017-9