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Temporal profiles of plasma proteome during childhood development.

Citation
Liu, C. -W., et al. “Temporal Profiles Of Plasma Proteome During Childhood Development.”. Journal Of Proteomics, pp. 321-328.
Center University of Colorado Denver
Author Chih-Wei Liu, Lisa Bramer, Bobbie-Jo Webb-Robertson, Kathleen Waugh, Marian J Rewers, Qibin Zhang
Keywords Childhood development, Human plasma proteome, Pediatric proteome, TMT10, Tandem mass tags, Temporal proteome profiling
Abstract

Human blood plasma proteome reflects physiological changes associated with a child's development as well as development of disease states. While age-specific normative values are available for proteins routinely measured in clinical practice, there is paucity of comprehensive longitudinal data regarding changes in human plasma proteome during childhood. We applied TMT-10plex isobaric labeling-based quantitative proteomics to longitudinally profile the plasma proteome in 10 healthy children during their development, each with 9 serial time points from 9months to 15years of age. In total, 1828 protein groups were identified at peptide and protein level false discovery rate of 1% and with at least two razor and unique peptides. The longitudinal expression profiles of 1747 protein groups were statistically modeled and their temporal changes were categorized into 7 different patterns. The patterns and relative abundance of proteins obtained by LC-MS were also verified with ELISA. To our knowledge, this study represents the most comprehensive longitudinal profiling of human plasma proteome to date. The temporal profiles of plasma proteome obtained in this study provide a comprehensive resource and reference for biomarker studies in childhood diseases. Biological significance: A pediatric plasma proteome database with longitudinal expression patterns of 1747 proteins from neonate to adolescence was provided to the research community. 970 plasma proteins had age-dependent expression trends, which demonstrated the importance of longitudinal profiling study to identify the potential biomarkers specific to childhood diseases, and the requirement of strictly age-matched clinical samples in a cross-sectional study in pediatric population.

Year of Publication
2017
Journal
Journal of proteomics
Volume
152
Number of Pages
321-328
Date Published
12/2017
ISSN Number
1876-7737
DOI
10.1016/j.jprot.2016.11.016
Alternate Journal
J Proteomics
PMID
27890796
PMCID
PMC5219852
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