Temporal profiles of plasma proteome during childhood development
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Published on: April 21, 2022
Chih-Wei Liu1, Lisa Bramer2, Bobbie-Jo Webb-Robertson2
1Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC, United States.
Insights
This study presents the most comprehensive longitudinal profiling of the human plasma proteome in children, revealing age-dependent protein expression patterns. This resource aids biomarker discovery for pediatric diseases.
Area of Science:
- Biochemistry
- Proteomics
- Pediatrics
Background:
- Human plasma proteome changes with development and disease.
- Limited longitudinal data exists for childhood plasma proteome.
- Age-specific normative values are scarce for many proteins.
Purpose of the Study:
- To longitudinally profile the plasma proteome in healthy children from infancy to adolescence.
- To establish a comprehensive database of pediatric plasma proteome changes.
- To identify age-dependent protein expression patterns for biomarker discovery.
Main Methods:
- Quantitative proteomics using TMT-10plex isobaric labeling.
- LC-MS/MS analysis of plasma samples from 10 children across 9 time points (9 months to 15 years).
- Statistical modeling of longitudinal expression profiles and verification with ELISA.
Main Results:
- Identified 1828 protein groups with high confidence.
- Statistically modeled longitudinal expression profiles for 1747 protein groups, revealing 7 distinct temporal patterns.
- Discovered 970 plasma proteins with significant age-dependent expression trends.
Conclusions:
- Provides the most comprehensive longitudinal pediatric plasma proteome database to date.
- Highlights the critical need for longitudinal data and age-matched samples in pediatric biomarker studies.
- Offers a valuable resource for understanding childhood development and identifying biomarkers for pediatric diseases.
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.
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