Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC, United States.
Applied Statistics & Computational Modeling, Pacific Northwest National Laboratory, Richland, WA, United States.
J Proteomics. 2017 Jan 30;152:321-328. doi: 10.1016/j.jprot.2016.11.016. Epub 2016 Nov 23.
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.
人类血浆蛋白质组反映了与儿童发育以及疾病状态发展相关的生理变化。虽然在临床实践中常规测量的蛋白质有特定年龄的规范值,但关于儿童期血浆蛋白质组变化的全面纵向数据却很少。我们应用 TMT-10plex 等压标记定量蛋白质组学技术,对 10 名健康儿童在发育过程中的血浆蛋白质组进行了纵向分析,每个儿童有 9 个时间点,时间跨度从 9 个月到 15 岁。总共在肽和蛋白质水平上鉴定出了 1828 个蛋白质组,假发现率为 1%,并且至少有两个剃刀和独特的肽。1747 个蛋白质组的纵向表达谱进行了统计学建模,它们的时间变化分为 7 种不同的模式。通过 LC-MS 获得的蛋白质组的模式和相对丰度也通过 ELISA 进行了验证。据我们所知,这是迄今为止对人类血浆蛋白质组进行的最全面的纵向分析。本研究中获得的血浆蛋白质组的时间图谱为儿童疾病的生物标志物研究提供了全面的资源和参考。生物学意义:提供了一个具有从新生儿到青春期的 1747 种蛋白质纵向表达模式的儿科血浆蛋白质组数据库。970 种血浆蛋白具有年龄依赖性表达趋势,这表明纵向分析研究对于识别特定于儿童疾病的潜在生物标志物非常重要,并且在儿科人群的横断面研究中需要严格匹配年龄的临床样本。