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Cited by 132Advanced Proteomics Techniques and ApplicationsAdvanced Biosensing Techniques and ApplicationsGenetics, Aging, and Longevity in Model Organisms

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Age-Related Differences in Plasma Proteins: How Plasma Proteins Change from Neonates to Adults

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Ignjatovic, Vera, Lai, Cera, Summerhayes, Robyn, Mathesius, Ulrike, Tawfilis, Sherif, Perugini, Matthew A., Monagle, Paul·2011·PLoS ONE
DOI 10.1371/journal.pone.0017213PMC PMC3041803
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Abstract

The incidence of major diseases such as cardiovascular disease, thrombosis and cancer increases with age and is the major cause of mortality world-wide, with neonates and children somehow protected from such diseases of ageing. We hypothesized that there are major developmental differences in plasma proteins and that these contribute to age-related changes in the incidence of major diseases. We evaluated the human plasma proteome in healthy neonates, children and adults using the 2D-DIGE approach. We demonstrate significant changes in number and abundance of up to 100 protein spots that have marked differences in during the transition of the plasma proteome from neonate and child through to adult. These proteins are known to be involved in numerous physiological processes such as iron transport and homeostasis, immune response, haemostasis and apoptosis, amongst others. Importantly, we determined that the proteins that are differentially expressed with age are not the same proteins that are differentially expressed with gender and that the degree of phosphorylation of plasma proteins also changes with age. Given the multi-functionality of these proteins in human physiology, understanding the differences in the plasma proteome in neonates and children compared to adults will make a major contribution to our understanding of developmental biology in humans.

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Figure 1 Comparison of the protein pattern from a representative 2D-DIGE gel of human plasma proteins. A: Cy3 stained Day 1 sample; B: Cy5 stained Adult sample; C: Image overlay (Cy3 - green, Cy5 - red, Identical areas – yellow). pH 3–11 left to right.
Figure 1 Comparison of the protein pattern from a representative 2D-DIGE gel of human plasma proteins. A: Cy3 stained Day 1 sample; B: Cy5 stained Adult sample; C: Image overlay (Cy3 - green, Cy5 - red, Identical areas – yellow). pH 3–11 left to right.CC BY · PubMed Central
Figure 2 Example of protein that changes with age. (A) Representative gel image showing locations of proteins that are differentially expressed across age, ≥1.5 change in abundance; p<0.05; (B) 3-D view example of a spot that is up-regulated with age (number 823); (C) expression pattern for spot 823 (Fibrinogen beta chain) across seven age-groups; y-axis represents log abundance.
Figure 2 Example of protein that changes with age. (A) Representative gel image showing locations of proteins that are differentially expressed across age, ≥1.5 change in abundance; p<0.05; (B) 3-D view example of a spot that is up-regulated with age (number 823); (C) expression pattern for spot 823 (Fibrinogen beta chain) across seven age-groups; y-axis represents log abundance.CC BY · PubMed Central
Figure 3 Validation of the age-specific variation in fibrinogen. (A) western blot image; (B) quantification (µg) of the western blot; (C) 2D-DIGE calculated relative log abundance.
Figure 3 Validation of the age-specific variation in fibrinogen. (A) western blot image; (B) quantification (µg) of the western blot; (C) 2D-DIGE calculated relative log abundance.CC BY · PubMed Central
Figure 4 Validation of the age-specific variation in alpha-2-macroglobulin. (A) western blot image; (B) semi-quantification of the western blot (densitometry units); (C) 2D-DIGE calculated relative log abundance.
Figure 4 Validation of the age-specific variation in alpha-2-macroglobulin. (A) western blot image; (B) semi-quantification of the western blot (densitometry units); (C) 2D-DIGE calculated relative log abundance.CC BY · PubMed Central
Figure 5 Hierarchical clustering of differentially abundant proteins across the age-groups. Relative expression patterns of each protein are expressed as a heat map ranging from −0.5 (green) to +0.5 (red), including proteins identified in Table 1 and Table 2.
Figure 5 Hierarchical clustering of differentially abundant proteins across the age-groups. Relative expression patterns of each protein are expressed as a heat map ranging from −0.5 (green) to +0.5 (red), including proteins identified in Table 1 and Table 2.CC BY · PubMed Central
Figure 6 Overlay of gel stained with Pro-Q Diamond Phosphoprotein Stain. Circled areas represent regions with differences in phosphorylation patterns between (A) Day 1 neonates and (B) adult samples. Red (Cy5) represents the total plasma proteome; Green (Cy3) represents the phosphoproteome.
Figure 6 Overlay of gel stained with Pro-Q Diamond Phosphoprotein Stain. Circled areas represent regions with differences in phosphorylation patterns between (A) Day 1 neonates and (B) adult samples. Red (Cy5) represents the total plasma proteome; Green (Cy3) represents the phosphoproteome.CC BY · PubMed Central

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Metadata

Authors
Ignjatovic, V., Lai, C., Summerhayes, R., Mathesius, U., Tawfilis, S., Perugini, M. A., & Monagle, P.
Affiliations
  • Royal Children's Hospital (AU)
  • Australian National University (AU)
  • The University of Melbourne (AU)
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2011-02-18
Volume
6
Issue
2
Pages
e17213
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0017213
PMC
PMC3041803
OpenAlex
W1971352522
Cited by
132
References
32
Citations by year
2026: 6 · 2025: 8 · 2024: 6 · 2023: 7 · 2022: 5 · 2021: 14 · 2020: 16 · 2019: 11 · 2018: 9 · 2017: 6 · 2016: 7 · 2015: 4 · 2014: 15 · 2013: 6 · 2012: 8
FWCI
4.65
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • ANU Open Research (Australian National University) (submittedVersion, cc-by)
Funders
University of Melbourne
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced Biosensing Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
Keywords
plasma proteome, age-related changes, neonates, children, developmental differences, protein phosphorylation, iron transport, hemostasis, immune response, apoptosis, sex differences, 2D-DIGE, human development
MeSH terms
Adolescent, Adult, Age Factors, Aging, Blood Proteins, Child, Child, Preschool, Female, Humans, Infant, Infant, Newborn, Male, Phosphoproteins, Electrophoresis, Gel, Two-Dimensional, Proteome, Validation Studies as Topic

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