Statistical analysis of variation in the human plasma proteome

Todd H. Corzett, Imola K. Fodor, Megan W. Choi, Vicki L. Walsworth, Ken W Turteltaub, Sandra L. McCutchen-Maloney, Brett A. Chromy

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability.Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where one human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate.Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.

Original languageEnglish (US)
Article number258494
JournalJournal of Biomedicine and Biotechnology
Volume2010
DOIs
StatePublished - 2010
Externally publishedYes

Fingerprint

Plasma (human)
Proteome
Statistical methods
Biomarkers
Proteins
Gels
Two-Dimensional Difference Gel Electrophoresis
Electrophoresis
Mass spectrometry
Coloring Agents
Proteomics
Cluster Analysis
Mass Spectrometry
Healthy Volunteers
Plasmas

ASJC Scopus subject areas

  • Biotechnology
  • Molecular Medicine
  • Genetics
  • Molecular Biology
  • Health, Toxicology and Mutagenesis
  • Medicine(all)

Cite this

Corzett, T. H., Fodor, I. K., Choi, M. W., Walsworth, V. L., Turteltaub, K. W., McCutchen-Maloney, S. L., & Chromy, B. A. (2010). Statistical analysis of variation in the human plasma proteome. Journal of Biomedicine and Biotechnology, 2010, [258494]. https://doi.org/10.1155/2010/258494

Statistical analysis of variation in the human plasma proteome. / Corzett, Todd H.; Fodor, Imola K.; Choi, Megan W.; Walsworth, Vicki L.; Turteltaub, Ken W; McCutchen-Maloney, Sandra L.; Chromy, Brett A.

In: Journal of Biomedicine and Biotechnology, Vol. 2010, 258494, 2010.

Research output: Contribution to journalArticle

Corzett, TH, Fodor, IK, Choi, MW, Walsworth, VL, Turteltaub, KW, McCutchen-Maloney, SL & Chromy, BA 2010, 'Statistical analysis of variation in the human plasma proteome', Journal of Biomedicine and Biotechnology, vol. 2010, 258494. https://doi.org/10.1155/2010/258494
Corzett, Todd H. ; Fodor, Imola K. ; Choi, Megan W. ; Walsworth, Vicki L. ; Turteltaub, Ken W ; McCutchen-Maloney, Sandra L. ; Chromy, Brett A. / Statistical analysis of variation in the human plasma proteome. In: Journal of Biomedicine and Biotechnology. 2010 ; Vol. 2010.
@article{b121d95d57304eeb9eb9e6f8bea0c9cb,
title = "Statistical analysis of variation in the human plasma proteome",
abstract = "Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability.Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where one human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate.Here, 21 protein spots had larger than 50{\%} CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.",
author = "Corzett, {Todd H.} and Fodor, {Imola K.} and Choi, {Megan W.} and Walsworth, {Vicki L.} and Turteltaub, {Ken W} and McCutchen-Maloney, {Sandra L.} and Chromy, {Brett A.}",
year = "2010",
doi = "10.1155/2010/258494",
language = "English (US)",
volume = "2010",
journal = "BioMed Research International",
issn = "2314-6133",
publisher = "Hindawi Publishing Corporation",

}

TY - JOUR

T1 - Statistical analysis of variation in the human plasma proteome

AU - Corzett, Todd H.

AU - Fodor, Imola K.

AU - Choi, Megan W.

AU - Walsworth, Vicki L.

AU - Turteltaub, Ken W

AU - McCutchen-Maloney, Sandra L.

AU - Chromy, Brett A.

PY - 2010

Y1 - 2010

N2 - Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability.Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where one human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate.Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.

AB - Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability.Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where one human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate.Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.

UR - http://www.scopus.com/inward/record.url?scp=77951237745&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77951237745&partnerID=8YFLogxK

U2 - 10.1155/2010/258494

DO - 10.1155/2010/258494

M3 - Article

VL - 2010

JO - BioMed Research International

JF - BioMed Research International

SN - 2314-6133

M1 - 258494

ER -