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 language | English (US) |
|---|---|
| Article number | 258494 |
| Journal | Journal of Biomedicine and Biotechnology |
| Volume | 2010 |
| DOIs | |
| State | Published - 2010 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Biotechnology
- Molecular Medicine
- Genetics
- Molecular Biology
- Health, Toxicology and Mutagenesis
- Medicine(all)
Cite this
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 journal › Article
}
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.
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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 -