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Title: Statistical Analysis of Variation in the Human Plasma Proteome

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.
Authors:
 [1] ;  [2] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1]
  1. Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550, USA
  2. Department of Biostatistics, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
Publication Date:
OSTI Identifier:
1198317
Grant/Contract Number:
AC52-07NA27344
Type:
Published Article
Journal Name:
Journal of Biomedicine and Biotechnology
Additional Journal Information:
Journal Volume: 2010; Related Information: CHORUS Timestamp: 2016-08-11 08:49:12; Journal ID: ISSN 1110-7243
Publisher:
Hindawi Publishing Corporation
Sponsoring Org:
USDOE
Country of Publication:
Country unknown/Code not available
Language:
English