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Investigating diversity in human plasma proteins
Author(s) -
Dobrin Nedelkov,
Urban A. Kiernan,
Eric E. Niederkofler,
Kemmons A. Tubbs,
Randall W. Nelson
Publication year - 2005
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.0500426102
Subject(s) - proteomics , proteome , population , biomarker , biology , human proteome project , computational biology , blood proteins , cohort , human plasma , bioinformatics , genetics , medicine , gene , biochemistry , chemistry , pathology , chromatography , environmental health
Plasma proteins represent an important part of the human proteome. Although recent proteomics research efforts focus largely on determining the overall number of proteins circulating in plasma, it is equally important to delineate protein variations among individuals, because they can signal the onset of diseases and be used as biological markers in diagnostics. To date, there has been no systematic proteomics effort to characterize the breadth of structural modifications in individual proteins in the general population. In this work, we have undertaken a population proteomics study to define gene- and protein-level diversity that is encountered in the general population. Twenty-five plasma proteins from a cohort of 96 healthy individuals were investigated through affinity-based mass spectrometric assays. A total of 76 structural forms/variants were observed for the 25 proteins within the samples cohort. Posttranslational modifications were detected in 18 proteins, and point mutations were observed in 4 proteins. The frequency of occurrence of these variations was wide-ranged, with some modifications being observed in only one sample, and others detected in all 96 samples. Even though a relatively small cohort of individuals was investigated, the results from this study illustrate the extent of protein diversity in the human population and can be of immediate aid in clinical proteomics/biomarker studies by laying a basal-level statistical foundation from which protein diversity relating to disease can be evaluated.

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