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Methods for the differential integrative omic analysis of plasma from a transgenic disease animal model
Authors:Davidov Eugene  Clish Clary B  Oresic Matej  Meys Michael  Stochaj Wayne  Snell Philip  Lavine Gary  Londo Thomas R  Adourian Aram  Zhang Xiang  Johnston Mark  Morel Nicole  Marple Edward W  Plasterer Thomas N  Neumann Eric  Verheij Elwin  Vogels Jack T W E  Havekes Louis M  van der Greef Jan  Naylor Stephen
Affiliation:Beyond Genomics, Inc., Waltham, Massachusetts, USA.
Abstract:Multitiered quantitative analysis of biological systems is rapidly becoming the desired approach to study hierarchical functional interactions between proteins and metabolites. We describe here a novel systematic approach to analyze organisms with complex metabolic regulatory networks. By using precise analytical methods to measure biochemical constituents and their relative abundance in whole plasma of transgenic ApoE*3-Leiden mice and an isogenic wild-type control group, simultaneous snapshots of metabolic and protein states were obtained. Novel data processing and multivariate analysis tools such as Impurity Resolution Software (IMPRESS) and Windows-based linear fit program (WINLIN) were used to compare protein and metabolic profiles in parallel. Canonical correlations of the resulting data show quantitative relationships between heterogeneous components in the TG animals. These results, obtained solely from whole plasma analysis allowed us, in a rapid manner, to corroborate previous findings as well as find new events pertaining to dominant and peripheral events in lipoprotein metabolism of a genetically modified mammalian organism in relation to ApoE3, a key mediator of lipoprotein metabolism.
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