Methods for the differential integrative Omic analysis of plasma from a transgenic disease animal model

Eugene Davidov, Clary B. Clish, Matej Orešič, Michael Meys, Wayne Stochaj, Philip Snell, Gary Lavine, Thomas R. Londo, Aram Adourian, Xian Zhang, Mark Johnston, Nicole Morel, Edward W. Marple, Thomas N. Plasterer, Eric Neumann, Elwin Verheij, Jack T.W.E. Vogels, Louis M. Havekes, Jan Van Der Greef, Stephen Naylor

Research output: Contribution to journalArticleScientificpeer-review

36 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)267-288
JournalOMICS: A Journal of Integrative Biology
Issue number4
Publication statusPublished - 2004
MoE publication typeA1 Journal article-refereed


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