title: Methods for the differential integrative omic analysis of plasma from a transgenic disease animal model.
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.
authors.affiliation: Beyond Genomics, Inc., Waltham, Massachusetts, USA.
authors.forename: Eugene
authors.initials: E
authors.lastname: Davidov
authors.forename: Clary B
authors.initials: CB
authors.lastname: Clish
authors.forename: Matej
authors.initials: M
authors.lastname: Oresic
authors.forename: Michael
authors.initials: M
authors.lastname: Meys
authors.forename: Wayne
authors.initials: W
authors.lastname: Stochaj
authors.forename: Philip
authors.initials: P
authors.lastname: Snell
authors.forename: Gary
authors.initials: G
authors.lastname: Lavine
authors.forename: Thomas R
authors.initials: TR
authors.lastname: Londo
authors.forename: Aram
authors.initials: A
authors.lastname: Adourian
authors.forename: Xiang
authors.initials: X
authors.lastname: Zhang
authors.forename: Mark
authors.initials: M
authors.lastname: Johnston
authors.forename: Nicole
authors.initials: N
authors.lastname: Morel
authors.forename: Edward W
authors.initials: EW
authors.lastname: Marple
authors.forename: Thomas N
authors.initials: TN
authors.lastname: Plasterer
authors.forename: Eric
authors.initials: E
authors.lastname: Neumann
authors.forename: Elwin
authors.initials: E
authors.lastname: Verheij
authors.forename: Jack T W E
authors.initials: JT
authors.lastname: Vogels
authors.forename: Louis M
authors.initials: LM
authors.lastname: Havekes
authors.forename: Jan
authors.initials: J
authors.lastname: van der Greef
authors.forename: Stephen
authors.initials: S
authors.lastname: Naylor
mesh_terms: D000818:Animals; D053318:Apolipoprotein E3; D001057:Apolipoproteins E / Q000097:blood* / Q000737:chemistry; D001161:Arteriosclerosis / Q000235:genetics*; D002853:Chromatography, Liquid; D003433:Crosses, Genetic; D005260:Female; D005799:Genes, Dominant; D005821:Genetic Techniques; D006801:Humans; D006951:Hyperlipoproteinemias / Q000235:genetics*; D050356:Lipid Metabolism; D008074:Lipoproteins / Q000737:chemistry; D009682:Magnetic Resonance Spectroscopy; D008297:Male; D013058:Mass Spectrometry; D051379:Mice; D008810:Mice, Inbred C57BL; D008822:Mice, Transgenic; D015999:Multivariate Analysis; D009154:Mutation; D010455:Peptides / Q000737:chemistry; D025341:Principal Component Analysis; D011506:Proteins / Q000737:chemistry; D012984:Software; D013997:Time Factors; D014357:Trypsin / Q000737:chemistry
chemical_list: D053318:Apolipoprotein E3; D001057:Apolipoproteins E; D008074:Lipoproteins; D010455:Peptides; D011506:Proteins; D014357:Trypsin