title: Interpreting metabolomic profiles using unbiased pathway models.
abstract: Human disease is heterogeneous, with similar disease phenotypes resulting from distinct combinations of genetic and environmental factors. Small-molecule profiling can address disease heterogeneity by evaluating the underlying biologic state of individuals through non-invasive interrogation of plasma metabolite levels. We analyzed metabolite profiles from an oral glucose tolerance test (OGTT) in 50 individuals, 25 with normal (NGT) and 25 with impaired glucose tolerance (IGT). Our focus was to elucidate underlying biologic processes. Although we initially found little overlap between changed metabolites and preconceived definitions of metabolic pathways, the use of unbiased network approaches identified significant concerted changes. Specifically, we derived a metabolic network with edges drawn between reactant and product nodes in individual reactions and between all substrates of individual enzymes and transporters. We searched for "active modules"--regions of the metabolic network enriched for changes in metabolite levels. Active modules identified relationships among changed metabolites and highlighted the importance of specific solute carriers in metabolite profiles. Furthermore, hierarchical clustering and principal component analysis demonstrated that changed metabolites in OGTT naturally grouped according to the activities of the System A and L amino acid transporters, the osmolyte carrier SLC6A12, and the mitochondrial aspartate-glutamate transporter SLC25A13. Comparison between NGT and IGT groups supported blunted glucose- and/or insulin-stimulated activities in the IGT group. Using unbiased pathway models, we offer evidence supporting the important role of solute carriers in the physiologic response to glucose challenge and conclude that carrier activities are reflected in individual metabolite profiles of perturbation experiments. Given the involvement of transporters in human disease, metabolite profiling may contribute to improved disease classification via the interrogation of specific transporter activities.
authors.affiliation: Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: Rahul C
authors.initials: RC
authors.lastname: Deo
authors.forename: Luke
authors.initials: L
authors.lastname: Hunter
authors.forename: Gregory D
authors.initials: GD
authors.lastname: Lewis
authors.forename: Guillaume
authors.initials: G
authors.lastname: Pare
authors.forename: Ramachandran S
authors.initials: RS
authors.lastname: Vasan
authors.forename: Daniel
authors.initials: D
authors.lastname: Chasman
authors.forename: Thomas J
authors.initials: TJ
authors.lastname: Wang
authors.forename: Robert E
authors.initials: RE
authors.lastname: Gerszten
authors.forename: Frederick P
authors.initials: FP
authors.lastname: Roth
mesh_terms: D026905:Amino Acid Transport Systems / Q000378:metabolism; D002352:Carrier Proteins / Q000378:metabolism; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D005110:Extracellular Space / Q000378:metabolism; D050485:GABA Plasma Membrane Transport Proteins; D005947:Glucose / Q000378:metabolism*; D044882:Glucose Metabolism Disorders / Q000378:metabolism; D005951:Glucose Tolerance Test; D006801:Humans; D042541:Intracellular Space / Q000378:metabolism; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D055442:Metabolome; D008954:Models, Biological; D025341:Principal Component Analysis
chemical_list: D026905:Amino Acid Transport Systems; D002352:Carrier Proteins; D050485:GABA Plasma Membrane Transport Proteins; C072207:betaine plasma membrane transport proteins; D005947:Glucose