title: Metabolomics of neural progenitor cells: a novel approach to biomarker discovery.
abstract: Finding biomarkers of human neurological diseases is one of the most pressing goals of modern medicine. Most neurological disorders are recognized too late because of the lack of biomarkers that can identify early pathological processes in the living brain. Late diagnosis leads to late therapy and poor prognosis. Therefore, during the past decade, a major endeavor of clinical investigations in neurology has been the search for diagnostic and prognostic biomarkers of brain disease. Recently, a new field of metabolomics has emerged, aiming to investigate metabolites within the cell/tissue/ organism as possible biomarkers. Similarly to other "omics" fields, metabolomics offers substantial information about the status of the organism at a given time point. However, metabolomics also provides functional insight into the biochemical status of a tissue, which results from the environmental effects on its genome background. Recently, we have adopted metabolomics techniques to develop an approach that combines both in vitro analysis of cellular samples and in vivo analysis of the mammalian brain. Using proton magnetic resonance spectroscopy, we have discovered a metabolic biomarker of neural stem/progenitor cells (NPCs) that allows the analysis of these cells in the live human brain. We have developed signal-processing algorithms that can detect metabolites present at very low concentration in the live human brain and can indicate possible pathways impaired in specific diseases. Herein, we present our strategy for both cellular and systems metabolomics, based on an integrative processing of the spectroscopy data that uses analytical tools from both metabolomic and spectroscopy fields. As an example of biomarker discovery using our approach, we present new data and discuss our previous findings on the NPC biomarker. Our studies link systems and cellular neuroscience through the functions of specific metabolites. Therefore, they provide a functional insight into the brain, which might eventually lead to discoveries of clinically useful biomarkers of the disease.
authors.affiliation: Departments of Neurology and Electrical and Computer Engineering, Stony Brook University, Stony Brook, New York 11790, USA.
authors.forename: M
authors.initials: M
authors.lastname: Maletić-Savatić
authors.forename: L K
authors.initials: LK
authors.lastname: Vingara
authors.forename: L N
authors.initials: LN
authors.lastname: Manganas
authors.forename: Y
authors.initials: Y
authors.lastname: Li
authors.forename: S
authors.initials: S
authors.lastname: Zhang
authors.forename: A
authors.initials: A
authors.lastname: Sierra
authors.forename: R
authors.initials: R
authors.lastname: Hazel
authors.forename: D
authors.initials: D
authors.lastname: Smith
authors.forename: M E
authors.initials: ME
authors.lastname: Wagshul
authors.forename: F
authors.initials: F
authors.lastname: Henn
authors.forename: L
authors.initials: L
authors.lastname: Krupp
authors.forename: G
authors.initials: G
authors.lastname: Enikolopov
authors.forename: H
authors.initials: H
authors.lastname: Benveniste
authors.forename: P M
authors.initials: PM
authors.lastname: Djurić
authors.forename: I
authors.initials: I
authors.lastname: Pelczer
mesh_terms: D000818:Animals; D015415:Biomarkers / Q000378:metabolism*; D001927:Brain Diseases / Q000175:diagnosis / Q000378:metabolism; D006801:Humans; D009682:Magnetic Resonance Spectroscopy; D055432:Metabolomics / Q000379:methods* / Q000706:statistics & numerical data; D009474:Neurons / Q000378:metabolism*; D012815:Signal Processing, Computer-Assisted; D013234:Stem Cells / Q000378:metabolism*; D049490:Systems Biology
chemical_list: D015415:Biomarkers