title: Alterations in metabolic pathways and networks in Alzheimer's disease.
abstract: The pathogenic mechanisms of Alzheimer's disease (AD) remain largely unknown and clinical trials have not demonstrated significant benefit. Biochemical characterization of AD and its prodromal phase may provide new diagnostic and therapeutic insights. We used targeted metabolomics platform to profile cerebrospinal fluid (CSF) from AD (n=40), mild cognitive impairment (MCI, n=36) and control (n=38) subjects; univariate and multivariate analyses to define between-group differences; and partial least square-discriminant analysis models to classify diagnostic groups using CSF metabolomic profiles. A partial correlation network was built to link metabolic markers, protein markers and disease severity. AD subjects had elevated methionine (MET), 5-hydroxyindoleacetic acid (5-HIAA), vanillylmandelic acid, xanthosine and glutathione versus controls. MCI subjects had elevated 5-HIAA, MET, hypoxanthine and other metabolites versus controls. Metabolite ratios revealed changes within tryptophan, MET and purine pathways. Initial pathway analyses identified steps in several pathways that appear altered in AD and MCI. A partial correlation network showed total tau most directly related to norepinephrine and purine pathways; amyloid-β (Ab42) was related directly to an unidentified metabolite and indirectly to 5-HIAA and MET. These findings indicate that MCI and AD are associated with an overlapping pattern of perturbations in tryptophan, tyrosine, MET and purine pathways, and suggest that profound biochemical alterations are linked to abnormal Ab42 and tau metabolism. Metabolomics provides powerful tools to map interlinked biochemical pathway perturbations and study AD as a disease of network failure.
authors.affiliation: Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA. rima.kaddurahdaouk@duke.edu
authors.forename: R
authors.initials: R
authors.lastname: Kaddurah-Daouk
authors.forename: H
authors.initials: H
authors.lastname: Zhu
authors.forename: S
authors.initials: S
authors.lastname: Sharma
authors.forename: M
authors.initials: M
authors.lastname: Bogdanov
authors.forename: S G
authors.initials: SG
authors.lastname: Rozen
authors.forename: W
authors.initials: W
authors.lastname: Matson
authors.forename: N O
authors.initials: NO
authors.lastname: Oki
authors.forename: A A
authors.initials: AA
authors.lastname: Motsinger-Reif
authors.forename: E
authors.initials: E
authors.lastname: Churchill
authors.forename: Z
authors.initials: Z
authors.lastname: Lei
authors.forename: D
authors.initials: D
authors.lastname: Appleby
authors.forename: M A
authors.initials: MA
authors.lastname: Kling
authors.forename: J Q
authors.initials: JQ
authors.lastname: Trojanowski
authors.forename: P M
authors.initials: PM
authors.lastname: Doraiswamy
authors.forename: S E
authors.initials: SE
authors.lastname: Arnold
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000134:cerebrospinal fluid / Q000378:metabolism*; D015415:Biomarkers / Q000134:cerebrospinal fluid; D016022:Case-Control Studies; D002853:Chromatography, Liquid; D060825:Cognitive Dysfunction / Q000134:cerebrospinal fluid / Q000378:metabolism; D005260:Female; D006801:Humans; D008297:Male; D053858:Metabolic Networks and Pathways; D055432:Metabolomics; D008875:Middle Aged; D009483:Neuropsychological Tests; D011446:Prospective Studies
chemical_list: D015415:Biomarkers