title: Comparing metabolomic and pathologic biomarkers alone and in combination for discriminating Alzheimer's disease from normal cognitive aging.
abstract: BACKGROUND
  A critical and as-yet unmet need in Alzheimer disease (AD) research is the development of novel markers that can identify individuals at risk for cognitive decline due to AD. This would aid intervention trials designed to slow the progression of AD by increasing diagnostic certainty, and provide new pathophysiologic clues and potential drug targets.
  
  
  RESULTS
  We used two metabolomics platforms (gas chromatography-time of flight mass spectrometry [GC-TOF] and liquid chromatography LC-ECA array [LC-ECA]) to measure a number of metabolites in cerebrospinal fluid (CSF) from patients with AD dementia and from cognitively normal controls. We used stepwise logistic regression models with cross-validation to assess the ability of metabolite markers to discriminate between clinically diagnosed AD participants and cognitively normal controls and we compared these data with traditional CSF Luminex immunoassay amyloid-β and tau biomarkers. Aβ and tau biomarkers had high accuracy to discriminate cases and controls (testing area under the curve: 0.92). The accuracy of GC-TOF metabolites and LC-ECA metabolites by themselves to discriminate clinical AD participants from controls was high (testing area under the curve: 0.70 and 0.96, respectively).
  
  
  CONCLUSIONS
  Our study identified several CSF small-molecule metabolites that discriminated especially well between clinically diagnosed AD and control groups. They appear to be suitable for further confirmatory and validation studies, and show the potential to provide predictive performance for AD.
authors.affiliation: Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA. kaddu001@mc.duke.edu.
authors.forename: Alison A
authors.initials: AA
authors.lastname: Motsinger-Reif
authors.forename: Hongjie
authors.initials: H
authors.lastname: Zhu
authors.forename: Mitchel A
authors.initials: MA
authors.lastname: Kling
authors.forename: Wayne
authors.initials: W
authors.lastname: Matson
authors.forename: Swati
authors.initials: S
authors.lastname: Sharma
authors.forename: Oliver
authors.initials: O
authors.lastname: Fiehn
authors.forename: David M
authors.initials: DM
authors.lastname: Reif
authors.forename: Dina H
authors.initials: DH
authors.lastname: Appleby
authors.forename: P Murali
authors.initials: PM
authors.lastname: Doraiswamy
authors.forename: John Q
authors.initials: JQ
authors.lastname: Trojanowski
authors.forename: Rima
authors.initials: R
authors.lastname: Kaddurah-Daouk
authors.forename: Steven E
authors.initials: SE
authors.lastname: Arnold
mesh_terms: D000368:Aged; D000375:Aging / Q000134:cerebrospinal fluid* / Q000187:drug effects / Q000473:pathology; D000544:Alzheimer Disease / Q000134:cerebrospinal fluid* / Q000175:diagnosis* / Q000188:drug therapy / Q000473:pathology; D016229:Amyloid beta-Peptides / Q000134:cerebrospinal fluid; D019540:Area Under Curve; D015415:Biomarkers / Q000134:cerebrospinal fluid; D002853:Chromatography, Liquid; D003071:Cognition; D003937:Diagnosis, Differential; D005260:Female; D008401:Gas Chromatography-Mass Spectrometry; D006801:Humans; D016015:Logistic Models; D008297:Male; D055432:Metabolomics / Q000379:methods; D009483:Neuropsychological Tests; D016875:tau Proteins / Q000134:cerebrospinal fluid
chemical_list: D016229:Amyloid beta-Peptides; D015415:Biomarkers; C054369:MAPT protein, human; D016875:tau Proteins