title: Multiplexed immunoassay panel identifies novel CSF biomarkers for Alzheimer's disease diagnosis and prognosis.
abstract: BACKGROUND
  Clinicopathological studies suggest that Alzheimer's disease (AD) pathology begins ∼10-15 years before the resulting cognitive impairment draws medical attention. Biomarkers that can detect AD pathology in its early stages and predict dementia onset would, therefore, be invaluable for patient care and efficient clinical trial design. We utilized a targeted proteomics approach to discover novel cerebrospinal fluid (CSF) biomarkers that can augment the diagnostic and prognostic accuracy of current leading CSF biomarkers (Aβ42, tau, p-tau181).
  
  
  RESULTS
  Using a multiplexed Luminex platform, 190 analytes were measured in 333 CSF samples from cognitively normal (Clinical Dementia Rating [CDR] 0), very mildly demented (CDR 0.5), and mildly demented (CDR 1) individuals. Mean levels of 37 analytes (12 after Bonferroni correction) were found to differ between CDR 0 and CDR>0 groups. Receiver-operating characteristic curve analyses revealed that small combinations of a subset of these markers (cystatin C, VEGF, TRAIL-R3, PAI-1, PP, NT-proBNP, MMP-10, MIF, GRO-α, fibrinogen, FAS, eotaxin-3) enhanced the ability of the best-performing established CSF biomarker, the tau/Aβ42 ratio, to discriminate CDR>0 from CDR 0 individuals. Multiple machine learning algorithms likewise showed that the novel biomarker panels improved the diagnostic performance of the current leading biomarkers. Importantly, most of the markers that best discriminated CDR 0 from CDR>0 individuals in the more targeted ROC analyses were also identified as top predictors in the machine learning models, reconfirming their potential as biomarkers for early-stage AD. Cox proportional hazards models demonstrated that an optimal panel of markers for predicting risk of developing cognitive impairment (CDR 0 to CDR>0 conversion) consisted of calbindin, Aβ42, and age.
  
  
  CONCLUSIONS
  Using a targeted proteomic screen, we identified novel candidate biomarkers that complement the best current CSF biomarkers for distinguishing very mildly/mildly demented from cognitively normal individuals. Additionally, we identified a novel biomarker (calbindin) with significant prognostic potential.
authors.affiliation: Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, United States of America.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Craig-Schapiro
authors.forename: Max
authors.initials: M
authors.lastname: Kuhn
authors.forename: Chengjie
authors.initials: C
authors.lastname: Xiong
authors.forename: Eve H
authors.initials: EH
authors.lastname: Pickering
authors.forename: Jingxia
authors.initials: J
authors.lastname: Liu
authors.forename: Thomas P
authors.initials: TP
authors.lastname: Misko
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Perrin
authors.forename: Kelly R
authors.initials: KR
authors.lastname: Bales
authors.forename: Holly
authors.initials: H
authors.lastname: Soares
authors.forename: Anne M
authors.initials: AM
authors.lastname: Fagan
authors.forename: David M
authors.initials: DM
authors.lastname: Holtzman
mesh_terms: D000465:Algorithms; D000544:Alzheimer Disease / Q000134:cerebrospinal fluid* / Q000150:complications / Q000175:diagnosis* / Q000235:genetics; D001185:Artificial Intelligence; D015415:Biomarkers / Q000134:cerebrospinal fluid*; D003072:Cognition Disorders / Q000134:cerebrospinal fluid / Q000150:complications; D003710:Demography; D005260:Female; D005838:Genotype; D006801:Humans; D007118:Immunoassay / Q000379:methods*; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D016016:Proportional Hazards Models; D012372:ROC Curve
chemical_list: D015415:Biomarkers