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PMID: 21526197 Published · epublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Multiplexed immunoassay panel identifies novel CSF biomarkers for Alzheimer's disease diagnosis and prognosis.

PloS one ·Vol. 6 ·No. 4 ·2011-04-19 ·Pages e18850

Craig-Schapiro R, Kuhn M, Xiong C, Pickering EH, Liu J, Misko TP, Perrin RJ, Bales KR, Soares H, Fagan AM, Holtzman DM

Abstract

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). 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. 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.

MeSH Terms
Algorithms Alzheimer Disease/cerebrospinal fluid,complications,diagnosis,genetics Artificial Intelligence Biomarkers/cerebrospinal fluid Cognition Disorders/cerebrospinal fluid,complications Demography Female Genotype Humans Immunoassay/methods Male Middle Aged Prognosis Proportional Hazards Models ROC Curve
Chemicals
Biomarkers
Authors & Affiliations
11 authors, click to expand affiliations / ORCID
Craig-Schapiro Rebecca
Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, United States of America.
Kuhn Max
Xiong Chengjie
Pickering Eve H
Liu Jingxia
Misko Thomas P
Perrin Richard J
Bales Kelly R
Soares Holly
Fagan Anne M
Holtzman David M
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Article Info
Journal
PloS one
Abbr.
PLoS One
ISSN
1932-6203
Published
2011-04-19
Epub
2011-00-19
Pages
e18850
Language
English
Region
United States
NLM ID
101285081
PMCID
PMC3079734
Subset
IM
Grants
NIA NIH HHS · P01 AG026276 · United States
NCATS NIH HHS · UL1 TR000448 · United States
NINDS NIH HHS · P30 NS057105 · United States
NIA NIH HHS · P50 AG05681 · United States
NIA NIH HHS · P01 AG003991 · United States
NIA NIH HHS · P50 AG005681 · United States
NIA NIH HHS · P01 AG03991 · United States
NCRR NIH HHS · UL1 RR024992 · United States
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