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      Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for Alzheimer's Disease Diagnosis and Prognosis

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          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).

          Methods and Findings

          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/Significance

          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.

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          Most cited references72

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          R: A Language and environmental for statistical computing

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            Cerebrospinal fluid beta-amyloid(1-42) in Alzheimer disease: differences between early- and late-onset Alzheimer disease and stability during the course of disease.

            To study the diagnostic potential of the 42 amino acid form of beta-amyloid (beta-amyloid(1-42)) in cerebrospinal fluid (CSF) as a biochemical marker for Alzheimer disease (AD), the intra-individual biological variation of CSF-beta-amyloid(1-42) level in patients with AD, and the possible effects of differential binding between beta-amyloid and apolipoprotein E isoforms on CSF-beta-amyloid(1-42) levels. A 20-month prospective follow-up study. Community population-based sample of consecutive patients with AD referred to the Piteå River Valley Hospital, Piteå, Sweden. Fifty-three patients with AD (mean +/- SD age, 71.4 +/- 7.4 years) diagnosed according to the National Institute of Neurological and Communicative Disorders and Stroke and Alzheimer's Disease and Related Disorders Association criteria and 21 healthy, age-matched (mean +/- SD age, 68.8 +/- 8.0 years) control subjects. Cerebrospinal fluid beta-amyloid(1-42) level--analyzed using enzyme-linked immunosorbent assay--and severity of dementia--analyzed using the Mini-Mental State Examination. Mean +/- SD levels of CSF-beta-amyloid(1-42) were decreased (P 25). The sensitivity of CSF-beta-amyloid(1-42) level as a diagnostic marker for AD is high. The intra-individual biological variation in CSF-beta-amyloid(1-42) level is low. Low CSF-beta-amyloid(1-42) levels are also found in the earlier stages of dementia in patients with AD. These findings suggest that CSF-beta-amyloid(1-42) analyses may be of value in the clinical diagnosis of AD, especially in the early course of the disease, when drug therapy may have the greatest potential of being effective but clinical diagnosis is particularly difficult.
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              Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                19 April 2011
                : 6
                : 4
                : e18850
                Affiliations
                [1 ]Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [2 ]The Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [3 ]Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [4 ]Division of Neuropathology, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [5 ]Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [6 ]Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [7 ]Neuroscience Research Unit, Pfizer Global Research and Development, Groton, Connecticut, United States of America
                [8 ]Neuroscience Research Unit, Pfizer Global Research and Development, St. Louis, Missouri, United States of America
                Mental Health Research Institute of Victoria, Australia
                Author notes

                Conceived and designed the experiments: RC-S MK CX EHP TPM RJP KRB HS AMF DMH. Performed the experiments: RC-S MK CX TPM. Analyzed the data: RC-S MK CX EHP JL KRB HS DMH. Contributed reagents/materials/analysis tools: RC-S MK CX EHP TPM AMF DMH. Wrote the paper: RC-S MK TPM RJP HS DMH.

                Article
                PONE-D-10-05833
                10.1371/journal.pone.0018850
                3079734
                21526197
                41de5a7d-5d23-4a0a-9fb7-4d6f7a6a2bc0
                Craig-Schapiro et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 28 November 2010
                : 21 March 2011
                Page count
                Pages: 15
                Categories
                Research Article
                Biology
                Biochemistry
                Proteins
                Proteome
                Proteomics
                Mathematics
                Statistics
                Biostatistics
                Medicine
                Diagnostic Medicine
                Pathology
                General Pathology
                Biomarkers
                Mental Health
                Psychiatry
                Dementia
                Neurology
                Dementia
                Alzheimer Disease
                Neurodegenerative Diseases
                Non-Clinical Medicine
                Health Care Policy
                Health Risk Analysis

                Uncategorized
                Uncategorized

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