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A multinational study distinguishing Alzheimer's and healthy patients using cerebrospinal fluid tau/Aβ42 cutoff with concordance to amyloid positron emission tomography imaging

  • Yi Mo
  • , Julie Stromswold
  • , Kimberly Wilson
  • , Daniel Holder
  • , Cyrille Sur
  • , Omar Laterza
  • , Mary J. Savage
  • , Arie Struyk
  • , Philip Scheltens
  • , Charlotte E. Teunissen
  • , James Burke
  • , S. Lance Macaulay
  • , Geir Bråthen
  • , Sigrid Botne Sando
  • , Linda R. White
  • , Christy Weiss
  • , Arturo Cowes
  • , Michele M. Bush
  • , Ganga DeSilva
  • , David G. Darby
  • Stephanie R. Rainey-Smith, Jackie Surls, Eileen Sagini, Michael Tanen, Amy Altman, Johan Luthman, Michael F. Egan

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Introduction Changes in cerebrospinal fluid (CSF) tau and amyloid β (Aβ)42 accompany development of Alzheimer's brain pathology. Robust tau and Aβ42 immunoassays were developed to establish a tau/Aβ42 cutoff distinguishing mild-to-moderate Alzheimer's disease (AD) subjects from healthy elderly control (HC) subjects. Methods A CSF tau/Aβ42 cutoff criteria was chosen, which distinguished the groups and maximized concordance with amyloid PET. Performance was assessed using an independent validation cohort. Results A tau/Aβ42 = 0.215 cutoff provided 94.8% sensitivity and 77.7% specificity. Concordance with PET visual reads was estimated at 86.9% in a ∼50% PET positive population. In the validation cohort, the cutoff demonstrated 78.4% sensitivity and 84.9% specificity to distinguish the AD and HC populations. Discussion A tau/Aβ42 cutoff with acceptable sensitivity and specificity distinguished HC from mild-to-moderate AD subjects and maximized concordance to brain amyloidosis. The defined cutoff demonstrated that CSF analysis may be useful as a surrogate to imaging assessment of AD pathology.

Original languageEnglish
Pages (from-to)201-209
Number of pages9
JournalAlzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
Volume6
Issue number1
DOIs
Publication statusPublished - 2017
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Alzheimer's disease
  • Amyloid β42
  • Diagnostic test assessment
  • PET
  • Tau

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