Quantitative structural MRI and CSF biomarkers in early diagnosis of Alzheimer's disease Academic Article uri icon

Overview

MeSH Major

  • Adenocarcinoma
  • Antineoplastic Agents
  • Drug Resistance, Neoplasm
  • Esophageal Neoplasms
  • Esophagogastric Junction
  • Niacinamide
  • Phenylurea Compounds
  • Stomach Neoplasms

abstract

  • Combined utility of biomarkers in prediction of neurodegenerative diseases gains popularity, and is expected to become a future standard for early diagnosis, screening and monitoring of disease progression. This study investigated combined use of MRI and CSF biomarkers for prediction of pre-clinical Alzheimer's disease (AD). Forty-five subjects (21 controls (NL-NL), 16 stable mild cognitive impairment patients (MCI-MCI) and 8 MCI patients who declined to AD (MCI-AD)) received MRI and lumbar puncture at baseline and again after 2-years. CSF biomarkers included total and phosphorylated tau (T-tau, P-tau231), amyloid beta Aβ42/Aβ40and isoprostane (IP). Structural MRI images were used to identify brain regions with differences of gray matter concentration (GMC) best distinguishing study groups and to calculate individual GMC values. Additionally, rate of medial temporal lobe (MTL) atrophy was examined using regional boundary shift (rBS) method. At baseline, for MRI, MCI-AD showed reduced GMC in MTL, and for CSF higher CSF T-tau, P-tau231, IP and lower Aβ42/ Aβ40as compared with MCI-MCI or NL-NL. Longitudinally, rBS-MTL atrophy was higher in MCI-AD than in either MCI-MCI or NL-NL, particularly in the left hemisphere. CSF data showed longitudinally greater increases of CSF IP in MCI-AD as compared with healthy controls. Combining baseline CSF-P-tau231and GMC-MTL significantly increased overall prediction accuracy of preclinical AD from 74 to 84% (pstep< 0.05). These results justify use of multiple modalities of biomarkers in the identification of memory clinic patients at increased risk for dementia. © 2011 The authors and IOS Press. All rights reserved.

publication date

  • December 2011

Research

keywords

  • Academic Article

Identity

Digital Object Identifier (DOI)

  • 10.3233/978-1-60750-793-2-141

Additional Document Info

start page

  • 141

end page

  • 152

volume

  • 2