Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline

J. Nettiksimmons, D. Harvey, J. Brewer, O. Carmichael, C. DeCarli, C. R. Jack, R. Petersen, L. M. Shaw, J. Q. Trojanowski, M. W. Weiner, L. Beckett

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

Cerebrospinal fluid (CSF) and structural magnetic resonance imaging (MRI) show patterns of change in Alzheimer's disease (AD) that precede dementia. The Alzheimer's Disease Neuroimaging Initiative (ADNI) studied normal controls (NC), subjects with mild cognitive impairment (MCI), and subjects with AD to identify patterns of biomarkers to aid in early diagnosis and effective treatment of AD. Two hundred twenty-two NC underwent baseline MRI and clinical examination at baseline and at least one follow-up. One hundred twelve also provided CSF at baseline. Unsupervised clustering based on initial CSF and MRI measures was used to identify clusters of participants with similar profiles. Repeated measures regression modeling assessed the relationship of individual measures, and of cluster membership, to cognitive change over 3 years. Most individuals showed little cognitive change. Individual biomarkers had limited predictive value for cognitive decline, but membership in the cluster with the most extreme profile was associated with more rapid decline in ADAS-cog. Subtypes among NC based on multiple biomarkers may represent the earliest stages of subclinical cognitive decline and AD.

Original languageEnglish (US)
Pages (from-to)1419-1428
Number of pages10
JournalNeurobiology of aging
Volume31
Issue number8
DOIs
StatePublished - Aug 2010

Keywords

  • Alzheimer's disease
  • Amyloid beta-protein
  • Cerebrospinal fluid
  • Clustering
  • Cognition
  • Dementia
  • Early diagnosis
  • Hippocampal volume
  • Normal controls
  • Structural magnetic resonance imaging
  • Tau protein

ASJC Scopus subject areas

  • General Neuroscience
  • Aging
  • Clinical Neurology
  • Developmental Biology
  • Geriatrics and Gerontology

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