MRI predictors of cognitive change in a diverse and carefully characterized elderly population

Owen Carmichael, Dan Mungas, Laurel Beckett, Danielle Harvey, Sarah Tomaszewski Farias, Bruce Reed, John Olichney, Joshua Miller, Charles DeCarli

Research output: Contribution to journalArticlepeer-review

59 Scopus citations

Abstract

Background: Trajectories of cognitive decline among elderly individuals are heterogeneous, and markers that have high reliability for predicting cognitive trajectories across a broad spectrum of the elderly population have yet to be identified. Method: This study examined the utility of a variety of MRI-based brain measures, obtained at baseline, as predictors of subsequent declines in domain-specific measures of cognitive function in a cohort of 307 community-dwelling elderly individuals with varying degrees of cognitive impairment who were diverse across several relevant demographic variables and were evaluated yearly. Psychometrically matched measures of cognition were used to assess episodic memory, semantic memory, and executive function. Relationships between baseline MRI measures, including the volumes of the brain, hippocampus, and white matter hyperintensities (WMH), and cognitive trajectories were assessed in mixed effects regression models that modeled MRI effects on cognitive performance at baseline and rate of change as well as interindividual variability in cognitive baseline and rate of change. Results: Greater baseline brain volume predicted slower subsequent rate of decline in episodic memory and smaller WMH volume predicted slower subsequent rate of decline in executive function and semantic memory. Baseline hippocampal volume, while strongly related to baseline cognitive function, was not predictive of subsequent change in any of the cognitive domains. Conclusions: Baseline measures of brain structure and tissue pathology predicted rate of cognitive decline in a diverse and carefully characterized cohort, suggesting that they may provide summary measures of pre-existing neuropathological damage or the capacity of the brain to compensate for the impact of subsequent neuropathology on cognition. Conventional MRI measures may have use for predicting cognitive outcomes in highly heterogeneous elderly populations.

Original languageEnglish (US)
Pages (from-to)83-95.e2
JournalNeurobiology of Aging
Volume33
Issue number1
DOIs
StatePublished - Jan 2012
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Aging
  • Clinical Neurology
  • Developmental Biology
  • Geriatrics and Gerontology

Keywords

  • Brain
  • Cognitive decline
  • Item response theory
  • MRI
  • Mixed effects modeling

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