Nonlinear time course of brain volume loss in cognitively normal and impaired elders

Norbert Schuff, Duygu Tosun, Philip S. Insel, Gloria C. Chiang, Diana Truran, Paul S. Aisen, Clifford R. Jack, Michael W. Weiner

Research output: Contribution to journalArticle

49 Scopus citations

Abstract

The goal was to elucidate the time course of regional brain atrophy rates relative to age in cognitively normal (CN) aging, mild cognitively impairment (MCI), and Alzheimer's disease (AD), without a priori models for atrophy progression. Regional brain volumes from 147 cognitively normal subjects, 164 stable MCI, 93 MCI-to-AD converters and 111 ad patients, between 51 and 91 years old and who had repeated 1.5 T magnetic resonance imaging (MRI) scans over 30 months, were analyzed. Relations between regional brain volume change and age were determined using generalized additive models, an established nonparametric concept for approximating nonlinear relations. Brain atrophy rates varied nonlinearly with age, predominantly in regions of the temporal lobe. Moreover, the atrophy rates of some regions leveled off with increasing age in control and stable MCI subjects whereas those rates progressed further in MCI-to-AD converters and AD patients. The approach has potential uses for early detection of AD and differentiation between stable and progressing MCI.

Original languageEnglish (US)
Pages (from-to)845-855
Number of pages11
JournalNeurobiology of aging
Volume33
Issue number5
DOIs
StatePublished - May 1 2012

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Keywords

  • Aging
  • Alzheimer's disease
  • Brain atrophy
  • Generalized additive models
  • Hippocampus
  • Magnetic resonance imaging
  • Mild cognitive impairment

ASJC Scopus subject areas

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

Cite this

Schuff, N., Tosun, D., Insel, P. S., Chiang, G. C., Truran, D., Aisen, P. S., Jack, C. R., & Weiner, M. W. (2012). Nonlinear time course of brain volume loss in cognitively normal and impaired elders. Neurobiology of aging, 33(5), 845-855. https://doi.org/10.1016/j.neurobiolaging.2010.07.012