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PMID: 20034503 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Brain substrates of learning and retention in mild cognitive impairment diagnosis and progression to Alzheimer's disease.

Neuropsychologia ·Vol. 48 ·No. 5 ·2010-04-00 ·Pages 1237-47

Chang YL, Bondi MW, Fennema-Notestine C, McEvoy LK, Hagler DJ, Jacobson MW, Dale AM, Alzheimer's Disease Neuroimaging Initiative

Abstract

Understanding the underlying qualitative features of memory deficits in mild cognitive impairment (MCI) can provide critical information for early detection of Alzheimer's disease (AD). This study sought to investigate the utility of both learning and retention measures in (a) the diagnosis of MCI, (b) predicting progression to AD, and (c) examining their underlying brain morphometric correlates. A total of 607 participants were assigned to three MCI groups (high learning-low retention; low learning-high retention; low learning-low retention) and one control group (high learning-high retention) based on scores above or below a 1.5 SD cutoff on learning and retention indices of the Rey Auditory Verbal Learning Test. Our results demonstrated that MCI individuals with predominantly a learning deficit showed a widespread pattern of gray matter loss at baseline, whereas individuals with a retention deficit showed more focal gray matter loss. Moreover, either learning or retention measures provided good predictive value for longitudinal clinical outcome over two years, although impaired learning had modestly better predictive power than impaired retention. As expected, impairments in both measures provided the best predictive power. Thus, the conventional practice of relying solely on the use of delayed recall or retention measures in studies of amnestic MCI misses an important subset of older adults at risk of developing AD. Overall, our results highlight the importance of including learning measures in addition to retention measures when making a diagnosis of MCI and for predicting clinical outcome.

Keywords
Amnestic MCI Early detection Episodic memory Longitudinal outcome MR morphometry
MeSH Terms
Aged Aged, 80 and over Alzheimer Disease/epidemiology,physiopathology Brain/anatomy & histology,physiopathology Cognition Disorders/diagnosis,epidemiology Disease Progression Female Humans Learning/physiology Magnetic Resonance Imaging Male Middle Aged Neuropsychological Tests Predictive Value of Tests Retention, Psychology Severity of Illness Index
Authors & Affiliations
8 authors, click to expand affiliations / ORCID
Chang Yu-Ling
Department of Psychiatry, University of California, San Diego, 8950 Villa La Jolla Drive Suite C101, La Jolla, CA 92037, USA. [email protected]
Bondi Mark W
Fennema-Notestine Christine
McEvoy Linda K
Hagler Donald J
Jacobson Mark W
Dale Anders M
Alzheimer's Disease Neuroimaging Initiative
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Article Info
Journal
Neuropsychologia
Abbr.
Neuropsychologia
ISSN
1873-3514
Published
2010-04-00
Epub
2009-00-23
Pages
1237-47
Language
English
Region
England
NLM ID
0020713
PMCID
PMC2851550
Subset
IM
Grants
NIA NIH HHS · R01 AG031224 · United States
NIA NIH HHS · K24 AG026431 · United States
NIA NIH HHS · K01AG029218 · United States
NIA NIH HHS · AG024904 · United States
NIA NIH HHS · U19 AG024904 · United States
NIA NIH HHS · R01 AG012674 · United States
NIA NIH HHS · R01 AG012674-12 · United States
NIA NIH HHS · K24 AG026431-03 · United States
NIMH NIH HHS · K01 MH079146 · United States
NIA NIH HHS · K01 AG029218 · United States
NIMH NIH HHS · K01 MH079146-02 · United States
NIA NIH HHS · R01 AG031224-02 · United States
NCRR NIH HHS · U24 RR021382 · United States
NIA NIH HHS · U01 AG024904 · United States
NIA NIH HHS · U19 AG010483 · United States
NIA NIH HHS · AG031224 · United States
NIA NIH HHS · K01 AG029218-03 · United States
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