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The association of Aβ amyloid and composite cognitive measures in healthy older adults and MCI

Published online by Cambridge University Press:  18 July 2013

Karra D. Harrington ,
Yen Ying Lim ,
Kathryn A. Ellis ,
Carly Copolov ,
David Darby ,
Michael Weinborn ,
David Ames ,
Ralph N. Martins ,
Greg Savage  and
Cassandra Szoeke
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Karra D. Harrington*
Affiliation:
Mental Health Research Institute, The University of Melbourne, Parkville, Victoria, Australia School of Psychology, RMIT University, Bundoora, Victoria, Australia
Yen Ying Lim
Affiliation:
Mental Health Research Institute, The University of Melbourne, Parkville, Victoria, Australia Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia
Kathryn A. Ellis
Affiliation:
Mental Health Research Institute, The University of Melbourne, Parkville, Victoria, Australia Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia Academic Unit for Psychiatry of Old Age, Department of Psychiatry, St George's Hospital, The University of Melbourne, Kew, Victoria, Australia
Carly Copolov
Affiliation:
Mental Health Research Institute, The University of Melbourne, Parkville, Victoria, Australia
David Darby
Affiliation:
Mental Health Research Institute, The University of Melbourne, Parkville, Victoria, Australia
Michael Weinborn
Affiliation:
School of Psychology, University of Western Australia, Perth, Western Australia, Australia
David Ames
Affiliation:
Academic Unit for Psychiatry of Old Age, Department of Psychiatry, St George's Hospital, The University of Melbourne, Kew, Victoria, Australia National Ageing Research Institute, Parkville, Victoria, Australia
Ralph N. Martins
Affiliation:
Centre of Excellence for Alzheimer's Disease Research and Care, School of Exercise, Biomedical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia
Greg Savage
Affiliation:
Department of Psychology and ARC Centre of Excellence in Cognition and Its Disorders, Macquarie University, Sydney, New South Wales, Australia
Cassandra Szoeke
Affiliation:
Mental Health Research Institute, The University of Melbourne, Parkville, Victoria, Australia National Ageing Research Institute, Parkville, Victoria, Australia
Christopher Rowe
Affiliation:
Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, Victoria, Australia Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, Victoria, Australia
Victor L. Villemagne
Affiliation:
Mental Health Research Institute, The University of Melbourne, Parkville, Victoria, Australia Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, Victoria, Australia Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, Victoria, Australia
Colin L. Masters
Affiliation:
Mental Health Research Institute, The University of Melbourne, Parkville, Victoria, Australia
Paul Maruff
Affiliation:
Mental Health Research Institute, The University of Melbourne, Parkville, Victoria, Australia CogState Ltd., Melbourne, Victoria, Australia
*
Correspondence should be addressed to: Karra Danyelle Harrington, Mental Health Research Institute, The University of Melbourne, 155 Oak St, Parkville, Victoria 3052, Australia. Phone: +61-3-9389-2932; Fax: +61-3-9388-1698. Email: [email protected].
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Abstract

Background:

To date evidence of the relationship between cognition and Aβ amyloid during the early stages of Alzheimer's Disease (AD) has been inconsistent. This study aimed to describe the nature and magnitude of the relationship between Aβ amyloid and cognitive performance of individuals without dementia.

Methods:

Composite cognitive measures were developed from the Australian Imaging Biomarkers and Lifestyle study neuropsychological test battery using data from 768 healthy older adults and 133 adults with mild cognitive impairment (MCI). A subgroup of this sample (174 healthy, 53 MCI) underwent neuroimaging for Aβ amyloid.

Results:

Within the MCI group individuals with high Aβ amyloid showed selective impairment for memory compared with those with low Aβ amyloid; however, this difference was not evident in the healthy group.

Conclusions:

The current findings provide further evidence of the relationship between Aβ amyloid and cognition, with memory impairment being the primary symptom of the underlying disease during the prodromal phases of AD.

Keywords

Alzheimer’s diseasemild cognitive impairmentneuroimagingneuropsychology
Type
Research Article
Information
International Psychogeriatrics , Volume 25 , Issue 10 , October 2013 , pp. 1667 - 1677
Copyright
Copyright © International Psychogeriatric Association 2013 

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References

Aizenstein, H.et al. (2008). Frequent amyloid deposition without significant cognitive impairment among the elderly. Archives of Neurology, 65, 1509–1517.CrossRefGoogle ScholarPubMed
Albert, M. S.et al. (2011). The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging and Alzheimer's Association workgroup. Alzheimer's and Dementia, 7, 270–279. doi:10.1016/j.jalz.2011.03.008.CrossRefGoogle Scholar
Amariglio, R. E.et al. (2012). Subjective cognitive complaints and amyloid burden in cognitively normal older individuals. Neuropsychologia, 50, 2880–2886.CrossRefGoogle ScholarPubMed
Crane, P.et al. (2012). Development and assessment of a composite score for memory in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Brain Imaging and Behavior, 6, 502–516. doi:10.1007/s11682-012-9186-z.CrossRefGoogle Scholar
Delis, D. C., Kaplan, E. and Kramer, J. H. (2001). The Delis-Kaplan Executive Function System (D-KEFS). San Antonio, TX: Psychological Corporation.Google Scholar
Delis, D., Kramer, J., Kaplan, E. and Ober, B. (2000). California Verbal Learning Test, 2nd Edn.San Antonio, TX: Psychological Corporation.Google Scholar
Dickerson, B. C. and Sperling, R. A. (2008). Functional abnormalities of the medial temporal lobe memory system in mild cognitive impairment and Alzheimer's disease: insights from functional MRI studies. Neuropsychologia, 46, 1624–1635. doi:10.1016/j.neuropsychologia.2007.11.030.CrossRefGoogle ScholarPubMed
Doraiswamy, P. M.et al. (2012). Amyloid-β assessed by florbetapir F 18 PET and 18-month cognitive decline: a multicenter study. Neurology, October 16, 1636–1644.CrossRefGoogle Scholar
Dubois, B.et al. (2010). Revising the definition of Alzheimer's disease: a new lexicon. Lancet Neurology, 9, 1118–1127.CrossRefGoogle ScholarPubMed
Dubois, B. and Albert, M. L. (2004). Amnestic MCI or prodromal Alzheimer's disease? Lancet Neurology, 3, 246–248. doi:10.1016/s1474-4422(04)00710-0.CrossRefGoogle ScholarPubMed
Ellis, K. A.et al. (2009). The Australian imaging, biomarkers and lifestyle study of aging: methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer's disease. International Psychogeriatrics, 21, 672–687. doi:10.1017/S1041610209009405.CrossRefGoogle ScholarPubMed
Gibbons, L.et al. (2012). A composite score for executive functioning, validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment. Brain Imaging and Behavior, 6, 517–527. doi:10.1007/s11682-012-9176-1.CrossRefGoogle Scholar
Hedden, T., Oh, H., Younger, A. P. and Patel, T. A. (2013). Meta-analysis of amyloid-cognition relations in cognitively normal older adults. Neurology, 80, 1341–1348.CrossRefGoogle ScholarPubMed
Jack, C. R.et al. (2008). 11C PiB and structural MRI provide complementary information in imaging of Alzheimer's disease and amnestic mild cognitive impairment. Brain, 131, 665–680.CrossRefGoogle ScholarPubMed
Johnson, J. K., Gross, A., Pa, J., Mclaren, D. G., Park, L. Q. and Manly, J. J. (2012). Longitudinal change in neuropsychological performance using latent growth models: a study of mild cognitive impairment. Brain Imaging and Behavior, 6, 540–550. doi:10.1007/s11682-012-9161-8.CrossRefGoogle ScholarPubMed
Libon, D.J., Swenson, R.A., Barnoski, E.J. and Sands, L.P. (1993). Clock drawing as an assessment tool for dementia. Archives of Clinical Neuropsychology, 8, 405–415.CrossRefGoogle ScholarPubMed
Mathis, C. A.et al. (2013). In vivo assessment of amyloid-β deposition in nondemented very elderly subjects. Annals of Neurology. doi:10.1002/ana.23797.CrossRefGoogle ScholarPubMed
Meyers, J. E. and Meyers, K. R. (1995). Rey Complex Figure Test and Recognition Trial, Professional Manual. Lutz, FL: Psychological Assessment Resource.Google Scholar
Nuechterlein, K. H.et al. (2008). The MATRICS consensus cognitive battery, part 1: test selection, reliability and validity. American Journal of Psychiatry, 165, 203–213.CrossRefGoogle ScholarPubMed
Pike, K. E.et al. (2007). β-amyloid imaging and memory in non-demented individuals: evidence for pre-clinical Alzheimer's disease. Brain, 130, 2837–2844. doi:10.1093/brain/awm238.CrossRefGoogle Scholar
Rowe, C. C.et al. (2010). Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Neurobiology of Aging, 31, 1275–1283. doi:10.1016/j.neurobiolaging.2010.04.007.CrossRefGoogle ScholarPubMed
Saxton, J.et al. (2000). Normative data on the Boston Naming Test and two equivalent 30-item short forms. Clinical Neuropychology, 14, 526–534.CrossRefGoogle ScholarPubMed
Sperling, R. A.et al. (2011). Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging and the Alzheimer's Association workgroup. Alzheimer's and Dementia, 7, 280–292. doi:10.1016/j.jalz.2011.03.003.CrossRefGoogle Scholar
Sperling, R. A.et al. (2013). Amyloid deposition detected with florbetapir F 18 (18F-AV-45) is related to lower episodic memory performance in clinically normal older individuals. Neurobiology of Aging, 34, 822–831.CrossRefGoogle ScholarPubMed
Strauss, E., Sherman, M. S. Elisabeth and Spreen, O. (2006). A Compendium of Neuropsychological Tests: Administration, Norms, and Commentary, 3rd edn.New York, NY: Oxford University Press.Google Scholar
Villemagne, V. L.et al. (2011). Longitudinal assessment of Aβ and cognition in aging and Alzheimer disease. Annals of Neurology, 69, 181–192. doi:10.1002/ana.22248.CrossRefGoogle ScholarPubMed
Wechsler, D. (1945). A standardised memory scale for clinical use. Journal of Psychology, 19, 87–95.CrossRefGoogle Scholar
Wechsler, D. (1997). Wechsler Adult Intelligence Scale (WAIS-III), 3rd edn.San Antonio, TX: Psychological Corporation.Google Scholar
Winblad, B.et al. (2004). Mild cognitive impairment – beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitve Impairment. Journal of Internal Medicine, 256, 240–246.CrossRefGoogle Scholar
Yang, L., Rieves, D. and Ganley, C. (2012). Brain amyloid imaging – FDA approval of Florbetapir F18 injection. New England Journal of Medicine, 367, 885–887. doi:10.1056/NEJMp1208061.CrossRefGoogle ScholarPubMed
Zakzanis, K. K. (2001). Statistics to tell the truth, the whole truth, and nothing but the truth: formulae, illustrative numerical examples, and heuristic interpretation of effect size analyses for neuropsychological researchers. Archives of Clinical Neuropsychology, 16, 653–667.CrossRefGoogle ScholarPubMed