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Predicting Alzheimer disease with β‐amyloid imaging: Results from the Australian imaging, biomarkers, and lifestyle study of ageing
Open accessAbstract
Objective: Biomarkers for Alzheimer disease (AD) can detect the disease pathology in asymptomatic subjects and individuals with mild cognitive impairment (MCI), but their cognitive prognosis remains uncertain. We aimed to determine the prognostic value of β‐amyloid imaging, alone and in combination with memory performance, hippocampal atrophy, and apolipoprotein E ε4 status in nondemented, older individuals. Methods: A total of 183 healthy individuals (age = 72.0 ± 7.26 years) and 87 participants with MCI (age = 73.7 ± 8.27) in the Australian Imaging, Biomarkers, and Lifestyle study of ageing were studied. Clinical reclassification was performed after 3 years, blind to biomarker findings. β‐Amyloid imaging was considered positive if the 11 C‐Pittsburgh compound B cortical to reference ratio was ≥1.5. Results: Thirteen percent of healthy persons progressed (15 to MCI, 8 to dementia), and 59% of the MCI cohort progressed to probable AD. Multivariate analysis showed β‐amyloid imaging as the single variable most strongly associated with progression. Of combinations, subtle memory impairment ( Z score = −0.5 to −1.5) with a positive amyloid scan was most strongly associated with progression in healthy individuals (odds ratio [OR] = 16, 95% confidence interval [CI] = 3.7–68; positive predictive value [PPV] = 50%, 95% CI = 19–81; negative predictive value [NPV] = 94%, 95% CI = 88–98). Almost all amnestic MCI subjects ( Z score ≤ −1.5) with a positive amyloid scan developed AD (OR = ∞; PPV = 86%, 95% CI = 72–95; NPV = 100%, 95% CI = 80–100). Hippocampal atrophy and ε4 status did not add further predictive value. Interpretation: Subtle memory impairment with a positive β‐amyloid scan identifies healthy individuals at high risk for MCI or AD. Clearly amnestic patients with a positive amyloid scan have prodromal AD and a poor prognosis for dementia within 3 years. Ann Neurol 2013;74:905–913
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“Numerous studies have shown that CU individuals with abnormal amyloid biomarkers have more rapid progression of atrophy, hypometabolism, and clinical/cognitive decline than individuals without biomarker evidence of Aβ deposition [13,33,80,93–99]”
From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [93]
In the citing paper
“Older studies of 11C-Pittsburgh compound B imaging suggested that only 13% of cognitively normal individuals that are positive for Aβ will transition to mild cognitive impairment (MCI) or AD (Rowe et al., 2013), whereas recent positron emission tomography (PET) imaging of tau indicates a stronger correlation of tau changes with cognitive impairment and transition to MCI (Hanseeuw et al., 2019).”
From Dendritic Spine Remodeling and Synaptic Tau Levels in PS19 Tauopathy Mice (2021) · cites this paper as Rowe et al., 2013
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Cites
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.005 · Cited by 18,657
Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., Gamst, A., Holtzman, D. M., Jagust, W. J., Petersen, R. C., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.008 · Cited by 10,152
Mild Cognitive Impairment: Clinical Characterization and Outcome
Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999) · Archives of Neurology · doi:10.1001/archneur.56.3.303 · Cited by 8,980
Sperling, R. A., Aisen, P. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M., Iwatsubo, T., Jack, C. R., Kaye, J., Montine, T. J., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.003 · Cited by 7,155
Self-citationWinblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L. ‐., Nordberg, A., Bäckman, L., Albert, M., Almkvist, O., et al. (2004) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2004.01380.x · Cited by 4,946
A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains
Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N. A., Friston, K. J., & Frackowiak, R. S. J. (2001) · NeuroImage · doi:10.1006/nimg.2001.0786 · Cited by 4,561
Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria
Dubois, B., Feldman, H. H., Jacova, C., DeKosky, S. T., Barberger-Gateau, P., Cummings, J., Delacourte, A., Galasko, D., Gauthier, S., Jicha, G., et al. (2007) · The Lancet Neurology · doi:10.1016/s1474-4422(07)70178-3 · Cited by 4,411
Gauthier, S. G., Reisberg, ., Zaudig, M., Petersen, R. C., Ritchie, K. A., Broich, K., Belleville, S., Brodaty, H., Bennett, D. A., Chertkow, H. M., et al. (2006) · The Lancet · doi:10.1016/s0140-6736(06)68542-5 · Cited by 4,094
Villemagne, V. L., Burnham, S., Bourgeat, P., Brown, B., Ellis, K. A., Salvado, O., Szoeke, C., Macaulay, S. L., Martins, R., Maruff, P., et al. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70044-9 · Cited by 2,279
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Research works printed but not linked: 2
- Delis DC, 2000, CVLT‐II: California Verbal Learning Test
- KlunkWE.Classification of amyloid‐positivity in controls: comparison of objective approaches to visual reads. Paper presented at: Human Amyloid Imaging Conference; April 11 2008; Chicago IL.
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Items 201–222 of 222
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Villemagne, V. L., Doré, V., Burnham, S. C., & Rowe, C. C. (2020) · Springer eBooks · doi:10.1007/978-3-030-53168-3_10 · Cited by 2
Self-citationGuidotti, L., Lucchesi, M., Daghini, E., Amato, R., Neri, G., Corsi, F., Marracci, S., Gargini, C., Borello, U., Cammalleri, M., et al. (2026) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.67.2.31 · Cited by 1
The research of AD early assessment based on EEG analysis
Li, X., Lu-Yun, Q., Qiu-Yue, L., & Ze-Tao, C. (2017) · Chinese Automation Congress · doi:10.1109/cac.2017.8243252 · Cited by 1
Ethics of Informed Consent, Coercive and Preventive Medication
Helmchen, H. (2020) · Springer eBooks · doi:10.1007/978-3-319-56015-1_404-1 · Cited by 1
Contribution of Global Amyloid-PET Imaging for Predicting Future Cognition in the MEMENTO Cohort
Ackley, S. F., Calmasini, C., Bouteloup, V., Hill‐Jarrett, T. G., Swinnerton, K. N., Chêne, G., Dufouil, C., Glymour, M. M., & for the MEMENTO Cohort Study Group and DPUK (2024) · Neurology · doi:10.1212/wnl.0000000000208054 · Cited by 1
Masters, C. L., Gu, B. J., Laws, S. M., Lim, Y. Y., Roberts, B. R., Villemagne, V. L., & Beyreuther, K. T. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-811304-2.00003-1 · Cited by 1
Self-citationBiomarkers in dementia with Lewy bodies
Donaghy, P. C. (2016)
Limitations of amyloid imaging in Alzheimer's disease
Weidman, D. A. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-815868-5.00031-1
Recapitulating Parkinson’s disease pathology in a three-dimensional neural cell culture model
Taylor-Whiteley, T. R. (2019) · Sheffield Hallam University · doi:10.7190/shu-thesis-00321
Dendritic spine remodeling and aging
Boros, B. D., & Herskowitz, J. H. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-817990-1.00022-6
Callisaya, M. L., Jayakody, O. M., & Delbaere, K. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108594455.008
Ethics of Informed Consent: Coercive and Preventive Medication
Helmchen, H. (2022) · Springer eBooks · doi:10.1007/978-3-030-62059-2_404
The potential of extracellular vesicle lipid profiling in Alzheimer's disease.Preprint
Su, H., Masters, C. L., Bush, A. I., Barnham, K. J., Reid, G. E., & Vella, L. J. (2023) · doi:10.22541/au.168388562.25020996/v1
Self-citationKancheva, A. K., Lyall, D., Tsvetanov, K. A., Kancheva, I. K., Mavromati, K., Koychev, I. G., Tari, B., García, D. J., Hughes, L., Wardlaw, J. M., et al. (2025) · medRxiv · doi:10.1101/2025.06.27.25330453
Kim, K. Y., Ha, J., Kim, M., Cho, S. Y., Kim, H., & Kim, E. (2022) · Figshare · doi:10.6084/m9.figshare.21501252
Kang, S. H., Lee, K. H., Chang, Y., Choe, Y. S., Kim, J. P., Jang, H., Shin, H. Y., Kim, H. J., Koh, S.-B., Na, D. L., et al. (2022) · Figshare · doi:10.6084/m9.figshare.21273939
Tagmazian, A. A., Schwarz, C., Lange, C., Pitkänen, E., Vuoksimaa, E., & Initiative, T. F. L. D. N. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.02.703218
Tomadesso, C. (2018) · theses.fr (ABES) · doi:10.70675/7fad6418zff81z49c7z984dz63aa2e44d7fc
Dautricourt, S. (2021) · theses.fr (ABES) · doi:10.70675/63472a25z31eaz4ebczaebdzd8d2e061b4b8
Soussi, C., Gonneaud, J., Cabé, N., Lanièpce, A., Marchant, N. L., Collette, F., de Florès, R., Foyard, E., Landeau, B., Mézenge, F., et al. (2026) · EBioMedicine · doi:10.1016/j.ebiom.2026.106376
Le concept de sujet à risque dans la maladie d’Alzheimer
Villain, N. (2026) · Bulletin de l Académie Nationale de Médecine · doi:10.1016/j.banm.2026.06.015
Metadata
- Authors
- Rowe, C. C., Bourgeat, P., Ellis, K. A., Brown, B., Lim, Y. Y., Mulligan, R., Jones, G., Maruff, P., Woodward, M., Price, R., Robins, P., Tochon‐Danguy, H., O'Keefe, G., Pike, K. E., Yates, P., Szoeke, C., Salvado, O., Macaulay, S. L., O'Meara, T., Head, R., Cobiac, L., Savage, G., Martins, R., Masters, C. L., Ames, D., & Villemagne, V. L.
- Affiliations
- Austin Health (AU)
- Australian e-Health Research Centre (AU)
- The University of Melbourne (AU)
- Edith Cowan University (AU)
- Sir Charles Gairdner Hospital (AU)
- La Trobe University (AU)
- National Ageing Research Institute (AU)
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Australian Research Council (AU)
- Corresponding author
- Rowe, Christopher C.
- ORCID
- Venue
- Annals of Neurology
- Publisher
- Wiley
- Published
- 2013-12
- Volume
- 74
- Issue
- 6
- Pages
- 905-913
- ISSN
- 0364-5134 (ISSN-L)
- 1531-8249
- OpenAlex
- W2003569140
- Cited by
- 222
- References
- 39
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 9 · 2023: 15 · 2022: 19 · 2021: 22 · 2020: 18 · 2019: 24 · 2018: 34 · 2017: 13 · 2016: 19 · 2015: 19 · 2014: 17 · 2013: 1
- FWCI
- 13.27
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Annals of Neurology (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Research Bank (Australian Catholic University) (submittedVersion)
- Murdoch University Research Portal (submittedVersion)
- Australasian Journal of Paramedicine (submittedVersion, cc-by-nc)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, other-oa)
- Griffith Research Online (submittedVersion, cc-by-nc)
- Funders
- Commonwealth Scientific Industrial Research Organization (CSIRO)
- Science Industry Endowment Fund
- National Health and Medical Research Council of Australia (1011689)
- Alzheimer's Association
- Alzheimer's Drug Discovery Foundation
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Oncology › Cancer-related cognitive impairment studies
- Keywords
- Alzheimer's disease, amyloid-beta imaging, Pittsburgh compound B, mild cognitive impairment, amnestic MCI, dementia progression, prodromal Alzheimer's disease, memory impairment, hippocampal atrophy, APOE ε4, predictive value, non-demented elderly
- MeSH terms
- Aged, Aged, 80 and over, Aging, Alzheimer Disease, Apolipoproteins E, Atrophy, Australia, Female, Hippocampus, Humans, Life Style, Male, Memory Disorders, Middle Aged, Predictive Value of Tests, Biomarkers, Single-Blind Method, Amyloid beta-Peptides, Cognitive Dysfunction
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