Prevalence and outcomes of amyloid positivity among persons without dementia in a longitudinal, population-based setting
Open accessAbstract
Importance: Brain amyloid deposition is a marker of Alzheimer disease (AD) pathology. The population-based prevalence and outcomes of amyloid positivity in a population without dementia are important for understanding the trajectory of amyloid positivity to clinically significant outcomes and for designing AD prevention trials. Objective: To determine prevalence and outcomes of amyloid positivity in a population without dementia. Design, Setting, and Participants: In the prospective, population-based Mayo Clinic Study of Aging in Olmsted County, Minnesota, participants without dementia were randomly selected from the county population and were clinically and cognitively evaluated at baseline and every 15 months from August 1, 2008, to September 18, 2018. They were also invited to undergo carbon11-Pittburgh compound B positron emission tomography (PET) imaging. Exposures: Amyloid positivity (defined as a standardized uptake value ratio >1.42 on PET). Main Outcomes and Measures: Prevalence of amyloid positivity in the Olmsted County population without dementia and risk of progression from no cognitive impairment (ie, normal cognition for age) to incident amnestic MCI (aMCI) and from MCI or aMCI to incident AD dementia. Results: Of 3894 participants, 1671 underwent PET imaging and were included in the study; 2198 did not undergo imaging, and 25 were excluded for other reasons. The mean (SD) age of participants was 71.3 (9.8) years; 892 (53.4%) were men, and 179 (10.7%) had prevalent MCI. The prevalence of amyloid positivity without cognitive impairment in the population without dementia increased from 2.7% (95% CI, 0.5% to 4.9%) in persons aged 50 to 59 years to 41.3% (95% CI, 33.4% to 49.2%) in those aged 80 to 89 years at baseline. Prevalence of amyloid-positive MCI in the population without dementia increased from 0% in persons aged 50 to 59 years to 16.4% (95% CI, 10.3% to 22.5%) in those aged 80 to 89 years. The incident aMCI risk increased more than 2-fold in participants without cognitive impairment who were amyloid positive vs those who were amyloid negative (hazard ratio [HR], 2.26; 95% CI, 1.52 to 3.35; P < .001). The risk of AD dementia was 1.86 (95% CI, 0.89 to 3.88; P = .10) for amyloid-positive participants with MCI vs amyloid-negative participants with MCI, 1.63 (95% CI, 0.78 to 3.41; P = .20) for participants with aMCI who were amyloid positive vs amyloid negative, and 2.56 (95% CI, 1.35 to 4.88; P = .004) for amyloid-positive participants who were either without cognitive impairment or had aMCI vs those who were amyloid negative. Global cognitive and memory domain z scores declined significantly in amyloid-positive individuals during follow-up. The mean (SD) follow-up time from baseline was 3.7 (1.9) years to incident aMCI and 3.8 (2.0) years to incident AD dementia. Conclusions and Relevance: Population-based prevalence of amyloid-positive status and progression rates of amyloid positivity provide valid information for designing AD prevention trials and assessing the public health outcomes of AD prevention and interventions.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Reduction of these risk factors might be protective for people with or without a genetic risk, although study findings have not been entirely consistent.
“Reduction of these risk factors might be protective for people with or without a genetic risk, although study findings have not been entirely consistent.175, 176, 177, 178”
From Dementia prevention, intervention, and care: 2020 report of the Lancet Commission (2020) · cites this paper as [177]
The Statistical Analyses section (page not available) mentions vascular diseases and ApoE ε4 genotype, but only as covariates in analyses of amyloid-related progression. Searches for risk-factor reduction, protection across genetic-risk groups, and inconsistent prevention findings found no passage addressing those points. (LLM, conf=0.76)
Experimental — accuracy not yet measuredThe shorter age-specific duration of the preclinical stage in APOE ε4 carriers is consistent with earlier onset of Alzheimer's disease dementia in epidemiological studies and faster cognitive decline in APOE ε4 carriers with preclinical Alzheimer's disease in research studies.
“The shorter age-specific duration of the preclinical stage in APOE ε4 carriers is consistent with the observed earlier onset of dementia due to AD in epidemiological studies and the faster cognitive decline of APOE ε4 carriers with preclinical AD in research studies [11, 42-44].”
From Duration of preclinical, prodromal, and dementia stages of Alzheimer's disease in relation to age, sex, and <i>APOE</i> genotype (2019) · cites this paper as [42]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Diagnostic and Statistical Manual of Mental Disorders
American Psychiatric Association (2013) · doi:10.1176/appi.books.9780890425596 · Cited by 116,369 · see citing works
Diagnostic and Statistical Manual of Mental Disorders
Williams, J. B. W., & First, M. B. (2013) · Oxford University Press eBooks · doi:10.1093/acrefore/9780199975839.013.104 · Cited by 109,841 · see citing works
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 · see citing works
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 · see citing works
Self-citationAlbert, 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 · see citing works
Self-citationMild cognitive impairment as a diagnostic entity
Petersen, R. C. (2004) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2004.01388.x · Cited by 7,864 · see citing works
Self-citationSperling, 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 · see citing works
Self-citationResearch 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 · see citing works
Albert, M., DeKosky, S. T., Dickson, D. W., Dubois, B., Feldman, H., Fox, N. C., Gamst, A. C., Holtzman, D. M., Jagust, W. J., Petersen, R. C., et al. (2013) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.11.1.96 · Cited by 2,630 · see citing works
Self-citationAlzheimer's Disease Neuroimaging Initiative (ADNI)
Petersen, R. C., Aisen, P. S., Beckett, L. A., Donohue, M. C., Gamst, A. C., Harvey, D. J., Jack, C. R., Jagust, W. J., Shaw, L. M., Toga, A. W., et al. (2010) · Neurology · doi:10.1212/wnl.0b013e3181cb3e25 · Cited by 2,572 · see citing works
Self-citationPreclinical Alzheimer’s Disease: Definition, Natural History, and Diagnostic Criteria
Dubois, B., Hampel, H., Feldman, H. H., Scheltens, P., Aisen, P., Andrieu, S., Bakardjian, H., Benali, H., Bertram, L., Blennow, K., et al. (2016) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2016.02.002 · Cited by 1,925 · see citing works
Self-citationA/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers
Jack, C. R., Bennett, D. A., Blennow, K., Carrillo, M. C., Feldman, H. H., Frisoni, G. B., Hampel, H., Jagust, W. J., Johnson, K. A., Knopman, D. S., et al. (2016) · Neurology · doi:10.1212/wnl.0000000000002923 · Cited by 1,864 · see citing works
Self-citationHansson, O., Zetterberg, H., Buchhave, P., Londos, E., Blennow, K., & Minthon, L. (2006) · The Lancet Neurology · doi:10.1016/s1474-4422(06)70355-6 · Cited by 1,700 · see citing works
Prevalence of Cerebral Amyloid Pathology in Persons Without Dementia: A Meta-analysis
Jansen, W. J., Ossenkoppele, R., Knol, D. L., Tijms, B. M., Scheltens, P., Verhey, F. R. J., Visser, P. J., Aalten, P., Aarsland, D., Alcolea, D., et al. (2015) · JAMA · doi:10.1001/jama.2015.4668 · Cited by 1,610 · see citing works
Defining imaging biomarker cut points for brain aging and Alzheimer's disease
Jack, C. R., Wiste, H. J., Weigand, S. D., Therneau, T. M., Lowe, V. J., Knopman, D. S., Gunter, J. L., Senjem, M. L., Jones, D. T., Kantarci, K., et al. (2017) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2016.08.005 · Cited by 931 · see citing works
Self-citationRoberts, R. O., Geda, Y. E., Knopman, D. S., Cha, R. H., Pankratz, V. S., Boeve, B. F., Ivnik, R. J., Tangalos, E. G., Petersen, R. C., & Rocca, W. A. (2008) · Neuroepidemiology · doi:10.1159/000115751 · Cited by 796 · see citing works
Self-citationPrevalence of mild cognitive impairment is higher in men
Petersen, R. C., Roberts, R. O., Knopman, D. S., Geda, Y. E., Cha, R. H., Pankratz, V. S., Boeve, B. F., Tangalos, E. G., Ivnik, R. J., & Rocca, W. A. (2010) · Neurology · doi:10.1212/wnl.0b013e3181f11d85 · Cited by 738 · see citing works
Self-citationAmyloid Deposition, Hypometabolism, and Longitudinal Cognitive Decline
Landau, S. M., Mintun, M., Joshi, A. D., Koeppe, R., Petersen, R. C., Aisen, P., Weiner, M., & Jagust, W. J. (2012) · Annals of Neurology · doi:10.1002/ana.23650 · Cited by 723 · see citing works
Self-citationPrevalence of Amyloid PET Positivity in Dementia Syndromes: A Meta-analysis
Ossenkoppele, R., Jansen, W. J., Rabinovici, G. D., Knol, D. L., van der Flier, W. M., van Berckel, B. N. M., Scheltens, P., Visser, P. J., Verfaillie, S. C. J., Zwan, M. D., et al. (2015) · JAMA · doi:10.1001/jama.2015.4669 · Cited by 677 · see citing works
Data Resource Profile: The Rochester Epidemiology Project (REP) medical records-linkage system
Sauver, J. L. S., Grossardt, B. R., Yawn, B. P., Melton, L. J., Pankratz, J. J., Brue, S. M., & Rocca, W. A. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dys195 · Cited by 613 · see citing works
Preclinical Alzheimer's disease and its outcome: a longitudinal cohort study
Vos, S. J., Xiong, C., Visser, P. J., Jasielec, M. S., Hassenstab, J., Grant, E. A., Cairns, N. J., Morris, J. C., Holtzman, D. M., & Fagan, A. M. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70194-7 · Cited by 564 · see citing works
Survey Nonresponse Adjustments for Estimates of Means
Little, R. J. A. (1986) · International Statistical Review · doi:10.2307/1403140 · Cited by 524 · see citing works
Donohue, M. C., Sperling, R. A., Petersen, R., Sun, C.-K., Weiner, M. W., Aisen, P. S., & Initiative, F. T. A. D. N. (2017) · JAMA · doi:10.1001/jama.2017.6669 · Cited by 452 · see citing works
Self-citationMayo's older americans normative studies: WAIS-R norms for ages 56 to 97
Ivnik, R. J., Malec, J. F., Smith, G. E., Tangalos, E. G., Petersen, R. C., Kokmen, E., & Kurland, L. T. (1992) · The Clinical Neuropsychologist · doi:10.1080/13854049208401877 · Cited by 446 · see citing works
Self-citationJack, C. R., Wiste, H. J., Weigand, S. D., Rocca, W. A., Knopman, D. S., Mielke, M. M., Lowe, V. J., Senjem, M. L., Gunter, J. L., Preboske, G. M., et al. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70194-2 · Cited by 358 · see citing works
Self-citationAdvances in strategies for minimizing and adjusting for survey nonresponse
Kessler, R. C., Little, R. J. A., & Groves, R. M. (1995) · Epidemiologic Reviews · doi:10.1093/oxfordjournals.epirev.a036176 · Cited by 341 · see citing works
Estimating and Using Propensity Scores with Partially Missing Data
D'Agostino, R., & Rubin, D. (2000) · Journal of the American Statistical Association · doi:10.1080/01621459.2000.10474263 · Cited by 330 · see citing works
The incidence of MCI differs by subtype and is higher in men
Roberts, R. O., Geda, Y. E., Knopman, D. S., Cha, R. H., Pankratz, V. S., Boeve, B. F., Tangalos, E. G., Ivnik, R. J., Rocca, W. A., & Petersen, R. C. (2012) · Neurology · doi:10.1212/wnl.0b013e3182452862 · Cited by 268 · see citing works
Self-citationMild cognitive impairment due to Alzheimer disease in the community
Petersen, R. C., Aisen, P., Boeve, B. F., Geda, Y. E., Ivnik, R. J., Knopman, D. S., Mielke, M., Pankratz, V. S., Roberts, R., Rocca, W. A., et al. (2013) · Annals of Neurology · doi:10.1002/ana.23931 · Cited by 265 · see citing works
Self-citationShort-term clinical outcomes for stages of NIA-AA preclinical Alzheimer disease
Knopman, D. S., Jack, C. R., Wiste, H. J., Weigand, S. D., Vemuri, P., Lowe, V. J., Kantarci, K., Gunter, J. L., Senjem, M. L., Ivnik, R. J., et al. (2012) · Neurology · doi:10.1212/wnl.0b013e3182563bbe · Cited by 243 · see citing works
Self-citationRowe, C. C., Bourgeat, P., Ellis, K. A., Brown, B., Lim, Y. Y., Mulligan, R., Jones, G., Maruff, P., Woodward, M., Price, R., et al. (2013) · Annals of Neurology · doi:10.1002/ana.24040 · Cited by 222 · see citing works
Senjem, M. L., Gunter, J. L., Shiung, M. S., Petersen, R. C., & Jack, C. R. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.02.005 · Cited by 206 · see citing works
Self-citationPetersen, R. C., Wiste, H. J., Weigand, S. D., Rocca, W. A., Roberts, R. O., Mielke, M. M., Lowe, V. J., Knopman, D. S., Pankratz, V. S., Machulda, M. M., et al. (2016) · JAMA Neurology · doi:10.1001/jamaneurol.2015.3098 · Cited by 196 · see citing works
Self-citationA European multicentre PET study of fibrillar amyloid in Alzheimer’s disease
Nordberg, A., Carter, S. F., Rinne, J., Drzezga, A., Brooks, D. J., Vandenberghe, R., Perani, D., Forsberg, A., Långström, B., Scheinin, N., et al. (2013) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-012-2237-2 · Cited by 186 · see citing works
Preclinical AD predicts decline in memory and executive functions in subjective complaints
van Harten, A. C., Smits, L. L., Teunissen, C. E., Visser, P. J., Koene, T., Blankenstein, M. A., Scheltens, P., & van der Flier, W. M. (2013) · Neurology · doi:10.1212/wnl.0b013e3182a8418b · Cited by 143 · see citing works
Rates of β-amyloid accumulation are independent of hippocampal neurodegeneration
Jack, C. R., Wiste, H. J., Knopman, D. S., Vemuri, P., Mielke, M. M., Weigand, S. D., Senjem, M. L., Gunter, J. L., Lowe, V. J., Gregg, B. E., et al. (2014) · Neurology · doi:10.1212/wnl.0000000000000386 · Cited by 124 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- Dubois B, Hampel H, Feldman HH, et al; Proceedings of the Meeting of the International Working Group (IWG) and the American Alzheimer's Association on "The Preclinical State of AD"; July 23, 2015;
Cited by
Sorted by citations
Dementia prevention, intervention, and care: 2020 report of the Lancet Commission
Livingston, G., Huntley, J., Sommerlad, A., Ames, D., Ballard, C., Banerjee, S., Brayne, C., Burns, A., Cohen-Mansfield, J., Cooper, C., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30367-6 · Cited by 10,430 · see citing works
RetractedKnopman, D. S., Amieva, H., Petersen, R. C., Chételat, G., Holtzman, D. M., Hyman, B. T., Nixon, R. A., & Jones, D. T. (2021) · Nature Reviews Disease Primers · doi:10.1038/s41572-021-00269-y · Cited by 2,606 · see citing works
Self-citationVermunt, L., Sikkes, S. A. M., van den Hout, A., Handels, R., Bos, I., van der Flier, W. M., Kern, S., Ousset, P., Maruff, P., Skoog, I., et al. (2019) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2019.04.001 · Cited by 570 · see citing works
Trial of solanezumab in preclinical Alzheimer's disease
Sperling, R. A., Donohue, M. C., Raman, R., Rafii, M. S., Johnson, K., Masters, C. L., van Dyck, C. H., Iwatsubo, T., Marshall, G. A., Yaari, R., et al. (2023) · New England Journal of Medicine · doi:10.1056/nejmoa2305032 · Cited by 429 · see citing works
Plasma Amyloid as Prescreener for the Earliest <scp>A</scp> lzheimer Pathological Changes
Verberk, I. M. W., Slot, R. E., Verfaillie, S. C. J., Heijst, H., Prins, N. D., van Berckel, B. N. M., Scheltens, P., Teunissen, C. E., & van der Flier, W. M. (2018) · Annals of Neurology · doi:10.1002/ana.25334 · Cited by 315 · see citing works
Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum
Jansen, W. J., Janssen, O., Tijms, B. M., Vos, S. J. B., Ossenkoppele, R., Visser, P. J., Amyloid Biomarker Study Group, Aarsland, D., Alcolea, D., Altomare, D., et al. (2022) · JAMA Neurology · doi:10.1001/jamaneurol.2021.5216 · Cited by 290 · see citing works
Heterogeneity of Alzheimer’s disease: consequence for drug trials?
Devi, G., & Scheltens, P. (2018) · Alzheimer's Research & Therapy · doi:10.1186/s13195-018-0455-y · Cited by 102 · see citing works
Dang, C., Harrington, K. D., Lim, Y. Y., Ames, D., Hassenstab, J., Laws, S. M., Yassi, N., Hickey, M., Rainey-Smith, S., Robertson, J., et al. (2018) · Journal of Alzheimer’s Disease · doi:10.3233/jad-180507 · Cited by 31 · see citing works
Zhukovsky, P., Coughlan, G., Buckley, R., Grady, C., & Voineskos, A. N. (2023) · Human Brain Mapping · doi:10.1002/hbm.26148 · Cited by 26 · see citing works
Souchet, B., Michaïl, A., Heuillet, M., Dupuy-Gayral, A., Haudebourg, E., Pech, C., Berthemy, A., Autelitano, F., Billoir, B., Domoto-Reilly, K., et al. (2024) · The Journal of Prevention of Alzheimer's Disease · doi:10.14283/jpad.2024.34 · Cited by 15 · see citing works
- Authors
- Roberts, R. O., Aakre, J. A., Kremers, W. K., Vassilaki, M., Knopman, D. S., Mielke, M. M., Alhurani, R., Geda, Y. E., Machulda, M. M., Coloma, P., Schauble, B., Lowe, V. J., Jack, C. R., & Petersen, R. C.
- Affiliations
- Mayo Clinic (US)
- F. Hoffmann-La Roche AG (CH)
- Medical Affairs, F. Hoffmann-La Roche Ltd, Basel, Switzerland
- Corresponding author
- Roberts, Rosebud O.
- ORCID
- Venue
- JAMA Neurology
- Publisher
- American Medical Association (AMA)
- Published
- 2018-08-01
- Volume
- 75
- Issue
- 8
- Pages
- 970
- ISSN
- 2168-6149 (ISSN-L)
- PMC
- PMC6142936
- OpenAlex
- W2801534945
- Cited by
- 223
- References
- 36
- Citations by year
- 2026: 23 · 2025: 45 · 2024: 33 · 2023: 28 · 2022: 22 · 2021: 31 · 2020: 22 · 2019: 12 · 2018: 7
- FWCI
- 14.17
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA Neurology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Mayo Foundation for Medical Education and Research
- GHR Foundation
- National Institutes of Health
- National Institute on Aging (R01AG034676, U01AG006786, R01AG011378, R01AG041851, P50AG016574)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Cancer-related cognitive impairment studies
- Keywords
- brain amyloid deposition, Alzheimer's disease, amyloid PET, amnestic mild cognitive impairment, conversion to dementia, cognitive impairment, Mayo Clinic Study of Aging, Olmsted County, Minnesota, standardized uptake value ratio, Pittsburgh compound B
- MeSH terms
- Aged, Alzheimer Disease, Aniline Compounds, Brain, Female, Humans, Longitudinal Studies, Male, Middle Aged, Prospective Studies, Thiazoles, United States, Prevalence, Proportional Hazards Models, Case-Control Studies, Positron-Emission Tomography, Asymptomatic Diseases, Plaque, Amyloid, Cognitive Dysfunction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
