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Preclinical Alzheimer's disease and its outcome: a longitudinal cohort study
Open accessAbstract
Background New research criteria for preclinical Alzheimer's disease have been proposed, which include stages for cognitively normal individuals with abnormal amyloid markers (stage 1), abnormal amyloid and neuronal injury markers (stage 2), or abnormal amyloid and neuronal injury markers and subtle cognitive changes (stage 3). We aimed to investigate the prevalence and long-term outcome of preclinical Alzheimer's disease according to these criteria.Methods Participants were cognitively normal (clinical dementia rating [CDR]=0) community-dwelling volunteers aged at least 65 years who were enrolled between 1998 and 2011 at the Washington University School of Medicine (MO, USA). CSF amyloid-β1-42 and tau concentrations and a memory composite score were used to classify participants as normal (both markers normal), preclinical Alzheimer's disease stage 1-3, or suspected non-Alzheimer pathophysiology (SNAP, abnormal injury marker without abnormal amyloid marker). The primary outcome was the proportion of participants in each preclinical AD stage. Secondary outcomes included progression to CDR at least 0·5, symptomatic Alzheimer's disease (score of at least 0·5 for memory and at least one other domain and cognitive impairments deemed to be due to Alzheimer's disease), and mortality. We undertook survival analyses using subdistribution and standard Cox hazards models and linear mixed models.Findings Of 311 participants, 129 (41%) were classed as normal, 47 (15%) as stage 1, 36 (12%) as stage 2, 13 (4%) as stage 3, 72 (23%) as SNAP, and 14 (5%) remained unclassified. The 5-year progression rate to CDR at least 0·5, symptomatic Alzheimer's disease was 2% for participants classed as normal, 11% for stage 1, 26% for stage 2, 56% for stage 3, and 5% for SNAP. Compared with individuals classed as normal, participants with preclinical Alzheimer's disease had an increased risk of death after adjusting for covariates (hazard ratio 6·2, 95% CI 1·1-35·0; p=0·040).Interpretation Preclinical Alzheimer's disease is common in cognitively normal elderly people and is associated with future cognitive decline and mortality. Thus, preclinical Alzheimer's disease could be an important target for therapeutic intervention.Funding National Institute of Aging of the National Institutes of Health (P01-AG003991, P50-AG05681, P01-AG02676), Internationale Stichting Alzheimer Onderzoek, the Center for Translational Molecular Medicine project LeARN, the EU/EFPIA Innovative Medicines Initiative Joint Undertaking, and the Charles and Joanne Knight Alzheimer Research Initiative.
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“Initial studies in this emerging area have identified subgroups of older adults with subtle cognitive decline that do not conform to expected patterns and investigators have designated them as Suspected Non-Alzheimer Pathology (SNAP) and Unclassified groups [51, 52].”
From Neuropsychological Criteria for Mild Cognitive Impairment Improves Diagnostic Precision, Biomarker Associations, and Progression Rates (2014) · cites this paper as [52]
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“The rate of cognitive decline is significantly greater for cognitively impaired and CU individuals who have abnormalities in both an amyloid biomarker and a second biomarker type (which could be CSF T-tau or P-tau, atrophy, or hypometabolism) in comparison to individuals who have neither or only one of these biomarker abnormalities [30–35,39,40,42–45].”
From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [32]
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“However, the combination of an abnormal MRI, CSF T-tau, or FDG PET study with an abnormal amyloid biomarker provides much more powerful prediction of future cognitive decline [30–35,39,40,42–45] than an abnormal amyloid study alone.”
From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [32]
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“longitudinal studies have demonstrated that soluble p-tau and t-tau are increased already in preclinical disease (e.g., no cognitive impairment but evidence of AD pathology).5,6”
From Cerebrospinal fluid p-tau231 as an early indicator of emerging pathology in Alzheimer's disease (2022) · cites this paper as [5]
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“Attempts to quantify the duration of AD should be age-specific, because age imposes the greatest risk for both dementia and mortality, and take into account APOE genotype, sex, and cerebrospinal fluid (CSF) tau levels [4, 6, 10-12].”
From Duration of preclinical, prodromal, and dementia stages of Alzheimer's disease in relation to age, sex, and APOE genotype (2019) · cites this paper as [12]
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Citations
Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
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
Self-citationA Proportional Hazards Model for the Subdistribution of a Competing Risk
Fine, J. P., & Gray, R. J. (1999) · Journal of the American Statistical Association · doi:10.1080/01621459.1999.10474144 · Cited by 14,290
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
Self-citationThe Clinical Dementia Rating (CDR): Current version and scoring rules
Morris, J. C. (1993) · Neurology · doi:10.1212/wnl.43.11.2412-a · Cited by 9,882
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
Self-citationEveritt, B. S. (2001) · Psychology Press eBooks · doi:10.4324/9781410605542-11 · Cited by 6,877
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
Self-citationClinical and biomarker changes in dominantly inherited Alzheimer's disease
Bateman, R. J., Xiong, C., Benzinger, T. L. S., Fagan, A. M., Goate, A., Fox, N. C., Marcus, D. S., Cairns, N. J., Xie, X., Blazey, T. M., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1202753 · Cited by 3,814
Self-citation
Cited by
Sorted by citations
Items 401–500 of 564
Leroi, I., Peel, C., Rebecca, D., Dunne, R. A., Louise, E., Mahesh, G., Krishnaswami, V., Jane, L., Helen, M., Jane, P., et al. (2020) · Journal of Neurodegenerative Disorders · doi:10.36959/459/600 · Cited by 6
“[10] have demonstrated that those with both positive amyloid and neuronal injury biomarkers have a 20 times higher risk (60% versus 5%) of progression from prodromal disease to dementia over a three-year period.”
BackgroundGrey zone amyloid burden affects memory function: the SCIENCe project
Ebenau, J. L., Verfaillie, S. C. J., van den Bosch, K. A., Timmers, T., Wesselman, L. M. P., van Leeuwenstijn, M. S. S. A., Tuncel, H., Golla, S. S. V., Yaqub, M. M., Windhorst, A. D., et al. (2020) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-020-05012-5 · Cited by 9
Preclinical Alzheimer's disease criteria
Fagan, A. M., & Vos, S. J. B. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70222-9 · Cited by 8
Self-citationvan Gils, A. M., Tolonen, A. J., van Harten, A. C., Vigneswaran, S., Barkhof, F., Visser, L. N. C., Koikkalainen, J. R., Herukka, S., Hasselbalch, S. G., Mecocci, P., et al. (2024) · Alzheimer s Research & Therapy · doi:10.1186/s13195-024-01614-5 · Cited by 7
“The early and accurate identification of individuals who may develop dementia due to AD, i.e., ‘preclinical disease’ [55], and who are eligible for DMT requires the implementation of broader large-scale screening measures and cost-effective detection and diagnostic tools [6, 48].”
Anderson, C. L., Gross, A. L., Pettigrew, C. A., Vazquez, J. P., Moghekar, A., Oh, S., Na, C. H., Albert, M., Worley, P. F., & Soldan, A. (2025) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2025.09.002 · Cited by 8
Abdullah, L. B., Zhou, Z., Hall, J., Petersen, M. E., Zhang, F., & O’Bryant, S. E. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251322966 · Cited by 7
“…Taken together, there is potential of neuroin fl ammation biomarkers along with tau, to serve as an AD biomarker candidate for individuals with ID. 40,41 In the overall sample, low pIQ was associated with increased N markers, re fl ecting that those with low pIQ experience greater burden of…”
InfluentialHowlett, J., Hill, S. M., Ritchie, C. W., & Tom, B. D. M. (2021) · Frontiers in Big Data · doi:10.3389/fdata.2021.676168 · Cited by 9
“These include survival and multi-state models for investigating transitions between disease states[17, 18, 19, 20, 21, 22]; mixed effects models (linear, generalized, non-linear) that incorporate subject-45 specific random effects and can be extended to handle latent time shifts, random change…”
BackgroundLobo, J. D., Moore, D. J., Bondi, M. W., Soontornniyomkij, V., Soontornniyomkij, B., Gouaux, B. D., Achim, C. L., Ellis, R. J., & Sundermann, E. E. (2022) · Journal of NeuroVirology · doi:10.1007/s13365-021-01048-x · Cited by 9
Bao, Y., Shea, Y. F., Chiu, P. K., Kwan, J. S. K., Chan, F. H.-W., & Mak, H. K. (2022) · Scientific Reports · doi:10.1038/s41598-022-14532-z · Cited by 7
How can secondary dementia prevention trials of Alzheimer's disease be clinically meaningful?
Liu, K. Y., Thambisetty, M., & Howard, R. J. (2022) · Alzheimer s & Dementia · doi:10.1002/alz.12788 · Cited by 8
Eruysal, E., Ravdin, L., Zhang, C., Kamel, H., Iadecola, C., & Ishii, M. (2022) · Journal of Alzheimer s Disease · doi:10.3233/jad-220686 · Cited by 7
“All participants were research volunteers enrolled in cohort studies at the Knight Alzheimer’s Disease Research Center at Washington University School of Medicine in St. Louis [18–20].”
Xiong, C., McCue, L. M., Buckles, V., Grant, E., Agboola, F., Coble, D. W., Bateman, R. J., Fagan, A. M., Benzinger, T. L. S., Hassenstab, J. J., et al. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.12912 · Cited by 7
Self-citationGarcía, S., Askew, R. L., Kavcic, V., Shair, S. R., Bhaumik, A., Rose, E., Campbell, S., May, N., Hampstead, B. M., Dodge, H. H., et al. (2023) · Alzheimer Disease & Associated Disorders · doi:10.1097/wad.0000000000000587 · Cited by 7
“9 Identifying aMCI early allows for better samples in AD clinical trials and related research.”
BackgroundDo preclinical Alzheimer's disease criteria work?
Petersen, R. C. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70217-5 · Cited by 7
An UNC5C Allele Predicts Cognitive Decline and Hippocampal Atrophy in Clinically Normal Older Adults
Yang, H., Chhatwal, J. P., Xu, J., White, C. C., Hanseeuw, B. J., Rabin, J. S., Papp, K. V., Buckley, R. F., Schultz, A. P., Properzi, M. J., et al. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-180788 · Cited by 7
“…not assess interactive association of A (cid:2) and rs3846455 G , a potential genetic risk factor of hippocampal neurodegeneration, despite multiple previous reports that A (cid:2) and neurodegeneration have synergistic predictive value for cognitive declineamongclinicallynormalolderadults[23–25].”
New Trajectory of Clinical and Biomarker Changes in Sporadic Alzheimer’s Disease
Zhuo, J., Zhang, Y., Liu, Y., Liu, B., Zhou, X. A., Bartlett, P. F., Jiang, T., & Initiative, A. D. N. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab017 · Cited by 7
Ribbe, M., Kern, S., Börjesson‐Hanson, A., Östling, S., Zetterberg, H., Blennow, K., & Skoog, I. G. (2019) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000499066 · Cited by 8
Li, J., Song, J., Suckling, J., Wang, Y., Zuo, C., Zhang, C. M., Gao, J., Song, Y., Xie, A., Tan, L., et al. (2023) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.11.002 · Cited by 7
“Among CN older individuals, the rates of cognitive decline and loss of hippocampal volume in individuals with SNAP are indistinguishable from those in the A-N-group (Burnham et al., 2016; Gordon et al., 2016; van Harten et al., 2013; Vos et al., 2013).”
InfluentialAlzheimer's disease biomarker states
Vos, S. J. B., & Fagan, A. M. (2015) · The Lancet Neurology · doi:10.1016/s1474-4422(15)00335-x · Cited by 6
Self-citationGenetic and degenerative disorders primarily causing dementia
Masdeu, J. C., & Pascual, B. (2016) · Handbook of clinical neurology · doi:10.1016/b978-0-444-53485-9.00026-x · Cited by 6
“26.9) (Sperling et al., 2011a; Jack et al., 2012; Villemagne et al., 2013; Vos et al., 2013).”
InfluentialPan, W., Teng, Y., Han, X., Liu, S., Pang, X., Wang, L., & Zhao, M. (2025) · The Journal of Prevention of Alzheimer s Disease · doi:10.1016/j.tjpad.2025.100193 · Cited by 5
“Studies have shown that phosphorylated tau is formed in brain tissue before appearance of AD symptoms [ 144 , 145 ], and that elevation of t-Tau in plasma is significantly correlated with AD [ 63 ].”
Mapping the Relationship of Contributing Factors for Preclinical Alzheimer’s Disease
Shi, L., Zhao, L., Wong, A., Wang, D., & Mok, V. (2015) · Scientific Reports · doi:10.1038/srep11259 · Cited by 5
“This coefficient was composed of the reported correlation coefficient (ri), the number of pAD subjects, and the cross-sectional penalty (αi) (equation (2)).”
BackgroundA Framework for Early Recognition of Alzheimer’s Using Machine Learning Approaches
Kumar, L. K., Rao, P. S., & Rao, S. S. (2022) · Lecture notes in networks and systems · doi:10.1007/978-981-19-4863-3_1 · Cited by 5
CSF sTREM2: marking the tipping point between preclinical AD and dementia?
Schindler, S. E., & Holtzman, D. M. (2016) · EMBO Molecular Medicine · doi:10.15252/emmm.201606245 · Cited by 5
Self-citationTowards Establishing Age-Related Cortical Plasticity on the Basis of Somatosensation
Hanley, C., Burianová, H., & Tommerdahl, M. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2019.01.023 · Cited by 6
Vilca, B. N. C., Torres-Simón, L., Żelwetro, A., Rodríguez‐Rojo, I. C., Carnes, A., Piñol‐Ripoll, G., Yubero, R., Paúl, N., & Maestú, F. (2023) · Biomedicines · doi:10.3390/biomedicines11123147 · Cited by 6
“For example, it has been observed that tau load is more directly correlated with cognitive decline than total amyloid plaque aggregates [16,17].”
BackgroundDifference in trajectories according to early amyloid accumulation in cognitively unimpaired elderly
Kim, Y. J., Yun, J., Seo, S. W., Kim, J. P., Jang, H., Kim, H. J., Na, D. L., Woo, S., Chun, M. Y., & Initiative, A. D. N. (2024) · European Journal of Neurology · doi:10.1111/ene.16482 · Cited by 5
Hashemi, M., Teimouri-Jervekani, Z., Mortazavi, S., Maracy, M. R., & Barekatain, M. (2018) · Arquivos de Neuro-Psiquiatria · doi:10.1590/0004-282x20180026 · Cited by 5
Gao, F., Shang, S., Chen, C., Dang, L., Gao, L., Wei, S., Wang, J., Huo, K., Deng, M., Wang, J., et al. (2020) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.557005 · Cited by 5
“Amyloid pathology, visualized on positron emission tomography (PET) scans or measured in cerebrospinal fluid (CSF), has been extensively studied and has proven clinical applications for AD (Sperling et al., 2013; Vos et al., 2013; Toledo et al., 2015; Dubois et al., 2016; Olsson et al., 2016; Donohue et al., 2017).”
BackgroundCognitive Decline in Preclinical Stage 2 Alzheimer Disease and Implications for Prevention Trials
Mormino, E. C., & Papp, K. V. (2016) · JAMA Neurology · doi:10.1001/jamaneurol.2016.0281 · Cited by 5
Zinkunegi, A. J., Wilson, R. E., Langhough, R. E., Ashton, N. J., Blennow, K., Johnson, S. C., Zetterberg, H., Bruno, D., & Mueller, K. D. (2025) · The Clinical Neuropsychologist · doi:10.1080/13854046.2025.2481119 · Cited by 4
“Furthermore, in preclinical AD, cognitive decline is strongly associated with episodic memory task performance (Aschenbrenner et al., 2024; Lim et al., 2013, 2016; Vos et al., 2013).”
Zeng, Y., Li, H., Zi, J., Hu, Y., Li, X., Cao, Q., Li, Y., Ran, Z., Wang, X., Cheng, G., et al. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.119999 · Cited by 4
Rådestig, M. A., Skoog, J., Zetterberg, H., Kern, J., Zettergren, A., Sacuiu, S. F., Wærn, M., Wetterberg, H., Blennow, K., Skoog, I. G., et al. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200751 · Cited by 5
“Population-based studies [7, 9, 12, 14–17] have yieldeddisparateresults,someshowingarelationship betweenamyloidpositivityonPETandsubtlecog-nitivechangesinotherwisecognitivelyunimpaired individuals[7,15–17, 19] , whileothersdemonstrate whileothersdemonstrate”
Na, S., Lee, C., Ho, S. H., Hong, Y. J., Jeong, J. H., Park, K. H., Kim, S., Wang, M. J., Choi, S. H., Han, S., et al. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-230667 · Cited by 4
“Individuals with preclinical AD, who are cognitively normal yet present evidence of amyloid pathology in the brain, are at an increased risk of developing dementia due to AD [52].”
Palade, J., Alsop, E. B., Courtright-Lim, A., Hsieh, M., Whitsett, T. G., Galasko, D. R., & Keuren‐Jensen, K. R. V. (2024) · Cells · doi:10.3390/cells13030207 · Cited by 4
Aschenbrenner, A. J., Hassenstab, J. J., Schindler, S. E., Janelidze, S., Hansson, O., Morris, J. C., & Grober, E. H. (2024) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2024.130 · Cited by 4
“The rate of cognitive decline in preclinical AD is strongly associated with performance on episodic memory tasks (12, 14-17).”
Self-citationThe need for “objective measurements” in FDG and amyloid PET neuroimaging
Perani, D., Iaccarino, L., & Bettinardi, V. (2014) · Clinical and Translational Imaging · doi:10.1007/s40336-014-0072-0 · Cited by 4
Park, D. C., & Farrell, M. E. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-411469-2.00005-4 · Cited by 4
Zhao, Y., Ou, Y., Ma, Y., Tan, L., & Yu, J. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-221154 · Cited by 4
“With amyloid pathology yet without objective cognitive impairment, stage 1 and 2 are considered as a pre-clinicalstate,whichareimportantstagesforcognitive interventions[4–6].”
Nouriziabari, B., Sarkar, S., Tanninen, S. E., Dayton, R. D., Klein, R. L., & Takehara‐Nishiuchi, K. (2018) · Journal of Alzheimer s Disease · doi:10.3233/jad-171033 · Cited by 6
“Convergent findings from people with autosomal dominant forms of Alzheimer’s disease (AD) and at-risk cohorts indicate that the pathophysiological process of AD is evident many years before the clinical diagnosis of dementia [1–3].”
Integrated multimodal imaging in neurodegenerative disease
Grossman, M. (2015) · The Lancet Neurology · doi:10.1016/s1474-4422(15)00182-9 · Cited by 4
Gertz, H. (2015) · Springer eBooks · doi:10.1007/978-3-662-47047-3_10 · Cited by 4
Biomarkers of Alzheimer’s disease
Bos (2018) · Research Publications (Maastricht University) · doi:10.26481/dis.20181012ib · Cited by 4
Boza-Calvo, C., Faustin, A., Zhang, Y., Briggs, A., Bernard, M. A., Bubu, O. M., Rao, J. A., Gurin, L. J., Tall, S. O., Osorio, R. S., et al. (2024) · Journal of Geriatric Psychiatry and Neurology · doi:10.1177/08919887241263097 · Cited by 3
“26 Studies of Hispanic populations living in the U.S. suggests that although SCD rates are comparable to NHWs, 12,19,24,27 it may develop at younger ages.”
Parhizi, B., Kolady, R., Vogel, M. T., Singh, R. K., Bekena, S., Chokkalingam, R., Zhu, Y., & Babulal, G. M. (2025) · Journal of Alzheimer s Disease Reports · doi:10.1177/25424823251407543 · Cited by 3
“38,39 Driving data and measures Data were collected from June 30, 2022, to January 3, 2024; additional data collection is ongoing for future use.”
Schweiger, A., Rodebaugh, T. L., Lenze, E. J., Keenoy, K., Hassenstab, J. J., Kloeckner, J., Gettinger, T. R., & Nicol, G. E. (2022) · JMIR Research Protocols · doi:10.2196/39233 · Cited by 4
“Nationally, 18.4% of adults 65 years and older report symptoms of depression; 12% report subjective [4] cognitive decline [5,6].”
InfluentialSelf-citationSaunders, T. S., Protsiv, M., Jenkins, N. D., Solomon, A., Blennow, K., Ritchie, C. W., & Terrera, G. M. (2023) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2023.31 · Cited by 3
Subjective cognitive decline and cerebral-cognitive reserve in late age
Sidenkova, A. P., Calabrese, V., Tomasello, M., & Fritsch, T. (2023) · Translational Medicine of Aging · doi:10.1016/j.tma.2023.11.001 · Cited by 4
Amyloid-Negative, Neurodegeneration-Negative Amnestic Mild Cognitive Impairment
Cardoso, S., Guerreiro, M., Montalvo, A., Silva, D., Alves, L., & de Mendonça, A. (2024) · Journal of Alzheimer s Disease · doi:10.3233/jad-240621 · Cited by 3
Delvenne, A., Gobom, J., Reus, L. M., Dobričić, V., ten Kate, M., Schindler, S. E., Ramakers, I. H. G. B., Tijms, B. M., Vandenberghe, R. R., Schaeverbeke, J. M., et al. (2025) · Brain Communications · doi:10.1093/braincomms/fcaf253 · Cited by 3
“Cognitive impairments in SNAP may result from various comorbid non-Alzheimer’s disease pathologies, 67-69 leading to a distinct underlying pathology than in NC-SNAP.”
Self-citationUPDATE ON PREVENTION TRIALS IN ALZHEIMER’S DISEASE
Vellas, B. J. (2014) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2014.30 · Cited by 3
“Only 2% of stage 0 subjects progressed, whereas, 11% of stage 1 subjects, 26% of stage 2 subjects, 56% of stage 3 subjects, and 5% of SNAP subjects progressed (16).”
BackgroundCerebral lactate metabolism and memory: Implications for Alzheimer's disease
Harris, R. A. (2017) · Scholarship@Western (Western University) · Cited by 3
The Default Mode Network and Executive Function
Brown, C. (2017) · UKnowledge (University of Kentucky) · doi:10.13023/etd.2017.367 · Cited by 3
“Further, using autopsy confirmed cut-off values, both Aβ42 and the tau/Aβ42 ratio are predictive of future development of AD (139,141).”
BackgroundThe Ethics of Biomarker-Based Preclinical Diagnosis of Alzheimer’s Disease
Kurz, A., & Lautenschlager, N. T. (2018) · Neuromethods · doi:10.1007/978-1-4939-7674-4_17 · Cited by 3
PET Imaging of Amyloid and Tau in Alzheimer’s Disease
Okamura, N., & Harada, R. (2022) · Springer eBooks · doi:10.1007/978-981-16-7977-3_19 · Cited by 3
Rådestig, M. A., Skoog, J., Zetterberg, H., Skillbäck, T. B., Zettergren, A., Sterner, T. R., Fässberg, M. M., Sacuiu, S. F., Wærn, M., Wetterberg, H., et al. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-220452 · Cited by 3
“In previous research, it has been shown that cognitively normal individuals with underlying amyloid pathology are at greater risk to convert to mild cognitive impairment (MCI) or dementia [3].”
BackgroundIncidence and Risk Factors of Post‐Lumbar Puncture Headache in Patients With Cognitive Impairment
Wang, X. Y., Qiao, Y., Liang, Y., Han, J., Duan, H., Tang, Y., & Qin, Q. (2025) · Brain and Behavior · doi:10.1002/brb3.70597 · Cited by 2
Ritchie, M., Hussen, K., Langford, O., Navarro, C., Kotadiya, Z., Donohue, M., Aisen, P. S. S., Sperling, R. A., Grill, J. D., & Raman, R. (2025) · Alzheimer s Research & Therapy · doi:10.1186/s13195-025-01867-8 · Cited by 2
“…biomarker testing and learning results is not a barrier to participation [11, 12], these trials face novel challenges to recruitment and retention as they are typically longer in duration, have high rates of ineligibility, and require larger sample sizes to achieve sufficient power [13, 14].”
CSF proteomics and machine learning reveal distinct stages across the Alzheimer’s disease continuum
Rathore, S., Dammer, E. B., Shantaraman, A., Wu, F., Duong, D. M., Fox, E. J., Johnson, E. C. B., Lah, J. J., Initiative, A. D. N., Levey, A. I., et al. (2026) · Molecular Neurodegeneration · doi:10.1186/s13024-026-00983-9 · Cited by 2
Self-citationKang, D. W., Wang, S., Um, Y. H., Kim, N. Y., Lee, C. U., & Lim, H. K. (2022) · Journal of Alzheimer s Disease · doi:10.3233/jad-220427 · Cited by 2
“In preclinical AD patients, the rate of conversion to mild cognitive impairment (MCI) and dementia is five times higher than that of the control group without A (cid:2) [4].”
Al-Hammadi, N. J., Abouelyazid, M., Brown, D. C., Lalwani, P., Devos, H., Carr, D. B., & Babulal, G. M. (2025) · The Journals of Gerontology Series B · doi:10.1093/geronb/gbaf023 · Cited by 2
Amyloid is associated with accelerated atrophy in cognitively unimpaired individuals
Stephenson, H. G., Betthauser, T. J., Langhough, R. E., Jonaitis, E. M., Du, L., Hulle, C. V., Kollmorgen, G., Quijano‐Rubio, C., Chin, N. A., Okonkwo, O. C., et al. (2025) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.70089 · Cited by 2
"A Sinking Heart": Beliefs of Distress in the Punjabi Community
Ruprai, S. K. (2016) · UEL Research Repository (University of East London) · doi:10.15123/pub.5412 · Cited by 2
One step towards dementia prevention
Frisoni, G. B., & Jessen, F. (2018) · The Lancet Neurology · doi:10.1016/s1474-4422(18)30086-3 · Cited by 2
Effects of Mediterranean Diet on Endothelial Function
Merino, J., KONES, R. J., & Ros, E. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-812348-5.00025-8 · Cited by 2
Elevated tau PET signal depends on abnormal amyloid levels and is uncommon in unimpaired individuals
Gordon, B. A., & Tijms, B. M. (2019) · Brain · doi:10.1093/brain/awz278 · Cited by 2
A Note on Changing Approach to Diagnosis of Alzheimer’s Disease
Tartaglione, A., & Sette, M. D. (2014) · EMJ Neurology · doi:10.33590/emjneurol/10310003 · Cited by 2
A Practical Tool for the Detection of Limbic-type-memory Deficit: 5-Word-Test
Kayserili, G., Yıldırım, Z., Çilengiroğlu, Ö. V., & Yener, G. (2019) · Turkish Journal Of Neurology · doi:10.4274/tnd.2019.39269 · Cited by 2
Huang, S., Zhu, J., Shen, X., Xu, W., Ma, Y., Li, H., Dong, Q., Tan, L., & Yu, J. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200059 · Cited by 2
“In our data, about 21% of individuals were classified as SNAP, which was similar to other biomarker/imaging literatures on SNAP [8, 19, 20, 22].”
Biomarqueurs du liquide cérébrospinal
Leroy, M., Vaudran, L., Deramecourt, V., Pasquier, F., Chen, Y., Schraen‐Maschke, S., & Lebouvier, T. (2021) · Pratique Neurologique - FMC · doi:10.1016/j.praneu.2021.03.014 · Cited by 4
Pronko, P. S., Zimatkin, S. M., & Kuz'mich, A. B. (1994) · PubMed · Cited by 2
Commentary: Diagnostic Accuracy of Blood-Based Biomarker Panels: A Systematic Review
Bhagavati, S. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.895398 · Cited by 2
IDEAS becoming reality on the roadmap for biomarker validation in Alzheimer's disease
Frisoni, G. B., Alves, I. L., & Barkhof, F. (2019) · The Lancet Neurology · doi:10.1016/s1474-4422(19)30166-8 · Cited by 1
Guo, H.-F., Wu, Y., Li, J., & Pan, F. (2023) · World Journal of Psychiatry · doi:10.5498/wjp.v13.i11.872 · Cited by 1
Desai, Y., Karunakaran, D., Singh, J. M., Noronha, A. R., Poojary, G., Chettri, B., Shenoy, R. R., Nampoothiri, M., & Bojja, S. L. (2024) · Indian Journal of Pharmacology · doi:10.4103/ijp.ijp_761_23 · Cited by 1
“[2] Recent studies highlighted the significance of multidomain lifestyle modification including exercise, diet, and cognitive stimulation for AD prevention.”
Chun, M. Y., Park, Y. H., Kim, H. J., Na, D. L., Kim, J. P., Seo, S. W., & Jang, H. (2025) · Clinical Nuclear Medicine · doi:10.1097/rlu.0000000000005793 · Cited by 1
“4,13,14 15 – 20 These fi ndings indicate the potential differences between SNAP-CU and SNAP-MCI.”
Dubbelman, M. A., Elias, U., Palmer, P., Dafni‐Merom, A., Gazit, L., Udeogu, O. J., Wang, S. X., Papp, K. V., Amariglio, R. E., Arzy, S., et al. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251334781 · Cited by 1
Cerebrospinal Fluid Biomarkers of Alzheimer Disease
Васильевна, Н. К., Shpilyukova, Y. A., Шабалина, А. А., Fedotova, E. Y., & Illarioshkin, S. N. (2025) · Annals of Clinical and Experimental Neurology · doi:10.17816/acen.1185 · Cited by 1
Mallika, A. P., Jairani, P. S., Sivasankara, M. P., Menon, R. N., & Banerjee, M. (2025) · Neurogenetics · doi:10.1007/s10048-025-00834-7 · Cited by 1
“…dementias, a combination of factors such as socioeconomic status, genetic predisposition, educational background, environmental influences, and the presence of other health conditions (like midlife cardiovascular risk) can all contribute to a higher risk of cognitive decline later in life [ 7 , 8].”
Huang, X., Xu, Z., Fu, F., Song, J., Zeng, J., Huang, S., & Yue, F. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110849 · Cited by 1
Protective mutations associated with APOE in Alzheimer’s disease
Ma, Y., Li, Y., Wu, G., Liu, L., Tian, M., Han, X., Chen, X., Xuan, X., Zheng, T., Gao, X., et al. (2026) · Molecular Psychiatry · doi:10.1038/s41380-026-03496-5 · Cited by 1
“A β accumulation typically begins in individuals between 60 and 80 years old, reaching a stable level before the onset of symptoms, and subsequently transforms into MCI or AD [122 – 124].”
Biomarkers for Alzheimer's Disease and Potential Future Directions
Paracha, U. Z., Qadri, I., Hayat, K., & Hussain, T. (2013) · Cited by 1
A Fate Worse Than Death?: How Biomarkers for Alzheimer's Disease Could Affect End-of-Life Choices
Dresser, R. S. (2015) · Indiana Health Law Review · doi:10.18060/3911.0004 · Cited by 1
Hilgemberg, G. R., da Silva, A. J. D. O. K., Fermino, B. L., Diedrich, C., Benincá, S. C., Pinheiro, D. F., Ivanski, F., dos Santos, F. S., da Silva, W. C. F. N., Mazur, C. E., et al. (2018) · F1000Research · doi:10.12688/f1000research.13835.1
Mikuniya, Y., Kudo, R., Yamauchi, K., Kudo, N., Sasaki, A., Sawada, K., Jung, S., & Matsubara, A. (2021) · Nihon Bika Gakkai Kaishi (Japanese Journal of Rhinology) · doi:10.7248/jjrhi.60.509 · Cited by 1
Li, X., Ng, K. P., Ba, M., Rosa‐Neto, P., & Gauthier, S. G. (2017) · Mental health and illness worldwide · doi:10.1007/978-981-10-2414-6_6 · Cited by 1
Cognitive Aging and the Transition to Early Alzheimer’s Disease
Mormino, E. C., & Jagust, W. J. (2024) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780190917982.013.59 · Cited by 1
A Serious Game Prototype of Combined Cognitive Training for Alzheimer’s Patients
Yang, X. Q., Tang, M., & Ushaw, G. (2024) · IEEE Conference on Cybernetics and Intelligent Systems · doi:10.1109/cis-ram61939.2024.10673387 · Cited by 1
“We have explored 5 studies [2, 5, 6, 15, 16] that were conducted in the past three decades with over 300 participants for each.”
BackgroundRamsingh, N., Lin, H., Ouyang, Y., Ravona‐Springer, R., Livny, A., Soleimani, L., Bendlin, B. B., Matatov, A., Niv, T., Shamir, T., et al. (2025) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.70060 · Cited by 1
“Cerebrospinal fluid (CSF), blood and PET based AD‐related biomarkers [4, 5] and subjective cognitive impairment [6] are used to determine high risk individuals [7] and to classify pre-clinical AD.”
Riello, M., Moroni, M., Bovo, S., Ragni, F., Buganza, M., Giacopo, R. D., Chierici, M., Gios, L., Pardini, M., Massa, F., et al. (2025) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2025.1565006 · Cited by 1
“As the disease progresses, individuals with pathological evidence of AD, but cognitively normal, named “preclinical AD” patients (Morris et al., 2009; Vos et al., 2013), might suffer from cognitive decline that is detectable by sensitive neuropsychological measures (Albert et al., 2011).”
Neuropsychiatric Symptoms in Mild Cognitive Impairment as Risk Factors for Progression to Dementia
Martinez, D. A. P. (2016) · Journal of Neurology and Neuroscience · doi:10.21767/2171-6625.100001 · Cited by 1
Jellinger, K. A. (2015) · EMJ Neurology · doi:10.33590/emjneurol/10311025 · Cited by 1
Pan, L., Ou, Y., Tan, L., Tan, L., & Yu, J. (2021) · Brain Science Advances · doi:10.26599/bsa.2021.9050003 · Cited by 1
The Role of Polyphenols in the Treatment of Alzheimer's Disease: Narrative Review
Alattiya, R. H., Tarish, F. K., Hashim, L. L., & Hussain, S. A. (2021) · Al-Rafidain Journal of Medical Sciences · doi:10.54133/ajms.v1i.31 · Cited by 1
Sustainability in Microfinance Institutions
Pérez, I. G. (2019) · doi:10.6035/14102.2019.470663 · Cited by 1
Li, J., Song, J., John Suckling, A., Wang, Y., Zuo, C., Zhang, C. M., Gao, J., Song, Y., Xie, A., Tan, L., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-2744271/v1 · Cited by 1
BrainVAE: Exploring the role of white matter BOLD in preclinical Alzheimer’s disease classificationPreprint
Li, Y., Xu, L., Zuo, L., Chang, Y., Ding, Z., Anderson, A. W., Schilling, K. G., Gore, J. C., Gao, Y., & Initiative, T. A. D. N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.07.652697 · Cited by 1
Foloppe, D. A. (2017) · theses.fr (ABES) · doi:10.70675/ea5c564azcf19z4d1dzacdezb265118ff3a8 · Cited by 1
The course of mild cognitive impairment and the role of comorbidity
Hamel, R. E. G. (2015) · Research Publications (Maastricht University) · doi:10.26481/dis.20150703rh
Hohe Prävalenz und rasches Fortschreiten
Wolf, D. G. F. (2014) · InFo Neurologie + Psychiatrie · doi:10.1007/s15005-014-0805-7
Metadata
- Authors
- 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.
- Affiliations
- Maastricht University (NL)
- Washington University in St. Louis (US)
- Corresponding author
- Vos, Stephanie JB
- Fagan, Anne M
- ORCID
- Venue
- The Lancet Neurology
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 12
- Issue
- 10
- Pages
- 957-965
- ISSN
- 1474-4422 (ISSN-L)
- PMC
- PMC3904678
- OpenAlex
- W2096063777
- Cited by
- 564
- References
- 45
- Citations by year
- 2026: 20 · 2025: 37 · 2024: 30 · 2023: 17 · 2022: 40 · 2021: 39 · 2020: 45 · 2019: 54 · 2018: 63 · 2017: 54 · 2016: 53 · 2015: 52 · 2014: 52 · 2013: 7
- FWCI
- 38.74
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- The Lancet Neurology (publishedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion)
- Pure Amsterdam UMC (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- PubMed Central (acceptedVersion)
- Research Publications (Maastricht University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Mayo Clinic
- Center for Translational Molecular Medicine
- National Institute on Aging (P 50 AG05681, P50AG005681, P01AG003991, U19AG032438, P01-AG02676, P01AG026276)
- National Institute of Diabetes and Digestive and Kidney Diseases (K23DK094982)
- National Institute of Neurological Disorders and Stroke (P30NS057105)
- 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
- preclinical Alzheimer's disease, amyloid-beta 42, tau protein, cerebrospinal fluid biomarkers, cognitive decline, conversion to dementia, mortality, prevalence, cognitively normal elderly, Alzheimer's disease staging, community-dwelling older adults
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Apolipoproteins E, Brain, Female, Humans, Longitudinal Studies, Male, Middle Aged, Neuropsychological Tests, Peptide Fragments, Psychiatric Status Rating Scales, Severity of Illness Index, Prevalence, Survival Analysis, Amyloid beta-Peptides, tau Proteins, Disease Progression, Memory, Episodic, Prodromal Symptoms
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