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Detection and treatment of Alzheimer’s disease in its preclinical stage – Nature Aging


  • Knopman, D. S. et al. Alzheimer disease. Nat. Rev. Dis. Primers 7, 33 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Aisen, P. S. et al. On the path to 2025: understanding the Alzheimer’s disease continuum. Alzheimers Res. Ther. 9, 60 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Jack, C. R. Jr et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 12, 207–216 (2013).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Raskin, J., Cummings, J., Hardy, J., Schuh, K. & Dean, R. A. Neurobiology of Alzheimer’s disease: integrated molecular, physiological, anatomical, biomarker, and cognitive dimensions. Curr. Alzheimer Res. 12, 712–722 (2015).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Jack, C. R. Jr et al. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol. 9, 119–128 (2010).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bateman, R. J. et al. Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. N. Engl. J. Med. 367, 795–804 (2012).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Fortea, J. et al. Clinical and biomarker changes of Alzheimer’s disease in adults with Down syndrome: a cross-sectional study. Lancet 395, 1988–1997 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Dubois, B. et al. Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol. 13, 614–629 (2014).

    Article 
    PubMed 

    Google Scholar
     

  • Donohue, M. C. et al. Association between elevated brain amyloid and subsequent cognitive decline among cognitively normal persons. JAMA 317, 2305–2316 (2017).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ossenkoppele, R. et al. Amyloid and tau PET-positive cognitively unimpaired individuals are at high risk for future cognitive decline. Nat. Med. 28, 2381–2387 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Aisen, P. S., Jimenez-Maggiora, G. A., Rafii, M. S., Walter, S. & Raman, R. Early-stage Alzheimer disease: getting trial-ready. Nat. Rev. Neurol. 18, 389–399 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • US Department of Health and Human Services, Food and Drug Administration. Guidance for Industry: Early Alzheimer’s Disease: Developing Drugs for Treatment https://www.fda.gov/regulatory-information/search-fda-guidance-documents/alzheimers-disease-developing-drugs-treatment-guidance-industy (2018).

  • Rowe, C. C. et al. Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Neurobiol. Aging 31, 1275–1283 (2010).

    Article 
    PubMed 

    Google Scholar
     

  • Mintun, M. A. et al. [11C]PIB in a nondemented population: potential antecedent marker of Alzheimer disease. Neurology 67, 446–452 (2006).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Jack, C. R. Jr et al. 11C PiB and structural MRI provide complementary information in imaging of Alzheimer’s disease and amnestic mild cognitive impairment. Brain 131, 665–680 (2008).

    Article 
    PubMed 

    Google Scholar
     

  • De Meyer, G. et al. Diagnosis-independent Alzheimer disease biomarker signature in cognitively normal elderly people. Arch. Neurol. 67, 949–956 (2010).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Arriagada, P. V., Marzloff, K. & Hyman, B. T. Distribution of Alzheimer-type pathologic changes in nondemented elderly individuals matches the pattern in Alzheimer’s disease. Neurology 42, 1681–1688 (1992).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Morris, J. C. et al. Cerebral amyloid deposition and diffuse plaques in “normal” aging: evidence for presymptomatic and very mild Alzheimer’s disease. Neurology 46, 707–719 (1996).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Villemagne, V. L. et al. Aβ deposits in older non-demented individuals with cognitive decline are indicative of preclinical Alzheimer’s disease. Neuropsychologia 46, 1688–1697 (2008).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Stonnington, C. M. et al. Fibrillar amyloid correlates of preclinical cognitive decline. Alzheimers Dement. 10, e1–e8 (2014).

    Article 
    PubMed 

    Google Scholar
     

  • Moonis, M. et al. Familial Alzheimer disease: decreases in CSF Aβ42 levels precede cognitive decline. Neurology 65, 323–325 (2005).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Klunk, W. E. et al. Amyloid deposition begins in the striatum of presenilin-1 mutation carriers from two unrelated pedigrees. J. Neurosci. 27, 6174–6184 (2007).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ringman, J. M. et al. Biochemical markers in persons with preclinical familial Alzheimer disease. Neurology 71, 85–92 (2008).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Reiman, E. M. et al. Fibrillar amyloid-β burden in cognitively normal people at 3 levels of genetic risk for Alzheimer’s disease. Proc. Natl Acad. Sci. USA 106, 6820–6825 (2009).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Boerwinkle, A. H. et al. Comparison of amyloid burden in individuals with Down syndrome versus autosomal dominant Alzheimer’s disease: a cross-sectional study. Lancet Neurol. 22, 55–65 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Pike, K. E. et al. β-amyloid imaging and memory in non-demented individuals: evidence for preclinical Alzheimer’s disease. Brain 130, 2837–2844 (2007).

    Article 
    PubMed 

    Google Scholar
     

  • Wirth, M. et al. The effect of amyloid β on cognitive decline is modulated by neural integrity in cognitively normal elderly. Alzheimers Dement. 9, 687–698 (2013).

    Article 
    PubMed 

    Google Scholar
     

  • Mormino, E. C. et al. Synergistic effect of β-amyloid and neurodegeneration on cognitive decline in clinically normal individuals. JAMA Neurol. 71, 1379–1385 (2014).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lim, Y. Y. et al. Effect of amyloid on memory and non-memory decline from preclinical to clinical Alzheimer’s disease. Brain 137, 221–231 (2014).

    Article 
    PubMed 

    Google Scholar
     

  • Landau, S. M. et al. Amyloid deposition, hypometabolism, and longitudinal cognitive decline. Ann. Neurol. 72, 578–586 (2012).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Storandt, M., Mintun, M. A., Head, D. & Morris, J. C. Cognitive decline and brain volume loss as signatures of cerebral amyloid-β peptide deposition identified with Pittsburgh compound B: cognitive decline associated with Aβ deposition. Arch. Neurol. 66, 1476–1481 (2009).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Pietrzak, R. H. et al. Trajectories of memory decline in preclinical Alzheimer’s disease: results from the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing. Neurobiol. Aging 36, 1231–1238 (2015).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Jicha, G. A. et al. Preclinical AD Workgroup staging: pathological correlates and potential challenges. Neurobiol. Aging 33, 622.e1–622.e16 (2012).

    Article 
    PubMed 

    Google Scholar
     

  • Vos, S. J. et al. Preclinical Alzheimer’s disease and its outcome: a longitudinal cohort study. Lancet Neurol. 12, 957–965 (2013).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Knopman, D. S. et al. Short-term clinical outcomes for stages of NIA-AA preclinical Alzheimer disease. Neurology 78, 1576–1582 (2012).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Toledo, J. B. et al. CSF Apo-E levels associate with cognitive decline and MRI changes. Acta Neuropathol. 127, 621–632 (2014).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ryman, D. C. et al. Symptom onset in autosomal dominant Alzheimer disease: a systematic review and meta-analysis. Neurology 83, 253–260 (2014).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • de Graaf, G., Buckley, F. & Skotko, B. G. Estimation of the number of people with Down syndrome in the United States. Genet. Med. 19, 439–447 (2017).

    Article 
    PubMed 

    Google Scholar
     

  • Rafii, M. S., Wishnek, H. & Brewer, J. B. The Down Syndrome Biomarker Initiative (DSBI) pilot: proof of concept for deep phenotyping of Alzheimer’s disease biomarkers in Down syndrome. Front. Behav. Neurosci. 9, 239 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Neale, N., Padilla, C., Fonseca, L. M., Holland, T. & Zaman, S. Neuroimaging and other modalities to assess Alzheimer’s disease in Down syndrome. NeuroImage Clin. 17, 263–271 (2018).

    Article 
    PubMed 

    Google Scholar
     

  • Handen, B. L., Cohen, A. D. & Channamalappa, U. Imaging brain amyloid in nondemented young adults with Down syndrome using Pittsburgh compound B. Alzheimers Dement. 8, 496–501 (2012).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Annus, T., Wilson, L. R. & Hong, Y. T. The pattern of amyloid accumulation in the brains of adults with Down syndrome. Alzheimers Dement. 12, 538–545 (2016).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lao, P. J., Betthauser, T. J. & Hillmer, A. T. The effects of normal aging on amyloid-β deposition in nondemented adults with Down syndrome as imaged by carbon 11-labeled Pittsburgh compound B. Alzheimers Dement. 12, 380–390 (2016).

    Article 
    PubMed 

    Google Scholar
     

  • Fortea, J. et al. Plasma and CSF biomarkers for the diagnosis of Alzheimer’s disease in adults with Down syndrome: a cross-sectional study. Lancet Neurol. 17, 860–869 (2018).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Fleisher, A. S., Chen, K. & Quiroz, Y. T. Associations between biomarkers and age in the presenilin 1 E280A autosomal dominant Alzheimer disease kindred: a cross-sectional study. JAMA Neurol. 72, 316–324 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Rafii, M. S. et al. A randomized, double-blind, placebo-controlled, phase II study of oral ELND005 (scyllo-inositol) in young adults with Down syndrome without dementia. J. Alzheimers Dis. 58, 401–411 (2017).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Rafii, M. S. et al. Safety, tolerability, and immunogenicity of the ACI-24 vaccine in adults with Down syndrome: a phase 1b randomized clinical trial. JAMA Neurol. 79, 565–574 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Rafii, M. S. Alzheimer’s disease in Down syndrome: progress in the design and conduct of drug prevention trials. CNS Drugs 34, 785–794 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Jack, C. R. Jr et al. A/T/N: an unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology 87, 539–547 (2016).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Knopman, D. S. et al. The National Institute on Aging and the Alzheimer’s Association Research Framework for Alzheimer’s disease: perspectives from the Research Roundtable. Alzheimers Dement. 14, 563–575 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Strikwerda-Brown, C. et al. Association of elevated amyloid and tau positron emission tomography signal with near-term development of Alzheimer disease symptoms in older adults without cognitive impairment. JAMA Neurol. 79, 975–985 (2022).

  • van der Flier, W. M. & Scheltens, P. The ATN framework—moving preclinical Alzheimer disease to clinical relevance. JAMA Neurol. 79, 968–970 (2022).

    Article 
    PubMed 

    Google Scholar
     

  • Soldan, A. et al. ATN profiles among cognitively normal individuals and longitudinal cognitive outcomes. Neurology 92, e1567–e1579 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Vos, S. J. B. & Duara, R. The prognostic value of ATN Alzheimer biomarker profiles in cognitively normal individuals. Neurology 92, 643–644 (2019).

    Article 
    PubMed 

    Google Scholar
     

  • Delmotte, K. et al. Prognostic value of amyloid/tau/neurodegeneration (ATN) classification based on diagnostic cerebrospinal fluid samples for Alzheimer’s disease. Alzheimers Res. Ther. 13, 84 (2021).

    Article 
    CAS 

    Google Scholar
     

  • Allegri, R. F. et al. Prognostic value of ATN Alzheimer biomarkers: 60-month follow-up results from the Argentine Alzheimer’s Disease Neuroimaging Initiative. Alzheimers Dement. 12, e12026 (2020).


    Google Scholar
     

  • Selvackadunco, S. et al. Comparison of clinical and neuropathological diagnoses of neurodegenerative diseases in two centres from the Brains for Dementia Research (BDR) cohort. J. Neural Transm. 126, 327–337 (2019).

    Article 
    PubMed 

    Google Scholar
     

  • Morris, J. C. et al. Pittsburgh compound B imaging and prediction of progression from cognitive normality to symptomatic Alzheimer disease. Arch. Neurol. 66, 1469–1475 (2009).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Vemuri, P. et al. MRI and CSF biomarkers in normal, MCI, and AD subjects: predicting future clinical change. Neurology 73, 294–301 (2009).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Fagan, A. M. et al. Decreased cerebrospinal fluid Aβ42 correlates with brain atrophy in cognitively normal elderly. Ann. Neurol. 65, 176–183 (2009).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lowe, V. J. et al. Association of hypometabolism and amyloid levels in aging, normal subjects. Neurology 82, 1959–1967 (2014).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Nettiksimmons, J. et al. Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline. Neurobiol. Aging 31, 1419–1428 (2010).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Pankratz, V. S. et al. Predicting the risk of mild cognitive impairment in the Mayo Clinic Study of Aging. Neurology 84, 1433–1442 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Stomrud, E. et al. Correlation of longitudinal cerebrospinal fluid biomarkers with cognitive decline in healthy older adults. Arch. Neurol. 67, 217–223 (2010).

    Article 
    PubMed 

    Google Scholar
     

  • Sutphen, C. L. et al. Longitudinal cerebrospinal fluid biomarker changes in preclinical Alzheimer disease during middle age. JAMA Neurol. 72, 1029–1042 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Dumurgier, J. et al. Alzheimer’s disease biomarkers and future decline in cognitive normal older adults. J. Alzheimers Dis. 60, 1451–1459 (2017).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Farrell, M. E. et al. Defining the lowest threshold for amyloid-PET to predict future cognitive decline and amyloid accumulation. Neurology 96, e619–e631 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Campbell, M. R. et al. P-tau/Aβ42 and Aβ42/40 ratios in CSF are equally predictive of amyloid PET status. Alzheimers Dement. 13, e12190 (2021).


    Google Scholar
     

  • Schindler, S. E. et al. Predicting symptom onset in sporadic Alzheimer disease with amyloid PET. Neurology 97, e1823–e1834 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bourgeat, P. et al. β-amyloid burden in the temporal neocortex is related to hippocampal atrophy in elderly subjects without dementia. Neurology 74, 121–127 (2010).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Oh, H. et al. β-amyloid affects frontal and posterior brain networks in normal aging. NeuroImage 54, 1887–1895 (2011).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Dickerson, B. C. et al. The cortical signature of Alzheimer’s disease: regionally specific cortical thinning relates to symptom severity in very mild to mild AD dementia and is detectable in asymptomatic amyloid-positive individuals. Cereb. Cortex 19, 497–510 (2009).

    Article 

    Google Scholar
     

  • Sperling, R. A. et al. Amyloid deposition is associated with impaired default network function in older persons without dementia. Neuron 63, 178–188 (2009).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Hedden, T. et al. Disruption of functional connectivity in clinically normal older adults harboring amyloid burden. J. Neurosci. 29, 12686–12694 (2009).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Mormino, E. C. et al. Relationships between β-amyloid and functional connectivity in different components of the default mode network in aging. Cereb. Cortex 21, 2399–2407 (2011).

  • Rentz, D. M. et al. Face–name associative memory performance is related to amyloid burden in normal elderly. Neuropsychologia 49, 2776–2783 (2011).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Chetelat, G. et al. Independent contribution of temporal β-amyloid deposition to memory decline in the pre-dementia phase of Alzheimer’s disease. Brain 134, 798–807 (2011).

    Article 
    PubMed 

    Google Scholar
     

  • Nakamura, A. et al. High performance plasma amyloid-β biomarkers for Alzheimer’s disease. Nature 554, 249–254 (2018).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Schindler, S. E. et al. High-precision plasma β-amyloid 42/40 predicts current and future brain amyloidosis. Neurology 93, e1647–e1659 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Li, Y. et al. Validation of plasma amyloid-β 42/40 for detecting Alzheimer disease amyloid plaques. Neurology 98, e688–e699 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Fandos, N. et al. Plasma amyloid β 42/40 ratios as biomarkers for amyloid β cerebral deposition in cognitively normal individuals. Alzheimers Dement. 8, 179–187 (2017).


    Google Scholar
     

  • Mattsson, N., Cullen, N. C., Andreasson, U., Zetterberg, H. & Blennow, K. Association between longitudinal plasma neurofilament light and neurodegeneration in patients with Alzheimer disease. JAMA Neurol. 76, 791–799 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Mielke, M. M. et al. Plasma phospho-tau181 increases with Alzheimer’s disease clinical severity and is associated with tau- and amyloid-positron emission tomography. Alzheimers Dement. 14, 989–997 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Janelidze, S. et al. Plasma p-tau181 in Alzheimer’s disease: relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer’s dementia. Nat. Med. 26, 379–386 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Palmqvist, S. et al. Performance of fully automated plasma assays as screening tests for Alzheimer disease-related β-amyloid status. JAMA Neurol. 76, 1060–1069 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Cullen, N. C. et al. Plasma biomarkers of Alzheimer’s disease improve prediction of cognitive decline in cognitively unimpaired elderly populations. Nat. Commun. 12, 3555 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ossenkoppele, R. et al. Accuracy of tau positron emission tomography as a prognostic marker in preclinical and prodromal Alzheimer disease: a head-to-head comparison against amyloid positron emission tomography and magnetic resonance imaging. JAMA Neurol. 78, 961–971 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Rafii, M. S. et al. The AHEAD 3-45 Study: design of a prevention trial for Alzheimer’s disease. Alzheimers Dement. https://doi.org/10.1002/alz.12748 (2022).

  • Johnson, K. A. et al. Tau positron emission tomographic imaging in aging and early Alzheimer disease. Ann. Neurol. 79, 110–119 (2016).

    Article 
    PubMed 

    Google Scholar
     

  • Insel, P. S. et al. Tau positron emission tomography in preclinical Alzheimer’s disease. Brain 146, 700–711 (2023).

    Article 
    PubMed 

    Google Scholar
     

  • Mattsson-Carlgren, N. et al. Prediction of longitudinal cognitive decline in preclinical Alzheimer disease using plasma biomarkers. JAMA Neurol. 80, 360–369 (2023).

  • Mosconi, L. et al. Hippocampal hypometabolism predicts cognitive decline from normal aging. Neurobiol. Aging 29, 676–692 (2008).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Kennedy, A. M. et al. Deficits in cerebral glucose metabolism demonstrated by positron emission tomography in individuals at risk of familial Alzheimer’s disease. Neurosci. Lett. 186, 17–20 (1995).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • de Leon, M. J. et al. Prediction of cognitive decline in normal elderly subjects with 2-[18F]fluoro-2-deoxy-d-glucose/positron-emission tomography (FDG/PET). Proc. Natl Acad. Sci. USA 98, 10966–10971 (2001).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Jagust, W. J. et al. Brain imaging evidence of preclinical Alzheimer’s disease in normal aging. Ann. Neurol. 59, 673–681 (2006).

    Article 
    PubMed 

    Google Scholar
     

  • Serrano, M. E., Kim, E., Petrinovic, M. M., Turkheimer, F. & Cash, D. Imaging synaptic density: the next holy grail of neuroscience? Front. Neurosci. 16, 796129 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Mecca, A. P. et al. In vivo measurement of widespread synaptic loss in Alzheimer’s disease with SV2A PET. Alzheimers Dement. 16, 974–982 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Arvidsson Rådestig, M. et al. Cerebrospinal fluid biomarkers of axonal and synaptic degeneration in a population-based sample. Alzheimers Res. Ther. 15, 44 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zetterberg, H. et al. Association of cerebrospinal fluid neurofilament light concentration with Alzheimer disease progression. JAMA Neurol. 73, 60–67 (2016).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ferreira, P. C. L. et al. Plasma biomarkers identify older adults at risk of Alzheimer’s disease and related dementias in a real-world population-based cohort. Alzheimers Dement. https://doi.org/10.1002/alz.12986 (2023).

  • Pettigrew, C. et al. Progressive medial temporal lobe atrophy during preclinical Alzheimer’s disease. NeuroImage Clin. 16, 439–446 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Pettigrew, C. et al. Cortical thickness in relation to clinical symptom onset in preclinical AD. NeuroImage Clin. 12, 116–122 (2016).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Mueller, S. G. et al. Hippocampal atrophy patterns in mild cognitive impairment and Alzheimer’s disease. Hum. Brain Mapp. 31, 1339–1347 (2010).


    Google Scholar
     

  • McRae-McKee, K. et al. Combining hippocampal volume metrics to better understand Alzheimer’s disease progression in at-risk individuals. Sci. Rep. 9, 7499 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Elias, M. F. et al. The preclinical phase of Alzheimer disease: a 22-year prospective study of the Framingham Cohort. Arch. Neurol. 57, 808–813 (2000).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Saxton, J. et al. Preclinical Alzheimer disease: neuropsychological test performance 1.5 to 8 years prior to onset. Neurology 63, 2341–2347 (2004).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Donohue, M. C. et al. The preclinical Alzheimer cognitive composite: measuring amyloid-related decline. JAMA Neurol. 71, 961–970 (2014).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bransby, L. et al. Sensitivity of a Preclinical Alzheimer’s Cognitive Composite (PACC) to amyloid β load in preclinical Alzheimer’s disease. J. Clin. Exp. Neuropsychol. 41, 591–600 (2019).

    Article 
    PubMed 

    Google Scholar
     

  • Papp, K. V. et al. Sensitivity of the Preclinical Alzheimer’s Cognitive Composite (PACC), PACC5, and Repeatable Battery for Neuropsychological Status (RBANS) to amyloid status in preclinical Alzheimer’s disease—Atabecestat Phase 2b/3 EARLY Clinical Trial. J. Prev. Alzheimers Dis. 9, 255–261 (2022).

    CAS 
    PubMed 

    Google Scholar
     

  • Ayutyanont, N. et al. The Alzheimer’s Prevention Initiative Composite Cognitive Test score: sample size estimates for the evaluation of preclinical Alzheimer’s disease treatments in presenilin 1 E280A mutation carriers. J. Clin. Psychiatry 75, 652–660 (2014).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Langbaum, J. B. et al. The Alzheimer’s Prevention Initiative Composite Cognitive Test: a practical measure for tracking cognitive decline in preclinical Alzheimer’s disease. Alzheimers Res. Ther. 12, 66 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Amariglio, R. E. et al. Tracking early decline in cognitive function in older individuals at risk for Alzheimer disease dementia: the Alzheimer’s Disease Cooperative Study Cognitive Function Instrument. JAMA Neurol. 72, 446–454 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Li, C. et al. The utility of the Cognitive Function Instrument (CFI) to detect cognitive decline in non-demented older adults. J. Alzheimers Dis. 60, 427–437 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Galasko, D. et al. ADCS Prevention Instrument Project: assessment of instrumental activities of daily living for community-dwelling elderly individuals in dementia prevention clinical trials. Alzheimer Dis. Assoc. Disord. 20, S152–S169 (2006).

    Article 
    PubMed 

    Google Scholar
     

  • Marshall, G. A. et al. Measuring instrumental activities of daily living in non-demented elderly: a comparison of the new performance-based Harvard Automated Phone Task with other functional assessments. Alzheimers Res. Ther. 11, 4 (2019).

    Article 

    Google Scholar
     

  • Weintraub, S. et al. Measuring cognition and function in the preclinical stage of Alzheimer’s disease. Alzheimers Dement. 4, 64–75 (2018).

    Article 

    Google Scholar
     

  • Barnes, D. E. & Yaffe, K. The projected effect of risk factor reduction on Alzheimer’s disease prevalence. Lancet Neurol. 10, 819–828 (2011).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ding, J. et al. Antihypertensive medications and risk for incident dementia and Alzheimer’s disease: a meta-analysis of individual participant data from prospective cohort studies. Lancet Neurol. 19, 61–70 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Marinelli, J. P. et al. Association between hearing loss and development of dementia using formal behavioural audiometric testing within the Mayo Clinic Study of Aging (MCSA): a prospective population-based study. Lancet Healthy Longev. 3, e817–e824 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Middleton, L. E., Barnes, D. E., Lui, L. Y. & Yaffe, K. Physical activity over the life course and its association with cognitive performance and impairment in old age. J. Am. Geriatr. Soc. 58, 1322–1326 (2010).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Yiannopoulou, K. G., Anastasiou, A. I., Zachariou, V. & Pelidou, S. H. Reasons for failed trials of disease-modifying treatments for Alzheimer disease and their contribution in recent research. Biomedicines 7, 97 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Arndt, J. W. et al. Structural and kinetic basis for the selectivity of aducanumab for aggregated forms of amyloid-β. Sci. Rep. 8, 6412 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ferrero, J. et al. First-in-human, double-blind, placebo-controlled, single-dose escalation study of aducanumab (BIIB037) in mild-to-moderate Alzheimer’s disease. Alzheimers Dement. 2, 169–176 (2016).

    Article 

    Google Scholar
     

  • Sevigny, J. et al. The antibody aducanumab reduces Aβ plaques in Alzheimer’s disease. Nature 537, 50–56 (2016).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Budd Haeberlein, S. et al. Two randomized phase 3 studies of aducanumab in early Alzheimer’s disease. J. Prev. Alzheimers Dis. 9, 197–210 (2022).

    CAS 
    PubMed 

    Google Scholar
     

  • Ostrowitzki, S. et al. Mechanism of amyloid removal in patients with Alzheimer disease treated with gantenerumab. Arch. Neurol. 69, 198–207 (2012).

    Article 
    PubMed 

    Google Scholar
     

  • Klein, G. et al. Gantenerumab reduces amyloid-β plaques in patients with prodromal to moderate Alzheimer’s disease: a PET substudy interim analysis. Alzheimers Res. Ther. 11, 101 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Doody, R. Clinical Trial in Alzheimer’s Disease (CTAD) meeting, November 29 (2022).

  • Salloway, S. et al. A trial of gantenerumab or solanezumab in dominantly inherited Alzheimer’s disease. Nat. Med. 27, 1187–1196 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lowe, S. L. et al. Donanemab (LY3002813) phase 1b study in Alzheimer’s disease: rapid and sustained reduction of brain amyloid measured by florbetapir F18 imaging. J. Prev. Alzheimers Dis. 8, 414–424 (2021).

    CAS 
    PubMed 

    Google Scholar
     

  • Mintun, M. A. et al. Donanemab in early Alzheimer’s disease. N. Engl. J. Med. 384, 1691–1704 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Swanson, C. J. et al. A randomized, double-blind, phase 2b proof-of-concept clinical trial in early Alzheimer’s disease with lecanemab, an anti-Aβ protofibril antibody. Alzheimers Res. Ther. 13, 80 (2021).

    Article 
    CAS 

    Google Scholar
     

  • van Dyck, C. H. et al. Lecanemab in early Alzheimer’s disease. N. Engl. J. Med. 388, 9–21 (2023).

    Article 
    PubMed 

    Google Scholar
     

  • Sperling, R. A. et al. Amyloid-related imaging abnormalities in amyloid-modifying therapeutic trials: recommendations from the Alzheimer’s Association Research Roundtable Workgroup. Alzheimers Dement. 7, 367–385 (2011).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Barakos, J. et al. Detection and management of amyloid-related imaging abnormalities in patients with Alzheimer’s disease treated with anti-amyloid β therapy. J. Prev. Alzheimers Dis. 9, 211–220 (2022).

    CAS 
    PubMed 

    Google Scholar
     

  • Piazza, F. et al. Anti-amyloid β autoantibodies in cerebral amyloid angiopathy-related inflammation: implications for amyloid-modifying therapies. Ann. Neurol. 73, 449–458 (2013).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Salloway, S. et al. Amyloid-related imaging abnormalities in 2 phase 3 studies evaluating aducanumab in patients with early Alzheimer disease. JAMA Neurol. 79, 13–21 (2022).

    Article 
    PubMed 

    Google Scholar
     

  • Doody, R. S. et al. Phase 3 trials of solanezumab for mild-to-moderate Alzheimer’s disease. N. Engl. J. Med. 370, 311–321 (2014).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Honig, L. S. et al. Trial of solanezumab for mild dementia due to Alzheimer’s disease. N. Engl. J. Med. 378, 321–330 (2018).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Lilly. Lilly provides update on A4 study of solanezumab for preclinical Alzheimer’s disease. investory.lilly.com, https://investor.lilly.com/news-releases/news-release-details/lilly-provides-update-a4-study-solanezumab-preclinical#:~:text=INDIANAPOLIS%2C%20March%208%2C%202023%20%2FPRNewswire%2F%20–%20Eli%20Lilly,known%20as%20the%20preclinical%20stage%20of%20AD%201 (8 March 2023).

  • Vassar, R. et al. β-secretase cleavage of Alzheimer’s amyloid precursor protein by the transmembrane aspartic protease BACE. Science 286, 735–741 (1999).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Jonsson, T. et al. A mutation in APP protects against Alzheimer’s disease and age-related cognitive decline. Nature 488, 96–99 (2012).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Egan, M. F. et al. Randomized trial of verubecestat for prodromal Alzheimer’s disease. N. Engl. J. Med. 380, 1408–1420 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Henley, D. et al. Preliminary results of a trial of atabecestat in preclinical Alzheimer’s disease. N. Engl. J. Med. 380, 1483–1485 (2019).

    Article 
    PubMed 

    Google Scholar
     

  • Wessels, A. M. et al. Efficacy and safety of lanabecestat for treatment of early and mild Alzheimer disease: the AMARANTH and DAYBREAK-ALZ randomized clinical trials. JAMA Neurol. 77, 199–209 (2019).

    Article 
    PubMed Central 

    Google Scholar
     

  • Sperling, R. et al. Findings of efficacy, safety, and biomarker outcomes of atabecestat in preclinical Alzheimer disease: a truncated randomized phase 2b/3 clinical trial. JAMA Neurol. 78, 293–301 (2021).

    Article 
    PubMed 

    Google Scholar
     

  • McDade, E. et al. The case for low-level BACE1 inhibition for the prevention of Alzheimer disease. Nat. Rev. Neurol. 17, 703–714 (2021).

    Article 
    PubMed 

    Google Scholar
     

  • Congdon, E. E. & Sigurdsson, E. M. Tau-targeting therapies for Alzheimer disease. Nat. Rev. Neurol. 14, 399–415 (2018).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Langbaum, J. B. et al. Recommendations to address key recruitment challenges of Alzheimer’s disease clinical trials. Alzheimers Dement. 19, 696–707 (2023).

    Article 
    PubMed 

    Google Scholar
     

  • Indorewalla, K. K., O’Connor, M. K., Budson, A. E., Guess DiTerlizzi, C. & Jackson, J. Modifiable barriers for recruitment and retention of older adults participants from underrepresented minorities in Alzheimer’s disease research. J. Alzheimers Dis. 80, 927–940 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Aisen, P. S. et al. The Trial-Ready Cohort for Preclinical/Prodromal Alzheimer’s Disease (TRC-PAD) project: an overview. J. Prev. Alzheimer’s Dis. 7, 208–212 (2020).

    CAS 

    Google Scholar
     

  • Aisen, P. S. et al. The Trial-Ready Cohort for Preclinical/Prodromal Alzheimer’s Disease (TRC-PAD) project: an overview. J. Prev. Alzheimers Dis. 7, 208–212 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     



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