Age-specific and sex-specific prevalence of cerebral β-amyloidosis, tauopathy, and neurodegeneration in cognitively unimpaired individuals aged 50–95 years: a cross-sectional study
Open accessAbstract
Background A new classification for biomarkers in Alzheimer's disease and cognitive ageing research is based on grouping the markers into three categories: amyloid deposition (A), tauopathy (T), and neurodegeneration or neuronal injury (N). Dichotomising these biomarkers as normal or abnormal results in eight possible profiles. We determined the clinical characteristics and prevalence of each ATN profile in cognitively unimpaired individuals aged 50 years and older. Methods All participants were in the Mayo Clinic Study of Aging, a population-based study that uses a medical records linkage system to enumerate all individuals aged 50-89 years in Olmsted County, MN, USA. Potential participants are randomly selected, stratified by age and sex, and invited to participate in cognitive assessments; individuals without medical contraindications are invited to participate in brain imaging studies. Participants who were judged clinically as having no cognitive impairment and underwent multimodality imaging between Oct 11, 2006, and Oct 5, 2016, were included in the current study. Participants were classified as having normal (A-) or abnormal (A+) amyloid using amyloid PET, normal (T-) or abnormal (T+) tau using tau PET, and normal (N-) or abnormal (N+) neurodegeneration or neuronal injury using cortical thickness assessed by MRI. We used the cutoff points of standard uptake value ratio (SUVR) 1·42 (centiloid 19) for amyloid PET, 1·23 SUVR for tau PET, and 2·67 mm for MRI cortical thickness. Age-specific and sex-specific prevalences of the eight groups were determined using multinomial models combining data from 435 individuals with amyloid PET, tau PET, and MRI assessments, and 1113 individuals who underwent amyloid PET and MRI, but not tau PET imaging. Findings The numbers of participants in each profile group were 165 A-T-N-, 35 A-T+N-, 63 A-T-N+, 19 A-T+N+, 44 A+T-N-, 25 A+T+N-, 35 A+T-N+, and 49 A+T+N+. Age differed by ATN group (p<0·0001), ranging from a median 58 years (IQR 55-64) in A-T-N- and 57 years (54-64) in A-T+N- to a median 80 years (75-84) in A+T-N+ and 79 years (73-87) in A+T+N+. The number of APOE ε4 carriers differed by ATN group (p=0·04), with carriers roughly twice as frequent in each A+ group versus the corresponding A- group. White matter hyperintensity volume (p<0·0001) and cognitive performance (p<0·0001) also differed by ATN group. Tau PET and neurodegeneration biomarkers were discordant in most individuals who would be categorised as stage 2 or 3 preclinical Alzheimer's disease (A+T+N-, A+T-N+, and A+T+N+; 86% at age 65 years and 51% at age 80 years) or with suspected non-Alzheimer's pathophysiology (A-T+N-, A-T-N+, and A-T+N+; 92% at age 65 years and 78% at age 80 years). From age 50 years, A-T-N- prevalence declined and A+T+N+ and A-T+N+ prevalence increased. In both men and women, A-T-N- was the most prevalent until age late 70s. After about age 80 years, A+T+N+ was most prevalent. By age 85 years, more than 90% of men and women had one or more biomarker abnormalities. Interpretation Biomarkers of fibrillar tau deposition can be included with those of β-amyloidosis and neurodegeneration or neuronal injury to more fully characterise the heterogeneous pathological profiles in the population. Both amyloid- dependent and amyloid-independent pathological profiles can be identified in the cognitively unimpaired population. The prevalence of each ATN group changed substantially with age, with progression towards more biomarker abnormalities among individuals who remained cognitively unimpaired. Funding National Institute on Aging (part of the US National Institutes of Health), the Alexander Family Professorship of Alzheimer's Disease Research, the Mayo Clinic, and the GHR Foundation.
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?
Up to 60% of CU individuals over age 80 years have AD neuropathologic changes at autopsy or by biomarkers.
“Up to 60% of CU individuals over age 80 years have AD neuropathologic changes at autopsy or by biomarkers [60,152,212–214].”
From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [152]
The Results and Discussion report that the A+T+N+ biomarker profile becomes the most prevalent profile among cognitively normal individuals after about age 80. However, our copy does not give a 60% prevalence for AD changes in that age group; the Findings’ figure of over 90% at age 85 includes any biomarker abnormality, including non-AD profiles. This study assessed imaging biomarkers, not autopsy findings. (LLM, conf=0.84)
Experimental — accuracy not yet measuredA+T−(N)+ represents evidence of comorbidity, that is, A+T− represents Alzheimer's pathologic change while in the A+T− context, (N)+ represents evidence of non-AD neurodegeneration/neuronal injury.
“We believe that A+T−(N)+ represents evidence of comorbidity, that is, A+T− represents Alzheimer’s pathologic change while in the A+T− context, (N) + represents evidence of non-AD neurodegeneration/neuronal injury [152] and thus A+T−(N)− and A+T−(N)+ indicate meaningfully different pathologic states [153].”
From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [152]
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
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-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-citationJack, C. R., Knopman, D. S., Jagust, W. J., Petersen, R. C., Weiner, M. W., Aisen, P. S., Shaw, L. M., Vemuri, P., Wiste, H. J., Weigand, S. D., et al. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(12)70291-0 · Cited by 4,396 · see citing works
Self-citationAdvancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria
Dubois, B., Feldman, H. H., Jacova, C., Hampel, H., Molinuevo, J. L., Blennow, K., DeKosky, S. T., Gauthier, S., Selkoe, D., Bateman, R., et al. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70090-0 · Cited by 3,321 · 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-citationJack, C. R., Albert, M. S., Knopman, D. S., McKhann, G. M., Sperling, R. A., Carrillo, M. C., Thies, B., & Phelps, C. H. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.004 · Cited by 2,042 · 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-citationPrimary age-related tauopathy (PART): a common pathology associated with human aging
Crary, J. F., Trojanowski, J. Q., Schneider, J. A., Abisambra, J. F., Abner, E. L., Alafuzoff, I., Arnold, S. E., Attems, J., Beach, T. G., Bigio, E. H., et al. (2014) · Acta Neuropathologica · doi:10.1007/s00401-014-1349-0 · Cited by 1,467 · see citing works
Self-citationThe Centiloid Project: standardizing quantitative amyloid plaque estimation by PET
Klunk, W. E., Koeppe, R. A., Price, J. C., Benzinger, T. L., Devous, M. D., Jagust, W. J., Johnson, K. A., Mathis, C. A., Minhas, D., Pontecorvo, M. J., et al. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2014.07.003 · Cited by 1,348 · see citing works
CSF markers for incipient Alzheimer's disease
Blennow, K., & Hampel, H. (2003) · The Lancet Neurology · doi:10.1016/s1474-4422(03)00530-1 · Cited by 1,291 · see citing works
PET Imaging of Tau Deposition in the Aging Human Brain
Schöll, M., Lockhart, S. N., Schonhaut, D. R., O’Neil, J. P., Janabi, M., Ossenkoppele, R., Baker, S. L., Vogel, J. W., Faria, J., Schwimmer, H. D., et al. (2016) · Neuron · doi:10.1016/j.neuron.2016.01.028 · Cited by 1,214 · see citing works
Tau positron emission tomographic imaging in aging and early <scp>A</scp> lzheimer disease
Johnson, K. A., Schultz, A., Betensky, R. A., Becker, J. A., Sepulcre, J., Rentz, D., Mormino, E., Chhatwal, J., Amariglio, R., Papp, K., et al. (2016) · Annals of Neurology · doi:10.1002/ana.24546 · Cited by 986 · 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-citationTau and Aβ imaging, CSF measures, and cognition in Alzheimer’s disease
Brier, M. R., Gordon, B., Friedrichsen, K., McCarthy, J., Stern, A., Christensen, J., Owen, C., Aldea, P., Su, Y., Hassenstab, J., et al. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aaf2362 · Cited by 734 · see citing works
Sauver, J. L. S., Grossardt, B. R., Leibson, C. L., Yawn, B. P., Melton, L. J., & Rocca, W. A. (2012) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2011.11.009 · Cited by 652 · see citing works
Self-citationMarquié, M., Normandin, M. D., Vanderburg, C. R., Costantino, I. M., Bien, E. A., Rycyna, L. G., Klunk, W. E., Mathis, C. A., Ikonomovic, M. D., Debnath, M. L., et al. (2015) · Annals of Neurology · doi:10.1002/ana.24517 · Cited by 615 · see citing works
Jack, C. R., Knopman, D. S., Weigand, S. D., Wiste, H. J., Vemuri, P., Lowe, V., Kantarci, K., Gunter, J. L., Senjem, M. L., Ivnik, R. J., et al. (2012) · Annals of Neurology · doi:10.1002/ana.22628 · Cited by 602 · see citing works
Self-citationPreclinical 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
Head size, age and gender adjustment in MRI studies: a necessary nuisance?
Barnes, J., Ridgway, G. R., Bartlett, J. W., Henley, S. M. D., Lehmann, M., Hobbs, N. Z., Clarkson, M. J., MacManus, D. G., Sebastien Ourselin, A., & Fox, N. C. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.06.025 · Cited by 513 · see citing works
Tau imaging: early progress and future directions
Villemagne, V. L., Fodero-Tavoletti, M. T., Masters, C. L., & Rowe, C. C. (2015) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70252-2 · Cited by 501 · see citing works
An autoradiographic evaluation of AV-1451 Tau PET in dementia
Lowe, V. J., Curran, G., Fang, P., Liesinger, A. M., Josephs, K. A., Parisi, J. E., Kantarci, K., Boeve, B. F., Pandey, M. K., Bruinsma, T., et al. (2016) · Acta Neuropathologica Communications · doi:10.1186/s40478-016-0315-6 · Cited by 474 · see citing works
Self-citationSchwarz, A. J., Yu, P., Miller, B. B., Shcherbinin, S., Dickson, J., Navitsky, M., Joshi, A. D., Devous, M. D., & Mintun, M. S. (2016) · Brain · doi:10.1093/brain/aww023 · Cited by 425 · see citing works
Schwarz, C. G., Gunter, J. L., Wiste, H. J., Przybelski, S. A., Weigand, S. D., Ward, C. P., Senjem, M. L., Vemuri, P., Murray, M. E., Dickson, D. W., et al. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.05.017 · Cited by 422 · see citing works
Self-citationNelson, P. T., Head, E., Schmitt, F. A., Davis, P. R., Neltner, J. H., Jicha, G. A., Abner, E. L., Smith, C. D., Van Eldik, L. J., Kryscio, R. J., et al. (2011) · Acta Neuropathologica · doi:10.1007/s00401-011-0826-y · Cited by 365 · see citing works
Mormino, E. C., Betensky, R. A., Hedden, T., Schultz, A. P., Amariglio, R. E., Rentz, D. M., Johnson, K. A., & Sperling, R. A. (2014) · JAMA Neurology · doi:10.1001/jamaneurol.2014.2031 · Cited by 328 · see citing works
Vulnerable Neural Systems and the Borderland of Brain Aging and Neurodegeneration
Jagust, W. J. (2013) · Neuron · doi:10.1016/j.neuron.2013.01.002 · Cited by 321 · see citing works
Gouw, A. A., Seewann, A., Vrenken, H., van der Flier, W. M., Rozemuller, J. M., Barkhof, F., Scheltens, P., & Geurts, J. J. G. (2008) · Brain · doi:10.1093/brain/awn265 · Cited by 281 · see citing works
Jack, C. R., Wiste, H. J., Weigand, S. D., Knopman, D. S., Mielke, M. M., Vemuri, P., Lowe, V. J., Senjem, M. L., Gunter, J. L., Reyes, D. A., et al. (2015) · Brain · doi:10.1093/brain/awv283 · Cited by 252 · see citing works
Self-citationBurnham, S. C., Bourgeat, P., Doré, V., Savage, G., Brown, B., Laws, S., Maruff, P., Salvado, O., Ames, D., Martins, R. N., et al. (2016) · The Lancet Neurology · doi:10.1016/s1474-4422(16)30125-9 · Cited by 207 · see citing works
Brain injury biomarkers are not dependent on β‐amyloid in normal elderly
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., Mielke, M. M., et al. (2013) · Annals of Neurology · doi:10.1002/ana.23816 · Cited by 183 · see citing works
Self-citationPreclinical 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
Mild cognitive impairment with suspected nonamyloid pathology (SNAP): Prediction of progression
Caroli, A., Prestia, A., Galluzzi, S., Ferrari, C., van der Flier, W. M., Ossenkoppele, R., Van Berckel, B., Barkhof, F., Teunissen, C., Wall, A. E., et al. (2015) · Neurology · doi:10.1212/wnl.0000000000001209 · Cited by 142 · see citing works
Self-citationGordon, B. A., Blazey, T., Su, Y., Fagan, A. M., Holtzman, D. M., Morris, J. C., & Benzinger, T. L. S. (2016) · JAMA Neurology · doi:10.1001/jamaneurol.2016.2642 · Cited by 105 · see citing works
Thrombogenic microvesicles and white matter hyperintensities in postmenopausal women
Raz, L., Jayachandran, M., Tosakulwong, N., Lesnick, T. G., Wille, S. M., Murphy, M. C., Senjem, M. L., Gunter, J. L., Vemuri, P., Jack, C. R., et al. (2013) · Neurology · doi:10.1212/wnl.0b013e3182840c9f · Cited by 102 · see citing works
Self-citationVos, S. J. B., Gordon, B. A., Su, Y., Visser, P. J., Holtzman, D. M., Morris, J. C., Fagan, A. M., & Benzinger, T. L. S. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.03.025 · Cited by 98 · see citing works
Insights into CNS ageing from animal models of senescence
Yeoman, M. S., Scutt, G., & Faragher, R. (2012) · Nature reviews. Neuroscience · doi:10.1038/nrn3230 · Cited by 98 · see citing works
Suspected non-AD pathology in mild cognitive impairment
Wisse, L. E. M., Butala, N., Das, S. R., Davatzikos, C., Dickerson, B. C., Vaishnavi, S. N., Yushkevich, P. A., & Wolk, D. A. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.08.029 · Cited by 78 · see citing works
Mormino, E. C., Papp, K. V., Rentz, D. M., Schultz, A. P., LaPoint, M. R., Amariglio, R. E., Hanseeuw, B. J., Marshall, G. A., Hedden, T., Johnson, K. A., et al. (2016) · JAMA Neurology · doi:10.1001/jamaneurol.2016.2237 · Cited by 65 · see citing works
Does amyloid deposition produce a specific atrophic signature in cognitively normal subjects?
Whitwell, J. L., Tosakulwong, N., Weigand, S. D., Senjem, M. L., Lowe, V. J., Gunter, J. L., Boeve, B. F., Knopman, D. S., Dickerson, B. C., Petersen, R. C., et al. (2013) · NeuroImage Clinical · doi:10.1016/j.nicl.2013.01.006 · Cited by 47 · see citing works
Self-citation
Flagged first, then by citations
1 of the 43 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- [2]McKhann GM Knopman DS Chertkow H Hyman BT Jack CR Jr Kawas CH Klunk WE Koroshetz WJ Manly JJ Mayeux R Mohs RC Morric JC Rosser MN Scheltens P Thies W Weintraub S Phelps CH The diagnosis of dementia due to Alzheimer's disease: Recommendations from the National Institute on Aging and the Alzheimer's Assocation Workgrou Alzheimers Dement 2011 7 3 263 9 21514250 PMC3312024
- [17]Schwarz AJ Yu P Miller BB Shcherbinin S Dickson J Navitsky M Joshi AD Devous MD Sr Mintun MS Regional profiles of the candidate tau PET ligand 18F-AV-1451 recapitulate key features of Braak histopathologicalstages Brain: a journal of neurology 2016 139 Pt 5 1539 50 26936940
Cited by
Sorted by citations
NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease
Jack, C. R., Bennett, D. A., Blennow, K., Carrillo, M. C., Dunn, B., Haeberlein, S. B., Holtzman, D. M., Jagust, W., Jessen, F., Karlawish, J., et al. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.02.018 · Cited by 10,537 · see citing works
Self-citationLimbic-predominant age-related TDP-43 encephalopathy (LATE): consensus working group report
Nelson, P. T., Dickson, D. W., Trojanowski, J. Q., Jack, C. R., Boyle, P. A., Arfanakis, K., Rademakers, R., Alafuzoff, I., Attems, J., Brayne, C., et al. (2019) · Brain · doi:10.1093/brain/awz099 · Cited by 1,547 · see citing works
Self-citationReligious Orders Study and Rush Memory and Aging Project
Bennett, D. A., Buchman, A. S., Boyle, P. A., Barnes, L. L., Wilson, R. S., & Schneider, J. A. (2018) · Journal of Alzheimer's Disease · doi:10.3233/jad-179939 · Cited by 1,260 · see citing works
Sex differences in Alzheimer disease — the gateway to precision medicine
for the Women’s Brain Project and the Alzheimer Precision Medicine Initiative, Ferretti, M. T., Iulita, M. F., Cavedo, E., Chiesa, P. A., Schumacher Dimech, A., Santuccione Chadha, A., Baracchi, F., Girouard, H., Misoch, S., et al. (2018) · Nature Reviews Neurology · doi:10.1038/s41582-018-0032-9 · Cited by 1,009 · see citing works
A critical appraisal of amyloid-β-targeting therapies for Alzheimer disease
Panza, F., Lozupone, M., Logroscino, G., & Imbimbo, B. P. (2019) · Nature Reviews Neurology · doi:10.1038/s41582-018-0116-6 · Cited by 965 · see citing works
Understanding the impact of sex and gender in Alzheimer’s disease: A call to action
Nebel, R. A., Aggarwal, N. T., Barnes, L. L., Gallagher, A., Goldstein, J. M., Kantarci, K., Mallampalli, M. P., Mormino, E. C., Scott, L., Yu, W. H., et al. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.04.008 · Cited by 839 · see citing works
Self-citationImaging the evolution and pathophysiology of Alzheimer disease
Jagust, W. (2018) · Nature Reviews Neuroscience · doi:10.1038/s41583-018-0067-3 · Cited by 604 · see citing works
Amyloid-β-independent regulators of tau pathology in Alzheimer disease
van der Kant, R., Goldstein, L. S. B., & Ossenkoppele, R. (2020) · Nature reviews. Neuroscience · doi:10.1038/s41583-019-0240-3 · Cited by 580 · see citing works
Ossenkoppele, R., Rabinovici, G. D., Smith, R., Cho, H., Schöll, M., Strandberg, O., Palmqvist, S., Mattsson, N., Janelidze, S., Santillo, A., et al. (2018) · JAMA · doi:10.1001/jama.2018.12917 · Cited by 472 · 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
Resistance vs resilience to Alzheimer disease
Arenaza‐Urquijo, E. M., & Vemuri, P. (2018) · Neurology · doi:10.1212/wnl.0000000000005303 · Cited by 372 · see citing works
Self-citationSex-Specific Association of Apolipoprotein E With Cerebrospinal Fluid Levels of Tau
Hohman, T. J., Dumitrescu, L., Barnes, L. L., Thambisetty, M., Beecham, G., Kunkle, B., Gifford, K. A., Bush, W. S., Chibnik, L. B., Mukherjee, S., et al. (2018) · JAMA Neurology · doi:10.1001/jamaneurol.2018.0821 · Cited by 340 · see citing works
Jack, C. R., Wiste, H. J., Therneau, T. M., Weigand, S. D., Knopman, D. S., Mielke, M. M., Lowe, V. J., Vemuri, P., Machulda, M. M., Schwarz, C. G., et al. (2019) · JAMA · doi:10.1001/jama.2019.7437 · Cited by 324 · see citing works
Self-citationAssociation of Factors With Elevated Amyloid Burden in Clinically Normal Older Individuals
Sperling, R. A., Donohue, M., Raman, R., Sun, C., Yaari, R., Holdridge, K. C., Siemers, E., Johnson, K. A., Aisen, P. S. S., & for the A4 Study Team (2020) · JAMA Neurology · doi:10.1001/jamaneurol.2020.0387 · Cited by 326 · see citing works
Associations between tau, Aβ, and cortical thickness with cognition in Alzheimer disease
Ossenkoppele, R., Smith, R. A., Ohlsson, T. G., Strandberg, O. T., Mattsson, N., Insel, P. S., Palmqvist, S., & Hansson, O. (2019) · Neurology · doi:10.1212/wnl.0000000000006875 · Cited by 312 · see citing works
Jack, C. R., Therneau, T. M., Weigand, S. D., Wiste, H. J., Knopman, D. S., Vemuri, P., Lowe, V. J., Mielke, M. M., Roberts, R. O., Machulda, M. M., et al. (2019) · JAMA Neurology · doi:10.1001/jamaneurol.2019.1971 · Cited by 300 · see citing works
Self-citationSex-specific effects of microbiome perturbations on cerebral Aβ amyloidosis and microglia phenotypes
Dodiya, H. B., Kuntz, T., Shaik, S. M., Baufeld, C., Leibowitz, J., Zhang, X., Gottel, N., Zhang, X., Butovsky, O., Gilbert, J. A., et al. (2019) · Journal of Experimental Medicine · doi:10.1084/jem.20182386 · Cited by 288 · see citing works
Brain aging mechanisms with mechanical manifestations
Blinkouskaya, Y., Caçoilo, A., Gollamudi, T., Jalalian, S., & Weickenmeier, J. (2021) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2021.111575 · Cited by 274 · see citing works
White matter hyperintensities: relationship to amyloid and tau burden
Graff-Radford, J., Arenaza-Urquijo, E. M., Knopman, D. S., Schwarz, C. G., Brown, R. D., Rabinstein, A. A., Gunter, J. L., Senjem, M. L., Przybelski, S. A., Lesnick, T., et al. (2019) · Brain · doi:10.1093/brain/awz162 · Cited by 253 · see citing works
Self-citationMilà‐Alomà, M., Salvadó, G., Gispert, J. D., Vilor‐Tejedor, N., Grau‐Rivera, O., Sala‐Vila, A., Sánchez‐Benavides, G., Arenaza‐Urquijo, E. M., Crous‐Bou, M., González‐de‐Echávarri, J. M., et al. (2020) · Alzheimer's & Dementia · doi:10.1002/alz.12131 · Cited by 241 · see citing works
Dubois, B., Epelbaum, S., Nyasse, F., Bakardjian, H., Gagliardi, G. P., Uspenskaya, O., Houot, M., Lista, S., Cacciamani, F., Potier, M., et al. (2018) · The Lancet Neurology · doi:10.1016/s1474-4422(18)30029-2 · Cited by 239 · see citing works
Rossini, P. M., Iorio, R. D., Vecchio, F., Anfossi, M., Babiloni, C., Bozzali, M., Bruni, A. C., Cappa, S. F., Escudero, J., Fraga, F. J., et al. (2020) · Clinical Neurophysiology · doi:10.1016/j.clinph.2020.03.003 · Cited by 239 · see citing works
Quantification of amyloid PET for future clinical use: a state-of-the-art review
Pemberton, H. G., Collij, L. E., Heeman, F., Bollack, A., Shekari, M., Salvadó, G., Alves, I. L., Garcia, D. V., Battle, M., Buckley, C., et al. (2022) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-022-05784-y · Cited by 226 · see citing works
Sex and gender differences in cognitive resilience to aging and Alzheimer's disease
Arenaza‐Urquijo, E. M., Boyle, R., Casaletto, K., Anstey, K. J., Vila‐Castelar, C., Colverson, A., Palpatzis, E., Eissman, J. M., Kheng Siang Ng, T., Raghavan, S., et al. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.13844 · Cited by 223 · see citing works
Self-citationLeuzy, A., Smith, R., Ossenkoppele, R., Santillo, A., Borroni, E., Klein, G., Ohlsson, T., Jögi, J., Palmqvist, S., Mattsson-Carlgren, N., et al. (2020) · JAMA Neurology · doi:10.1001/jamaneurol.2020.0989 · Cited by 222 · see citing works
Biomarker-based staging of Alzheimer disease: rationale and clinical applications
Therriault, J., Schindler, S. E., Salvadó, G., Pascoal, T. A., Benedet, A. L., Ashton, N. J., Karikari, T. K., Apostolova, L. G., Murray, M. E., Verberk, I. M. W., et al. (2024) · Nature Reviews Neurology · doi:10.1038/s41582-024-00942-2 · Cited by 206 · see citing works
Self-citationATN classification and clinical progression in subjective cognitive decline: The SCIENCe project
Ebenau, J. L., Timmers, T., Wesselman, L. M. P., Verberk, I. M. W., Verfaillie, S. C. J., Slot, R. E. R., van Harten, A. C., Teunissen, C. E., Barkhof, F., van den Bosch, K. A., et al. (2020) · Neurology · doi:10.1212/wnl.0000000000009724 · Cited by 191 · see citing works
Duara, R., & Barker, W. (2022) · Neurotherapeutics · doi:10.1007/s13311-022-01185-z · Cited by 187 · see citing works
Amadoru, S., Doré, V., McLean, C. A., Hinton, F., Shepherd, C. E., Halliday, G. M., Leyton, C. E., Yates, P. A., Hodges, J. R., Masters, C. L., et al. (2020) · Alzheimer's Research & Therapy · doi:10.1186/s13195-020-00587-5 · Cited by 181 · see citing works
López, O. L., & Kuller, L. H. (2019) · Handbook of clinical neurology · doi:10.1016/b978-0-12-804766-8.00009-1 · Cited by 182 · see citing works
A second X chromosome contributes to resilience in a mouse model of Alzheimer’s disease
Davis, E. J., Broestl, L., Abdulai-Saiku, S., Worden, K., Bonham, L. W., Miñones-Moyano, E., Moreno, A. J., Wang, D., Chang, K., Williams, G., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aaz5677 · Cited by 176 · see citing works
Association of Neighborhood-Level Disadvantage With Cerebral and Hippocampal Volume
Hunt, J. F. V., Buckingham, W. J., Kim, A. J., Oh, J. M., Vogt, N. M., Jonaitis, E. M., Hunt, T. K. A., Zuelsdorff, M. L., Powell, W. R., Norton, D., et al. (2020) · JAMA Neurology · doi:10.1001/jamaneurol.2019.4501 · Cited by 166 · see citing works
Ossenkoppele, R., Lyoo, C. H., Jester-Broms, J., Sudre, C. H., Cho, H., Ryu, Y. H., Choi, J. Y., Smith, R., Strandberg, O., Palmqvist, S., et al. (2020) · JAMA Neurology · doi:10.1001/jamaneurol.2019.5154 · Cited by 161 · see citing works
Lipid lowering and Alzheimer disease risk: A mendelian randomization study
Williams, D. M., Finan, C., Schmidt, A. F., Burgess, S., & Hingorani, A. D. (2020) · Annals of Neurology · doi:10.1002/ana.25642 · Cited by 157 · see citing works
Ferretti, M. T., Martínková, J., Biskup, E. M., Benke, T., Gialdini, G., Nedelská, Z., Rauen, K., Mantua, V., Religa, D., Hort, J., et al. (2020) · European Journal of Neurology · doi:10.1111/ene.14174 · Cited by 150 · see citing works
Knopman, D. S., Haeberlein, S. B., Carrillo, M. C., Hendrix, J. A., Kerchner, G., Margolin, R. A., Maruff, P. T., Miller, D. S., Tong, G., Tome, M. B., et al. (2018) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2018.03.002 · Cited by 140 · see citing works
Self-citationAlzheimer’s disease profiled by fluid and imaging markers: tau PET best predicts cognitive decline
Bucci, M., Chiotis, K., Nordberg, A., & Initiative, F. T. A. D. N. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01263-2 · Cited by 140 · see citing works
Astrocyte Biomarkers in Alzheimer Disease: A Systematic Review and Meta-analysis
Bellaver, B., Ferrari-Souza, J. P., Uglione da Ros, L., Carter, S. F., Rodriguez-Vieitez, E., Nordberg, A., Pellerin, L., Rosa-Neto, P., Leffa, D. T., & Zimmer, E. R. (2021) · Neurology · doi:10.1212/wnl.0000000000012109 · Cited by 123 · see citing works
Parker, T. D., Slattery, C. F., Zhang, J., Nicholas, J. M., Paterson, R. W., Foulkes, A. J. M., Malone, I. B., Thomas, D. L., Modat, M., Cash, D. M., et al. (2018) · Human Brain Mapping · doi:10.1002/hbm.24056 · Cited by 122 · see citing works
Shir, D., Graff‐Radford, J., Hofrenning, E. I., Lesnick, T. G., Przybelski, S. A., Lowe, V. J., Knopman, D. S., Petersen, R. C., Jack, C. R., Vemuri, P., et al. (2022) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12291 · Cited by 122 · see citing works
Self-citationPrevalence of preclinical Alzheimer disease
Kern, S., Zetterberg, H., Kern, J., Zettergren, A., Wærn, M., Höglund, K., Andréasson, U., Wetterberg, H., Börjesson‐Hanson, A., Blennow, K., et al. (2018) · Neurology · doi:10.1212/wnl.0000000000005476 · Cited by 120 · see citing works
Alzheimer disease blood biomarkers: considerations for population-level use
Mielke, M. M., & Fowler, N. R. (2024) · Nature Reviews Neurology · doi:10.1038/s41582-024-00989-1 · Cited by 123 · see citing works
Self-citationMilà‐Alomà, M., Brinkmalm, A., Ashton, N. J., Kvartsberg, H., Shekari, M., Operto, G., Salvadó, G., Falcón, C., Gispert, J. D., Vilor‐Tejedor, N., et al. (2021) · Neurology · doi:10.1212/wnl.0000000000012853 · Cited by 117 · see citing works
The metabolic brain signature of cognitive resilience in the 80+: beyond Alzheimer pathologies
Arenaza‐Urquijo, E. M., Przybelski, S. A., Lesnick, T. G., Graff‐Radford, J., Machulda, M. M., Knopman, D. S., Schwarz, C. G., Lowe, V. J., Mielke, M. M., Petersen, R. C., et al. (2019) · Brain · doi:10.1093/brain/awz037 · Cited by 112 · see citing works
Self-citationCavedo, E., Chiesa, P. A., Houot, M., Ferretti, M. T., Grothe, M. J., Teipel, S. J., Lista, S., Habert, M., Potier, M., Dubois, B., et al. (2018) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2018.05.014 · Cited by 107 · see citing works
Armstrong, N. M., An, Y., Beason‐Held, L. L., Doshi, J. J., Erus, G., Ferrucci, L., Davatzikos, C. A., & Resnick, S. M. (2019) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2019.05.020 · Cited by 109 · see citing works
Fluid and PET biomarkers for amyloid pathology in Alzheimer's disease
Cohen, A. D., Landau, S. M., Snitz, B. E., Klunk, W. E., Blennow, K., & Zetterberg, H. (2018) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2018.12.004 · Cited by 107 · see citing works
ATN profiles among cognitively normal individuals and longitudinal cognitive outcomes
Soldan, A., Pettigrew, C. A., Fagan, A. M., Schindler, S. E., Moghekar, A., Fowler, C. J., Li, Q.-X., Collins, S. J., Carlsson, C. M., Asthana, S., et al. (2019) · Neurology · doi:10.1212/wnl.0000000000007248 · Cited by 104 · see citing works
Hypersynchronization in mild cognitive impairment: the ‘X’ model
Pusil, S. A., López, M. E., Cuesta, P., Bruña, R., Pereda, E., & Maestú, F. (2019) · Brain · doi:10.1093/brain/awz320 · Cited by 99 · see citing works
Li, H., Liu, C.-C., Zheng, H., & Huang, T. Y. (2018) · Translational Neurodegeneration · doi:10.1186/s40035-018-0139-3 · Cited by 103 · see citing works
Mullane, K., & Williams, M. (2018) · Biochemical Pharmacology · doi:10.1016/j.bcp.2018.09.026 · Cited by 98 · see citing works
Sex differences in Alzheimer’s disease: Understanding the molecular impact
Toro, C. A., Zhang, L., Cao, J., & Cai, D. (2019) · Brain Research · doi:10.1016/j.brainres.2019.05.031 · Cited by 97 · see citing works
From Menopause to Neurodegeneration—Molecular Basis and Potential Therapy
Cheng, Y., Lin, C., & Lane, H. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22168654 · Cited by 99 · see citing works
Therriault, J., Pascoal, T. A., Benedet, A. L., Tissot, C., Savard, M., Chamoun, M., Lussier, F., Kang, M. S., Berzgin, G., Wang, T., et al. (2021) · Neurology · doi:10.1212/wnl.0000000000011416 · Cited by 91 · see citing works
Dubal, D. B. (2020) · Handbook of clinical neurology · doi:10.1016/b978-0-444-64123-6.00018-7 · Cited by 88 · see citing works
Sex as an important factor in nanomedicine
Hajipour, M. J., Aghaverdi, H., Serpooshan, V., Vali, H., Sheibani, S., & Mahmoudi, M. (2021) · Nature Communications · doi:10.1038/s41467-021-23230-9 · Cited by 90 · see citing works
Associations between Vascular Function and Tau PET Are Associated with Global Cognition and Amyloid
Albrecht, D., Isenberg, A. L., Stradford, J., Monreal, T. K., Sagare, A. P., Pachicano, M., Sweeney, M. D., Toga, A. W., Zloković, B. V., Chui, H. C., et al. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.1230-20.2020 · Cited by 85 · see citing works
Gamache, J., Yun, Y., & Chiba-Falek, O. (2020) · Disease Models & Mechanisms · doi:10.1242/dmm.045211 · Cited by 84 · see citing works
Leuzy, A., Pascoal, T. A., Strandberg, O. T., Insel, P. S., Smith, R. A., Mattsson, N., Benedet, A. L., Cho, H., Lyoo, C. H., Joie, R. L., et al. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05401-4 · Cited by 86 · see citing works
Sex differences in CSF biomarkers vary by Alzheimer disease stage and APOE ε4 genotype
Mofrad, R. B., Tijms, B. M., Scheltens, P., Barkhof, F., van der Flier, W. M., Sikkes, S. A. M., & Teunissen, C. E. (2020) · Neurology · doi:10.1212/wnl.0000000000010629 · Cited by 80 · see citing works
Applying the ATN scheme in a memory clinic population
Altomare, D., de Wilde, A., Ossenkoppele, R., Pelkmans, W., Bouwman, F. H., Groot, C., van Maurik, I. S., Zwan, M. D., Yaqub, M. M., Barkhof, F., et al. (2019) · Neurology · doi:10.1212/wnl.0000000000008361 · Cited by 78 · see citing works
The A/T/N biomarker scheme and patterns of brain atrophy assessed in mild cognitive impairment
Ekman, U., Ferreira, D., & Westman, E. (2018) · Scientific Reports · doi:10.1038/s41598-018-26151-8 · Cited by 78 · see citing works
The Importance of the Validation of M/EEG With Current Biomarkers in Alzheimer's Disease
Maestú, F., Cuesta, P., Hasan, O., Fernández, A., Funke, M. E., & Schulz, P. E. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00017 · Cited by 74 · see citing works
Ramanan, V. K., Castillo, A. M., Knopman, D. S., Graff‐Radford, J., Lowe, V. J., Petersen, R. C., Jack, C. R., Mielke, M. M., & Vemuri, P. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.13909 · Cited by 71 · see citing works
Self-citationYu, J., Li, J., John Suckling, A., Feng, L., Pan, A., Wang, Y., Song, B., Zhu, S., Li, D., Wang, H.-F., et al. (2019) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2019.05.006 · Cited by 73 · see citing works
Anti-Tau Trials for Alzheimer's Disease: A Report from the EU/US/CTAD Task Force
Cummings, J. L., Blennow, K., Johnson, K. A., Keeley, M. B., Bateman, R. J., Molinuevo, J. L., Touchon, J., Aisen, P. S. S., & Vellas, B. J. (2019) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2019.14 · Cited by 71 · see citing works
NIA‐AA Alzheimer's Disease Framework: Clinical Characterization of Stages
Petersen, R. C., Wiste, H. J., Weigand, S. D., Fields, J. A., Geda, Y. E., Graff‐Radford, J., Knopman, D. S., Kremers, W. K., Lowe, V. J., Machulda, M. M., et al. (2021) · Annals of Neurology · doi:10.1002/ana.26071 · Cited by 72 · see citing works
Self-citationBrain aerobic glycolysis and resilience in Alzheimer disease
Goyal, M. S., Blazey, T., Metcalf, N. V., McAvoy, M. P., Strain, J. F., Rahmani, M., Durbin, T. J., Xiong, C., Benzinger, T. L. S., Morris, J. C., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2212256120 · Cited by 72 · see citing works
Rosenberg, A., Öhlund-Wistbacka, U., Hall, A., Bonnard, A., Hagman, G., Rydén, M., Thunborg, C., Wiggenraad, F., Sandebring-Matton, A., Solomon, A., et al. (2022) · Neurology · doi:10.1212/wnl.0000000000201043 · Cited by 70 · see citing works
Challenges associated with biomarker‐based classification systems for Alzheimer's disease
Illán‐Gala, I., Pegueroles, J., Montal, V., Vilaplana, E., Carmona‐Iragui, M., Alcolea, D., Dickerson, B. C., Sánchez‐Valle, R., de Leon, M. J., Blesa, R., et al. (2018) · Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring · doi:10.1016/j.dadm.2018.03.004 · Cited by 62 · see citing works
Morphometric network differences in ageing versus Alzheimer’s disease dementia
Binette, A. P., Gonneaud, J., Vogel, J. W., Joie, R. L., Rosa‐Neto, P., Collins, D. L., Poirier, J., Breitner, J. C. S., Villeneuve, S., Vachon‐Presseau, É., et al. (2019) · Brain · doi:10.1093/brain/awz414 · Cited by 54 · see citing works
Hypothesis review: Alzheimer's overture guidelines
Ferrer, I. (2022) · Brain Pathology · doi:10.1111/bpa.13122 · Cited by 54 · see citing works
Alzheimer's disease neuroimaging
Whitwell, J. L. (2018) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000570 · Cited by 64 · see citing works
Wisch, J. K., Meeker, K. L., Gordon, B. A., Flores, S. E., Dincer, A., Grant, E., Benzinger, T. L. S., Morris, J. C., & Ances, B. M. (2020) · Alzheimer Disease & Associated Disorders · doi:10.1097/wad.0000000000000393 · Cited by 56 · see citing works
Comparison of CSF phosphorylated tau 181 and 217 for cognitive decline
Mielke, M. M., Aakre, J. A., Algeciras‐Schimnich, A., Proctor, N. K., Machulda, M. M., Eichenlaub, U., Knopman, D. S., Vemuri, P., Graff‐Radford, J., Jack, C. R., et al. (2022) · Alzheimer's & Dementia · doi:10.1002/alz.12415 · Cited by 55 · see citing works
Self-citationGanguli, M., Albanese, E., Seshadri, S. S., Bennett, D. A., Lyketsos, C. G., Kukull, W. A., Skoog, I. G., & Hendrie, H. C. (2018) · Alzheimer Disease & Associated Disorders · doi:10.1097/wad.0000000000000237 · Cited by 55 · see citing works
Comparison of plasma and CSF biomarkers in predicting cognitive decline
Aschenbrenner, A. J., Li, Y., Henson, R. L., Volluz, K., Hassenstab, J. J., Verghese, P. B., West, T., Meyer, M. R., Kirmess, K. M., Fagan, A. M., et al. (2022) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.51670 · Cited by 59 · see citing works
Towards a Redefinition of Cognitive Frailty
Mantovani, E., Zucchella, C., Schena, F. F., Romanelli, M. G., Venturelli, M., & Tamburin, S. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200137 · Cited by 55 · see citing works
Beta-secretase inhibitors in phase I and phase II clinical trials for Alzheimer’s disease
Moussa, C. (2017) · Expert Opinion on Investigational Drugs · doi:10.1080/13543784.2017.1369527 · Cited by 46 · see citing works
Neurogenetic disorders across the lifespan: from aberrant development to degeneration
Hickman, R. A., O’Shea, S. A., Mehler, M. F., & Chung, W. K. (2022) · Nature Reviews Neurology · doi:10.1038/s41582-021-00595-5 · Cited by 55 · see citing works
Armstrong, N. M., An, Y., Beason‐Held, L. L., Doshi, J. J., Erus, G., Ferrucci, L., Davatzikos, C. A., & Resnick, S. M. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.10.024 · Cited by 51 · see citing works
PET imaging of neural activity, β-amyloid, and tau in normal brain aging
Zhang, K., Mizuma, H., Zhang, X., Takahashi, K., Jin, C., Song, F., Gao, Y., Kanayama, Y., Wu, Y., Li, Y., et al. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05230-5 · Cited by 50 · see citing works
Sex differences in the genetic architecture of Alzheimer’s disease
Dumitrescu, L., Mayeda, E. R., Sharman, K., Moore, A. M., & Hohman, T. J. (2019) · Current Genetic Medicine Reports · doi:10.1007/s40142-019-0157-1 · Cited by 48 · see citing works
Alzheimer’s disease-related transcriptional sex differences in myeloid cells
Coales, I., Tsartsalis, S., Fancy, N., Weinert, M., Clode, D., Owen, D., & Matthews, P. M. (2022) · Journal of Neuroinflammation · doi:10.1186/s12974-022-02604-w · Cited by 49 · see citing works
Abnormal tau in amyloid PET negative individuals
Yoon, B., Guo, T., Provost, K., Korman, D., Ward, T. J., Landau, S. M., & Jagust, W. J. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2021.09.019 · Cited by 48 · see citing works
Costoya‐Sánchez, A., Moscoso, A., Silva‐Rodríguez, J., Pontecorvo, M. J., Devous, M. D., Aguiar, P., Schöll, M., Grothe, M. J., Initiative, A. D. N., Weiner, M. W., et al. (2023) · JAMA Neurology · doi:10.1001/jamaneurol.2023.2560 · Cited by 48 · see citing works
Self-citationNeuropsychological Profiles and Trajectories in Preclinical Alzheimer’s Disease
Ho, J. K., Nation, D. A., & Initiative, A. D. N. (2018) · Journal of the International Neuropsychological Society · doi:10.1017/s135561771800022x · Cited by 46 · see citing works
Hippocampal Sclerosis, Argyrophilic Grain Disease, and Primary Age-Related Tauopathy
Jicha, G. A., & Nelson, P. T. (2019) · CONTINUUM Lifelong Learning in Neurology · doi:10.1212/con.0000000000000697 · Cited by 49 · see citing works
Longitudinal Association Between Brain Amyloid-Beta and Gait in the Mayo Clinic Study of Aging
Wennberg, A. M. V., Lesnick, T. G., Schwarz, C. G., Savica, R., Hagen, C. E., Roberts, R. O., Knopman, D. S., Hollman, J. H., Vemuri, P., Jack, C. R., et al. (2017) · The Journals of Gerontology Series A · doi:10.1093/gerona/glx240 · Cited by 45 · see citing works
Self-citationGrilli, M. D., Knoff, A. A. W., Bercel, J. J., & Ryan, L. (2018) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617718000577 · Cited by 45 · see citing works
Cui, S.-Y., Yang, M.-X., Zhang, Y.-H., Zheng, V., Zhang, H.-T., Gurney, M., Xu, Y., & O'Donnell, J. (2019) · Journal of Pharmacology and Experimental Therapeutics · doi:10.1124/jpet.119.259986 · Cited by 34 · see citing works
What’s the cut-point?: a systematic investigation of tau PET thresholding methods
Weigand, A. J., Maaß, A., Eglit, G. L., & Bondi, M. W. (2022) · Alzheimer s Research & Therapy · doi:10.1186/s13195-022-00986-w · Cited by 44 · see citing works
Wang, M.-L., Yu, M., Wei, X., Li, W., & Li, Y. (2020) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2020.12.014 · Cited by 43 · see citing works
Castrillo, J. I., Lista, S., Hampel, H. J., & Ritchie, C. W. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-7704-8_3 · Cited by 44 · see citing works
Lindgrén, N., Rinne, J. O., Palviainen, T., Kaprio, J. A., & Vuoksimaa, E. (2019) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.5205 · Cited by 43 · see citing works
Abner, E. L., Neltner, J. H., Jicha, G. A., Patel, E., Anderson, S., Wilcock, D. M., Eldik, L. J. V., & Nelson, P. T. (2018) · Journal of Alzheimer s Disease · doi:10.3233/jad-180514 · Cited by 42 · see citing works
Marongiu, R. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00242 · Cited by 44 · see citing works
The A/T/N model applied through imaging biomarkers in a memory clinic
Dodich, A., Mendes, A., Assal, F., Chicherio, C., Rakotomiaramanana, B., Andryszak, P., Festari, C., Ribaldi, F., Scheffler, M., Schibli, R., et al. (2019) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-019-04536-9 · Cited by 42 · see citing works
Bannai, T., Mano, T., Chen, X., Ohtomo, G., Ohtomo, R., Tsuchida, T., Mano, K. K., Hashimoto, T., Okazawa, H., Iwatsubo, T., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-39494-7 · Cited by 41 · see citing works
Testing the amyloid cascade hypothesis: Prevention trials in autosomal dominant Alzheimer disease
Levin, J., Vöglein, J., Quiroz, Y. T., Bateman, R. J., Ghisays, V., Lopera, F., McDade, E., Reiman, E., Tariot, P. N., & Morris, J. C. (2022) · Alzheimer's & Dementia · doi:10.1002/alz.12624 · Cited by 40 · see citing works
- Authors
- Jack, C. R., Wiste, H. J., Weigand, S. D., Therneau, T. M., Knopman, D. S., Lowe, V., Vemuri, P., Mielke, M. M., Roberts, R. O., Machulda, M. M., Senjem, M. L., Gunter, J. L., Rocca, W. A., & Petersen, R. C.
- Affiliations
- Mayo Clinic (US)
- Corresponding author
- Jack, Clifford R
- ORCID
- Venue
- The Lancet Neurology
- Publisher
- Elsevier BV
- Published
- 2017-06
- Volume
- 16
- Issue
- 6
- Pages
- 435-444
- ISSN
- 1474-4422 (ISSN-L)
- PMC
- PMC5516534
- OpenAlex
- W2608642452
- Cited by
- 333
- References
- 43
- Citations by year
- 2026: 28 · 2025: 27 · 2024: 42 · 2023: 26 · 2022: 39 · 2021: 39 · 2020: 36 · 2019: 46 · 2018: 41 · 2017: 9
- FWCI
- 29.66
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- The Lancet Neurology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion, cc-by)
- PubMed Central (acceptedVersion, cc-by)
- Funders
- Mayo Clinic
- National Institutes of Health
- National Institute on Aging (R01AG034676, U01AG006786, R01AG011378, R01AG041851, R37AG011378)
- National Institute of Neurological Disorders and Stroke (R01NS097495)
- 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
- Alzheimer's disease biomarkers, tauopathy, neurodegeneration, cognitively unimpaired older adults, amyloid PET, tau PET, cortical thickness, prevalence, age-specific prevalence, sex differences, Mayo Clinic Study of Aging, cognitive aging, neuroimaging biomarkers, centiloid, standard uptake value ratio, multimodal neuroimaging
- MeSH terms
- Age Factors, Aged, Aged, 80 and over, Amyloidosis, Cross-Sectional Studies, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Minnesota, Sex Factors, Biomarkers, Prevalence, Amyloid beta-Peptides, Neurodegenerative Diseases, Tauopathies, Positron-Emission Tomography
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