The DOI matches its Crossref record; 43 of the 44 references it cites were found in a registry or an index.
Neuropathologically defined subtypes of Alzheimer's disease with distinct clinical characteristics: a retrospective study
Open accessAbstract
Background Neurofibrillary pathology has a stereotypical progression in Alzheimer's disease (AD) that is encapsulated in the Braak staging scheme; however, some AD cases are atypical and do not fit into this scheme. We aimed to compare clinical and neuropathological features between typical and atypical AD cases.Methods AD cases with a Braak neurofibrillary tangle stage of more than IV were identified from a brain bank database. By use of thioflavin-S fluorescence microscopy, we assessed the density and the distribution of neurofibrillary tangles in three cortical regions and two hippocampal sectors. These data were used to construct an algorithm to classify AD cases into typical, hippocampal sparing, or limbic predominant. Classified cases were then compared for clinical, demographic, pathological, and genetic characteristics. An independent cohort of AD cases was assessed to validate findings from the initial cohort.Findings 889 cases of AD, 398 men and 491 women with age at death of 37-103 years, were classified with the algorithm as hippocampal sparing (97 cases [11%]), typical (665 [75%]), or limbic predominant (127 [14%]). By comparison with typical AD, neurofibrillary tangle counts per 0.125 mm(2) in hippocampal sparing cases were higher in cortical areas (median 13, IQR 11-16) and lower in the hippocampus (7.5, 5.2-9.5), whereas counts in limbic-predominant cases were lower in cortical areas (4.3, 3.0-5.7) and higher in the hippocampus (27, 22-35). Hippocampal sparing cases had less hippocampal atrophy than did typical and limbic-predominant cases. Patients with hippocampal sparing AD were younger at death (mean 72 years [SD 10]) and a higher proportion of them were men (61 [63%]), whereas those with limbic-predominant AD were older (mean 86 years [SD 6]) and a higher proportion of them were women (87 [69%]). Microtubule-associated protein tau (MAPT) H1H1 genotype was more common in limbic-predominant AD (54 [70%]) than in hippocampal sparing AD (24 [46%]; p=0.011), but did not differ significantly between limbic-predominant and typical AD (204 [59%]; p=0.11). Apolipoprotein E (APOE) ɛ4 allele status differed between AD subtypes only when data were stratified by age at onset. Clinical presentation, age at onset, disease duration, and rate of cognitive decline differed between the AD subtypes. These findings were confirmed in a validation cohort of 113 patients with AD.Interpretation These data support the hypothesis that AD has distinct clinicopathological subtypes. Hippocampal sparing and limbic-predominant AD subtypes might account for about 25% of cases, and hence should be considered when designing clinical, genetic, biomarker, and treatment studies in patients with AD.Funding US National Institutes of Health via Mayo Alzheimer's Disease Research Center, Mayo Clinic Study on Aging, Florida Alzheimer's Disease Research Center, and Einstein Aging Study; and State of Florida Alzheimer's Disease Initiative.
Overview
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
Verification
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“clinical features lack specificity for a pathologic process, but rather indicate brain regions or systems affected by the disease process [3, 4].”
From The neuropathological diagnosis of Alzheimer's disease (2019) · cites this paper as [3]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Three major subtypes of AD can be classified by the relative density of hippocampal neurofibrillary tangles with respect to neocortical tangles [3].”
From The neuropathological diagnosis of Alzheimer's disease (2019) · cites this paper as [3]
The cited source says what the claim attributes to it.
In the citing paper
“Genetic analyses of APOE suggest APOE4 is more closely linked to typical or limbic predominant than hippocampal sparing AD [3].”
From The neuropathological diagnosis of Alzheimer's disease (2019) · cites this paper as [3]
The cited source says what the claim attributes to it.
In the citing paper
“Nonamnestic clinical presentations, that is, language, visuospatial, and executive disorders, may also be due to AD [63–66].”
From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [65]
In the citing paper
“Another challenge of CPC studies is that the molecular, anatomic, and clinical changes of AD may not progress in a uniform fashion (7, 12-15).”
From Correlation of Alzheimer Disease Neuropathologic Changes With Cognitive Status: A Review of the Literature (2012) · cites this paper as [12]
In the citing paper
“and that not all AD cases fall within the same spatial continuum with regard to brain NFT distributions (12, 15, 151).”
From Correlation of Alzheimer Disease Neuropathologic Changes With Cognitive Status: A Review of the Literature (2012) · cites this paper as [12]
In the citing paper
“Nevertheless, Braak staging also masks the fact that marked variability in pathologic lesion density across cases exists within a given Braak stage (7, 12)”
From Correlation of Alzheimer Disease Neuropathologic Changes With Cognitive Status: A Review of the Literature (2012) · cites this paper as [12]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
Neuropathological stageing of Alzheimer-related changes.
Braak, H., & Braak, E. (1991) · Acta Neuropathologica · doi:10.1007/bf00308809 · Cited by 16,123
Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade
Jack, C. R., Knopman, D. S., Jagust, W. J., Shaw, L. M., Aisen, P. S., Weiner, M. W., Petersen, R. C., & Trojanowski, J. Q. (2010) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70299-6 · Cited by 4,806
Self-citationNeurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimer's disease
Arriagada, P. V., Growdon, J. H., Hedley-Whyte, E. T., & Hyman, B. T. (1992) · Neurology · doi:10.1212/wnl.42.3.631 · Cited by 2,668
Diagnosis of Alzheimer's Disease
Khachaturian, Z. S. (1985) · Archives of Neurology · doi:10.1001/archneur.1985.04060100083029 · Cited by 2,499
HYMAN, B. T., & TROJANOWSKI, J. Q. (1997) · Journal of Neuropathology and Experimental Neurology · doi:10.1097/00005072-199710000-00002 · Cited by 1,542
Arnold, S. E., Hyman, B. T., Flory, J., Damasio, A. R., & Van Hoesen, G. W. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.103 · Cited by 1,380
TDP‐43 immunoreactivity in hippocampal sclerosis and Alzheimer's disease
Amador‐Ortiz, C., Lin, W., Ahmed, Z., Personett, D., Davies, P., Duara, R., Graff‐Radford, N. R., Hutton, M. L., & Dickson, D. W. (2007) · Annals of Neurology · doi:10.1002/ana.21154 · Cited by 916
Self-citationAssociation of an Extended Haplotype in the Tau Gene with Progressive Supranuclear Palsy
Baker, M., Litvan, I., Houlden, H., Adamson, J., Dickson, D., Perez-Tur, J., Hardy, J., Lynch, T., Bigio, E., & Hutton, M. (1999) · Human Molecular Genetics · doi:10.1093/hmg/8.4.711 · Cited by 781
Self-citationBarker, W., Luis, C. A., Kashuba, A., Luis, M., Harwood, D. G., Loewenstein, D., Waters, C., Jimison, P., Shepherd, E., Sevush, S., et al. (2002) · Alzheimer Disease & Associated Disorders · doi:10.1097/00002093-200210000-00001 · Cited by 714
Self-citation
Cited by
Sorted by citations
Items 901–971 of 971
Brain volumes discriminate clinical dementia rating scale categories
Christova, P. S., James, L. M., & Georgopoulos, A. P. (2025) · Scientific Reports · doi:10.1038/s41598-025-23418-9
Abdi, Z., Harding, E., Pelak, V. S., Yong, K. X. X., & Crutch, S. J. (2025) · Cambridge University Press eBooks · doi:10.1017/9781108985055.016
Alzheimer’s Disease: Preclinical to Advanced Dementia
Martínez, N. F., & Sánchez‐Valle, R. (2025) · Cambridge University Press eBooks · doi:10.1017/9781108985055.010
Structural heterogeneity reveals distinct amyloidopathies in Alzheimer’s diseasePreprint
Novotný, J., Čarná, M., Lyburn, I. D., Kuruvilla, T., Stokin, G. B., & Initiative, T. A. D. N. (2025) · medRxiv · doi:10.1101/2025.11.17.25340406
Baek, M. S., Cho, H., Lee, H. S., Lee, J. H., Ryu, Y. H., & Lyoo, C. H. (2020) · Figshare · doi:10.6084/m9.figshare.13174043
Additional file 2 of TDP-43-regulated cryptic RNAs accumulate in Alzheimer’s disease brains
Estades Ayuso, V., Pickles, S. R., Todd, T. W., Yue, M., Jansen‐West, K. R., Song, Y., Bejarano, J. G., Rawlinson, B. D., Deture, M. A., Graff‐Radford, N. R., et al. (2023) · Figshare · doi:10.6084/m9.figshare.24002645
Self-citationAdditional file 3 of TDP-43-regulated cryptic RNAs accumulate in Alzheimer’s disease brains
Estades Ayuso, V., Pickles, S. R., Todd, T. W., Yue, M., Jansen‐West, K. R., Song, Y., Bejarano, J. G., Rawlinson, B. D., Deture, M. A., Graff‐Radford, N. R., et al. (2023) · Figshare · doi:10.6084/m9.figshare.24002648
Self-citationHe, X.-Y., Wu, B.-S., Kuo, K., Zhang, W., Ma, Q., Xiang, S.-T., Li, Y.-Z., Wang, Z.-Y., Dong, Q., Feng, J.-F., et al. (2023) · Figshare · doi:10.6084/m9.figshare.23512814
Additional file 1 of TDP-43-regulated cryptic RNAs accumulate in Alzheimer’s disease brains
Estades Ayuso, V., Pickles, S. R., Todd, T. W., Yue, M., Jansen‐West, K. R., Song, Y., Bejarano, J. G., Rawlinson, B. D., Deture, M. A., Graff‐Radford, N. R., et al. (2023) · Figshare · doi:10.6084/m9.figshare.24002642
Self-citationAdditional file 1 of Data-driven FDG-PET subtypes of Alzheimer’s disease-related neurodegeneration
Levin, F., Ferreira, D., Lange, C., Dyrba, M., Westman, E., Buchert, R., Teipel, S. J., & Grothe, M. J. (2021) · Figshare · doi:10.6084/m9.figshare.14068058
Machado, A., Ferreira, D., Grothe, M. J., Eyjolfsdottir, H., Almqvist, P. M., Cavallin, L., Lind, G., Linderoth, B., Seiger, Å., Teipel, S., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12262178
Reddy, J. S., Allen, M., Ho, C. C. G., Oatman, S. R., İş, Ö., Quicksall, Z., Wang, X., Jin, J., Patel, T. A., Carnwath, T., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14643245
Self-citationScalco, R., Saito, N., Beckett, L. A., Nguyen, M.-L., Huie, E. Z., Wang, H.-P., Flaherty, D., Honig, L. S., DeCarli, C. S., Rissman, R. A., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26600926
Additional file 1 of Differential response to donepezil in MRI subtypes of mild cognitive impairment
Diaz‐Galvan, P., Lorenzon, G., Mohanty, R., Mårtensson, G., Cavedo, E., Lista, S., Vergallo, A., Kantarci, K., Hampel, H. J., Dubois, B., et al. (2023) · Figshare · doi:10.6084/m9.figshare.23573579
Wang, Z., Zhang, M., Liu, C., Zhang, Y., Cheng, R., Zhang, S., Yang, B., Wang, L., Guo, J., & Wang, X. (2026) · Naunyn-Schmiedeberg s Archives of Pharmacology · doi:10.1007/s00210-026-05926-1
Microbiota and Alzheimer's disease: Toward new clinical approaches
Đokić, J., & Dinić, M. (2025) · Medicinski podmladak · doi:10.5937/mp76-60520 · Cited by 1
Zhou, J., Chen, W., Song, J., Yu, D., Shi, C., Luo, H., & Huang, S. (2025) · Neurological Sciences · doi:10.1007/s10072-025-08667-w
The “Hyperactive” Phenotype of Alzheimer’s Disease
Horváth, A., & Kamondi, A. (2025) · Springer eBooks · doi:10.1007/978-3-031-95878-6_8
Graphical modeling of cortical tau pathology topography for its subtyping in Alzheimer’s disease
Yue, J., Wang, X., Ringman, J. M., & Shi, Y. (2026) · Imaging Neuroscience · doi:10.1162/imag.a.1110
Alpha-synuclein propagation trajectories in a population-based postmortem cohortPreprint
Khalafi, P., Vogel, J. W., Boghammer, P., Raunio, A., Kivistö, V., Savola, S. E., Kok, E., Mikhailenko, E., Myllykangas, L., & Dagher, A. (2026) · medRxiv · doi:10.64898/2026.01.13.26343943
Heterogeneous patterns of cognitive decline in Alzheimer's disease across three domains of cognition
Scollard, P., Mukherjee, S., Choi, S., Lee, M. L., Klinedinst, B. S., Gibbons, L. E., Trittschuh, E. H., Mez, J., Saykin, A. J., James, B. D., et al. (2026) · Journal of Alzheimer s Disease · doi:10.1177/13872877251414975 · Cited by 1
Behavioral Variant in Alzheimer's Disease.
Wu, C.-K., Dailey, J. M., & Donahue, J. E. (2026) · Acta neurologica Taiwanica · doi:10.4103/ant.ant-d-25-00098
Chaggar, P., Vogel, J. W., Thompson, T., Aldea, R., Strandberg, O. T., Stomrud, E., Palmqvist, S., Ossenkoppele, R., Jbabdi, S., Magon, S., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.27.701320
Wheatley, S., Ferreira, D., Nordberg, A., Mohanty, R., & Westman, E. (2026) · Research Square · doi:10.21203/rs.3.rs-8910160/v1
Wachi, K., Yamao, T., Miwa, K., Miyaji, N., Akiya, N., Horikawa, T., Masubuchi, M., Kimura, S., & Matsuda, H. (2026) · Annals of Nuclear Medicine · doi:10.1007/s12149-026-02184-2
Xu, X., Yu, J., Zhao, R., Chu, H., Hou, Y., Li, Z., Li, S., Hou, Q., Ma, L., Xu, Q., et al. (2026) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2026.106217
Pereira, F. L., Lew, C. H., Li, S. H., Rizzi, L., Soloviev, A., Paes, V. R., Brooks, S. D., Spina, S., Rexach, J. E., Newell, K. L., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.30.715299 · Cited by 1
Self-citationImplication des polynucléaires neutrophiles au cours de la maladie d’Alzheimer et des tauopathies
Dong, Y. (2018) · theses.fr (ABES) · doi:10.70675/0542df04zd02ez4a58za844z605f237e8f0b
Hayakawa, N., Takeda, S., Takahashi, H., Arisawa, A., Matsuo, C., Tomiyama, N., Nakajima, T., Miki, S., Kishino, Y., Teshirogi, S., et al. (2026) · Journal of Alzheimer s Disease · doi:10.1177/13872877261436754
Lam, S. (2021) · theses.fr (ABES) · doi:10.70675/60b353ffz56fcz41a2z9e53zf0d9ac078167 · Cited by 1
Dautricourt, S. (2021) · theses.fr (ABES) · doi:10.70675/63472a25z31eaz4ebczaebdzd8d2e061b4b8
The Use of Localized Proteomics to Understand the Pathogenesis of Alzheimer's Disease
Pires, G. (2021) · theses.fr (ABES) · doi:10.70675/45826fd6zd2c8z4b3dz91e0za5080544cb17
The aging eye: navigating molecular mechanisms and innovative interventions
Lin, Y., Han, Z., Zhang, Y., Yuan, R., Huang, M., Liu, Y., Wang, J., Xu, C., Liu, L., Yu, P., et al. (2026) · Biogerontology · doi:10.1007/s10522-026-10443-y
Dissecting Alzheimer’s disease heterogeneity by cross-trait polygenic predictionPreprint
Li, W. F., Mohammed, N., Bennett, D. A. A., Kellis, M., & Tanigawa, Y. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.15.725551
Teles, W. D. S., da Silva, M. C., de Carvalho, C. M. N., Santos, L. E. D. S., Souza, R. D. S., Santos, J. S. D. C., FARIAS, S. D. O., Andrade, Á. N. M., Santos, R. D. L., & Oliveira, F. K. F. (2026) · Research Society and Development · doi:10.33448/rsd-v15i5.51085
Podder, A., Liew, Y. J., Cary, G. A., Carter, G. W., & Uyar, A. (2026) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.70264
Tanaka, F., Taoka, T., Umino, M., Kogue, R., Ishikawa, H., Ii, Y., Shindo, A., Sakuma, H., & Maeda, M. (2026) · Biomedicines · doi:10.3390/biomedicines14061217
椎野, 顯., Shiino, A., Shirakashi, Y., Ishida, M., & Tanigaki, K. (2021) · Institutional Repositories DataBase (IRDB)
Dunlop, S. R., Lincoln, S., Peng, Z., Graff‐Radford, N. R., Lachner, C., Day, G. S., Tranovich, J. F., Reichard, R. R., Dickson, D. W., Petersen, R. C., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.01.735558
Self-citationJordan, D. M., Kritzer, E., Thompson, R. C., Lund, A. N., Patel, T., Grice, A. B., John, D., Initiative, A. D. N., Initiative, A. D. N., Goate, A., et al. (2026) · medRxiv · doi:10.64898/2026.07.07.26356710
Vamanu, A., Borza, L. R., Popa, L. L., Maștaleru, A., Covali, R. A., Bilcu, R.-V., Socolov-Mihaita, S. A., Dima-Cozma, L. C., Cozma, S. R., Șerban, R., et al. (2026) · Balneo and PRM Research Journal · doi:10.12680/balneo.2026.1062 · Cited by 1
Using CA1 rather than the whole hippocampus to capture tau-PET Braak stage II
Aumont, É., Trudel, L., Hall, B. J., Chan, T., Hosseini, S. A., Macedo, A. C., Therriault, J., Arias, J. F., Lebrun, A., Oliva-Lopez, D., et al. (2026) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-026-08074-z
Stark, D., Shin, H., Muenster, N., Federmann, L., Ritter, K., & Initiative, A. D. N. (2026) · medRxiv · doi:10.64898/2026.07.17.26358326
FastEBM: Fast, Scalable, and Uncertainty-Aware Event-Based Disease Progression ModelingPreprint
Javid, S., Nir, T. M., Zhu, A. H., Bhatt, R. R., Aksman, L., Jahanshad, N., & Initiative, A. D. N. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.18.739221
Huang, C., Watanabe, K., Kosaka, Y., & Nihey, F. (2026) · IEEE International Conference on Healthcare Informatics (ICHI) · doi:10.1109/ichi69079.2026.00225
EOAD-Signature Atrophy Predicts Dementia in Early-Onset MCI due to Alzheimer Disease
Paranhos, T., Katsumi, Y., Brickhouse, M. J., Eloyan, A., Eckbo, R., Zaitsev, A., Du, A., Joie, R. L., Thangarajah, M., Taurone, A., et al. (2026) · Neurology · doi:10.1212/wnl.0000000000218519
Self-citationTremblay, C., Freiburghaus, T., Pawlik, D., Hauer, K. O., Serrano, G. E., Zeighami, Y., Dadar, M., Intorcia, A. J., Ossenkoppele, R., Pontecorvo, M. J., et al. (2026) · Journal of Neuropathology & Experimental Neurology · doi:10.1093/jnen/nlag093
Le, N. H., Ishrat, S., Yaghooti, B., Murad, T., Sapkota, R., Thakuri, D. S., Wong, D. F., Cruchaga, C., Initiative, A. D. N., & Chand, G. B. (2026) · medRxiv · doi:10.64898/2026.09.02.26361668
Mao, C., Qiu, Y., Li, B., Jiang, Y., Bao, J., You, Y., Wang, T., Li, Y., Chu, S., Jin, W., et al. (2026) · NeuroImage · doi:10.1016/j.neuroimage.2026.122215
Data-driven subtypes of Alzheimer’s Disease: A multicohort studyPreprint
Metz, A., Polizzi, C., Moqadam, R., Chadwick, K., Tremblay, C., Chen, Z., Zeighami, Y., Villeneuve, S., Initiative, A. D. N., & Dadar, M. (2026) · medRxiv · doi:10.64898/2026.09.09.26362683
Tansey, M. G., Bozeat, S., Ackerman, P., Atri, A., Barnum, C. J., Brundin, P., de Carvalho, C. M. A., Fleisher, A., Graf, A., Head, E., et al. (2026) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.70287
Self-citationLaureyssen, C., Thal, D. R., & Sleegers, K. (2026) · Acta Neuropathologica · doi:10.1007/s00401-026-03085-4
Uncovering heterogeneous effects via localized feature selection
Liu, X., Gu, J., Chen, Z., Chu, B. B., Liu, L., Morrison, T., Butler, R. R., Edelson, J. L., Li, J., Longo, F. M., et al. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2527033123
Atypical Alzheimer disease: a multi-axis framework toward defining heterogeneity
Grinberg, L. T., & Murray, M. E. (2026) · Nature Reviews Neurology · doi:10.1038/s41582-026-01267-y
Self-citationGG-AE: Genetically-Guided Autoencoder for Disentangling Structural Networks of Brain Atrophy
Pian, M. D., Wen, J., & Davatzikos, C. A. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-38239-9_23
Zhang, J., Yu, Z., Zhang, X., & Wang, H. (2026) · npj Dementia · doi:10.1038/s44400-026-00124-5
The Adult Neurogenesis Theory of Alzheimer’s Disease Predicts Where Tauopathy Develops in the Brain
Abbate, C. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27198776
Salvadó, G., Groot, C., Wisse, L. E. M., Vogel, J. W., Beach, T. G., Serrano, G. E., Reiman, E. M., Schneider, J. A., Bennett, D. A., Ossenkoppele, R., et al. (2026) · Acta Neuropathologica · doi:10.1007/s00401-026-03095-2
Heterogeneous progression of AT(N) biomarkers in data-driven subtypes of Alzheimer’s disease
Teng, Z., Hu, M., Zhang, Z., Zhou, M., Yin, P., & Initiative, T. A. D. N. (2026) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2026.1902282
Sasaki, S. (2026) · Journal of Alzheimer s Disease Reports · doi:10.1177/25424823261496507
He, Z., Zeng, J., Wang, G., Li, Y., & Zhang, F. (2026) · MedComm · doi:10.1002/mco2.71090
Avant, J. S. (2013) · Digital Scholarship - UNLV (University of Nevada Reno)
Clinical aspects of cerebral small vessel disease
Pantoni, L., & Gorelick, P. B. (2014) · Cambridge University Press eBooks · doi:10.1017/cbo9781139382694.019
Metadata
- Authors
- Murray, M. E., Graff-Radford, N. R., Ross, O. A., Petersen, R. C., Duara, R., & Dickson, D. W.
- Affiliations
- Mayo Clinic (US)
- Mount Sinai Medical Center (US)
- Corresponding author
- Dickson, Dennis W
- Venue
- The Lancet Neurology
- Publisher
- Elsevier BV
- Published
- 2011-09
- Volume
- 10
- Issue
- 9
- Pages
- 785-796
- ISSN
- 1474-4422 (ISSN-L)
- PMC
- PMC3175379
- OpenAlex
- W2075444764
- Cited by
- 972
- References
- 44
- Citations by year
- 2026: 60 · 2025: 80 · 2024: 78 · 2023: 96 · 2022: 80 · 2021: 104 · 2020: 70 · 2019: 73 · 2018: 56 · 2017: 50 · 2016: 55 · 2015: 37 · 2014: 36 · 2013: 54 · 2012: 35
- FWCI
- 29.28
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- The Lancet Neurology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Mayo Clinic
- National Institutes of Health
- National Institute on Aging (P50‐AG16574, U01AG06786, P50 AG215711, P01AG03949, U01AG006786, P01AG003949, R21AG038736, P50AG025711, P01AG017216, P50AG016574)
- National Institute of Neurological Disorders and Stroke (P50NS072187)
- 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
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, neurofibrillary tangles, Braak staging, hippocampal sparing, hippocampal atrophy, tau pathology, clinical features, atypical Alzheimer's disease, sex differences, age at death, genetic risk factors
- MeSH terms
- Adult, Aged, Aged, 80 and over, Alzheimer Disease, Female, Hippocampus, Humans, Limbic System, Male, Middle Aged, Retrospective Studies, Cohort Studies, Neurofibrillary Tangles, tau Proteins, Apolipoprotein E4
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
