Proteomic clusters underlie heterogeneity in preclinical Alzheimer’s disease progression
Open accessAbstract
Heterogeneity in progression to Alzheimer's disease (AD) poses challenges for both clinical prognosis and clinical trial implementation. Multiple AD-related subtypes have previously been identified, suggesting differences in receptivity to drug interventions. We identified early differences in preclinical AD biomarkers, assessed patterns for developing preclinical AD across the amyloid-tau-(neurodegeneration) [AT(N)] framework, and considered potential sources of difference by analysing the CSF proteome. Participants (n = 10) enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center completed four or more lumbar punctures. These individuals were cognitively normal at baseline. Cerebrospinal fluid measures of amyloid-β (Aβ)42, phosphorylated tau (pTau181), and neurofilament light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including PET amyloid and tau, and structural MRI, were repeatedly obtained when available. Individuals were staged according to the amyloid-tau-(neurodegeneration) framework. Growth mixture modelling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau181 and Aβ42. Two groups (AD Biomarker Positive and Intermediate AD Biomarker) showed distinct progression from normal biomarker status to having biomarkers consistent with preclinical AD. A third group (AD Biomarker Negative) did not develop abnormal AD biomarkers over time. Participants grouped by CSF trajectories were re-classified using only proteomic profiles (AUCAD Biomarker Positive versus AD Biomarker Negative = 0.857, AUCAD Biomarker Positive versus Intermediate AD Biomarkers = 0.525, AUCIntermediate AD Biomarkers versus AD Biomarker Negative = 0.952). We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified some individuals who became amyloid positive before the age of 50 years. A second group, Intermediate AD Biomarkers, developed elevated CSF ptau181 significantly before becoming amyloid positive. A third group were AD Biomarker Negative over repeated testing. Our results could influence the selection of participants for specific treatments (e.g. amyloid-reducing versus other agents) in clinical trials. CSF proteome analysis highlighted additional non-AT(N) biomarkers for potential therapies, including blood–brain barrier-, vascular-, immune-, and neuroinflammatory-related targets.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
Proteomic clustering has identified subgroups particularly responsive to drugs that modulate synaptic function and restore blood-brain barrier integrity.
“Proteomic clustering has identified subgroups particularly responsive to drugs that modulate synaptic function and restore BBB integrity342,345,347,350,352,399,400.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [347]
Adding neuroimaging data enriches stratification by revealing distinct progression patterns across biomarker-defined subgroups.
“The addition of neuroimaging data further enriches stratification efforts by revealing distinct progression patterns across biomarker-defined subgroups347,401,402.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [347]
Cites
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-citationHypothetical 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 · see citing works
Functional mapping and annotation of genetic associations with FUMA
Watanabe, K., Taskesen, E., van Bochoven, A., & Posthuma, D. (2017) · Nature Communications · doi:10.1038/s41467-017-01261-5 · Cited by 4,083 · see citing works
2020 Alzheimer's disease facts and figures
(2020) · Alzheimer's & Dementia · doi:10.1002/alz.12068 · Cited by 2,353 · see citing works
Ruppert, D., WAND, M. P., & Carroll, R. J. (2003) · Cambridge University Press eBooks · doi:10.1017/cbo9780511755453 · Cited by 2,153 · see citing works
Hansson, O., Zetterberg, H., Buchhave, P., Londos, E., Blennow, K., & Minthon, L. (2006) · The Lancet Neurology · doi:10.1016/s1474-4422(06)70355-6 · Cited by 1,700 · see citing works
Morris, J. C. (1997) · International Psychogeriatrics · doi:10.1017/s1041610297004870 · Cited by 1,641 · see citing works
Self-citationFagan, A. M., Mintun, M. A., Mach, R. H., Lee, S., Dence, C. S., Shah, A. R., LaRossa, G. N., Spinner, M. L., Klunk, W. E., Mathis, C. A., et al. (2006) · Annals of Neurology · doi:10.1002/ana.20730 · Cited by 1,246 · see citing works
Self-citationDickerson, B. C., Bakkour, A., Salat, D. H., Feczko, E., Pacheco, J., Greve, D. N., Grodstein, F., Wright, C. I., Blacker, D., Rosas, H. D., et al. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn113 · Cited by 1,153 · see citing works
Self-citationRam, N., & Grimm, K. J. (2009) · International Journal of Behavioral Development · doi:10.1177/0165025409343765 · Cited by 1,143 · see citing works
Correction for partial volume effects in PET: principle and validation.
ROUSSET, O. G., Ma, Y., & Evans, A. C. (1998) · PubMed · Cited by 919 · see citing works
<i>APOE</i> predicts amyloid‐beta but not tau Alzheimer pathology in cognitively normal aging
Morris, J. C., Roe, C. M., Xiong, C., Fagan, A. M., Goate, A. M., Holtzman, D. M., & Mintun, M. A. (2010) · Annals of Neurology · doi:10.1002/ana.21843 · Cited by 830 · see citing works
Self-citation14-3-3 proteins: A historic overview
Aitken, A. (2006) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2006.03.005 · Cited by 829 · see citing works
Tang, M.-X. (1998) · JAMA · doi:10.1001/jama.279.10.751 · Cited by 771 · see citing works
Molecular Biologist's Guide to Proteomics
Graves, P. R., & Haystead, T. (2002) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.66.1.39-63.2002 · Cited by 691 · see citing works
On the path to 2025: understanding the Alzheimer’s disease continuum
Aisen, P. S., Cummings, J., Jack, C. R., Morris, J. C., Sperling, R., Frölich, L., Jones, R. W., Dowsett, S. A., Matthews, B. R., Raskin, J., et al. (2017) · Alzheimer's Research & Therapy · doi:10.1186/s13195-017-0283-5 · Cited by 556 · see citing works
Self-citationGWAS of Cerebrospinal Fluid Tau Levels Identifies Risk Variants for Alzheimer’s Disease
Cruchaga, C., Kauwe, J. S. K., Harari, O., Jin, S. C., Cai, Y., Karch, C. M., Benitez, B. A., Jeng, A. T., Skorupa, T., Carrell, D., et al. (2013) · Neuron · doi:10.1016/j.neuron.2013.02.026 · Cited by 383 · see citing works
Self-citationMolecular mechanisms of aging-associated inflammation.
Sarkar, D., & Fisher, P. (2006) · Cancer Letters · doi:10.1016/j.canlet.2005.04.009 · Cited by 379 · see citing works
Assessment of Racial Disparities in Biomarkers for Alzheimer Disease
Morris, J. C., Schindler, S. E., McCue, L. M., Moulder, K. L., Benzinger, T. L. S., Cruchaga, C., Fagan, A. M., Grant, E., Gordon, B. A., Holtzman, D. M., et al. (2019) · JAMA Neurology · doi:10.1001/jamaneurol.2018.4249 · Cited by 366 · see citing works
Self-citationAPOE2: protective mechanism and therapeutic implications for Alzheimer’s disease
Li, Z., Shue, F., Zhao, N., Shinohara, M., & Bu, G. (2020) · Molecular Neurodegeneration · doi:10.1186/s13024-020-00413-4 · Cited by 306 · see citing works
A Registration and Interpolation Procedure for Subvoxel Matching of Serially Acquired MR Images
Hajnal, J. V., Saeed, N., Soar, E. J., Oatridge, A., YOUNG, I. R., & Bydder, G. M. (1995) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-199503000-00022 · Cited by 303 · see citing works
Sutphen, C. L., Jasielec, M. S., Shah, A. R., Macy, E. M., Xiong, C., Vlassenko, A. G., Benzinger, T. L. S., Stoops, E., Vanderstichele, H., Brix, B., et al. (2015) · JAMA Neurology · doi:10.1001/jamaneurol.2015.1285 · Cited by 294 · see citing works
Self-citationYang, C., Farias, F. H. G., Ibanez, L., Suhy, A., Sadler, B., Fernandez, M. V., Wang, F., Bradley, J. L., Eiffert, B., Bahena, J. A., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00886-6 · Cited by 290 · see citing works
Self-citationCerebrospinal fluid biomarkers measured by Elecsys assays compared to amyloid imaging
Schindler, S. E., Gray, J. D., Gordon, B. A., Xiong, C., Batrla‐Utermann, R., Quan, M., Wahl, S., Benzinger, T. L. S., Holtzman, D. M., Morris, J. C., et al. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.01.013 · Cited by 284 · see citing works
Self-citationReducing between scanner differences in multi-center PET studies
Joshi, A., Koeppe, R. A., & Fessler, J. A. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.01.057 · Cited by 247 · see citing works
Partial volume correction in quantitative amyloid imaging
Su, Y., Blazey, T. M., Snyder, A. Z., Raichle, M. E., Marcus, D. S., Ances, B. M., Bateman, R. J., Cairns, N. J., Aldea, P., Cash, L., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.11.058 · Cited by 247 · see citing works
Self-citationQuantitative Analysis of PiB-PET with FreeSurfer ROIs
Su, Y., D'Angelo, G. M., Vlassenko, A. G., Zhou, G., Snyder, A. Z., Marcus, D. S., Blazey, T. M., Christensen, J. J., Vora, S., Morris, J. C., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0073377 · Cited by 246 · see citing works
Self-citationCSF biomarkers predict a more malignant outcome in Alzheimer disease
Wallin, A., Blennow, K., Zetterberg, H., Londos, E., Minthon, L., & Hansson, O. (2010) · Neurology · doi:10.1212/wnl.0b013e3181dd4dd8 · Cited by 223 · see citing works
Pathophysiological subtypes of Alzheimer’s disease based on cerebrospinal fluid proteomics
Tijms, B. M., Gobom, J., Reus, L. M., Jansen, I. E., Hong, S., Dobričić, V., Kilpert, F., ten Kate, M., Barkhof, F., Tsolaki, M., et al. (2020) · Brain · doi:10.1093/brain/awaa325 · Cited by 192 · see citing works
Gordon, B. A., Friedrichsen, K., Brier, M., Blazey, T., Su, Y., Christensen, J., Aldea, P., McConathy, J., Holtzman, D. M., Cairns, N. J., et al. (2016) · Brain · doi:10.1093/brain/aww139 · Cited by 184 · see citing works
Self-citationTau Protein and Its Role in Blood–Brain Barrier Dysfunction
Michalicová, A., Majerová, P., & Kováč, A. (2020) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2020.570045 · Cited by 179 · see citing works
AV-1451 PET imaging of tau pathology in preclinical Alzheimer disease: Defining a summary measure
Mishra, S., Gordon, B. A., Su, Y., Christensen, J. J., Friedrichsen, K. A., Jackson, K., Hornbeck, R. C., Balota, D. A., Cairns, N. J., Morris, J. C., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.050 · Cited by 173 · see citing works
Self-citationSupervised clustering of genes
Dettling, M., & Bühlmann, P. (2002) · Genome biology · doi:10.1186/gb-2002-3-12-research0069 · Cited by 164 · see citing works
Subgroups of Alzheimer's disease based on cerebrospinal fluid molecular markers
Iqbal, K., Flory, M. J., Khatoon, S., Soininen, H. S., Pirttilä, T., Lehtovirta, M., Alafuzoff, I. I., Blennow, K., Andreasen, N., Vanmechelen, E., et al. (2005) · Annals of Neurology · doi:10.1002/ana.20639 · Cited by 163 · see citing works
Targeted brain proteomics uncover multiple pathways to Alzheimer's dementia
Yu, L., Petyuk, V. A., Gaiteri, C., Mostafavi, S., Young‐Pearse, T., Shah, R. C., Buchman, A. S., Schneider, J. A., Piehowski, P. D., Sontag, R. L., et al. (2018) · Annals of Neurology · doi:10.1002/ana.25266 · Cited by 124 · see citing works
Cellular, synaptic, and biochemical features of resilient cognition in Alzheimer’s disease
Arnold, S. E., Louneva, N., Cao, K., Wang, L.-S., Han, L.-Y., Wolk, D. A., Negash, S., Leurgans, S. E., Schneider, J. A., Buchman, A. S., et al. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2012.03.004 · Cited by 123 · see citing works
CSF biomarkers in relationship to cognitive profiles in Alzheimer disease
van der Vlies, A. E., Verwey, N. A., Bouwman, F. H., Blankenstein, M. A., Klein, M., Scheltens, P., & van der Flier, W. M. (2009) · Neurology · doi:10.1212/01.wnl.0000345014.48839.71 · Cited by 106 · see citing works
CSF biomarker changes precede symptom onset of mild cognitive impairment
Moghekar, A., Li, S., Lu, Y., Li, M., Wang, M.-C., Albert, M., O’Brien, R., & For the BIOCARD Research Team (2013) · Neurology · doi:10.1212/01.wnl.0000435558.98447.17 · Cited by 103 · see citing works
Grothe, M. J., Moscoso, A., Ashton, N. J., Karikari, T. K., Lantero‐Rodriguez, J., Snellman, A., Zetterberg, H., Blennow, K., Schöll, M., & Initiative, A. D. N. (2021) · Neurology · doi:10.1212/wnl.0000000000012513 · Cited by 96 · see citing works
Small, B. J., & Bäckman, L. (2007) · Cortex · doi:10.1016/s0010-9452(08)70682-8 · Cited by 86 · see citing works
A Systematic Review of Longitudinal Studies Which Measure Alzheimer’s Disease Biomarkers
Lawrence, E., Vegvari, C., Ower, A. K., Hadjichrysanthou, C., de Wolf, F., & Anderson, R. M. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-170261 · Cited by 84 · see citing works
Ithapu, V. K., Singh, V., Lindner, C., Austin, B. P., Chris Hinrichs, A., Carlsson, C. M., Bendlin, B. B., & Johnson, S. C. (2014) · Human Brain Mapping · doi:10.1002/hbm.22472 · Cited by 83 · see citing works
Spatially distinct atrophy is linked to β-amyloid and tau in preclinical Alzheimer disease
Wang, L. Y., Benzinger, T. L. S., Hassenstab, J. J., Blazey, T., Owen, C., Liu, J., Fagan, A. M., Morris, J. C., & Ances, B. M. (2015) · Neurology · doi:10.1212/wnl.0000000000001401 · Cited by 79 · see citing works
Self-citationInsel, P. S., Ossenkoppele, R., Gessert, D., Jagust, W., Landau, S. M., Hansson, O., Weiner, M. W., & Mattsson, N. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00281 · Cited by 75 · see citing works
Mendonça, C. F., Kuras, M., Nogueira, F. C. S., Plá, I., Hortobágyi, T., Csiba, L., Palkovits, M., Renner, É., Döme, P., Marko‐Varga, G., et al. (2019) · Neurobiology of Disease · doi:10.1016/j.nbd.2019.104509 · Cited by 68 · see citing works
Cognitive Reserve in Model Systems for Mechanistic Discovery: The Importance of Longitudinal Studies
McQuail, J. A., Dunn, A. R., Stern, Y., Barnes, C. A., Kempermann, G., Rapp, P. R., Kaczorowski, C. C., & Foster, T. C. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.607685 · Cited by 65 · see citing works
Downregulation of 14-3-3 Proteins in Alzheimer’s Disease
Gu, Q., Cuevas, E., Raymick, J. B., Kanungo, J., & Sarkar, S. (2019) · Molecular Neurobiology · doi:10.1007/s12035-019-01754-y · Cited by 58 · see citing works
Su, Y., Blazey, T. M., Owen, C. J., Christensen, J. J., Friedrichsen, K., Joseph-Mathurin, N., Wang, Q., Hornbeck, R. C., Ances, B. M., Snyder, A. Z., et al. (2016) · PLOS ONE · doi:10.1371/journal.pone.0152082 · Cited by 56 · see citing works
Self-citationSørensen, Ø., Walhovd, K. B., & Fjell, A. M. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117596 · Cited by 50 · see citing works
Groot, C., Smith, R. A., Stomrud, E., Binette, A. P., Leuzy, A., Wuestefeld, A., Wisse, L. E. M., Palmqvist, S., Mattsson, N., Janelidze, S., et al. (2022) · Brain · doi:10.1093/brain/awac329 · Cited by 50 · see citing works
Time between milestone events in the Alzheimer's disease amyloid cascade
Insel, P. S., Donohue, M., Berron, D., Hansson, O., & Mattsson, N. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117676 · Cited by 48 · see citing works
Characterization of extrastriatal D2 in vivo specific binding of [18F](N‐methyl)benperidol using PET
Eisenstein, S. A., Koller, J. M., Piccirillo, M. L., Kim, A., Antenor‐Dorsey, J. A. V., Videen, T. O., Snyder, A. Z., Karimi, M., Moerlein, S. M., BLACK, K. J., et al. (2012) · Synapse · doi:10.1002/syn.21566 · Cited by 44 · see citing works
Modulation of SPARC/Hevin Proteins in Alzheimer’s Disease Brain Injury
Strunz, M., Jarrell, J. T., Cohen, D. S., Rosin, E. R., Vanderburg, C. R., & Huang, X. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-181032 · Cited by 43 · see citing works
Cognitive and functional progression in Alzheimer disease: A prediction model of latent classes
Haaksma, M. L., Calderón‐Larrañaga, A., Rikkert, M. G. M. O., Melis, R. J. F., & Leoutsakos, J. (2018) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.4893 · Cited by 39 · see citing works
Biomarkers: Our Path Towards a Cure for Alzheimer Disease
Tarawneh, R. M. (2020) · Biomarker Insights · doi:10.1177/1177271920976367 · Cited by 37 · see citing works
Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease
Dincer, A., Gordon, B. A., Hari‐Raj, A., Keefe, S., Flores, S. E., McKay, N. S., Paulick, A. M., Shady, K., Feldman, R. L., Hornbeck, R. C., et al. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102491 · Cited by 35 · see citing works
Self-citationBoerwinkle, A. H., Wisch, J. K., Chen, C. D., Gordon, B. A., Butt, O. H., Schindler, S. E., Sutphen, C. L., Flores, S. E., Dincer, A., Benzinger, T. L. S., et al. (2021) · Neurology · doi:10.1212/wnl.0000000000012123 · Cited by 28 · see citing works
Self-citationCerebrospinal fluid dynamics and discordant amyloid biomarkers
Graff‐Radford, J., Jones, D. T., Wiste, H. J., Cogswell, P. M., Weigand, S. D., Lowe, V. J., Elder, B. D., Vemuri, P., van Harten, A. C., Mielke, M. M., et al. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2021.10.017 · Cited by 24 · see citing works
Tijms, B. M., Gobom, J., Teunissen, C. E., Dobričić, V., Tsolaki, M., Verhey, F. R. J., Popp, J., Martínez‐Lage, P., Vandenberghe, R. R., Lleó, A., et al. (2021) · Proteomes · doi:10.3390/proteomes9030036 · Cited by 23 · see citing works
Qiu, P., Zeng, M., Kuang, W., Meng, S. S., Cai, Y., Wang, H., & Wan, Y. (2020) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.5334 · Cited by 20 · see citing works
Untangling the tau microtubule-binding region
Toombs, J., & Zetterberg, H. (2020) · Brain · doi:10.1093/brain/awaa468 · Cited by 8 · see citing works
Cruchaga, C., Sung, Y. J., Yang, C., Wang, F., Suhy, A., Norton, J. B., Novotny, B. C., Eteleeb, A. M., Fagan, A. M., Bateman, R. J., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-923492/v1 · Cited by 4 · see citing works
Self-citationLin, W., Donohue, M., Insel, P. S., Schwartzman, A., & Thompson, W. K. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.10.434854 · Cited by 3 · see citing works
Flagged first, then by citations
1 of the 64 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Emerging diagnostics and therapeutics for Alzheimer disease
Self, W. K., & Holtzman, D. M. (2023) · Nature Medicine · doi:10.1038/s41591-023-02505-2 · Cited by 381 · see citing works
Self-citationDisease staging of Alzheimer’s disease using a CSF-based biomarker model
Salvadó, G., Horie, K., Barthélemy, N. R., Vogel, J. W., Binette, A. P., Chen, C. D., Aschenbrenner, A. J., Gordon, B. A., Benzinger, T. L. S., Holtzman, D. M., et al. (2024) · Nature Aging · doi:10.1038/s43587-024-00599-y · Cited by 120 · see citing works
Self-citationRen, F., Wei, J., Chen, Q., Hu, M., Yu, L., Mi, J., Zhou, X., Qin, D., Wu, J., & Wu, A. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.07.030 · Cited by 97 · see citing works
Nilsson, J., Binette, A. P., Palmqvist, S., Brum, W. S., Janelidze, S., Ashton, N. J., Spotorno, N., Stomrud, E., Gobom, J., Zetterberg, H., et al. (2024) · Brain · doi:10.1093/brain/awae032 · Cited by 82 · see citing works
Novel CSF tau biomarkers can be used for disease staging of sporadic Alzheimer’s
Salvadó, G., Horie, K., Barthélemy, N. R., Vogel, J. W., Binette, A. P., Chen, C. D., Aschenbrenner, A. J., Gordon, B. A., Benzinger, T. L. S., Holtzman, D. M., et al. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.075367 · Cited by 13 · see citing works
Self-citationToward a new nosology of neurodegenerative diseases
Menéndez‐González, M. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13041 · Cited by 10 · see citing works
Smith, B. J., Guest, P. C., & Martins‐de‐Souza, D. (2024) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-061522-041154 · Cited by 4 · see citing works
Wei, X., Zhang, T., Xiong, R., Zhang, Q., Zhang, J., Jin, Z., & Li, L. (2026) · Translational Psychiatry · doi:10.1038/s41398-026-03902-0 · Cited by 2 · see citing works
Tau-Connectome Subtypes and Solanezumab Response in Preclinical Alzheimer’s DiseasePreprint
Abuwarda, H., Tsai, W., Ding, S., Elhassan, M. O. E., Shen, X., Zhao, Y., Constable, R. T., & Fredericks, C. A. (2025) · medRxiv · doi:10.1101/2025.09.13.25335690
Reframing Alzheimer's disease as a complex adaptive system: More than an amyloid beta–tau connection
Giorelli, M. (2026) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.70256
- Authors
- Wisch, J. K., Butt, O. H., Gordon, B. A., Schindler, S. E., Fagan, A. M., Henson, R. L., Yang, C., Boerwinkle, A. H., Benzinger, T. L. S., Holtzman, D. M., Morris, J. C., Cruchaga, C., & Ances, B. M.
- Affiliations
- Washington University in St. Louis (US)
- Corresponding author
- Ances, Beau M
- ORCID
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2022-12-21
- Volume
- 146
- Issue
- 7
- Pages
- 2944-2956
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- PMC
- PMC10316757
- OpenAlex
- W4312057911
- Cited by
- 11
- References
- 64
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 3 · 2023: 3
- FWCI
- 1.47
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Brain (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (R01NR012907, R01NR012657, R01NR014449, RF1AG053303, RF1AG058501, U01AG058922, K01 AG053474, P30 AG066444, P01AG003991, P01AG026276, U19 AG032438, U19 AG024904)
- Barnes-Jewish Hospital
- Washington University Institute of Clinical and Translational Sciences Foundation (TR000448)
- Hope Center for Neurological Disorders
- the Paula and Rodger O. Riney Fund
- the Daniel J Brennan MD Fund
- Fred Simmons Olga Mohan Fund and the Chuck Zuckerberg Initiative
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Cerebrospinal fluid and hydrocephalus
- Keywords
- preclinical Alzheimer's disease, Alzheimer's disease progression, CSF proteome, amyloid-beta 42, phosphorylated tau 181, neurofilament light chain, growth mixture modeling, biomarker trajectories, clinical trial participant selection, neuroinflammation, blood-brain barrier, vascular risk factors
- MeSH terms
- Alzheimer Disease, Humans, Middle Aged, Biomarkers, Amyloid beta-Peptides, tau Proteins, Disease Progression, Proteome, Proteomics
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
