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Tau biomarkers in Alzheimer's disease: towards implementation in clinical practice and trials
Open accessAbstract
Background Deposition of tau aggregates is a pathological hallmark of Alzheimer's disease that is closely linked both spatially and temporally to emergence of neurodegeneration and manifestation of clinical symptoms. There is an urgent need for accurate PET, CSF, and plasma biomarkers of tau pathology to improve the diagnostic process in clinical practice and the selection of participants and monitoring of treatment effects in trials.Recent developments Innovative second-generation tau-PET tracers with high affinity and selectivity to tau pathology in Alzheimer's disease have enabled detection of tau pathology in medial temporal lobe subregions that are affected in the earliest disease stages. Furthermore, novel but common tau spreading subtypes have been discovered using tau-PET, suggesting much greater interindividual differences in the distribution of tau pathology across the brain than previously assumed. In the CSF biomarker field, novel phosphorylated tau (p-tau) assays have been introduced that better reflect tau tangle load than established CSF biomarkers of tau pathology. The advent of cost-effective and accessible blood-based biomarkers for tau pathophysiology (ie, p-tau181, p-tau217, and p-tau231) might transform the Alzheimer's disease field, as these biomarkers correlate with post-mortem Alzheimer's disease pathology, differentiate Alzheimer's disease from other types of dementia, and predict future progression from normal cognition and mild cognitive impairment to Alzheimer's disease. In controlled investigational settings, improvements in tau-PET and biofluid p-tau markers have led to earlier disease detection, more accurate diagnostic methods, and refinement of prognosis. The anti-tau therapy landscape is rapidly evolving, with multiple ongoing phase 1 and 2 trials of post-translational modification of tau, tau immunotherapy, tau aggregation inhibitors, and targeting production of tau and reduction of intracellular tau levels. Neuroimaging and biofluid tau markers hold potential for optimising such clinical trials by augmenting participant selection, providing evidence of target engagement, and monitoring treatment efficacy. WHERE NEXT?: Major challenges to overcome are the high cost of tau-PET, partial sensitivity to detect early-stage Alzheimer's disease pathology, and off-target tracer binding. Prospective validation studies of biofluid p-tau markers are needed, and assay-related preanalytical and analytical factors need further refinement. Future studies should focus on demonstrating the diagnostic and prognostic accuracy of tau biomarkers-blood-based markers in particular-in non-tertiary settings, such as primary care, which is characterised by a diverse population with medical comorbidities. Large-scale head-to-head studies are needed across different stages of Alzheimer's disease to determine which tau biomarker is optimal in various clinical scenarios, such as early diagnosis, differential diagnosis, and prognosis, and for aspects of clinical trial design, such as proving target engagement, optimising participant selection, and refining monitoring of treatment effects.
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“it is crucial to find ways to reduce the need for PET scans due to their relative inaccessibility and costliness, while still preserving the ability to estimate the load and distribution of AD pathology as accurately and comprehensively. 12 , 13”
From Machine learning prediction of tau‐PET in Alzheimer's disease using plasma, MRI, and clinical data (2025) · cites this paper as [12]
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“Tau‐PET is often considered a state‐of‐the‐art outcome in AD research studies, a very accurate prognostic tool in patients with AD, and frequently used in clinical trials for AD during screening and to monitor treatment effects. 12 , 14 , 15 , 16”
From Machine learning prediction of tau‐PET in Alzheimer's disease using plasma, MRI, and clinical data (2025) · cites this paper as [12]
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“As a major component of NFTs, tau protein exhibits a spatial and temporal distribution that strongly correlates with clinical symptoms, making it a highly specific pathological biomarker in AD patients.152”
From Recent advances in Alzheimer's disease: Mechanisms, clinical trials and new drug development strategies. (2024) · cites this paper as [152]
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“Tau‐PET is often considered a state‐of‐the‐art outcome in AD research studies, a very accurate prognostic tool in patients with AD, and frequently used in clinical trials for AD during screening and to monitor treatment effects. 12 , 14 , 15 , 16”
From Machine learning prediction of tau‐PET in Alzheimer's disease using plasma, MRI, and clinical data (2025) · cites this paper as [12]
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“Tau‐PET is often considered a state‐of‐the‐art outcome in AD research studies, a very accurate prognostic tool in patients with AD, and frequently used in clinical trials for AD during screening and to monitor treatment effects. 12 , 14 , 15 , 16”
From Machine learning prediction of tau‐PET in Alzheimer's disease using plasma, MRI, and clinical data (2025) · cites this paper as [12]
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“Plasma tau measurement could thus be used as a screening test in early-stage clinical trials to enrich trial participation with individuals more likely to have AD pathology (76, 77, 90).”
From All the Tau We Cannot See (2023) · cites this paper as [90]
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Cites
Scheltens, P., De Strooper, B., Kivipelto, M., Holstege, H., Chételat, G., Teunissen, C. E., Cummings, J., & van der Flier, W. M. (2021) · The Lancet · doi:10.1016/s0140-6736(20)32205-4 · Cited by 5,465
Nelson, P. T., Alafuzoff, I., Bigio, E. H., Bouras, C., Braak, H., Cairns, N. J., Castellani, R. J., Crain, B. J., Davies, P., Tredici, K. D., et al. (2012) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/nen.0b013e31825018f7 · Cited by 2,050
Donanemab in Early Alzheimer’s Disease
Mintun, M. A., Lo, A. C., Duggan Evans, C., Wessels, A. M., Ardayfio, P. A., Andersen, S. W., Shcherbinin, S., Sparks, J., Sims, J. R., Brys, M., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2100708 · Cited by 1,728
Palmqvist, S., Janelidze, S., Quiroz, Y. T., Zetterberg, H., Lopera, F., Stomrud, E., Su, Y., Chen, Y., Serrano, G. E., Leuzy, A., et al. (2020) · JAMA · doi:10.1001/jama.2020.12134 · Cited by 1,603
Self-citationKarikari, T. K., Pascoal, T. A., Ashton, N. J., Janelidze, S., Benedet, A. L., Rodriguez, J. L., Chamoun, M., Savard, M., Kang, M. S., Therriault, J., et al. (2020) · The Lancet Neurology · doi:10.1016/s1474-4422(20)30071-5 · Cited by 1,316
Self-citationJanelidze, S., Mattsson, N., Palmqvist, S., Smith, R., Beach, T. G., Serrano, G. E., Chai, X., Proctor, N. K., Eichenlaub, U., Zetterberg, H., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0755-1 · Cited by 1,247
Self-citationPET 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
Self-citationThe Intersection of Amyloid Beta and Tau at Synapses in Alzheimer’s Disease
Spires-Jones, T. L., & Hyman, B. T. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.004 · Cited by 1,201
Tau PET patterns mirror clinical and neuroanatomical variability in Alzheimer’s disease
Ossenkoppele, R., Schonhaut, D. R., Schöll, M., Lockhart, S. N., Ayakta, N., Baker, S. L., O’Neil, J. P., Janabi, M., Lazaris, A., Cantwell, A., et al. (2016) · Brain · doi:10.1093/brain/aww027 · Cited by 1,185
Self-citationBiomarkers for neurodegenerative diseases
Hansson, O. (2021) · Nature Medicine · doi:10.1038/s41591-021-01382-x · Cited by 1,159
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Mason, M., Bacioglu, M., Vivacqua, G., Spillantini, M. G., & Tolkovsky, A. M. (2023) · The Lancet Neurology · doi:10.1016/s1474-4422(23)00108-4 · Cited by 1
Sharma, A., Feng, L., Muresanu, D. F., Tian, Z. R., Lafuente, J. V., Buzoianu, A. D., Nozari, A., Bryukhovetskiy, I., Manzhulo, I., Wiklund, L., et al. (2023) · Advances in neurobiology · doi:10.1007/978-3-031-32997-5_1 · Cited by 1
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Essa, M., Ahmed, N., Kakar, A., Akber, W., Barech, S., Farooq, A., & Mumtaz, T. (2024) · doi:10.32948/ajsep.2024.03.28 · Cited by 1
Sex Differences in Alzheimer’s Disease Pathogenesis
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Sun, Y., Islam, S., Gao, Y., Nakamura, T., Tomita, T., Michikawa, M., & Zou, K. (2024) · Journal of Neurochemistry · doi:10.1111/jnc.16155 · Cited by 2
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Harput, E., Peretti, D. E., Scheffler, M., Ashton, N. J., Blennow, K., Zetterberg, H., Smith, R. A., Frisoni, G. B., Garibotto, V., & Boccalini, C. (2025) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-025-07452-3 · Cited by 1
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Suo, X., Li, Z., Zuo, C., Lan, H., Pan, N., Lui, S., & Gong, Q. (2022) · Scientia Sinica Vitae · doi:10.1360/ssv-2022-0168
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Garg, N., Choudhry, M. S., & Bodade, R. M. (2023) · International Conference on Computational Intelligence, Communication Technology and Networking (CICTN) · doi:10.1109/cictn57981.2023.10141079
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Zhang, M., Ge, M., Li, Q., Li, H., Jiao, L., & Wu, W. (2023) · Preprints.org · doi:10.20944/preprints202306.0919.v1
Yu, M., Risacher, S. L., Nho, K. T., Wen, Q., Oblak, A. L., Unverzagt, F. W., Apostolova, L. G., Farlow, M. R., Brosch, J. R., Clark, D. G., et al. (2023) · medRxiv · doi:10.1101/2023.08.12.23294017
Yu, Y., Lin, H., Chen, X., Sun, M., Wei, C., Xue, M., Gao, Y., Tang, W., Zheng, C., Li, S., et al. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4564797
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Yan, M. (2024) · International Conference on Biological Engineering and Medical Science (ICBioMed) · doi:10.1117/12.3012816
Chen, M., Feng, X., Liu, J., Wang, J., Yang, X., Yu, X., Kong, W., Sun, B., & Wu, H. (2024) · Vaccine · doi:10.1016/j.vaccine.2023.12.072
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Qi, W., Dong, N., Peiru, W. U., Fu, W., Liu, Q., Zhang, X., Wu, H., He, X., Wu, L., Ward, N., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-4458094/v1
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Ji, J., Hou, Z., He, Y., Liu, L., Xue, F., Chen, H., & Yuan, Z. (2024) · Statistics in Medicine · doi:10.1002/sim.10155
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Affeldt, A. M. (2024) · Zeitschrift für Gerontologie und Geriatrie · doi:10.1007/s00391-024-02361-w
Cambier, J., Masson, M., Masson-Boivin, C., & Dehen, H. (2024) · Elsevier eBooks · doi:10.1016/b978-2-294-78318-0.00024-0
Xie, Y., Pi, S., Zhong, J., Lu, Y., Liu, J., Li, X., Jiang, J., Li, H., Su, H., Zhao, Z., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-5219476/v1
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Pimentel, A. P. A., Rosas, B. D. P. S., Parente, C. T. C., & Rezende, G. D. O. (2024) · Revista Contemporânea · doi:10.56083/rcv4n10-192 · Cited by 24
Wang, R., Jian, Z., Yu, L., & Wang, C. (2024) · Scientia Sinica Chimica · doi:10.1360/ssc-2024-0194
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Ran, X., Li, L., Peng, M., Ruan, L.-H., Li, L., Wang, Y., Cao, J., & Yang, J. (2024) · Food Science and Human Wellness · doi:10.26599/fshw.2024.9250404
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Yu, F. (2024) · Highlights in Science Engineering and Technology · doi:10.54097/19y6pk70
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李, 越. (2025) · Advances in Clinical Medicine · doi:10.12677/acm.2025.154977
Jing, S., Wang, Y., Liu, Y., Luo, Y., Wen, X., Ma, Y., Zhu, H., Chen, G. L., & Ouyang, X. (2025) · Journal of Medical Biochemistry · doi:10.5937/jomb0-57713
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Garg, N., Garg, A., & Choudhry, M. S. (2025) · doi:10.1109/icsc64553.2025.10967815
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Tsakiri, E. N., Samiotaki, M. K., Skoulakis, E. M. C., & Papanikolopoulou, K. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26199741
Bellver-Sanchis, A., Sanchez-Arfelis, A., Choudhary, B. S., Irisarri, A., Vilella, M. R., Sukanya, S., Banerjee, D. R., Morales-García, J. A., Wüst, C., Castellanos, A., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.24.684310
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Zeng, J., Bao, Z., Huang, W., Fu, A., Liang, Z., & Zhu, H. (2025) · Journal of Alzheimer s Disease Reports · doi:10.1177/25424823251394408
LG, P., J., B. B., & Krishna, K. L. (2025) · International Journal of Applied Pharmaceutics · doi:10.22159/ijap.2025v17i6.55475
Wang, L., Yu, L., Li, J., Wang, H., Zhang, Z., Fu, Z., Yu, H., Cui, Y., & Han, L. (2025) · Microbial Pathogenesis · doi:10.1016/j.micpath.2025.108177
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Additional file 2 of Differential proteomic profile of lumbar and ventricular cerebrospinal fluid
Rostgaard, N., Olsen, M. H., Ottenheijm, M. E., Drici, L., Simonsen, A. H., Plomgaard, P., Gredal, H., Poulsen, H. H., Zetterberg, H., Blennow, K., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26563123
Kang, X., Wang, D., Zhang, L., Huang, T., Liu, S., Feng, X., Guo, Y., Zhang, Z., Wang, Z., Ren, H., et al. (2023) · Figshare · doi:10.6084/m9.figshare.26615083
Lu, J., Ma, X., Zhang, H., Xiao, Z., Li, M., Wu, J., Ju, Z., Chen, L., Zheng, L., Ge, J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26600593
Wu, J. H., Xiao, Z., Wang, M., Wu, W., Ma, X., Liang, X., Zheng, L., Ding, S., Luo, J., Cao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25210649
Additional file 1 of The dynamics of plasma biomarkers across the Alzheimer’s continuum
Guo, Y., Shen, X.-N., Wang, H.-F., Chen, S.-D., Zhang, Y.-R., Chen, S., Cui, M., Cheng, W., Dong, Q., Ma, T., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26567207
Bernick, C. B., Shan, G., Ritter, A., Ashton, N. J., Blennow, K., Lantero‐Rodriguez, J., Snellman, A., & Zetterberg, H. (2024) · Figshare · doi:10.6084/m9.figshare.26626312
Bernick, C. B., Shan, G., Ritter, A., Ashton, N. J., Blennow, K., Lantero‐Rodriguez, J., Snellman, A., & Zetterberg, H. (2024) · Figshare · doi:10.6084/m9.figshare.26626315
Additional file 1 of Differential proteomic profile of lumbar and ventricular cerebrospinal fluid
Rostgaard, N., Olsen, M. H., Ottenheijm, M. E., Drici, L., Simonsen, A. H., Plomgaard, P., Gredal, H., Poulsen, H. H., Zetterberg, H., Blennow, K., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26563120
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Gong, S.-G., Sun, Y.-Y., He, J., Wu, W.-H., Zhao, Q., Liu, P., Li, J.-L., Li, H., Luo, C., Qiu, H., et al. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5702452
Tang, P., Chen, X., Li, P., Zhang, L., Tang, B., Wen, J., Liu, Y., Kalsoom, I., & Cheng, C. (2025) · PLoS ONE · doi:10.1371/journal.pone.0338901
Nasiri, H., Farahani, S., Mozafar, M., Ghiasi, Y., Fard, A. M., Naseri, N., Khodadadi, A., Asl, A. S., Mirzapour, M., Hamidi, H., et al. (2025) · Health Science Reports · doi:10.1002/hsr2.71671
Qi, A., He, Y., Zhang, F., Liu, S., Xiang, Q., Dong, Y., Wang, B., & Zhao, Y. (2025) · Neural Regeneration Research · doi:10.4103/nrr.nrr-d-25-00851
The Dementia Cascade: From the Preclinical Stage
Chen, Q., Xu, J., Gao, H., & Cai, H. (2026) · Springer eBooks · doi:10.1007/978-981-95-5222-1_1
Gao, H., Yang, S., Ouyang, Z., Wang, Y., Tang, J., Hou, Q., Fang, Z., Shao, N., & Cai, B. (2026) · 3 Biotech · doi:10.1007/s13205-025-04679-7
Incidental 18F-Flortaucipir Uptake in Pituitary Macroadenoma
Xiong, M., Liu, Y., Luo, X., & Jiang, S. (2026) · Clinical Nuclear Medicine · doi:10.1097/rlu.0000000000006313
Alzheimer’s Disease: Bioinformatics Constructs Protein Network Related to Pyroptosis
魏, 怡. (2026) · Advances in Clinical Medicine · doi:10.12677/acm.2026.162485
Matias-Guiu, J. A., Ortega‐Madueño, I., Gil‐Moreno, M. J., Cárdenas, M. C., Saro, P. A., Puerto, J. R., López‐Carbonero, J. I., Gordillo, E. V., Aguilera, L., Carrillo-Molina, T., et al. (2026) · Journal of Neurology · doi:10.1007/s00415-026-13676-6
Patel, H., Choi, A., Weng, P. J., Karl, J. J., Joseph, S., Johnson, K. G., Berger, M., Whitson, H. E., Grewal, D. S., & Fekrat, S. (2026) · Journal of Alzheimer s Disease · doi:10.1177/13872877261423968
Dual-tracer PET/CT Imaging using 18F-AV-45 and 18F-AV-1451 for the Diagnosis of Alzheimer's Disease
Pan, Z., Han, Y., Wang, G., Zhang, S., Lu, X., Su, X., & Liu, Z. (2026) · Journal of Visualized Experiments · doi:10.3791/69479
Clinical relevance of CSF analysis in various neurodegenerative diseases
André, Z., Gaštanová, B., Kopániová, A., & Gmitterová, K. (2026) · Neurologie pro praxi · doi:10.36290/neu.2025.022
Choi, H. J., Cho, A. J., You, J. H., Park, S., Lee, S. R., & Kim, D. H. (2026) · Medicina · doi:10.3390/medicina62030529
The role of MicroRNAs in Alzheimer’s disease: from pathogenesis to therapeutic potential
Zhou, Y., Li, S., & Xiang, J. (2026) · Molecular Biology Reports · doi:10.1007/s11033-026-11746-6
Wang, L., Gao, Y., Lu, J., Jiang, Q., Wang, H., Dong, F., Zhao, Q., Guan, Y., Qi, X., Zuo, C., et al. (2026) · NeuroImage · doi:10.1016/j.neuroimage.2026.121904
D, J. H., Gowda, J., Mallamma, T., & Prakash Goudanavar, S. O. P. (2026) · SN Comprehensive Clinical Medicine · doi:10.1007/s42399-026-02299-7
Tau Accumulation Increases the Susceptibility to Effective Seizures of Electroconvulsive Therapy
Ohya, T., Arakawa, R., Sakayori, T., Nogami, T., Uchiyama, S., & Tateno, A. (2026) · Translational Psychiatry · doi:10.1038/s41398-026-04016-3
ADAS-Cog11 performance as a surrogate of tau PET burden in an Asian Alzheimer's disease cohort
Hong, Y.-J., Huang, S.-Y., Hsiao, I., Wu, H.-C., Lin, K., Huang, K., Huang, C.-C., & Hsu, J. (2026) · Journal of Alzheimer s Disease · doi:10.1177/13872877261441801
Gut microbiota composition causally linked to Alzheimer’s disease: Mendelian randomization evidence
Zhou, Y., Tang, H., Sun, Y., Li, C., Zhao, Y., & Chen, L. (2025) · Aging Research · doi:10.26599/agr.2025.9340071
Li, L., Yan, X., Cui, M. A., Yuting, W., Dou, T., & Xie, W. (2026) · Journal of Acupuncture and Tuina Science · doi:10.1007/s11726-026-1567-8
Thia, B. W. Q., Tan, D. Y. Z., Wong, B. W. X., Shen, L., Gong, L., Ling, L., Chen, C. L., & Yong, E. (2026) · Pulse · doi:10.1159/000552328
Hosseini, I., Northey, J. M., D'Cunha, N. M., Rojas, R. F., Shrestha, A., & Ghahramani, M. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1728588
Atypical involvement of Alzheimer’s tau proteins in diseases beyond tauopathies
Meng, J., Deng, Z., Zhang, J., Yu, W., Wu, X., & Lei, P. (2026) · Life Medicine · doi:10.1093/lifemedi/lnag016
Identification and application of biomarkers for Alzheimer's disease
Kim, C. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-45844-6.00030-5
Metadata
- Authors
- Ossenkoppele, R., van der Kant, R., & Hansson, O.
- Affiliations
- Lund University (SE)
- Corresponding author
- Ossenkoppele, Rik
- Venue
- The Lancet Neurology
- Publisher
- Elsevier BV
- Published
- 2022-08
- Volume
- 21
- Issue
- 8
- Pages
- 726-734
- ISSN
- 1474-4422 (ISSN-L)
- OpenAlex
- W4281564421
- Cited by
- 557
- References
- 79
- Citations by year
- 2026: 127 · 2025: 174 · 2024: 142 · 2023: 98 · 2022: 15
- FWCI
- 14.76
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The Lancet Neurology (publishedVersion)
- PubMed (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- Pure Amsterdam UMC (acceptedVersion, other-oa)
- Lund University Publications (Lund University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Deutsches Zentrum für Neurodegenerative Erkrankungen
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Clinical Neurology › Cerebrospinal fluid and hydrocephalus
- Keywords
- Alzheimer's disease, tau pathology, tau biomarkers, tau PET tracers, phosphorylated tau, cerebrospinal fluid biomarkers, blood-based biomarkers, anti-tau therapy, clinical trial participant selection, early disease detection, tau immunotherapy, tau aggregation inhibitors, dementia diagnosis, mild cognitive impairment, primary care
- MeSH terms
- Alzheimer Disease, Brain, Humans, Biomarkers, Amyloid beta-Peptides, tau Proteins, Neuroimaging, Cognitive Dysfunction
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