The DOI matches its Crossref record; 77 of the 79 references it cites were found in a registry or an index.
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.
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
“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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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]
The cited source says what the claim attributes to it.
In the citing paper
“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]
The cited source says what the claim attributes to it.
In the citing paper
“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]
In the citing paper
“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]
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
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
Self-citation
Cited by
Sorted by citations
Zhang, J., Zhang, Y., Wang, J., Xia, Y., Zhang, J., & Chen, L. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01911-3 · Cited by 1,138
“152 In recent years, there has been a heightened focus on tau deposition, including the correlation between tau deposition, brain atrophy, and glucose metabolism in both typical and atypical AD, 167,168 as well as the effects of tau deposition at the molecular and cellular levels.”
BackgroundMitochondria in oxidative stress, inflammation and aging: from mechanisms to therapeutic advances
Xu, X., Pang, Y., & Fan, X. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02253-4 · Cited by 1,016
A biological classification of Parkinson's disease: the SynNeurGe research diagnostic criteria
Höglinger, G. U., Adler, C. H., Berg, D., Klein, C., Outeiro, T. F., Poewe, W. H., Postuma, R. B., Stoessl, A. J., & Lang, A. E. (2024) · The Lancet Neurology · doi:10.1016/s1474-4422(23)00404-0 · Cited by 607
Head-to-head comparison of 10 plasma phospho-tau assays in prodromal Alzheimer’s disease
Janelidze, S., Bali, D., Ashton, N. J., Barthélemy, N. R., Vanbrabant, J., Stoops, E., Vanmechelen, E., He, Y., Dolado, A. O., Triana-Baltzer, G., et al. (2023) · Brain · doi:10.1093/brain/awac333 · Cited by 522
Self-citationOssenkoppele, R., Pichet Binette, A., Groot, C., Smith, R., Strandberg, O., Palmqvist, S., Stomrud, E., Tideman, P., Ohlsson, T., Jögi, J., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-02049-x · Cited by 496
Self-citationEmerging 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
CSF MTBR-tau243 is a specific biomarker of tau tangle pathology in Alzheimer’s disease
Horie, K., Salvadó, G., Barthélemy, N. R., Janelidze, S., Li, Y., He, Y., Saef, B., Chen, C. D., Jiang, H., Strandberg, O., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02443-z · Cited by 249
Self-citationPontecorvo, M. J., Lu, M., Burnham, S. C., Schade, A. E., Dage, J. L., Shcherbinin, S., Collins, E. C., Sims, J. R., & Mintun, M. A. (2022) · JAMA Neurology · doi:10.1001/jamaneurol.2022.3392 · Cited by 261
Cummings, J. L. (2023) · Drugs · doi:10.1007/s40265-023-01858-9 · Cited by 266
Specific associations between plasma biomarkers and postmortem amyloid plaque and tau tangle loads
Salvadó, G., Ossenkoppele, R., Ashton, N. J., Beach, T. G., Serrano, G. E., Reiman, E. M., Zetterberg, H., Mattsson‐Carlgren, N., Janelidze, S., Blennow, K., et al. (2023) · EMBO Molecular Medicine · doi:10.15252/emmm.202217123 · Cited by 205
Self-citationUpdates in Alzheimer's disease: from basic research to diagnosis and therapies
Liu, E., Zhang, Y., & Wang, J. (2024) · Translational Neurodegeneration · doi:10.1186/s40035-024-00432-x · Cited by 241
Cerebrospinal fluid proteomics define the natural history of autosomal dominant Alzheimer’s disease
Johnson, E. C. B., Bian, S., Haque, R. U., Carter, E. K., Watson, C. M., Gordon, B. A., Ping, L., Duong, D. M., Epstein, M. P., McDade, E., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02476-4 · Cited by 170
Pais, M. V., Forlenza, O. V., & Diniz, B. S. (2023) · Journal of Alzheimer s Disease Reports · doi:10.3233/adr-230029 · Cited by 184
Challenges in the practical implementation of blood biomarkers for Alzheimer’s disease
Schöll, M., Verberk, I. M. W., del Campo, M., Delaby, C., Therriault, J., Chong, J. R., Palmqvist, S., & Alcolea, D. A. (2024) · The Lancet Healthy Longevity · doi:10.1016/j.lanhl.2024.07.013 · Cited by 150
Tau pathology in neurodegenerative disease: disease mechanisms and therapeutic avenues
Samudra, N. P., Lane‐Donovan, C., VandeVrede, L. A., & Boxer, A. L. (2023) · Journal of Clinical Investigation · doi:10.1172/jci168553 · Cited by 142
Plasma MTBR-tau243 biomarker identifies tau tangle pathology in Alzheimer’s disease
Horie, K., Salvadó, G., Koppisetti, R. K., Janelidze, S., Barthélemy, N. R., He, Y., Sato, C., Gordon, B. A., Jiang, H., Benzinger, T. L. S., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03617-7 · Cited by 164
Self-citationTREM2: Potential therapeutic targeting of microglia for Alzheimer's disease
Li, Y., Xu, H., Wang, H., Yang, K., Luan, J., & Wang, S. (2023) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2023.115218 · Cited by 133
Alzheimer’s Disease: Novel Targets and Investigational Drugs for Disease Modification
Cummings, J. L., Osse, A. M. L., & Kinney, J. W. (2023) · Drugs · doi:10.1007/s40265-023-01938-w · Cited by 125
Disease 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 129
Self-citationOssenkoppele, R., Salvadó, G., Janelidze, S., Binette, A. P., Bali, D., Karlsson, L., Palmqvist, S., Mattsson, N., Stomrud, E., Therriault, J., et al. (2025) · Nature Aging · doi:10.1038/s43587-025-00835-z · Cited by 144
Self-citationCascaded multi-modal mixing transformers for Alzheimer’s disease classification with incomplete data
Liu, L., Liu, S., Zhang, L., To, X. V., Nasrallah, F., & Chandra, S. S. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120267 · Cited by 101
Tau in neurodegenerative diseases: molecular mechanisms, biomarkers, and therapeutic strategies
Zhang, X., Wang, J., Zhang, Z., & Ye, K. (2024) · Translational Neurodegeneration · doi:10.1186/s40035-024-00429-6 · Cited by 119
The dynamics of plasma biomarkers across the Alzheimer’s continuum
Guo, Y., Shen, X., Wang, H.-F., Chen, S.-D., Zhang, Y.-R., Chen, S., Cui, M., Cheng, W., Dong, Q., Ma, T., et al. (2023) · Alzheimer s Research & Therapy · doi:10.1186/s13195-023-01174-0 · Cited by 91
Treatment of Alzheimer’s Disease: Beyond Symptomatic Therapies
Buccellato, F. R., D’Anca, M., Tartaglia, G. M., Del Fabbro, M., Scarpini, E., & Galimberti, D. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241813900 · Cited by 94
“In light of this evidence, two large phase III studies were started, with three arms (high dose, low dose, placebo) [57–60].”
BackgroundMoussa, N., & Dayoub, N. (2023) · Saudi Pharmaceutical Journal · doi:10.1016/j.jsps.2023.101729 · Cited by 92
Pathological mechanisms and treatment progression of Alzheimer’s disease
Zhang, J., Kong, G., Yang, J., Pang, L., & Li, X. (2025) · European journal of medical research · doi:10.1186/s40001-025-02886-9 · Cited by 111
P-tau217 as a Reliable Blood-Based Marker of Alzheimer’s Disease
Lai, R., Li, B., & Bishnoi, R. J. (2024) · Biomedicines · doi:10.3390/biomedicines12081836 · Cited by 81
Zhang, Z., Yang, W., Wang, L., Zhu, C., Cui, S., Wang, T., Gu, X., Liu, Y., & Qiu, P. (2024) · Journal of Neuroinflammation · doi:10.1186/s12974-024-03285-3 · Cited by 85
Cummings, J. L. (2025) · Neurotherapeutics · doi:10.1016/j.neurot.2025.e00570 · Cited by 86
The China Alzheimer Report 2025
Zhi, N., Ren, R., Qi, J., Liu, X., Yun, Z., Lin, S., Hu, Y., Li, H., Xie, X., Wang, J., et al. (2025) · General Psychiatry · doi:10.1136/gpsych-2024-102020 · Cited by 87
Zhang, Y., Shen, Y., Liufu, N., Liu, L., Li, W., Shi, Z., Zheng, H., Mei, X., Chen, C.-Y., Jiang, Z., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02216-7 · Cited by 83
Da, Z., Yang, K., Guo, H., Zeng, J., Wang, S., Xu, H., Ge, A., Zeng, L., Chen, S., & Ge, J. (2023) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2023.114312 · Cited by 77
Role of mitochondria in physiological activities, diseases, and therapy
Wang, L., Zhou, X., & Lu, T. (2025) · Molecular Biomedicine · doi:10.1186/s43556-025-00284-5 · Cited by 87
Cheng, M., Yuan, C., Ju, Y., Liu, Y., Shi, B., Yang, Y., Jin, S., He, X., Zhang, L., & Min, D. (2024) · Behavioural Neurology · doi:10.1155/2024/5698119 · Cited by 80
Li, Y., Liu, Y., Yu, X., Xu, Y., Pan, X., Sun, Y. E., Wang, Y., Song, Y.-H., & Shen, Z. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-02013-w · Cited by 72
de Ruyter, F. J. H., Morrema, T. H. J., den Haan, J., Bank, N. B., Twisk, J. W. R., de Boer, J. F., Scheltens, P., Boon, B. D. C., Thal, D. R., Rozemüller, A. J. M., et al. (2022) · Acta Neuropathologica · doi:10.1007/s00401-022-02525-1 · Cited by 70
PET molecular imaging for pathophysiological visualization in Alzheimer’s disease
Wang, J., Jin, C., Zhou, J., Zhou, R., Tian, M., Lee, H. J., & Zhang, H. (2022) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-022-05999-z · Cited by 71
Targeting aging and age-related diseases with vaccines
Wu, R., Sun, F., Zhang, W., Ren, J., & Liu, G.-H. (2024) · Nature Aging · doi:10.1038/s43587-024-00597-0 · Cited by 66
Obesity-induced chronic low-grade inflammation in adipose tissue: A pathway to Alzheimer’s disease
Zhai, W., Meng, Z., Chunxiao, W., Lingjie, M., Anguo, Z., Zhang, Y., Xinran, C., Yanjiao, X., & Li, S. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102402 · Cited by 69
Fluid-based biomarkers for neurodegenerative diseases
Cao, Y., Xu, Y., Cao, M., Chen, N., Zeng, Q., Lai, M. K. P., Fan, D., Sethi, G., & Cao, Y. (2025) · Ageing Research Reviews · doi:10.1016/j.arr.2025.102739 · Cited by 67
AI-driven fusion of multimodal data for Alzheimer’s disease biomarker assessment
Jasodanand, V. H., Kowshik, S. S., Puducheri, S., Romano, M. F., Xu, L., Au, R., & Kolachalama, V. B. (2025) · Nature Communications · doi:10.1038/s41467-025-62590-4 · Cited by 76
Nagori, K., Nakhate, K. T., Yadav, K., Ajazuddin, & Pradhan, M. (2023) · Future Pharmacology · doi:10.3390/futurepharmacol3040053 · Cited by 61
Kang, J. H., Korecka, M., Lee, E. B., Cousins, K. A. Q., Tropea, T. F., Chen-Plotkin, A. A., Irwin, D. J., Wolk, D., Brylska, M., Wan, Y., et al. (2023) · Clinical Chemistry · doi:10.1093/clinchem/hvad139 · Cited by 64
Blood-Based Biomarkers in Alzheimer’s Disease: Advancing Non-Invasive Diagnostics and Prognostics
Dhauria, M., Mondal, R., Deb, S., Shome, G., Chowdhury, D., Sarkar, S., & Benito‐León, J. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms252010911 · Cited by 62
Ossenkoppele, R., Coomans, E. M., Apostolova, L. G., Baker, S. L., Barthel, H., Beach, T. G., Benzinger, T. L. S., Betthauser, T. J., Bischof, G. N., Bottlaender, M., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-02000-6 · Cited by 60
Self-citationPrevalence of Alzheimer’s disease pathology in the community
Aarsland, D., Sunde, A. L., Tovar, D., Leuzy, A., Fladby, T., Zetterberg, H., Blennow, K., Tan, K., Santis, G. D., Yakoub, Y., et al. (2025) · Nature · doi:10.1038/s41586-025-09841-y · Cited by 75
Huang, Z., Hamblin, M. R., & Zhang, Q. (2024) · Alzheimer s Research & Therapy · doi:10.1186/s13195-024-01484-x · Cited by 54
The ATN Framework—Moving Preclinical Alzheimer Disease to Clinical Relevance
van der Flier, W. M., & Scheltens, P. (2022) · JAMA Neurology · doi:10.1001/jamaneurol.2022.2967 · Cited by 50
Molecular mechanisms and therapeutic potential of icariin in the treatment of Alzheimer's disease
Zheng, L., Wu, S., Jin, H., Wu, J., Wang, X., Cao, Y., Zhou, Z., Jiang, Y., Li, L., Yang, X., et al. (2023) · Phytomedicine · doi:10.1016/j.phymed.2023.154890 · Cited by 48
Biomarkers in Alzheimer’s disease
Rajendran, K., & Krishnan, U. M. (2024) · Clinica Chimica Acta · doi:10.1016/j.cca.2024.119857 · Cited by 53
The evolving landscape of Alzheimer’s disease therapy: From Aβ to tau
Courade, J., Zetterberg, H., Höglinger, G. U., & Dewachter, I. (2025) · Cell · doi:10.1016/j.cell.2025.11.033 · Cited by 57
Ni, H., Liao, Y., Zhang, Y., Lu, H., Huang, Z., Huang, F., Zhang, Z., Dong, Y., Wang, Z., & Huang, Y. (2023) · International Immunopharmacology · doi:10.1016/j.intimp.2023.110783 · Cited by 48
Kang, X., Wang, D., Zhang, L., Huang, T., Liu, S., Feng, X., Guo, Y., Zhang, Z., Wang, Z., Ren, H., et al. (2023) · Molecular Medicine · doi:10.1186/s10020-023-00718-2 · Cited by 51
Rao, G., Gao, H., Wang, X., Zhang, J., Ye, M., & Rao, L. (2023) · Medicine · doi:10.1097/md.0000000000034997 · Cited by 46
Disentangling tau: One protein, many therapeutic approaches
Lane‐Donovan, C., & Boxer, A. L. (2024) · Neurotherapeutics · doi:10.1016/j.neurot.2024.e00321 · Cited by 49
Song, L., Qu, Y. Q., Tang, Y. P., Chen, X., Lo, H. H., Li, Q., Yun, Y. X., Wong, V. K. W., Zhang, R. L., Wang, H. M., et al. (2023) · Redox Biology · doi:10.1016/j.redox.2023.102637 · Cited by 45
Emerging nanotechnology for Alzheimer's disease: From detection to treatment
Song, N., Sun, S., Chen, K., Wang, Y., Wang, H., Meng, J., Guo, M., Zhang, X.-D., & Zhang, R. (2023) · Journal of Controlled Release · doi:10.1016/j.jconrel.2023.07.004 · Cited by 44
The role of high mobility group box 1 in neuroinflammatory related diseases
Mo, J., Hu, J., & Cheng, X. (2023) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2023.114541 · Cited by 44
Schöll, M., Vrillon, A., Ikeuchi, T., Quevenco, F. C., Iaccarino, L., Vasileva-Metodiev, S. Z., Burnham, S. C., Hendrix, J. A., Epelbaum, S., Zetterberg, H., et al. (2025) · The Journal of Prevention of Alzheimer s Disease · doi:10.1016/j.tjpad.2024.100056 · Cited by 48
Fluid biomarkers for the diagnosis of neurodegenerative diseases
Luebke, M., Parulekar, M. S., & Thomas, F. P. (2023) · Biomarkers in Neuropsychiatry · doi:10.1016/j.bionps.2023.100062 · Cited by 42
Ding, J., Zhao, C., Hao, X., & Jiao, H. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70709 · Cited by 50
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. (2023) · Fluids and Barriers of the CNS · doi:10.1186/s12987-022-00405-0 · Cited by 39
Hyman, B. (2023) · Annual Review of Medicine · doi:10.1146/annurev-med-042921-023749 · Cited by 39
Hu, Y., Cho, M., Sachdev, P., Dage, J., Hendrix, S., Hansson, O., Bateman, R. J., & Hampel, H. (2024) · Med · doi:10.1016/j.medj.2024.08.004 · Cited by 42
Self-citationLiu, P., Zhang, T., Wu, Y., Chen, Q., Sun, T., & Jiang, C. (2024) · Advanced Materials · doi:10.1002/adma.202408729 · Cited by 42
New Pathways Identify Novel Drug Targets for the Prevention and Treatment of Alzheimer’s Disease
Penke, B., Szűcs, M., & Bogár, F. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24065383 · Cited by 39
Pharmacological mTOR inhibitors in ameliorating Alzheimer’s disease: current review and perspectives
Xie, P.-L., Zheng, M.-Y., Han, R., Chen, W., & Mao, J.-H. (2024) · Frontiers in Pharmacology · doi:10.3389/fphar.2024.1366061 · Cited by 40
Muneer, G., Chen, C., & Chen, Y. (2024) · PROTEOMICS · doi:10.1002/pmic.202400087 · Cited by 40
Machine learning prediction of tau‐PET in Alzheimer's disease using plasma, MRI, and clinical data
Karlsson, L., Vogel, J., Arvidsson, I., Åström, K., Strandberg, O., Seidlitz, J., Bethlehem, R. A. I., Stomrud, E., Ossenkoppele, R., Ashton, N. J., et al. (2025) · Alzheimer's & Dementia · doi:10.1002/alz.14600 · Cited by 43
Self-citationA blood-based biomarker workflow for optimal tau-PET referral in memory clinic settings
Brum, W. S., Cullen, N. C., Therriault, J., Janelidze, S., Rahmouni, N., Stevenson, J., Servaes, S., Benedet, A. L., Zimmer, E. R., Stomrud, E., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-46603-2 · Cited by 41
Self-citationZhang, Y., Tang, C., He, Y., Zhang, Y., Li, Q., Zhang, T., Zhao, B., Tong, A., Zhong, Q., & Zhong, Z. (2024) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2024.117540 · Cited by 36
Donison, N. S., Palik, J., Volkening, K., & Strong, M. J. (2025) · Molecular Neurodegeneration · doi:10.1186/s13024-025-00842-z · Cited by 42
Gibson, L. L., Ruiz, C. A., Chong, J. R., Ballard, C. G., & Aarsland, D. (2023) · Current Opinion in Neurology · doi:10.1097/wco.0000000000001173 · Cited by 36
Su, Y., Liu, N., Sun, R., Ma, J., Li, Z., Wang, P., Ma, H., Sun, Y., Song, J., & Zhang, Z. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1115387 · Cited by 35
Smith, R., Hägerström, D., Pawlik, D., Klein, G., Jögi, J., Ohlsson, T., Stomrud, E., & Hansson, O. (2023) · JAMA Neurology · doi:10.1001/jamaneurol.2023.1323 · Cited by 33
Self-citationYu, 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. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113691 · Cited by 36
Jarek, D. J., Mizerka, H., Nuszkiewicz, J., & Szewczyk‐Golec, K. (2024) · Biomedicines · doi:10.3390/biomedicines12040786 · Cited by 37
Alcohol Use Disorder and Dementia: A Review
Zahr, N. M. (2024) · Alcohol research · doi:10.35946/arcr.v44.1.03 · Cited by 42
Su, Y., Wang, D., Liu, N., Yang, J., Sun, R., & Zhang, Z. (2023) · PLoS ONE · doi:10.1371/journal.pone.0286086 · Cited by 33
Unlocking the Therapeutic Potential of Natural Products for Alzheimer’s Disease
Li, Z., Zhang, Z., & Yu, B. (2025) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.4c03049 · Cited by 33
Impact of Nut Consumption on Cognition across the Lifespan
Nishi, S. K., Sala‐Vila, A., Júlvez, J., Sabaté, J., & Ros, E. (2023) · Nutrients · doi:10.3390/nu15041000 · Cited by 33
Geerts, H., Bergeler, S., Walker, M., van der Graaf, P. H., & Courade, J. (2023) · Scientific Reports · doi:10.1038/s41598-023-41382-0 · Cited by 32
Giacomucci, G., Mazzeo, S., Crucitti, C., Ingannato, A., Bagnoli, S., Padiglioni, S., Galdo, G., Emiliani, F., Frigerio, D., Moschini, V., et al. (2023) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2023.120805 · Cited by 31
Qi, Y., Zhang, J., Zhang, Y., Zhu, H., Wang, J., Xu, X., Jin, S., Wang, C., Zhang, F., Zhao, M., et al. (2025) · Phytomedicine · doi:10.1016/j.phymed.2025.156482 · Cited by 32
Neurodegenerative diseases and neuroinflammation-induced apoptosis
Huang, S., Lu, Y., Fang, W., Huang, Y., Li, Q., & Xu, Z. (2025) · Open Life Sciences · doi:10.1515/biol-2022-1051 · Cited by 32
Yang, J., Shi, X., Wang, Y., Ma, M., Liu, H., Wang, J., & Xu, Z. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-230593 · Cited by 33
Wu, J., Xiao, Z., Wang, M., Wu, W., Ma, X., Liang, X., Zheng, L., Ding, S., Luo, J., Cao, Y., et al. (2024) · Alzheimer s Research & Therapy · doi:10.1186/s13195-024-01401-2 · Cited by 31
Alzheimer’s Disease Biomarker Detection Using Field Effect Transistor-Based Biosensor
Le, P. G., Choi, S. H., & Cho, S. (2023) · Biosensors · doi:10.3390/bios13110987 · Cited by 29
Fominykh, V., Shadrin, A. A., Jaholkowski, P. P., Bahrami, S., Athanasiu, L., Wightman, D. P., Uffelmann, E., Posthuma, D., Selbæk, G., Dale, A. M., et al. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106174 · Cited by 28
Pan, S., Zhang, Y., Ye, T., Kong, Y., Cui, X., Yuan, S., Liu, J., & Zhang, Y. (2023) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.202300601 · Cited by 30
Ning, P., Guo, X.-Z., Qu, Q.-M., & Li, R. (2023) · Environmental science and pollution research international · doi:10.1007/s11356-023-31047-w · Cited by 27
Mohammadi, Z., Alizadeh, H., Marton, J., & Cumming, P. D. (2023) · Biomolecules · doi:10.3390/biom13020290 · Cited by 28
Head-to-head comparison of plasma and PET imaging ATN markers in subjects with cognitive complaints
Lu, J., Ma, X., Zhang, H., Xiao, Z., Li, M., Wu, J., Ju, Z., Chen, L., Zheng, L., Ge, J., et al. (2023) · Translational Neurodegeneration · doi:10.1186/s40035-023-00365-x · Cited by 28
Current therapeutics for Alzheimer’s disease and clinical trials
Xiao, D., & Zhang, C. (2024) · Exploration of Neuroscience · doi:10.37349/en.2024.00048 · Cited by 30
Rubenstein, R., McQuillan, L. E., Wang, K., Robertson, C. S., Chang, B., Yang, Z., Xu, H., Williamson, J. B., & Wagner, A. K. (2023) · Journal of Neurotrauma · doi:10.1089/neu.2022.0479 · Cited by 26
Gérard, T., Colmant, L., Malotaux, V., Salman, Y., Huyghe, L., Quenon, L., Dricot, L., Ivanoiu, A., Lhommel, R., & Hanseeuw, B. J. (2024) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-024-06603-2 · Cited by 28
The Role of Reactive Oxygen Species in Alzheimer's Disease: From Mechanism to Biomaterials Therapy
Yu, Z., & Luo, F. H. (2024) · Advanced Healthcare Materials · doi:10.1002/adhm.202304373 · Cited by 30
Advancements and challenges in mouse models of Alzheimer’s disease
Qian, Z., Li, Y., & Ye, K. (2024) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2024.10.010 · Cited by 30
Fu, Y., Zhang, J., Qin, R., Ren, Y., Zhou, T., Han, B., & Liu, B. (2025) · Pharmacological Reviews · doi:10.1016/j.pharmr.2025.100053 · Cited by 29
Alzheimer’s Disease: From Molecular Mechanisms to Promising Therapeutic Strategies
Ivanova, A. V., Kutuzova, A. D., Kuzmichev, I., & Abakumov, M. A. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26199444 · Cited by 33
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
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