Cited by 703Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsCancer-related cognitive impairment studies

The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.

Multimodal techniques for diagnosis and prognosis of Alzheimer's disease

Open access

Perrin, Richard J., Fagan, Anne M., Holtzman, David M.·2009·Nature

DOI 10.1038/nature08538PMC PMC2810658

Open this paper in CoChat — free account

Abstract

Alzheimer's disease affects millions of people around the world. Currently, there are no treatments that prevent or slow the disease. Like other neurodegenerative diseases, Alzheimer's disease is characterized by protein misfolding in the brain. This process and the associated brain damage begin years before the substantial neurodegeneration that accompanies dementia. Studies using new neuroimaging techniques and fluid biomarkers suggest that Alzheimer's disease pathology can be detected preclinically. These advances should allow the design of new clinical trials and early mechanism-based therapeutic intervention.

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

Crossref · 10.1038/nature08538

Cites

83 of 83 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The Amyloid Hypothesis of Alzheimer’s Disease: Progress and Problems on the Road to Therapeutics
Hardy, J., & Selkoe, D. J. (2002) · Science · doi:10.1126/science.1072994 · Cited by 13,864
Amyloid oligomers exacerbate tau pathology in a mouse model of tauopathy
Selenica, M.-L. B., Brownlow, M., Jimenez, J. P., Lee, D. C., Pena, G., Dickey, C. A., Gordon, M. N., & Morgan, D. (2013) · Neurodegenerative Diseases · doi:10.1159/000337230 · Cited by 10,359
The Clinical Dementia Rating (CDR): Current version and scoring rules
Morris, J. C. (1993) · Neurology · doi:10.1212/wnl.43.11.2412-a · Cited by 9,882
The Brain's Default Network: Anatomy, Function, and Relevance to Disease
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761
Mild Cognitive Impairment: Clinical Characterization and Outcome
Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999) · Archives of Neurology · doi:10.1001/archneur.56.3.303 · Cited by 8,980
The Consortium to Establish a Registry for Alzheimer's Disease (CERAD): Part II. Standardization of the neuropathologic assessment of Alzheimer's disease
Mirra, S. S., Heyman, A., McKeel, D., Sumi, S. M., Crain, B. J., Brownlee, L. M., Vogel, F. S., Hughes, J. P., Belle, G. V., Berg, L., et al. (1991) · Neurology · doi:10.1212/wnl.41.4.479 · Cited by 4,961
Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound‐B
Klunk, W. E., Engler, H., Nordberg, A., Wang, Y., Blomqvist, G., Holt, D. P., Bergström, M., Savitcheva, I., Huang, G., Estrada, S., et al. (2004) · Annals of Neurology · doi:10.1002/ana.20009 · Cited by 4,496
Searching for a baseline: Functional imaging and the resting human brain
Gusnard, D. A., & Raichle, M. E. (2001) · Nature Reviews Neuroscience · doi:10.1038/35094500 · Cited by 3,371
Consortium to Establish a Registry for Alzheimer's Disease (CERAD)
Fillenbaum, G., & Heyman, A. (2002) · doi:10.1002/0470846410.ch42(iii · Cited by 2,859
Diagnosis of Alzheimer's Disease
Khachaturian, Z. S. (1985) · Archives of Neurology · doi:10.1001/archneur.1985.04060100083029 · Cited by 2,499

Show all 83 references

Research works printed but not linked: 3

Alzheimer, A. About a peculiar disease of the cerebral cortex [translation]. Alzheimer Dis. Assoc. Disord. 1, 7–8 (1987).
Morris J. C. et al. PIB imaging predicts progression to symptomatic Alzheimer's disease. Arch. Neurol. (in the press).
Cairns, N. J. et al. PiB-PET detection of cerebral Aβ may lag clinical, cognitive, and CSF markers of Alzheimer's disease: a case report. Arch. Neurol. (in the press).

Sorted by citations

Items 301–400 of 703

An MRI brain tumour detection using logistic regression-based machine learning model
Gajula, S., & Rajesh, V. (2022) · International Journal of Systems Assurance Engineering and Management · doi:10.1007/s13198-022-01680-8 · Cited by 35
Delivery systems for theranostics in neurodegenerative diseases
Li, Y., Liu, R., Ji, W., Li, Y., Liu, L., & Zhang, X. (2018) · Nano Research · doi:10.1007/s12274-018-2067-z · Cited by 35
A combination of lycopene and human amniotic epithelial cells can ameliorate cognitive deficits and suppress neuroinflammatory signaling by choroid plexus in Alzheimer's disease rat
Xu, Z., Liu, C., Wang, R., Gao, X.-R., Hao, C., & Liu, C. (2020) · The Journal of Nutritional Biochemistry · doi:10.1016/j.jnutbio.2020.108558 · Cited by 37
Improving Alzheimer's Disease Diagnosis With Multi-Modal PET Embedding Features by a 3D Multi-Task MLP-Mixer Neural Network
Zhang, Z.-C., Zhao, X., Dong, G., & Zhao, X. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2023.3280823 · Cited by 35
Specific self-monitoring of metal-associated amyloid-β peptide disaggregation by a fluorescent chelator
Yang, T., Wang, X., Zhang, C., Ma, X., Wang, K., Wang, Y., Luo, J. H., Liu, Y., Yao, C., & Wang, X. (2015) · Chemical Communications · doi:10.1039/c5cc08898d · Cited by 35
Lifestyle Factors Are Important Contributors to Subjective Memory Complaints among Patients without Objective Memory Impairment or Positive Neurochemical Biomarkers for Alzheimer’s Disease
Miley-Åkerstedt, A., Jelić, V., Marklund, K., Walles, H., Åkerstedt, T., Hagman, G., & Andersson, C. (2018) · Dementia and Geriatric Cognitive Disorders Extra · doi:10.1159/000493749 · Cited by 35
The prognostic value of amyloid imaging
Gelosa, G., & Brooks, D. J. (2012) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-012-2108-x · Cited by 35
Lotus Seedpod Inspired SERS Substrates: A Novel Platform Consisting of 3D Sub‐10 nm Annular Hot Spots for Ultrasensitive SERS Detection
Jin, B., He, J., Li, J., & Zhang, Y. (2018) · Advanced Optical Materials · doi:10.1002/adom.201800056 · Cited by 34
A multimodal neuroimaging classifier for alcohol dependence
Guggenmos, M., Schmack, K., Veer, I. M., Lett, T. A. P., Sekutowicz, M., Sebold, M., Garbusow, M., Sommer, C., Wïttchen, H., Zimmermann, U. S., et al. (2020) · Scientific Reports · doi:10.1038/s41598-019-56923-9 · Cited by 36
Microcalorimetry-guided pore-microenvironment optimization to improve sensitivity of Ni-MOF electrochemical biosensor for chiral galantamine
Zhang, L., Qiao, C., Cai, X., Xia, Z., Han, J., Yang, Q., Zhou, C., Chen, S., & Gao, S. (2021) · Chemical Engineering Journal · doi:10.1016/j.cej.2021.130730 · Cited by 34
Multifunctional Metal–Organic Framework as a Versatile Nanoplatform for Aβ Oligomer Imaging and Chemo-Photothermal Treatment in Living Cells
Yan, X., Pan, Y., Ji, L., Gu, J., Hu, Y., Xia, Y., Li, C., Zhou, X., Yang, D., & Yu, Y. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.1c02459 · Cited by 34
Deciphering the biological effects of acupuncture treatment modulating multiple metabolism pathways
Zhang, A., Yan, G., Sun, H. J., Cheng, W., Meng, X., Li, L., Xie, N., & Wang, X. (2016) · Scientific Reports · doi:10.1038/srep19942 · Cited by 34
n Bu 4 NPF 6 promoted regioselective cascade synthesis of functionally embellished naphthofurans under acid, metal & solvent free conditions
Pareek, A., Dada, R., Rana, M., Sharma, A. K., & Yaragorla, S. (2016) · RSC Advances · doi:10.1039/c6ra17411f · Cited by 34
Multimodal Imaging Gd-nanoparticles Functionalized With Pittsburgh Compound B Or a Nanobody for Amyloid Plaques Targeting
Pansieri, J., Plissonneau, M., Stransky-Heilkron, N., Dumoulin, M., Heinrich, L., Rivory, P., Morfin, J., Tóth, É., Saraiva, M. J., Allémann, É., et al. (2017) · Nanomedicine · doi:10.2217/nnm-2017-0079 · Cited by 34
Genetically modified non-human primate models for research on neurodegenerative diseases
Pan, M.-T., 暨南大学粤港澳中枢神经再生研究院, 广., Zhang, H., Li, X., & Guo, X. (2024) · 动物学研究 · doi:10.24272/j.issn.2095-8137.2023.197 · Cited by 36
Reduction of kinesin I heavy chain decreases tau hyperphosphorylation, aggregation, and memory impairment in Alzheimer’s disease and tauopathy models
Selvarasu, K., Singh, A. K., Iyaswamy, A., Sreenivasmurthy, S. G., Krishnamoorthi, S., Bera, A. K., Huang, J., & Durairajan, S. S. K. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.1050768 · Cited by 33
Restoring neuronal chloride extrusion reverses cognitive decline linked to Alzheimer’s disease mutations
Keramidis, I., McAllister, B. B., Bourbonnais, J., Wang, F., Isabel, D., Rezaei, E., Sansonetti, R., Degagne, P., Hamel, J. P., Nazari, M., et al. (2023) · Brain · doi:10.1093/brain/awad250 · Cited by 37
Early Indications of Future Cognitive Decline: Stable versus Declining Controls
Rizk‐Jackson, A., Insel, P. S., Petersen, R. C., Aisen, P. S. S., Jack, C. R., & Weiner, M. W. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074062 · Cited by 34
Alzheimer’s amyloid-β A2T variant and its N-terminal peptides inhibit amyloid-β fibrillization and rescue the induced cytotoxicity
Lin, T.-W., Chang, C., Chang, Y., Liao, Y., Yu, H., & Chen, Y. (2017) · PLoS ONE · doi:10.1371/journal.pone.0174561 · Cited by 33
Age-associated changes in amyloid-β and formaldehyde concentrations in cerebrospinal fluid of rhesus monkeys
Li, Z.-H., 650223，中国, 中. 昆., He, X., Li, H., He, R., Hu, X., 650204，中国, 中. 昆., 671000，中国, 大. 大., 200031，中国, 中., 650223，中国, 中. 昆., et al. (2020) · 动物学研究 · doi:10.24272/j.issn.2095-8137.2020.088 · Cited by 32
Design, synthesis and evaluation of cinnamic acid hybrids as multi-target-directed agents for the treatment of Alzheimer’s disease
Wang, K., Shi, J., Zhou, Y. M., He, Y., Mi, J., Yang, J. L., Liu, S., Tang, X., Liu, W., Tan, Z., et al. (2021) · Bioorganic Chemistry · doi:10.1016/j.bioorg.2021.104879 · Cited by 32
Prognosis of Alzheimer’s Disease Using Quantitative Mass Spectrometry of Human Blood Plasma Proteins and Machine Learning
Kononikhin, A. S., Zakharova, N. V., Semenov, S. D., Bugrova, A. E., Brzhozovskiy, A. G., Indeykina, M. I., Fedorova, Y. B., Колыхалов, И. В., Strelnikova, P. A., Ikonnikova, A. Y., et al. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23147907 · Cited by 33
Imaging proteomics for diagnosis, monitoring and prediction of Alzheimer's disease
Nazeri, A., Ganjgahi, H., Roostaei, T., Nichols, T. E., & Zarei, M. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.08.041 · Cited by 33
Multi-Threshold Recurrence Rate Plot: A Novel Methodology for EEG Analysis in Alzheimer’s Disease and Frontotemporal Dementia
Zheng, H., Xiong, X., & Zhang, X. (2024) · Brain Sciences · doi:10.3390/brainsci14060565 · Cited by 31
Translational opportunities for amyloid-targeting fluorophores
Cao, K., & Yang, J. (2018) · Chemical Communications · doi:10.1039/c8cc03619e · Cited by 32
Anomaly Analysis of Alzheimer’s Disease in PET Images Using an Unsupervised Adversarial Deep Learning Model
Baydargil, H. B., Park, J.-S., & Kang, D.-Y. (2021) · Applied Sciences · doi:10.3390/app11052187 · Cited by 30
Multimodal neuroimaging computing: the workflows, methods, and platforms
Liu, S., Cai, W., Liu, S., Zhang, F., FULHAM, M. J., Feng, D. D., Pujol, S., & Kikinis, R. (2015) · Brain Informatics · doi:10.1007/s40708-015-0020-4 · Cited by 30
Amyloid Beta1–42 and the Phoshorylated Tau Threonine 231 in Brains of Aged Cynomolgus Monkeys (Macaca fascicularis)
Darusman, H. S., GJEDDE, A. H., Sajuthi, D., Schapiro, S. J., Kalliokoski, O., Kristianingrum, Y. P., Handaryani, E., & Hau, J. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00313 · Cited by 30
Dementia, stroke and migraine — Some common pathological mechanisms
Sas, K., Párdutz, Á., Toldi, J., & Vécsei, L. (2010) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2010.08.001 · Cited by 30
Exploration of a Library of 3,4‐(Methylenedioxy)aniline‐Derived Semicarbazones as Dual Inhibitors of Monoamine Oxidase and Acetylcholinesterase: Design, Synthesis, and Evaluation
Tripathi, R. K. P., Rai, G. K., & Ayyannan, S. R. (2016) · ChemMedChem · doi:10.1002/cmdc.201600128 · Cited by 30
Quercetin ameliorates cognitive deficit, expression of amyloid precursor gene, and pro-inflammatory cytokines in an experimental models of Alzheimer's disease in Wistar rats
Safarzadeh, E., Ataei, S., Akbari, M., Abolhasani, R., Baziar, M., Asghariazar, V., & Dadkhah, M. (2024) · Experimental Gerontology · doi:10.1016/j.exger.2024.112466 · Cited by 30
Multi-Constraint Latent Representation Learning for Prognosis Analysis Using Multi-Modal Data
Ning, Z., Lin, Z., Xiao, Q., Du, D., Feng, Q., Chen, W., & Zhang, Y. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3112194 · Cited by 29
Validation of a Multiplex Assay for Simultaneous Quantification of Amyloid-β Peptide Species in Human Plasma with Utility for Measurements in Studies of Alzheimer's Disease Therapeutics
Lachno, D. R., Emerson, J. K., Vanderstichele, H., Gonzales, C., Martényi, F., Konrad, R. J., Talbot, J. A., Lowe, S. L., Oefinger, P. E., & Dean, R. A. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2012-121075 · Cited by 29
Cell Purification: A New Challenge for Biobanks
Almeida, M. I., García‐Montero, A. C., & Órfão, A. (2014) · Pathobiology · doi:10.1159/000358306 · Cited by 29
Real-Time Analysis of Binding Events between Different Aβ1–42 Species and Human Lilrb2 by Dual Polarization Interferometry
Hu, T., Wang, S., Chen, C., Sun, J., & Yang, X. (2017) · Analytical Chemistry · doi:10.1021/acs.analchem.6b04950 · Cited by 28
Computational modeling of the relationship between amyloid and disease
Hall, D. R., & Edskes, H. K. (2012) · Biophysical Reviews · doi:10.1007/s12551-012-0091-x · Cited by 29
Retracted: Effect of microRNA‐186 on oxidative stress injury of neuron by targeting interleukin 2 through the janus kinase‐signal transducer and activator of transcription pathway in a rat model of Alzheimer’s disease
Wu, D., Wen, X., Wang, Y., Han, X., Wang, S., Shen, M., Fan, S., Zhuang, J., Zhang, Z.-F., Shan, Q., et al. (2018) · Journal of Cellular Physiology · doi:10.1002/jcp.26843 · Cited by 28
Retracted
Biomarkers for the Clinical Diagnosis of Alzheimer’s Disease: Metabolomics Analysis of Brain Tissue and Blood
Wang, Y., Sun, Y., Luo, Y., Peng, D., Li, X., Yang, B., Wang, Q., & Kuang, H. (2021) · Frontiers in Pharmacology · doi:10.3389/fphar.2021.700587 · Cited by 29
Identification of early-onset photoreceptor degeneration in transgenic mouse models of Alzheimer's disease
Zhang, J., Gao, F., Ma, Y., Xue, T., & Shen, Y. (2021) · iScience · doi:10.1016/j.isci.2021.103327 · Cited by 28
Multi-Target-Directed Cinnamic Acid Hybrids Targeting Alzheimer’s Disease
Drakontaeidi, A., & Pontiki, E. A. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25010582 · Cited by 28
Glia-based biomarkers and their functional role in the CNS
Jha, M. K., & Suk, K. (2013) · Expert Review of Proteomics · doi:10.1586/epr.12.70 · Cited by 28
Entorhinal cortex volume is associated with episodic memory related brain activation in normal aging and amnesic mild cognitive impairment
Trivedi, M. A., Stoub, T. R., Murphy, C. M., George, S., deToledo‐Morrell, L., Shah, R. C., Whitfield, S., Gabrieli, J. D. E., & Stebbins, G. T. (2011) · Brain Imaging and Behavior · doi:10.1007/s11682-011-9117-4 · Cited by 27
Correlations between serum levels of beta amyloid, cerebrospinal levels of tau and phospho tau, and delayed response tasks in young and aged cynomolgus monkeys ( M acaca fascicularis)
Darusman, H. S., Sajuthi, D., Kalliokoski, O., Jacobsen, K. R., Call, J., Schapiro, S. J., GJEDDE, A. H., Abelson, K., & Hau, J. (2013) · Journal of Medical Primatology · doi:10.1111/jmp.12044 · Cited by 27
Bayesian functional joint models for multivariate longitudinal and time-to-event data
Li, K., & Luo, S. (2018) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2018.07.015 · Cited by 27
Advances in fluorescent probes for detection and imaging of amyloid-β peptides in Alzheimer's disease
Zhang, Y., Ding, C., Li, C., & Wang, X. (2021) · Advances in clinical chemistry · doi:10.1016/bs.acc.2020.08.008 · Cited by 28
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma DistributionsPreprint
Ma, H., Han, Z., Zhang, C., Fu, H., Zhou, J. T., & Hu, Q. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.08456 · Cited by 27
An isoform‐specific role of FynT tyrosine kinase in Alzheimer's disease
Lee, C., Low, C. Y. B., Francis, P. T., Attems, J., Wong, P. T. ‐., Lai, M. K. P., & Tan, M. G. K. (2016) · Journal of Neurochemistry · doi:10.1111/jnc.13429 · Cited by 27
Modeling Uncertainty in Multi-Modal Fusion for Lung Cancer Survival Analysis
Wang, H., Subramanian, V., & Syeda-Mahmood, T. (2021) · 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi48211.2021.9433823 · Cited by 26
Semicarbazones, thiosemicarbazone, thiazole and oxazole analogues as monoamine oxidase inhibitors: Synthesis, characterization, biological evaluation, molecular docking, and kinetic studies
Qazi, S. U., Naz, A., Hameed, A., Osra, F. A., Jalil, S., Iqbal, J., Shah, S. A. A., & Mirza, A. Z. (2021) · Bioorganic Chemistry · doi:10.1016/j.bioorg.2021.105209 · Cited by 26
CSF-Derived CD4 + T-Cell Diversity Is Reduced in Patients With Alzheimer Clinical Syndrome
Joshi, C., Sivaprakasam, K., Christley, S., Ireland, S. J., Rivas, J. R., Zhang, W., Sader, D., Logan, R., Lambracht‐Washington, D., Rosenberg, R. N., et al. (2021) · Neurology Neuroimmunology & Neuroinflammation · doi:10.1212/nxi.0000000000001106 · Cited by 26
Poor memory performance in aged cynomolgus monkeys with hippocampal atrophy, depletion of amyloid beta 1-42 and accumulation of tau proteins in cerebrospinal fluid.
Darusman, H. S., Pandelaki, J., Mulyadi, R., Sajuthi, D., Putri, I. A., Kalliokoski, O., Call, J., Abelson, K., Schapiro, S. J., GJEDDE, A. H., et al. (2014) · PubMed · Cited by 26
Evaluation of Antioxidant, Radical Scavenging Activity and Polyphenolics Profile in Solanum torvum L. Fruits
Ramamurthy, C., Kumar, M. S., Suyavaran, V. S. A., Mareeswaran, R., & Thirunavukkarasu, C. (2012) · Journal of Food Science · doi:10.1111/j.1750-3841.2012.02830.x · Cited by 26
Ethical issues in Alzheimer’s disease: an overview
Leuzy, A., & Gauthier, S. G. (2012) · Expert Review of Neurotherapeutics · doi:10.1586/ern.12.38 · Cited by 27
Quantitative Neuroproteomics: Classical and Novel Tools for Studying Neural Differentiation and Function
Colucci-D’Amato, L., Farina, A., Vissers, J. P. C., & Chambery, A. (2010) · Stem Cell Reviews and Reports · doi:10.1007/s12015-010-9136-3 · Cited by 25
Genetic variation in the lymphotoxin-α ( LTA )/ tumour necrosis factor-α ( TNFα ) locus as a risk factor for idiopathic achalasia
Wouters, M. M., Lambrechts, D., Becker, J., Cleynen, I., Tack, J. F., Vigo, A., de León, A. R., Urcelay, E., de la Serna, J. P., Rohof, W. O., et al. (2013) · Gut · doi:10.1136/gutjnl-2013-304848 · Cited by 25
Genetic algorithm-based hybrid deep learning model for explainable Alzheimer’s disease prediction using temporal multimodal cognitive data
Saleh, H., El-Rashidy, N. M., Elaziz, M. A., Aseeri, A. O., & El–Sappagh, S. (2024) · International Journal of Data Science and Analytics · doi:10.1007/s41060-024-00514-z · Cited by 24
Supporting the Detection of Early Alzheimer’s Disease with a Four-Channel EEG Analysis
Perez‐Valero, E., Morillas, C. A., López-Gordo, M. A., & Minguillón, J. (2023) · International Journal of Neural Systems · doi:10.1142/s0129065723500211 · Cited by 24
Brain disease research based on functional magnetic resonance imaging data and machine learning: a review
Teng, J., Mi, C., Shi, J., & Li, N. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1227491 · Cited by 25
Clinical Neuroproteomics and Biomarkers
Shoemaker, L. D., Achrol, A. S., Sethu, P., Steinberg, G. K., & Chang, S. D. (2011) · Neurosurgery · doi:10.1227/neu.0b013e3182333a26 · Cited by 24
Ultraeffective Inhibition of Amyloid Fibril Assembly by Nanobody–Gold Nanoparticle Conjugates
Zhao, L., Xin, Y., Li, Y., Yang, X., Luo, L., & Meng, F. (2018) · Bioconjugate Chemistry · doi:10.1021/acs.bioconjchem.8b00797 · Cited by 24
Correlation between Topographic N400 Anomalies and Reduced Cerebral Blood Flow in the Anterior Temporal Lobes of Patients with Dementia
Grieder, M., Crinelli, R. M., Jann, K., Federspiel, A., Wirth, M., Koenig, T. W., Stein, M., Wahlund, L., & Dierks, T. (2013) · Journal of Alzheimer s Disease · doi:10.3233/jad-121690 · Cited by 23
Discovering and targeting the basic mechanism of neurodegeneration: The role of peptides from the C-terminus of acetylcholinesterase
Greenfield, S. A. (2013) · Chemico-Biological Interactions · doi:10.1016/j.cbi.2013.03.015 · Cited by 23
Multifunctional 3-Schiff base-4-hydroxycoumarin derivatives with monoamine oxidase inhibition, anti-β-amyloid aggregation, metal chelation, antioxidant and neuroprotection properties against Alzheimer's disease
Wang, Z., Xie, S., Li, X., Wu, J., Wang, X., & Kong, L. (2015) · RSC Advances · doi:10.1039/c5ra13594j · Cited by 23
A multinational study distinguishing Alzheimer's and healthy patients using cerebrospinal fluid tau/Aβ42 cutoff with concordance to amyloid positron emission tomography imaging
Yi, M., Stromswold, J., Wilson, K., Holder, D., Sur, C., Laterza, O., Savage, M. J., Struyk, A. F., Scheltens, P., Teunissen, C. E., et al. (2017) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2017.02.004 · Cited by 23
Integrating Health Promotion Into Physical Therapy Practice to Improve Brain Health and Prevent Alzheimer Disease
McGough, E. L., Kirk-Sanchez, N. J., & Liu-Ambrose, T. Y. L. (2017) · Neurology Report · doi:10.1097/npt.0000000000000181 · Cited by 24
The ubiquitin ligase UBE4B regulates amyloid precursor protein ubiquitination, endosomal trafficking, and amyloid β42 generation and secretion
Gireud, M., Reyes‐Esteves, S., Tewari, R., Patrizz, A., Howe, M. D., Kofler, J., Waxham, M. N., McCullough, L. D., & Bean, A. J. (2020) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2020.103542 · Cited by 24
Identification of promethazine as an amyloid-binding molecule using a fluorescence high-throughput assay and MALDI imaging mass spectrometry
McClure, R., Chumbley, C. W., Reyzer, M. L., Wilson, K., Caprioli, R. M., Gore, J. C., & Pham, W. N. (2013) · NeuroImage Clinical · doi:10.1016/j.nicl.2013.04.015 · Cited by 23
Dementia screening, biomarkers and protein misfolding
Galvin, J. E. (2011) · Prion · doi:10.4161/pri.5.1.14439 · Cited by 23
Thiamine for preventing dementia development among patients with alcohol use disorder: A nationwide population-based cohort study
Chou, W.-P., Chang, Y.-H., Lin, H.-C., Chang, Y.-H., Chen, Y.-Y., & Ko, C.-H. (2019) · Clinical Nutrition · doi:10.1016/j.clnu.2018.05.009 · Cited by 22
Nmnat1 protects neuronal function without altering phospho‐tau pathology in a mouse model of tauopathy
Musiek, E. S., Xiong, D. D., Patel, T. K., Sasaki, Y., Wang, Y., Bauer, A. Q., Singh, R., Finn, S. L., Culver, J. P., Milbrandt, J., et al. (2016) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.308 · Cited by 22
Self-citation
APOE ε4-dependent effects on the early amyloid pathology in induced neurons of patients with Alzheimer’s disease
Kim, H., Kim, S., Cho, B., Shin, J., & Kim, J. (2022) · Translational Neurodegeneration · doi:10.1186/s40035-022-00319-9 · Cited by 22
How many biomarkers to discriminate neurodegenerative dementia?
Sancesario, G. M., & Bernardini, S. (2015) · Critical Reviews in Clinical Laboratory Sciences · doi:10.3109/10408363.2015.1051658 · Cited by 23
The Brain’s Structural Connectome Mediates the Relationship between Regional Neuroimaging Biomarkers in Alzheimer’s Disease
Pandya, S., Initiative, A. D. N., Kuceyeski, A. F., & Raj, A. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-160090 · Cited by 24
MS4A6A genotypes are associated with the atrophy rates of Alzheimer's disease related brain structures
Ma, J., Initiative, A. D. N., Zhang, W., Tan, L., Wang, H.-F., Wan, Y., Sun, F.-R., Tan, C.-C., Yu, J.-T., & Tan, L. (2016) · Oncotarget · doi:10.18632/oncotarget.9563 · Cited by 23
The synthesis and bioactivity of apigenin derivatives
Liu, S., Zheng, X., Luo, Z., Tang, C., Hu, Y., Peng, Q., Mi, P., Chen, H., & Xu, Y. (2024) · Fitoterapia · doi:10.1016/j.fitote.2024.106228 · Cited by 21
Advances in PET Imaging of Degenerative, Cerebrovascular, and Traumatic Causes of Dementia
Eisenmenger, L. B., Huo, E. J., Hoffman, J. M., Minoshima, S., Matesan, M. C., Lewis, D. H., Lopresti, B. J., Mathis, C. A., Okonkwo, D. O., & Mountz, J. M. (2015) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2015.09.003 · Cited by 21
T-Tau is Associated with Objective Memory Decline Over Two Years in Persons Seeking Help for Subjective Cognitive Decline: A Report from the Gothenburg-Oslo MCI Study
Hessen, E., Nordlund, A., Stålhammar, J., Eckerström, M., Bjerke, M., Eckerström, C., Göthlin, M., Fladby, T., Reinvang, I., & Wallin, A. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-150109 · Cited by 21
Amyloid β-Binding Bifunctional Chelators with Favorable Lipophilicity for 64 Cu Positron Emission Tomography Imaging in Alzheimer’s Disease
Wang, Y., Huynh, T. T., Cho, H.-J., Wang, Y.-C., Rogers, B. E., & Mirica, L. M. (2021) · Inorganic Chemistry · doi:10.1021/acs.inorgchem.1c02079 · Cited by 25
Generation of Clickable Pittsburgh Compound B for the Detection and Capture of β-Amyloid in Alzheimer’s Disease Brain
Diner, I., Dooyema, J. M., Gearing, M., Walker, L. C., & Seyfried, N. T. (2017) · Bioconjugate Chemistry · doi:10.1021/acs.bioconjchem.7b00500 · Cited by 21
Early molecular events of autosomal‐dominant Alzheimer's disease in marmosets with PSEN1 mutations
Homanics, G. E., Park, J. E., Bailey, L. S., Schaeffer, D. J., Schaeffer, L. K. H., He, J., Li, S., Zhang, T., Haber, A., Spruce, C. A., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13806 · Cited by 20
The hard Test Your Memory. Evaluation of a short cognitive test to detect mild Alzheimer's disease and amnestic mild cognitive impairment
Brown, J. M., Wiggins, J., Dong, H., Harvey, R. C., Richardson, F., Hunter, K., Dawson, K., & Parker, R. A. (2013) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.4005 · Cited by 20
DNA detection using a light-emitting polymer single nanowire
Park, D. H., Kim, N., Cui, C., Hong, Y. K., Kim, M. S., Yang, D.-H., Kim, D.-C., Lee, H., Kim, J., Ahn, D. J., et al. (2011) · Chemical Communications · doi:10.1039/c1cc11362c · Cited by 20
Network-guided analysis of hippocampal proteome identifies novel proteins that colocalize with Aβ in a mice model of early-stage Alzheimer’s disease
Aladeokin, A. C., Akiyama, T. H., Kimura, A., Kimura, Y., Jitsuki‐Takahashi, A., Nakamura, H., Makihara, H., Masukawa, D., Nakabayashi, J., Hirano, H., et al. (2019) · Neurobiology of Disease · doi:10.1016/j.nbd.2019.104603 · Cited by 23
Muscle-Directed Anti-Aβ Single-Chain Antibody Delivery via AAV1 Reduces Cerebral Aβ Load in an Alzheimer’s Disease Mouse Model
Yang, J., Pattanayak, A., Song, M., Kou, J., Taguchi, H., Paul, S., Ponnazhagan, S., Lalonde, R., & Fukuchi, K.-I. (2012) · Journal of Molecular Neuroscience · doi:10.1007/s12031-012-9877-3 · Cited by 20
Nanomedicine against Alzheimer’s and Parkinson’s Disease
Tandon, A., Singh, S. J., & Chaturvedi, R. K. (2020) · Current Pharmaceutical Design · doi:10.2174/1381612826666201021140904 · Cited by 20
Molecular Biomarkers for the Diagnosis, Prognosis, and Pharmacodynamics of Spinal Muscular Atrophy
Babić, M., Banović, M., Berečić, I., Banić, T., Leko, M. B., Ulamec, M., Junaković, A., Kopić, J., Sertić, J., Barišić, N., et al. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12155060 · Cited by 19
CSF Biomarkers of Alzheimer’s Disease: Impact on Disease Concept, Diagnosis, and Clinical Trial Design
Fagan, A. M. (2014) · Advances in Geriatrics · doi:10.1155/2014/302712 · Cited by 21
Self-citation
Is interaction of amyloid β-peptides with metals involved in cognitive activity?
Tamano, H., & Takeda, A. (2015) · Metallomics · doi:10.1039/c5mt00076a · Cited by 19
Ultrasmall T 1 – T 2 Magnetic Resonance Multimodal Imaging Nanoprobes for the Detection of β-amyloid Aggregates in Alzheimer’s Disease Mice
Cai, J., Yi, P., Miao, Y., Liu, J., Hu, Y., Liu, Q., Feng, Y., Chen, H., & Li, L. (2020) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.0c01597 · Cited by 19
Finding a pathological diagnosis for A lzheimer's disease: Are inflammatory molecules the answer?
Bhamra, M. S., & Ashton, N. J. (2012) · Electrophoresis · doi:10.1002/elps.201200161 · Cited by 21
Aβ self-association and adsorption on a hydrophobic nanosurface: competitive effects and the detection of small oligomers via electrical response
Jana, A. K., & Sengupta, N. (2014) · Soft Matter · doi:10.1039/c4sm01845a · Cited by 19
Insights into the Impact of a Membrane-Anchoring Moiety on the Biological Activities of Bivalent Compounds As Potential Neuroprotectants for Alzheimer’s Disease
Liu, H., Jiang, Y., Liu, K., Gómez‐Murcia, V., Ma, X., Torrecillas, A., Chen, Q., Zhu, X., Lesnefsky, E. J., Gómez-Fernández, J. C., et al. (2017) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.7b01284 · Cited by 18
Behavioral and psychological symptoms of dementia (BPSD) and impaired cognition reflect unsuccessful neuronal compensation in the pre-plaque stage and serve as early markers for Alzheimer’s disease in the APP23 mouse model
Pfeffer, A., Munder, T., Schreyer, S., Klein, C., Rasińska, J., Winter, Y., & Steiner, B. (2018) · Behavioural Brain Research · doi:10.1016/j.bbr.2018.03.030 · Cited by 20
Preferential Neurodegeneration in the Dentate Gyrus by Amyloid β1–42-Induced Intracellular Zn2+Dysregulation and Its Defense Strategy
Tamano, H., Takiguchi, M., Tanaka, Y., Murakami, T., Adlard, P. A., Bush, A. I., & Takeda, A. (2019) · Molecular Neurobiology · doi:10.1007/s12035-019-01853-w · Cited by 18
Detecting Alzheimer’s Dementia Degree
Wu, E. Q., Peng, X.-Y., Chen, S.-D., Zhao, X.-Y., & Tang, Z. (2022) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2020.3015131 · Cited by 17
Analyzing Olfactory Neuron Precursors Non-Invasively Isolated through NADH FLIM as a Potential Tool to Study Oxidative Stress in Alzheimer’s Disease
Gomez‐Virgilio, L., Luarte, A., Ponce, D. P., Bruna, B., & Behrens, M. I. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22126311 · Cited by 18
Use of Cerebrospinal Fluid Biomarkers for Diagnosis of Incipient Alzheimer Disease in Patients with Mild Cognitive Impairment
Dean, R. A., & Shaw, L. M. J. (2009) · Clinical Chemistry · doi:10.1373/clinchem.2009.134692 · Cited by 18
An amylin analog used as a challenge test for Alzheimer's disease
Zhu, H., Stern, R. A., Tao, Q., Bourlas, A. P., Essis, M. D., Chivukula, M., Rosenzweig, J. L., Steenkamp, D., Xia, W., Mercier, G., et al. (2017) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1016/j.trci.2016.12.002 · Cited by 19
The impact of companion diagnostic device measurement performance on clinical validation of personalized medicine
Li, M., Yu, T., & Hu, Y. (2015) · Statistics in Medicine · doi:10.1002/sim.6476 · Cited by 17
Methods to investigate intrathecal adaptive immunity in neurodegeneration
Oh, H. S., Leventhal, O., Channappa, D., Henderson, V. W., Wyss‐Coray, T., Lehallier, B., & Gate, D. (2021) · Molecular Neurodegeneration · doi:10.1186/s13024-021-00423-w · Cited by 18

Authors: Perrin, R. J., Fagan, A. M., & Holtzman, D. M.
Affiliations: Washington University in St. Louis (US)
ORCID: Perrin, Richard J.
Fagan, Anne M.
Holtzman, David M.
Venue: Nature
Publisher: Springer Science and Business Media LLC
Published: 2009-10
Volume: 461
Issue: 7266
Pages: 916-922
ISSN: 0028-0836 (ISSN-L)
1476-4687
DOI: 10.1038/nature08538
PMC: PMC2810658
OpenAlex: W2085558649
Cited by: 702
References: 83
Citations by year: 2026: 20 · 2025: 29 · 2024: 30 · 2023: 28 · 2022: 43 · 2021: 56 · 2020: 38 · 2019: 38 · 2018: 36 · 2017: 48 · 2016: 33 · 2015: 49 · 2014: 53 · 2013: 58 · 2012: 60
FWCI: 5.97
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.springer.com/tdm (tdm)
Locations: Nature (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Funders: National Institutes of Health (5t32ns007205-32)
National Institute on Aging (P50AG005681, P01 AG0 3991, P01AG003991, P50AG00568125, P01AG026276)
National Institute of Neurological Disorders and Stroke (T32-NS007205)
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
Health Sciences › Medicine › Oncology › Cancer-related cognitive impairment studies
Keywords: Alzheimer's disease, multimodal diagnosis, prognosis, neuroimaging, fluid biomarkers, preclinical detection, protein misfolding, neurodegeneration, dementia, clinical trials
MeSH terms: Alzheimer Disease, Humans, Inflammation, Prognosis, Amyloid beta-Peptides, tau Proteins, Oxidative Stress, 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

Multimodal techniques for diagnosis and prognosis of Alzheimer's disease

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks