Cited by 900Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsMedicinal Plants and Neuroprotection

The DOI matches its Crossref record; 61 of the 62 references it cites were found in a registry or an index.

Global estimates on the number of persons across the Alzheimer's disease continuum

Open access

Gustavsson, Anders, Norton, Nicholas, Fast, Thomas, Frölich, Lutz, Georges, Jean, Holzapfel, Drew, Kirabali, Tunahan, Krolak‐Salmon, Pierre, Rossini, Paolo M., Ferretti, Maria Teresa, Lanman, Lydia, Chadha, Antonella Santuccione, van der Flier, Wiesje M.·2023·Alzheimer's & Dementia

DOI 10.1002/alz.12694

Open this paper in CoChat — free account Open PDF

Abstract

Introduction: Global estimates on numbers of persons in early stages of Alzheimer's disease (AD), including prodromal and preclinical, are lacking, yet are needed to inform policy decisions on preventive measures and planning for future therapies targeting AD pathology. Methods: We synthesized the literature on prevalence across the AD continuum and derived a model estimating the number of persons, stratified by 5‐year age groups, sex, and disease stage (AD dementia, prodromal AD, and preclinical AD). Results: The global number of persons with AD dementia, prodromal AD, and preclinical AD were estimated at 32, 69, and 315 million, respectively. Together they constituted 416 million across the AD continuum, or 22% of all persons aged 50 and above. Discussion: Considering predementia stages, the number of persons with AD is much larger than conveyed in available literature. Our estimates are uncertain, especially for predementia stages in low‐ and middle‐income regions where biomarker studies are missing.

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 · 10.1002/alz.12694

Cites

61 of 61 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.

1 retracted

Dementia prevention, intervention, and care: 2020 report of the Lancet Commission
Livingston, G., Huntley, J., Sommerlad, A., Ames, D., Ballard, C., Banerjee, S., Brayne, C., Burns, A., Cohen-Mansfield, J., Cooper, C., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30367-6 · Cited by 10,430
Retracted
Clinical diagnosis of Alzheimer's disease: Report of the NINCDS‐ADRDA Work Group* under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019
Vos, T., Lim, S. S., Abbafati, C., Abbas, K. M., Abbasi, M., Abbasifard, M., Abbasi-Kangevari, M., Abbastabar, H., Abd-Allah, F., Abdelalim, A., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30925-9 · Cited by 19,358
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
Mild cognitive impairment as a diagnostic entity
Petersen, R. C. (2004) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2004.01388.x · Cited by 7,864
Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease
Sperling, R. A., Aisen, P. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M., Iwatsubo, T., Jack, C. R., Kaye, J., Montine, T. J., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.003 · Cited by 7,155
Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019
Nichols, E., Steinmetz, J. D., Vollset, S. E., Fukutaki, K., Chalek, J., Abd-Allah, F., Abdoli, A., Abualhasan, A., Abu-Gharbieh, E., Akram, T. T., et al. (2022) · The Lancet Public Health · doi:10.1016/s2468-2667(21)00249-8 · Cited by 5,575
Mild cognitive impairment – Beyond controversies, towards a consensus: Report of the International Working Group on Mild Cognitive Impairment.
Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L. ‐., Nordberg, A., Bäckman, L., Albert, M., Almkvist, O., et al. (2004) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2004.01380.x · Cited by 4,946
Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria
Dubois, B., Feldman, H. H., Jacova, C., DeKosky, S. T., Barberger-Gateau, P., Cummings, J., Delacourte, A., Galasko, D., Gauthier, S., Jicha, G., et al. (2007) · The Lancet Neurology · doi:10.1016/s1474-4422(07)70178-3 · Cited by 4,411
A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial
Ngandu, T., Lehtisalo, J., Solomon, A., Levälahti, E., Ahtiluoto, S., Antikainen, R., Bäckman, L., Hänninen, T., Jula, A., Laatikainen, T., et al. (2015) · The Lancet · doi:10.1016/s0140-6736(15)60461-5 · Cited by 3,689

Flagged first, then by citations

Show all 62 references

1 of the 62 references couldn’t be matched to a known paper.

Research works printed but not linked: 3

WHO, 2019, Risk reduction of cognitive decline and dementia: WHO guidelines, Geneva: World Health Organization
American Psychiatric Association Diagnostic and statistical manual of mental disorders.2000(4th edition).
WHO, 2021, Global status report on the public health response to dementia, Geneva: World Health Organization

Sorted by citations

Items 701–800 of 900

Microbial transformation of oleanonic acid by Aspergillus minisclerotigenes and the anti-neuroinflammatory properties of products
Xu, D., Zhou, J., Zhou, S.-Y., Gong, S., & Zhao, W. (2025) · Natural Product Research · doi:10.1080/14786419.2025.2487684
Frontiers and hotspot evolution in research on Alzheimer’s disease and hypertension: a bibliometric analysis from 2004 to 2023
Liu, W., Zhao, Y., Rao, Y., Wu, Z., Peng, Y. F., & Gong, L. (2025) · Frontiers in Neurology · doi:10.3389/fneur.2025.1514054
Predicting and Evaluating Cognitive Status in Aging Populations Using Decision Tree Models
Luo, Z., Wang, S., Ho, E., Yao, L., & Gershon, R. C. (2025) · American Journal of Alzheimer s Disease & Other Dementias® · doi:10.1177/15333175251339730 · Cited by 1
Translational studies on biological signatures, risk profiles, and prevention of dementia
Alanko, V. (2025) · doi:10.69622/28624745
[18F]Florbetapir Pet Uptake Differences in White Matter Across the Alzheimer's Disease Continuum: From Cognitively Normal to MCI and Dementia
Khasayeva, N., Jensen, K. M., Eierud, C., Petropoulos, H., Calhoun, V. D., & Iraji, A. (2025) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi60581.2025.10981043
Current Status and Developments in the Clinical Treatment of Alzheimer’s Disease
Li, Z. (2025) · Theoretical and Natural Science · doi:10.54254/2753-8818/2025.22922
Differences in Glucose Metabolism Between Single Memory Domain and Multidomain Subjective Cognitive Decline: A Longitudinal Study From SILCODE
Wei, M., Wang, L., Yu, X., Hu, W., Wang, M., Zhang, Q., Guo, T., Zhong, J., Li, C., Jiang, J., et al. (2025) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.70264
Unveiling Heterogeneity in Early Alzheimer's Disease: A Data-Driven Exploration of Mild Cognitive Impairment and Normal Cognition
Nguyen, M., Dương, N. T., Duc, V. T., Phan, C., Phan, T. N. M., & Ha, H. (2025) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-031-90194-2_29
Sex-Based Differences in the Association of Epigenetic Age Acceleration with Alzheimer's Disease Biomarkers and Cognitive Measures.
Edwards, T. A., Zhai, T., Nho, K. T., Saykin, A. J., Long, Q., & Shen, L. (2025) · Europe PMC (PubMed Central)
CRISPR Therapies for Alzheimer’s Disease
Sun, J., & Roy, S. (2025) · Springer eBooks · doi:10.1007/978-3-031-89307-0_12 · Cited by 1
Deciphering the molecular and neuropathological dimensions of dementia
Dutta, S., Bhattacharjee, P., Noori, S., Adhikari, N., Dule, S., Soyel, M. I., Besra, M., Borah, S., & Gupta, P. (2025) · NPG. Neurologie, psychiatrie, gériatrie/NPG · doi:10.1016/j.npg.2025.05.002
Biomarker-driven diagnosis of Alzheimer's disease: Toward precision neurology
Altuna, M. (2025) · Medicina Clínica · doi:10.1016/j.medcli.2025.107105
Global, Regional, and Socioeconomic Trends in Alzheimer's Disease Burden, 1990–2040: A Population-Based Analysis of the Global Burden of Disease Study 2021Preprint
Zhang, Y., Ye, Z., Wang, Z., Shen, Z., Liu, J., Zhang, W., Zheng, C., Deng, K., Lu, L., Han, H., et al. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5350601
APOE Polymorphism and Brain Imaging
Obenaus, A., & Territo, P. R. (2025) · Springer eBooks · doi:10.1007/978-3-031-52641-1_69-1
CLARITY in Alzheimer’s Research: Merging Tissue Transparency with Next-Gen Neurotechnologies
Trisal, A., & Singh, A. K. (2025) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2025.110554 · Cited by 1
Brain inflammation may be the reason behind muscle fatigue after infection and injury
Rincón-Limas, D. E., & Johnson, A. N. (2024) · doi:10.64628/aai.ewcmquh5e
Characterizing the research participant recruitment funnel for Alzheimer's secondary prevention trials: Results from a survey of U.S. adults
Largent, E. A., Grill, J. D., Karlawish, J. H., & Bleakley, A. (2025) · Alzheimer s & Dementia Behavior & Socioeconomics of Aging · doi:10.1002/bsa3.70035 · Cited by 1
Redefining Early Diagnosis: Quantitative Susceptibility Mapping at MRI Forecasts Onset of Mild Cognitive Impairment
Arasa, V. C. A. (2025) · Radiology · doi:10.1148/radiol.252398
Multi-Modal Approaches to Alzheimer’s Diagnosis: Combining Cognitive assessments with Biomarkers and ImagingPreprint
Afridi, M. A., Khalid, M. M., & Din, R. U. (2025) · Research Square · doi:10.21203/rs.3.rs-7404405/v1
Sex specific differences of protein expression profiles in Alzheimer’s disease
Tian, F., Zhang, Y., Li, J., Meng, S., Ge, W., & Wang, X. (2025) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/csb-2025-5121
Bridging Bench to Bedside for Brain Health: Non-Invasive Brain Stimulation for Neurodegenerative Diseases
Nencha, U., & Hummel, F. C. (2025) · Clinical and Translational Neuroscience · doi:10.3390/ctn9030043
Morphogeometric variation analysis of cortical surfaces in Alzheimer's Disease. A novel approach for prognostic biomarker discovery
González-Cabrero, J., Gómez, C., & Cavas, F. (2025) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2025.109089
Alzheimer’s Disease: Engaging with an Unstable Category
Daly, T. P., & Keuck, L. (2025) · Springer eBooks · doi:10.1007/978-94-024-2252-8_113
Estimating preclinical amyloid positivity: A case study transporting ADNI to ARIC
Stapp, E. K., Mayeda, E. R., Stuart, E. A., Gottesman, R. F., Zimmerman, S. C., Wong, D. F., Mosley, T. H., Griswold, M. E., Glymour, M. M., Power, M. C., et al. (2025) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.70158
Targeting of β-Amyloid Peptide Fibers, a Biomarker of Alzheimer’s Disease, by Designing Specifically Functionalized Iron Oxide Nanoparticles
Porras, G. R. G., Brison, A., Becker, A., Calvé, S. L., David, M., Ulrich, G., Mazan, V., Schmutz, M., Bigo−Simon, A., Mertz, D., et al. (2025) · ACS Applied Nano Materials · doi:10.1021/acsanm.5c03459
Sex-dependent effects of maternal high-fat diet during lactation in the offspring of adult THY-Tau22 mice
Gauvrit, T., Benderradji, H., Pelletier, A., Carvalho, K., Aboulouard, S., Faivre, É., Chatelain, E., Cannafarina, H., Labous, L., Launay, A., et al. (2025) · Brain · doi:10.1093/brain/awaf417
l1 Regularization Based Random Vector Functional Link Network for Alzheimer’s Disease Diagnosis
Goel, T., Pilli, R., Verma, S., Tanveer, M., Murugan, R., & Suganthan, P. N. (2025) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn64981.2025.11228103
Optimierung der Arbeit von Gedächtnisambulanzen unter Gesichtspunkten von „value-based healthcare“ – ein Ansatz aus dem Zentrum für Gedächtnisstörungen der Uniklinik Köln
Schönberger, A. R., Schild, A., Steinmetz, A., Simandi, F., Benson, G. S., Hausner, L., Schöttler, M., Hennig, B., Knudsen, A., Maier, F., et al. (2025) · Der Nervenarzt · doi:10.1007/s00115-025-01903-w
Self-citation
Psychometric properties of the Brazilian version of the “Caregiver Guilt Questionnaire” (CGQ-BR)
Pfutzenreuter, K. C., Losada‐Baltar, A., Márquez‐González, M., & Falcão, D. V. D. S. (2025) · Dementia & Neuropsychologia · doi:10.1590/1980-5764-dn-2025-0325
Improving Cognitive Assessment Utility in Community Settings: Stratified Normative Data and Age-Specific Score Conversions between the MoCA-J and MMSE in Community-Dwelling Older AdultsPreprint
Moe, K., Susumu, O., Yamashiro, D., Kobayashi, M., Yu, N., Sanmei, C., Narazaki, K., Kawai, H., Murayama, H., Kumagai, S., et al. (2025) · Research Square · doi:10.21203/rs.3.rs-7504458/v1
Targeting the PS1-ELK1 protein-protein interaction with a peptide-based inhibitor reduces Aβ production and alleviates memory decline in Alzheimer's disease
Yi, L., Tian, Q., Xu, B., Pang, Y., & Dong, Z. (2025) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2025.149074
Multi-modal approaches to Alzheimer's disease diagnosis: Combining cognitive assessments with biomarkers and imaging
Afridi, M. A., Khalid, M. M., & Din, R. U. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251394315
Risk prediction of mild cognitive impairment using electronic health record data
Li, G., Cobb, B. R., Nelson, T. M., Devanarayan, V., Borentain, S., Mielke, M. M., Galvin, J. E., Kivipelto, M., Tkatch, R., Santi, S. D., et al. (2025) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.70209 · Cited by 1
Migraine and Dementia: A Narrative Review of Current Evidence
Choudhary, A. K. (2025) · Psikhiatriya · doi:10.30629/2618-6667-2025-23-4-81-92
Formal and Informal Care Utilization in Mild Cognitive Impairment and Mild Dementia due to Alzheimer’s Disease: Cross-Sectional and Longitudinal Analyses of RUD-Lite Data from the Tauriel Study
Teng, E., Li, Y., Blendstrup, M., & Lansdall, C. J. (2025) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000549652
Adenylate kinase 5, a novel genetic risk factor for Alzheimer’s disease, regulates microglial inflammatory activation
Seong, W. J., An, S. J., Gim, J., Gupta, D. P., Park, J. Y., Kang, S., Lee, K. H., & Song, G. J. (2025) · Molecular Brain · doi:10.1186/s13041-025-01257-z
Identification and validation of PANoptosis-related genes in Alzheimer's disease
Zhou, W., Lin, H., Huang, X., & Zhou, X. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251396927
Protein Compositional Ratio Representation (PCRR) Systematically Improves Human Disease PredictionPreprint
Madduri, A. V., Ellis, R. J., & Patel, C. J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.29.691286
Biomarker-driven diagnosis of Alzheimer's disease: Toward precision neurology
Altuna, M. (2025) · Medicina Clínica (English Edition) · doi:10.1016/j.medcle.2025.107105
Sex-related upregulation of bone morphogenetic protein signaling inhibits adult neurogenesis in APPNL−G−F alzheimer’s disease model mice
Su, X., Takayanagi, R., Maeda, H., Saido, T. C., & Ohshima, T. (2025) · Biology of Sex Differences · doi:10.1186/s13293-025-00799-0 · Cited by 1
The effects of Bacopa Monnieri extract alone and in combination with Ginkgo biloba, biotin and coenzyme Q10 on memory impairment induced by scopolamine in mice
Abaei, M. K., Hosseini-Sharifabad, A., & Rabbani, M. (2025) · Next research. · doi:10.1016/j.nexres.2025.101237
The role of amyloid and tau biomarkers in assessing the effectiveness of drug treatment for Alzheimer’s disease.
Sun, J., Ling, Y., Chen, J., & Zhao, M. (2025) · Investigación Clínica · doi:10.54817/ic.v66n4a01
Additional file 2 of Disease severity and mortality in Alzheimer's disease: an analysis using the U.S. National Alzheimer’s Coordinating Center Uniform Data Set
Crowell, V., Reyes, A., Zhou, S. Q., Vassilaki, M. E., Gsteiger, S., & Gustavsson, A. (2023) · Figshare · doi:10.6084/m9.figshare.23949732
Self-citation
Additional file 5 of Unraveling the intercellular communication disruption and key pathways in Alzheimer’s disease: an integrative study of single-nucleus transcriptomes and genetic association
Liu, A., Fernandes, B. S., Citu, C., & Zhao, Z. (2024) · Figshare · doi:10.6084/m9.figshare.26658997
Additional file 4 of Unraveling the intercellular communication disruption and key pathways in Alzheimer’s disease: an integrative study of single-nucleus transcriptomes and genetic association
Liu, A., Fernandes, B. S., Citu, C., & Zhao, Z. (2024) · Figshare · doi:10.6084/m9.figshare.26658994
Additional file 2 of Unraveling the intercellular communication disruption and key pathways in Alzheimer’s disease: an integrative study of single-nucleus transcriptomes and genetic association
Liu, A., Fernandes, B. S., Citu, C., & Zhao, Z. (2024) · Figshare · doi:10.6084/m9.figshare.24934656
Additional file 1 of Unraveling the intercellular communication disruption and key pathways in Alzheimer’s disease: an integrative study of single-nucleus transcriptomes and genetic association
Liu, A., Fernandes, B. S., Citu, C., & Zhao, Z. (2024) · Figshare · doi:10.6084/m9.figshare.24934307
Additional file 1 of Recruitment of pre-dementia participants: main enrollment barriers in a longitudinal amyloid-PET study
Bader, I., Bader, I., Lopes Alves, I., García, D. V., Vellas, B. J., Dubois, B., Boada, M., Marquié, M., Altomare, D., Scheltens, P., et al. (2023) · Figshare · doi:10.6084/m9.figshare.24494206
Additional file 7 of Unraveling the intercellular communication disruption and key pathways in Alzheimer’s disease: an integrative study of single-nucleus transcriptomes and genetic association
Liu, A., Fernandes, B. S., Citu, C., & Zhao, Z. (2024) · Figshare · doi:10.6084/m9.figshare.26659003
Additional file 1 of Identifying exercise and cognitive intervention parameters to optimize executive function in older adults with mild cognitive impairment and dementia: a systematic review and meta-analyses of randomized controlled trials
Chen, W., Leuk, J. S.-P., Wu, Y., Huang, N., & Teo, W.-P. (2024) · Figshare · doi:10.6084/m9.figshare.26944329
Additional file 6 of Unraveling the intercellular communication disruption and key pathways in Alzheimer’s disease: an integrative study of single-nucleus transcriptomes and genetic association
Liu, A., Fernandes, B. S., Citu, C., & Zhao, Z. (2024) · Figshare · doi:10.6084/m9.figshare.26659000
Additional file 1 of Disease severity and mortality in Alzheimer's disease: an analysis using the U.S. National Alzheimer’s Coordinating Center Uniform Data Set
Crowell, V., Reyes, A., Zhou, S. Q., Vassilaki, M. E., Gsteiger, S., & Gustavsson, A. (2023) · Figshare · doi:10.6084/m9.figshare.23949729
Self-citation
Additional file 3 of Unraveling the intercellular communication disruption and key pathways in Alzheimer’s disease: an integrative study of single-nucleus transcriptomes and genetic association
Liu, A., Fernandes, B. S., Citu, C., & Zhao, Z. (2024) · Figshare · doi:10.6084/m9.figshare.26658991
Additional file 1 of Progression analysis versus traditional methods to quantify slowing of disease progression in Alzheimer’s disease
Jönsson, L., Ivkovic, M., Atri, A., Handels, R. L. H., Gustavsson, A., Hahn-Pedersen, J. H., León, T., Lilja, M., Gundgaard, J., & Rakêt, L. L. (2024) · Figshare · doi:10.6084/m9.figshare.25322842
Self-citation
Selection of five different types of animal models of Alzheimer’s disease: based on pathological similarity and research objectives
Yang, W., Yu, Z., Wang, W., & Yan, S. (2025) · Ageing and Neurodegenerative Diseases · doi:10.20517/and.2025.29
Investigation of therapeutic potential of Portulaca oleracea Linn. in treatment of Alzheimer’s disease: In vitro and in silico approaches
Yadav, V., Murmu, A., Matore, B. W., Das, S., Satpathy, S., Mandal, V., Roy, P. P., Singh, J., & Patra, A. (2025) · South African Journal of Botany · doi:10.1016/j.sajb.2025.12.007
Acetylcholinesterase inhibitory and antioxidant activities of whole plant ethanolic extract of Ophiorrhiza recurvipetala in aluminium chloride induced Drosophila melanogaster model of Alzheimer’s disease
Vidya, V., Prema, A., Manivasagam, T., Subasri, P., & Thenmozhi, A. J. (2025) · International Journal of Biosciences (IJB) · doi:10.12692/ijb/27.6.44-53
Assessment of Healthcare Resource Requirements for Disease-Modifying Dementia Therapies in Türkiye
Avşar, T. S. (2025) · Sağlık Bilimleri Dergisi · doi:10.34108/eujhs.1675326
Improving Alzheimer’s Disease and Related Dementias Phenotyping in Electronic Health Records Through Transfer Learning
Shao, Y., Yin, Y., Tsuang, D. W., Ma, P., ZAMRINI, E. Y., Ahmed, A., Faselis, C. J., Wilson, K., Brown, K., & Zeng‐Treitler, Q. (2026) · Smart innovation, systems and technologies · doi:10.1007/978-981-95-1361-1_36
Investigating gender differences in Alzheimer's disease
Fouad, G. I., Ando, H., & Ichihara, G. (2026) · Journal of Alzheimer s Disease · doi:10.1177/13872877251410204 · Cited by 2
Risk prediction of progression from normal cognitive function to Alzheimer's disease in elderly aged 65 and above based on deep learning methods
Liu, Y., Su, H., Guan, T., Li, X., Dong, C., Hu, Z., & Zhang, Y. (2026) · Journal of Alzheimer s Disease · doi:10.1177/13872877251410937
Performance and Interpretability Study of VGG19 and ConvNeXt V2 for Multi-Stage Alzheimer's Classification on Brain MRI
Nurrahmadayeni, Fawwaz, I., Syahputra, M. F., Selvida, D., Rassy, R. P., & Rahmat, R. F. (2025) · International Conference on Computing and Applied Informatics (ICCAI) · doi:10.1109/iccai65301.2025.11279646
The role of diet and nutrition in Alzheimer's disease: Exploring the gut-cognitive health connection
Bhattacharya, P., Athwani, V., Vijay, T., & Aathi, M. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-33655-3.00007-9
The Psycho/Bio/Neurological Bases of Subjective Time Flow
Shiota, S. (2026) · Journal of Nursing Care & Reports · doi:10.47485/3065-7636.1045
A Systematic Review on Nursing for AD by Using a Semantic Analysis Approach
Dai, Y., Li, R., & Huang, Z. (2025) · International Symposium on Artificial Intelligence for Medicine Sciences (ISAIMS) · doi:10.1145/3777577.3777713
Investigating the molecular mechanisms of glutamine metabolism and mitochondria-related biomarkers in Alzheimer’s disease through transcriptomics and experimental validation
Si, X., Tian, S., Chen, Y., Li, X., Wu, G., Yao, Y., & Wang, M. (2026) · European journal of medical research · doi:10.1186/s40001-025-03747-1
Integrating Fuzzy Logic with AI in Healthcare: A Comprehensive Survey of Physical, Mental, and Neurological Health Applications
Benmoujane, A., Madani, A., & Kissi, M. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-10895-1_25
Incorporating mixed-effects into Adaptive time relation multi-task learning with longitudinal data for Alzheimer’s disease progression prediction
Miao, L., Chen, H., Xiang, B., Yuan, Z., Luo, C., & Li, T. (2026) · Applied Soft Computing · doi:10.1016/j.asoc.2026.114716
The role of diet in the risk of Alzheimer’s disease
Grant, W. B. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-33841-0.00031-2
Cost‐effectiveness and impact at scale of collaborative care and lecanemab for Alzheimer's disease
Atkins, K. J., Kahn, J. G., & Possin, K. L. (2026) · Alzheimer s & Dementia Behavior & Socioeconomics of Aging · doi:10.1002/bsa3.70054
Spatial amyloid–informed multimodal brain age as an early marker of Alzheimer’s-related vulnerability and risk stratification
Cui, L., Wang, Q.-M., Zhang, Z., Wang, M., Tu, Y.-Y., Jiang, J., Guan, Y., Li, Y.-H., Xie, F., & Guo, Q.-H. (2026) · The Journal of Prevention of Alzheimer s Disease · doi:10.1016/j.tjpad.2026.100501
White Matter Microstructural Alterations Mediate the Association between Polygenic Risk for Alzheimer’s Disease and Cognitive Performance in Clinically Asymptomatic Adults
Zou, R., Takabayashi, K., Andica, C., Uchida, W., Kitagawa, T., Mizuta, K., Hagiwara, A., Kikuta, J., Aoki, S., & Kamagata, K. (2026) · Magnetic Resonance in Medical Sciences · doi:10.2463/mrms.mp.2025-0182
Elucidating the toxicological impact and mechanism of plasticizers exposure on Alzheimer's disease through network toxicology and molecular docking
Ge, Y., Weng, Y., & Chen, Y. (2026) · Food and Chemical Toxicology · doi:10.1016/j.fct.2026.116005
Mechanistic modeling of amyloid dynamics relating to Alzheimer's disease progression
Przekwas, A. J., Norris, C., & Garimella, H. T. (2026) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2026.1730480 · Cited by 1
E3 Ubiquitin Ligases in Alzheimer’s Disease
Gavilán, E. (2026) · Springer eBooks · doi:10.1007/978-981-95-6099-8_10
Next-generation sequencing study identifies the first genes associated with Alzheimer's disease in Bangladeshi population: The CARED study
Hakim, M., Ranjan, R., Ken‐Dror, G., Yusuf, M. A., Uddin, M. N., Mamun, M. T., Mamun, A. A., Kawnayn, G., & Sharma, P. K. (2026) · Journal of Alzheimer s Disease · doi:10.1177/13872877261419066
Microemulsion-based dual delivery of malkangani and phalsa: formulation, optimization and in-vivo pharmacodynamics in rats
Jarande, S. S., Damle, M. C., Saldanha, T., & Khot, S. V. (2026) · Brazilian Journal of Pharmaceutical Sciences · doi:10.1590/s2175-97902026e24520
Comorbidity of type 2 diabetes and Alzheimer's disease
Pöeggeler, B. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-32848-0.00029-7
Molecular mechanism of Alzheimer’s disease using integrated multi-omics
Alhusaini, M., Mussa, B. M., İlçe, B. Y., Alhaj, H. A., & Hamoudi, R. (2026) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2026.1735696
Glial and BBB modifications correlate with early anxio-depressive-like behaviors and cognitive inflexibility in 3xTg-AD micePreprint
Benhora-Chabeaux, G., MORISSET, C., NICOD, T., Mor, D., DELABROUILLE-CAULIEZ, S., Cabeza, L., Etiévant, A., & Bourasset, F. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.13.711598
Estimates of current capacity for diagnosing and implementation of new treatment Alzheimer's disease in Slovenia
Županič, E., Stegnar, G., Rakuša, M., Prelog, P. R., Švab, I., & Kramberger, M. G. (2026) · Journal of Alzheimer s Disease Reports · doi:10.1177/25424823261424524
Decreased Length of Locus Coeruleus Norepinephrine Axons and Increased Amyloid Beta Pathology in Male APP/PS1 Mice During Protracted Abstinence From Alcohol
Garland, I. J. Z., Engel, S., Scalf, M., Payne, N. R., Lee, A. M., & Graves, S. M. (2026) · Neurotoxicity Research · doi:10.1007/s12640-026-00794-2
Beneficios del Candesartán en la Enfermedad de Alzheimer a través del Eje Aminopeptidasa/Angiotensina Iv/Receptor de Angiotensina Iv
Barraza, J. D. G., Conde-Cardona, G., Contreras‐Puentes, N., Rodríguez, R. E., Torres, K. V., Rivera, S. T., Gazabon, K. Z., & Peñaloza, E. O. (2026) · Revista Ciencias Biomédicas · doi:10.32997/rcb-2025-5245
Targeting Neuroinflammation in Alzheimer's Disease: Repurposed Nucleoside Reverse Transcriptase Inhibitors and the Therapeutic Potential of Kamuvudine‐9
Hussain, M., Ikram, M., & Vohora, D. (2026) · Fundamental and Clinical Pharmacology · doi:10.1111/fcp.70079
Methodological innovations in drug development lifecycle with the advent of targeted immunotherapy
Abbas, R. (2024) · theses.fr (ABES) · doi:10.70675/62edf842z447dz4fcfz8051zd7ac23a193fa
The light at the end of the tunnel : study of early-stage brain dynamics alterations in Alzheimer’s disease and beneficial effects of light stimulation in the AppNL-F/MAPT mouse model
Aguilera, M. (2024) · theses.fr (ABES) · doi:10.70675/dc614591zf8f9z4a6dzb174za8a482fa3ece
The moderation and mediation roles of white matter insults in relationship of APOE ε4 genotype with Alzheimer’s disease and related phenotypes: two longitudinal studies
Liu, K.-Z., Zhou, X., Dong, Y.-F., Luo, X., Tan, L., Tan, C., & Xu, W. (2026) · Journal of Advanced Research · doi:10.1016/j.jare.2026.04.030
Exploring the Biological Potency of Carotenoids Against Alzheimer’s Disease: An Integrated Approach of Molecular Docking and Molecular Dynamics
Khedraoui, M., Karim, E. M., Yamari, I., Errougui, A., Dermawan, D., Alotaiq, N., & Chtita, S. (2026) · Current Issues in Molecular Biology · doi:10.3390/cimb48040407
Longitudinal Multi‐Domain Cognitive Assessment of Anti‐Amyloid Monoclonal Antibodies Versus Acetylcholinesterase Inhibitors in Early Alzheimer's Disease: A Systematic Review and Meta‐Analysis
Lee, C., Hsu, T. L., Kao, Y., Tseng, P., Hsu, C., Lin, Y., & Liang, C. (2026) · Geriatrics and gerontology international/Geriatrics & gerontology international · doi:10.1111/ggi.70492
Neuroprotective effect of standardized Vitex pubescens Vahl bark extract and its n-butanol fraction against scopolamine-induced cognitive impairment in Sprague-Dawley rats in relationship to its isolated phytochemicals
Abdelbaset, S., Ayoub, I. M., Tawfiq, R. A., Majrashi, T. A., Hassab, M. A. E., Eldehna, W., El‐Kersh, D. M., & Eldahshan, O. A. (2026) · Frontiers in Pharmacology · doi:10.3389/fphar.2026.1775571
Green carbon dots in neurological disorders
Thokchom, B., Singh, S. R., Bhavi, S. M., Abbigeri, M. B., Kulkarni, S. R., Padti, A. C., & Yarajarla, R. B. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-34121-2.00011-x
Role of Biomarker in Treating Alzheimer's Disease
Anand, P., Kumar, D., Gupta, S., Tiwari, J., & Singh, S. N. (2026) · BENTHAM SCIENCE PUBLISHERS eBooks · doi:10.2174/9798898814953126010006
Gene Therapy and RNA-Based Innovations for Management of Alziemer's
Tiwari, J., Anand, P., Kumar, D., & Singh, S. N. (2026) · BENTHAM SCIENCE PUBLISHERS eBooks · doi:10.2174/9798898814953126010011
Signaling cross-talk driving neuronal survival, death and inflammation in neurodegeneration
Singh, L. (2026) · Neurophysiology · doi:10.1007/s11062-026-10003-7
Mood and Age Predict Cognitive Complaints in Memory Clinic Patients: A Machine‐Learning and Linear Modeling Approach
Sander, F. W., Pittet, M. P., Manera, V., Krebs, C. R., Brill, E., Guevara, A. B., Ryvlin, P., Anguera, J. A., Gazzaley, A. H., Robert, P. H., et al. (2026) · European Journal of Neurology · doi:10.1111/ene.70583 · Cited by 2
Alcohol and neurodegenerative diseases: a review of mechanistic insights and disease specific effects
Mei, J., Xia, M., Peng, L., & Li, X. (2026) · The American Journal of Drug and Alcohol Abuse · doi:10.1080/00952990.2026.2645215
ICAM ‐1 mediated inhibition of microglial inflammation through ERK / STAT3 signalling pathway improves cognitive functions in 5xFAD mouse model of Alzheimer's disease
Goswami, S., Gorai, N., & Biswas, S. C. (2026) · FEBS Journal · doi:10.1111/febs.70531
Computational Drug Repurposing to Develop Human EAAT2 Receptor Agonists as Newer Therapeutics for Alzheimer’s Disease
Mujwar, S., Singh, M., Dhankhar, S., Chauhan, S., Singh, R., Mishra, K. K., & Singh, T. (2026) · Letters in Applied NanoBioScience · doi:10.33263/lianbs151.016
Proteomic signatures of protected APOE ε4 carriers reveal causal pathways associated with delayed Alzheimer's disease onset
Guen, Y. L., Park, J. Y., Peña‐Tauber, A., & Greicius, M. D. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71688
Circadian disruption induces sex-specific Alzheimer’s pathophysiology and immune cell reprogrammingPreprint
Cordi, C. V., Falkenberg, N. G., Clark, G. T., Allen, N. G., Chuah, J., Ulbrich, R., Herzog, A. A., Lanka, M., Collins, E. J., Bentley, M., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.30.721994

Authors: Gustavsson, A., Norton, N., Fast, T., Frölich, L., Georges, J., Holzapfel, D., Kirabali, T., Krolak‐Salmon, P., Rossini, P. M., Ferretti, M. T., Lanman, L., Chadha, A. S., & van der Flier, W. M.
Affiliations: Karolinska Institutet (SE)
Quantify Research (Sweden) (SE)
Heidelberg University (DE)
Alzheimer Europe (LU)
CEO Initiative on Alzheimer's Disease Philadelphia USA
Biogen (Switzerland) (CH)
Hospices Civils de Lyon (FR)
Università Cattolica del Sacro Cuore (IT)
Women's Brain Project (CH)
F. Hoffmann-La Roche AG (CH)
Alzheimer Center Amsterdam Department of Neurology Department of Epidemiology and Data Science Amsterdam Neuroscience Amsterdam UMC, Vrije Universiteit Amsterdam Amsterdam the Netherlands
Corresponding author: Gustavsson, Anders
ORCID: Gustavsson, Anders
Norton, Nicholas
Georges, Jean
Kirabali, Tunahan
Krolak‐Salmon, Pierre
Rossini, Paolo M.
Ferretti, Maria Teresa
Chadha, Antonella Santuccione
Venue: Alzheimer's & Dementia
Publisher: Wiley
Published: 2022-06-02
Volume: 19
Issue: 2
Pages: 658-670
ISSN: 1552-5260 (ISSN-L)
1552-5279
DOI: 10.1002/alz.12694
OpenAlex: W4281674975
Cited by: 895
References: 62
Citations by year: 2026: 207 · 2025: 323 · 2024: 236 · 2023: 114 · 2022: 15
FWCI: 112.57
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by-nc
creativecommons.org/licenses/by-nc/4.0/ (vor)
Locations: Alzheimer s & Dementia (publishedVersion, cc-by-nc)
PubMed (publishedVersion)
Pure Amsterdam UMC (publishedVersion, other-oa)
Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Funders: F. Hoffmann-La Roche
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 › Complementary and alternative medicine › Medicinal Plants and Neuroprotection
Keywords: Alzheimer's disease, Alzheimer's disease continuum
MeSH terms: Alzheimer Disease, Humans, Biomarkers, Prevalence, Prodromal Symptoms

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

Global estimates on the number of persons across the Alzheimer's disease continuum

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