Frequency and clinical outcomes associated with tau positron emission tomography positivity

Alexis Moscoso; Fiona Heeman; Sheelakumari Raghavan; Alejandro Costoya-Sánchez; Martijn van Essen; Ismini Mainta; Valle Camacho; Omar Rodríguez-Fonseca; Jesús Silva-Rodríguez; Andrés Perissinotti; Yuna Gu; Jihwan Yun; Debora Peretti; Federica Ribaldi; Emma M Coomans; Wagner S Brum; Michel J Grothe; Pablo Aguiar; Gérard N Bischof; Alexander Drzezga; Sang Won Seo; Sylvia Villeneuve; Maura Malpetti; John T O’Brien; James B Rowe; Elsmarieke M van de Giessen; Rik Ossenkoppele; William J Jagust; Ruben Smith; Oskar Hansson; Giovanni B Frisoni; Valentina Garibotto; David N Soleimani-Meigooni; Maria Carrillo; Bradford C Dickerson; Renaud La Joie; Gil D Rabinovici; Liana G Apostolova; Pamela J LaMontagne; Michael J Pontecorvo; Keith A Johnson; Reisa A Sperling; Michael W Weiner; Ronald C Petersen; Clifford R Jack, Jr; Prashanthi Vemuri; Michael Schöll; for the PREVENT-AD Research Group; for the Harvard Aging Brain Study; for the LEADS Consortium; for the Alzheimer’s Disease Neuroimaging Initiative

doi:10.1001/jama.2025.7817

. Author manuscript; available in PMC: 2026 Jan 29.

Published in final edited form as: JAMA. 2025 Jul 15;334(3):229–242. doi: 10.1001/jama.2025.7817

Frequency and clinical outcomes associated with tau positron emission tomography positivity

Alexis Moscoso ^1,^2,^3,^*, Fiona Heeman ^1,², Sheelakumari Raghavan ⁴, Alejandro Costoya-Sánchez ^3,^5,⁶, Martijn van Essen ⁷, Ismini Mainta ⁸, Valle Camacho ⁹, Omar Rodríguez-Fonseca ¹⁰, Jesús Silva-Rodríguez ^6,¹¹, Andrés Perissinotti ^12,¹³, Yuna Gu ¹⁴, Jihwan Yun ¹⁵, Debora Peretti ¹⁶, Federica Ribaldi ^17,¹⁸, Emma M Coomans ^19,^20,²¹, Wagner S Brum ^1,²², Michel J Grothe ^1,^2,^6,¹¹, Pablo Aguiar ^3,²³, Gérard N Bischof ^24,²⁵, Alexander Drzezga ^24,^25,²⁶, Sang Won Seo ^14,^15,^27,²⁸, Sylvia Villeneuve ^29,^30,³¹, Maura Malpetti ^32,³³, John T O’Brien ³⁴, James B Rowe ^32,³⁵, Elsmarieke M van de Giessen ^19,²⁰, Rik Ossenkoppele ^20,^21,³⁶, William J Jagust ³⁷, Ruben Smith ^36,³⁸, Oskar Hansson ^36,³⁸, Giovanni B Frisoni ^17,¹⁸, Valentina Garibotto ^8,^16,³⁹, David N Soleimani-Meigooni ^40,⁴¹, Maria Carrillo ⁴², Bradford C Dickerson ⁴³, Renaud La Joie ⁴⁰, Gil D Rabinovici ^40,⁴⁴, Liana G Apostolova ^45,^46,⁴⁷, Pamela J LaMontagne ^48,⁴⁹, Michael J Pontecorvo ⁵⁰, Keith A Johnson ^51,⁵², Reisa A Sperling ^43,⁵², Michael W Weiner ^53,^54,^55,^56,⁵⁷, Ronald C Petersen ⁵⁸, Clifford R Jack Jr ⁴, Prashanthi Vemuri ⁴, Michael Schöll ^1,^2,^59,^60,^*; for the PREVENT-AD Research Group; for the Harvard Aging Brain Study; for the LEADS Consortium; for the Alzheimer’s Disease Neuroimaging Initiative

¹Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

²Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.

³Nuclear medicine department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostela, Travesía da Choupana s/n, Santiago de Compostela, Spain.

⁴Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA.

⁵Universidade de Santiago de Compostela, Santiago de Compostela, Spain.

⁶Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain.

⁷Department of Clinical Physiology, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden.

⁸Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland.

⁹Nuclear Medicine Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.

¹⁰Nuclear Medicine Department, Lucus Augusti University Hospital (HULA), 27003 Lugo, Spain.

¹¹Reina Sofía Alzheimer’s Centre, CIEN Foundation, ISCIII, Madrid, 28031, Spain.

¹²Nuclear Medicine Department, Hospital Clínic Barcelona-IDIBAPS, Barcelona, Spain.

¹³Biomedical Research Networking Centre of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), ISCIII, Barcelona, Spain.

¹⁴Samsung Alzheimer Research Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea.

¹⁵Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea.

¹⁶Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland.

¹⁷Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland.

¹⁸Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.

¹⁹Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.

²⁰Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.

²¹Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081HV Amsterdam, The Netherlands.

²²Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.

²³Molecular Imaging and Pharmacokinetic Modelling Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela, Spain.

²⁴Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany.

²⁵Research Center Juelich, Institute for Neuroscience and Medicine II, Molecular Organization of the Brain, Juelich, Germany.

²⁶German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.

²⁷Department of Clinical Research Design & Evaluation, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Korea.

²⁸Department of Health Science and Technology, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Korea.

²⁹McConnell Brain Imaging Centre, McGill University, Montreal, H3A 2B4, QC, Canada.

³⁰Douglas Mental Health University Institute—Research Center, Verdun, H4H 1R3, QC, Canada.

³¹Department of Psychiatry, McGill University, Montreal, H3A 1A1, QC, Canada.

³²Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0SZ, UK.

³³UK Dementia Research Institute at University of Cambridge, Cambridge CB2 0XY, UK.

³⁴Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom

³⁵Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.

³⁶Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.

³⁷Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, USA.

³⁸Memory Clinic, Skåne University Hospital, Lund University, Lund, Sweden.

³⁹CIBM Center for Biomedical Imaging, Geneva, Switzerland.

⁴⁰Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.

⁴¹Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.

⁴²Alzheimer’s Association, Chicago, IL, USA.

⁴³Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.

⁴⁴Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA.

⁴⁵Department of Neurology, Indiana University School of Medicine, 355 W 16th St, Indianapolis, IN, USA.

⁴⁶Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, 355W 16th St, Indianapolis, IN, USA.

⁴⁷Department of Medical and Molecular Genetics, Indiana University School of Medicine, 355W 16th St, Indianapolis, IN, USA.

⁴⁸Departments of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.

⁴⁹Knight Alzheimer’s Disease Research Center, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.

⁵⁰Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA.

⁵¹Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston.

⁵²Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, Massachusetts.

⁵³Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, California, USA.

⁵⁴Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.

⁵⁵Department of Medicine, University of California, San Francisco, California, USA.

⁵⁶Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, California, USA.

⁵⁷Department of Neurology, University of California, San Francisco, California, USA.

⁵⁸Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA.

⁵⁹Dementia Research Centre, Institute of Neurology, University College London, London, UK.

⁶⁰Department of Psychiatry, Cognition and Aging Psychiatry, Sahlgrenska University Hospital, Mölndal, Sweden.

Corresponding authors: Michael Schöll, Ph.D., Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. Address: Wallinsgatan 6, 431 41 Mölndal, Sweden, michael.scholl@neuro.gu.se; Alexis Moscoso, Ph.D., Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. Address: Wallinsgatan 6, 431 41 Mölndal, Sweden, alexis.moscoso@gu.se

PMCID: PMC12848857 NIHMSID: NIHMS2121854 PMID: 40522652

Abstract

Importance:

Tau-positron emission tomography (PET) allows in vivo detection of neurofibrillary tangles, a core neuropathologic feature of Alzheimer disease (AD).

Objective:

To provide estimates of the frequency of tau-PET positivity and its associated risk of clinical outcomes.

Design, Setting, and Participants:

Longitudinal study using data pooled from 21 cohorts, comprising a convenience sample of 6514 participants from 13 countries, collected between January 2013 and June 2024. Cognitively unimpaired individuals and patients with a clinical diagnosis of mild cognitive impairment (MCI), AD dementia, or other neurodegenerative disorders were included.

Exposures:

Tau-PET with [¹⁸F]flortaucipir, Aβ-PET, and clinical examinations. Tau-PET scans were visually rated as positive according to an FDA/EMA-approved method, designed to indicate the presence of advanced neurofibrillary tangle pathology (Braak stages V-VI).

Main Outcomes and Measures:

Frequency of tau-PET positivity and absolute risk of clinical progression (e.g., progression to MCI or dementia).

Results:

Among the 6514 participants (mean age, 69.5 years; 50.5% female), median follow-up time ranged from 1.5 to 4.0 years. Out of 3487 cognitively unimpaired participants, 349 (9.8%) were tau-PET-positive; the estimated frequency of tau-PET positivity was < 1% in those aged under 50 years, and increased from 3% [95% CI, 3%–4%] at 60 years to 19% [95% CI, 15%–24%] at 90 years. Tau-PET positivity frequency estimates increased across MCI and AD dementia clinical diagnoses (43% [95% CI, 41%–46%] and 79% [95% CI, 76%–82%] at 75 years, respectively). Most tau-PET-positive individuals (92%) were also Aβ-PET-positive. Cognitively unimpaired participants who were both Aβ-PET-positive and tau-PET-positive had a higher absolute risk of progression to MCI or dementia over the following 5 years (57% [95% CI, 45%–71%]) compared to both Aβ-PET-positive/tau-PET-negative (17% [95% CI, 12%–22%]) and Aβ-PET-negative/tau-PET-negative individuals (6% [95% CI, 5%–8%]). Among participants with MCI at the time of the tau-PET scan, an Aβ-PET-positive/tau-PET-positive profile was associated with a 5-year absolute risk of progression to dementia of 70% [95% CI, 59%–81%]).

Conclusions and Relevance:

In a large convenience sample, a positive tau-PET scan occurred at a non-negligible rate among cognitively unimpaired individuals, and the combination of Aβ-PET positivity and tau-PET positivity was associated with a high risk of clinical progression in both preclinical and symptomatic stages of AD. These findings underscore the potential of tau-PET as a biomarker for staging AD pathology.

INTRODUCTION

The development of imaging and fluid biomarkers of amyloid-β (Aβ) plaques,^1,2 a core neuropathologic feature of Alzheimer disease (AD),³ has had a major impact on AD research and drug development.⁴ Positron emission tomography (PET) imaging of Aβ has also demonstrated clinical utility in patients with mild cognitive impairment (MCI) or dementia of uncertain etiology.⁵ However, the precise clinical consequences of Aβ positivity in earlier stages of the disease remain uncertain, as Aβ positivity can occur in asymptomatic older individuals⁶ who remain symptom-free over their lifetime.⁷ This lack of strong correspondence between Aβ positivity and relevant outcomes has led some experts in the AD field to question the clinical utility of biological definitions of AD independent of symptoms,⁸ although this opinion is not universally accepted.⁹

Contrary to Aβ, autopsy studies have found that the presence of widespread neocortical tau neurofibrillary tangles, another neuropathologic hallmark of AD,³ was strongly associated with neurodegeneration and clinical symptoms.^10,11 This close relationship underscores the importance of detecting tau pathology in vivo, complementing the information provided by Aβ biomarkers. To date, the only biomarker of neurofibrillary tangles approved for clinical use by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) is tau-PET imaging with [¹⁸F]flortaucipir (formerly known as [¹⁸F]T807 or [¹⁸F]AV1451).¹² When assessed using an approved visual interpretation method, a positive [¹⁸F]flortaucipir PET scan reflects the presence of advanced neurofibrillary tangle pathology, corresponding to Braak stages V-VI at autopsy¹³. Braak staging¹⁴ is a neuropathological framework that describes the spatial progression of tau neurofibrillary tangle pathology in AD. In this system, stages I-II involve the transentorhinal region, III-IV extend to limbic areas, and V-VI represent the most advanced stages with widespread neocortical involvement. Clinically, Braak stages V-VI represent the neuropathological stage most closely associated significant cognitive impairment and dementia.^3,10,11,15

The investigation of tau-PET imaging using an FDA/EMA-approved method to establish positivity could provide valuable insights directly relevant for its use in clinical settings. However, previous studies on tau-PET have relied on the use of varying, non-clinically applicable definitions of tau-PET positivity, leading to conflicting results on crucial metrics that inform its potential utility. These include inconsistent frequency estimates of tau-PET positivity (e.g. ranging from 2–3%^16,17 to 20–50%^18–20 in Aβ-negative cognitively unimpaired individuals), as well as highly variable estimates of the risk of clinical progression associated with tau-PET positivity, with some studies suggesting limited relevance¹⁸ while others have reported a high risk.^16,17 To clarify the potential of tau-PET in clinical settings, it is essential to investigate the frequency of and outcomes associated with tau-PET positivity when established using clinically applicable methods.

The purpose of this study was to contribute to a better understanding of the potential of tau-PET by providing estimates of two key metrics: the frequency of tau-PET positivity and its associated risk of clinical progression. For this, we analyzed data from a large convenience sample of participants who underwent tau-PET imaging with an approved radiotracer, [¹⁸F]flortaucipir, in whom tau-PET positivity was determined using a clinically applicable visual interpretation method.

METHODS

Local institutional review boards for human research at each participating institution approved use of data for this study. All participants provided written informed consent. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

Participants

A convenience sample of 6514 participants pooled from 21 different cohorts was included (eMethods 1.1 and eTable 1). All participants underwent a tau-PET scan with [¹⁸F]flortaucipir between January 2013 and June 2024 and had a concurrent clinical evaluation. Participants were either cognitively unimpaired (defined as not MCI, dementia or any other major neurological disorder; see eMethods 1.1) or met established clinical criteria for a syndromic diagnosis of MCI,²¹ AD dementia (including posterior and logopenic variants),²² dementia with Lewy Bodies,²³ behavioral variant frontotemporal dementia,²⁴ semantic or nonfluent variant primary progressive aphasia,²⁵ Parkinson disease²⁶ with cognitive impairment, progressive supranuclear palsy,²⁷ or corticobasal syndrome.²⁸ This diagnostic categorization was based solely on the aforementioned clinical criteria, independent of biomarker results or dementia severity rating instruments.

In addition, to assess whether the frequency of visual tau-PET positivity (a proxy of Braak stages V-VI) was consistent with the frequency of autopsy-confirmed Braak stages V-VI across different ages, we conducted an indirect comparison using an independent sample of participants from the National Alzheimer’s Coordinating Center dataset. These participants were either cognitively unimpaired or had a clinical diagnosis of AD dementia within one year of death, and were assessed neuropathologically postmortem (“Neuropathology cohort”, n=3178).²⁹ None of these participants had available tau-PET scans.

PET imaging

All tau-PET scans were performed with [¹⁸F]flortaucipir and classified as either positive or negative using its FDA/EMA-approved visual interpretation method.¹² This method defines a scan as positive if it exhibits increased signal in posterolateral temporal, occipital, and/or parietal/precuneus regions, with or without elevated signal in frontal areas. A visually positive [¹⁸F]flortaucipir PET scan reflects Braak stages V-VI.¹³ Additional details can be found in eMethods 1.2.

To visually assess the large number of tau-PET scans in our sample, we gathered a team of 18 readers, including nuclear medicine physicians and neuroimaging researchers, who were trained using materials provided by Avid Radiopharmaceuticals to interpret [¹⁸F]flortaucipir PET scans (eMethods 1.3–1.4). The robustness of our visual interpretation procedure was validated in inter-rater agreement analyses (Cohen’s κ across readers, mean: 0.89, range 0.78–0.97, eResults 2.1 and eFigure 2).

Aβ-PET scans were available for most of the study participants (n=5729, 87.9%). Aβ-PET positivity was defined as a Centiloid³⁰ higher than 24.4³¹ or with visual reads.

Outcomes

The outcomes were 1) frequency of visual tau-PET positivity as a function of clinical diagnosis, age, Aβ-PET status, sex, and APOE ε4 carriership; and 2) clinically relevant progression among tau-PET-positive individuals. For the latter, we studied three different definitions of relevant progression as perceived by patients, caregivers, and clinicians:^32,33 a) progression to a clinical diagnosis of MCI or dementia among initially cognitively unimpaired individuals or progression to dementia among individuals with MCI; b) progression on the CDR Global score (CDR-G), defined as any increase in the score;³⁴ and c) group-level average Clinical Dementia Rating Sum of Boxes (CDR-SB) score after five years (baseline age 70 years) higher than 1 for cognitively unimpaired, 5 for MCI (baseline CDR-G 0.5–1), and 10 for mild AD dementia (baseline CDR-G 0.5–1), which correspond to scores consistent with MCI, mild AD dementia, and moderate AD dementia,³⁵ respectively. The CDR-G score ranges from 0 to 3, with higher values indicating more severe cognitive and functional impairment. The CDR-SB score ranges from 0 to 18, based on the sum of ratings across six domains; higher scores reflect greater overall impairment.

Clinical progressions to MCI or dementia at follow-up visits were established by the respective study clinicians and committees based on published criteria.^21,22,36 The CDR was administered through a semi-structured interview with both the participant and their study partner. While outcome assessors were not fully blinded to tau-PET scans, clinical assessments were conducted independently of biomarker and CDR results, and tau-PET visual reads were performed only after outcome ascertainment.

Statistical analysis

We used generalized additive models to derive frequency estimates of tau-PET positivity conditional on covariates (age, sex, APOE ε4 carriership, and Aβ-PET status) and diagnostic categories. Educational attainment was not included as covariate due to its limited association with clinical decline,^37,38 age-cohort differences, and the lack of a standardized education metric across the included studies. Of note, the models account for the impact of studies that overrepresent Aβ-positive individuals, such as the A4 study, on the frequency of tau-PET positivity. 95% confidence intervals were calculated using either the Wald approximation when estimates were derived directly from model predictions or using the bootstrap method (n=1000 repetitions) when estimates involved combining predictions from multiple models. Additional details can be found in eMethods 1.5.

Generalized additive mixed models were used to estimate average temporal trajectories of the CDR-SB score (eMethods 1.6). 95% confidence intervals were calculated using the Wald approximation.

The probability of clinical progression over the next 5 years (for cognitively unimpaired and MCI) or 3 years (for AD dementia) across different Aβ-PET/tau-PET profiles was estimated using illness-death models, which is the simplest form of a multistate Markov model.³⁹ This approach combines the “naïve” hazard functions for clinical progression and mortality to account for the competing risk of death during follow-up precluding clinical progression, allowing for the estimation of unbiased probabilities of progression (eMethods 1.7). The “naïve” hazard functions describing clinical progression were estimated using either Kaplan Meier estimators (for global absolute risk estimates) or Cox proportional hazards regression (for age- and sex-specific absolute risk estimates). Because death events were not consistently recorded across all cohorts included in this study, we followed a previously published approach⁴⁰ and estimated “naïve” hazard functions for mortality based on publicly available life tables from the 2019 U.S. general population (https://mortality.org/). These estimates were further adjusted to account for the increased mortality risk associated with MCI or dementia⁴¹ (see eMethods 1.7). 95% confidence intervals of the estimated absolute risks were computed using bootstrap (n=1000 repetitions).

Analyses of the clinical outcomes of the Aβ-PET-negative/tau-PET-positive groups were regarded as exploratory due to reduced sample size and reported in the Online Supplement.

Analyses of between-cohort variability in the frequency of positivity and risk estimates were performed by estimating the additional explained variation that can be attributed to cohort membership (eMethods 1.8).

All analyses were conducted using the full pooled dataset, with statistical models run separately for cognitively unimpaired and cognitively impaired individuals. A complete-case approach was applied, as the proportion of missing Aβ-PET, APOE ε4, and CDR data was relatively small compared to the overall dataset. Sensitivity analyses using multiple imputation yielded results consistent with the primary findings, indicating that the impact of the missing data was minimal. A two-sided P value < 0.05 was considered statistically significant. R version 4.3.2 (R Foundation for Statistical Computing) and MATLAB 2023b (The MathWorks) were used for all statistical analyses.

RESULTS

A total of 6514 participants with tau-PET scans (mean age, 69.5 years; 50.5% female) pooled from 21 different cohorts were included. Baseline and follow-up characteristics of the included participants are reported in Table 1, eTables 2–9, and eFigure 1.

Table 1.

Characteristics of the study participants.

Baseline Characteristics	Cognitively unimpaired (n=3487)	Mild cognitive impairment (n=1326)	Alzheimer disease dementia (n=1332)	Dementia with Lewy Bodies (n=81)	Behavioral-variant FTD (n=69)	Semantic variant PPA (n=29)	Non-fluent variant PPA (n=29)	Parkinson disease (n= 31)	Progressive supranuclear palsy (n= 73)	Corticobasal syndrome (n=57)
Age, median (Q1, Q3), y	70 (65, 77)	72 (65, 78)	69 (60, 76)	70 (66, 75)	65 (58, 69)	67 (63, 70)	70 (58, 75)	71 (65, 75)	71 (66, 74)	70 (64, 74)
Sex, women, No (%)	1875 (53.8)	565 (42.6)	695 (52.2)	17 (21.0)	33 (47.8)	9 (31.0)	19 (65.5)	11 (35.5)	36 (49.3)	29 (50.9)
APOE ε4 carrier, No (%)	1069 (34.2) [NA: 363]	453 (44.4) [NA: 305]	617 (63.3) [NA: 358]	24 (42.1) [NA: 24]	6 (27.3) [NA: 47]	2 (25.0) [NA: 21]	1 (33.3) [NA: 26]	NA	NA	0 (0.0) [NA: 56]
Clinical Dementia Rating (CDR)
CDR-Global^a, median (range)	0 (0 to 0.5)	0.5 (0 to 2)	1 (0 to 3)	1 (0 to 3)	1 (0 to 2)	0.5 (0 to 2)	0.5 (0 to 3)	0.5 (0 to 2)	0.5 (0 to 3)	0.5 (0 to 2)
CDR-Sum of boxes^b, median (range)	0 (0 to 4)	1.5 (0 to 12)	4.5 (0 to 18)	4.8 (1.5 to 17)	5.5 (0.5 to 12)	3 (0 to 7.5)	1.5 (0 to 14)	4 (0 to 12)	4 (0 to 15)	1.5 (0 to 10)
Not assessed	534	148	211	32	15	10	9	0	40	22
Aβ-PET
Centiloid^c, mean (range)	26 (−37 to 212)	49 (−39 to 248)	88 (−31 to 196)	50 (−6 to 157)	10 (−32 to 122)	25 (−7 to 113)	16 (−14 to 141)	4 (−5 to 44)	9 (−11 to 69)	8 (−34 to 127)
Aβ-positive (> 24.4 Centiloids), No (%)	1074 (34.1)	695 (57.9)	1050 (90.8)	35 (59.3)	8 (18.2)	5 (29.4)	3 (16.7)	1 (10.0)	5 (19.2)	9 (17.0)
Not assessed	342	126	175	22	25	12	11	21	47	4
Tau-PET
Positive^d, No (%)	343 (9.8)	605 (45.6)	1165 (87.5)	29 (35.8)	23 (33.3)	20 (69.0)	9 (31.0)	9 (29.0)	3 (4.1)	15 (26.3)
Follow-up characteristics ^e
Participants with follow-up data, No
Clinical diagnosis	1977	490	NA	NA	NA	NA	NA	NA	NA	NA
Clinical Dementia Rating	2253	647	560	NA	NA	NA	NA	NA	NA	NA
Follow-up time, median^f (maximum), y
Clinical diagnosis	3.8 (7.1)	2.9 (6.8)	NA	NA	NA	NA	NA	NA	NA	NA
Clinical Dementia Rating	4.0 (8.1)	1.7 (7.0)	1.5 (6.4)	NA	NA	NA	NA	NA	NA	NA

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Abbreviations: FTD, frontotemporal dementia; PPA, primary progressive aphasia; APOE-ε4, apolipoprotein ε4 allele; CDR, Clinical dementia rating; Aβ, amyloid-β; PET, positron emission tomography; NA, not assessed/available.

Clinical Dementia Rating-Global scores range from 0 (best) to 3 (worst).

Clinical Dementia Rating-Sum of boxes scores range from 0 (best) to 18 (worst).

Assessed with [¹⁸F]florbetapir, [¹⁸F]florbetaben, [¹⁸F]NAV4694 or [¹¹C]PiB.

Assessed using the approved visual interpretation method for [¹⁸F]flortaucipir PET.

Longitudinal analyses included only participants with Aβ status available at baseline. For those with MCI or AD dementia, a baseline CDR-G score of 0.5 or 1 was also required.

Median follow-up times were estimated using the reverse Kaplan-Meier method.⁵²

Frequency of tau-PET positivity

Out of 3487 cognitively unimpaired participants, 349 (9.8%) were tau-PET-positive. Quantitative neuroimaging analyses revealed significantly elevated tau-PET signal in temporo-parietal and frontal regions (eResults 2.2 and eFigure 3). The estimated frequency of tau-PET positivity in cognitively unimpaired aged under 50 years was below 1%, and increased from 3% [95% CI, 3%–4%] at 60 years to 19% [95% CI, 15%–24%] at 90 years (Figure 1A, eTable 10). The estimated frequency of Braak stages V-VI in cognitively unimpaired participants from the Neuropathology cohort paralleled that of tau-PET positivity until ~60 years of age but was consistently lower for older ages (Figure 1A, eTable 10).

Tau-PET positivity was more frequent among the 1326 patients with MCI and 1332 patients with AD dementia. In patients with MCI, the estimated frequency at 40 years was 26% [95% CI, 20%–33%] and increased with age (from 35% [95% CI, 31%–39%] at 60 years to 51% [95% CI, 46%–57%] at 90 years, Figure 1B, eTable 10). Among participants with clinically diagnosed AD dementia, tau-PET positivity was estimated to be >85% under 65 years of age; however, its estimated frequency decreased with advancing age (from 88% [95% CI, 86%–91%] at 60 years to 65% [95% CI, 58%–72%] at 90 years, Figure 1C, eTable 10). This decreasing trend was also observed for the frequency estimates of Braak stages V-VI in the Neuropathology cohort, which closely matched the frequency curve of tau-PET positivity (Figure 1C, eTable 10).

Estimates of tau-PET positivity for other neurodegenerative disorders are displayed in Figure 1D. The estimated frequency of positivity was relatively high in frontotemporal dementia patients, particularly in those with semantic variant primary progressive aphasia (20/29, 69% [95% CI, 49%–85%]), the majority of whom were Aβ-PET negative (eFigure 4D).

Among cognitively unimpaired participants and those with a clinical diagnosis of MCI and AD dementia, tau-PET positivity was more frequently observed in Aβ-PET-positive than in Aβ-PET-negative individuals (Aβ-PET-positive vs Aβ-PET-negative, cognitively unimpaired: 268/1074, 25% [95% CI, 22%–28%] vs 46/2071, 2% [95% CI, 2%–3%]; MCI: 511/695, 74% [95% CI, 70%–77%] vs 43/505, 9% [95% CI, 6%–11%]; AD dementia: 976/1050, 93% [95% CI, 91%–94%] vs 33/107, 31% [95% CI, 22%–40%], eFigure 4A–C). Older age was associated with higher frequency estimates of tau-PET positivity among Aβ-PET-positive cognitively unimpaired individuals, but with lower frequencies among those Aβ-PET-positive participants with MCI or AD dementia (Figure 2A, eTable 11). In Aβ-PET-negative participants, the estimated frequency of positivity increased with age in the cognitively unimpaired and MCI groups, while remained approximately constant or decreased slightly for those Aβ-PET-negative participants with AD dementia (Figure 2B, eTable 11). Higher Aβ levels (Centiloids) were associated with increased probability of a positive tau-PET scan in a dose-dependent manner (eFigure 5).

Figure 2. — Frequency of tau-PET positivity among Aβ-PET-positive and Aβ-PET-negative individuals, stratified by clinical diagnosis.

Panels A and B show the estimated frequency of tau-PET positivity as a function of age among Aβ-PET-positive and Aβ-PET-negative individuals, separately for cognitively unimpaired (grey), mild cognitive impairment (green), and patients with a clinical diagnosis of Alzheimer disease dementia (red). Whiskers represent 95% confidence intervals.

Abbreviations: Aβ, amyloid-β; PET, positron emission tomography.

Frequency estimates of tau-PET positivity according to age, Aβ-PET status, sex, and APOE ε4 carriership can be seen in eFigures 6–7 and eTables 12–15. The estimated frequency of tau-PET positivity was higher in Aβ-PET-positive cognitively impaired women than in men (75-year-old MCI, 74% for women vs 62% for men, difference 12% [95% CI, 6%–19%]; 75-year-old AD dementia, 91% for women vs 85% for men, difference 6% [95% CI, 3%–9%], eFigure 6), but this association was not statistically significant in cognitively unimpaired individuals (eFigure 6C–D, eTables 12–14). APOE ε4 carriership was associated with increased probability of tau-PET positivity in both Aβ-PET-negative and Aβ-PET-positive cognitively unimpaired (75-year-old Aβ-PET-negative: 4% for carriers vs 2% for non-carriers, difference 2% [95% CI, 0%–3%]; 75-year-old Aβ-PET-positive: 32% for carriers vs 21% for non-carriers, difference 11% [95% CI, 7%–17%]) and Aβ-PET-positive impaired individuals (75-year-old MCI, 71% for carriers vs 59% for non-carriers, difference 12% [95% CI, 5%–19%]; 75-year-old AD dementia, 90% for carriers vs 85% for non-carriers, difference 5% [95% CI, 2%–10%]) (eFigure 6A–B, eTables 12–14). These associations were largely attenuated in Aβ-PET-negative cognitively impaired individuals (eFigure 7, eTable 15).

Percent deviance attributable to cohort differences was 0.8% for cognitively unimpaired and 11.1% for symptomatic participants, indicating relatively low cohort-related variability in frequency estimates. Visual inspection of study-specific estimates also confirmed low variability (eFigure 8).

Clinical outcomes

The Aβ-PET-positive/tau-PET-positive profile was associated with a significantly increased estimated risk of experiencing all the evaluated clinical outcomes compared to both the Aβ-PET-negative/tau-PET-negative and Aβ-PET-positive/tau-PET-negative profiles (Figure 3, Table 2, eTables 16–17). For example, among initially cognitively unimpaired individuals with an Aβ-PET-positive/tau-PET-positive profile, the cause-specific hazard ratio for progression to MCI or dementia was 8.1 [95% CI, 5.5–12.0], P < .001 compared with Aβ-PET-negative/tau-PET-negative cognitively unimpaired, and 3.8 [95% CI, 2.6 to 5.6], P < 0.001 compared with those with an Aβ-PET-positive/tau-PET-negative profile. Similar findings were observed for Aβ-PET-positive/tau-PET-positive individuals with MCI, with a hazard ratio of 6.8 [95% CI, 4.1 to 11.0], P<0.001 for progression to dementia compared to the Aβ-PET-negative/tau-PET-negative MCI group, and a hazard ratio of 4.7 [95% CI, 2.6 to 8.4], P < 0.001 compared to the Aβ-PET-positive/tau-PET-negative MCI group.

Figure 3. — Clinical outcomes of tau-PET-positive individuals.

Aβ± and vTAU± represent Aβ-PET and tau-PET status (positive/negative), respectively.

Panels A and B show Kaplan-Meier-based estimates of the absolute risk (accounting for the competing risk of death during follow-up) of clinical progression, defined as progression to MCI or dementia among initially cognitively unimpaired individuals (A) or progression to dementia among individuals with MCI (B), according to different Aβ-PET/tau-PET biomarker profiles. The inserts show covariate-adjusted *cause-specific* hazard ratios (HR) of clinical progression (see Statistical Analysis section), using the respective Aβ-PET-negative/tau-PET-negative profile as the reference; quantities between parentheses are 95% confidence intervals. Panels C and D show Kaplan-Meier-based estimates of the absolute risk (accounting for the competing risk of death during follow-up) of progressing CDR-G, defined as any increase in the score, across initially cognitively unimpaired individuals and patients with MCI or AD dementia. The inserts show covariate-adjusted *cause-specific* hazard ratios (HR) of progressing CDR-G, using the respective Aβ-PET-negative/tau-PET-negative group as the reference; quantities between parentheses are 95% confidence intervals. Crosses on Kaplan Meier curves from panels A-E represent censored time points. Panels E and F show average trajectories of the CDR-SB score (range, 0 to 18, with higher scores indicating worse clinical symptoms) among cognitively unimpaired individuals and patients with MCI or AD dementia, according to Aβ-PET/tau-PET profiles. Dashed and dotted lines represent previously specified CDR-SB scores consistent with MCI (panel E, dashed line), mild AD dementia (panel F, dashed line), or moderate AD dementia (panel F, dotted line) (see Outcomes section). Modelled trajectories are conditional on age (70 years). Shaded areas represent 95% confidence intervals. All the aforementioned analyses in participants with MCI and AD dementia were restricted to individuals with baseline CDR-G of 0.5 or 1. Exploratory analyses of the Aβ-PET-negative/tau-PET-positive group are reported in the Online Supplement (eFigure 9).

Abbreviations: Aβ, amyloid-β; AD, Alzheimer disease; CDR-G, Clinical Dementia Rating Global score; CDR-SB, Clinical Dementia Rating Sum of Boxes score; MCI, mild cognitive impairment; PET, positron emission tomography; vTAU, tau-PET status (positive/negative).

Table 2.

Absolute risk of clinical progression, by Aβ-PET/tau-PET profile.

	Absolute risk, % (95% CI)
Outcome	Aβ−/vTAU−	Aβ+/vTAU−	Aβ+/vTAU+
Progression to MCI or dementia over the next 5 years among cognitively unimpaired	6.4 (4.7 to 8.2)	16.6 (12.5 to 21.8)	57.4 (45.4 to 70.8)
Progression to dementia over the next 5 years among MCI	15.3 (9.5 to 22.2)	30.4 (15.9 to 47.8)	69.9 (59.3 to 81.2)
Progressing CDR-G score over the next 5 years among cognitively unimpaired	7.8 (6.0 to 9.6)	20.0 (16.5 to 23.7)	56.1 (48.2 to 64.2)
Progressing CDR-G score over the next 5 years among MCI	11.1 (5.9 to 17)	15.2 (6.6 to 24.9)	60.6 (49.2 to 72.6)
Progressing CDR-G score over the next 3 years among AD dementia	33.9 (15.5 to 55.7)	32.4 (20.6 to 44.9)	67.2 (60.8 to 73.6)

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Aβ± and vTAU± represent Aβ-PET and tau-PET status (positive/negative), respectively.

Shown are the estimated absolute risks of clinical progression (i.e. the probability of clinical progression accounting for the competing risk of death during follow-up, see eMethods 1.7 for details) to different outcomes among initially cognitively unimpaired, MCI or AD dementia individuals with different Aβ-PET/tau-PET biomarker profiles. 95% confidence intervals were estimated using bootstrap.

Abbreviations: Aβ, amyloid-β; AD, Alzheimer disease; CDR-G, Clinical Dementia Rating Global score; MCI, mild cognitive impairment; PET, positron emission tomography; vTAU, tau-PET status (positive/negative).

The Aβ-PET-positive/tau-PET-positive profile was associated with a high absolute risk of progression to MCI or dementia among initially cognitively unimpaired individuals (5-year absolute risk: 57.4% [95% CI, 45.4%–70.8], Figure 3A and eTable 18) as well as to progression to dementia among participants with MCI (5-year absolute risk: 69.9% [95% CI, 59.3%–81.2%], Figure 3B and eTable 19). Moreover, the 5-year absolute risk estimates of progression were dependent on baseline age and sex for both Aβ-PET-positive/tau-PET-positive cognitively unimpaired (60 years, 30% [95% CI, 17%–43%] for women vs 31% [95% CI, 16%–45%] for men; 80 years, 63% [95% CI, 52%–75%] for women vs 62% [95% CI, 50%–74%] for men) and Aβ-PET-positive/tau-PET-positive participants with MCI (60 years, 77% [95% CI, 59%–90%] for women vs 74% [95% CI, 55%–88%] for men; 80 years, 71% [95% CI, 55%–84%] for women vs 66% [95% CI, 55%–76%] for men). Similarly, Aβ-PET-positive/tau-PET-positive individuals were at high risk of progression on all the CDR-G outcomes (Figure 3C–D, Table 2, eTables 17, 20–22). Additional estimates of the absolute risks of clinical progression, conditional on age and sex, are provided in eTables 18–22. At the group level, only the Aβ-PET-positive/tau-PET-positive groups surpassed specified thresholds on the CDR-SB at five years (Figure 3E–F).

The outcomes of the Aβ-PET-positive/tau-PET-negative groups were more similar to those of the corresponding Aβ-PET-negative/tau-PET-negative groups, particularly among symptomatic (MCI or AD dementia) participants (Figure 3 and eTable 23). Analyses of the Aβ-PET-negative/tau-PET-positive groups revealed numerically higher rates of clinical decline compared with their Aβ-PET-negative/tau-PET-negative counterparts (eFigure 9).

Explainable variation in risk of clinical progression attributable to cohort membership ranged from 8.8% to 33.3% (eTable 24). Percent deviance on CDR-SB trajectories attributable to cohort membership was low (0.2% for cognitively unimpaired and 0.3% for symptomatic participants), and visual inspection of cohort-specific trajectories confirmed limited variability (eFigure 10).

DISCUSSION

In this study that applied an FDA/EMA-approved method for determining tau-PET positivity in a large convenience sample from 21 pooled cohorts, the findings suggest that cognitively unimpaired older individuals have visually positive tau-PET scans more frequently than previously suggested,⁴² exceeding frequencies of 10% in those aged 75 and older. Tau-PET positivity in the cognitively unimpaired group was also systematically higher than the prevalence of Braak stages V-VI in an independent cognitively unimpaired sample from the Neuropathology cohort (Figure 1A). This discrepancy likely reflects selection bias in the Neuropathology cohort,⁴³ which overrepresents healthy older individuals who reached old age (median age at death: 88 years) without experiencing cognitive decline. As a result, this population tends to have a lower AD neuropathologic burden, leading to a lower frequency of Braak stages V-VI.²⁹ Moreover, the fact that most of the tau-PET-positive cognitively unimpaired individuals were also Aβ-positive (85%), exhibited elevated tau-PET signal in regions consistent with Braak V-VI stages (eFigure 3), and were at high risk of clinical progression (Figure 3) suggest that the FDA/EMA-approved method for defining tau-PET positivity is indeed reflecting neurofibrillary tangle pathology in these individuals.

Previous studies have reported conflicting findings on the clinical outcomes of Aβ-positive/tau-PET-positive cognitively unimpaired individuals,^16–18 leaving the implications of this biomarker profile unclear. These discrepancies may stem from substantial differences in how tau-PET positivity was defined across studies, including variations in cut-points, brain regions, quantification methods, and radiotracers. Consequently, these studies may lack generalizability to clinical practice, where only approved methods for visual tau-PET assessment are used. In the present study that used an FDA/EMA-approved method for determining tau-PET positivity, an Aβ-PET-positive/tau-PET-positive profile in cognitively unimpaired individuals was associated with higher rates of progression to MCI or dementia over the following 5 years compared with their Aβ-PET-positive/tau-PET-negative and Aβ-PET-negative/tau-PET-negative counterparts. These results highlight the potential clinical relevance of Aβ-PET and tau-PET positivity in the absence of symptoms.

In AD dementia, the frequency curve of tau-PET positivity closely matched that of Braak V-VI derived in the Neuropathology cohort (Figure 1C), further supporting that a positive tau-PET scan reflects advanced tau pathology in AD.¹³ The decrease in frequency with age is likely attributable to two factors: 1) with advancing age, neuropathological changes other than AD pathology are more likely to result in an AD-like clinical syndrome;^44,45 and 2) with advancing age, the likelihood of developing comorbid Aβ pathology increases.⁶ These two phenomena lead to a higher frequency of elderly individuals with an AD-like clinical syndrome primarily caused by a non-AD condition, in whom comorbid Aβ pathology is present.^46,47

An Aβ-PET-positive/tau-PET-positive profile was associated with increased incidence of clinically relevant outcomes in both participants with MCI and early AD dementia (Figure 3). These results suggest that tau-PET positivity is a reliable indicator of AD pathology being a dominant contributor to clinical symptoms. However, interpretation of tau-PET findings must consider that positivity can also occur in Aβ-negative patients. The reasons behind tau-PET positivity in the absence of Aβ remain unclear, although explanations include [¹⁸F]flortaucipir binding to AD-like tau aggregates present in tangle-dominant forms of dementia,⁴⁸ binding to targets other than tau, and false positive Aβ-PET and/or tau-PET scans. It is also important to note that tau-PET radiotracers other than [¹⁸F]flortaucipir may have different off-target binding profiles,⁴⁹ and the frequency of positivity in Aβ-negative conditions with these radiotracers may differ from the estimates derived in this study.

Between 10% to 30% of the participants with a clinical diagnosis of dementia with Lewy bodies, behavioral variant frontotemporal dementia, semantic or nonfluent variant primary progressive aphasia, or corticobasal syndrome exhibited an Aβ-positive/tau-PET-positive profile (eFigure 4). While Aβ positivity alone should not be used to infer that AD pathology is a primary contributor to symptoms in non-AD disorders,⁴² the relevance of concurrent Aβ and tau-PET positivity in these patients remains uncertain. Future studies are needed to clarify the relevance of this profile in these non-AD conditions.

Tau-PET positivity was more frequent in cognitively impaired females, consistent with prior reports of sex-related increases in tau-PET signal.⁵⁰ This pattern was not observed in cognitively unimpaired individuals, possibly due to subthreshold or regionally restricted differences. Similarly, higher tau-PET positivity rates among APOE ε4 carriers align with previously observed tau-PET signal elevations associated with this genotype.⁵¹

Limitations

This study has several limitations. First, pooling data from independent studies may introduce biases due to differences in study design. However, complementary analyses showed limited cohort-related variability, with relatively small between-cohort differences (eFigures 8, 10, and eTable 24). Second, cognitively unimpaired individuals were primarily recruited from research cohorts that are not representative of the general population, which may have introduced bias in the estimated frequency of tau-PET positivity. However, comparisons with estimates derived solely from the Mayo Clinic Study of Aging—a population-based cohort—revealed only minimal differences (eFigure 11), suggesting that any potential bias is likely limited. Third, absolute risk estimates were informed by incorporating 2019 U.S. mortality rates into the estimates and may differ in populations with varying life expectancies. Fourth, despite being the largest tau-PET study using clinically approved methods, the sample sizes for Aβ-PET-negative/tau-PET-positive individuals, other neurodegenerative disorders, and those aged 90+ were relatively small and should be interpreted with caution. Fifth, tau-PET quantification or alternative visual read methods might detect early tau deposition (e.g., isolated mesial temporal signal) that is not captured by [¹⁸F]flortaucipir’s visual interpretation, which may also be linked to higher clinical progression risk.¹⁶ Sixth, this study only included [¹⁸F]flortaucipir PET scans, as second-generation tau tracers currently lack a standardized, neuropathologically validated, and clinically approved definition of tau-PET positivity. Seventh, many cohorts did not collect race or ethnicity data, preventing a robust analysis of the influence of these factors on tau-PET positivity and clinical outcomes. Additionally, the majority of participants were White and thus the generalizability of these findings to more diverse populations remains to be confirmed.

CONCLUSIONS

In conclusion, tau-PET positivity is detectable in a small but non-negligible proportion of individuals in the preclinical stages of AD, with increasing frequency in symptomatic stages of the disease. The combination of a positive tau-PET scan with a positive Aβ-PET scan was associated with an increased risk of clinically relevant outcomes across the entire AD spectrum. These findings highlight the potential role of tau-PET for staging AD-related neuropathologic changes.

Supplementary Material

NIHMS2121854-supplement-Supplementary_Material.docx^{(6.1MB, docx)}

KEY POINTS.

Question:

What is the frequency of tau positron emission tomography (PET) positivity, defined using a clinically applicable visual interpretation method, and its associated risk of cognitive decline?

Findings:

In this longitudinal cohort study that included a convenience sample of 6514 participants from 21 cohorts, 9.8% of cognitively unimpaired individuals had positive tau-PET scans, and the frequency of positivity increased with age and across increasingly symptomatic stages of Alzheimer disease (AD). Participants who were both amyloid-β (Aβ)-PET-positive and tau-PET-positive had a higher risk of clinically relevant cognitive decline over the following 5 years compared to both Aβ-PET-positive/tau-PET-negative and Aβ-PET-negative/tau-PET-negative individuals.

Meaning:

These findings underscore the potential role of tau-PET as a biomarker for staging AD neuropathologic changes across the spectrum of the disease.

ACKNOWLEDGEMENTS

The Mayo Clinic Study of Aging data was obtained under the research grant U01 AG006786. Data collection and sharing for this project was funded in part by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. The A4 Study was funded by a public-private-philanthropic partnership, including funding from the National Institutes of Health-National Institute on Aging, Eli Lilly and Company, Alzheimer's Association, Accelerating Medicines Partnership, GHR Foundation, an anonymous foundation, and additional private donors, with in-kind support from Avid Radiopharmaceuticals, Cogstate, Albert Einstein College of Medicine and the Foundation for Neurologic Diseases. The companion observational Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) Study was funded by the Alzheimer's Association and GHR Foundation. The A4 and LEARN Studies were led by Dr. Reisa Sperling at Brigham and Women's Hospital, Harvard Medical School, and Dr. Paul Aisen at the Alzheimer's Therapeutic Research Institute (ATRI) at the University of Southern California. The A4 and LEARN Studies were coordinated by ATRI at the University of Southern California, and the data are made available under the auspices of Alzheimer’s Clinical Trial Consortium through the Global Research & Imaging Platform (GRIP). The complete A4 Study Team list is available on: https://www.actcinfo.org/a4-study-team-lists/. We would like to acknowledge the dedication of the study participants and their study partners who made the A4 and LEARN Studies possible. Data were provided in part by OASIS-3: Longitudinal Multimodal Neuroimaging: Principal Investigators: T. Benzinger, D. Marcus, J. Morris; NIH P30 AG066444, P50 AG00561, P30 NS09857781, P01 AG026276, P01 AG003991, R01 AG043434, UL1 TR000448, R01 EB009352. AV-45 doses were provided by Avid Radiopharmaceuticals, a wholly owned subsidiary of Eli Lilly; and OASIS-3_AV1451: Principal Investigators: T. Benzinger, J. Morris; NIH P30 AG066444, AW00006993. AV-1451 doses were provided by Avid Radiopharmaceuticals, a wholly owned subsidiary of Eli Lilly. Data collection and dissemination of the data presented in this manuscript was supported by the LEADS Consortium (R56/U01 AG057195, funded by the National Institute on Aging). The manuscript has been reviewed by the LEADS Publications Committee for scientific content. The authors acknowledge the invaluable contributions of the participants in LEADS as well as the assistance of the investigators and support staff at each of the participating sites. The A05, PX01, and LZAX studies were supported by Avid Radiopharmaceuticals and/or Eli Lilly and Company. The NACC database is funded by NIA/NIH Grant U24 AG072122. NACC data are contributed by the NIA-funded ADRCs: P30 AG062429 (PI James Brewer, MD, PhD), P30 AG066468 (PI Oscar Lopez, MD), P30 AG062421 (PI Bradley Hyman, MD, PhD), P30 AG066509 (PI Thomas Grabowski, MD), P30 AG066514 (PI Mary Sano, PhD), P30 AG066530 (PI Helena Chui, MD), P30 AG066507 (PI Marilyn Albert, PhD), P30 AG066444 (PI John Morris, MD), P30 AG066518 (PI Jeffrey Kaye, MD), P30 AG066512 (PI Thomas Wisniewski, MD), P30 AG066462 (PI Scott Small, MD), P30 AG072979 (PI David Wolk, MD), P30 AG072972 (PI Charles DeCarli, MD), P30 AG072976 (PI Andrew Saykin, PsyD), P30 AG072975 (PI David Bennett, MD), P30 AG072978 (PI Neil Kowall, MD), P30 AG072977 (PI Robert Vassar, PhD), P30 AG066519 (PI Frank LaFerla, PhD), P30 AG062677 (PI Ronald Petersen, MD, PhD), P30 AG079280 (PI Eric Reiman, MD), P30 AG062422 (PI Gil Rabinovici, MD), P30 AG066511 (PI Allan Levey, MD, PhD), P30 AG072946 (PI Linda Van Eldik, PhD), P30 AG062715 (PI Sanjay Asthana, MD, FRCP), P30 AG072973 (PI Russell Swerdlow, MD), P30 AG066506 (PI Todd Golde, MD, PhD), P30 AG066508 (PI Stephen Strittmatter, MD, PhD), P30 AG066515 (PI Victor Henderson, MD, MS), P30 AG072947 (PI Suzanne Craft, PhD), P30 AG072931 (PI Henry Paulson, MD, PhD), P30 AG066546 (PI Sudha Seshadri, MD), P20 AG068024 (PI Erik Roberson, MD, PhD), P20 AG068053 (PI Justin Miller, PhD), P20 AG068077 (PI Gary Rosenberg, MD), P20 AG068082 (PI Angela Jefferson, PhD), P30 AG072958 (PI Heather Whitson, MD), P30 AG072959 (PI James Leverenz, MD). Data collected by SCAN and shared by NACC are contributed by the NIA-funded ADRCs as follows: Arizona Alzheimer’s Center - P30 AG072980 (PI: Eric Reiman, MD); R01 AG069453 (PI: Eric Reiman (contact), MD); P30 AG019610 (PI: Eric Reiman, MD); and the State of Arizona which provided additional funding supporting our center; Boston University - P30 AG013846 (PI Neil Kowall MD); Cleveland ADRC - P30 AG062428 (James Leverenz, MD); Cleveland Clinic, Las Vegas - P20AG068053; Columbia - P50 AG008702 (PI Scott Small MD); Duke/UNC ADRC - P30 AG072958; Emory University - P30AG066511 (PI Levey Allan, MD, PhD); Indiana University - R01 AG19771 (PI Andrew Saykin, PsyD); P30 AG10133 (PI Andrew Saykin, PsyD); P30 AG072976 (PI Andrew Saykin, PsyD); R01 AG061788 (PI Shannon Risacher, PhD); R01 AG053993 (PI Yu-Chien Wu, MD, PhD); U01 AG057195 (PI Liana Apostolova, MD); U19 AG063911 (PI Bradley Boeve, MD); and the Indiana University Department of Radiology and Imaging Sciences; Johns Hopkins - P30 AG066507 (PI Marilyn Albert, Phd.); Mayo Clinic - P50 AG016574 (PI Ronald Petersen MD PhD); Mount Sinai - P30 AG066514 (PI Mary Sano, PhD); R01 AG054110 (PI Trey Hedden, PhD); R01 AG053509 (PI Trey Hedden, PhD); New York University - P30AG066512-01S2 (PI Thomas Wisniewski, MD); R01AG056031 (PI Ricardo Osorio, MD); R01AG056531 (PIs Ricardo Osorio, MD; Girardin Jean-Louis, PhD); Northwestern University - P30 AG013854 (PI Robert Vassar PhD); R01 AG045571 (PI Emily Rogalski, PhD); R56 AG045571, (PI Emily Rogalski, PhD); R01 AG067781, (PI Emily Rogalski, PhD); U19 AG073153, (PI Emily Rogalski, PhD); R01 DC008552, (M.-Marsel Mesulam, MD); R01 AG077444, (PIs M.-Marsel Mesulam, MD, Emily Rogalski, PhD); R01 NS075075 (PI Emily Rogalski, PhD); R01 AG056258 (PI Emily Rogalski, PhD); Oregon Health and Science University - P30 AG008017 (PI Jeffrey Kaye MD); R56 AG074321 (PI Jeffrey Kaye, MD); Rush University - P30 AG010161 (PI David Bennett MD); Stanford - P30AG066515; P50 AG047366 (PI Victor Henderson MD MS); University of Alabama, Birmingham - P20; University of California, Davis - P30 AG10129 (PI Charles DeCarli, MD); P30 AG072972 (PI Charles DeCarli, MD); University of California, Irvine - P50 AG016573 (PI Frank LaFerla PhD); University of California, San Diego - P30AG062429 (PI James Brewer, MD, PhD); University of California, San Francisco - P30 AG062422 (Rabinovici, Gil D., MD); University of Kansas - P30 AG035982 (Russell Swerdlow, MD); University of Kentucky - P30 AG028283-15S1 (PIs Linda Van Eldik, PhD and Brian Gold, PhD); University of Michigan ADRC - P30AG053760 (PI Henry Paulson, MD, PhD) P30AG072931 (PI Henry Paulson, MD, PhD) Cure Alzheimer's Fund 200775 - (PI Henry Paulson, MD, PhD) U19 NS120384 (PI Charles DeCarli, MD, University of Michigan Site PI Henry Paulson, MD, PhD) R01 AG068338 (MPI Bruno Giordani, PhD, Carol Persad, PhD, Yi Murphey, PhD) S10OD026738-01 (PI Douglas Noll, PhD) R01 AG058724 (PI Benjamin Hampstead, PhD) R35 AG072262 (PI Benjamin Hampstead, PhD) W81XWH2110743 (PI Benjamin Hampstead, PhD) R01 AG073235 (PI Nancy Chiaravalloti, University of Michigan Site PI Benjamin Hampstead, PhD) 1I01RX001534 (PI Benjamin Hampstead, PhD) IRX001381 (PI Benjamin Hampstead, PhD); University of New Mexico - P20 AG068077 (Gary Rosenberg, MD); University of Pennsylvania - State of PA project 2019NF4100087335 (PI David Wolk, MD); Rooney Family Research Fund (PI David Wolk, MD); R01 AG055005 (PI David Wolk, MD); University of Pittsburgh - P50 AG005133 (PI Oscar Lopez MD); University of Southern California - P50 AG005142 (PI Helena Chui MD); University of Washington - P50 AG005136 (PI Thomas Grabowski MD); University of Wisconsin - P50 AG033514 (PI Sanjay Asthana MD FRCP); Vanderbilt University - P20 AG068082; Wake Forest - P30AG072947 (PI Suzanne Craft, PhD); Washington University, St. Louis - P01 AG03991 (PI John Morris MD); P01 AG026276 (PI John Morris MD); P20 MH071616 (PI Dan Marcus); P30 AG066444 (PI John Morris MD); P30 NS098577 (PI Dan Marcus); R01 AG021910 (PI Randy Buckner); R01 AG043434 (PI Catherine Roe); R01 EB009352 (PI Dan Marcus); UL1 TR000448 (PI Brad Evanoff); U24 RR021382 (PI Bruce Rosen); Avid Radiopharmaceuticals / Eli Lilly; Yale - P50 AG047270 (PI Stephen Strittmatter MD PhD); R01AG052560 (MPI: Christopher van Dyck, MD; Richard Carson, PhD); R01AG062276 (PI: Christopher van Dyck, MD); 1Florida - P30AG066506-03 (PI Glenn Smith, PhD); P50 AG047266 (PI Todd Golde MD PhD). The data from the Mayo Clinic Alzheimer’s Disease Research Center (P30 AG067677) was obtained under research grants from the National Institute on Aging and GHR Foundation. Data from UCSF ADRC was supported by NIH/NIA P30-AG062422 (UCSF ADRC), NIH/NIA R35 AG072362 (GDR), and Rainwater Charitable Foundation (GDR) grants. Data from the Geneva Memory Center was funded by the following private donors under the supervision of the Private Foundation of Geneva University Hospitals: A.P.R.A.: Association Suisse pour la Recherche sur la Maladie d'Alzheimer, Genève; Fondation Segré, Genève; Race Against Dementia Foundation, London, UK; Fondation Child Care, Genève; Fondation Edmond J. Safra, Genève; Fondation Minkoff, Genève; Fondazione Agusta, Lugano; McCall Macbain Foundation, Canada; Nicole et René Keller, Genève; Fondation AETAS, Genève. The BioFINDER study was supported by the National Institute of Aging (R01AG083740), European Research Council (ADG-101096455), Alzheimer’s Association (ZEN24-1069572, SG-23-1061717), GHR Foundation, Swedish Research Council (2022-00775), ERA PerMed (ERAPERMED2021-184), Knut and Alice Wallenberg foundation (2022-0231), Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson’s disease) at Lund University, Swedish Alzheimer Foundation (AF-980907), Swedish Brain Foundation (FO2021-0293), Parkinson foundation of Sweden (1412/22), Cure Alzheimer’s fund, Rönström Family Foundation, Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse, Skåne University Hospital Foundation (2020-O000028), Regionalt Forskningsstöd (2022-1259) and Swedish federal government under the ALF agreement (2022-Projekt0080). The precursor of 18F-flortaucipir was provided by AVID radiopharmaceuticals. The precursor of 18F-flutemetamol was sponsored by GE Healthcare. The funding sources had no role in the design and conduct of the study; in the collection, analysis, interpretation of the data; or in the preparation, review, or approval of the manuscript. Data used in the preparation of this article were obtained from the Harvard Aging Brain Study (HABS - P01AG036694; https://habs.mgh.harvard.edu). The HABS study was launched in 2010, funded by the National Institute on Aging, and is led by principal investigators Reisa A. Sperling MD and Keith A. Johnson MD at Massachusetts General Hospital/Harvard Medical School in Boston, MA. BACS data was supported by AG034570 and AG067418 grants. Alzheimer center Amsterdam is part of the neurodegeneration research program of Amsterdam Neuroscience. Data from Amsterdam UMC is supported by Stichting Alzheimer Nederland and Stichting VUmc fonds. Data from the University of Cambridge cohort was supported by the Cambridge Centre for Parkinson-Plus; the National Institute for Health Research, Cambridge Biomedical Research Centre (BRC-1215-20014; NIHR203312) Medical Research Council (MC_UU_00030/14; MR/T033371/1 JBR; and ref. 146281) the Wellcome Trust (220258); the Association of British Neurologists, Patrick Berthoud Charitable Trust (RG99368); the Evelyn Trust (RG84654); and the Race Against Dementia Alzheimer’s Research UK (ARUK-RADF2021A-010). Data used in the preparation of this article were obtained in part from the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer’s Disease (PREVENT-AD) program data release 6.0. PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the Fonds de Recherche du Québec - Santé (FRQ-S), an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. Private sector contributions are facilitated by the Development Office of the McGill University Faculty of Medicine and by the Douglas Hospital Research Centre Foundation (http://www.douglas.qc.ca/). The Founders of the program were John C. S. Breitner, MD, MPH, Judes Poirier, PhD and Pierre Etienne, MD, Douglas Hospital Research Centre and Faculty of Medicine, McGill University, Montréal, QC, Canada. Program Current Director is Judes Poirier, PhD, the Co-Director is Sylvia Villeneuve, PhD and the Study Coordinator is Jennifer Tremblay-Mercier, MSc. PREVENT-AD is the result of efforts of many other co-investigators from a range of academic institutions and private corporations, as well as an extraordinarily dedicated and talented clinical and technical assistant staff, students, and post-doctoral fellows. Subjects are recruited from the greater Montréal area and more distant locations in Québec. For up-to-date information, see https://prevent-alzheimer.net/?page_id=42&lang=en https://douglas.research.mcgill.ca/stop-ad-centre. Data from the Samsung Medical Center was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare and Ministry of science and ICT, Republic of Korea (grant number: HU20C0111, HU22C0170 and HU20C0414), the Korea Health Industry Development Institute (No. HU22C0052), the Ministry of Health Welfare, Republic of Korea (grant number: HR21C0885), the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2019R1A5A2027340 and NRF-2020R1A2C1009778), Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2021-0-02068, Artificial Intelligence Innovation Hub), and the ’Korea National Institute of Health’ research project (2021-ER1006-02). Data from the University of Cologne was funded by the Deutsche Forschungsgemeinschaft (DFG), project ID 431549029-SFB 1451, and partially by DFG, DR 445/9-1. Dr Schöll receives funding from the Knut and Alice Wallenberg Foundation (Wallenberg Centre for Molecular and Translational Medicine; KAW2014.0363 and KAW2023.0371), the Swedish Research Council (2017-02869, 2021-02678, 2021-06545 and 2023-06188), the European Union’s Horizon Europe research and innovation program under grant agreement no 101132933 (AD-RIDDLE) and 101112145 (PROMINENT), the National Institute of Health (R01 AG081394-01), Gates Ventures, the National Research Foundation of Korea (RS-2023-00263612), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (ALFGBG-813971 and ALFGBG-965326), the Swedish Brain Foundation (FO2021-0311 and FO2024-0372), the Swedish Alzheimer Foundation (AF-1011738), Familjen Rönström’s Foundation, the Sahlgrenska Academy at the University of Gothenburg, the Västra Götaland Region R&D (VGFOUREG-995510) and Innovation platforms, Sahlgrenska Science Park and the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre.

Role of the Funder/Sponsor:

The funders/sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclosures:

Dr. Silva-Rodríguez reports personal fees from Qubiotech Health Intelligence SL outside the submitted work. Dr. Bischof reports personal fees from Life Molecular Imaging outside the submitted work. Dr. Drzezga reports grants from DFG funding (German Research Association) during the conduct of the study; non-financial support from Siemens Healthineers, Life Molecular Imaging, GE Healthcare, AVID Radiopharmaceuticals, Sofie, Eisai, Novartis/AAA, Ariceum Therapeutics, personal fees from Siemens Healthineers, Sanofi, GE Healthcare, Biogen, Novo Nordisk, Invicro, Novartis/AAA, Bayer Vital, Lilly, Peer View Institute for Medical Education, International Atomic Energy Agency, and other from Siemens Healthineers, Lantheus Holding, Lilly stock outside the submitted work; in addition, Dr. Drzezga has a patent for Patent No.: EP3765097A1; Date of patent: Jan. 20, 2021 issued. Dr. Malpetti reports grants from Race Against Dementia Alzheimer’s Research UK (Grant Ref: ARUK - RADF2021A - 010) during the conduct of the study; personal fees from Astex Pharmaceuticals (counsulting) outside the submitted work. Dr. O’Brien reports personal fees from Biogen acted as consultant, personal fees from Roche acted as consultant, personal fees from GE Healthcare acted as consultant and received Received honorarium for lectures, and personal fees from Okwin acted as consultant outside the submitted work; and In advisory board for: 1)DSMB, 2)TauRx, 3)Novo Nordisk. Acted as Chair of UK Alzheimer’s Society Research Strategy Council. Received academic support for research from: 1) Avid/ Lilly, 2) Merck, 3) UCB, 4) Alliance Medical. Dr. Rowe reports grants from NIHR, grants from Wellcome, grants from Medical Research Council, and grants from PSP Association during the conduct of the study; personal fees from Asceneuron, personal fees from Astex, personal fees from Astronautx, personal fees from Alector, personal fees from Booster Therapeutics, personal fees from Draig Therapeutics, personal fees from CumulusNeuro, personal fees from Eisai, personal fees from Ferrer, personal fees from WAVE, personal fees from Prevail, personal fees from Clinical Ink, personal fees from Curasen, and personal fees from SVHealth outside the submitted work. Dr. van de Giessen reports grants from ZonMw paid to institution, grants from Hersenstichting paid to institution, grants from Alzheimer Nederland paid to institution, and grants from Health~Holland paid to institution outside the submitted work; and contract research with Heuron Inc., AC Immune and Roche and consultancy agreements with IXICO and Life Molecular Imaging for reading PET scans, all support was paid to the institution. Dr. Ossenkoppele reports research funding/support from Avid Radiopharmaceuticals, Janssen Research & Development, Roche, Quanterix and Optina Diagnostics, has given lectures in symposia sponsored by GE Healthcare, received speaker fees from Springer, is an advisory board member for Asceneuron and a steering committee member for Biogen and Bristol Myers Squibb. All the aforementioned has been paid to his institutions. Dr. Jagust reports grants from National Institute on Aging during the conduct of the study; personal fees from Lilly outside the submitted work; and Equity in Optoceutics and Molecular Medicine. Dr. Smith reports grants from the Swedish federal government under the ALF agreement during the conduct of the study; personal fees from Hoffman La Roche Ltd Lecture honorarium, personal fees from Triolab Lecture honorarium, personal fees from Novo Nordisk Consultancy agreement, and personal fees from Eli Lilly Consultancy agreement outside the submitted work. Dr. Hansson reports non-financial support from Roche material for RO948 PET imaging and non-financial support from Lilly material for FTP PET imaging during the conduct of the study; other from Lilly I am employed by Lilly outside the submitted work. Dr. Garibotto reports grants from Siemens Healthineers to institution, grants from GE Healthcare to institution, and personal fees from Novartis to institution outside the submitted work. Dr. Carrillo reports full time employee of the Alzheimer’s Association. Dr. Dickerson reports personal fees from Biogen, personal fees from Eisai, personal fees from Lantheus, personal fees from Lilly, personal fees from Merck, personal fees from Novo Nordisk, and grants from Quanterix outside the submitted work. Dr. La Joie reports personal fees from GE healthcare, grants from NIH/NIA, grants from Alzheimer’s Association, and grants from US department of defense outside the submitted work. Dr. Rabinovici reports grants from NIH and grants from Rainwater Charitable Foundation during the conduct of the study; grants from Eli Lilly, grants from GE Healthcare, grants from Life Molecular Imaging, grants from Genentech, personal fees from Alector SAB, personal fees from Bristol Myers Squibb SAB, personal fees from Eli Lilly SAB, personal fees from Johnson & Johnson DSMB, personal fees from Merck SAB, personal fees from Roche SAB, personal fees from Novo Nordisk SAB, personal fees from Peerview Paid speaker, and personal fees from Medscape Paid speaker outside the submitted work; and Associate Editor, JAMA. Dr. Pontecorvo reports I am an employee and minor stockholder of Eli Lilly and Company. Dr. Johnson reports other from NIH Research Grant and other from Eli Lilly Research Grant during the conduct of the study; other from Novartis Consulting, other from Merck Consulting, and other from Janssen Consulting outside the submitted work. Dr. Sperling reports grants from Eli Lilly Clinical Trial Funding, grants from Eisai Clinical Trial Funding, other from Abbvie Consulting, other from AC Immune Consulting, other from Acumen Consulting, other from Alector Consulting, other from Apellis Consulting, other from Biohaven Consulting, other from Bristol Myers Squibb Consulting, other from Genentech Consulting, other from Ionis Consulting, other from Janssen Consulting, other from Nervgen Consulting, other from Oligomerix Consulting, other from Prothena Consulting, other from Roche Consulting, other from Vigil Neuroscience Consulting, and other from Vaxxinity Consulting outside the submitted work. Dr. Weiner reports grants from NIH/NIA, grants from Dept. of Defense, grants from CA Dept. of Public Health, grants from Alzheimer’s Assoc., grants from Johnson & Johnson, grants from Kevin & Connie Shanahan, grants from Siemens, grants from Biogen, grants from Hillblom Foundation, grants from GE, grants from VUmc, grants from Australian Catholic U., grants from The Stroke Foundation, grants from Veterans Administration (Also WOC employer), personal fees from Acadia Pharmaceuticals consulting, personal fees from Boxer Capital consulting, personal fees from Cerecin consulting, personal fees from Clario/BioClinica consulting, personal fees from Dementia Society of Japan consulting, personal fees from Eisai consulting, personal fees from Guidepoint consulting, personal fees from Health & Wellness Partners consulting, personal fees from Indiana U. consulting, personal fees from LCN Consulting consulting, personal fees from Merck Sharp & Dohme (Also honoraria and travel support), personal fees from Duke U. consulting, personal fees from Owkin France consulting, personal fees from NovoNordisk consulting, personal fees from ProMIS Neurosciences consulting, personal fees from Prova Education consulting, personal fees from Sai MedPartners consulting, personal fees from T3D Therapeutics consulting, personal fees from U. Southern CA consulting, personal fees from WebMD consulting, personal fees from MEDA Corp. consulting, personal fees from China Assoc for AD honoraria, personal fees from Taipei Medical U. honoraria, personal fees from Cleveland Clinic honoraria and travel funding, personal fees from Banner Health honoraria and travel funding, personal fees from AD/PD Congress honoraria and travel funding, personal fees from Kenes honoraria and travel funding, personal fees from Foundation of Learning; Health Society, Japan honoraria and travel funding, personal fees from Japan Society for Dementia Research honoraria and travel funding, personal fees from U. Toulouse honoraria and travel funding, personal fees from Korean Dementia Society honoraria and travel funding, personal fees from U. Madison Wisconsin honoraria, other from Alzeca stock options, other from Alzheon, Inc. stock options, other from ALZPath stock options, personal fees from CTAD Congress travel funds, and personal fees from National Center for Geriatrics and Gerontology, Japan travel funds outside the submitted work. Dr. Petersen reports grants from National Institute on Aging, grants from GHR Foundation, and grants from Alexander Family Foundation during the conduct of the study; personal fees from Roche, Inc., personal fees from Genentech, Inc., personal fees from Eli Lilly and Co., non-financial support from Eisai, Inc., personal fees from Novartis, and personal fees from Novo Nordisk outside the submitted work; and Royalties: Oxford University Press, UpToDate Educational materials: Medscape. Dr. Vemuri reports grants from NIH outside the submitted work. Dr. Schöll reports grants from Knut and Alice Wallenberg Foundation and grants from Swedish Research Council during the conduct of the study; grants from European Union’s Horizon Europe research and innovation program, grants from National Institute of Health, grants from Gates Ventures, grants from National Research Foundation of Korea, grants from Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement, grants from Swedish Brain Foundation, grants from Swedish Alzheimer Foundation, grants from Familjen Rönström’s Foundation, grants from Sahlgrenska Academy at the University of Gothenburg, grants from Västra Götaland Region R&D, grants from Sahlgrenska Science Park, grants from National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre, personal fees from Eli Lilly and Company, grants from Novo Nordisk, personal fees from Novo Nordisk, non-financial support from Roche, personal fees from Roche, grants from Bioarctic, personal fees from Bioarctic, personal fees from Triolabs, and non-financial support from Beckman Coulter outside the submitted work; and I am a co-founder and shareholder of Centile Bioscience and serve as Associate Editor with Alzheimer’s Research & Therapy. The rest of the authors have nothing to disclose.

Footnotes

Access to Data: Alexis Moscoso, PhD, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Additional Information

Data used in preparation of this article were obtained from the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer’s Disease (PREVENT-AD) program (https://douglas.research.mcgill.ca/stop-ad-centre), data release 6.0. A complete listing of PREVENT-AD Research Group can be found in the PREVENT-AD database: https://preventad.loris.ca/acknowledgements/acknowledgements.php?date=[2024-09-22]

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: https://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

Data Sharing Statement:

See Supplement 2.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material

NIHMS2121854-supplement-Supplementary_Material.docx^{(6.1MB, docx)}

Data Availability Statement

See Supplement 2.

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PERMALINK

Frequency and clinical outcomes associated with tau positron emission tomography positivity

Alexis Moscoso, PhD

Fiona Heeman, PhD

Sheelakumari Raghavan, PhD

Alejandro Costoya-Sánchez, PhD

Martijn van Essen, MD, PhD

Ismini Mainta, MD

Valle Camacho, MD, PhD

Omar Rodríguez-Fonseca, MD, PhD

Jesús Silva-Rodríguez, PhD

Andrés Perissinotti, MD, PhD

Yuna Gu, MSc

Jihwan Yun, MSc

Debora Peretti, PhD

Federica Ribaldi, PhD

Emma M Coomans, PhD

Wagner S Brum

Michel J Grothe, PhD

Pablo Aguiar, PhD

Gérard N Bischof, PhD

Alexander Drzezga, MD

Sang Won Seo, MD, PhD

Sylvia Villeneuve, PhD

Maura Malpetti, PhD

John T O’Brien, DM

James B Rowe, MD, PhD

Elsmarieke M van de Giessen, MD, PhD

Rik Ossenkoppele, PhD

William J Jagust, MD

Ruben Smith, MD, PhD

Oskar Hansson, MD, PhD

Giovanni B Frisoni, MD

Valentina Garibotto, MD

David N Soleimani-Meigooni, MD

Maria Carrillo, PhD

Bradford C Dickerson, MD

Renaud La Joie, PhD

Gil D Rabinovici, MD

Liana G Apostolova, MD

Pamela J LaMontagne, PhD

Michael J Pontecorvo, PhD

Keith A Johnson, MD

Reisa A Sperling, MD

Michael W Weiner, MD

Ronald C Petersen, MD, PhD

Clifford R Jack Jr, MD

Prashanthi Vemuri, PhD

Michael Schöll, PhD

Abstract

Importance:

Objective:

Design, Setting, and Participants:

Exposures:

Main Outcomes and Measures:

Results:

Conclusions and Relevance:

INTRODUCTION

METHODS

Participants

PET imaging

Outcomes

Statistical analysis

RESULTS

Table 1.

Frequency of tau-PET positivity

Figure 1.

Figure 2.

Clinical outcomes

Figure 3.

Table 2.

DISCUSSION

Limitations

CONCLUSIONS

Supplementary Material

KEY POINTS.

Question:

Findings:

Meaning:

ACKNOWLEDGEMENTS