Association of Phosphorylated Tau Biomarkers With Amyloid Positron Emission Tomography vs Tau Positron Emission Tomography

Joseph Therriault; Marie Vermeiren; Stijn Servaes; Cécile Tissot; Nicholas J Ashton; Andréa Lessa Benedet; Thomas K Karikari; Juan Lantero-Rodriguez; Wagner S Brum; Firoza Z Lussier; Gleb Bezgin; Jenna Stevenson; Nesrine Rahmouni; Peter Kunach; Yi-Ting Wang; Jaime Fernandez-Arias; Kely Quispialaya Socualaya; Arthur C Macedo; João Pedro Ferrari-Souza; Pâmela C L Ferreira; Bruna Bellaver; Douglas T Leffa; Eduardo R Zimmer; Paolo Vitali; Jean-Paul Soucy; Gallen Triana-Baltzer; Hartmuth C Kolb; Tharick A Pascoal; Paramita Saha-Chaudhuri; Serge Gauthier; Henrik Zetterberg; Kaj Blennow; Pedro Rosa-Neto

doi:10.1001/jamaneurol.2022.4485

. 2022 Dec 12;80(2):188–199. doi: 10.1001/jamaneurol.2022.4485

Association of Phosphorylated Tau Biomarkers With Amyloid Positron Emission Tomography vs Tau Positron Emission Tomography

Joseph Therriault ^1,², Marie Vermeiren ^1,³, Stijn Servaes ^1,², Cécile Tissot ¹, Nicholas J Ashton ^4,^5,^6,⁷, Andréa Lessa Benedet ⁴, Thomas K Karikari ^4,⁸, Juan Lantero-Rodriguez ⁴, Wagner S Brum ^4,⁹, Firoza Z Lussier ^1,⁸, Gleb Bezgin ^1,², Jenna Stevenson ¹, Nesrine Rahmouni ¹, Peter Kunach ^1,², Yi-Ting Wang ^1,², Jaime Fernandez-Arias ^1,², Kely Quispialaya Socualaya ^1,², Arthur C Macedo ^1,², João Pedro Ferrari-Souza ⁸, Pâmela C L Ferreira ⁸, Bruna Bellaver ⁸, Douglas T Leffa ⁸, Eduardo R Zimmer ⁹, Paolo Vitali ², Jean-Paul Soucy ², Gallen Triana-Baltzer ¹⁰, Hartmuth C Kolb ¹⁰, Tharick A Pascoal ⁸, Paramita Saha-Chaudhuri ¹¹, Serge Gauthier ^1,², Henrik Zetterberg ^4,^12,^13,^14,¹⁵, Kaj Blennow ^4,¹², Pedro Rosa-Neto ^1,^2,^✉

¹Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada

²Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada

³Erasmus Medical Center, Erasmus University Rotterdam, Rotterdam, the Netherlands

⁴Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden

⁵Wallenberg Centre for Molecular Medicine, University of Gothenburg, Gothenburg, Sweden

⁶King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, United Kingdom

⁷NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, United Kingdom

⁸Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania

⁹Department of Pharmacology, Graduate Program in Biological Sciences: Biochemistry and Pharmacology and Therapeutics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil

¹⁰Neuroscience Biomarkers, Janssen Research & Development, La Jolla, California

¹¹Department of Math & Statistics, University of Vermont, Burlington

¹²Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden

¹³Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom

¹⁴UK Dementia Research Institute at UCL, London, United Kingdom

¹⁵Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China

Accepted for Publication: October 13, 2022.

Published Online: December 12, 2022. doi:10.1001/jamaneurol.2022.4485

^✉

Corresponding Author: Pedro Rosa-Neto, MD, PhD, Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, 6875 La Salle Blvd, Frank B. Common Pavilion Room 3149, Montreal, QC H4H1R3, Canada (pedro.rosa@mcgill.ca).

Author Contributions: Dr Rosa-Neto had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Therriault and Vermeiren contributed equally to this work.

Concept and design: Therriault, Tissot, Ashton, Zimmer, Kolb, Pascoal, Gauthier, Zetterberg, Blennow, Rosa-Neto.

Acquisition, analysis, or interpretation of data: Therriault, Vermeiren, Servaes, Tissot, Ashton, Benedet, Karikari, Lantero-Rodriguez, Scheeren Brum, Lussier, Bezgin, Stevenson, Rahmouni, Kunach, Wang, Fernandez-Arias, Quispialaya Socualaya, Cassa Macedo, Ferrari-Souza, Ferreira, Bellaver, Leffa, Zimmer, Vitali, Soucy, Triana-Baltzer, Kolb, Saha-Chaudhuri, Zetterberg, Blennow.

Drafting of the manuscript: Therriault, Vermeiren, Kunach, Zimmer, Pascoal, Rosa-Neto.

Critical revision of the manuscript for important intellectual content: Vermeiren, Servaes, Tissot, Ashton, Benedet, Karikari, Lantero-Rodriguez, Scheeren Brum, Lussier, Bezgin, Stevenson, Rahmouni, Wang, Fernandez-Arias, Quispialaya Socualaya, Cassa Macedo, Ferrari-Souza, Ferreira, Bellaver, Leffa, Zimmer, Vitali, Soucy, Triana-Baltzer, Kolb, Saha-Chaudhuri, Gauthier, Zetterberg, Blennow.

Statistical analysis: Therriault, Vermeiren, Servaes, Tissot, Scheeren Brum, Bezgin, Ferrari-Souza, Ferreira, Bellaver, Zimmer, Rosa-Neto.

Obtained funding: Therriault, Tissot, Karikari, Kolb, Zetterberg, Blennow.

Administrative, technical, or material support: Ashton, Benedet, Lantero-Rodriguez, Lussier, Bezgin, Stevenson, Rahmouni, Fernandez-Arias, Quispialaya Socualaya, Cassa Macedo, Soucy, Triana-Baltzer, Zetterberg, Blennow.

Supervision: Servaes, Zimmer, Vitali, Kolb, Saha-Chaudhuri, Gauthier, Blennow.

Conflict of Interest Disclosures: Dr Karikari reported receiving a patent issued by H. Lundbeck A/S. Dr Wang reported receiving grants from Fonds de Recherche du Québec outside the submitted work. Dr Ferrari-Souza reported receiving grants from Conselho Nacional de Desenvolvimento Científico e Tecnológico during the conduct of the study. Dr Zimmer reported receiving advisory board fees from Next Generation Therapeutics (Nintx) outside the submitted work. Dr Triana-Baltzer reported being an employee of Janssen R&D during the conduct of the study and having a patent for Plasma p217+tau assay pending. Dr Kolb reported being an employee of Janssen R&D during the conduct of the study and having a patent for p217Tau plasma assay pending. Dr Triana-Baltzar reported being an employee of Janssen R&D. Dr Gauthier reported receiving personal fees from Cerveau during the conduct of the study; being a scientific advisor to TauRx and AmyriAD; and being a lecturer on behalf of Biogen Canada, Lundbeck. Dr Zetterberg reported receiving advisory board fees or consultant fees from Denali, Roche Diagnostics, Wave, Samumed, Siemens Healthineers, Pinteon Therapeutics, CogRx, Eisai, Nervgen, AZTherapies, Red Abbey Labs, Alector, Triplet Therapeutics, ALZPath, AbbVie, Acumen, Annexon, Apellis, Artery Therapeutics, Novo Nordisk, Passage Bio, and reMYND; conducting a sponsored lecture for Cellectricon, Alzecure, Fujirebio, Biogen, and Roche; being cofounder of and having stock in Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program; and being an employee of Janssen R&D outside the submitted work. Dr Blennow reported receiving grants from the Swedish Alzheimer Foundation, Hjärnfonden, Sweden, the Swedish state under the agreement between the Swedish government and the County Councils, the ALF agreement, and the Alzheimer’s Association 2021 Zenith Award; and serving as a consultant, acted on advisory boards, or participated in data monitoring committees for Abcam, Axon, BioArctic, Biogen, JOMDD/Shimadzu, Julius Clinical, Lilly, MagQu, Novartis, Ono Pharma, Pharmatrophix, Prothena, Roche Diagnostics, and Siemens Healthineers; and being a cofounder of Brain Biomarker Solutions in Gothenburg AB, which is a part of the GU Ventures Incubator Program. Dr Rosa-Neto reported receiving consultant fees from Cerveau Radiopharmaceuticals. Drs Pascoal, Gauthier, and Rosa-Neto reported being members of the Canadian Institutes of Health Research and the Canadian Consortium of Neurodegeneration and Aging. No other disclosures were reported.

Funding/Support: This work was supported by grants MOP-11-51-31 and RFN 152985, 159815, 162303 from the Canadian Institutes of Health Research (CIHR); MOP-11-51-31 from the Canadian Consortium of Neurodegeneration and Aging (CCNA); the Weston Brain Institute; grants NIRG-12-92090, NIRP-12-259245 from the Alzheimer’s Association; grants 34874 and 33397 from Brain Canada Foundation; 2020-VICO-279314 from the Fonds de Recherche du Québec—Santé (FRQS); the CIHR doctoral award (Dr Therriault); and Alzheimer Nederland (Dr Vermeiren). Dr Karikari was supported by grants 2021-03244 from the Swedish Research Council; AARF-21-850325 from the Alzheimer’s Association; A2020812F from the BrightFocus Foundation; the International Society for Neurochemistry’s Career Development Grant; AF-930627 from the Swedish Alzheimer Foundation; FO2020-0240 from the Swedish Brain Foundation; the Swedish Dementia Foundation; the Swedish Parkinson Foundation; the Gamla Tjänarinnor Foundation; the Aina (Ann) Wallströms and Mary-Ann Sjöbloms Foundation; 2020-00124 from the Agneta Prytz-Folkes & Gösta Folkes Foundation; the Gun and Bertil Stohnes Foundation; and the Anna Lisa and Brother Björnsson’s Foundation. Dr Zetterberg is a Wallenberg Scholar supported by grant 2018-02532 from the Swedish Research Council; 681712 from the European Research Council; ALFGBG-71320 from Swedish State Support for Clinical Research; 201809-2016862 from the Alzheimer Drug Discovery Foundation; ADSF-21-831376-C, ADSF-21-831381-C, and ADSF-21-831377-C from the AD Strategic Fund and the Alzheimer’s Association; the Olav Thon Foundation; the Erling-Persson Family Foundation; FO2019-0228 from Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden; the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE); JPND2021-00694 from the European Union Joint Programme—Neurodegenerative Disease Research; and UKDRI-1003 from the UK Dementia Research Institute at UCL. Dr Blennow is supported by grant 2017-00915 from the Swedish Research Council; RDAPB-201809-2016615 from the Alzheimer Drug Discovery Foundation; AF-930351, AF-939721, and AF-968270 from the Swedish Alzheimer Foundation; Hjärnfonden, Sweden; grants FO2017-0243 and ALZ2022-0006 from the Swedish state under the agreement between the Swedish government and the County Councils; ALFGBG-715986 and ALFGBG-965240 from the ALF agreement; JPND2019-466-236 from the European Union Joint Program for Neurodegenerative Disorders; 1R01AG068398-01 from the National Institutes of Health; and ZEN-21-848495 from the Alzheimer’s Association 2021 Zenith Award.

Role of the Funder/Sponsor: The funders 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.

^✉

Corresponding author.

PMCID: PMC9856704 PMID: 36508198

This cross-sectional study of 2 observational cohorts investigates if phosphorylated tau biomarkers are more associated with the presence of cerebral β-amyloidosis or tau neurofibrillary tangle aggregation.

Key Points

Question

Do soluble phosphorylated tau (p-tau) biomarkers preferentially reflect the presence of cerebral β-amyloidosis or tau neurofibrillary tangle aggregation?

Findings

In this cross-sectional study of 2 observational cohorts, 4 p-tau biomarkers in the cerebrospinal fluid (CSF; p-tau₁₈₁, p-tau₂₁₇, p-tau₂₃₁, p-tau₂₃₅) were significantly more closely associated with amyloid PET (positron emission tomography) than with tau PET. These results were replicated in an independent group of individuals with plasma p-tau₁₈₁, p-tau₂₁₇, and p-tau₂₃₁ and in another independent cohort with CSF p-tau₁₈₁.

Meaning

Results suggest that soluble p-tau biomarkers are more closely associated with cerebral amyloid-β than with tau aggregation assessed with PET; this finding supports the need for careful interpretation of p-tau biomarkers in the context of the amyloid/tau/neurodegeneration, or A/T/(N), framework.

Abstract

Importance

The recent proliferation of phosphorylated tau (p-tau) biomarkers has raised questions about their preferential association with the hallmark pathologies of Alzheimer disease (AD): amyloid-β plaques and tau neurofibrillary tangles.

Objective

To determine whether cerebrospinal fluid (CSF) and plasma p-tau biomarkers preferentially reflect cerebral β-amyloidosis or neurofibrillary tangle aggregation measured with positron emission tomography (PET).

Design, Setting, and Participants

This was a cross-sectional study of 2 observational cohorts: the Translational Biomarkers in Aging and Dementia (TRIAD) study, with data collected between October 2017 and August 2021, and the Alzheimer’s Disease Neuroimaging Initiative (ADNI), with data collected between September 2015 and November 2019. TRIAD was a single-center study, and ADNI was a multicenter study. Two independent subsamples were derived from TRIAD. The first TRIAD subsample comprised individuals assessed with CSF p-tau (p-tau₁₈₁, p-tau₂₁₇, p-tau₂₃₁, p-tau₂₃₅), [¹⁸F]AZD4694 amyloid PET, and [¹⁸F]MK6240 tau PET. The second TRIAD subsample included individuals assessed with plasma p-tau (p-tau₁₈₁, p-tau₂₁₇, p-tau₂₃₁), [¹⁸F]AZD4694 amyloid PET, and [¹⁸F]MK6240 tau PET. An independent cohort from ADNI comprised individuals assessed with CSF p-tau₁₈₁, [¹⁸F]florbetapir PET, and [¹⁸F]flortaucipir PET. Participants were included based on the availability of p-tau and PET biomarker assessments collected within 9 months of each other. Exclusion criteria were a history of head trauma or magnetic resonance imaging/PET safety contraindications. No participants who met eligibility criteria were excluded.

Exposures

Amyloid PET, tau PET, and CSF and plasma assessments of p-tau measured with single molecule array (Simoa) assay or enzyme-linked immunosorbent assay.

Main Outcomes and Measures

Associations between p-tau biomarkers with amyloid PET and tau PET.

Results

A total of 609 participants (mean [SD] age, 66.9 [13.6] years; 347 female [57%]; 262 male [43%]) were included in the study. For all 4 phosphorylation sites assessed in CSF, p-tau was significantly more closely associated with amyloid-PET values than tau-PET values (p-tau₁₈₁ difference, 13%; 95% CI, 3%-22%; P = .006; p-tau₂₁₇ difference, 11%; 95% CI, 3%-20%; P = .003; p-tau₂₃₁ difference, 15%; 95% CI, 5%-22%; P < .001; p-tau₂₃₅ difference, 9%; 95% CI, 1%-19%; P = .02) . These results were replicated with plasma p-tau₁₈₁ (difference, 11%; 95% CI, 1%-22%; P = .02), p-tau₂₁₇ (difference, 9%; 95% CI, 1%-19%; P = .02), p-tau₂₃₁ (difference, 13%; 95% CI, 3%-24%; P = .009), and CSF p-tau₁₈₁ (difference, 9%; 95% CI, 1%-21%; P = .02) in independent cohorts.

Conclusions and Relevance

Results of this cross-sectional study of 2 observational cohorts suggest that the p-tau abnormality as an early event in AD pathogenesis was associated with amyloid-β accumulation and highlights the need for careful interpretation of p-tau biomarkers in the context of the amyloid/tau/neurodegeneration, or A/T/(N), framework.

Introduction

Alzheimer disease (AD) is defined by the presence of cerebral amyloid-β plaques and tau neurofibrillary tangles.^1,2 The A/T/(N) biomarker classification system identifies 3 classes of AD biomarkers: amyloid-β, tau, and neurodegeneration, in which amyloid-β and tau biomarkers are specific to AD.^3,4 Amyloid-β biomarkers include amyloid positron emission tomography (PET) as well as cerebrospinal fluid (CSF) and plasma concentrations of amyloid-β. Tau biomarkers include quantification of insoluble neurofibrillary tangles using PET, as well as soluble phosphorylated tau (p-tau) in the CSF and plasma. Because of their specificity, amyloid-β and tau biomarkers are increasingly used in AD diagnosis⁵ and as inclusion criteria for disease-modifying clinical trials.^6,7

Although soluble p-tau biomarkers are interpreted as biomarkers of tau pathology, several recent observational studies provide evidence that concentrations of p-tau are closely correlated with amyloid-β deposition.^{8,9,10,11,12,13,14} A longitudinal study in autosomal dominant AD provides evidence that concentrations of soluble p-tau biomarkers begin to rise in conjunction with amyloid-β aggregation, several years before neocortical tau abnormality.¹⁵ Furthermore, longitudinal biomarker studies in sporadic AD report that soluble p-tau₂₁₇ mediates the association between amyloid-β and tau-PET change.^8,16 Correspondingly, recent biomarker models of AD suggest that p-tau reflects a state between amyloid-β plaques and tau aggregation.^16,17,18 However, it is unclear to what extent biofluid measurements of p-tau are preferentially associated with the presence of amyloid-β or tau neurofibrillary tangles in the brain.

The objective of the current study was to determine whether soluble p-tau biomarkers are preferentially associated with cerebral amyloid-β plaques or tau neurofibrillary tangles. We evaluated the association between 4 p-tau biomarkers in the CSF (p-tau₁₈₁, p-tau₂₁₇, p-tau₂₃₁, p-tau₂₃₅) and 3 in plasma (p-tau₁₈₁, p-tau₂₁₇, p-tau₂₃₁) with amyloid-β and tau aggregation assessed with PET in the Translational Biomarkers in Aging and Dementia (TRIAD) study cohort. In addition, we evaluated the association between CSF p-tau₁₈₁ with amyloid PET and tau PET in the Alzheimer Disease Neuroimaging Initiative (ADNI) cohort.

Methods

Participants

Translational Biomarkers in Aging and Dementia

This study was approved by the Montreal Neurological Institute PET working committee and the Douglas Mental Health University Institute Research Ethics Board. Written informed consent was obtained for all participants. For this cross-sectional study, we assessed 2 independent subsamples of participants in the TRIAD¹⁹ cohort: a CSF p-tau subsample (n = 181) and a plasma p-tau subsample (n = 171). Participants included in the CSF subsample had measures of CSF p-tau (p-tau₁₈₁, p-tau₂₁₇, p-tau₂₃₁, p-tau₂₃₅), amyloid PET with [¹⁸F]AZD4694, tau PET with [¹⁸F]MK6240, and magnetic resonance imaging (MRI). The median (IQR) time difference between CSF and PET data collection was 53 (86) days. In the second subsample (n = 171), individuals had measures of plasma p-tau (p-tau₁₈₁, p-tau₂₁₇, p-tau₂₃₁), amyloid PET with [¹⁸F]AZD4694, tau PET with [¹⁸F]MK6240, and MRI. The median (IQR) time difference between plasma and PET data collection was 70 (112) days. The individuals in the second TRIAD subsample did not have CSF measures of p-tau and thus represent an independent sample of individuals. Participants had paired fluid p-tau and PET biomarker assessments available within a 9-month interval. All individuals were included between October 2017 and August 2021. Individuals from the following race and ethnicity categories were included: Asian, Black, Hawaiian/Pacific Islander, Hispanic/Latinx, non-Hispanic/Latinx, multiracial, White, and unknown/not reported. Race and ethnicity were identified using official National Institutes of Health classifications. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.

Cognitively unimpaired (CU) individuals had no objective cognitive impairment and a Clinical Dementia Rating (CDR) score of 0. Individuals with mild cognitive impairment had subjective and/or objective cognitive impairment and a CDR score of 0.5.²⁰ Individuals with dementia had a CDR score of 1 or 2.²¹ Participants were excluded from this study if they had systemic conditions that were not adequately controlled through a stable medication regimen. Other exclusion criteria were active substance abuse, recent head trauma, recent major surgery, or MRI/PET safety contraindications. PET acquisition and processing are described in eMethods 1 of the Supplement. All p-tau residues measured from the CSF, as well as plasma p-tau₁₈₁ and p-tau₂₃₁, were quantified in the Clinical Neurochemistry Laboratory, University of Gothenburg, Mölndal, Sweden, by scientists blinded to participant clinical and PET information; this information is described in detail in eMethods 2 of Supplement. Plasma p-tau₂₁₇ was quantified by scientists at Janssen Research & Development blinded to clinical and PET information.

Alzheimer Disease Neuroimaging Initiative

The ADNI study was approved by the institutional review boards of all participating institutions. All participants provided informed written consent. We examined the open-access ADNI cohort, a North American multisite cohort launched in 2003. All participants had amyloid PET with [¹⁸F]florbetapir, tau-PET with [¹⁸F]flortaucipir, and CSF p-tau₁₈₁. ADNI PET acquisition and processing data are described in eMethods 1 of the Supplement, and CSF p-tau₁₈₁ quantification is described in eMethods 2 of the Supplement. The median (IQR) time difference between CSF and PET data collection was 13 (29) days. CU participants had a CDR of 0, individuals with mild cognitive impairment had a CDR of 0.5, and individuals with dementia had a CDR score of 1 or 2. Full information regarding the ADNI inclusion and exclusion criteria is available on the ADNI informational site.²² Plasma p-tau₁₈₁ was not investigated in ADNI due to the small number of individuals with plasma p-tau evaluations and tau PET at the same visit.

Statistical Analysis

Statistical analyses were performed in R, version 4.1.1 (R Foundation for Statistical Computing) and Matlab, version 2015a (MathWorks). Assumptions of normality were tested using the D’Agastino-Pearson normality test. Associations between p-tau biomarkers with [¹⁸F]AZD4694 PET and [¹⁸F]MK6240 PET were investigated using the Spearman nonparametric test. Statistical evaluation of whether correlations were significantly different was performed in R using the cocor package,²³ a statistical framework for comparing associations between intercorrelated measurements. As secondary confirmatory analyses, we conducted partial correlation analyses to determine the extent to which p-tau biomarker concentrations were associated with amyloid PET when correcting for tau PET and tau PET correcting for amyloid PET using the ppcor package. We also conducted analyses correcting for age and sex. P values were 2-sided, and statistical significance was defined as P <.05.

Because PET measures of pathology reflect accumulation within specific brain regions, which may preferentially reflect protein aggregation at specific disease stages, we conducted supplementary sensitivity analyses stratified by cognitive impairment, and we used summary composite regions of interest (ROIs) considered to become positive earlier in the AD process. For amyloid PET, the Biofinder Early Aβ-PET ROI²⁴ was used, and for tau PET, the inferior temporal cortical ROI was used, previously implemented to capture early tau aggregation in studies of CU individuals^25,26 and in the early stages of autosomal dominant AD.²⁷ We also compared global amyloid PET with tau-PET uptake in Braak I-II regions. We also compared CSF concentrations of Aβ (indexed by the Aβ42/40 ratio) with tau-PET uptake. Finally, we compared whole-cortex amyloid-PET and whole-cortex tau-PET standardized uptake value ratios (SUVRs).

Results

Participants

A total of 609 participants (mean [SD] age, 66.9 [13.6] years; 347 female [57%]; 262 male [43%]) were included in the study. The first TRIAD subsample included 181 participants; the second subsample included 171 participants. The mean (SD) age of participants in the CSF TRIAD subsample was 61.7 (17.9) years, with 196 female individuals (55.7%) and 156 male individuals (44.3%). The mean (SD) age of participants in the plasma TRIAD subsample was 66.3 (15.2) years, with 113 female individuals (66.1%) and 58 male individuals (33.9%). The ADNI cohort included a total of 257 participants (mean [SD] age, 70.6 [6.7] years; 131 female [51.0%]; 126 male [49.0%]). Our study included the following race and ethnicity groups: 17 Asian (2.8%), 17 Black (2.8%), 1 Hawaiian/Pacific Islander (0.2%), 10 Hispanic/Latinx (1.6%), 577 non-Hispanic/Latinx (94.7%), 4 multiracial (0.7%), 551 White (90.5%), and 19 unknown/not reported (3.1%). Demographic, clinical, and biomarker information for all samples is reported in the Table.

Table. Demographic Characteristics of the Samples.

Characteristic	No. (%)
Characteristic	Young adults	Cognitively unimpaired older adults	Mild cognitive impairment	Dementia
A: TRIAD cerebrospinal fluid sample
No.	27	86	45	23
Age, mean (SD), y	22.8 (1.9)	69.5 (8.0)	71.3 (7.5)	62.4 (6.5)
Sex
Male	11 (40.7)	32 (37.2)	18 (40.0)	12 (52.2)
Female	16 (59.3)	54 (62.8)	27 (60.0)	11 (47.8)
Education, mean (SD), y	16.7 (1.5)	14.8 (3.5)	14.9 (3.2)	15.1 (3.5)
APOE ε4 carriers, %	6 (22.2)	25 (29.1)	17 (37.7)	13 (56.5)
MMSE, mean (SD)	29.8 (0.5)	29.1 (1.0)	27.7 (1.8)	18.7 (5.6)
Self-reported race
American Indian/Alaskan Native	0 (0)	0 (0)	0 (0)	0 (0)
Asian	9 (33.3)	0 (0)	1 (2.2)	1 (4.3)
Black	1 (3.7)	1 (1.2)	0 (2.3)	0 (0)
Hawaiian/Pacific Islander	0 (0)	0 (0)	0 (0)	0 (0)
Multiracial	1 (3.7)	0 (0)	0 (0)	0 (0)
White	16 (59.3)	78 (90.7)	42 (93.3)	21 (91.3)
Unknown/not reported	0 (0)	7 (8.1)	2 (4.4)	1 (4.3)
Self-reported ethnicity
Hispanic/Latinx	0 (0)	1 (1.2)	0 (0)	0 (0)
Not Hispanic/Latinx	27 (100)	78 (90.7)	43 (95.5)	21 (91.3)
Unknown/not reported	0 (0)	7 (8.1)	2 (4.4)	2 (8.7)
B: TRIAD plasma sample
No.	9	88	43	31
Age, mean (SD), y	22.6 (1.6)	69.5 (12.2)	67.2 (11.4)	69.0 (9.7)
Sex
Male	2 (22.2)	27 (30.7)	17 (39.5)	12 (38.7)
Female	7 (77.8)	61 (69.3)	26 (60.5)	19 (61.3)
Education, mean (SD), y	16.1 (1.4)	15.9 (4.0)	15.2 (4.1)	13.8 (3.6)
APOE ε4 carriers, %	3 (33.3)	19 (21.6)	15 (38.5)	15 (48.3)
MMSE, mean (SD)	30.0 (0.0)	29.2 (1.1)	28.0 (1.8)	20.0 (5.9)
Self-reported race
American Indian/Alaskan Native	0 (0)	0 (0)	0 (0)	0 (0)
Asian	4 (44.4)	0 (0)	1 (2.3)	1 (3.2)
Black	0 (0)	1 (1.1)	1 (2.3)	0 (0)
Hawaiian/Pacific Islander	0 (0)	0 (0)	0 (0)	0 (0)
Multiracial	0 (0)	0 (0)	0 (0)	0 (0)
White	5 (55.6)	80 (90.9)	41 (95.3)	28 (90.3)
Unknown/not reported	0 (0)	7 (7.9)	0 (0)	2 (6.5)
Self-reported ethnicity
Hispanic/Latinx	0 (0)	1 (1.1)	0 (0)	0 (0)
Not Hispanic/Latinx	9 (100)	80 (90.1)	43 (100)	29 (93.5)
Unknown/not reported	0 (0)	7 (7.8)	0 (0)	2 (6.5)
C: ADNI CSF sample
No.	0	153	88	16
Age, mean (SD), y	NA	71.4 (6.3)	69.7 (7.1)	67.9 (8.0)
Sex, No. (%)
Male	NA	63 (41.2)	54 (61.4)	9 (56.2)
Female	NA	90 (58.8)	34 (38.6)	7 (43.8)
Education, mean (SD), y	NA	16.8 (2.4)	16.6 (2.6)	15.4 (2.2)
APOE ε4 carriers, %	NA	50 (32.9)	34 (41.5)	11 (68.8)
MMSE, mean (SD)	NA	29.1 (1.2)	27.9 (2.0)	20.9 (2.8)
Self-reported race, No. (%)
American Indian/Alaska Native	NA	0 (0)	0 (0)	0 (0)
Asian		0 (0)	0 (0)	0 (0)
Black		10 (6.5)	2 (2.3)	1 (6.3)
Hawaiian/Pacific Islander		0 (0)	1 (1.1)	0 (0)
Multiracial		3 (2.0)	0 (0)	0 (0)
White		140 (91.5)	85 (96.6)	15 (93.7)
Unknown/not reported		0 (0)	0 (0)	0 (0)
Self-reported ethnicity, No. (%)
Hispanic/Latinx	NA	6 (3.9)	2 (2.3)	0 (0)
Not Hispanic/Latinx		145 (94.8)	86 (97.7)	16 (100)
Unknown/not reported		2 (1.3)	0 (0)	0 (0)

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Abbreviations: ADNI, Alzheimer’s Disease Neuroimaging Initiative; APOE, apolipoprotein E; CSF, cerebrospinal fluid; MMSE, Mini-Mental State Examination; NA, not applicable; SUVR, standardized uptake value ratio; TRIAD, the Translational Biomarkers in Aging and Dementia.

Associations Between CSF p-Tau and PET Biomarkers

Figure 1 displays voxelwise associations between CSF p-tau₁₈₁, p-tau₂₁₇, p-tau₂₃₁, and p-tau₂₃₅ with amyloid PET and with tau PET in the TRIAD cohort. CSF p-tau₂₃₁ and p-tau₂₁₇ had the strongest associations with amyloid PET across the cerebral cortex. Lower correlations were observed across the cerebral cortex for CSF p-tau₁₈₁, p-tau₂₁₇, p-tau₂₃₁, and p-tau₂₃₅ with tau PET. For all CSF p-tau phosphorylation sites, correlations above 0.65 were restricted to the medial temporal cortices. Frequency distributions of correlations are displayed in Figure 1C. For all p-tau biomarkers, associations with amyloid PET were more widespread across the brain.

Figure 2 displays associations between CSF p-tau biomarkers with summary measures of amyloid PET and tau PET in the TRIAD cohort. CSF concentrations of p-tau₂₁₇ and p-tau₂₃₁ were the most closely associated with neocortical summary measurements of amyloid PET (p-tau₂₁₇, ρ = 0.77; 95% CI, 0.69-0.82; P < .001; p-tau₂₃₁, ρ = 0.80; 95% CI, 0.73-0.85; P < .001). Correlations for CSF p-tau₁₈₁ and p-tau₂₃₅ with summary amyloid-PET SUVR were relatively lower (p-tau₁₈₁, ρ = 0.70; 95% CI, 0.61-0.77; P < .001; p-tau₂₃₅, ρ = 0.70; 95% CI, 0.60-0.76; P < .001). When investigating associations between CSF p-tau phosphorylation and tau-PET summary measurements, we observed that p-tau₂₁₇ and p-tau₂₃₁ biomarkers were most closely associated with tau PET in the temporal meta-ROI (p-tau₂₁₇, ρ = 0.66; 95% CI, 0.57-0.74; P < .001; p-tau₂₃₁, ρ = 0.65; 95% CI, 0.56-0.73; P < .001). Lower correlations were observed for p-tau₁₈₁ and p-tau₂₃₅ (p-tau₁₈₁, ρ = 0.57; 95% CI, 0.46-0.66; P < .001; p-tau₂₃₅, ρ = 0.61; 95% CI, 0.50-0.70; P < .001). Comparison of correlations revealed that for all p-tau phosphorylation sites, p-tau was significantly more closely associated with summary measurements of amyloid PET than with summary measures of tau-PET (p-tau₁₈₁ difference, 13%; t value = 2.54; P = .006; 95% CI, 0.03-0.22; p-tau₂₁₇ difference, 11%; t value = 2.77; P = .003; 95% CI, 0.03-0.20; p-tau₂₃₁ difference, 15%; t value = 3.96; P < .001; 95% CI, 0.05-0.22; p-tau₂₃₅ difference, 9%; t value = 1.98; 95% CI, 0.01-0.19; P = .02). In sensitivity analyses using the early amyloid PET from the Biomarkers for Identifying Neurodegenerative Disorders Early and Reliably (BioFINDER) study and inferior temporal ROIs, all p-tau biomarkers were more closely associated with amyloid PET than tau PET (eResults, eFigure 1, and eTable 5 in the Supplement). A summary of correlation comparisons for summary PET measures in the CSF TRIAD sample is provided in eTable 1 in the Supplement. A similar pattern of results was observed when examining CSF Aβ42/40 and tau-PET (eResults, eFigure 2, and eTable 2 in the Supplement). The CSF Aβ42/40 ratio was more closely associated with amyloid PET than tau PET (eFigure 3 in the Supplement). In analyses stratified by the presence of cognitive impairment, p-tau biomarkers were much more strongly associated with amyloid PET in CU individuals, whereas no differences were detected in cognitively impaired individuals (eTables 3 and 4 in the Supplement). Analyses comparing amyloid PET and tau PET across the entire cerebral cortex yielded the same pattern of results, although the results were stronger in magnitude (eTable 6 in the Supplement). In analyses comparing global amyloid PET to tau PET in Braak I-II regions, only p-tau₂₁₇ and p-tau₂₃₁ were significantly more closely associated with amyloid PET (eTable 7 in the Supplement). Partial correlation analyses revealed that CSF p-tau biomarkers were more closely associated with amyloid PET when controlling for tau-PET (eTable 8 in the Supplement). The same pattern of results held when controlling for age (eTable 9 in the Supplement) and sex (eTable 10 in the Supplement). Furthermore, CSF p-tau₁₈₁ in ADNI was more closely correlated with summary measurements of amyloid PET than with summary measurements of tau PET (t value, 2.21; 95% CI, 0.01-0.21; P < .05) (Figure 3). Subgroup analyses are reported in the eTable 11 in the Supplement.

Figure 3. — Scatterplots show the association between CSF p-tau₁₈₁ and summary measures of [¹⁸F]florbetapir amyloid PET and [¹⁸F]flortaucipir tau PET in the Alzheimer Disease Neuroimaging Initiative study. ROI indicates region of interest; SUVR, standardized uptake value ratio.

Associations Between Plasma p-Tau and PET Biomarkers

Finally, we investigated associations of plasma concentrations of p-tau₁₈₁, p-tau₂₁₇, and p-tau₂₃₁ with amyloid PET and tau PET in a nonoverlapping subsample in TRIAD (the individuals in the plasma analyses reported here did not undergo CSF p-tau assessments). Voxelwise analyses revealed that plasma p-tau₁₈₁, p-tau₂₁₇, and p-tau₂₃₁ had strong associations with amyloid PET across the neocortex (Figure 4). Furthermore, p-tau₁₈₁, p-tau₂₁₇, and p-tau₂₃₁ were closely associated with summary measures of amyloid-PET uptake (p-tau₁₈₁, ρ = 0.61; 95% CI, 0.49-0.70; P < .001; p-tau₂₁₇, ρ = 0.74; 95% CI, 0.66-0.81; P < .001; p-tau₂₃₁, ρ = 0.62; 95% CI, 0.51-0.73; P < .001). In comparison, associations between plasma concentrations of p-tau₁₈₁, p-tau₂₁₇, and p-tau₂₃₁ with tau PET were lower (p-tau₁₈₁, ρ = 0.50; 95% CI, 0.39-0.64; P < .001; p-tau₂₁₇, ρ = 0.64; 95% CI, 0.54-0.73; P < .001; p-tau₂₃₁, ρ = 0.49; 95% CI, 0.37-0.61; P < .001), including in medial temporal cortices. Comparison of correlations revealed that p-tau₁₈₁, p-tau₂₁₇, and p-tau₂₃₁ were significantly more closely associated with amyloid PET than with tau PET (plasma p-tau₁₈₁ difference, 11%; 95% CI, 1%-22%; P = .02; p-tau₂₁₇ difference, 9%; 95% CI, 1%-19%; P = .02; p-tau₂₃₁ difference, 13%; 95% CI, 3%-24%; P = .009). A summary of the correlation comparisons in the plasma TRIAD sample is provided in eTable 12 in the Supplement. Partial correlation analyses revealed that plasma p-tau biomarkers were more closely associated with amyloid PET when controlling for tau PET (eTable 13 in the Supplement). Results were similar when controlling for age (eTable 14 in the Supplement).

Figure 4. — Scatterplots show the association between plasma p-tau₁₈₁, p-tau₂₁₇, p-tau₂₃₁, and summary measures of amyloid PET and tau PET in the Translational Biomarkers in Aging and Dementia study. Brain images show the voxelwise associations of plasma p-tau₁₈₁, p-tau₂₁₇, and p-tau₂₃₁ with [¹⁸F]AZD4694 standardized uptake value ratio (SUVR) and [¹⁸F]MK6240 SUVR. ROI indicates region of interest.

Discussion

This cross-sectional study of 2 observational cohorts investigated the association between fluid measures of p-tau with amyloid-β plaques and tau neurofibrillary tangles assessed with PET. For all 4 p-tau phosphorylation sites examined in CSF, p-tau was more closely associated with cerebral amyloid-β plaques than with tau neurofibrillary tangles. These results were replicated with plasma p-tau₁₈₁, p-tau₂₁₇, and p-tau₂₃₁ in an independent subsample and with CSF p-tau₁₈₁ in a large independent cohort of individuals assessed with different amyloid-PET and tau-PET imaging agents. Our findings highlight the need for careful interpretation of p-tau biomarkers in the context of the A/T/(N) biomarker framework and for the biomarker-assisted identification of AD, especially in CU individuals.

Observational studies in humans have reported strong correlations between concentrations of amyloid PET and p-tau at various phosphorylation sites in individuals at different clinical stages of AD.^{14,17,28,29,30} Strong associations between antemortem plasma p-tau₁₈₁, p-tau₂₁₇, and p-tau₂₃₁ with amyloid-β plaques at autopsy have also been reported.³¹ In longitudinal observational studies, CU individuals with elevated amyloid-PET burden had increased concentrations of plasma and CSF p-tau₂₁₇ and p-tau₁₈₁ in the absence of neocortical tau-PET deposition.^16,32,33 Furthermore, soluble p-tau appeared to drive the association between amyloid-β plaques and insoluble tau aggregation measured with PET.^16,33 In individuals with dominantly inherited AD, p-tau₂₁₇ closely followed by p-tau₁₈₁ increased in response to amyloid-β accumulation, subsequently followed by tau-PET abnormality several years later.¹⁵ Furthermore, plasma p-tau₁₈₁ is elevated in individuals who are amyloid-PET positive but tau-PET negative (even in Braak I regions)³² and is elevated approximately 16 years before the onset of symptoms in dominantly inherited AD.³⁴ Moreover, a study using PET-based Braak staging suggested that both amyloid-PET and p-tau concentrations in CSF plateau at late stages of tangle aggregation,³⁵ in agreement with a recent autopsy study.³⁶ Taken together, these studies provide converging evidence supporting strong associations between amyloid-β plaques and p-tau biomarkers, which both precede widespread neurofibrillary tangle aggregation.

Several recent preclinical studies have reported that soluble p-tau levels in cell media, human tissue samples, and mouse models rise in response to aggregated amyloid-β.^37,38,39,40 In vitro models suggest that tau hyperphosphorylation is induced in neurons that take up neuronally secreted amyloid-β.^37,38 Amyloid-β plaques are also linked to increased neuronal release of hyperphosphorylated tau.³⁹ Studies in transgenic mice report that p-tau concentrations in CSF rise as a consequence of amyloid-β deposition,⁴⁰ and human neural stem cell–derived cell culture systems overexpressing APP and PSEN1 induced tau phosphorylation closely linked with amyloid-β concentrations.⁴¹ A study using stable isotope labeling kinetics in humans demonstrated that soluble p-tau production was positively correlated with amyloid-PET signal but did not change in the presence of elevated tau PET.⁴² These studies support increased tau phosphorylation as an early event in the amyloid-β cascade, closely linked with concentrations of amyloid-β pathology.

Recent p-tau biomarker studies have raised questions about the preferential association of various p-tau epitopes with AD stage, severity, and neuropathological hallmarks.⁴³ Tau can be phosphorylated at over 80 different sites on the tau protein,⁴⁴ and the pathophysiological roles of phosphorylation at different sites are unclear.⁴⁵ However, recent studies have provided evidence that specific p-tau phosphorylation sites appear to become elevated in a disease stage-dependent manner^15,46 and that phosphorylation at specific peptides is associated with increased tau seeding activity and clinical disease progression.⁴⁷ In our study, p-tau biomarkers were most closely associated with tau aggregation in medial temporal brain regions (though still less so than with global amyloid PET), supporting p-tau as an early biomarker. This result is consistent with a recent community-based study that observed a stronger association between plasma p-tau with entorhinal tau PET than commonly used summary measures of tau PET.⁴⁸ Of the 4 p-tau biomarkers examined in CSF, p-tau₂₁₇ and p-tau₂₃₁ showed the highest association with amyloid PET. In plasma, p-tau₂₁₇ was most closely associated with cerebral amyloid-PET concentrations. Although site-specific patterns of tau phosphorylation may provide information regarding disease stage in AD, it also will be crucial to understand the contribution of analytical properties of different assays.

Our study highlights the need for a granular approach to tau biomarkers, in which different tau biomarkers provide complementary but not interchangeable information.^{21,28,45,49,50} Although the tau biomarker category in the A/T/(N) framework currently includes tau PET and p-tau in biofluids,^3,4 it is important to draw distinctions between both classes of biomarkers. Tau-PET ligands are considered to bind to insoluble neurofibrillary tangles, consisting of paired helical filament aggregates of hyperphosphorylated tau.^51,52 Fluid biomarkers of soluble p-tau, in contrast, measure the concentration of tau phosphorylated at specific serine, threonine, or tyrosine amino acids on the tau protein, which have leaked from the extracellular space into the CSF or blood compartments. CSF and plasma p-tau biomarkers are reported to rise early in the AD pathophysiological process.^8,16 Tau tangle aggregation measured with PET occurs later and is strongly predictive of cognitive decline.⁵³ In this connection, the much higher association of p-tau biomarkers with amyloidosis than tangle burden in CU individuals suggests that p-tau biomarkers may be less well-positioned to predict future cognitive decline. In contrast, the high association of p-tau biomarkers with both amyloidosis and tangle burden in individuals with cognitive impairment suggest that abnormal p-tau biomarkers have a strong predictive value for AD in diagnostic settings. Taken together, these results highlight the need to distinguish between biomarkers of phosphorylated and aggregated tau in the A/T/(N) framework, particularly in CU individuals.

Limitations

Results of this study should be interpreted in the context of several limitations. First, tau (hyper)phosphorylation is a dynamic process, the understanding of which is anticipated to evolve with respect to the availability of more biomarkers. Because tau can be phosphorylated at over 80 sites, some of which are hypothesized to have site-specific associations with disease stage, it is unknown whether all future p-tau biomarkers will exhibit the preferential association with amyloid PET reported in this study. Another limitation is that PET biomarker signals (used in this study as measurements of amyloid-β plaques and tau tangles) are influenced by their affinities (1 / equilibrium dissociation constant [K_d]) for their target. However, because [¹⁸F]MK6240 has a higher affinity for tau tangles than [¹⁸F]AZD4694 does for amyloid-β plaques, the stronger association of p-tau with amyloid PET is unlikely to be driven by sensitivity issues. Replication in an independent cohort (ADNI) with different PET imaging agents helps further attenuate these concerns. Similar to PET biomarkers, biofluid assay performance can affect interpretation of the results in this study. For example, it is unclear to what degree the stronger associations of p-tau₂₁₇ and p-tau₂₃₁ with PET biomarkers are driven by biological properties of phosphorylation of a specific amino acid compared with differences in the assays used to detect them (ie, antibody affinity, robustness of individual reagents, assay platform). Other limitations of this study include the lack of availability of plasma p-tau₂₃₅ in the TRIAD cohort and the lack of availability of plasma p-tau₁₈₁ at the same time point as tau-PET in ADNI. Furthermore, the TRIAD and ADNI cohorts consist of individuals motivated to participate in a study of AD, which may limit generalizability. Finally, the cohorts are not demographically representative of the populations at risk for dementia in North America.

Conclusions

In conclusion, results of this cross-sectional study of 2 observational cohorts suggest that p-tau biomarkers better reflect the concentration of amyloid-β plaques than cerebral tau pathology quantified with PET. Our findings contribute to the growing understanding of the role of tau phosphorylation in the amyloid-β cascade and highlight the need for careful interpretation of p-tau biomarkers in CU individuals and as outcomes in disease-modifying clinical trials.⁷

Supplement.

eMethods 1. Positron Emission Tomography Image Acquisition and Processing

eMethods 2. CSF and Plasma Sample Handling and Assays

eResults. Sensitivity Analyses

eFigure 1. Relationship Between CSF p-Tau Biomarkers and Early PET ROIs

eFigure 2. Relationship Between CSF p-Tau Biomarkers and CSF Aβ42/40 and Tau-PET

eFigure 3. Relationship of CSF Aβ42/40 Ratio With Amyloid-PET and Tau-PET

eTable 1. Statistical Comparison of Correlation Between CSF p-Tau Biomarkers and Summary Amyloid- and Tau-PET Biomarkers in TRIAD

eTable 2. Statistical Comparison of Correlations Between CSF p-Tau Biomarkers With CSF Aβ42/40 and Tau-PET Biomarkers in TRIAD

eTable 3. Statistical Comparison of Correlations Between CSF p-Tau With Amyloid-PET and Tau-PET in CU Individuals in TRIAD

eTable 4. Statistical Comparison of Correlations Between CSF p-Tau With Amyloid-PET and Tau-PET in CI Individuals in TRIAD

eTable 5. Statistical Comparison of Correlations Between CSF p-Tau Biomarkers and Early Amyloid- and Tau-PET Biomarkers in TRIAD

eTable 6. Statistical Comparison of Correlations Between CSF p-Tau Biomarkers and Whole-Cortex Amyloid-PET and Whole-Cortex Tau-PET in TRIAD

eTable 7. Statistical Comparison of Correlations Between CSF p-Tau Biomarkers and Summary Amyloid-PET and Braak I-II Tau-PET Biomarkers in TRIAD

eTable 8. Statistical Comparison of Partial Correlations Between CSF p-Tau With Amyloid-PET and Tau-PET in TRIAD Correcting for Each Other

eTable 9. Statistical Comparison of Partial Correlations Between CSF p-Tau With Amyloid-PET and Tau-PET in TRIAD Correcting for Age

eTable 10. Statistical Comparison of CSF p-Tau Associations With Amyloid-PET and Tau-PET in TRIAD Correcting for Sex

eTable 11. Statistical Comparison of Correlations Between CSF p-Tau With Amyloid-PET and Tau-PET in ADNI

eTable 12. Statistical Comparison of Correlations Between Plasma p-Tau Biomarkers and Summary Amyloid-PET and Tau-PET Biomarkers in TRIAD

eTable 13. Statistical Comparison of Correlations Between Plasma p-Tau Biomarkers With Amyloid-PET and Tau-PET in TRIAD Correcting for Each Other

eTable 14. Statistical Comparison of Correlations Between Plasma p-Tau Biomarkers With Amyloid-PET and Tau-PET in TRIAD Correcting for Age

References

Click here for additional data file.^{(526.1KB, pdf)}

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