Tau PET as Progression Marker: It’s the Spread, Not the Brightness

Series - AD/PD™ 2025: Advances in Science & Therapy:

Tau PET correlates closely with cognitive decline in Alzheimer’s disease, making it a potential surrogate outcome measure. Yet in amyloid immunotherapy trials to date, this signal has not always tracked well with cognitive benefits. At the International Conference on Alzheimer’s and Parkinson’s Diseases, held April 1-5 in Vienna, Arthur Macedo at McGill University, Montreal, suggested changing the way tau PET is measured. Rather than calculating signal intensity via the standard uptake value ratio, he quantified what he called the spatial extent of tauopathy. SEOT, for short, grows as tangles creep across the brain. SEOT outperformed SUVR at diagnosing and staging AD, especially early in the disease, and it correlated more closely with severity as measured by CDR-SB and biomarkers of neurodegeneration. “SEOT might be a good surrogate measure of efficacy in early AD trials,” Macedo concluded.

  • Measures of tau spread beat out SUVR for diagnosing and staging early AD.
  • This could make them promising outcome measures.
  • A secondary prevention trial of an anti-tau vaccine is using this approach.

This work reflects a trend in the field, with several groups publishing similar methods recently. “This is a very promising approach,” said Tammie Benzinger at Washington University, St. Louis, an author on one such study. Diane Stephenson at the Critical Path Institute in Tucson, Arizona, which helps accelerate progress toward neurodegenerative disease treatments, agreed. “I firmly believe that spatial distribution is key,” she wrote to Alzforum.

Companies are beginning to incorporate such measures into trials. In Vienna, scientists at Johnson & Johnson described how the Phase 2 trial, in preclinical AD, of their active tau vaccine JNJ-64042056 will evaluate whether tangles move into new brain regions, rather than measuring an increase in total tau burden. “This is an individualized, precision approach,” noted J&J’s Lennert Steukers.

Spread First, Then Accumulate. In Braak stage I-II (left), III-IV (middle), and V-VI (right) brain regions, tangles appear in new neurons (y axis) long before those cells become positive by SUVR (x axis). [Courtesy of Arthur Macedo.]

Tauopathy Extent Peaks First, Load Later
Why spatial extent? Scientists have known for a decade that neuronal activity releases tau (Feb 2014 news; Jun 2016 news). More recently, they have shown that the hyperexcitability sparked by amyloid plaques strews tangles across the brain, allowing the pathology to colonize new regions (Dec 2023 news; Jan 2025 news; Feb 2025 conference news).

Consequently, several groups are now investigating if assessing tangle spread could be useful. All report that spatial extent changes earlier than SUVR and correlates better with cognitive decline (St-Onge et al., 2024; Gérard et al., 2024; Doering et al., 2024).

In Vienna, Macedo, who received a junior faculty award at the conference, built on this. A graduate student in the lab of Pedro Rosa-Neto at McGill, he compared SEOT and SUVR in Montreal’s Translational Biomarkers in Aging and Dementia (TRIAD) longitudinal cohort. He assessed 466 participants, average age 68, who ranged from cognitively healthy and plaque-free to severe AD dementia. Half were cognitively impaired; 55 percent were amyloid-positive. As in many AD studies, nearly all were non-Hispanic white; 60 percent were women.

To measure SEOT, Macedo calculated the mean and standard deviation of the signal intensity on the MK-6240 tau PET scans of a reference group of 42 young adults. He used this to evaluate tau PET scans in the TRIAD cohort. Every voxel on the TRIAD scans was scored as having either a normal or abnormal tau load, where abnormal was defined as more than 2.5 standard deviations above the amount in the healthy young controls (Pascoal et al., 2020). The percentage of abnormal voxels in a region gave the SEOT.

Macedo compared SEOT and SUVR in the brain regions that comprise Braak stages I-II, III-IV, and V-VI. In each region, he found that SEOT grew first. In Braak I-II, SUVR became positive only after SEOT had plateaued, with all voxels abnormal. In the later regions, SUVR turned positive a little earlier, after more than half of voxels had accumulated tangles (image above).

Due to this time shift, SEOT was better at detecting early disease. In Braak regions III-IV and V-VI, SEOT beat out SUVR for distinguishing mild cognitive impairment from cognitively healthy people, with or without plaque. In Braak V-VI, SEOT was more accurate at detecting the presence of amyloid plaques, both in cognitively impaired and unimpaired groups.

SEOT was also more sensitive to disease severity. In Braak III-IV and V-VI, SEOT outperformed SUVR in flagging hippocampal atrophy, p-tau217 in cerebrospinal fluid, amyloid plaque load, and decline on the CDR-SB. In Braak I-II, SEOT offered an edge in detecting hippocampal atrophy, but not the other markers, which change little at this early timepoint.

Space, An Early Frontier. When a brain region is tau-negative by SUVR (green arrow, left), spatial extent (dark blue) correlates better with measures of disease severity than does SUVR (light blue). Once the region becomes tau-positive (red arrow, right), both measures perform equally well. [Courtesy of Arthur Macedo.]

The picture became more complicated when Macedo took disease stage into account. He found that the relative performance of SEOT and SUVR depended on how much tau was in a region. When the tau burden was below the positivity threshold on SUVR, SEOT correlated better with disease severity. Once SUVR turned positive, it correlated better with markers of severity than did SEOT in Braak I-II, and performed equally well in Braak III-IV and V-VI (image above).

Likewise, in two-year longitudinal data on 154 participants, when a Braak region was tau-negative on SUVR, SEOT bested SUVR at predicting future tangle accumulation, both in that region and in the next Braak region. When a Braak region was tau-positive, both measures predicted future pathology equally well.

SEOT captures the initial spreading phase of tauopathy, while SUVR measures the accumulation phase, Macedo concluded. This makes him think that SEOT will likely be a better outcome measure for trials targeting early AD. However, both are useful. “SEOT and SUVR offer complementary insights into tau pathology. Evaluating both together could offer a more comprehensive picture of disease progression and therapeutic response,” Macedo told Alzforum. The audience in Vienna called these data exciting and asked many technical questions.

Spread Defines Stage
Spatial extent is also being applied to diagnosis. The proposed new Alzheimer’s disease criteria use both tangle location and load to stage disease. Tangles in the medial temporal lobe, i.e., Braak stage I-II, are considered early disease; moderate neocortical tau, i.e., Braak III-IV, is considered intermediate; and high neocortical tau in Braak V-VI is considered advanced (Aug 2023 conference news; Nov 2023 conference news).

In Vienna, Macedo presented work from Lydia Trudel in the Rosa-Neto group, who evaluated how well this staging system predicts future tangle accumulation. Trudel analyzed longitudinal data from 230 TRIAD and 312 ADNI participants; about a third of each cohort were cognitively impaired. Tau PET scans in the TRIAD cohort were done with MK-6240, those in ADNI with the less-sensitive tracer flortaucipir. (To compare this to disease staging by tau fluid biomarkers, see Part 7 of this series.)

In the TRIAD cohort, a tau PET signal in the medial temporal lobe predicted accumulation in both Braak I-II and III-IV over the next two years. Meanwhile, a neocortical signal, whether moderate or high, predicted tangle growth in Braak III-IV and V-VI. In the ADNI cohort, medial temporal lobe tau predicted only Braak I-II accumulation, and moderate neocortical tau only Braak III-IV, over the next 3.5 years. This difference was likely due to the lower sensitivity of the tracer used in this study, Trudel believes. High neocortical tau in ADNI predicted change in both Braak III-IV and V-VI, just as in TRIAD.

When using tau PET as an outcome measure, scientists need to take tracer differences into account, Macedo said in Vienna. Scientists also need to pay attention to which regions are expected to accumulate tangles at a given disease stage. For example, in the donanemab Phase 3 Trailblazer-Alz2 trial, the antibody did not significantly slow tangle growth in frontal brain regions as quantified by flortaucipir. However, about two-thirds of participants had low to medium baseline tangle loads, and would not be expected to accumulate tau in frontal regions during the duration of the trial. Analyzing only the high-tau participants, those on donanemab did develop fewer frontal tangles than did those on placebo, as would be expected for a disease-modifying treatment, Trudel found.

“It is important to know which regions are expected to increase, so we can look for a treatment effect in the right regions,” Macedo said in Vienna.

CenTauR Unifies SUVR Scale—Could it Aid SEOT, Too?
To grapple with tracer differences, the Critical Path Institute recently spearheaded the development of a unified scale for tau PET scans. Called CenTauR (CTR), it is similar to the centiloid scale for amyloid, allowing scans done with different tracers to be evaluated on an equal footing (Aug 2023 conference news). The method converts SUVR to CTR. The CenTauR scale was published last year, and is now in use in many observational studies and trials, Stephenson noted (Leuzy et al., 2024). In the future, calculations of SEOT, or other measures of tangle spread, could perhaps employ CTR instead of SUVR to determine a neuron’s positive or negative tangle status. This would allow scientists to make use of data from multiple tracers.

Untouched by Tangles. To measure the effect of an anti-tau vaccine, Johnson & Johnson researchers will identify “tau-naïve” voxels (pink, right) on a baseline tau PET scan (left), then evaluate how many of them remain pristine after treatment. [Courtesy of Johnson & Johnson, 2025.]

Tau Spread as Treatment Trial Outcome Measure
Johnson & Johnson scientists believe tangle spread is likely to be the best marker of success for their anti-tau vaccine JNJ-64042056. This construct, originally developed by AC Immune as ACI-35.030, induces antibodies specific for phosphorylated tau in mice and monkeys (Theunis et al., 2013). In Phase 1, it provoked a strong immune response in humans, too, generating antibodies that recognized paired helical filaments of tau from AD brains (Dec 2022 conference news).

In Vienna, Clara Theunis at Johnson & Johnson reported that antibodies induced by JNJ-64042056 inhibited cellular uptake of tau aggregates in vitro. Bruno Vasconcelos at J&J introduced tau seeds isolated from AD brain to rat primary cortical neuron cultures. A week later, endogenous tau in these neurons had clumped up. When polyclonal antibodies from immunized rhesus monkeys were added at the same time as tau seeds, however, only half as many aggregates formed.

Steukers detailed how the Phase 2 Retain trial will test this vaccine. This secondary prevention trial aims to enroll 500 cognitively healthy people who are positive for amyloid and tau. Prospective participants will be screened by plasma p-tau217 to find those likely to be positive, with tauopathy confirmed by MK-6240 tau PET. Half the participants will receive the vaccine, half placebo, with three immunizations in the first six months followed by boosters every six months. The trial will run for four years, because prior studies showed that about half of cognitively healthy people who are positive for amyloid and tau develop MCI within 3.5 years (Ossenkoppele et al., 2022).

The primary outcome will be change on the PACC-5 cognitive composite. Tau PET is the key secondary endpoint. To measure spread, scientists will record which voxels on each person’s baseline scan are “tau naïve,” defined as being within one standard deviation of the PET signal in that spot in amyloid-negative controls (image above). At the end of the trial, scientists will compare how many tau-naïve voxels have become positive in treatment versus placebo groups.

This is a new, ambitious measure requiring great precision. Even so, J&J scientists hope tau spread will prove to be a better outcome measure than SUVR. They think so because, mechanistically, the vaccine is expected to prevent uptake of tau aggregates into new neurons, not break down existing tangles. Hence, treatment should change a person’s estimated future spread of tangles, not their baseline load, Steukers noted. The study is currently enrolling at 69 sites in Australia, France, Japan, Spain, Sweden, the U.K., and the U.S., with plans to expand into Belgium, Germany, and South Korea.—Madolyn Bowman Rogers

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References

News Citations

  1. Neurons Release Tau in Response to Excitation
  2. Excited Neurons Release More Aberrant Tau
  3. Plaques Kick Neocortical Neurons into Overdrive, Entangling Tau
  4. Plaques Spur Spread of Tangles by Sending Synapses into Overdrive
  5. When Tau Wanders Off, Subcortical Axon Firing Goes Mum
  6. Revised Again: Alzheimer's Diagnostic Criteria Get Another Makeover
  7. New Alzheimer’s Diagnostic Criteria Remain ‘Research Only’
  8. Looking Good: Immunoassays for Blood Markers
  9. Biomarkers and Efficacy: Not (Yet?) a Perfect Union
  10. Two New Stabs at Vaccinating People Against Pathologic Tau

Therapeutics Citations

  1. Kisunla

Paper Citations

  1. St-Onge F, Chapleau M, Breitner JC, Villeneuve S, Pichet Binette A. Tau accumulation and its spatial progression across the Alzheimer's disease spectrum. Brain Commun. 2024;6(1):fcae031. Epub 2024 Feb 7 PubMed.
  2. Gérard T, Colmant L, Malotaux V, Salman Y, Huyghe L, Quenon L, Dricot L, Ivanoiu A, Lhommel R, Hanseeuw B. The spatial extent of tauopathy on [18F]MK-6240 tau PET shows stronger association with cognitive performances than the standard uptake value ratio in Alzheimer's disease. Eur J Nucl Med Mol Imaging. 2024 May;51(6):1662-1674. Epub 2024 Jan 17 PubMed.
  3. Doering S, McCullough A, Gordon BA, Chen CD, McKay N, Hobbs D, Keefe S, Flores S, Scott J, Smith H, Jarman S, Jackson K, Hornbeck RC, Ances BM, Xiong C, Aschenbrenner AJ, Hassenstab J, Cruchaga C, Daniels A, Bateman RJ, Dominantly Inherited Alzheimer Network (DIAN) Investigators, Morris JC, Benzinger TL. Deconstructing pathological tau by biological process in early stages of Alzheimer disease: a method for quantifying tau spatial spread in neuroimaging. EBioMedicine. 2024 May;103:105080. Epub 2024 Mar 28 PubMed.
  4. Pascoal TA, Therriault J, Mathotaarachchi S, Kang MS, Shin M, Benedet AL, Chamoun M, Tissot C, Lussier F, Mohaddes S, Soucy JP, Massarweh G, Gauthier S, Rosa-Neto P, Alzheimer's Disease Neuroimaging Initiative. Topographical distribution of Aβ predicts progression to dementia in Aβ positive mild cognitive impairment. Alzheimers Dement (Amst). 2020;12(1):e12037. Epub 2020 Jun 21 PubMed.
  5. Leuzy A, Raket LL, Villemagne VL, Klein G, Tonietto M, Olafson E, Baker S, Saad ZS, Bullich S, Lopresti B, Bohorquez SS, Boada M, Betthauser TJ, Charil A, Collins EC, Collins JA, Cullen N, Gunn RN, Higuchi M, Hostetler E, Hutchison RM, Iaccarino L, Insel PS, Irizarry MC, Jack CR Jr, Jagust WJ, Johnson KA, Johnson SC, Karten Y, Marquié M, Mathotaarachchi S, Mintun MA, Ossenkoppele R, Pappas I, Petersen RC, Rabinovici GD, Rosa-Neto P, Schwarz CG, Smith R, Stephens AW, Whittington A, Carrillo MC, Pontecorvo MJ, Haeberlein SB, Dunn B, Kolb HC, Sivakumaran S, Rowe CC, Hansson O, Doré V. Harmonizing tau positron emission tomography in Alzheimer's disease: The CenTauR scale and the joint propagation model. Alzheimers Dement. 2024 Sep;20(9):5833-5848. Epub 2024 Jul 23 PubMed.
  6. Theunis C, Crespo-Biel N, Gafner V, Pihlgren M, López-Deber MP, Reis P, Hickman DT, Adolfsson O, Chuard N, Ndao DM, Borghgraef P, Devijver H, Van Leuven F, Pfeifer A, Muhs A. Efficacy and Safety of A Liposome-Based Vaccine against Protein Tau, Assessed in Tau.P301L Mice That Model Tauopathy. PLoS One. 2013;8(8):e72301. PubMed.
  7. Ossenkoppele R, Pichet Binette A, Groot C, Smith R, Strandberg O, Palmqvist S, Stomrud E, Tideman P, Ohlsson T, Jögi J, Johnson K, Sperling R, Dore V, Masters CL, Rowe C, Visser D, van Berckel BN, van der Flier WM, Baker S, Jagust WJ, Wiste HJ, Petersen RC, Jack CR Jr, Hansson O. Amyloid and tau PET-positive cognitively unimpaired individuals are at high risk for future cognitive decline. Nat Med. 2022 Nov;28(11):2381-2387. Epub 2022 Nov 10 PubMed.

Other Citations

  1. JNJ-64042056

External Citations

  1. Phase 2 Retain trial

Further Reading

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