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It’s Official: Tau PET Sees Tangles, and Staging Tangles Predicts Decline

Series - Clinical Trials on Alzheimer's Disease 2018:

Do tau PET tracers truly detect tangles? How will we use them? The cutting edge on these evolving questions was on display at the 11th Clinical Trials on Alzheimer’s Disease conference, held October 24–27 in Barcelona, Spain.

  • It’s official: Flortaucipir reflects tangles in late-stage tauopathy.
  • Second-generation tau tracers are less noisy.
  • Tau PET will help select trial participants, identify AD subtypes.

Mark Mintun of the Eli Lilly subsidiary Avid Radiopharmaceuticals, Philadelphia, presented postmortem validation data that confirmed the flortaucipir signal indeed picked up tau tangles in the brain, at least at advanced Braak stages. Other scientists advanced newer tau tracers from Merck, Roche, and Life Molecular Imaging (formerly Piramal). Their data showed that these second-generation tracers are more sensitive and have less noise than flortaucipir, or other early tracers that have since faded, such as THK5351. Practical applications of tau imaging are starting up, from screening people for clinical trials to picking up subtypes of Alzheimer’s disease. Tau PET talks generated intense interest from an engaged audience.

“These are incredible studies,” said Eric Siemers, who retired from Lilly and now consults at Siemers Integration LLC in Indianapolis.

More Signal, Less Noise. New tau tracers, such as PI-2620 shown here, have little background. [Courtesy of Andrew Stephens.]

It’s Official: Flortaucipir Measures Tangles in Late-Stage Tauopathy
Lilly first announced findings from its Phase 3 postmortem study in a press release (Sep 2018 news), and in Barcelona, Mintun showed detailed data. The trial recruited people who had less than six months to live and were willing to have a flortaucipir scan and donate their brains. Out of 64 participants who came to autopsy, 49 had been clinically diagnosed with dementia and one with mild cognitive impairment. Their average age was 82. On postmortem examination, 39 of them had tangle pathology consistent with Braak stage 5 or 6; the other 25 were at earlier stages.

For one primary study endpoint, Lilly measured flortaucipir’s ability to predict Braak stage 5/6 pathology. Tracer signal in AD brain regions had to be 65 percent higher than in cerebellum in order to count as a positive scan. Five independent, blinded readers evaluated the scans. They correctly identified 36 of the 39 advanced-stage brains as positive, for a diagnostic sensitivity of 92 percent. However, they also called positive the scans from five people who were at earlier Braak stages, leading to a specificity of only 80 percent.

In answer to a question from Gil Rabinovici of the University of California, San Francisco, Mintun said these false positives were mostly Braak stage 4. Rabinovici challenged the decision to select such an advanced stage of disease as the criteria for a positive scan. Mintun said Lilly deemed this a useful clinical threshold and is examining the use of lower thresholds as an exploratory outcome. Others noted both publicly and to Alzforum that identifying people at earlier Braak stages would be important for selecting trial participants. It is unclear how well flortaucipir would perform at this stage of disease, when the tracer signal is lower and likely to be more muddied by background off-target binding.

As a co-primary endpoint, Lilly researchers evaluated flortaucipir’s ability to discern high levels of AD neuropathology as per NIA/AA criteria (Hyman et al., 2012; Jan 2012 news). Results were similar to the Braak analysis, with scan reads reaching a sensitivity of 95 percent and specificity of 81 percent. The area under the curve was 0.94, which Minton noted was good for a diagnostic test.

Brains with AD neuropathology had tracer signal in the posterior lateral temporal and occipital lobes. At the most advanced stages of disease, parietal and frontal regions lit up as well. For both endpoints, the readers agreed on how to interpret a scan 90 percent of the time. False-positive calls varied the most between readers, and Mintun said Lilly will look into the reasons behind this variability.

Researchers in Barcelona greeted the data with enthusiasm. “This is a major advance. I’m very excited,” said Stephen Salloway of Brown University in Providence, Rhode Island. At the same time, Salloway expressed concern that using a negative/positive dichotomy for tau scans could limit research. After all, the new NIA/AA research framework describes tau pathology as a continuum. Mintun agreed that quantifying tau might be more useful than assigning a cutoff for positivity. In a separate, higher-resolution study of three additional postmortem brains, researchers measured the amount of tangles in several brain regions and compared it to the SUVR signal. Mintun said the signal strength correlated well with absolute levels of pathology. “We have good hope of treating tau pathology as a continuum,” he said.

See Tau Early. Roche’s tau tracer RO-948 better discriminates AD patients from controls based on tangles in Braak regions 1/2 than in 3/4. People with cognitive decline (SCD/MCI) took up the same amount of tracer as age-matched controls (OC) in all regions. [Courtesy of Gregory Klein.]

Sharper Image with New Tracers?
One limitation of flortaucipir is its high background signal in the basal ganglia and choroid plexus, which sits right above the hippocampus. New tracers appear more specific. In Barcelona, Gregory Klein at Roche reported findings for that company’s tau tracer RO-948 (May 2018 news). Oskar Hansson and colleagues at Lund University, Sweden, used RO-948 to scan 223 participants in BioFINDER2, who included 30 young controls, 21 cognitively healthy older controls, 84 people with some cognitive impairment, 50 people diagnosed with AD, and 30 with other dementias, as well as a few whose diagnosis was uncertain.

The RO-948 signal distinguished people with an AD diagnosis from age-matched controls with high significance. P values stayed in the 0.0005 range whether the researchers examined tracer binding in transentorhinal regions corresponding to Braak stage 1/2, limbic regions corresponding to Braak 3/4, or cortical regions corresponding to Braak 5/6. In fact, the difference was most pronounced in regions 1/2 (see image above).

In people with mild or subjective cognitive impairment, on the other hand, tracer binding was only elevated in the transentorhinal cortex, and the average was not much different from binding in age-matched cognitively healthy controls. This suggests some transentorhinal cortex binding may represent normal aging-related changes, though the uptake range in this group was wide. Does this suggest that tau PET clearly flags people only once their clinical symptoms advance beyond MCI? Supporting this, the authors found that more tangles in limbic regions correlated with lower MMSEs, with SUVRs of 1.5 or higher corresponding to an average MMSE below 25.

The SUVR signal in this cohort ran from zero to 4, providing a wide dynamic range. RO-948 had little off-target binding, with 9 percent of participants having a small signal in the basal ganglia, and 14 percent in the choroid plexus. Almost a third of the cohort had a signal in their meninges, however; in the seven with the strongest binding here, the authors speculated that it could interfere with measuring tau in cortical regions of interest. In addition, off-target binding in the substantia nigra and retina was common.

Andrew Stephens of Life Molecular Imaging presented similar data for the tracer PI-2620, on 12 people diagnosed with AD and 10 healthy controls. (For previous PI-2620 data, see Apr 2017 conference news; Dec 2017 conference news). In AD patients, the researchers saw increased tracer binding in a mesial temporal cortical composite region, as well as in a temporoparietal composite. In both cases, the Cohen’s d effect size was larger than 2, i.e. the difference between AD and controls exceeded two standard deviations. This tracer generated no signal in basal ganglia or choroid plexus (see image above). Like RO-948, PI-2620 had peak SUVRs of 4 or more. It performed best when scans were done 30 to 90 minutes after injection. In this time window, test-retest variability remained below 5 percent, but was higher at later time points.

This contrasts with Merck’s MK-6240. Previous work had suggested an optimal time window of 70 to 90 minutes for scanning with this tracer (May 2018 conference news), but in Barcelona, Tharick Pascoal of McGill University, Montreal, reported that MK-6240 gives more reliable results when measured between 90 and 110 minutes after injection. His studies indicate the tracer is slow, reaching equilibrium in regions with low tauopathy after 60 minutes but taking 90 minutes in regions with high pathology (Pascoal et al., 2018). In a study of 16 participants, Pascoal and colleagues found that scanning sooner than 90 minutes after injection led to underestimates of tangle burden in regions with SUVRs above 2. This gets more pronounced the higher the tau burden. In a therapeutic trial using tau PET as an outcome measure, this could underrate a drug effect, Pascoal said, because the pretreatment signal would underestimate tau burden more than the post-treatment signal would.

Putting Tau PET to Use
As tau PET imaging becomes more reliable, researchers are investigating how it might work in practice. In Barcelona, Adam Fleisher of Avid said tau scans could help sites screen participants for therapy trials, picking out those who are most likely to decline cognitively in the near future but are not too advanced to benefit from therapy. Fleisher analyzed data from selected participants in the Phase 3 EXPEDITION3 and a Phase 2 flortaucipir trial. This ad hoc cohort comprised 65 people with prodromal AD and 181 with AD dementia, with an average age of 73. Both trials ran for 18 months, with repeat cognitive testing, and the selected participants had baseline flortaucipir and florbetapir scans. Twenty percent of the cohort were amyloid-negative, and all of that group were also tau-negative. Among the amyloid-positive group, 77 percent were tau-positive, too.

The researchers evaluated tau burden in two different ways. In the first method, a purely quantitative one, they divided the group into quartiles based on their levels of tau tracer signal. Curiously, participants with AD dementia were equally distributed across the tau quartiles. In the second method, a regional one, researchers determined by visual read whether tau scans had an “AD pattern.” As in the autopsy study, this was defined as uptake in the posterior lateral temporal and occipital lobes, with the most advanced cases also having parietal and frontal uptake.

By either method, people with more tau pathology declined faster on cognitive tests. For the quartile method, those in the first quartile stayed about stable, while those in the second or third quartile slid by an average of 5 points from their baseline performance on the ADAS-Cog11, and those in the fourth quartile dropped a whopping 11 points. For visual reads, participants broke into two categories. Those without parietal tau barely declined, while those with tau there lost six points on the ADAS-Cog11. The pattern for MMSE scores and tau burden was similar.

Overall, the distribution of tau better predicted cognitive decline than the quantity, Fleisher noted. People whose tangles had spread beyond the posterior lateral temporal (PLT) lobe declined equally fast regardless of whether they fell into the first, second, or third quartiles. Tau extending beyond this region seems to trigger cognitive decline, Fleisher concluded. Frontal tau uptake marked another key event, as everyone in this category fell into the fourth quartile, with the fastest decline.

Combining quantitative and qualitative data best captured disease progression, Fleisher said. People whose florbetapir SUVR exceeds 1.10, with tangles in the PLT, are at risk for imminent cognitive decline, while those with an SUVR of 1.46 or higher and uptake in the frontal cortex have global tauopathy and will decline steeply. These two thresholds define an optimal window for therapeutic intervention, Fleisher proposed.

A different application of tau imaging came from Rik Ossenkoppele of VU University Medical Center, Amsterdam. Ossenkoppele wondered whether the uptake pattern could reveal subtypes of Alzheimer’s. Some people have a limbic-predominant form of the disease, with atrophy mostly in the hippocampus, while others have a hippocampal-sparing form, with atrophy mostly in the neocortex. In typical AD, both regions shrink (Murray et al., 2011; Whitwell et al., 2012; Ferreira et al., 2017). Can tau PET tell them apart? Ossenkoppele and colleagues took a look.

They analyzed data from 260 amyloid-positive people with symptomatic AD, who were in the Swedish BioFINDER study or were seen at the University of California San Francisco AD Research Center or the Memory Disorder Clinic of Gangnam Severance Hospital in Seoul, South Korea. The researchers used MRI volumetry to divide this cohort into the three AD subtypes based on their atrophy in these respective regions. This categorized 70 participants as typical, 77 as limbic-predominant, and 76 as hippocampal-sparing AD. The remaining 37 participants had little evidence of brain atrophy. Several differences emerged. People with typical AD had more white-matter hyperintensities than the other groups. Participants with the hippocampal-sparing form tended to be younger and were less likely to carry ApoE4. They declined the fastest on the MMSE over four years, but were less likely than the other subtypes to have memory problems.

What about tau, though? As expected, flortaucipir scans unmasked a distinct pattern of tracer uptake for each subtype. Limbic-predominant AD had most tangles in the entorhinal cortex, hippocampal-sparing AD in parietal and frontal cortex, while typical AD was marked by tangles in lateral temporal as well as frontal and occipital cortices. In short, tau PET can be used as a proxy for atrophy, Ossenkoppele concluded.

As researchers train their sights on tau pathology as a therapeutic target, being able to measure and track tangles will be crucial, noted Lennart Mucke of the Gladstone Institute of Neurological Disease in San Francisco, in a plenary. “I’m excited that the pipeline is filling up with tau biomarkers,” he said.—Madolyn Bowman Rogers

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References

News Citations

  1. Flortaucipir Meets Primary Endpoints in Phase 3 Autopsy Trial
  2. New Pathology Criteria Published: Alzheimer’s Without Dementia?
  3. Move Over, Flortaucipir? New Tau Tracers Tested in People
  4. Next-Generation Tau PET Tracers Strut Their Stuff
  5. At CTAD, Tau PET Emerges as Favored Outcome Biomarker for Trials

Paper Citations

  1. Hyman BT, Phelps CH, Beach TG, Bigio EH, Cairns NJ, Carrillo MC, Dickson DW, Duyckaerts C, Frosch MP, Masliah E, Mirra SS, Nelson PT, Schneider JA, Thal DR, Thies B, Trojanowski JQ, Vinters HV, Montine TJ. National Institute on Aging-Alzheimer's Association guidelines for the neuropathologic assessment of Alzheimer's disease. Alzheimers Dement. 2012 Jan;8(1):1-13. PubMed.
  2. Pascoal TA, Shin M, Kang MS, Chamoun M, Chartrand D, Mathotaarachchi S, Bennacef I, Therriault J, Ng KP, Hopewell R, Bouhachi R, Hsiao HH, Benedet AL, Soucy JP, Massarweh G, Gauthier S, Rosa-Neto P. In vivo quantification of neurofibrillary tangles with [18 F]MK-6240. Alzheimers Res Ther. 2018 Jul 31;10(1):74. PubMed.
  3. Murray ME, Graff-Radford NR, Ross OA, Petersen RC, Duara R, Dickson DW. Neuropathologically defined subtypes of Alzheimer's disease with distinct clinical characteristics: a retrospective study. Lancet Neurol. 2011 Sep;10(9):785-96. PubMed.
  4. Whitwell JL, Dickson DW, Murray ME, Weigand SD, Tosakulwong N, Senjem ML, Knopman DS, Boeve BF, Parisi JE, Petersen RC, Jack CR, Josephs KA. Neuroimaging correlates of pathologically defined subtypes of Alzheimer's disease: a case-control study. Lancet Neurol. 2012 Oct;11(10):868-77. PubMed.
  5. Ferreira D, Verhagen C, Hernández-Cabrera JA, Cavallin L, Guo CJ, Ekman U, Muehlboeck JS, Simmons A, Barroso J, Wahlund LO, Westman E. Distinct subtypes of Alzheimer's disease based on patterns of brain atrophy: longitudinal trajectories and clinical applications. Sci Rep. 2017 Apr 18;7:46263. PubMed.

External Citations

  1. study 
  2. Phase 3 EXPEDITION3
  3. Phase 2

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