The sequential tangling up of the tau protein in different regions of the brain is part and parcel of Alzheimer’s disease progression. Being able to predict if, where, and to what extent tangles will accumulate in a given person is a crucial component of clinical drug trials that aim to derail this process. And the field is getting there. According to a paper published December 20 in JAMA Neurology, the first serial tau PET scans using the 18F-RO948 tracer detected early increases in the medial temporal lobe in people with preclinical AD, followed later by rises in the outer neocortex as clinical symptoms first emerged and then worsened. For people in the preclinical stage of the disease, however, plasma p-tau217 beat PET at predicting neurofibrillary tangles that still lay some time in their future.
- Plasma p-tau217 best predicted subsequent tau-tangle accumulation in people with preclinical AD.
- Tau PET worked better in those with symptoms.
- Screening using plasma and imaging biomarkers could cut size of clinical trials significantly.
For its part, tau PET itself had slightly greater predictive power in people who had already developed symptoms. The two measures together posted the strongest prognostic value, regardless of what disease stage a person was at, at the time of measurement. Ultimately, the researchers found, using plasma and/or imaging biomarkers could halve the needed size of trials aimed at taking down tangles.
As clinical trials increasingly include people in the preclinical or prodromal stages of AD, effective use of biomarkers—both for selecting participants and for gauging their response to therapy—can mean the difference between success or failure. Tau accumulation tracks closely with disease progression, and is an ideal biomarker for these purposes. Some trials are already employing tau PET or plasma tau biomarkers to select participants (Nov 2021 news). But researchers need more data to understand in detail which measure of tau is the most sensitive readout of pathology in the brain at each stage of this long disease, and which is the best at predicting future accumulation of tau.
First author Antoine Leuzy and colleagues addressed these questions in their study, which tracked tau accumulation in 343 participants in BioFINDER 2. This Swedish study is the first to take longitudinal tau PET measurements with the 18F-RO948 tracer, which reportedly has less off-target binding than do first-generation tracers, such as flortaucipir. Tau PET was serially measured in 107 people with Aβ accumulation, of whom 49 were cognitively normal and 58 had MCI; in 173 people without Aβ accumulation, including 137 who were unimpaired and 36 with MCI; and in 63 people with AD dementia. Participants received two tau PET scans, spaced an average of 20 months apart.
The researchers used a computational method called event-based modeling (EBM) to derive five stages of tau progression. For example, stage I comprised the entorhinal cortex, hippocampus, and amygdala, while stage II encompassed the temporal cortical regions (see image below). For people who started the study in the preclinical stage of AD—i.e., cognitively normal people with Aβ accumulation—tau tangles increased primarily in the stage I regions between their two scans. For people with Aβ accumulation and MCI, tangle increases predominated in stage II areas. For those with AD dementia at the beginning of the study, the greatest changes were seen in stage IV, which included frontal regions.
Path of Progression. Medial (top) and lateral views (bottom) show that in stage I, tau accumulates in the medial temporal lobe (red), moving into the temporal cortex by stage II and into outer neocortical regions in subsequent stages. [Courtesy of Leuzy et al., JAMA Neurology, 2021.]
For the most part, the EBM stages aligned roughly with Braak stages of tau-tangle progression, by which tau accumulates early in the medial temporal lobe before spreading out into neocortical regions as symptoms emerge. The scientists therefore observed similar trends in the rate of tau progression when using regions defined by Braak stages instead of EBM.
For Aβ-negative people, regardless of cognitive status, small increases in tau accumulation occurred in the medial temporal lobe, consistent with primary age-related tauopathy as had been reported by others (Nov 2014 news).
With these tau trajectories in hand, the researchers next asked which baseline biomarkers correlated best with subsequent progression of tangle pathology. They limited these analyses to people with Aβ accumulation. In cognitively normal people with amyloid, plasma p-tau217 correlated strongly with subsequent accumulation of tau in stage I regions. Their baseline tau and amyloid-PET scans correlated less well. In contrast, for people with MCI, baseline tau PET SUVR in stage II regions more strongly predicted subsequent tangle accumulation in those regions than did plasma p-tau217, although both were significantly associated with subsequent change. The researchers reached similar conclusions when they used plasma p-tau181 instead of p-tau217, or CSF instead of plasma. Results were similar in a separate cohort of patients in whom flortaucipir served as the tau tracer instead of 18F-RO948.
Overall, the findings support the idea that baseline biomarkers of tau accumulation could help trialists select participants who are likely to accumulate tau over the duration of the trial. By how much would these markers cut the number of participants needed to see a treatment effect on tangle progression? The researchers found that, for preclinical AD, combining plasma p-tau217 and tau PET would reduce this number by 43 percent and, for MCI, by 68 percent. Comparing individual biomarkers for each study population, the authors report that plasma p-tau217 alone would reduce the sample size in a preclinical AD trial by 31 percent, compared to 22 percent if tau PET was used. For an MCI trial, tau PET outperformed plasma p-tau217 at whittling down the numbers—dropping its size by 47 compared to 28 percent.—Jessica Shugart
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- Leuzy A, Smith R, Cullen NC, Strandberg O, Vogel JW, Binette AP, Borroni E, Janelidze S, Ohlsson T, Jögi J, Ossenkoppele R, Palmqvist S, Mattsson-Carlgren N, Klein G, Stomrud E, Hansson O. Biomarker-Based Prediction of Longitudinal Tau Positron Emission Tomography in Alzheimer Disease. JAMA Neurol. 2021 Dec 20; PubMed.