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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. 2022 Feb 1;79(2):149-158. PubMed.
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Washington University
This paper shows an analysis of longitudinal tau PET with the 18F-RO948 tracer, which may have less off-target binding than flortaucipir. These data show clear progression of tau PET pathology that is largely consistent with neuropathologically established Braak stages. In the normal group (amyloid-negative/cognitively unimpaired), tau PET SUVR only increased in the early regions described in this paper as being in EBM stage 1 (entorhinal cortex, hippocampus, and amygdala), which could represent either primary age-related tauopathy or very early AD. In the preclinical AD group (amyloid-positive/cognitively unimpaired), tau PET SUVR increased more rapidly in these same early regions, but tau PET SUVR also started to increase in areas all over the brain, including cortical regions. By the time individuals developed symptomatic AD (MCI or AD dementia), tau PET signal was increasing robustly throughout the brain. This data is consistent with previous reports that tau PET starts to robustly increase shortly before symptom onset.
Notably, the rates of increasing tau PET SUVR seemed to plateau at about 4 to 5 percent per year, and this plateau is reached in different regions at different stages of disease. In the preclinical AD group (amyloid-positive/cognitively unimpaired), the rate of increase in tau PET SUVR in the early regions (EBM stage 1) seemed to have already plateaued at 4 percent per year and remained at this level in the MCI and AD dementia groups. For the EBM 2 regions, the rate of increase in tau PET SUVR seemed to plateau in MCI. In contrast, the later EBM 4 and 5 regions did not reach this plateau until AD dementia. The rate of change in the later EBM 4 and 5 regions could potentially be used as a measure of disease stage from normal to AD dementia, as it appears to increase throughout the disease course. In contrast, the rate of change in the earlier regions may only be informative in distinguishing normal, preclinical AD and MCI.
The authors selected the preclinical AD and MCI groups, which would be expected to have the largest variance in tau PET SUVR rate of change, to evaluate the association of tau PET SUVR rate of change with other biomarkers, including plasma p-tau217. Plasma p-tau217 was moderately correlated with change in tau PET SUVR. It is important that a single blood test (baseline p-tau217) provided similar information to longitudinal tau PET, which is much more burdensome and expensive.
It was also interesting that baseline tau PET SUVR predicted the rate of change in tau PET SUVR, at least during preclinical AD (R2=0.13) and MCI (R2=0.33). Notably, baseline amyloid PET SUVR is correlated with change in amyloid PET SUVR during the preclinical phase of AD, but this correlation fades around the time of symptom onset. It is possible that tau PET has a similar pattern, but beginning in the transition from preclinical to symptomatic AD. It would be interesting to apply analytical approaches developed with longitudinal amyloid PET (e.g. Villemagne et al., 2013; Jack et al., 2013; Koscik et al., 2020; Schindler et al., 2021) to better understand change in tau PET. It is possible that the tau PET clock starts ticking about the time when the amyloid PET clock stops.
References:
Villemagne VL, Burnham S, Bourgeat P, Brown B, Ellis KA, Salvado O, Szoeke C, Macaulay SL, Martins R, Maruff P, Ames D, Rowe CC, Masters CL, Australian Imaging Biomarkers and Lifestyle (AIBL) Research Group. Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study. Lancet Neurol. 2013 Apr;12(4):357-67. Epub 2013 Mar 8 PubMed.
Jack CR, Wiste HJ, Lesnick TG, Weigand SD, Knopman DS, Vemuri P, Pankratz VS, Senjem ML, Gunter JL, Mielke MM, Lowe VJ, Boeve BF, Petersen RC. Brain β-amyloid load approaches a plateau. Neurology. 2013 Mar 5;80(10):890-6. PubMed.
Koscik RL, Betthauser TJ, Jonaitis EM, Allison SL, Clark LR, Hermann BP, Cody KA, Engle JW, Barnhart TE, Stone CK, Chin NA, Carlsson CM, Asthana S, Christian BT, Johnson SC. Amyloid duration is associated with preclinical cognitive decline and tau PET. Alzheimers Dement (Amst). 2020;12(1):e12007. Epub 2020 Feb 13 PubMed.
Schindler SE, Li Y, Buckles VD, Gordon BA, Benzinger TL, Wang G, Coble D, Klunk WE, Fagan AM, Holtzman DM, Bateman RJ, Morris JC, Xiong C. Predicting Symptom Onset in Sporadic Alzheimer Disease With Amyloid PET. Neurology. 2021 Nov 2;97(18):e1823-e1834. Epub 2021 Sep 9 PubMed.
View all comments by Suzanne SchindlerWashington University
This is nice work and is generally supportive of what we know about these biomarkers: At the asymptomatic stage, fluid biomarkers of p-tau are the most dynamic and therefore had the strongest association with early regional tau PET change in the temporal lobes. At later stages, baseline tau PET had the strongest association with subsequent tau PET change.
In general, for a screening procedure, these results suggest that starting with plasma pT217 (using the Eli Lilly-developed Meso Scale Discovery platform-based assay) could be an efficient method to determine individuals with a higher probability of having tau PET changes. But also that this is very much dependent on the population being enriched for abnormal Aβ-biomarkers (supplemental table e14).
Ultimately, it will very likely be the presence of tau PET retention outside of the entorhinal cortex plus the presence of Aβ-plaques that will determine the likelihood of tau PET progression, and this study further emphasizes the use of pT217 as a strong marker of Aβ-pathology dependent effects on neuronal dysfunction. A major limitation to this study is the lack of inclusion of cognitive performance as a predictor of longitudinal tau PET in the univariate and multivariate models.
An interesting finding is the lack of clear association of most “neurodegenerative” biomarkers (e.g., plasma NfL, MRI measures of atrophy) with longitudinal tau PET. This is somewhat in contrast to another study from this population (Ossenkoppele et al., 2021). Some of this is likely related to the individual characteristics of these measures such as variance. Even so, this lack of association continues to raise questions as to the interchangeability of biomarkers in the A/T/N classification system, and causes some pause as to what we should expect in clinical trials that have tau PET as a key outcome.
It would be more reassuring to see markers of neurodegeneration correlate with changes of tau PET in order to increase the probability that a drug specifically targeting aggregated tau will result in a clinical benefit.
References:
Ossenkoppele R, Reimand J, Smith R, Leuzy A, Strandberg O, Palmqvist S, Stomrud E, Zetterberg H, Alzheimer's Disease Neuroimaging Initiative, Scheltens P, Dage JL, Bouwman F, Blennow K, Mattsson-Carlgren N, Janelidze S, Hansson O. Tau PET correlates with different Alzheimer's disease-related features compared to CSF and plasma p-tau biomarkers. EMBO Mol Med. 2021 Aug 9;13(8):e14398. Epub 2021 Jul 13 PubMed.
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