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. 2020 Oct 1;143(10):3136-3150.
doi: 10.1093/brain/awaa248.

Predicting future rates of tau accumulation on PET

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Predicting future rates of tau accumulation on PET

Clifford R Jack et al. Brain. .

Abstract

Clinical trials with anti-tau drugs will need to target individuals at risk of accumulating tau. Our objective was to identify variables available in a research setting that predict future rates of tau PET accumulation separately among individuals who were either cognitively unimpaired or cognitively impaired. All 337 participants had: a baseline study visit with MRI, amyloid PET, and tau PET exams, at least one follow-up tau PET exam; and met clinical criteria for membership in one of two clinical diagnostic groups: cognitively unimpaired (n = 203); or cognitively impaired (n = 134, a combined group of participants with either mild cognitive impairment or dementia with Alzheimer's clinical syndrome). Our primary analyses were in these two clinical groups; however, we also evaluated subgroups dividing the unimpaired group by normal/abnormal amyloid PET and the impaired group by clinical phenotype (mild cognitive impairment, amnestic dementia, and non-amnestic dementia). Linear mixed effects models were used to estimate associations between age, sex, education, APOE genotype, amyloid and tau PET standardized uptake value ratio (SUVR), cognitive performance, cortical thickness, and white matter hyperintensity volume at baseline, and the rate of subsequent tau PET accumulation. Log-transformed tau PET SUVR was used as the response and rates were summarized as annual per cent change. A temporal lobe tau PET meta-region of interest was used. In the cognitively unimpaired group, only higher baseline amyloid PET was a significant independent predictor of higher tau accumulation rates (P < 0.001). Higher rates of tau accumulation were associated with faster rates of cognitive decline in the cognitively unimpaired subgroup with abnormal amyloid PET (P = 0.03), but among the subgroup with normal amyloid PET. In the cognitively impaired group, younger age (P = 0.02), higher baseline amyloid PET (P = 0.05), APOE ε4 (P = 0.05), and better cognitive performance (P = 0.05) were significant independent predictors of higher tau accumulation rates. Among impaired individuals, faster cognitive decline was associated with faster rates of tau accumulation (P = 0.01). While we examined many possible predictor variables, our results indicate that screening of unimpaired individuals for potential inclusion in anti-tau trials may be straightforward because the only independent predictor of high tau rates was amyloidosis. In cognitively impaired individuals, imaging and clinical variables consistent with early onset Alzheimer's disease phenotype were associated with higher rates of tau PET accumulation suggesting this may be a highly advantageous group in which to conduct proof-of-concept clinical trials that target tau-related mechanisms. The nature of the dementia phenotype (amnestic versus non-amnestic) did not affect this conclusion.

Keywords: Alzheimer’s disease; Alzheimer’s disease clinical trials; serial tau PET; tau; tau PET.

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Figures

Figure 1
Figure 1
Tau PET trajectories by age and primary clinical group. (A) Tau PET trajectories within each individual over age (time) coloured by cognitive status: cognitively unimpaired (CU) or cognitively impaired (CI). (B) Mean tau PET trajectory by age within each diagnosis group. Mean baseline tau PET SUVR and annual per cent change in tau PET were calculated within age groups of 50–65, 60–75, 70–85, and 80–95. Overlapping age groups were used to reduce noise and number of individuals in each age and cognitive group are shown at the bottom of the figure. Mean ± SD annual per cent change for each age and cognitive group are shown at the top. (C) Distribution of annual per cent change in tau PET by clinical diagnosis with mean ± SD annual per cent change for each cognitive group at the top. Box plots indicate median and interquartile range (IQR) of the distributions with whiskers extending from the quartiles to the farthest point within 1.5 times the IQR.
Figure 2
Figure 2
Multivariable associations with annual per cent change in tau PET among cognitively unimpaired and cognitively impaired. The estimated mean (95%) difference in annual per cent change in tau PET from a linear mixed effects model fit separately within each group is shown for specified differences in predictors. For cognition, the difference in annual per cent change in tau PET is shown for a 1.5 unit decrease in memory z-score among cognitively unimpaired individuals and for a 5-point decrease in the MoCA for cognitively impaired individuals.
Figure 3
Figure 3
Tau PET trajectories by age and clinical subgroups. The cognitively unimpaired (CU) individuals are split by normal/abnormal amyloid PET (A−/A+) and the cognitively impaired individuals are split by clinical syndrome: MCI, amnestic dementia, and non-amnestic dementia. (A) Tau PET trajectories within each individual over age (time) coloured by subgroup. (B) The distribution of annual per cent change in tau PET by subgroup with mean ± SD annual per cent change for each subgroup at the top. Box plots indicate median and IQR of the distributions with whiskers extending from the quartiles to the farthest point within 1.5 times the IQR.
Figure 4
Figure 4
Multivariable associations with annual per cent change in tau PET among cognitively unimpaired (CU) and cognitively impaired (CI) subgroups. The cognitively unimpaired individuals were split by normal/abnormal amyloid PET (A−/A+) and the cognitively impaired individuals were split by clinical syndrome: MCI, amnestic dementia, and non-amnestic dementia. The estimated mean (95%) difference in annual per cent change in tau PET from a linear mixed effects model fit separately within each group is shown for specified differences in predictors. For cognition, the difference in annual per cent change in tau PET is shown for a 1.5 unit decrease in memory z-score among cognitively unimpaired subgroups and for a 5-point decrease in the MoCA for cognitively impaired subgroups. Note that because of the wide confidence intervals in the cognitively unimpaired subgroups, the x-axis ranges for the cognitively unimpaired and cognitively impaired panels are different.
Figure 5
Figure 5
Scatter plots of annual change in cognition versus annual change in tau PET among cognitively unimpaired (CU) and cognitively impaired individuals. Points are coloured by normal/abnormal amyloid PET (A−/A+) within the cognitively unimpaired group and by clinical syndrome (MCI, amnestic dementia, and non-amnestic dementia) in the cognitively impaired group. Spearman correlation coefficients and P-values are shown at the top of each plot. Memory z-score was used for the cognition measure in the cognitively impaired group and the MoCA was used in the cognitively impaired group.

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