Predicting future rates of tau accumulation on PET

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.

Differential associations of APOE-ε2 and APOE-ε4 alleles with PET-measured amyloid-β and tau deposition in older individuals without dementia

“…On the other hand, a previous longitudinal tau PET study did not find any significant APOE-ε4 effect on regional tau accumulation rates in CU individuals from the Berkeley aging cohort, although this negative finding could be related to the relatively low number of ε4 carriers in that study [64]. Finally, a recent longitudinal tau PET study found no APOE-ε4 effect on tau accumulation rates among CU individuals after controlling for baseline Aβ load [65]. However, the study reported a marginally significant independent APOE-ε4 effect on higher tau accumulation rates in a group of cognitively impaired individuals, but the interpretation of this finding is complicated by the mixed clinical composition of this group that included patients with MCI as well as typical and atypical AD dementia phenotypes.…”

Glucose metabolism reflects local atrophy and tau pathology in symptomatic Alzheimer’s disease

“…We did not find an effect of local amyloid-PET on FDG-PET, which is consistent with other cohorts of amyloid-positive individuals. 5,[31][32][33][34][35] Given that the degree of amyloid pathology reaches a plateau soon after symptom onset 76 in contrast with the increasing levels of tau pathology, 77,78 it is likely that any direct influence from amyloid plaque pathology may be difficult to detect given the neurotoxicity of tau pathology at this symptomatic stage.…”

How Can Hearing Loss Cause Dementia?

“…The AD pathology that best correlates with the cognitive phenotype is neurofibrillary change related to tau pathology (Jack et al, 2019;Morris and Price, 2001;Pereira et al, 2019). The earliest neurofibrillary changes in typical AD are found in MTL structures, particularly the perirhinal cortex, which has a strong functional relationship to the hippocampus (Braak and Braak, 1991;Khan et al, 2014).…”

“…Finally, hearing loss may also affect the mechanisms for auditory grouping and segregation in the posterior neocortex and predispose to another AD variant: posterior cortical atrophy (Firth et al, 2019). Increasingly, clinical work has used biomarkers of AD pathology in cerebrospinal fluid (Jack and Holtzman, 2013) and brain imaging of biomarkers (Jack et al, 2019;Morris et al, 2016;Pereira et al, 2019) to provide estimates of the extent and distribution of disease. In research studies of incident dementia related to hearing loss, amyloid and tau imaging in particular could allow the assessment of regional AD pathology related to possible models for the interaction between hearing loss and dementia pathology.…”