Citations

Abstract Alzheimer’s disease is characterized by the presence of amyloid-β and tau deposition in the brain, hippocampal atrophy and increased rates of hippocampal atrophy over time. Another protein, TAR DNA binding protein 43 (TDP-43) has been identified in up to 75% of cases of Alzheimer’s disease. TDP-43, tau and amyloid-β have all been linked to hippocampal atrophy. TDP-43 and tau have also been linked to hippocampal atrophy in cases of primary age-related tauopathy, a pathological entity with features that strongly overlap with those of Alzheimer’s disease. At present, it is unclear whether and how TDP-43 and tau are associated with early or late hippocampal atrophy in Alzheimer’s disease and primary age-related tauopathy, whether either protein is also associated with faster rates of atrophy of other brain regions and whether there is evidence for protein-associated acceleration/deceleration of atrophy rates. We therefore aimed to model how these proteins, particularly TDP-43, influence non-linear trajectories of hippocampal and neocortical atrophy in Alzheimer’s disease and primary age-related tauopathy. In this longitudinal retrospective study, 557 autopsied cases with Alzheimer’s disease neuropathological changes with 1638 ante-mortem volumetric head MRI scans spanning 1.0–16.8 years of disease duration prior to death were analysed. TDP-43 and Braak neurofibrillary tangle pathological staging schemes were constructed, and hippocampal and neocortical (inferior temporal and middle frontal) brain volumes determined using longitudinal FreeSurfer. Bayesian bivariate-outcome hierarchical models were utilized to estimate associations between proteins and volume, early rate of atrophy and acceleration in atrophy rates across brain regions. High TDP-43 stage was associated with smaller cross-sectional brain volumes, faster rates of brain atrophy and acceleration of atrophy rates, more than a decade prior to death, with deceleration occurring closer to death. Stronger associations were observed with hippocampus compared to temporal and frontal neocortex. Conversely, low TDP-43 stage was associated with slower early rates but later acceleration. This later acceleration was associated with high Braak neurofibrillary tangle stage. Somewhat similar, but less striking, findings were observed between TDP-43 and neocortical rates. Braak stage appeared to have stronger associations with neocortex compared to TDP-43. The association between TDP-43 and brain atrophy occurred slightly later in time (∼3 years) in cases of primary age-related tauopathy compared to Alzheimer’s disease. The results suggest that TDP-43 and tau have different contributions to acceleration and deceleration of brain atrophy rates over time in both Alzheimer’s disease and primary age-related tauopathy.

Purpose Individuals with primary progressive apraxia of speech (AOS) have AOS in which disruptions in articulation and prosody predominate the speech pattern. Many develop aphasia and/or dysarthria later in the disease course. The aim of this study was to describe the communication limitations in these patients, as measured by (a) the patient via the Communicative Participation Item Bank (CPIB) and (b) the speech-language pathologist via the American Speech-Language-Hearing Association's (ASHA) Functional Communication Measures (FCMs) and an adapted motor speech disorder (MSD) severity rating. Method Speech and language evaluations were completed for 24 patients with progressive AOS ( n = 7 with isolated AOS; n = 17 with a combination of AOS and aphasia). Descriptive comparisons were utilized to evaluate differences in communication measures among patients with various combinations of MSDs and aphasia. Differences associated with phonetic predominant or prosodic predominant AOS were also examined. Across the entire cohort, correlations were calculated between the participation ratings and other clinical assessment measures. Results The CPIB reflected greater limitations for those with aphasia and AOS compared to isolated AOS, but was not notably different when dysarthria occurred with AOS ( n = 9/24). Across the cohort, there were statistically significant correlations between the CPIB and ASHA FCM–Motor Speech and Language Expression ratings and the MSD severity rating. The CPIB did not correlate with the ASHA FCM–Language Comprehension or other speech-language measures. Conclusions Patients with neurodegenerative AOS experience reduced participation in communication that is further exacerbated by co-occurring language deficits. The study suggests measures of severity cannot be assumed to correlate with measures of participation restrictions and offers a foundation for further research examining the day-to-day sequela of progressive speech and language disorders. Supplemental Material https://doi.org/10.23641/asha.12743252

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.

Abstract Alzheimer’s disease can present clinically with either the typical amnestic phenotype or with atypical phenotypes, such as logopenic progressive aphasia and posterior cortical atrophy. We have recently described longitudinal patterns of flortaucipir PET uptake and grey matter atrophy in the atypical phenotypes, demonstrating a longitudinal regional disconnect between flortaucipir accumulation and brain atrophy. However, it is unclear how these longitudinal patterns differ from typical Alzheimer’s disease, to what degree flortaucipir and atrophy mirror clinical phenotype in Alzheimer’s disease, and whether optimal longitudinal neuroimaging biomarkers would also differ across phenotypes. We aimed to address these unknowns using a cohort of 57 participants diagnosed with Alzheimer’s disease (18 with typical amnestic Alzheimer’s disease, 17 with posterior cortical atrophy and 22 with logopenic progressive aphasia) that had undergone baseline and 1-year follow-up MRI and flortaucipir PET. Typical Alzheimer’s disease participants were selected to be over 65 years old at baseline scan, while no age criterion was used for atypical Alzheimer’s disease participants. Region and voxel-level rates of tau accumulation and atrophy were assessed relative to 49 cognitively unimpaired individuals and among phenotypes. Principal component analysis was implemented to describe variability in baseline tau uptake and rates of accumulation and baseline grey matter volumes and rates of atrophy across phenotypes. The capability of the principal components to discriminate between phenotypes was assessed with logistic regression. The topography of longitudinal tau accumulation and atrophy differed across phenotypes, with key regions of tau accumulation in the frontal and temporal lobes for all phenotypes and key regions of atrophy in the occipitotemporal regions for posterior cortical atrophy, left temporal lobe for logopenic progressive aphasia and medial and lateral temporal lobe for typical Alzheimer’s disease. Principal component analysis identified patterns of variation in baseline and longitudinal measures of tau uptake and volume that were significantly different across phenotypes. Baseline tau uptake mapped better onto clinical phenotype than longitudinal tau and MRI measures. Our study suggests that optimal longitudinal neuroimaging biomarkers for future clinical treatment trials in Alzheimer’s disease are different for MRI and tau-PET and may differ across phenotypes, particularly for MRI. Baseline tau tracer retention showed the highest fidelity to clinical phenotype, supporting the important causal role of tau as a driver of clinical dysfunction in Alzheimer’s disease.

AbstractObjectiveTo assess the relationships between MRI volumetry and [18F]flortaucipir PET of typical and atypical clinical phenotypes of Alzheimer’s disease, by genarian (age by decade).MethodsFive‐hundred and sixty‐four participants including those with typical (n = 86) or atypical (n = 80) Alzheimer’s dementia and normal controls (n = 398) underwent apolipoprotein E genotyping, MRI, flortaucipir, and 11C‐PiB; all 166 Alzheimer’s participants were beta‐amyloid positive and all controls were beta‐amyloid negative. Grey matter volume and flortaucipir standard uptake value ratios were calculated for hippocampus, entorhinal cortex, and neocortex. Ratios of hippocampal‐to‐neocortical and entorhinal‐to‐neocortical volume and flortaucipir uptake were also calculated. Linear regression models assessed relationships among regional volume, flortaucipir uptake, and ratios and phenotypes, within three genarians (50–59, 60–69, and 70+). Voxel‐level analyses were also performed.ResultsFor 50–59 greater medial temporal atrophy and flortaucipir uptake was observed in the typical compared with atypical phenotype. The typical phenotype also showed greater frontal neocortex uptake with the voxel‐level analysis. For 60–69 and 70+ there was greater hippocampal volume loss in the typical compared with atypical phenotype while only the 60–69, but not the 70+ group, showed a difference in hippocampal flortaucipir uptake. We also observed a pattern for higher neocortical flortaucipir uptake to correlate with younger age decade for both phenotypes.InterpretationMRI volumetry versus flortaucipir PET relationships differ across Alzheimer’s clinical phenotypes, and also within phenotype across age decades. This suggests that there is potential risk of masked effects by not accounting for genarian in participants with beta‐amyloid and tau‐positive biomarker defined Alzheimer’s disease.

Background: Transactive response DNA-binding protein of 43 kDa (TDP-43) is associated with hippocampal atrophy in Alzheimer’s disease (AD), but whether the association is modified by other factors is unknown. Objective: To evaluate whether the associations between TDP-43 and hippocampal volume and atrophy rate are affected by age, gender, apolipoprotein E ( APOE) ɛ4, Lewy bodies (LBs), amyloid-β (Aβ), or Braak neurofibrillary tangle (NFT) stage. Methods: In this longitudinal neuroimaging-clinicopathological study of 468 cases with AD neuropathological changes (Aβ-positive) that had completed antemortem head MRI, we investigated how age, gender, APOE ɛ4, presence of LBs, Aβ, TDP-43, and Braak NFT stages are associated with hippocampal volumes and rates of atrophy over time. We included field strength in the models since our cohort included 1.5T and 3T scans. We then determined whether the associations between hippocampal atrophy and TDP-43 are modified by these factors using mixed effects models. Results: Older age, female gender, APOE ɛ4, higher field strength, higher TDP-43, and Braak NFT stages were associated with smaller hippocampi. Rate of atrophy was greater with higher TDP-43 and Braak NFT stage, but lower in older patients. The association of TDP-43 with greater rate of atrophy was enhanced in APOE ɛ4 carriers ( p = 0.04). Conclusion: Neurodegenerative effects of TDP-43 seem to be independent of most factors except perhaps APOE in cases with AD neuropathological changes. TDP-43 and tau appear to behave independently of one another.