Citations

AbstractBackgroundAlzheimer’s disease (AD) is marked by selective disruptions to anatomically‐distinct brain regions and their connectivity which collectively support cognition. Based on a variation of pattern‐recognition analysis of FDG‐PET images, we previously developed a framework, the global functional state space (GFSS), which captures this macroscale architecture by assigning each individual a series of weightings on 10 independent patterns (eigenbrains=EBs). In this study, we applied the GFSS as a quantitative endophenotype to test whether known AD genetic risk factors were associated with variability in large‐scale neurodynamics represented by the GFSS.MethodThe study sample included 410 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) with evidence of cognitive impairment (CDR‐global>0) and amyloidosis (positive amyloid‐PET). The GFSS was estimated for each individual using the set of 10 EBs to describe global patterns of variation in glucose metabolism. AD genetic risk variants identified in prior large consortium case‐control studies were included for analysis if the variant (or a proxy by linkage disequilibrium r 2>0.7) was assayed on both genotyping platforms used in the sample and if the minor allele frequency exceeded 1%. Genetic associations with the collective set of EBs were tested using multivariate linear regression under a dominant genetic model.ResultSignificant multivariate associations were identified for CD33 (p=7.04x10‐4), MEF2C (p=0.001), and SORL1 (p=0.02). These findings remained significant after covarying for age and sex. The strongest component loadings for CD33 (p=9.09x10‐4; std. β=‐0.16) and MEF2C (p=1.59x10‐4; std. β=‐0.18) were for EB1, with the minor allele in each case associated with a negative axis deviation in the direction of the GFSS area representing episodic memory dysfunction. SORL1 displayed its strongest loading onto EB4 (p=0.03, std. β=‐0.11). The association of APOE ɛ4 with the GFSS was marginally nonsignificant (p=0.09).ConclusionWe identified associations of risk variants in CD33, MEF2C, and SORL1 with differences in patterns of FDG hypometabolism in persons with symptomatic AD. These findings establish the GFSS as a useful endophenotype for genetic analyses, particularly as an avenue toward a mechanistic understanding of how heritable factors may influence inter‐individual variability and syndromic diversity in AD. Further investigation in larger and independent cohorts is warranted.

AbstractBackgroundThe Network Failure Quotient (NFQ) metric summarizes functional MRI network integrity. We wanted to investigate the stability of the NFQ results across time, hardware, software and protocol changes during the last decade in ADNI Resting State (RS‐) fMRI.MethodIn ADNI‐2 (2009‐2016) RS‐fMRI was acquired on Philips scanners. In ADNI‐3 (2017‐present) RS‐fMRI is acquired on GE, Philips, and Siemens systems with “Basic” and “Advanced” variants based on the availability of simultaneous multi‐slice (SMS, multi‐band) imaging. (Table 1.) Resting state images were preprocessed by performing slice timing correction, trimming volumes from the first 10 seconds of acquired data, despiking and within‐series alignment. Simultaneous bandpass and regression was performed using spatial registration parameters and their first temporal derivatives, mean WM signal, mean CSF signal and global signal. Dual regression via GIFT was applied creating regional time courses. The NFQ is calculated as NFQ=(pDMN_to_vDMN + pDMN_to_adDMN) / (pDMN +vDMN) where pDMN_to_vDMN and pDMN_to_adDMN are correlations between time courses in the posterior DMN, ventral DMN and anterior‐dorsal DMN. pDMN and vDMN are the within‐region correlations. NFQ values from 1447 scans of 739 individual study participants (Table 1) were analyzed using linear mixed effects models to account for age, clinical diagnosis, vendor, and time trends.ResultBox plots of NFQ values by diagnosis within ADNI‐phase and protocol are shown in Figure 2 and suggest important differences among clinical diagnoses and between ADNI‐2 and ADNI‐3. The mixed model analysis indicates that a 10‐year increase in age is associated with a 0.05±0.01 (mean±SD) increase in NFQ; individuals with MCI average roughly 0.05±0.01 higher than unimpaired and individuals with dementia average 0.14±0.02 higher. Differences by vendor for ADNI‐2 and ADNI‐3 are summarized in Figures 2 and 3 with effect sizes on par with these clinical factors. Mean NFQ for Phillips ADNI‐2 were highest (0.54±0.02); somewhat lower were Philips ADNI‐3 (0.51±0.02) and Siemens ADNI‐3 advanced (0.49±0.03); Siemens ADNI‐3 basic (0.40±0.02) and GE ADNI‐3 were the lowest (0.38±0.02).ConclusionNFQ values consistently increase with impairment. Vendor‐specific differences are observed and vendor changes over the life of a study introduce variability on the scale of disease‐related changes in NFQ.

AbstractBackgroundIt is important to determine the natural history of sporadic and familial frontotemporal lobar degeneration (FTLD) and generate clinical, neuropsychological, neuroimaging and biofluid data for planning disease‐modifying trials.MethodAs part of the ARTFL LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD; U19 AG063911) protocol, investigators at 19 centers in North America will enroll 2100 participants with FTLD over the next 5 years beginning in early 2020.ResultAs of 1/20/20, the ARTFL/LEFFTDS (A/L) Consortium had enrolled 1832 participants, including 850 in kindreds with familial FTLD (239 associated with mutations in MAPT, 192 in GRN, 370 in C9orf72, 4 with mutations in both GRN and C9orf72, and 45 with a mutation in a different gene or no mutation in any known FTLD‐associated gene). Over 500 participants have undergone 2 or more annual visits to date. MRI has been performed in 1105. Biofluid samples have also been collected, with blood (DNA, plasma, serum, mRNA, PBMC) in 1413 and CSF in 303. Over 60 manuscripts using A/L data or samples have been published to date. Five clinical trials involving A/L and ALLFTD participants are in progress or planned. The longitudinal arm in ALLFTD will enroll 500 of existing A/L and 600 future participants for annual assessments with similar methodology to A/L. An additional 1000 FTLD patients will undergo focused one‐time clinical evaluations and biofluid collection.ConclusionThe data/samples from already‐enrolled and planned participants in ALLFTD and findings published to date underscore the utility of evaluating FTLD subjects. The absence of identifiable mutations in some with familial FTLD suggests that other genes are yet to be discovered. ALLFTD data will inform clinical trial design, and many participants will be eligible for future trials. The key data and samples in ALLFTD are available to interested investigators worldwide. Supported by: AG063911, AG045390, NS092089, AG016976, AG21886.

AbstractBackgroundWe report a group of individuals presenting with a progressive dementia syndrome characterized by predominant dysfunction in core executive functions and positive biomarkers for Alzheimer’s pathophysiology.MethodIn this retrospective review, we report on 55 participants with a clinically defined progressive dysexecutive syndrome with 18F‐fluorodeoxyglucose‐positron emission tomography (FDG) and AD biomarker positivity. A subset of these individuals enrolled in our ADRC were compared to other phenotypic variants of AD.ResultSixty‐two percent were female with a mean of 15.2 years of education. Mean age of symptom onset was 53.8 while mean age at diagnosis was 57.2 years. Multi‐domain cognitive impairment was evident in neuropsychological testing with executive dysfunction most consistently and severely affected. The frontal and/or parietal regions demonstrate clear hypometabolism on positron emission tomography in all cases. Genetic testing for autosomal dominant genes was negative in all 8 participants tested and at least one APOE ε4 allele was present in 14/26. EEG was abnormal in 14/17 cases. CSF and neuroimaging biomarkers (PIB‐PET and Tau‐PET) were consistent with Alzheimer’s disease pathophysiology, although CSF p‐tau was normal in 24% of cases. In two participants that came to autopsy, the hippocampus was relatively spared compared to frontal and parietal cortex. Participants presenting with a progressive dysexecutive syndrome and evidence of AD pathology are labeled dAD. Comparing FDG in dAD relative to other AD phenotypes revealed unique areas of relatively greater hypometabolism in parieto‐frontal cortex and relative sparing of medial temporal (vs typical AD), visual (vs PCA), and left temporal (vs lvPPA) (Figure 1). Controlling for age did not alter patterns of regional differences. This demonstrates regional variability related to clinical phenotype not accountable by variation in age, duration, stage, or severity (Figure 2).ConclusionA progressive dysexecutive syndrome should be recognized as a distinct clinical phenotype. This clinical presentation can be due to Alzheimer’s disease but is not specific for any single etiology (non‐AD cases of progressive dysexecutive syndrome will be discussed). Prominent impairment of executive task performance, young‐age of onset, normal CSF p‐tau, and relative preservation of the hippocampus were commonly encountered in this case series of dAD.

AbstractThe mechanisms through which tau and amyloid-beta (Aβ) accumulate in the brain of Alzheimer’s disease patients may differ but both are related to neuronal networks. We examined such mechanisms on neuroimaging in 58 participants with atypical Alzheimer’s disease (posterior cortical atrophy or logopenic progressive aphasia). Participants underwent Aβ-PET, longitudinal tau-PET, structural MRI and resting-state functional MRI, which was analyzed with graph theory. Regions with high levels of Aβ were more likely to be functional hubs, with a high number of functional connections important for resilience to cascading network failures. Regions with high levels of tau were more likely to have low clustering coefficients and degrees, suggesting a lack of trophic support or vulnerability to local network failures. Regions strongly functionally connected to the disease epicenters were more likely to have higher levels of tau and, less strongly, of Aβ. The regional rate of tau accumulation was associated with tau levels in functionally connected regions, in support of tau accumulation in a functional network. This study elucidates the relations of tau and Aβ to functional connectivity metrics in atypical Alzheimer’s disease, strengthening the hypothesis that the spread of the 2 proteins is driven by different biological mechanisms related to functional networks.

ObjectiveTo examine associations between tau and amyloid β (Aβ) molecular positron emission tomography (PET) and both Alzheimer‐related pathology and 4‐repeat tau pathology in autopsy‐confirmed frontotemporal lobar degeneration (FTLD).MethodsTwenty‐four patients had [18F]‐flortaucipir–PET and died with FTLD (progressive supranuclear palsy [PSP], n = 10; corticobasal degeneration [CBD], n = 10; FTLD‐TDP, n = 3; and Pick disease, n = 1). All but 1 had Pittsburgh compound B (PiB)‐PET. Braak staging, Aβ plaque and neurofibrillary tangle counts, and semiquantitative tau lesion scores were performed. Flortaucipir standard uptake value ratios (SUVRs) were calculated in a temporal meta region of interest (meta‐ROI), entorhinal cortex and cortical/subcortical regions selected to match the tau lesion analysis. Global PiB SUVR was calculated. Autoradiography was performed in 1 PSP patient, with digital pathology used to quantify tau burden.ResultsNine cases (37.5%) had Aβ plaques. Global PiB SUVR correlated with Aβ plaque count, with 100% specificity and 50% sensitivity for diffuse plaques. Twenty‐one (87.5%) had Braak stages I to IV. Flortaucipir correlated with neurofibrillary tangle counts in entorhinal cortex, but entorhinal and meta‐ROI SUVRs were not elevated in Braak IV or primary age‐related tauopathy. Flortaucipir uptake patterns differed across FTLD pathologies and could separate PSP and CBD. Flortaucipir correlated with tau lesion score in red nucleus and midbrain tegmentum across patients, but not in cortical or basal ganglia regions. Autoradiography demonstrated minimal uptake of flortaucipir, although flortaucipir correlated with quantitative tau burden across regions.InterpretationMolecular PET shows expected correlations with Alzheimer‐related pathology but lacks sensitivity to detect mild Alzheimer pathology in FTLD. Regional flortaucipir uptake was able to separate CBD and PSP. ANN NEUROL 2020;88:1009–1022

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.