Daniel Schonhaut

PET Imaging of Tau Deposition in the Aging Human Brain

Tau pathology is a hallmark of Alzheimers disease (AD) but also occurs in normal cognitive aging. Using the tau PET agent (18)F-AV-1451, we examined retention patterns in cognitively normal older people in relation to young controls and AD patients. Age and β-amyloid (measured using PiB PET) were differentially associated with tau tracer retention in healthy aging. Older age was related to increased tracer retention in regions of the medial temporal lobe, which predicted worse episodic memory performance. PET detection of tau in other isocortical regions required the presence of cortical β-amyloid and was associated with decline in global cognition. Furthermore, patterns of tracer retention corresponded well with Braak staging of neurofibrillary tau pathology. The present study defined patterns of tau tracer retention in normal aging in relation to age, cognition, and β-amyloid deposition.

Tau, amyloid, and hypometabolism in a patient with posterior cortical atrophy.

Determining the relative contribution of amyloid plaques and neurofibrillary tangles to brain dysfunction in Alzheimer disease is critical for therapeutic approaches, but until recently could only be assessed at autopsy. We report a patient with posterior cortical atrophy (visual variant of Alzheimer disease) who was studied using the novel tau tracer [18F]AV‐1451 in conjunction with [11C]Pittsburgh compound B (PIB; amyloid) and [18F]fluorodeoxyglucose (FDG) positron emission tomography. Whereas [11C]PIB bound throughout association neocortex, [18F]AV‐1451 was selectively retained in posterior brain regions that were affected clinically and showed markedly reduced [18F]FDG uptake. This provides preliminary in vivo evidence that tau is more closely linked to hypometabolism and symptomatology than amyloid. Ann Neurol 2014.

Reference tissue-based kinetic evaluation of 18F-AV-1451 in aging and dementia

The goal of this paper was to evaluate the in vivo kinetics of the novel tau-specific PET radioligand 18F-AV-1451 in cognitively healthy control (HC) and Alzheimer disease (AD) subjects, using reference region analyses. Methods: 18F-AV-1451 PET imaging was performed on 43 subjects (5 young HCs, 23 older HCs, and 15 AD subjects). Data were collected from 0 to 150 min after injection, with a break from 100 to 120 min. T1-weighted MR images were segmented using FreeSurfer to create 14 bilateral regions of interest (ROIs). In all analyses, cerebellar gray matter was used as the reference region. Nondisplaceable binding potentials (BPNDs) were calculated using the simplified reference tissue model (SRTM) and SRTM2; the Logan graphical analysis distribution volume ratio (DVR) was calculated for 30–150 min (DVR30–150). These measurements were compared with each other and used as reference standards for defining an appropriate 20-min window for the SUV ratio (SUVR). Pearson correlations were used to compare the reference standards to 20-min SUVRs (start times varied from 30 to 130 min), for all values, for ROIs with low 18F-AV-1451 binding (lROIs, mean of BPND + 1 and DVR30–150 < 1.5), and for ROIs with high 18F-AV-1451 binding (hROIs, mean of BPND + 1 and DVR30–150 > 1.5). Results: SRTM2 BPND + 1 and DVR30–150 were in good agreement. Both were in agreement with SRTM BPND + 1 for lROIs but were greater than SRTM BPND + 1 for hROIs, resulting in a nonlinear relationship. hROI SUVRs increased from 80–100 to 120–140 min by 0.24 ± 0.15. The SUVR time interval resulting in the highest correlation and slope closest to 1 relative to the reference standards for all values was 120–140 min for hROIs, 60–80 min for lROIs, and 80–100 min for lROIs and hROIs. There was minimal difference between methods when statistical significance between ADs and HCs was calculated. Conclusion: Despite later time periods providing better agreement between reference standards and SUVRs for hROIs, a good compromise for studying lROIs and hROIs is SUVR80–100. The lack of SUVR plateau for hROIs highlights the importance of precise acquisition time for longitudinal assessment.

Frontotemporal dementia with the V337M MAPT mutation: Tau-PET and pathology correlations

Objective: To assess the efficacy of [18F]AV1451 PET in visualizing tau pathology in vivo in a patient with frontotemporal dementia (FTD) associated with the V337M microtubule-associated protein tau (MAPT) mutation. Methods: MAPT mutations are associated with the deposition of hyperphosphorylated tau protein in neurons and glia. The PET tracer [18F]AV1451 binds with high affinity to paired helical filaments tau that comprises neurofibrillary tangles in Alzheimer disease (AD), while postmortem studies suggest lower or absent binding to the tau filaments of the majority of non-AD tauopathies. We describe clinical, structural MRI, and [18F]AV1451 PET findings in a V337M MAPT mutation carrier affected by FTD and pathologic findings in his affected mother and in an unrelated V337M MAPT carrier also affected with FTD. The biochemical similarity between paired helical filament tau in AD and MAPT V337M predicts that the tau pathology associated with this mutation constitutes a compelling target for [18F]AV1451 imaging. Results: We found a strong association between topography and degree of [18F]AV1451 tracer retention in the proband and distribution of tau pathology in the brain of the probands mother and the unrelated V337M mutation carrier. We also found a significant correlation between the degree of regional MRI brain atrophy and the extent of [18F]AV1451 binding in the proband and a strong association between the probands clinical presentation and the extent of regional brain atrophy and tau accumulation as assessed by structural brain MRI and [18F]AV1451PET. Conclusion: Our study supports the usefulness of [18F]AV1451 to characterize tau pathology in at least a subset of pathogenic MAPT mutations.

Local and distant relationships between amyloid, tau and neurodegeneration in Alzheimer's Disease

The relationships between β-amyloid (Aβ), tau and neurodegeneration within Alzheimers Disease pathogenesis are not fully understood. To explore these associations in vivo, we evaluated 30 Aβ PET-positive patients (mean ± sd age 62.4 ± 8.3) with mild probable AD and 12 Aβ PET-negative healthy controls (HC) (mean ± sd age 77.3 ± 6.9) as comparison. All participants underwent 3 T MRI, 11C-PiB (Aβ) PET and 18F-AV1451 (tau) PET. Multimodal correlation analyses were run at both voxel- and region-of-interest levels. 11C-PiB retention in AD showed the most diffuse uptake pattern throughout association neocortex, whereas 18F-AV1451 and gray matter volume reduction (GMR) showed a progressive predilection for posterior cortices (p<0.05 Family-Wise Error-[FWE]-corrected). Voxel-level analysis identified negative correlations between 18F-AV1451 and gray matter peaking in medial and infero-occipital regions (p<0.01 False Discovery Rate-[FDR]-corrected). 18F-AV1451 and 11C-PiB were positively correlated in right parietal and medial/inferior occipital regions (p<0.001 uncorrected). 11C-PiB did not correlate with GMR at the voxel-level. Regionally, 18F-AV1451 was largely associated with local/adjacent GMR whereas frontal 11C-PiB correlated with GMR in posterior regions. These findings suggest that, in mild AD, tau aggregation drives local neurodegeneration, whereas the relationships between Aβ and neurodegeneration are not region specific and may be mediated by the interaction between Aβ and tau.

Associations Between Tau, β-Amyloid, and Cognition in Parkinson Disease

Importance Multiple disease processes are associated with cognitive impairment in Parkinson disease (PD), including Lewy bodies, cerebrovascular disease, and Alzheimer disease. It remains unknown whether tau pathology relates to cognition in patients with PD without dementia. Objective To compare tau aggregation in patients with PD who are cognitively normal (PD-CN), patients with PD with mild cognitive impairment (PD-MCI), and healthy control participants, and evaluate the relationships between &bgr;-amyloid (A&bgr;), tau, and cognition in patients with PD who did not have dementia. Design, Setting, and Participants This cross-sectional study recruited 30 patients with Parkinson disease (15 with PD-CN and 15 with PD-MCI) from a tertiary care medical center and research institutions from July 2015 through October 2016. One patient with PD-MCI did not receive a magnetic resonance imaging scan and thus was excluded from all analyses; 29 patients with PD were included in the present study. Participants underwent tau positron emission tomographic (PET) scanning with fluorine 18–labeled AV-1451, A&bgr; PET scanning with carbon 11–labeled Pittsburgh compound B, magnetic resonance imaging, cognitive testing, and neurologic evaluation. Imaging measures were compared with 49 healthy control participants. Main Outcomes and Measures Outcomes were tau PET measurements of groups of patients with PD-CN and PD-MCI. We hypothesized that tau aggregation across groups would be related to age and A&bgr; status. Results Of the 78 participants, 47 (60%) were female, and the mean (SD) age was 71.1 (6.6) years. Six patients with PD (21%) were A&bgr;-positive, of whom 1 was mildly cognitively impaired; 23 were A&bgr;-negative (79%). (Of the 49 healthy controls, 25 were A&bgr;-negative and 24 A&bgr;-positive.) Voxelwise contrasts of whole-brain tau PET uptake between patients with PD-CN and patients with PD-MCI, and additionally between all patients with PD and A&bgr;-negative controls, did not reveal significant differences. Tau PET binding did not differ between patients with PD-MCI and PD-CN in brain regions reflecting Alzheimer disease Braak stages 1/2, 3/4, or 5/6, and did not differ from A&bgr;-negative healthy older adults. Mean (SD) tau PET binding was significantly elevated in A&bgr;-positive patients with PD relative to A&bgr;-negative patients with PD within brain regions reflecting Alzheimer disease Braak stage 3/4 (1.22 [0.07] vs 1.14 [0.07]; P = .03) and Braak stage 5/6 (1.20 [0.07] vs 1.11 [0.08]; P = .02). Conclusions and Relevance These findings suggest that patterns of cortical A&bgr; and tau do not differ in people with PD-CN, people with PD-MCI, and healthy older adults. Age, A&bgr;, and tau do not differentiate patients with PD-CN and PD-MCI. Tau deposition is related to A&bgr; status and age in both people with PD and healthy older adults. Cognitive deficits in people with PD without dementia do not appear to reflect measureable Alzheimer disease.

Distinct [18F]AV1451 retention patterns in clinical variants of Alzheimer’s disease

N 5 4 3 19 Age 64 63 68 79 Sex (m/f) 2/3 1/3 0/3 6/13 MMSE 23 20 22 29 [F]AV1451 SUYr (Tau) Occipital 2.21 1.71 1.65 1.06 Parietal 2.41 2.26 2.20 1.11 Temporal 2.04 2.36 2.12 1.15 Frontal 1.56 1.79 1.36 1.10 MTL 1.47 1.30 1.67 1.18 [E]FDG SUYc (Glucose metabolism) Occipital 1.31 1.89 1.78 1.59 Parietal 1.18 1.43 1.41 1.55 Temporal 1.13 1.25 1.24 1.35 Frontal 1.43 1.53 1.58 1.50 MTL 1.03 1.11 1.09 1.11 [C]PIB DVR (Amyloid) Occipital 1.49 1.65 1.38 1.09 Parietal 1.80 2.17 1.84 1.19 Temporal 1.61 2.02 1.63 1.08 Frontal 1.79 2.28 1.82 1.13 MTL 1.12 1.34 1.21 1.05

TAU-PET PATTERNS OVERLAP AND EXCEED HYPOMETABOLISM IN ALZHEIMER'S DISEASE

latent variables as follows: (1) AgeEduct, denoted for Age and Education variables; (2) Brain, denoted, for ventricular, intracranial, whole brain, midtemporal, fusiform, entorhinal, and hippocampal volumes; and (3) TestN, denoted , for Functional assessment questionnaire (FAQ), ADAS, CDR and MMSE test results. The SEM model with the lowest root mean square error with respect to absolute values was when our outcome variable of interest, Brain, was predicted by AgeEduct and TestN, on top of measured volumes. We then used this model to compare APOEe4 status in the ADNI population. Results: Descriptive statistics for the measured variables according to APOEe4 status are shown in Table 1. Path diagrams for the SEM model according to APOEe4 status are shown in Figures 1 and 2. Results of the SEM model fit by APOEe4 groups are shown in Table 2. For the selected SEM model, we obtain similar results whether or not one takes into account APOEe4 status. Conclusions:We have selected the best SEM model, taking into consideration brain volumes, age, education and neuropsychological test results. This model is not influenced by APOEe4 status in the ADNI population.

In vivo braak staging using 18F-AV1451 Tau PET imaging

Age 73 6 10.6 66.3 68.2 Education 13.2 66.2 16.1 62.5 MMSE 28.9 61.2 22.3 64.9 ApoE ε4 (0/1/2/na) 11/5/0/5 2/1/2/3 Michael Sch€oll, Daniel Schonhaut, Sam Lockhart, Jacob W. Vogel, Suzanne Baker, Henry Schwimmer, Rik Ossenkoppele, Gil D. Rabinovici, William J. Jagust, University of California Berkeley, Berkeley, CA, USA; University of Gothenburg, Gothenburg, Sweden; University of California San Francisco, San Francisco, CA, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, USA; VU University Amsterdam, Amsterdam, Netherlands. Contact e-mail: Michael. Scholl@neuro.gu.se

TAU PATHOLOGY AND GRAY MATTER ATROPHY CONTRIBUTE TO COGNITIVE IMPAIRMENT IN ALZHEIMER’S DISEASE

approaches produced comparable results in both cohorts, with an average quantification error close to 2% (was 2.9% in PiB). Therefore, the simpler mean atlas approach appears to be sufficient, although the PCA approach might be closer to MR quantification in the Me. Looking at the PCA decomposition, it is interesting to note that hippocampus uptake is mostly driven by spill over from the choroid plexus (CP). The CP is prominently represented in the mean image, and in the 3rd mode (5% of the variability). Uptake in the CP is therefore fairly consistent across the population, and variations in its uptake are independent from tracer retention in the Me. While not significant, there was a trend association between increasing CP uptake and increasing age in both AIBL (p1⁄40.10) and ADNI (p1⁄40.25) cohorts. Conclusions: Results show that all quantification performed using PET-only normalization approaches did equally well, with an average quantification error around 2% in both cohorts. Partial volume correctionmight however be required to account for spill over.