Rabinovici, Gil D.

ImportancePlasma phosphorylated tau217 (p-tau217), a biomarker of Alzheimer disease (AD), is of special interest in corticobasal syndrome (CBS) because autopsy studies have revealed AD is the driving neuropathology in up to 40% of cases. This differentiates CBS from other 4-repeat tauopathy (4RT)–associated syndromes, such as progressive supranuclear palsy Richardson syndrome (PSP-RS) and nonfluent primary progressive aphasia (nfvPPA), where underlying frontotemporal lobar degeneration (FTLD) is typically the primary neuropathology.ObjectiveTo validate plasma p-tau217 against positron emission tomography (PET) in 4RT-associated syndromes, especially CBS.Design, Setting, and ParticipantsThis multicohort study with 6, 12, and 24-month follow-up recruited adult participants between January 2011 and September 2020 from 8 tertiary care centers in the 4RT Neuroimaging Initiative (4RTNI). All participants with CBS (n = 113), PSP-RS (n = 121), and nfvPPA (n = 39) were included; other diagnoses were excluded due to rarity (n = 29). Individuals with PET-confirmed AD (n = 54) and PET-negative cognitively normal control individuals (n = 59) were evaluated at University of California San Francisco. Operators were blinded to the cohort.Main Outcome and MeasuresPlasma p-tau217, measured by Meso Scale Discovery electrochemiluminescence, was validated against amyloid-β (Aβ) and flortaucipir (FTP) PET. Imaging analyses used voxel-based morphometry and bayesian linear mixed-effects modeling. Clinical biomarker associations were evaluated using longitudinal mixed-effect modeling.ResultsOf 386 participants, 199 (52%) were female, and the mean (SD) age was 68 (8) years. Plasma p-tau217 was elevated in patients with CBS with positive Aβ PET results (mean [SD], 0.57 [0.43] pg/mL) or FTP PET (mean [SD], 0.75 [0.30] pg/mL) to concentrations comparable to control individuals with AD (mean [SD], 0.72 [0.37]), whereas PSP-RS and nfvPPA showed no increase relative to control. Within CBS, p-tau217 had excellent diagnostic performance with area under the receiver operating characteristic curve (AUC) for Aβ PET of 0.87 (95% CI, 0.76-0.98; P < .001) and FTP PET of 0.93 (95% CI, 0.83-1.00; P < .001). At baseline, individuals with CBS-AD (n = 12), defined by a PET-validated plasma p-tau217 cutoff 0.25 pg/mL or greater, had increased temporoparietal atrophy at baseline compared to individuals with CBS-FTLD (n = 39), whereas longitudinally, individuals with CBS-FTLD had faster brainstem atrophy rates. Individuals with CBS-FTLD also progressed more rapidly on a modified version of the PSP Rating Scale than those with CBS-AD (mean [SD], 3.5 [0.5] vs 0.8 [0.8] points/year; P = .005).Conclusions and RelevanceIn this cohort study, plasma p-tau217 had excellent diagnostic performance for identifying Aβ or FTP PET positivity within CBS with likely underlying AD pathology. Plasma P-tau217 may be a useful and inexpensive biomarker to select patients for CBS clinical trials.

AbstractBackgroundChronic traumatic encephalopathy (CTE) is a neurodegenerative disease that is characterized by perivascular foci of phosphorylated tau (p‐tau) notably in the depths of sulci, with varying patterns in the cerebral cortex. Prior studies show elevated flortaucipir (FTP) PET binding in former American professional football players(PRO). However, the association of p‐tau with clinical measures remains unclear using regional FTP SUVR as early signs of CTE related tau pathology. Graph theory (GT) takes advantages of the spatial variability in p‐tau load and allows the integration of regional measures to define GT based measures. Here we examine the GT based measures in two CTE cohorts to evaluate their utility in assessing p‐tau related pathology in CTE.MethodThe graph procedure was optimized in FTP PET images in a group of 26 PRO with reported cognitive and/or behavorial symptoms and 30 asymptomatic controls without a history of traumatic brain injury (the DETECT Study) and identified the GT measure, entorhinal tau strength, as the target metric with the best group separation between PRO and controls. The optimized graph procedures were then applied to the DIAGNOSE CTE Research Project dataset (99 former PRO, 51 former college football players [COL], and 52 controls without exposure to repetitive head impacts [CTL]) and we examined entorhinal tau strength’s ability to differentiate the exposure groups and relationship to consensus based diagnoses of Traumatic Encephalopathy Syndrome (TES), the clinical syndrome associated with CTE.ResultEntorhinal tau strength was significantly different among the three exposure groups (p=0.0001) similar to regional SUVR measures (Figure 1). Regional SUVR did not differentiate players (PRO+COL) with and without TES, while entorhinal tau strength approached although did not reach significance (Figure 2). Entorhinal tau strength is the only FTP measure that showed significant differences (p=0.006) between those players with cognitive impairment and players without (Figure 3).ConclusionWhile there is still considerable overlap in between‐group measurements, GT based entorhinal tau strength, is potentially more sensitive in detecting tau changes in players with and without TES. Additional studies are necessary to clarify the value of this new measure in detecting underlying CTE pathology.

AbstractBackgroundPreviously, we found that female sex is associated with greater pathology burden in early‐onset Alzheimer’s disease (EOAD) in the Longitudinal EOAD Study (LEADS). Here, we have expanded our analyses by adding APOE‐ε4 carrier status as a further predictor of EOAD pathologic burden.MethodWe included 180 EOAD LEADS participants with available APOE genotype, Flortaucipir PET, Florbetaben PET, and MRI data. Demographic and biomarker differences were analyzed using ANOVA. EOAD participants were split by sex and APOE‐ε4 carrier status. Box plots were created in R and a voxel‐wise multiple linear regression in SPM12 yielded statistical brain maps of gray matter density (GMD), amyloid and tau burden.ResultCompared to males, EOAD females showed significantly greater global amyloid uptake (mean SUVR, p=0.002) and greater tau SUVR in the MetaROI, Braak 3&4 and 5&6 regions (p=0.0007, p=0.001, p=0.01, resp., Table 1). Female APOE‐ε4 carriers showed greater tau SUVR in Braak regions 1&2 than female non‐carriers (p<0.01, Figure 2B). Male APOE‐ε4 carriers showed trend‐level thinner entorhinal cortex than male non‐carriers (p=0.06, Figure 1). Interestingly however, femaleAPOE‐ε4 non‐carriers showed greater global amyloid SUVR than female carriers (p<0.01, Figure 2A). Further, APOE‐ε4 non‐carriers showed significantly thinner medial temporal cortices than carriers in both sexes (M, p<0.05; F, p<0.01). Male APOE‐ε4 non‐carriers also showed significantly lower mean cortical thickness than male carriers (p<0.05, Figure 1). Female APOE‐ε4 non‐carriers showed trend‐level lower mean cortical thickness than female carriers (p=0.06, Figure 1). The FWE corrected SPM12 maps showed significantly greater GM atrophy in the right temporal lobe and greater amyloid burden in a right lateralized occipitoparietal pattern in female APOE‐ε4 non‐carriers compared to female carriers. Further, male APOE‐ε4 non‐carriers showed greater tau uptake in the left frontal lobe than male carriers (Figure 3).ConclusionThese results suggest that APOE‐ε4 non‐carrier status is associated with greater atrophy, amyloid and tau deposition in EOAD. This might be due to the presence of other strong genetic drivers of disease pathology in EOAD.

AbstractBackgroundThere is a critical need for tau PET radiotracers that accurately detect non‐Alzheimer’s disease (AD) tau pathology. We aim to evaluate [18F]PI‐2620 PET tracer retention in patients with non‐AD, 4R tau‐related clinical syndromes, including progressive supranuclear palsy (PSP) with Richardson’s syndrome (PSP‐RS) and with predominant parkinsonism (PSP‐P), corticobasal syndrome (CBS), and nonfluent/agrammatic variant of primary progressive aphasia (nfvPPA).Method38 participants underwent amyloid and [18F]PI‐2620 PET (Table 1). 5 mCi ± 10% of [18F]PI‐2620 was administered. [18F]PI‐2620 PET SUVR images were generated using an inferior cerebellar gray matter reference from PET data acquired 30‐60 minutes post‐injection. Mean SUVR values were extracted from each participant in neuroanatomical structures that have elevated tau burden in PSP and CBS due to corticobasal degeneration (regions of interest in Table 2). Comparison between each diagnostic group and healthy controls (HCs) was performed using a one‐tailed, independent‐samples t‐test. Spearman correlation was used to evaluate the relationship between tracer binding (SUVR) and disease severity (PSP rating scale) in patients with PSP‐RS.ResultPatients with PSP‐RS had increased tracer retention in the left globus pallidus internus and externus, left subthalamic nucleus, and left dorsolateral prefrontal cortex compared to HCs (all p < 0.05). CBS and nfvPPA patients did not have increased tracer retention at any ROIs compared to HCs, but there were low numbers of patients in these groups (Table 2, Figures 1‐3). PSP rating scale values did not correlate with tracer binding in PSP‐RS (no correlations in any regions, rs < 0.44, p > 0.05 uncorrected).Conclusion[18F]PI‐2620 PET 30‐60 minute SUVR images may have limited ability to distinguish PSP from HCs, especially on visual read, and tracer uptake did not correlate with PSP disease severity. Other post‐injection PET acquisition windows (e.g., 30‐40 minute SUVR, 0‐60 minute DVR) will be evaluated to determine if they can maximize differences between PSP and HCs. A limitation of this preliminary study is the modest number of patients and controls, with most controls provided from a different study. Additional participants are being scanned in the multicenter 4RTNI study to understand the utility of this tracer as a neuroimaging biomarker for 4R tauopathies.

AbstractBackgroundDyadic (self and study partner) subjective reports of an individual’s recent cognitive and functional decline are an efficient approach to facilitate identification of older adults with, and at risk for, Mild Cognitive Impairment (MCI). Such methods can be easily adapted for remote administration, but few studies have investigated the ability of remotely‐collected, unsupervised dyadic subjective reports to accurately detect MCI and cognitive decline.MethodsIn 289 older adults enrolled in the Brain health Registry (BHR), with clinically‐confirmed diagnoses of Cognitively‐unimpaired (CU) or MCI, we identified the optimal combination of remote measures to accurately distinguish CU from MCI. We then externally validated our predictive model in 217 participants enrolled in a separate cohort, Validation of Online Methods to Predict Cognitive Decline (eVAL). Predictors included Cogstate Brief Battery One Card Learning (OCL) accuracy; self‐ and study partner‐reported memory concern (SMCs); performance on online adaptations of Everyday Cognition Scale (ECog, self‐ and study partner‐report versions), Geriatric Depression Scale Short Form (GDS); family history of AD, age, gender, and education. We calculated 10‐fold cross validated area under the ROC curves (cvAUC), 95% confidence intervals (CI), and the percentage of participants correctly classified (accuracy) for all models. Likelihood ratio (LR) tests were used to compare model fits.ResultsIn the BHR cohort, models including dyad‐report ECog, family history of AD, GDS, and Cogstate OCL scores distinguished CU from MCI with the highest accuracy (cvAUC = 0.90; 95% CI = 0.83, 0.92; accuracy = 85.5%). Models excluding study partner‐report ECog distinguished diagnostic groups with moderate accuracy (cvAUC = 0.83; 95% CI = 0.78, 0.85; accuracy = 75.9%) When applied to the validation cohort, the optimal training model including dyadic report performed with moderate accuracy ( Table 2 ). In the validation cohort, inclusion of study partner (but not self) report SMC, in addition to dyadic‐report ECog, improved model fit (LR test p<0.01).ConclusionsRemotely‐collected dyadic subjective measures, along with other remote measures, accurately distinguish CU from MCI. Subjective cognitive and functional decline and concerns about memory problems independently contribute to diagnostic discrimination. Results support future utilization of remote dyadic subjective measures to efficiently identify older adults with MCI for prodromal AD clinical trials, and in clinical care settings.

AbstractBackgroundThe overarching goal of the Longitudinal Early‐onset Alzheimer Disease study (LEADS) is to optimally characterize early‐onset AD (EOAD) and establish an EOAD clinical trials network. Here we report the baseline demographic and imaging biomarker comparisons of the LEADS cohort to late‐onset AD (LOAD) subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI3).Method123 amyloid‐positive EOAD, 47 amyloid‐negative EOnonAD, 60 cognitively normal young controls were compared to 130 amyloid‐positive LOAD, 110 amyloid‐negative LOnonAD and 286 amyloid‐negative cognitively normal older controls. To account for the effect of cognitive aging between EO and LO populations, each cognitive measure was Z‐transformed. Cortical and hippocampal atrophy were quantified using W‐scores adjusted for age, sex and total intracranial volume. Z‐scores and W‐scores were compared using t‐test or Wilcoxson rank test as appropriate. All p‐values were corrected for multiple comparisons using the false discovery rate correction.ResultEOAD showed greater pathology burden and greater cortical atrophy (AD signature) relative to LOAD. EOAD also showed greater cognitive impairment across all cognitive tests. EOAD showed greater functional impairment, more depression but less neuropsychiatric behaviors overall compared to LOAD (Table 1 and Figure 1, all ps<0.05). Repeating the analyses stratified by cognitive stage (MCI/dementia) or CDR global rating (0.5/1) did not result in any major differences.EOnonAD differed from LOnonAD by also showing greater impairment on all cognitive and functional measures There were no significant differences in amyloid and tau burden, or atrophy W‐scores between these groups. EOnonAD were more depressed and showed more functional impairment compared to LOnonAD (Table 2 and Figure 2, all ps<0.05). Repeating the analyses split by cognitive stage (MCI/dementia) or CDR global rating (0.5/1) did not result in any major differences.ConclusionConsistent with our preexisting hypotheses, EOAD and EOnonAD perform much worse relative to their LO counterparts. EOAD also show greater pathological burden as expected. The reported analyses were done in chronological rather than disease time (time since disease onset). Benchmarking individuals along the disease spectrum might prove to be a better strategy especially when conducting analyses on rate of disease progression.

AbstractBackgroundClinicopathologic studies reported that the NACC Uniform Dataset (UDS) 2.0 core measures do not adequately differentiate patients who ultimately died of Frontotemporal Lobar Degeneration (FTLD) from Alzheimer’s disease (AD). The FTLD Module (FTLD‐MOD) assesses core features of behavioral variant FTD (bvFTD) and primary progressive aphasia (PPA). Initial investigations suggest that the FTLD‐MOD improves discrimination between biomarker‐supported bvFTD and typical late‐onset AD, and that clinically diagnosed PPA participants performed worse than bvFTD on all FTLD‐MOD language tasks. However, the utility of these measures in the differential diagnosis of AD vs. major FTLD syndromes in young‐onset cases remains underexplored.MethodWe examined participants with age‐of‐onset < 65 years in the ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) consortium and the Longitudinal Early Onset AD Study (LEADS). 115 bvFTD, 53 semantic variant PPA (svPPA), 29 non‐fluent variant PPA (nfvPPA) and 124 early‐onset AD (eoAD) cases completed the UDS3 and FLTD‐MOD. Linear regression analyses measured group differences in FLTD‐MOD raw scores and UDS3 neuropsychological z‐scores after accounting for group differences in demographic variables and global severity ratings. Alpha was 0.05 with Bonferroni corrections.ResultsParticipants with eoAD demonstrated the most impaired scores on tasks of attention, working memory, and processing speed, including Digit Span Backward (z=‐1.87) and Trails A (z=‐3.82). They also demonstrated difficulty on FTLD‐MOD language tasks with a working memory requirement (sentence repetition raw=3.68/5) and, as expected, memory (story delayed recall z=‐2.4z). svPPA performed the worst on FTLD‐MOD and UDS3 tasks assessing semantic memory, especially naming (all p’s ≤ 0.03). nfvPPA performed worst on sentence reading, sentence repetition, and letter fluency (all p’s ≤ 0.02). Consistent with previous work, these measures differentiate between bvFTD and PPA variants. However, relative to eoAD, bvFTD was equivalent (Trails B: bvFTDz=‐3.8, eoADz=‐3.82; p=0.12) or outperformed (sentence repetition: bvFTD=4.22/5, eoAD=3.68/5; p<0.001) the eoAD group on all tasks.ConclusionsWe undertook this analysis to compare performance of the major young‐onset sporadic AD and FTLD clinical syndromes in the ALLFTD and LEADS studies. Results demonstrate relatively distinct cognitive profiles among eoAD, svPPA, and nfvPPA, but not in bvFTD. Future analyses will include FTLD‐MOD behavioral symptom questionnaires to assess their utility in differentiating bvFTD.

AbstractStudies supporting a strong association between tau deposition and neuronal loss, neurodegeneration, and cognitive decline have heightened the allure of tau and tau‐related mechanisms as therapeutic targets. In February 2020, leading tau experts from around the world convened for the first‐ever Tau2020 Global Conference in Washington, DC, co‐organized and cosponsored by the Rainwater Charitable Foundation, the Alzheimer's Association, and CurePSP. Representing academia, industry, government, and the philanthropic sector, presenters and attendees discussed recent advances and current directions in tau research. The meeting provided a unique opportunity to move tau research forward by fostering global partnerships among academia, industry, and other stakeholders and by providing support for new drug discovery programs, groundbreaking research, and emerging tau researchers. The meeting also provided an opportunity for experts to present critical research‐advancing tools and insights that are now rapidly accelerating the pace of tau research.

Abstract Introduction Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD‐MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD‐MC and could help predict risk for dementia during trial enrollment. Methods We created a dementia risk score by entering standardized gray‐matter volumes from 231 DIAD‐MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD‐MC followed longitudinally. Results Our risk score separated asymptomatic versus demented DIAD‐MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%–98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD‐MC participants for prevention trials.

AbstractPatients with early‐onset Alzheimer's disease (EOAD) are commonly excluded from large‐scale observational and therapeutic studies due to their young age, atypical presentation, or absence of pathogenic mutations. The goals of the Longitudinal EOAD Study (LEADS) are to (1) define the clinical, imaging, and fluid biomarker characteristics of EOAD; (2) develop sensitive cognitive and biomarker measures for future clinical and research use; and (3) establish a trial‐ready network. LEADS will follow 400 amyloid beta (Aβ)‐positive EOAD, 200 Aβ‐negative EOnonAD that meet National Institute on Aging–Alzheimer's Association (NIA‐AA) criteria for mild cognitive impairment (MCI) or AD dementia, and 100 age‐matched controls. Participants will undergo clinical and cognitive assessments, magnetic resonance imaging (MRI), [18F]Florbetaben and [18F]Flortaucipir positron emission tomography (PET), lumbar puncture, and blood draw for DNA, RNA, plasma, serum and peripheral blood mononuclear cells, and post‐mortem assessment. To develop more effective AD treatments, scientists need to understand the genetic, biological, and clinical processes involved in EOAD. LEADS will develop a public resource that will enable future planning and implementation of EOAD clinical trials.