Toga, Arthur W.

AbstractObjectiveThe Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS) seeks to provide comprehensive understanding of early‐onset Alzheimer's disease (EOAD; onset <65 years), with the current study profiling baseline clinical, cognitive, biomarker, and genetic characteristics of the cohort nearing the data‐collection mid‐point.MethodsData from 371 LEADS participants were compared based on diagnostic group classification (cognitively normal [n = 89], amyloid‐positive EOAD [n = 212], and amyloid‐negative early‐onset non‐Alzheimer's disease [EOnonAD; n = 70]).ResultsCognitive performance was worse for EOAD than other groups, and EOAD participants were apolipoprotein E (APOE) ε4 homozygotes at higher rates. An amnestic presentation was common among impaired participants (81%), with several clinical phenotypes present. LEADS participants generally consented at high rates to optional trial procedures.ConclusionsWe present the most comprehensive baseline characterization of sporadic EOAD in the United States to date. EOAD presents with widespread cognitive impairment within and across clinical phenotypes, with differences in APOE ε4 allele carrier status appearing to be relevant.HIGHLIGHTS Findings represent the most comprehensive baseline characterization of sporadic early‐onset Alzheimer's disease (EOAD) to date. Cognitive impairment was widespread for EOAD participants and more severe than other groups. EOAD participants were homozygous apolipoprotein E (APOE) ε4 carriers at higher rates than the EOnonAD group. Amnestic presentation predominated in EOAD and EOnonAD participants, but other clinical phenotypes were present.

Accurate prediction of progression in subjects at risk of Alzheimer's disease is crucial for enrolling the right subjects in clinical trials. However, a prospective comparison of state-of-the-art algorithms for predicting disease onset and progression is currently lacking. We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. The methods used by challenge participants included multivariate linear regression, machine learning methods such as support vector machines and deep neural networks, as well as disease progression models. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guesswork. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as the slope or maxima/minima of patient-specific biomarkers. On a limited, cross-sectional subset of the data emulating clinical trials, performance of the best algorithms at predicting clinical diagnosis decreased only slightly (2 percentage points) compared to the full longitudinal dataset. The submission system remains open via the website https://tadpole.grand-challenge.org, while TADPOLE SHARE (https://tadpole-share.github.io/) collates code for submissions. TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease. However, results call into question the usage of cognitive test scores for patient selection and as a primary endpoint in clinical trials.

AbstractIntroductionEmpathy relies on fronto‐cingular and temporal networks that are selectively vulnerable in behavioral variant frontotemporal dementia (bvFTD). This study modeled when in the disease process empathy changes begin, and how they progress.MethodsFour hundred thirty‐one individuals with asymptomatic genetic FTD (n = 114), genetic and sporadic bvFTD (n = 317), and 163 asymptomatic non‐carrier controls were enrolled. In sub‐samples, we investigated empathy measured by the informant‐based Interpersonal Reactivity Index (IRI) at each disease stage and over time (n = 91), and its correspondence to underlying atrophy (n = 51).ResultsEmpathic concern (estimate = 4.38, 95% confidence interval [CI] = 2.79, 5.97; p < 0.001) and perspective taking (estimate = 5.64, 95% CI = 3.81, 7.48; p < 0.001) scores declined between the asymptomatic and very mild symptomatic stages regardless of pathogenic variant status. More rapid loss of empathy corresponded with subcortical atrophy.DiscussionLoss of empathy is an early and progressive symptom of bvFTD that is measurable by IRI informant ratings and can be used to monitor behavior in neuropsychiatry practice and treatment trials.

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.

AbstractBackgroundThe U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is a 2‐year randomized controlled trial to evaluate the effect of lifestyle interventions in older adults (60‐79 years). The POINTER Imaging ancillary study is collecting Arterial Spin Labeling (ASL) MRI data to map cerebral blood flow (CBF) and evaluate the effect of interventions in the perfusion imaging biomarker. The optimization of timing parameters is essential for robust and efficient acquisition of ASL MRI.MethodA subset (n=83; F/M=51/32; age=69.0±5.5) of POINTER Imaging participants at two imaging sites underwent two ASL MRI scans during the same baseline session. Two 3D Pulsed ASL were obtained with TI1 of 790ms and TI2 values of 2000ms or 2750ms, which provide the delay times (between labeling and imaging) of 1210ms or 1960ms. ASL images were quantified into a physiological unit of CBF, ml/100g/min, using a single compartment kinetic model. CBF maps from two scans were normalized into a standard space and a voxel‐wise paired t‐test was performed after site variations were harmonized and covariates (age and sex) were adjusted. The age and sex effects in the difference of CBF values between two scans were also examined using linear regression. To control false positives, clusters smaller than 41ml were removed based on a simulation with α=0.05.ResultThe CBF values in ASL MRI rely on the timing of image acquisition: only a fraction of label bolus arrives in the tissue with a short delay while images suffer from low signal due to the magnetization decay with a long delay. Figure 1 shows the regions that require a long delay time (red) or a short delay (blue). The difference in CBF is proportional to arterial transit time (ATT) and the analysis shows females have shorter ATT mainly in the peri‐Sylvian region (Figure 2). No cluster survived correction in the analysis of the aging effect.ConclusionThe acquisition of two CBF maps not only offers optimization of acquisition timing but provides an additional perfusion parameter, arterial transit time, which may be a potential biomarker of cerebrovascular pathophysiology.

AbstractIntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to validate biomarkers for Alzheimer's disease (AD) clinical trials. To improve generalizability, ADNI4 aims to enroll 50‐60% of its new participants from underrepresented populations (URPs) using new biofluid and digital technologies. ADNI4 has received funding from the National Institute on Aging beginning September 2022.MethodsADNI4 will recruit URPs using community‐engaged approaches. An online portal will screen 20,000 participants, 4000 of whom (50‐60% URPs) will be tested for plasma biomarkers and APOE. From this, 500 new participants will undergo in‐clinic assessment joining 500 ADNI3 rollover participants. Remaining participants (∼3500) will undergo longitudinal plasma and digital cognitive testing. ADNI4 will add MRI sequences and new PET tracers. Project 1 will optimize biomarkers in AD clinical trials.Results and DiscussionADNI4 will improve generalizability of results, use remote digital and blood screening, and continue providing longitudinal clinical, biomarker, and autopsy data to investigators.

AbstractThe extent to which the pathophysiology of autosomal dominant Alzheimer's disease corresponds to the pathophysiology of ‘sporadic’ late onset Alzheimer's disease is unknown, thus limiting the extrapolation of study findings and clinical trial results in autosomal dominant Alzheimer's disease to late onset Alzheimer's disease.We compared brain MRI and amyloid PET data, as well as CSF concentrations of amyloid-β42, amyloid-β40, tau and tau phosphorylated at position 181, in 292 carriers of pathogenic variants for Alzheimer's disease from the Dominantly Inherited Alzheimer Network, with corresponding data from 559 participants from the Alzheimer’s Disease Neuroimaging Initiative. Imaging data and CSF samples were reprocessed as appropriate to guarantee uniform pipelines and assays. Data analyses yielded rates of change before and after symptomatic onset of Alzheimer's disease, allowing the alignment of the ∼30-year age difference between the cohorts on a clinically meaningful anchor point, namely the participant age at symptomatic onset.Biomarker profiles were similar for both autosomal dominant Alzheimer's disease and late onset Alzheimer's disease. Both groups demonstrated accelerated rates of decline in cognitive performance and in regional brain volume loss after symptomatic onset. Although amyloid burden accumulation as determined by PET was greater after symptomatic onset in autosomal dominant Alzheimer's disease than in late onset Alzheimer's disease participants, CSF assays of amyloid-β42, amyloid-β40, tau and p-tau181 were largely overlapping in both groups. Rates of change in cognitive performance and hippocampal volume loss after symptomatic onset were more aggressive for autosomal dominant Alzheimer's disease participants.These findings suggest a similar pathophysiology of autosomal dominant Alzheimer's disease and late onset Alzheimer's disease, supporting a shared pathobiological construct.

AbstractBackgroundFrontotemporal dementia spectrum disorders (FTD) display complex neuropathological substrates and poor clinicopathological correlations, which hinders therapy development. Plasma P‐tau217 is an emerging tool to screen for Alzheimer’s disease (AD) pathology and may have diagnostic value in FTD.MethodPlasma P‐tau217 was measured cross‐sectionally by electrochemiluminescence in FTD patients referred to ALLFTD from ARTFL (n = 628, 45.7% female, median age 66 ± 12 years). P‐tau217 differences by baseline phenotype, disease severity and genotype were determined with non‐parametric tests and general linear models. Associations between P‐tau217 and measures of disease severity and neuropsychological performance were determined with linear regressions corrected for age, sex, phenotype and APOE.ResultThe sample included 33% behavioral variant FTD, 23.6% primary progressive aphasia (PPA), 28.5% atypical parkinsonism, 1.6% amnestic dementia (AmDem), 2.8% FTD/motoneuron disease, 3% mild cognitive/behavioral impairment and 7.5% healthy controls. Only 1.6% carried FTD‐causing mutations. P‐tau217 was not related to age (r = 0.034, 95%CI ‐0.03 – 0.12, p = 0.4). Compared to controls (0.18 ± 0.07 pg/mL), P‐tau217 was elevated only in AmDem (0.58 ± 0.9 pg/mL, p = 0.001) and logopenic PPA (lvPPA, 0.71 ± 0.62 pg/mL p < 0.001). P‐tau217 ≥ 0.42 pg/mL effectively discriminated AmDem and lvPPA from all other phenotypes (AUC 0.87, 95%CI 0.77 – 0.96, p = 0.001, 77% sensitivity, 92% specificity). AmDem (60%) and lvPPA (91.7%) had the highest prevalence of high (≥ 0.42 pg/mL) P‐tau217, and the highest prevalence of APOE4 (AmDem 40%, lvPPA 63.6%). APOE4 carriers (0.23 ± 0.22 pg/mL) had higher P‐tau217, than non‐carriers (0.19 ± 0.09 pg/mL), regardless of phenotype (APOE effect p = .002, APOE x phenotype, p = 0.44). P‐tau217 was associated with worse clinical severity, mood, memory and executive function, but not with worse motor symptoms or social cognition.ConclusionWhen FTD is suspected, high plasma P‐tau217 is strongly associated with amnestic dementia and logopenic PPA phenotypes. Pending completion of ongoing neuropathological, CSF and molecular neuroimaging analyses, the data support the use of plasma P‐tau217 to identify atypical AD as a cause or AD as a co‐pathology contributing to FTD clinical presentation.

AbstractBackgroundThe U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is a 2‐year randomized controlled trial to evaluate the effect of lifestyle interventions in older adults (60‐79 years) who are cognitively unimpaired but at increased risk for cognitive decline/dementia due to factors such as cardiovascular disease and family history. The POINTER Imaging ancillary study is collecting PET and MRI data to evaluate neuroimaging biomarkers of AD and cerebrovascular pathophysiology in this at‐risk sample.MethodPOINTER Imaging is actively enrolling 1250 participants, 23% from under‐represented racial/ethnic groups (URG), recruited from five U.S. POINTER clinical sites. Participants have undergone PET imaging with [18F]Florbetaben (FBB) to measure Aβ and [18F]MK‐6240 to measure tau burden, as well as MRI to measure brain morphometry, white matter hyperintensities and cerebral blood flow. FBB and MK‐6240 data were quality checked, pre‐processed, and quantified using previously validated methods. PET images were coregistered to a structural MRI, which was also used to create FreeSurfer‐defined reference regions and regions of interest. We examined PET imaging measures (global Aβ, regional tau) and basic demographic (age, sex, race/ethnicity) characteristics of the sample.Result96 participants (mean age 69.3±5.0) have been enrolled in POINTER Imaging. Of these, 59 (61%) are women and 22 (23%) are URG, which is similar to rates of women (75%) and URG (22%) in the main trial. This dataset is <10% of targeted enrollment, was predominantly recruited from 2/5 clinical sites and may not represent the final imaging cohort. FBB quantification (N=20) revealed a mean cortical summary SUVR of 1.09±0.12 (19.6±18.4 centiloids) (whole cerebellum normalization; previously validated positivity threshold=1.08), and 8/20 (40%) of these participants were Aβ+ (Fig. 1A). MK‐6240 quantification (N=23) showed predominantly no/minimal binding with a few exceptions in medial and lateral temporal lobes (Fig. 1B&C).ConclusionThe POINTER imaging study is meeting the target URG enrollment and representative of the main U.S. POINTER trial. Higher frequency of Aβ positivity than published in population cohorts coupled with greater cardiovascular risk factors among POINTER participants highlights our success in recruiting individuals at increased risk of cognitive decline.

AbstractBackgroundClinical trials for tauopathies require novel biomarkers for disease detection and monitoring. One previous study found functional connectivity (FC) alterations in presymptomatic (preSx) MAPT mutation carriers (Whitwell et al., 2011), yet studies have not examined FC networks along the MAPT disease continuum. We hypothesized that both symptomatic (Sx) and preSx MAPT mutation carriers would show FC alterations compared to healthy controls (HC).MethodLeveraging task‐free fMRI data from the UCSF Memory and Aging Center and the ARTFL/LEFFTDS Consortia (Boeve et al., 2019), we compared 14 Sx and 33 preSx to 80 HC to characterize their FC profiles. Using a seed‐based approach, we studied FC within networks associated with different MAPT clinical syndromes (i.e., salience network [SN] for behavioral variant frontotemporal dementia, default mode network [DMN] for Alzheimer’s‐like amnestic syndrome, corticobasal syndrome [CBS] and progressive supranuclear palsy [PSP] networks). Complementing the seed‐based approach, we next calculated whole‐brain intra‐/inter‐network FC matrices for 14 networks (Brown et al., 2019), and applied K‐means clustering to assess whether preSx displayed heterogeneous connectivity profiles. ComBat was applied to harmonize multi‐site imaging data (Fortin et al., 2017, 2018). Thresholding was set at a joint height and extent threshold of p<0.05 (uncorrected) with age, sex, education and handedness as nuisance covariates.ResultCompared to HC, Sx featured disrupted FC within key hubs of all four networks, and regions of cerebellar and pontine hyperconnectivity within CBS and PSP networks. As seen in Sx vs. HC, preSx had similar anatomical patterns of SN/CBS network hypoconnectivity and CBS/PSP network hyperconnectivity vs. HC. In contrast to Sx, who had DMN disruption, preSx showed DMN hyperconnectivity vs. HC.Whole‐brain analyses revealed that Sx had disrupted intra‐/inter‐network FC in networks involving the insula/anterior temporal lobe. Clustering analysis identified two preSx subgroups. Compared to HC, preSx1 principally had disrupted FC across networks including those disrupted in Sx, whereas preSx2 mainly demonstrated hyperconnectivity.ConclusionSx and preSx both demonstrated robust FC alterations. Future studies will investigate whether the preSx subgroup whose whole‐brain FC was similar to Sx in that it showed principally FC disruption may be at greater risk for imminent symptom conversion and/or neurodegeneration.