Zammit, Matthew D.

Abstract Background Alzheimer Disease (AD) pathology evolves over decades, and understanding this progression is critical to the understanding of the disease and timing therapeutic interventions. Since individuals with Autosomal Dominant AD (ADAD) develop symptoms around the same age as their parent, it is possible to predict symptom onset and stage individuals by their estimated years to symptom onset (EYO). This approach does not generalize to other forms of AD, thus there is a pressing need for the timecourse of ADAD to be defined in broadly relevant terms. The objective of this project is to validate the Sampled Iterative Local Approximation (SILA) algorithm in a cohort with a known disease timecourse. SILA generates an estimate of time from amyloid positivity (A time ) based on longitudinal PET data. Method We evaluated A time in a longitudinal ADAD sample ( N = 316) with PET PiB data in three ways. First, we compared predicted age at amyloid positive (A+) to observed age at A+ for individuals who became A+ during enrollment. Next, using linear regression, we compared estimated age at A+ to estimated age at symptom onset (EYO=0). Finally, we used generalized additive models to compare the amount of variance in concurrent cognitive performance explained both A time and EYO. Result We observed a mean average error of 1.15 years between actual age at A+ ( N = 26) and the SILA‐predicted A time . Across all participants, SILA‐estimated age at A+ explained 39% of the variance in estimated age at symptom onset ( β = 0.918, p < 0.0001). Finally, we observed a nonlinear association between cognition and both A time and EYO. A time explained 19% of the variance in the general cognitive composite while EYO explained 43% of the variance. Conclusion SILA produces a valid estimate of time‐from‐amyloid positivity in ADAD. This work allows for disease stage in ADAD to be compared to staging for broad forms of AD, which was not previously possible using EYO. However, this work also illustrates that there is a high degree of heterogeneity in preclinical disease duration that is not explained by amyloid alone.

Abstract INTRODUCTION Preclinical Alzheimer's disease (AD) can be described relative to biomarker positivity onset time. METHODS We estimated time from amyloid positivity (A+) using sampled iterative local approximation (SILA) in a longitudinal autosomal dominant AD (ADAD) sample ( N = 379) with amyloid positron emission tomography. We compared (1) predicted age at A+ to imputed age, (2) estimated age at A+ to estimated age at symptom onset, and (3) variance in cognitive performance explained. RESULTS Mean error between imputed and SILA‐estimated age at A+ ( N = 26) was 1.15 years. Age at A+ explained 39% of estimated years to symptom onset (EYO) variance. Time from A+ explained 19% of cognitive composite variance and 14% of Clinical Dementia Rating Sum of Boxes CDR‐SB variance; EYO explained 43% and 57%, respectively. DISCUSSION SILA estimates A+ age in ADAD with reasonably good accuracy. SILA‐estimated time from A+ describes the start of pathology, but the time from A+ onset to symptoms is variable in ADAD and better described by EYO. Highlights Amyloid chronicity predicts a 14‐year preclinical AD phase in ADAD. SILA accurately estimates age at A+ (MAE < 2 years). EYO outperforms chronicity in predicting symptom onset. APP mutation carriers show atypical amyloid accumulation. Chronicity models help reveal AD heterogeneity in preclinical stages.

AbstractBackgroundAdults with Down Syndrome (DS) develop Alzheimer disease (AD)‐like pathology and dementia as they age. This is attributed to triplication of the amyloid precursor protein gene. Recent work demonstrated that amyloid is elevated in DS and accumulates in a similar topography to autosomal dominant AD (ADAD). Tau accumulation is the second hallmark of AD and may be measured using tau positron emission tomography (PET) imaging. The pattern of tau accumulation remains unknown in DS.MethodIn a cross‐sectional analysis we evaluated amyloid and tau positron emission tomography (PET) in 124 participants with DS (109 cognitively stable, 8 symptomatic, 7 no consensus), 29 ADAD mutation carriers (26 asymptomatic, 3 symptomatic), and 201 cognitively normal non‐mutation carriers (CN). Regional cortical standard uptake value ratios (SUVR) for tau imaging were obtained and compared by cognitive status. Similarly, regional cortical amyloid SUVR were obtained and converted to centiloids. We then compared the magnitude of tau burden as well as spatial spread of tau across groups relative to amyloid burden.ResultCompared to CN, tau PET binding was elevated in participants with (µDS = 2.12 ± 0.22 SUVR, µADAD = 2.52 ± 0.37 SUVR) and without (µDS = 1.24 ± 0.15 SUVR, µADAD = 1.16 ± 0.19 SUVR) cognitive changes. For both groups, tau increased with increasing amyloid (centiloids). In some regions, DS had greater tau burden for a given amyloid level (centiloids) (Figure 1). There was increased spatial distribution of tau throughout the brain for participants with DS compared to CN. In contrast, tau burden was more focal in participants with ADAD with tau primarily elevated in posterior regions (Figure 2).ConclusionWhile tau burden was higher with symptomatic disease for both groups, significant differences existed in the overall amount and spatial spread. Tau spread was greatest in participants with DS and more diffuse compared to ADAD. These results indicate a substantial tau burden is present in DS, and suggest not only anti‐amyloid but also tau‐reducing agents should be considered for treating cognitive decline in adults with DS.

AbstractINTRODUCTIONDown syndrome (DS) is a genetic cause of early‐onset Alzheimer's disease (AD). The National Institute on Aging–Alzheimer's Association AT(N) Research Framework is a staging model for AD biomarkers but has not been assessed in DS.METHODData are from the Alzheimer's Biomarker Consortium–Down Syndrome. Positron emission tomography (PET) amyloid beta (Aβ; 15 mCi of [11C]Pittsburgh compound B) and tau (10 mCi of [18F]AV‐1451) were used to classify amyloid (A) –/+ and tau (T) +/–. Hippocampal volume classified neurodegeneration (N) –/+. The modified Cued Recall Test assessed episodic memory.RESULTSAnalyses included 162 adults with DS (aged M = 38.84 years, standard deviation = 8.41). Overall, 69.8% of participants were classified as A–/T–/(N)–, 11.1% were A+/T–/(N)–, 5.6% were A+/T+/(N)–, and 9.3% were A+/T+/(N)+. Participants deemed cognitively stable were most likely to be A–T–(N)– and A+T–(N)–. Tau PET (T+) most closely aligning with memory impairment and AD clinical status.DISCUSSIONFindings add to understanding of AT(N) biomarker profiles in DS.Highlights Overall, 69.8% of adults with Down syndrome (DS) aged 25 to 61 years were classified as amyloid (A)–/tau (T)–/neurodegeneration (N)–, 11.1% were A+/T–/(N)–, 5.6% were A+/T+/(N)–, and 9.3% were A+/T+/(N)+. The AT(N) profiles were associated with clinical Alzheimer's disease (AD) status and with memory performance, with the presence of T+ aligned with AD clinical symptomology. Findings inform models for predicting the transition to the prodromal stage of AD in DS.