Citations

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 The cortical asymmetry index evaluates the cortical thickness asymmetry between hemispheres. We investigated cortical asymmetry index in asymptomatic and symptomatic mutation carriers of autosomal dominant Alzheimer’s disease to explore the brain asymmetry within the Alzheimer’s disease continuum. Sixty baseline T1-weighted MRI scans were obtained from the Clinic Barcelona cohort. Baseline and longitudinal MRI data from 564 participants within the dominantly inherited Alzheimer network observational study were used as an independent, confirmatory cohort. Cerebrospinal fluid and plasma neurofilament light chain levels were included when available. Cortical thickness was calculated using Freesurfer and cortical asymmetry index was calculated via an open-source pipeline. Cross-sectional analyses examined cortical asymmetry index differences based on clinical classification and APOE ε4 status, adjusting for age, sex and estimated years from onset, while correlations were assessed with age, estimated years from onset, mini-mental state examination scores, and neurofilament light. Longitudinal cortical asymmetry index evolution was modelled using generalized additive models in the dominantly inherited Alzheimer network observational study cohort, incorporating age, sex, and the interaction between group and estimated years from onset. The cortical asymmetry index successfully distinguished asymptomatic mutation carrier and symptomatic mutation carriers from healthy controls in the Clinic Barcelona cohort and symptomatic mutation carriers from controls in dominantly inherited Alzheimer network observational study. Higher cortical asymmetry index in mutation carriers (asymptomatic mutation carrier and symptomatic mutation carriers combined) and in symptomatic mutation carriers were associated with higher plasma neurofilament light levels, a closer proximity to symptom onset, and lower mini-mental state examination in the Clinic Barcelona cohort. In the dominantly inherited Alzheimer network observational study cohort, mutation carriers exhibited increased cortical asymmetry index compared to controls and correlated with elevated neurofilament light (plasma and Cerebrospinal fluid), lower mini-mental state examination, and a closer proximity to symptom onset. APOE3/3 carriers showed greater asymmetry than other APOE genotypes and significant cortical asymmetry index differences between asymptomatic mutation carrier and symptomatic mutation carriers. Longitudinally, cortical asymmetry index increased over time significantly in symptomatic mutation carriers. These findings underscore brain asymmetry as a potential biomarker for early Alzheimer’s disease progression in autosomal dominant Alzheimer’s disease, with implications for detection and monitoring tracking disease-related neuroanatomical changes.

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.

Abstract BACKGROUND Tau‐derived cerebrospinal fluid (CSF) biomarkers correlate with amyloid‐beta (Aβ) plaques or tau tangles in Alzheimer's disease (AD). This study assessed the effects of long‐term anti‐Aβ antibodies on amyloid plaques, tau tangles, and CSF tau species to determine the relationships between them. METHODS A post‐hoc analysis of the DIAN‐TU‐001 trial (NCT01760005) examined 142 participants at risk for dominantly inherited AD randomized to solanezumab ( n = 50), gantenerumab ( n = 52), or placebo ( n = 40). High‐resolution mass spectrometry quantified CSF tau species over four years. RESULTS Phosphorylated tau (p‐tau) species (153, 181, 217, 231) increased early in preclinical AD but were reduced with gantenerumab‐mediated Aβ plaque reduction. Nearly a decade later, MTBR‐tau243 and p‐tau205 increased, showing no association with Aβ reduction, aligning with tau tangle pathology progression. DISCUSSION Initially changing soluble p‐tau species track Aβ plaque reduction, while ptau205 and MTBR‐243 reflect tau tangle pathology, informing different pathways of therapeutic strategies. Highlights p‐tau217 and p‐tau231 correlate with Aβ‐PET and respond to Aβ‐plaque lowering therapies. Aβ immunotherapy trials support a direct link between p‐tau changes and Aβ plaques Gantenerumab reduces Aβ plaques but does not affect tau NFT‐related biomarkers. Blood‐based p‐tau217 assays may provide a non‐invasive tool to monitor Aβ therapies. MTBR‐tau243 strongly correlates with tau PET and tracks NFT pathology progression. Further studies are needed to validate tau biomarkers for tracking NFT‐targeting therapies.

Abstract INTRODUCTION Monoclonal anti‐amyloid therapies are now accessible, but how these treatments influence changes within the brain is still not clear. We investigated overall and regional change in amyloid removal, glucose metabolism, and atrophy in trial participants with dominantly inherited Alzheimer's disease (DIAD). METHODS In the DIAN‐TU‐001 trial, 92 carriers received gantenerumab or placebo and underwent serial neuroimaging assessments including [ 11 C]‐Pittsburgh compound‐B (PiB) positron emission tomography (PET), [ 18 F]‐fluoro‐2‐deoxyglucose (FDG) PET, and magnetic resonance imaging (MRI). RESULTS Gantenerumab significantly reduced PiB‐PET uptake overall and in most regions and showed no changes in FDG‐PET or MRI measures. Drug effects were associated with baseline PiB‐PET uptake, and the largest effects occurred in medial regions. DISCUSSION Treated DIAD participants, and especially those with higher amyloid burden, showed a decrease in PiB‐PET uptake, which was more pronounced in the basal ganglia and medial frontal structures. These results may inform patient response and future drug trial design. Highlights Gantenerumab unevenly decreased Aβ burden as measured by PiB‐PET across brain regions. The strongest decrease in PiB‐PET uptake was in basal ganglia and medial frontal structures. Variable drug effect on Aβ was partly due to the amount of burden present before treatment. There was no regional effect on FDG‐PET metabolism or MRI volumetrics after 4 years.

Abstract We present a comprehensive global analysis of genetic variants associated with autosomal-dominant Alzheimer’s disease (ADAD). A total of 550 variants in the APP, PSEN1 and PSEN2 genes were identified, of which 279 were classified as pathogenic or likely pathogenic based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology criteria, utilizing data from the Dominantly Inherited Alzheimer Network (DIAN), literature and public databases. Symptomatic age at onset (AAO) data were estimated for 227 of these variants, allowing detailed characterization of their frequency, pathogenicity and AAO. Importantly, 226 variants met eligibility criteria for inclusion in disease-modifying clinical trials. Furthermore, we demonstrated the predictive value of mean variant AAO and parental AAO in predicting symptomatic AAO, validated against converters who became symptomatic during follow-up in the DIAN Observational Study. This dataset provides critical insights into the global landscape of ADAD and reveals the genetic and AAO heterogeneity of ADAD variants while refining variant trial eligibility criteria.

Abstract Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer’s disease (AD). Computational simulations and animal experiments have hinted at the theory of activity-dependent degeneration as the cause of this hub vulnerability. However, two critical issues remain unresolved. First, past research has not clearly distinguished between two scenarios: hub regions facing a higher risk of connectivity disruption (targeted attack) and all regions having an equal risk (random attack). Second, human studies offering support for activity-dependent explanations remain scarce. We refined the hub disruption index to demonstrate a hub disruption pattern in functional connectivity in autosomal dominant AD that aligned with targeted attacks. This hub disruption is detectable even in preclinical stages, 12 years before the expected symptom onset and is amplified alongside symptomatic progression. Moreover, hub disruption was primarily tied to regional differences in global connectivity and sequentially followed changes observed in amyloid-beta positron emission tomography cortical markers, consistent with the activity-dependent degeneration explanation. Taken together, our findings deepen the understanding of brain network organization in neurodegenerative diseases and could be instrumental in refining diagnostic and targeted therapeutic strategies for AD in the future.

AbstractINTRODUCTIONWhile Latin America (LatAm) is facing an increasing burden of dementia due to the rapid aging of the population, it remains underrepresented in dementia research, diagnostics, and care.METHODSIn 2023, the Alzheimer's Association hosted its eighth satellite symposium in Mexico, highlighting emerging dementia research, priorities, and challenges within LatAm.RESULTSSignificant initiatives in the region, including intracountry support, showcased their efforts in fostering national and international collaborations; genetic studies unveiled the unique genetic admixture in LatAm; researchers conducting emerging clinical trials discussed ongoing culturally specific interventions; and the urgent need to harmonize practices and studies, improve diagnosis and care, and use affordable biomarkers in the region was highlighted.DISCUSSIONThe myriad of topics discussed at the 2023 AAIC satellite symposium highlighted the growing research efforts in LatAm, providing valuable insights into dementia biology, genetics, epidemiology, treatment, and care.