Utilizing the Centiloid scale in cross-sectional and longitudinal PiB PET studies

Predicting Driving Cessation Among Cognitively Normal Older Drivers: The Role of Alzheimer Disease Biomarkers and Clinical Assessments

BACKGROUND AND OBJECTIVES

With the aging US population and increasing incidence of Alzheimer disease (AD), understanding factors contributing to driving cessation among older adults is crucial for clinicians. Driving is integral for maintaining independence and functional mobility, but the risk factors for driving cessation, particularly in the context of normal aging and preclinical AD, are not well understood. We studied a well-characterized community cohort to examine factors associated with driving cessation.

METHODS

This prospective, longitudinal observation study enrolled participants from the Knight Alzheimer Disease Research Center and The DRIVES Project. Participants were enrolled if they were aged 65 years or older, drove weekly, and were cognitively normal (Clinical Dementia Rating [CDR] = 0) at baseline. Participants underwent annual clinical, neurologic, and neuropsychological assessments, including β-amyloid PET imaging and CSF (Aβ42, total tau [t-Tau], and phosphorylated tau [p-Tau]) collection every 2-3 years. The primary outcome was time from baseline visit to driving cessation, accounting for death as a competing risk. The cumulative incidence function of driving cessation was estimated for each biomarker. The Fine and Gray subdistribution hazard model was used to examine the association between time to driving cessation and biomarkers adjusting for clinical and demographic covariates.

RESULTS

Among the 283 participants included in this study, there was a mean follow-up of 5.62 years. Driving cessation (8%) was associated with older age, female sex, progression to symptomatic AD (CDR ≥0.5), and poorer performance on a preclinical Alzheimer cognitive composite (PACC) score. Aβ PET imaging did not independently predict driving cessation, whereas CSF biomarkers, specifically t-Tau/Aβ42 (hazard ratio [HR] 2.82, 95% CI 1.23-6.44, p = 0.014) and p-Tau/Aβ42 (HR 2.91, 95% CI 1.28-6.59, p = 0.012) ratios, were independent predictors in the simple model adjusting for age, education, and sex. However, in the full model, progression to cognitive impairment based on the CDR and PACC score across each model was associated with a higher risk of driving cessation, whereas AD biomarkers were not statistically significant.

DISCUSSION

Female sex, CDR progression, and neuropsychological measures of cognitive functioning obtained in the clinic were strongly associated with future driving cessation. The results emphasize the need for early planning and conversations about driving retirement in the context of cognitive decline and the immense value of clinical measures in determining functional outcomes.

Associations Between Self and Study Partner Report of Cognitive Decline With Regional Tau in a Multicohort Study

BACKGROUND AND OBJECTIVES

Self-reported cognitive decline is an early behavioral manifestation of Alzheimer disease (AD) at the preclinical stage, often believed to precede concerns reported by a study partner. Previous work shows cross-sectional associations with β-amyloid (Aβ) status and self-reported and study partner-reported cognitive decline, but less is known about their associations with tau deposition, particularly among those with preclinical AD.

METHODS

This cross-sectional study included participants from the Anti-Amyloid Treatment in Asymptomatic AD/Longitudinal Evaluation of Amyloid Risk and Neurodegeneration studies (N = 444) and the Harvard Aging Brain Study and affiliated studies (N = 231), which resulted in a cognitively unimpaired (CU) sample of individuals with both nonelevated (Aβ-) and elevated Aβ (Aβ+). All participants and study partners completed the Cognitive Function Index (CFI). Two regional tau composites were derived by averaging flortaucipir PET uptake in the medial temporal lobe (MTL) and neocortex (NEO). Global Aβ PET was measured in Centiloids (CLs) with Aβ+ >26 CL. We conducted multiple linear regression analyses to test associations between tau PET and CFI, covarying for amyloid, age, sex, education, and cohort. We also controlled for objective cognitive performance, measured using the Preclinical Alzheimer Cognitive Composite (PACC).

RESULTS

Across 675 CU participants (age = 72.3 ± 6.6 years, female = 59%, Aβ+ = 60%), greater tau was associated with greater self-CFI (MTL: β = 0.28 [0.12, 0.44], p < 0.001, and NEO: β = 0.26 [0.09, 0.42], p = 0.002) and study partner CFI (MTL: β = 0.28 [0.14, 0.41], p < 0.001, and NEO: β = 0.31 [0.17, 0.44], p < 0.001). Significant associations between both CFI measures and MTL/NEO tau PET were driven by Aβ+. Continuous Aβ showed an independent effect on CFI in addition to MTL and NEO tau for both self-CFI and study partner CFI. Self-CFI (β = 0.01 [0.001, 0.02], p = 0.03), study partner CFI (β = 0.01 [0.003, 0.02], p = 0.01), and the PACC (β = -0.02 [-0.03, -0.01], p < 0.001) were independently associated with MTL tau, but for NEO tau, PACC (β = -0.02 [-0.03, -0.01], p < 0.001) and study partner report (β = 0.01 [0.004, 0.02], p = 0.002) were associated, but not self-CFI (β = 0.01 [-0.001, 0.02], p = 0.10).

DISCUSSION

Both self-report and study partner report showed associations with tau in addition to Aβ. Additionally, self-report and study partner report were associated with tau above and beyond performance on a neuropsychological composite. Stratification analyses by Aβ status indicate that associations between self-reported and study partner-reported cognitive concerns with regional tau are driven by those at the preclinical stage of AD, suggesting that both are useful to collect on the early AD continuum.

Data-driven decomposition and staging of flortaucipir uptake in Alzheimer's disease

INTRODUCTION

Previous approaches pursuing in vivo staging of tau pathology in Alzheimer's disease (AD) have typically relied on neuropathologically defined criteria. In using predefined systems, these studies may miss spatial deposition patterns which are informative of disease progression.

METHODS

We selected discovery (n = 418) and replication (n = 132) cohorts with flortaucipir imaging. Non-negative matrix factorization (NMF) was applied to learn tau covariance patterns and develop a tau staging system. Flortaucipir components were also validated by comparison with amyloid burden, gray matter loss, and the expression of AD-related genes.

RESULTS

We found eight flortaucipir covariance patterns which were reproducible and overlapped with relevant gene expression maps. Tau stages were associated with AD severity as indexed by dementia status and neuropsychological performance. Comparisons of flortaucipir uptake with amyloid and atrophy also supported our model of tau progression.

DISCUSSION

Data-driven decomposition of flortaucipir uptake provides a novel framework for tau staging which complements existing systems.

HIGHLIGHTS

NMF reveals patterns of tau deposition in AD. Data-driven staging of flortaucipir tracks AD severity. Learned flortaucipir patterns overlap with AD-related gene expression.

Quantitative Brain Amyloid PET

Since the development of amyloid tracers for PET imaging, there has been interest in quantifying amyloid burden in the brains of patients with Alzheimer disease. Quantitative amyloid PET imaging is poised to become a valuable approach in disease staging, theranostics, monitoring, and as an outcome measure for interventional studies. Yet, there are significant challenges and hurdles to overcome before it can be implemented into widespread clinical practice. On November 17, 2022, the U.S. Food and Drug Administration, Society of Nuclear Medicine and Molecular Imaging, and Medical Imaging and Technology Alliance cosponsored a public workshop comprising experts from academia, industry, and government agencies to discuss the role of quantitative brain amyloid PET imaging in staging, prognosis, and longitudinal assessment of Alzheimer disease. The workshop discussed a range of topics, including available radiopharmaceuticals for amyloid imaging; the methodology, metrics, and analytic validity of quantitative amyloid PET imaging; its use in disease staging, prognosis, and monitoring of progression; and challenges facing the field. This report provides a high-level summary of the presentations and the discussion.

Timing of Biomarker Changes in Sporadic Alzheimer's Disease in Estimated Years from Symptom Onset

OBJECTIVE

A clock relating amyloid positron emission tomography (PET) to time was used to estimate the timing of biomarker changes in sporadic Alzheimer disease (AD).

METHODS

Research participants were included who underwent cerebrospinal fluid (CSF) collection within 2 years of amyloid PET. The ages at amyloid onset and AD symptom onset were estimated for each individual. The timing of change for plasma, CSF, imaging, and cognitive measures was calculated by comparing restricted cubic splines of cross-sectional data from the amyloid PET positive and negative groups.

RESULTS

The amyloid PET positive sub-cohort (n = 118) had an average age of 70.4 ± 7.4 years (mean ± standard deviation) and 16% were cognitively impaired. The amyloid PET negative sub-cohort (n = 277) included individuals with low levels of amyloid plaque burden at all scans who were cognitively unimpaired at the time of the scans. Biomarker changes were detected 15-19 years before estimated symptom onset for CSF Aβ42/Aβ40, plasma Aβ42/Aβ40, CSF pT217/T217, and amyloid PET; 12-14 years before estimated symptom onset for plasma pT217/T217, CSF neurogranin, CSF SNAP-25, CSF sTREM2, plasma GFAP, and plasma NfL; and 7-9 years before estimated symptom onset for CSF pT205/T205, CSF YKL-40, hippocampal volumes, and cognitive measures.

INTERPRETATION

The use of an amyloid clock enabled visualization and analysis of biomarker changes as a function of estimated years from symptom onset in sporadic AD. This study demonstrates that estimated years from symptom onset based on an amyloid clock can be used as a continuous staging measure for sporadic AD and aligns with findings in autosomal dominant AD. ANN NEUROL 2024;95:951-965.

Investigating reliable amyloid accumulation in Centiloids: Results from the AMYPAD Prognostic and Natural History Study

INTRODUCTION

To support clinical trial designs focused on early interventions, our study determined reliable early amyloid-β (Aβ) accumulation based on Centiloids (CL) in pre-dementia populations.

METHODS

A total of 1032 participants from the Amyloid Imaging to Prevent Alzheimer's Disease-Prognostic and Natural History Study (AMYPAD-PNHS) and Insight46 who underwent [18F]flutemetamol, [18F]florbetaben or [18F]florbetapir amyloid-PET were included. A normative strategy was used to define reliable accumulation by estimating the 95th percentile of longitudinal measurements in sub-populations (NPNHS = 101/750, NInsight46 = 35/382) expected to remain stable over time. The baseline CL threshold that optimally predicts future accumulation was investigated using precision-recall analyses. Accumulation rates were examined using linear mixed-effect models.

RESULTS

Reliable accumulation in the PNHS was estimated to occur at >3.0 CL/year. Baseline CL of 16 [12,19] best predicted future Aβ-accumulators. Rates of amyloid accumulation were tracer-independent, lower for APOE ε4 non-carriers, and for subjects with higher levels of education.

DISCUSSION

Our results support a 12-20 CL window for inclusion into early secondary prevention studies. Reliable accumulation definition warrants further investigations.

Expression of regional brain amyloid-β deposition with [18F]Flutemetamol in Centiloid scale -a multi-site study

PURPOSE

The Centiloid project helps calibrate the quantitative amyloid-β (Aβ) load into a unified Centiloid (CL) scale that allows data comparison across multi-site. How the smaller regional amyloid converted into CL has not been attempted. We first aimed to express regional Aβ deposition in CL using [18F]Flutemetamol and evaluate regional Aβ deposition in CL with that in standardized uptake value ratio (SUVr). Second, we aimed to determine the presence or absence of focal Aβ deposition by measuring regional CL in equivocal cases showing negative global CL.

METHODS

Following the Centiloid project pipeline, Level-1 replication, Level-2 calibration, and quality control were completed to generate corresponding Centiloid conversion equations to convert SUVr into Centiloid at regional levels. In equivocal cases, the regional CL was compared with visual inspection to evaluate regional Aβ positivity.

RESULTS

14 out of 16 regional conversions from [18F]Flutemetamol SUVr to Centiloid successfully passed the quality control, showing good reliability and relative variance, especially precuneus/posterior cingulate and prefrontal regions with good stability for Centiloid scaling. The absence of focal Aβ deposition could be detected by measuring regional CL, showing a high agreement rate with visual inspection. The regional Aβ positivity in the bilateral anterior cingulate cortex was most prevalent in equivocal cases.

CONCLUSION

The expression of regional brain Aβ deposition in CL with [18F]Flutemetamol has been attempted in this study. Equivocal cases had focal Aβ deposition that can be detected by measuring regional CL.

Comparison of cerebrospinal fluid, plasma and neuroimaging biomarker utility in Alzheimer's disease

Alzheimer's disease biomarkers are crucial to understanding disease pathophysiology, aiding accurate diagnosis and identifying target treatments. Although the number of biomarkers continues to grow, the relative utility and uniqueness of each is poorly understood as prior work has typically calculated serial pairwise relationships on only a handful of markers at a time. The present study assessed the cross-sectional relationships among 27 Alzheimer's disease biomarkers simultaneously and determined their ability to predict meaningful clinical outcomes using machine learning. Data were obtained from 527 community-dwelling volunteers enrolled in studies at the Charles F. and Joanne Knight Alzheimer Disease Research Center at Washington University in St Louis. We used hierarchical clustering to group 27 imaging, CSF and plasma measures of amyloid beta, tau [phosphorylated tau (p-tau), total tau t-tau)], neuronal injury and inflammation drawn from MRI, PET, mass-spectrometry assays and immunoassays. Neuropsychological and genetic measures were also included. Random forest-based feature selection identified the strongest predictors of amyloid PET positivity across the entire cohort. Models also predicted cognitive impairment across the entire cohort and in amyloid PET-positive individuals. Four clusters emerged reflecting: core Alzheimer's disease pathology (amyloid and tau), neurodegeneration, AT8 antibody-associated phosphorylated tau sites and neuronal dysfunction. In the entire cohort, CSF p-tau181/Aβ40lumi and Aβ42/Aβ40lumi and mass spectrometry measurements for CSF pT217/T217, pT111/T111, pT231/T231 were the strongest predictors of amyloid PET status. Given their ability to denote individuals on an Alzheimer's disease pathological trajectory, these same markers (CSF pT217/T217, pT111/T111, p-tau/Aβ40lumi and t-tau/Aβ40lumi) were largely the best predictors of worse cognition in the entire cohort. When restricting analyses to amyloid-positive individuals, the strongest predictors of impaired cognition were tau PET, CSF t-tau/Aβ40lumi, p-tau181/Aβ40lumi, CSF pT217/217 and pT205/T205. Non-specific CSF measures of neuronal dysfunction and inflammation were poor predictors of amyloid PET and cognitive status. The current work utilized machine learning to understand the interrelationship structure and utility of a large number of biomarkers. The results demonstrate that, although the number of biomarkers has rapidly expanded, many are interrelated and few strongly predict clinical outcomes. Examining the entire corpus of available biomarkers simultaneously provides a meaningful framework to understand Alzheimer's disease pathobiological change as well as insight into which biomarkers may be most useful in Alzheimer's disease clinical practice and trials.

Relationships of Cognitive Measures with Cerebrospinal Fluid but Not Imaging Biomarkers of Alzheimer Disease Vary between Black and White Individuals

OBJECTIVE

Biomarkers of Alzheimer disease vary between groups of self-identified Black and White individuals in some studies. This study examined whether the relationships between biomarkers or between biomarkers and cognitive measures varied by racialized groups.

METHODS

Cerebrospinal fluid (CSF), amyloid positron emission tomography (PET), and magnetic resonance imaging measures were harmonized across four studies of memory and aging. Spearman correlations between biomarkers and between biomarkers and cognitive measures were calculated within each racialized group, then compared between groups by standard normal tests after Fisher's Z-transformations.

RESULTS

The harmonized dataset included at least one biomarker measurement from 495 Black and 2,600 White participants. The mean age was similar between racialized groups. However, Black participants were less likely to have cognitive impairment (28% vs 36%) and had less abnormality of some CSF biomarkers including CSF Aβ42/40, total tau, p-tau181, and neurofilament light. CSF Aβ42/40 was negatively correlated with total tau and p-tau181 in both groups, but at a smaller magnitude in Black individuals. CSF Aβ42/40, total tau, and p-tau181 had weaker correlations with cognitive measures, especially episodic memory, in Black than White participants. Correlations of amyloid measures between CSF (Aβ42/40, Aβ42) and PET imaging were also weaker in Black than White participants. Importantly, no differences based on race were found in correlations between different imaging biomarkers, or in correlations between imaging biomarkers and cognitive measures.

INTERPRETATION

Relationships between CSF biomarkers but not imaging biomarkers varied by racialized groups. Imaging biomarkers performed more consistently across racialized groups in associations with cognitive measures. ANN NEUROL 2024;95:495-506.

Harmonizing florbetapir and PiB PET measurements of cortical Aβ plaque burden using multiple regions-of-interest and machine learning techniques: An alternative to the Centiloid approach

INTRODUCTION

Machine learning (ML) can optimize amyloid (Aβ) comparability among positron emission tomography (PET) radiotracers. Using multi-regional florbetapir (FBP) measures and ML, we report better Pittsburgh compound-B (PiB)/FBP harmonization of mean-cortical Aβ (mcAβ) than Centiloid.

METHODS

PiB-FBP pairs from 92 subjects in www.oasis-brains.org and 46 in www.gaain.org/centiloid-project were used as the training/testing sets. FreeSurfer-extracted FBP multi-regional Aβ and actual PiB mcAβ in the training set were used to train ML models generating synthetic PiB mcAβ. The correlation coefficient (R) between the synthetic/actual PiB mcAβ in the testing set was assessed.

RESULTS

In the testing set, the synthetic/actual PiB mcAβ correlation R = 0.985 (R2  = 0.970) using artificial neural network was significantly higher (p ≤ 6.6e-4) than the FBP/PiB correlation R = 0.927 (R2  = 0.860), improving total variance percentage (R2 ) from 86% to 97%. Other ML models such as partial least square, ensemble, and relevance vector regressions also improved R (p = 9.677e-05 /0.045/0.0017).

DISCUSSION

ML improved mcAβ comparability. Additional studies are needed for the generalizability to other amyloid tracers, and to tau PET. Highlights Centiloid is a calibration of the amyloid scale, not harmonization. Centiloid unifies the amyloid scale without improving inter-tracer association (R2 ). Machine learning (ML) can harmonize the amyloid scale by improving R2 . ML harmonization maps multi-regional florbetapir SUVRs to PiB mean-cortical SUVR. Artificial neural network ML increases Centiloid R2 from 86% to 97%.

Impact of simulated reduced injected dose on the assessment of amyloid PET scans

PURPOSE

To investigate the impact of reduced injected doses on the quantitative and qualitative assessment of the amyloid PET tracers [18F]flutemetamol and [18F]florbetaben.

METHODS

Cognitively impaired and unimpaired individuals (N = 250, 36% Aβ-positive) were included and injected with [18F]flutemetamol (N = 175) or [18F]florbetaben (N = 75). PET scans were acquired in list-mode (90-110 min post-injection) and reduced-dose images were simulated to generate images of 75, 50, 25, 12.5 and 5% of the original injected dose. Images were reconstructed using vendor-provided reconstruction tools and visually assessed for Aβ-pathology. SUVRs were calculated for a global cortical and three smaller regions using a cerebellar cortex reference tissue, and Centiloid was computed. Absolute and percentage differences in SUVR and CL were calculated between dose levels, and the ability to discriminate between Aβ- and Aβ + scans was evaluated using ROC analyses. Finally, intra-reader agreement between the reduced dose and 100% images was evaluated.

RESULTS

At 5% injected dose, change in SUVR was 3.72% and 3.12%, with absolute change in Centiloid 3.35CL and 4.62CL, for [18F]flutemetamol and [18F]florbetaben, respectively. At 12.5% injected dose, percentage change in SUVR and absolute change in Centiloid were < 1.5%. AUCs for discriminating Aβ- from Aβ + scans were high (AUC ≥ 0.94) across dose levels, and visual assessment showed intra-reader agreement of > 80% for both tracers.

CONCLUSION

This proof-of-concept study showed that for both [18F]flutemetamol and [18F]florbetaben, adequate quantitative and qualitative assessments can be obtained at 12.5% of the original injected dose. However, decisions to reduce the injected dose should be made considering the specific clinical or research circumstances.

Baseline levels and longitudinal rates of change in plasma Aβ42/40 among self-identified Black/African American and White individuals

Objective

The use of blood-based biomarkers of Alzheimer disease (AD) may facilitate access to biomarker testing of groups that have been historically under-represented in research. We evaluated whether plasma Aβ42/40 has similar or different baseline levels and longitudinal rates of change in participants racialized as Black or White.

Methods

The Study of Race to Understand Alzheimer Biomarkers (SORTOUT-AB) is a multi-center longitudinal study to evaluate for potential differences in AD biomarkers between individuals racialized as Black or White. Plasma samples collected at three AD Research Centers (Washington University, University of Pennsylvania, and University of Alabama-Birmingham) underwent analysis with C2N Diagnostics' PrecivityAD™ blood test for Aβ42 and Aβ40. General linear mixed effects models were used to estimate the baseline levels and rates of longitudinal change for plasma Aβ measures in both racial groups. Analyses also examined whether dementia status, age, sex, education, APOE ε4 carrier status, medical comorbidities, or fasting status modified potential racial differences.

Results

Of the 324 Black and 1,547 White participants, there were 158 Black and 759 White participants with plasma Aβ measures from at least two longitudinal samples over a mean interval of 6.62 years. At baseline, the group of Black participants had lower levels of plasma Aβ40 but similar levels of plasma Aβ42 as compared to the group of White participants. As a result, baseline plasma Aβ42/40 levels were higher in the Black group than the White group, consistent with the Black group having lower levels of amyloid pathology. Racial differences in plasma Aβ42/40 were not modified by age, sex, education, APOE ε4 carrier status, medical conditions (hypertension and diabetes), or fasting status. Despite differences in baseline levels, the Black and White groups had a similar longitudinal rate of change in plasma Aβ42/40.

Interpretation

Black individuals participating in AD research studies had a higher mean level of plasma Aβ42/40, consistent with a lower level of amyloid pathology, which, if confirmed, may imply a lower proportion of Black individuals being eligible for AD clinical trials in which the presence of amyloid is a prerequisite. However, there was no significant racial difference in the rate of change in plasma Aβ42/40, suggesting that amyloid pathology accumulates similarly across racialized groups.

Characterizing the emergence of amyloid and tau burden in Down syndrome

INTRODUCTION

Almost all individuals with Down syndrome (DS) will develop neuropathological features of Alzheimer's disease (AD). Understanding AD biomarker trajectories is necessary for DS-specific clinical interventions and interpretation of drug-related changes in the disease trajectory.

METHODS

A total of 177 adults with DS from the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) underwent positron emission tomography (PET) and MR imaging. Amyloid-beta (Aβ) trajectories were modeled to provide individual-level estimates of Aβ-positive (A+) chronicity, which were compared against longitudinal tau change.

RESULTS

Elevated tau was observed in all NFT regions following A+ and longitudinal tau increased with respect to A+ chronicity. Tau increases in NFT regions I-III was observed 0-2.5 years following A+. Nearly all A+ individuals had tau increases in the medial temporal lobe.

DISCUSSION

These findings highlight the rapid accumulation of amyloid and early onset of tau relative to amyloid in DS and provide a strategy for temporally characterizing AD neuropathology progression that is specific to the DS population and independent of chronological age.

HIGHLIGHTS

Longitudinal amyloid trajectories reveal rapid Aβ accumulation in Down syndrome NFT stage tau was strongly associated with A+ chronicity Early longitudinal tau increases were observed 2.5-5 years after reaching A.

Combining Blood-Based Biomarkers and Structural MRI Measurements to Distinguish Persons with and without Significant Amyloid Plaques

Background

Amyloid-β (Aβ) plaques play a pivotal role in Alzheimer's disease. The current positron emission tomography (PET) is expensive and limited in availability. In contrast, blood-based biomarkers (BBBMs) show potential for characterizing Aβ plaques more affordably. We have previously proposed an MRI-based hippocampal morphometry measure to be an indicator of Aβ plaques.

Objective

To develop and validate an integrated model to predict brain amyloid PET positivity combining MRI feature and plasma Aβ42/40 ratio.

Methods

We extracted hippocampal multivariate morphometry statistics from MR images and together with plasma Aβ42/40 trained a random forest classifier to perform a binary classification of participant brain amyloid PET positivity. We evaluated the model performance using two distinct cohorts, one from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the other from the Banner Alzheimer's Institute (BAI), including prediction accuracy, precision, recall rate, F1 score, and AUC score.

Results

Results from ADNI (mean age 72.6, Aβ+ rate 49.5%) and BAI (mean age 66.2, Aβ+ rate 36.9%) datasets revealed the integrated multimodal (IMM) model's superior performance over unimodal models. The IMM model achieved prediction accuracies of 0.86 in ADNI and 0.92 in BAI, surpassing unimodal models based solely on structural MRI (0.81 and 0.87) or plasma Aβ42/40 (0.73 and 0.81) predictors.

CONCLUSIONS

Our IMM model, combining MRI and BBBM data, offers a highly accurate approach to predict brain amyloid PET positivity. This innovative multiplex biomarker strategy presents an accessible and cost-effective avenue for advancing Alzheimer's disease diagnostics, leveraging diverse pathologic features related to Aβ plaques and structural MRI.

Predicting cognitive decline: Which is more useful, baseline amyloid levels or longitudinal change?

The use of biomarkers for the early detection of Alzheimer's disease (AD) is crucial for developing potential therapeutic treatments. Positron Emission Tomography (PET) is a well-established tool used to detect β-amyloid (Aβ) plaques in the brain. Previous studies have shown that cross-sectional biomarkers can predict cognitive decline (Schindler et al.,2021). However, it is still unclear whether longitudinal Aβ-PET may have additional value for predicting time to cognitive impairment in AD. The current study aims to evaluate the ability of baseline- versus longitudinal rate of change in-11C-Pittsburgh compound B (PiB) Aβ-PET to predict cognitive decline. A cohort of 153 participants who previously underwent PiB-PET scans and comprehensive clinical assessments were used in this study. Our analyses revealed that baseline Aβ is significantly associated with the rate of change in cognitive composite scores, with cognition declining more rapidly when baseline PiB Aβ levels were higher. In contrast, no signification association was identified between the rate of change in PiB-PET Aβ and cognitive decline. Additionally, the ability of the rate of change in the PiB-PET measures to predict cognitive decline was significantly influenced by APOE ε4 carrier status. These results suggest that a single PiB-PET scan is sufficient to predict cognitive decline and that longitudinal measures of Aβ accumulation do not improve the prediction of cognitive decline once someone is amyloid positive.

T1 and FLAIR signal intensities are related to tau pathology in dominantly inherited Alzheimer disease

Carriers of mutations responsible for dominantly inherited Alzheimer disease provide a unique opportunity to study potential imaging biomarkers. Biomarkers based on routinely acquired clinical MR images, could supplement the extant invasive or logistically challenging) biomarker studies. We used 1104 longitudinal MR, 324 amyloid beta, and 87 tau positron emission tomography imaging sessions from 525 participants enrolled in the Dominantly Inherited Alzheimer Network Observational Study to extract novel imaging metrics representing the mean (μ) and standard deviation (σ) of standardized image intensities of T1-weighted and Fluid attenuated inversion recovery (FLAIR) MR scans. There was an exponential decrease in FLAIR-μ in mutation carriers and an increase in FLAIR and T1 signal heterogeneity (T1-σ and FLAIR-σ) as participants approached the symptom onset in both supramarginal, the right postcentral and right superior temporal gyri as well as both caudate nuclei, putamina, thalami, and amygdalae. After controlling for the effect of regional atrophy, FLAIR-μ decreased and T1-σ and FLAIR-σ increased with increasing amyloid beta and tau deposition in numerous cortical regions. In symptomatic mutation carriers and independent of the effect of regional atrophy, tau pathology demonstrated a stronger relationship with image intensity metrics, compared with amyloid pathology. We propose novel MR imaging intensity-based metrics using standard clinical T1 and FLAIR images which strongly associates with the progression of pathology in dominantly inherited Alzheimer disease. We suggest that tau pathology may be a key driver of the observed changes in this cohort of patients.

Neuropsychiatric Symptoms and Alzheimer Disease Biomarkers Independently Predict Progression to Incident Cognitive Impairment

OBJECTIVES

To investigate the effect of neuropsychiatric symptoms and depression symptoms, respectively, and Alzheimer disease (AD) biomarkers (cerebrospinal fluid [CSF] or Positron Emission Tomography [PET] imaging) on the progression to incident cognitive impairment among cognitively normal older adults.

DESIGN

Prospective, observation, longitudinal study.

SETTING

Knight Alzheimer Disease Research Center (ADRC) at Washington University School of Medicine.

PARTICIPANTS

Older adults aged 65 and above who participated in AD longitudinal studies (n = 286).

MEASUREMENTS

CSF and PET biomarkers, Clinical Dementia Rating (CDR), Geriatric Depression Scale (GDS), and Neuropsychiatric Inventory Questionnaire (NPI-Q).

RESULTS

Participants had an average follow-up of eight years, and 31 progressed from CDR 0 to CDR >0. After adjusting for sex, age, and education in the Cox proportional hazards survival models, neuropsychiatric symptoms as a time-dependent covariate was statistically significant in the three CSF (Aβ42/Aβ40, t-Tau/Aβ42, p-Tau/Aβ42) PET imaging models (HR = 1.33-1.50). The biomarkers were also significant as main effects (HR = 2.00-4.04). Change in depression symptoms was not significant in any models. The interactions between biomarkers and neuropsychiatric symptoms and depression were not statistically significant.

CONCLUSIONS

Changes in neuropsychiatric symptoms increase the risk of progression to cognitive impairment among healthy, cognitively normal adults, independent of AD biomarkers. Routine assessment of neuropsychiatric symptoms could provide valuable clinical information about cognitive functioning and preclinical disease state.

Determinants of physical activity engagement in older adults

In order to increase engagement in physical activity, it is important to determine which factors contribute to physical activity engagement in older adults. The current study examined the relative predictive ability of several potential determinants, in terms of both the concurrent level as well as longitudinal trajectories. Clinically normal adults aged 61-92 completed the Physical Activity Scale for the Elderly (n = 189 for cross-sectional models; n = 214 for longitudinal models). Potential determinants included age, gender, education, physical health, sensory health, mood, cardiovascular health, cognitive status, and biomarkers of Alzheimer disease (AD). We observed a novel finding that both concurrent physical health (p < 0.001) and change in physical health (p < 0.001) were significant predictors above and beyond other determinants. Concurrent mood predicted levels of physical activity (p = 0.035), particularly in females. These findings suggest that poor physical health and low mood might be important to consider as potential barriers to physical activity engagement in older adults.

Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods

PURPOSE

Amyloid positron emission tomography (PET) with [18F]florbetaben (FBB) is an established tool for detecting Aβ deposition in the brain in vivo based on visual assessment of PET scans. Quantitative measures are commonly used in the research context and allow continuous measurement of amyloid burden. The aim of this study was to demonstrate the robustness of FBB PET quantification.

METHODS

This is a retrospective analysis of FBB PET images from 589 subjects. PET scans were quantified with 15 analytical methods using nine software packages (MIMneuro, Hermes BRASS, Neurocloud, Neurology Toolkit, statistical parametric mapping (SPM8), PMOD Neuro, CapAIBL, non-negative matrix factorization (NMF), AmyloidIQ) that used several metrics to estimate Aβ load (SUVR, centiloid, amyloid load, and amyloid index). Six analytical methods reported centiloid (MIMneuro, standard centiloid, Neurology Toolkit, SPM8 (PET only), CapAIBL, NMF). All results were quality controlled.

RESULTS

The mean sensitivity, specificity, and accuracy were 96.1 ± 1.6%, 96.9 ± 1.0%, and 96.4 ± 1.1%, respectively, for all quantitative methods tested when compared to histopathology, where available. The mean percentage of agreement between binary quantitative assessment across all 15 methods and visual majority assessment was 92.4 ± 1.5%. Assessments of reliability, correlation analyses, and comparisons across software packages showed excellent performance and consistent results between analytical methods.

CONCLUSION

This study demonstrated that quantitative methods using both CE marked software and other widely available processing tools provided comparable results to visual assessments of FBB PET scans. Software quantification methods, such as centiloid analysis, can complement visual assessment of FBB PET images and could be used in the future for identification of early amyloid deposition, monitoring disease progression and treatment effectiveness.

Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN)

The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual's point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of 'sporadic' AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers.

Longitudinal head-to-head comparison of 11C-PiB and 18F-florbetapir PET in a Phase 2/3 clinical trial of anti-amyloid-β monoclonal antibodies in dominantly inherited Alzheimer's disease

PURPOSE

Pittsburgh Compound-B (11C-PiB) and 18F-florbetapir are amyloid-β (Aβ) positron emission tomography (PET) radiotracers that have been used as endpoints in Alzheimer's disease (AD) clinical trials to evaluate the efficacy of anti-Aβ monoclonal antibodies. However, comparing drug effects between and within trials may become complicated if different Aβ radiotracers were used. To study the consequences of using different Aβ radiotracers to measure Aβ clearance, we performed a head-to-head comparison of 11C-PiB and 18F-florbetapir in a Phase 2/3 clinical trial of anti-Aβ monoclonal antibodies.

METHODS

Sixty-six mutation-positive participants enrolled in the gantenerumab and placebo arms of the first Dominantly Inherited Alzheimer Network Trials Unit clinical trial (DIAN-TU-001) underwent both 11C-PiB and 18F-florbetapir PET imaging at baseline and during at least one follow-up visit. For each PET scan, regional standardized uptake value ratios (SUVRs), regional Centiloids, a global cortical SUVR, and a global cortical Centiloid value were calculated. Longitudinal changes in SUVRs and Centiloids were estimated using linear mixed models. Differences in longitudinal change between PET radiotracers and between drug arms were estimated using paired and Welch two sample t-tests, respectively. Simulated clinical trials were conducted to evaluate the consequences of some research sites using 11C-PiB while other sites use 18F-florbetapir for Aβ PET imaging.

RESULTS

In the placebo arm, the absolute rate of longitudinal change measured by global cortical 11C-PiB SUVRs did not differ from that of global cortical 18F-florbetapir SUVRs. In the gantenerumab arm, global cortical 11C-PiB SUVRs decreased more rapidly than global cortical 18F-florbetapir SUVRs. Drug effects were statistically significant across both Aβ radiotracers. In contrast, the rates of longitudinal change measured in global cortical Centiloids did not differ between Aβ radiotracers in either the placebo or gantenerumab arms, and drug effects remained statistically significant. Regional analyses largely recapitulated these global cortical analyses. Across simulated clinical trials, type I error was higher in trials where both Aβ radiotracers were used versus trials where only one Aβ radiotracer was used. Power was lower in trials where 18F-florbetapir was primarily used versus trials where 11C-PiB was primarily used.

CONCLUSION

Gantenerumab treatment induces longitudinal changes in Aβ PET, and the absolute rates of these longitudinal changes differ significantly between Aβ radiotracers. These differences were not seen in the placebo arm, suggesting that Aβ-clearing treatments may pose unique challenges when attempting to compare longitudinal results across different Aβ radiotracers. Our results suggest converting Aβ PET SUVR measurements to Centiloids (both globally and regionally) can harmonize these differences without losing sensitivity to drug effects. Nonetheless, until consensus is achieved on how to harmonize drug effects across radiotracers, and since using multiple radiotracers in the same trial may increase type I error, multisite studies should consider potential variability due to different radiotracers when interpreting Aβ PET biomarker data and, if feasible, use a single radiotracer for the best results.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01760005. Registered 31 December 2012. Retrospectively registered.

Gut microbiome composition may be an indicator of preclinical Alzheimer's disease

Alzheimer's disease (AD) pathology is thought to progress from normal cognition through preclinical disease and ultimately to symptomatic AD with cognitive impairment. Recent work suggests that the gut microbiome of symptomatic patients with AD has an altered taxonomic composition compared with that of healthy, cognitively normal control individuals. However, knowledge about changes in the gut microbiome before the onset of symptomatic AD is limited. In this cross-sectional study that accounted for clinical covariates and dietary intake, we compared the taxonomic composition and gut microbial function in a cohort of 164 cognitively normal individuals, 49 of whom showed biomarker evidence of early preclinical AD. Gut microbial taxonomic profiles of individuals with preclinical AD were distinct from those of individuals without evidence of preclinical AD. The change in gut microbiome composition correlated with β-amyloid (Aβ) and tau pathological biomarkers but not with biomarkers of neurodegeneration, suggesting that the gut microbiome may change early in the disease process. We identified specific gut bacterial taxa associated with preclinical AD. Inclusion of these microbiome features improved the accuracy, sensitivity, and specificity of machine learning classifiers for predicting preclinical AD status when tested on a subset of the cohort (65 of the 164 participants). Gut microbiome correlates of preclinical AD neuropathology may improve our understanding of AD etiology and may help to identify gut-derived markers of AD risk.

Operationalizing the centiloid scale for [18F]florbetapir PET studies on PET/MRI

INTRODUCTION

The Centiloid scale aims to harmonize amyloid beta (Aβ) positron emission tomography (PET) measures across different analysis methods. As Centiloids were created using PET/computerized tomography (CT) data and are influenced by scanner differences, we investigated the Centiloid transformation with data from Insight 46 acquired with PET/magnetic resonanceimaging (MRI).

METHODS

We transformed standardized uptake value ratios (SUVRs) from 432 florbetapir PET/MRI scans processed using whole cerebellum (WC) and white matter (WM) references, with and without partial volume correction. Gaussian-mixture-modelling-derived cutpoints for Aβ PET positivity were converted.

RESULTS

The Centiloid cutpoint was 14.2 for WC SUVRs. The relationship between WM and WC uptake differed between the calibration and testing datasets, producing implausibly low WM-based Centiloids. Linear adjustment produced a WM-based cutpoint of 18.1.

DISCUSSION

Transformation of PET/MRI florbetapir data to Centiloids is valid. However, further understanding of the effects of acquisition or biological factors on the transformation using a WM reference is needed.

HIGHLIGHTS

Centiloid conversion of amyloid beta positron emission tomography (PET) data aims to standardize results.Centiloid values can be influenced by differences in acquisition.We converted florbetapir PET/magnetic resonance imaging data from a large birth cohort.Whole cerebellum referenced values could be reliably transformed to Centiloids.White matter referenced values may be less generalizable between datasets.

CSF tau phosphorylation occupancies at T217 and T205 represent improved biomarkers of amyloid and tau pathology in Alzheimer's disease

Cerebrospinal fluid (CSF) amyloid-β peptide (Aβ)42/Aβ40 and the concentration of tau phosphorylated at site 181 (p-tau181) are well-established biomarkers of Alzheimer's disease (AD). The present study used mass spectrometry to measure concentrations of nine phosphorylated and five nonphosphorylated tau species and phosphorylation occupancies (percentage phosphorylated/nonphosphorylated) at ten sites. In the present study we show that, in 750 individuals with a median age of 71.2 years, CSF pT217/T217 predicted the presence of brain amyloid by positron emission tomography (PET) slightly better than Aβ42/Aβ40 (P = 0.02). Furthermore, for individuals with positive brain amyloid by PET (n = 263), CSF pT217/T217 was more strongly correlated with the amount of amyloid (Spearman's ρ = 0.69) than Aβ42/Aβ40 (ρ = -0.42, P < 0.0001). In two independent cohorts of participants with symptoms of AD dementia (n = 55 and n = 90), CSF pT217/T217 and pT205/T205 were better correlated with tau PET measures than CSF p-tau181 concentration. These findings suggest that CSF pT217/T217 and pT205/T205 represent improved CSF biomarkers of amyloid and tau pathology in AD.

Validity Assessment of an Automated Brain Morphometry Tool for Patients with De Novo Memory Symptoms

BACKGROUND AND PURPOSE

Automated volumetric analysis of structural MR imaging allows quantitative assessment of brain atrophy in neurodegenerative disorders. We compared the brain segmentation performance of the AI-Rad Companion brain MR imaging software against an in-house FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline.

MATERIALS AND METHODS

T1-weighted images of 45 participants with de novo memory symptoms were selected from the OASIS-4 database and analyzed through the AI-Rad Companion brain MR imaging tool and the FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline. Correlation, agreement, and consistency between the 2 tools were compared among the absolute, normalized, and standardized volumes. Final reports generated by each tool were used to compare the rates of detection of abnormality and the compatibility of radiologic impressions made using each tool, compared with the clinical diagnoses.

RESULTS

We observed strong correlation, moderate consistency, and poor agreement between absolute volumes of the main cortical lobes and subcortical structures measured by the AI-Rad Companion brain MR imaging tool compared with FreeSurfer. The strength of the correlations increased after normalizing the measurements to the total intracranial volume. Standardized measurements differed significantly between the 2 tools, likely owing to differences in the normative data sets used to calibrate each tool. When considering the FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline as a reference standard, the AI-Rad Companion brain MR imaging tool had a specificity of 90.6%-100% and a sensitivity of 64.3%-100% in detecting volumetric abnormalities. There was no difference between the rate of compatibility of radiologic and clinical impressions when using the 2 tools.

CONCLUSIONS

The AI-Rad Companion brain MR imaging tool reliably detects atrophy in cortical and subcortical regions implicated in the differential diagnosis of dementia.

Association of Indication for Hospitalization With Subsequent Amyloid Positron Emission Tomography and Magnetic Resonance Imaging Biomarkers

BACKGROUND

Hospitalization in older age is associated with accelerated cognitive decline, typically preceded by neuropathologic changes. We assess the association between indication for hospitalization and brain neurodegeneration.

METHODS

Included were participants from the Mayo Clinic Study of Aging, a population-based longitudinal study, with ≥1 brain imaging available in those older than 60 years of age between 2004 and 2017. Primary analyses used linear mixed-effects models to assess association of hospitalization with changes in longitudinal trajectory of cortical thinning, amyloid accumulation, and white matter hyperintensities (WMH). Additional analyses were performed with imaging outcomes dichotomized (normal vs abnormal) using Cox proportional hazards regression.

RESULTS

Of 2 480 participants, 1 966 had no hospitalization and 514 had ≥1 admission. Hospitalization was associated with accelerated cortical thinning (annual slope change -0.003 mm [95% confidence interval (CI) -0.005 to -0.001], p = .002), but not amyloid accumulation (0.003 [95% CI -0.001 to 0.006], p = .107), or WMH increase (0.011 cm3 [95% CI -0.001 to 0.023], p = .062). Interaction analyses assessing whether trajectory changes are dependent on admission type (medical vs surgical) found interactions for all outcomes. While surgical hospitalizations were not, medical hospitalizations were associated with accelerated cortical thinning (-0.004 mm [95% CI -0.008 to -0.001, p = .014); amyloid accumulation (0.010, [95% CI 0.002 to 0.017, p = .011), and WMH increase (0.035 cm3 [95% CI 0.012 to 0.058, p = .006). Hospitalization was not associated with developing abnormal cortical thinning (p = .407), amyloid accumulation (p = .596), or WMH/infarctions score (p = .565).

CONCLUSIONS

Medical hospitalizations were associated with accelerated cortical thinning, amyloid accumulation, and WMH increases. These changes were modest and did not translate to increased risk for crossing the abnormality threshold.

Brain aerobic glycolysis and resilience in Alzheimer disease

The distribution of brain aerobic glycolysis (AG) in normal young adults correlates spatially with amyloid-beta (Aβ) deposition in individuals with symptomatic and preclinical Alzheimer disease (AD). Brain AG decreases with age, but the functional significance of this decrease with regard to the development of AD symptomatology is poorly understood. Using PET measurements of regional blood flow, oxygen consumption, and glucose utilization-from which we derive AG-we find that cognitive impairment is strongly associated with loss of the typical youthful pattern of AG. In contrast, amyloid positivity without cognitive impairment was associated with preservation of youthful brain AG, which was even higher than that seen in cognitively unimpaired, amyloid negative adults. Similar findings were not seen for blood flow nor oxygen consumption. Finally, in cognitively unimpaired adults, white matter hyperintensity burden was found to be specifically associated with decreased youthful brain AG. Our results suggest that AG may have a role in the resilience and/or response to early stages of amyloid pathology and that age-related white matter disease may impair this process.

The RSNA QIBA Profile for Amyloid PET as an Imaging Biomarker for Cerebral Amyloid Quantification

A standardized approach to acquiring amyloid PET images increases their value as disease and drug response biomarkers. Most 18F PET amyloid brain scans often are assessed only visually (per regulatory labels), with a binary decision indicating the presence or absence of Alzheimer disease amyloid pathology. Minimizing technical variance allows precise, quantitative SUV ratios (SUVRs) for early detection of β-amyloid plaques and allows the effectiveness of antiamyloid treatments to be assessed with serial studies. Methods: The Quantitative Imaging Biomarkers Alliance amyloid PET biomarker committee developed and validated a profile to characterize and reduce the variability of SUVRs, increasing statistical power for these assessments. Results: On achieving conformance, sites can justify a claim that brain amyloid burden reflected by the SUVR is measurable to a within-subject coefficient of variation of no more than 1.94% when the same radiopharmaceutical, scanner, acquisition, and analysis protocols are used. Conclusion: This overview explains the claim, requirements, barriers, and potential future developments of the profile to achieve precision in clinical and research amyloid PET imaging.

Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study

Background

Estimates of 'brain-predicted age' quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD) but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural MRI, but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored.

Methods

We trained three models to predict age from FC, structural (S), or multimodal MRI (S+FC) in 390 amyloid-negative cognitively normal (CN/A-) participants (18-89 years old). In independent samples of 144 CN/A-, 154 CN/A+, and 154 cognitively impaired (CI; CDR > 0) participants, we tested relationships between BAG and AD biomarkers of amyloid and tau, as well as a global cognitive composite.

Results

All models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG was significantly reduced in CN/A+ participants compared to CN/A-. In CI participants only, elevated S-BAG and S+FC BAG were associated with more advanced AD pathology and lower cognitive performance.

Conclusions

Both FC-BAG and S-BAG are elevated in CI participants. However, FC and structural MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to presymptomatic AD pathology, while S-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model improves sensitivity to healthy age differences.

Funding

This work was supported by the National Institutes of Health (P01-AG026276, P01- AG03991, P30-AG066444, 5-R01-AG052550, 5-R01-AG057680, 1-R01-AG067505, 1S10RR022984-01A1, and U19-AG032438), the BrightFocus Foundation (A2022014F), and the Alzheimer's Association (SG-20-690363-DIAN).

Comparing Tau PET Visual Interpretation with Tau PET Quantification, Cerebrospinal Fluid Biomarkers, and Longitudinal Clinical Assessment

BACKGROUND

18F-flortaucipir PET received FDA approval to visualize aggregated neurofibrillary tangles (NFTs) in brains of adult patients with cognitive impairment being evaluated for Alzheimer's disease (AD). However, manufacturer's guidelines for visual interpretation of 18F-flortaucipir PET differ from how 18F-flortaucipir PET has been measured in research settings using standardized uptake value ratios (SUVRs). How visual interpretation relates to 18F-flortaucipir PET SUVR, cerebrospinal fluid (CSF) biomarkers, or longitudinal clinical assessment is not well understood.

OBJECTIVE

We compare various diagnostic methods in participants enrolled in longitudinal observational studies of aging and memory (n = 189, 23 were cognitively impaired).

METHODS

Participants had tau PET, Aβ PET, MRI, and clinical and cognitive evaluation within 18 months (n = 189); the majority (n = 144) also underwent lumbar puncture. Two radiologists followed manufacturer's guidelines for 18F-flortaucipir PET visual interpretation.

RESULTS

Visual interpretation had high agreement with SUVR (98.4%)and moderate agreement with CSF p-tau181 (86.1%). Two participants demonstrated 18F-flortaucipir uptake from meningiomas. Visual interpretation could not predict follow-up clinical assessment in 9.52% of cases.

CONCLUSION

Visual interpretation was highly consistent with SUVR (discordant participants had hemorrhagic infarcts or occipital-predominant AD NFT deposition) and moderately consistent with CSF p-tau181 (discordant participants had AD pathophysiology not detectable on tau PET). However, close association between AD NFT deposition and clinical onset in group-level studies does not necessarily hold at the individual level, with discrepancies arising from atypical AD, vascular dementia, or frontotemporal dementia. A better understanding of relationships across imaging, CSF biomarkers, and clinical assessment is needed to provide appropriate diagnoses for these individuals.

Preclinical Alzheimer's disease biomarkers accurately predict cognitive and neuropathological outcomes

Alzheimer's disease biomarkers are widely accepted as surrogate markers of underlying neuropathological changes. However, few studies have evaluated whether preclinical Alzheimer's disease biomarkers predict Alzheimer's neuropathology at autopsy. We sought to determine whether amyloid PET imaging or CSF biomarkers accurately predict cognitive outcomes and Alzheimer's disease neuropathological findings. This study included 720 participants, 42-91 years of age, who were enrolled in longitudinal studies of memory and aging in the Washington University Knight Alzheimer Disease Research Center and were cognitively normal at baseline, underwent amyloid PET imaging and/or CSF collection within 1 year of baseline clinical assessment, and had subsequent clinical follow-up. Cognitive status was assessed longitudinally by Clinical Dementia Rating®. Biomarker status was assessed using predefined cut-offs for amyloid PET imaging or CSF p-tau181/amyloid-β42. Subsequently, 57 participants died and underwent neuropathologic examination. Alzheimer's disease neuropathological changes were assessed using standard criteria. We assessed the predictive value of Alzheimer's disease biomarker status on progression to cognitive impairment and for presence of Alzheimer's disease neuropathological changes. Among cognitively normal participants with positive biomarkers, 34.4% developed cognitive impairment (Clinical Dementia Rating > 0) as compared to 8.4% of those with negative biomarkers. Cox proportional hazards modelling indicated that preclinical Alzheimer's disease biomarker status, APOE ɛ4 carrier status, polygenic risk score and centred age influenced risk of developing cognitive impairment. Among autopsied participants, 90.9% of biomarker-positive participants and 8.6% of biomarker-negative participants had Alzheimer's disease neuropathological changes. Sensitivity was 87.0%, specificity 94.1%, positive predictive value 90.9% and negative predictive value 91.4% for detection of Alzheimer's disease neuropathological changes by preclinical biomarkers. Single CSF and amyloid PET baseline biomarkers were also predictive of Alzheimer's disease neuropathological changes, as well as Thal phase and Braak stage of pathology at autopsy. Biomarker-negative participants who developed cognitive impairment were more likely to exhibit non-Alzheimer's disease pathology at autopsy. The detection of preclinical Alzheimer's disease biomarkers is strongly predictive of future cognitive impairment and accurately predicts presence of Alzheimer's disease neuropathology at autopsy.

Deep residual inception encoder-decoder network for amyloid PET harmonization

INTRODUCTION

Multiple positron emission tomography (PET) tracers are available for amyloid imaging, posing a significant challenge to consensus interpretation and quantitative analysis. We accordingly developed and validated a deep learning model as a harmonization strategy.

METHOD

A Residual Inception Encoder-Decoder Neural Network was developed to harmonize images between amyloid PET image pairs made with Pittsburgh Compound-B and florbetapir tracers. The model was trained using a dataset with 92 subjects with 10-fold cross validation and its generalizability was further examined using an independent external dataset of 46 subjects.

RESULTS

Significantly stronger between-tracer correlations (P < .001) were observed after harmonization for both global amyloid burden indices and voxel-wise measurements in the training cohort and the external testing cohort.

DISCUSSION

We proposed and validated a novel encoder-decoder based deep model to harmonize amyloid PET imaging data from different tracers. Further investigation is ongoing to improve the model and apply to additional tracers.

Racial differences in longitudinal Alzheimer's disease biomarkers among cognitively normal adults

INTRODUCTION

Longitudinal changes in Alzheimer's disease (AD) biomarkers, including cerebrospinal fluid (CSF) analytes, amyloid uptakes from positron emission tomography (PET), structural outcomes from magnetic resonance imaging (MRI), and cognition, have not been compared between Blacks and Whites.

METHODS

A total of 179 Blacks and 1180 Whites who were cognitively normal at baseline and had longitudinal data from at least one biomarker modality were analyzed for the annual rates of change.

RESULTS

CSF amyloid beta (Aβ)42/Aβ40 declined more slowly (P = .0390), and amyloid (PET) accumulated more slowly (P = .0157), in Blacks than Whites. CSF Aβ42 changed in opposite directions over time between Blacks and Whites (P = .0039). The annual increase in CSF total tau and phosphorylated tau181 for Blacks was about half of that for Whites.

DISCUSSION

Longitudinal racial differences in amyloid biomarkers are observed. It will be important to comprehensively and prospectively examine the effects of apolipoprotein E genotype and sociocultural factors on these differences.

APOE ε4 genotype, amyloid-β, and sex interact to predict tau in regions of high APOE mRNA expression

The apolipoprotein E (APOE) ε4 allele is strongly linked with cerebral β-amyloidosis, but its relationship with tauopathy is less established. We investigated the relationship between APOE ε4 carrier status, regional amyloid-β (Aβ), magnetic resonance imaging (MRI) volumetrics, tau positron emission tomography (PET), APOE messenger RNA (mRNA) expression maps, and cerebrospinal fluid phosphorylated tau (CSF ptau₁₈₁). Three hundred fifty participants underwent imaging, and 270 had ptau₁₈₁. We used computational models to evaluate the main effect of APOE ε4 carrier status on regional neuroimaging values and then the interaction of ε4 status and global Aβ on regional tau PET and brain volumes as well as CSF ptau₁₈₁. Separately, we also examined the additional interactive influence of sex. We found that, for the same degree of Aβ burden, APOE ε4 carriers showed greater tau PET signal relative to noncarriers in temporal regions, but no interaction was present for MRI volumes or CSF ptau₁₈₁. This potentiation of tau aggregation irrespective of sex occurred in brain regions with high APOE mRNA expression, suggesting local vulnerabilities to tauopathy. There were greater effects of APOE genotype in females, although the interactive sex effects did not strongly mirror mRNA expression. Pathology is not homogeneously expressed throughout the brain but mirrors underlying biological patterns such as gene expression.

β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3

INTRODUCTION

The Centiloid scale was developed to harmonise the quantification of β-amyloid (Aβ) PET images across tracers, scanners, and processing pipelines. However, several groups have reported differences across tracers and scanners even after centiloid conversion. In this study, we aim to evaluate the impact of different pre and post-processing harmonisation steps on the robustness of longitudinal Centiloid data across three large international cohort studies.

METHODS

All Aβ PET data in AIBL (N = 3315), ADNI (N = 3442) and OASIS3 (N = 1398) were quantified using the MRI-based Centiloid standard SPM pipeline and the PET-only pipeline CapAIBL. SUVR were converted into Centiloids using each tracer's respective transform. Global Aβ burden from pre-defined target cortical regions in Centiloid units were quantified for both raw PET scans and PET scans smoothed to a uniform 8 mm full width half maximum (FWHM) effective smoothness. For Florbetapir, we assessed the performance of using both the standard Whole Cerebellum (WCb) and a composite white matter (WM)+WCb reference region. Additionally, our recently proposed quantification based on Non-negative Matrix Factorisation (NMF) was applied to all spatially and SUVR normalised images. Correlation with clinical severity measured by the Mini-Mental State Examination (MMSE) and effect size, as well as tracer agreement in 11C-PiB-18F-Florbetapir pairs and longitudinal consistency were evaluated.

RESULTS

The smoothing to a uniform resolution partially reduced longitudinal variability, but did not improve inter-tracer agreement, effect size or correlation with MMSE. Using a Composite reference region for 18F-Florbetapir improved inter-tracer agreement, effect size, correlation with MMSE, and longitudinal consistency. The best results were however obtained when using the NMF method which outperformed all other quantification approaches in all metrics used.

CONCLUSIONS

FWHM smoothing has limited impact on longitudinal consistency or outliers. A Composite reference region including subcortical WM should be used for computing both cross-sectional and longitudinal Florbetapir Centiloid. NMF improves Centiloid quantification on all metrics examined.

Focused ultrasound–mediated blood-brain barrier opening in Alzheimer’s disease: long-term safety, imaging, and cognitive outcomes

OBJECTIVE

MRI-guided low-intensity focused ultrasound (FUS) has been shown to reversibly open the blood-brain barrier (BBB), with the potential to deliver therapeutic agents noninvasively to target brain regions in patients with Alzheimer’s disease (AD) and other neurodegenerative conditions. Previously, the authors reported the short-term safety and feasibility of FUS BBB opening of the hippocampus and entorhinal cortex (EC) in patients with AD. Given the need to treat larger brain regions beyond the hippocampus and EC, brain volumes and locations treated with FUS have now expanded. To evaluate any potential adverse consequences of BBB opening on disease progression, the authors report safety, imaging, and clinical outcomes among participants with mild AD at 6–12 months after FUS treatment targeted to the hippocampus, frontal lobe, and parietal lobe.

METHODS

In this open-label trial, participants with mild AD underwent MRI-guided FUS sonication to open the BBB in β-amyloid positive regions of the hippocampus, EC, frontal lobe, and parietal lobe. Participants underwent 3 separate FUS treatment sessions performed 2 weeks apart. Outcome assessments included safety, imaging, neurological, cognitive, and florbetaben β-amyloid PET.

RESULTS

Ten participants (range 55–76 years old) completed 30 separate FUS treatments at 2 participating institutions, with 6–12 months of follow-up. All participants had immediate BBB opening after FUS and BBB closure within 24–48 hours. All FUS treatments were well tolerated, with no serious adverse events related to the procedure. All 10 participants had a minimum of 6 months of follow-up, and 7 participants had a follow-up out to 1 year. Changes in the Alzheimer’s Disease Assessment Scale–cognitive and Mini-Mental State Examination scores were comparable to those in controls from the Alzheimer’s Disease Neuroimaging Initiative. PET scans demonstrated an average β-amyloid plaque of 14% in the Centiloid scale in the FUS-treated regions.

CONCLUSIONS

This study is the largest cohort of participants with mild AD who received FUS treatment, and has the longest follow-up to date. Safety was demonstrated in conjunction with reversible and repeated BBB opening in multiple cortical and deep brain locations, with a concomitant reduction of β-amyloid. There was no apparent cognitive worsening beyond expectations up to 1 year after FUS treatment, suggesting that the BBB opening treatment in multiple brain regions did not adversely influence AD progression. Further studies are needed to determine the clinical significance of these findings. FUS offers a unique opportunity to decrease amyloid plaque burden as well as the potential to deliver targeted therapeutics to multiple brain regions in patients with neurodegenerative disorders.

Autosomal dominant and sporadic late onset Alzheimer's disease share a common in vivo pathophysiology

The 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.

Unsupervised high-frequency smartphone-based cognitive assessments are reliable, valid, and feasible in older adults at risk for Alzheimer's disease

OBJECTIVE

Smartphones have the potential for capturing subtle changes in cognition that characterize preclinical Alzheimer's disease (AD) in older adults. The Ambulatory Research in Cognition (ARC) smartphone application is based on principles from ecological momentary assessment (EMA) and administers brief tests of associative memory, processing speed, and working memory up to 4 times per day over 7 consecutive days. ARC was designed to be administered unsupervised using participants' personal devices in their everyday environments.

METHODS

We evaluated the reliability and validity of ARC in a sample of 268 cognitively normal older adults (ages 65-97 years) and 22 individuals with very mild dementia (ages 61-88 years). Participants completed at least one 7-day cycle of ARC testing and conventional cognitive assessments; most also completed cerebrospinal fluid, amyloid and tau positron emission tomography, and structural magnetic resonance imaging studies.

RESULTS

First, ARC tasks were reliable as between-person reliability across the 7-day cycle and test-retest reliabilities at 6-month and 1-year follow-ups all exceeded 0.85. Second, ARC demonstrated construct validity as evidenced by correlations with conventional cognitive measures (r = 0.53 between composite scores). Third, ARC measures correlated with AD biomarker burden at baseline to a similar degree as conventional cognitive measures. Finally, the intensive 7-day cycle indicated that ARC was feasible (86.50% approached chose to enroll), well tolerated (80.42% adherence, 4.83% dropout), and was rated favorably by older adult participants.

CONCLUSIONS

Overall, the results suggest that ARC is reliable and valid and represents a feasible tool for assessing cognitive changes associated with the earliest stages of AD.

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.

Effect of Race on Prediction of Brain Amyloidosis by Plasma Aβ42/Aβ40, Phosphorylated Tau, and Neurofilament Light

BACKGROUND AND OBJECTIVES

To evaluate whether plasma biomarkers of amyloid (Aβ42/Aβ40), tau (p-tau181 and p-tau231), and neuroaxonal injury (neurofilament light chain [NfL]) detect brain amyloidosis consistently across racial groups.

METHODS

Individuals enrolled in studies of memory and aging who self-identified as African American (AA) were matched 1:1 to self-identified non-Hispanic White (NHW) individuals by age, APOE ε4 carrier status, and cognitive status. Each participant underwent blood and CSF collection, and amyloid PET was performed in 103 participants (68%). Plasma Aβ42/Aβ40 was measured by a high-performance immunoprecipitation-mass spectrometry assay. Plasma p-tau181, p-tau231, and NfL were measured by Simoa immunoassays. CSF Aβ42/Aβ40 and amyloid PET status were used as primary and secondary reference standards of brain amyloidosis, respectively.

RESULTS

There were 76 matched pairs of AA and NHW participants (n = 152 total). For both AA and NHW groups, the median age was 68.4 years, 42% were APOE ε4 carriers, and 91% were cognitively normal. AA were less likely than NHW participants to have brain amyloidosis by CSF Aβ42/Aβ40 (22% vs 43% positive; p = 0.003). The receiver operating characteristic area under the curve of CSF Aβ42/Aβ40 status with the plasma biomarkers was as follows: Aβ42/Aβ40, 0.86 (95% CI 0.79-0.92); p-tau181, 0.76 (0.68-0.84); p-tau231, 0.69 (0.60-0.78); and NfL, 0.64 (0.55-0.73). In models predicting CSF Aβ42/Aβ40 status with plasma Aβ42/Aβ40 that included covariates (age, sex, APOE ε4 carrier status, race, and cognitive status), race did not affect the probability of CSF Aβ42/Aβ40 positivity. In similar models based on plasma p-tau181, p-tau231, or NfL, AA participants had a lower probability of CSF Aβ42/Aβ40 positivity (odds ratio 0.31 [95% CI 0.13-0.73], 0.30 [0.13-0.71], and 0.27 [0.12-0.64], respectively). Models of amyloid PET status yielded similar findings.

DISCUSSION

Models predicting brain amyloidosis using a high-performance plasma Aβ42/Aβ40 assay may provide an accurate and consistent measure of brain amyloidosis across AA and NHW groups, but models based on plasma p-tau181, p-tau231, and NfL may perform inconsistently and could result in disproportionate misdiagnosis of AA individuals.

Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer's disease

Objective

Although beta-amyloid (Aβ) positron emission tomography (PET) images are interpreted visually as positive or negative, approximately 10% are judged as equivocal in Alzheimer’s disease. Therefore, we aimed to develop an automated semi-quantitative analysis technique using ¹⁸F-flutemetamol PET images without anatomical images.

Methods

Overall, 136 cases of patients administered ¹⁸F-flutemetamol were enrolled. Of 136 cases, five PET images each with the highest and lowest values of standardized uptake value ratio (SUVr) of cerebral cortex-to-pons were used to create positive and negative templates. Using these templates, PET images of the remaining 126 cases were standardized, and SUVr images were produced with the pons as a reference region. The mean of SUVr values in the volume of interest delineated on the cerebral cortex was compared to those in the CortexID Suite (GE Healthcare). Furthermore, centiloid (CL) values were calculated for the 126 cases using data from the Centiloid Project (http://www.gaain.org/centiloid-project) and both templates. ¹⁸F-flutemetamol-PET was interpreted visually as positive/negative based on Aβ deposition in the cortex. However, the criterion "equivocal" was added for cases with focal or mild Aβ accumulation that were difficult to categorize. Optimal cutoff values of SUVr and CL maximizing sensitivity and specificity for Aβ detection were determined by receiver operating characteristic (ROC) analysis using the visual evaluation as a standard of truth.

Results

SUVr calculated by our method and CortexID were highly correlated (R² = 0.9657). The 126 PET images comprised 84 negative and 42 positive cases of Aβ deposition by visual evaluation, of which 11 and 10 were classified as equivocal, respectively. ROC analyses determined the optimal cutoff values, sensitivity, and specificity for SUVr as 0.544, 89.3%, and 92.9%, respectively, and for CL as 12.400, 94.0%, and 92.9%, respectively. Both semi-quantitative analyses showed that 12 and 9 of the 21 equivocal cases were negative and positive, respectively, under the optimal cutoff values.

Conclusions

This semi-quantitative analysis technique using ¹⁸F-flutemetamol-PET calculated SUVr and CL automatically without anatomical images. Moreover, it objectively and homogeneously interpreted positive or negative Aβ burden in the brain as a supplemental tool for the visual reading of equivocal cases in routine clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12149-022-01769-x.

Cerebrospinal fluid neurofilament light chain is a marker of aging and white matter damage

BACKGROUND

Cerebrospinal fluid (CSF) neurofilament light chain (NfL) reflects neuro-axonal damage and is increasingly used to evaluate disease progression across neurological conditions including Alzheimer disease (AD). However, it is unknown how NfL relates to specific types of brain tissue. We sought to determine whether CSF NfL is more strongly associated with total gray matter, white matter, or white matter hyperintensity (WMH) volume, and to quantify the relative importance of brain tissue volume, age, and AD marker status (i.e., APOE genotype, brain amyloidosis, tauopathy, and cognitive status) in predicting CSF NfL.

METHODS

419 participants (Clinical Dementia Rating [CDR] Scale > 0, N = 71) had CSF, magnetic resonance imaging (MRI), and neuropsychological data. A subset had amyloid positron emission tomography (PET) and tau PET. Pearson correlation analysis was used to determine the association between CSF NfL and age. Multiple regression was used to determine which brain volume (i.e., gray, white, or WMH volume) most strongly associated with CSF NfL. Stepwise regression and dominance analyses were used to determine the individual contributions and relative importance of brain volume, age, and AD marker status in predicting CSF NfL.

RESULTS

CSF NfL increased with age (r = 0.59, p < 0.001). Elevated CSF NfL was associated with greater total WMH volume (p < 0.001), but not gray or white matter volume (p's > 0.05) when considered simultaneously. Age and WMH volume were consistently more important (i.e., have greater R2 values) than AD markers when predicting CSF NfL.

CONCLUSIONS

CSF NfL is a non-specific marker of aging and white matter integrity with limited sensitivity to specific markers of AD. CSF NfL likely reflects processes associated with cerebrovascular disease.

Beta-amyloid moderates the relationship between cortical thickness and attentional control in middle- and older-aged adults

Although often unmeasured in studies of cognition, many older adults possess Alzheimer disease (AD) pathologies such as beta-amyloid (Aβ) deposition, despite being asymptomatic. We were interested in examining whether the behavior-structure relationship observed in later life was altered by the presence of preclinical AD pathology. A total of 511 cognitively unimpaired adults completed magnetic resonance imaging and three attentional control tasks; a subset (n = 396) also underwent Aβ-positron emissions tomography. A vertex-wise model was conducted to spatially represent the relationship between cortical thickness and average attentional control accuracy, while moderation analysis examined whether Aβ deposition impacted this relationship. First, we found that reduced cortical thickness in temporal, medial- and lateral-parietal, and dorsolateral prefrontal cortex, predicted worse performance on the attention task composite. Subsequent moderation analyses observed that levels of Aβ significantly influence the relationship between cortical thickness and attentional control. Our results support the hypothesis that preclinical AD, as measured by Aβ deposition, is partially driving what would otherwise be considered general aging in a cognitively normal adult population.

Intracranial internal carotid artery calcification is not predictive of future cognitive decline

Background

Intracranial internal carotid artery (ICA) calcification is a common incidental finding in non-contrast head CT. We evaluated the predictive value of ICAC (ICAC) for future risk of cognitive decline and compared the results with conventional imaging biomarkers of dementia.

Methods

In a retrospective observational cohort, we included 230 participants with a PET-CT scan within 18 months of a baseline clinical assessment and longitudinal imaging assessments. Intracranial ICAC was quantified on baseline CT scans using the Agatson calcium score, and the association between baseline ICA calcium scores and the risk of conversion from a CDR of zero in baseline to a persistent CDR > 0 at any follow-up visit, as well as longitudinal changes in cognitive scores, were evaluated through linear and mixed regression models. We also evaluated the association of conventional imaging biomarkers of dementia with longitudinal changes in cognitive scores and a potential indirect effect of ICAC on cognition through these biomarkers.

Results

Baseline ICA calcium score could not distinguish participants who converted to CDR > 0. ICA calcium score was also unable to predict longitudinal changes in cognitive scores, imaging biomarkers of small vessel disease such as white matter hyperintensities (WMH) volume, or AD such as hippocampal volume, AD cortical signature thickness, and amyloid burden. Severity of intracranial ICAC increased with age and in men. Higher WMH volume and amyloid burden as well as lower hippocampal volume and AD cortical signature thickness at baseline predicted lower Mini-Mental State Exam scores at longitudinal follow-up. Baseline ICAC was indirectly associated with longitudinal cognitive decline, fully mediated through WMH volume.

Conclusions

In elderly and preclinical AD populations, atherosclerosis of large intracranial vessels as demonstrated through ICAC is not directly associated with a future risk of cognitive impairment, or progression of imaging biomarkers of AD or small vessel disease.

Regional age-related atrophy after screening for preclinical alzheimer disease

Brain atrophy occurs in aging even in the absence of dementia, but it is unclear to what extent this is due to undetected preclinical Alzheimer disease. Here we examine a cross-sectional cohort (ages 18-88) free from confounding influence of preclinical Alzheimer disease, as determined by amyloid PET scans and three years of clinical evaluation post-imaging. We determine the regional strength of age-related atrophy using linear modeling of brain volumes and cortical thicknesses with age. Age-related atrophy was seen in nearly all regions, with greatest effects in the temporal lobe and subcortical regions. When modeling age with the estimated derivative of smoothed aging curves, we found that the temporal lobe declined linearly with age, subcortical regions declined faster at later ages, and frontal regions declined slower at later ages than during midlife. This age-derivative pattern was distinct from the linear measure of age-related atrophy and significantly associated with a measure of myelin. Atrophy did not detectably differ from a preclinical Alzheimer disease cohort when age ranges were matched.

Sex-Specific Patterns of Body Mass Index Relationship with White Matter Connectivity

BACKGROUND

Obesity is an increasingly recognized modifiable risk factor for Alzheimer's disease (AD). Increased body mass index (BMI) is related to distinct changes in white matter (WM) fiber density and connectivity.

OBJECTIVE

We investigated whether sex differentially affects the relationship between BMI and WM structural connectivity.

METHODS

A cross-sectional sample of 231 cognitively normal participants were enrolled from the Knight Alzheimer Disease Research Center. Connectome analyses were done with diffusion data reconstructed using q-space diffeomorphic reconstruction to obtain the spin distribution function and tracts were selected using a deterministic fiber tracking algorithm.

RESULTS

We identified an inverse relationship between higher BMI and lower connectivity in the associational fibers of the temporal lobe in overweight and obese men. Normal to overweight women showed a significant positive association between BMI and connectivity in a wide array of WM fibers, an association that reversed in obese and morbidly obese women. Interaction analyses revealed that with increasing BMI, women showed higher WM connectivity in the bilateral frontoparietal and parahippocampal parts of the cingulum, while men showed lower connectivity in right sided corticostriatal and corticopontine tracts. Subgroup analyses demonstrated comparable results in participants with and without positron emission tomography or cerebrospinal fluid evidence of brain amyloidosis, indicating that the relationship between BMI and structural connectivity in men and women is independent of AD biomarker status.

CONCLUSION

BMI influences structural connectivity of WM differently in men and women across BMI categories and this relationship does not vary as a function of preclinical AD.

Predicting Symptom Onset in Sporadic Alzheimer Disease With Amyloid PET

BACKGROUND AND OBJECTIVES

To predict when cognitively normal individuals with brain amyloidosis will develop symptoms of Alzheimer disease (AD).

METHODS

Brain amyloid burden was measured by amyloid PET with Pittsburgh compound B. The mean cortical standardized uptake value ratio (SUVR) was transformed into a timescale with the use of longitudinal data.

RESULTS

Amyloid accumulation was evaluated in 236 individuals who underwent >1 amyloid PET scan. The average age was 66.5 ± 9.2 years, and 12 individuals (5%) had cognitive impairment at their baseline amyloid PET scan. A tipping point in amyloid accumulation was identified at a low level of amyloid burden (SUVR 1.2), after which nearly all individuals accumulated amyloid at a relatively consistent rate until reaching a high level of amyloid burden (SUVR 3.0). The average time between levels of amyloid burden was used to estimate the age at which an individual reached SUVR 1.2. Longitudinal clinical diagnoses for 180 individuals were aligned by the estimated age at SUVR 1.2. In the 22 individuals who progressed from cognitively normal to a typical AD dementia syndrome, the estimated age at which an individual reached SUVR 1.2 predicted the age at symptom onset (R ² = 0.54, p < 0.0001, root mean square error [RMSE] 4.5 years); the model was more accurate after exclusion of 3 likely misdiagnoses (R ² = 0.84, p < 0.0001, RMSE 2.8 years).

CONCLUSION

The age at symptom onset in sporadic AD is strongly correlated with the age at which an individual reaches a tipping point in amyloid accumulation.

Comparing amyloid-β plaque burden with antemortem PiB PET in autosomal dominant and late-onset Alzheimer disease

Pittsburgh compound B (PiB) radiotracer for positron emission tomography (PET) imaging can bind to different types of amyloid-β plaques and blood vessels (cerebral amyloid angiopathy). However, the relative contributions of different plaque subtypes (diffuse versus cored/compact) to in vivo PiB PET signal on a region-by-region basis are incompletely understood. Of particular interest is whether the same staging schemes for summarizing amyloid-β burden are appropriate for both late-onset and autosomal dominant forms of Alzheimer disease (LOAD and ADAD). Here, we compared antemortem PiB PET with follow-up postmortem estimation of amyloid-β burden using stereologic methods to estimate the relative area fraction of diffuse and cored/compact amyloid-β plaques across 16 brain regions in 15 individuals with ADAD and 14 individuals with LOAD. In ADAD, we found that PiB PET correlated with diffuse plaques in the frontal, parietal, temporal, and striatal regions commonly used to summarize amyloid-β burden in PiB PET, and correlated with both diffuse and cored/compact plaques in the occipital lobe and parahippocampal gyrus. In LOAD, we found that PiB PET correlated with both diffuse and cored/compact plaques in the anterior cingulate, frontal lobe (middle frontal gyrus), and parietal lobe, and showed additional correlations with diffuse plaque in the amygdala and occipital lobe, and with cored/compact plaque in the temporal lobe. Thus, commonly used PiB PET summary regions predominantly reflect diffuse plaque burden in ADAD and a mixture of diffuse and cored/compact plaque burden in LOAD. In direct comparisons of ADAD and LOAD, postmortem stereology identified much greater mean amyloid-β plaque burdens in ADAD versus LOAD across almost all brain regions studied. However, standard PiB PET did not recapitulate these stereologic findings, likely due to non-trivial amyloid-β plaque burdens in ADAD within the cerebellum and brainstem-commonly used reference regions in PiB PET. Our findings suggest that PiB PET summary regions correlate with amyloid-β plaque burden in both ADAD and LOAD; however, they might not be reliable in direct comparisons of regional amyloid-β plaque burden between the two forms of AD.

Is comprehensiveness critical? Comparing short and long format cognitive assessments in preclinical Alzheimer disease

BACKGROUND

Comprehensive testing of cognitive functioning is standard practice in studies of Alzheimer disease (AD). Short-form tests like the Montreal Cognitive Assessment (MoCA) use a "sampling" of measures, administering key items in a shortened format to efficiently assess cognition while reducing time requirements, participant burden, and administrative costs. We compared the MoCA to a commonly used long-form cognitive battery in predicting AD symptom onset and sensitivity to AD neuroimaging biomarkers.

METHODS

Survival, area under the receiver operating characteristic (ROC) curve (AUC), and multiple regression analyses compared the MoCA and long-form measures in predicting time to symptom onset in cognitively normal older adults (n = 6230) from the National Alzheimer's Coordinating Center (NACC) cohort who had, on average, 2.3 ± 1.2 annual assessments. Multiple regression models in a separate sample (n = 416) from the Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) compared the sensitivity of the MoCA and long-form measures to neuroimaging biomarkers including amyloid PET, tau PET, and cortical thickness.

RESULTS

Hazard ratios suggested that both the MoCA and the long-form measures are similarly and modestly efficacious in predicting symptomatic conversion, although model comparison analyses indicated that the long-form measures slightly outperformed the MoCA (HRs > 1.57). AUC analyses indicated no difference between the measures in predicting conversion (DeLong's test, Z = 1.48, p = 0.13). Sensitivity to AD neuroimaging biomarkers was similar for the two measures though there were only modest associations with tau PET (rs = - 0.13, ps < 0.02) and cortical thickness in cognitively normal participants (rs = 0.15-0.16, ps < 0.007).

CONCLUSIONS

Both test formats showed weak associations with symptom onset, AUC analyses indicated low diagnostic accuracy, and biomarker correlations were modest in cognitively normal participants. Alternative assessment approaches are needed to improve how clinicians and researchers monitor cognitive changes and disease progression prior to symptom onset.

AMYQ: An index to standardize quantitative amyloid load across PET tracers

INTRODUCTION

Positron emission tomography (PET) amyloid quantification methods require magnetic resonance imaging (MRI) for spatial registration and a priori reference region to scale the images. Furthermore, different tracers have distinct thresholds for positivity. We propose the AMYQ index, a new measure of amyloid burden, to overcome these limitations.

METHODS

We selected 18F-amyloid scans from ADNI and Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) with the corresponding T1-MRI. A subset also had neuropathological data. PET images were normalized, and the AMYQ was calculated based on an adaptive template. We compared AMYQ with the Centiloid scale on clinical and neuropathological diagnostic performance.

RESULTS

AMYQ was related with amyloid neuropathological burden and had excellent diagnostic performance to discriminate controls from patients with Alzheimer's disease (AD) (area under the curve [AUC] = 0.86). AMYQ had a high agreement with the Centiloid scale (intraclass correlation coefficient [ICC] = 0.88) and AUC between 0.94 and 0.99 to discriminate PET positivity when using different Centiloid cutoffs.

DISCUSSION

AMYQ is a new MRI-independent index for standardizing and quantifying amyloid load across tracers.