IDEAS and New IDEAS: Amyloid PET in diverse populations

Contribution of Global Amyloid-PET Imaging for Predicting Future Cognition in the MEMENTO Cohort

BACKGROUND AND OBJECTIVES

Global amyloid-PET is associated with cognition and cognitive decline, but most research on this association does not account for past cognitive information. We assessed the prognostic benefit of amyloid-PET measures for future cognition when prior cognitive assessments are available, evaluating the added value of amyloid measures beyond information on multiple past cognitive assessments.

METHODS

The French MEMENTO cohort (a cohort of outpatients from French research memory centers to improve knowledge on Alzheimer disease and related disorders) includes older outpatients with incipient cognitive changes, but no dementia diagnosis at inclusion. Global amyloid burden was assessed using positron emission tomography (amyloid-PET) for a subset of participants; semiannual cognitive testing was subsequently performed. We predicted mini-mental state examination (MMSE) scores using demographic characteristics (age, sex, marital status, and education) alone or in combination with information on prior cognitive measures. The added value of amyloid burden as a predictor in these models was evaluated with percent reduction of the mean squared error (MSE). All models were conducted separately for evaluating the added value of dichotomous amyloid positivity status compared with a continuous amyloid-standardized uptake-value ratio.

RESULTS

Our analytic sample comprised 510 individuals who underwent amyloid-PET scans with at least 4 MMSE assessments. The mean age at the PET scan was 71.6 (standard deviation 7.4) years; 60.7% were female. The median follow-up was 4.6 years (interquartile range: 0.9 years). Adding amyloid burden when adjusting for only demographic characteristics reduced the MSE of predictions by 5.08% (95% CI 0.97%-10.86%) and 12.64% (95% CI 3.35%-25.28%) for binary and continuous amyloid, respectively. If the model included 1 past MMSE measure, the MSE improvement was 3.51% (95% CI 1.01%-7.28%) when adding binary amyloid and 8.83% (95% CI 2.63%-16.37%) when adding continuous amyloid. Improvements in model fit were smaller with the addition of amyloid burden when more than 1 past cognitive assessment was included. For all models incorporating past cognitive assessments, differences in predictions amounted to a fraction of 1 MMSE point on average.

DISCUSSION

In a clinical setting, global amyloid burden did not appreciably improve cognitive predictions when past cognitive assessments were available.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov Identifier: NCT02164643.

Accelerating diversity in Alzheimer's disease research by partnering with a community advisory board

Introduction

Community advisory boards (CABs) and researcher partnerships present a promising opportunity to accelerate enrollment of underrepresented groups (URGs). We outline the framework for how the CAB and researchers at the Indiana Alzheimer's Disease Research Center (IADRC) partnered to accelerate URG participation in AD neuroimaging research.

Methods

CAB and the IADRC researchers partnered to increase the CAB's impact on URG study enrollment through community and research interactions. Community interactions included the CAB collaboratively building a network of URG focused community organizations and collaborating with those URG-focused organizations to host IADRC outreach and recruitment events. Research interactions included direct impact (CAB members referring themselves or close contacts as participants) and strategic impact, mainly by the CAB working with researchers to develop and refine URG focused outreach and recruitment strategies for IADRC and affiliated studies to increase URG representation. We created a database infrastructure to measure how these interactions impacted URG study enrollment.

Results

Out of the 354 URG research referrals made to the IADRC between October 2019 and December 2022, 267 referrals were directly referred by the CAB (N = 36) or from community events in which CAB members organized and/or volunteered at (N = 231). Out of these 267 referrals, 34 were enrolled in IADRC and 2 were enrolled in Indiana University Longitudinal Early Onset AD Study (IU LEADS). Of note, both studies require the prospective participants to be willing to do MRI and PET scans. As of December 2022, 30 out of the 34 enrolled participants have received a consensus diagnosis; the majority were cognitively normal (64.7%), with the remainder having mild cognitive impairment (17.6%) or early-stage AD (2.9%).

Discussion

The IADRC CAB-researcher partnership had a measurable impact on the enrollment of African American/Black adults in AD neuroimaging studies. Future studies will need to test whether this conceptual model works for other sites and for other URGs.

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.