David A. Merrill

Background: Blood tests for Alzheimer's disease (AD) are emerging as alternative to amyloid positron emission tomography (PET) scans and analysis of cerebrospinal fluid (CSF). However, their effect on clinical decision-making and subsequent wait times in the diagnostic process remain unclear. Objective: To estimate wait times in the diagnostic process to determine potential eligibility for amyloid-targeting treatments. Methods: We used a structured expert consultation process to elicit how a blood test to rule out or to confirm AD pathology would inform decisions in primary and secondary care and a Markov model to project how those decisions would affect wait times for specialist visits and amyloid PET scans. Results: Compared with referral decisions based on the results of a brief cognitive assessment, the addition of an AD blood test is projected to reduce wait times for subsequent specialist appointments by 35%. A blood test for confirmation of AD pathology would also eliminate wait times for amyloid PET scans. Conclusions: High-performing AD blood tests have the potential to streamline the diagnostic journey and reduce wait times

Background: Medical and lifestyle management are crucial for Alzheimer's disease (AD). Cerebral blood flow (CBF), vital for brain health, and influenced by modifiable risk factors, is reduced in AD and may become uncoupled from metabolism due to neurovascular dysfunction in later stages. Objective: This mid-trial analysis tested the hypothesis that a coached, multi-modal intervention (PREVENTION) improved ASL-MRI-measured CBF and diabetic risk (QUICKI) in patients with early AD. Methods: The control arm received recommendations and medical management for one year; the active arm additionally received coaching, exercise training, and supplementation. We hypothesized that those in (1) the active arm and (2) with higher intervention adherence would have improved post-trial QUICKI and CBF, particularly in regions relevant to exercise, cardiovascular, diabetic, and AD risk. Post-trial CBF was analyzed using a linear model including arm, baseline CBF, adherence, age, education, and depressive symptoms. Change in QUICKI was analyzed using mixed effects general linear models, including arm, adherence, time, and interactions between time and treatment group and time and adherence, controlling for age. Results: The active arm (n = 18) showed greater post-trial CBF in regions related to exercise, cardiovascular, diabetic, and AD risk, compared to control (n = 20), but did not differ in global CBF, QUICKI, or adherence. Higher adherence scores were associated with greater regional post-trial CBF and improvement in QUICKI, but not global CBF. Conclusions: In this small sample, we found evidence that a multi-modal intervention focused on medical management, exercise, and a carbohydrate-restricted diet improved diabetic risk and CBF in patients with AD.

Background/Objectives: A high-performing blood biomarker (BBM) test for Alzheimer’s disease (AD) represents an accurate, accessible, and scalable tool to aid healthcare professionals (HCPs) evaluating patients presenting with signs or symptoms of mild cognitive impairment (MCI) or dementia. However, implementation of AD blood tests into clinical practice has not been extensively evaluated. The objective of this study was to assess the implementation of the multi-analyte PrecivityAD2™ blood test (C2N Diagnostics, LLC, St. Louis, MO, USA) into the clinical workflow of memory care clinics. Methods: A total of 8 HCPs (neurologists, geriatricians, geriatric psychiatrists) who served as site directors from 8 outpatient sites that evaluated 203 cognitively symptomatic patients were included in this sub-study of the real-world QUIP II Study (NCT06025877). Implementation of this blood test was assessed through surveying these HCPs using published frameworks including the Technology Acceptance Model, net promoter score, and forced choice preference questions. These assessments were analyzed using Wilcoxon signed-rank test, Fisher’s Exact test, and Wilcoxon signed-rank test, respectively. Results: HCPs reported acceptance scores that averaged 9.6 out of 10 (p < 0.0001, effect size 0.840): the test’s contribution to clinical decision-making as well as the ease of understanding test results received the highest ratings. The net promoter score was 75 (p < 0.0001), exceeding the typical benchmark of 30 reported as good levels of satisfaction in healthcare settings. The APS2 results and individual blood analyte results were rated with similar preference around their roles in HCP clinical decision-making. Conclusions: The results indicate early evidence of user acceptance and recognition by HCPs that this AD blood test can personalize the clinical care pathway for evaluating cognitively symptomatic patients.

Background/Objectives: Frailty is a well-established risk factor for cognitive decline and dementia, yet how its distinct physical, functional, and psychosocial components relate to brain health in Alzheimer’s disease (AD) remains poorly understood. This proof-of-concept study aimed to identify data-driven frailty factors and examine their cross-sectional associations with cognition and brain structure in biomarker-confirmed AD. Methods: Forty-eight adults with amyloid-β (Aβ)-positive AD underwent comprehensive clinical assessments, neuropsychological testing, dual-energy X-ray absorptiometry, and 3.0T magnetic resonance imaging of the brain. Exploratory factor analysis (EFA) was applied to characterize the underlying structure of physical (body composition measures), functional (performance-based metrics), and psychosocial (patient-reported outcomes) frailty domains. Multiple linear regression analysis was used to examine associations between extracted frailty factors and cognition (memory and executive function) and neuroanatomy (total gray matter and hippocampal volumes), adjusting for age, sex, education, APOE4 status, and total intracranial volume. Results: EFA revealed eight distinct frailty factors. Psychological distress was associated with worse memory (p=0.02) and smaller hippocampal volume (p=0.05). Physical and social limitations were associated with smaller total gray matter volume (p=0.03). Cognitive-motor dual-task performance was associated with superior executive functioning (p=0.002) and larger total gray matter volume (p=0.01). Lean mass was associated with larger hippocampal volume (p=0.0004). Conclusions: Distinct frailty factors exhibited specific cognitive and neuroanatomical signatures in AD. These preliminary findings underscore the multifaceted nature of frailty and suggest unique mechanistic pathways through which it may influence brain health. Larger longitudinal studies are warranted to validate these results and inform clinically relevant interventions.

Background Alzheimer’s disease (AD) leading to cognitive decline and dementia results from the interplay of multiple interacting dysfunctional biological systems. These systems can be categorized by domain, such as inflammation, cardiovascular health, proteostasis, or metabolism. Specific causes of AD differ between individuals, but each individual is likely to have causes stemming from multiple domains. Personalized multidomain therapy has been proposed as a standard of care for AD. Objectives We sought to enumerate and describe prospective randomized controlled trials (RCTs) for multidomain interventions for AD, and to extract their inclusion criteria, trial design parameters (length, number of participants), and outcome measures. We sought to clarify gaps and opportunities in research and clinical translation. Eligibility criteria We include all cohort studies and RCTs for multidomain (also known as multimodal, multicomponent, multidimensional, or multisystem) therapy of any stage of AD. Results There have been 22 studies (completed or reported as ongoing) of multidomain interventions for AD, including 18 RCTs. Of the 14 completed RCTs, 11 demonstrate benefit from their intervention in at least one arm. Conclusions Although these RCTs differ widely in their parameters, the majority support the use of multidomain therapy, and show effect sizes greater than reported for unimodal therapies, including pharmaceuticals. Multidomain therapy should be the standard of care for AD. Multidomain interventions (also known as treatments) should be employed widely, early, and first-line. Treatment or prevention is likely to be most effective at early, presymptomatic stages, but is worthwhile at all stages of disease. In order to influence multiple domains, multiple modes of therapy are likely necessary in all patients. Some individual modes, such as particular lifestyle interventions, may target multiple domains. Nevertheless, most patients will benefit from multiple modes of intervention (multimodal intervention) that together target multiple domains. Standard-of-care guidelines should explicitly include multidomain interventions. Future clinical trials must be designed to iteratively improve multidomain therapies. Payors should embrace reimbursement for effective multidomain intervention, including personalized coaching.

Objective: The objective of this study was to assess clinical decision-making associated with the use of a multi-analyte blood biomarker (BBM) test among patients presenting with signs or symptoms of mild cognitive impairment or dementia. Methods: The Quality Improvement PrecivityAD2 (QUIP II) Clinician Survey (NCT06025877) study evaluated the clinical utility of the PrecivityAD2™ blood test in a prospective, single cohort of 203 patients presenting with symptoms of Alzheimer’s disease (AD) or other causes of cognitive decline across 12 memory specialists. The PrecivityAD2 blood test (C2N Diagnostics, St. Louis, MO) combines the plasma Aβ42/Aβ40 ratio and the p-tau217/np-tau217 ratio (%p-tau217) measurements in a statistical algorithm to yield an Amyloid Probability Score 2 (APS2) that informs on the likelihood of brain amyloid plaques. After receiving the BBM test results, clinicians completed surveys on management strategies for each patient. Results: Patients had a median age of 74, 53% were female, and 28% were traditionally under-represented in Black, Hispanic, and Asian groups. The composite primary endpoint, defined as a change in AD diagnostic certainty, drug therapy, or additional brain amyloid evaluation pre- and post-BBM testing, was 75% (p < 0.0001 versus the pre-specified threshold of 20% clinically meaningful change). Anti-AD medication orders decreased among negative APS2 patients and increased among positive APS2 patients (p < 0.0001). Additional brain amyloid testing decreased among negative APS2 patients (p < 0.0001). Conclusions: This blood biomarker test can help memory specialists guide patients to anti-AD therapies as well as rule out AD to allow for other diagnostic considerations.

Across many resting-state electroencephalography (EEG) studies, dementia is associated with changes to the power spectrum and fractal dimension. Here, we describe a novel method to examine changes in the fractal dimension over time and within frequency bands. This method, which we call fractal dimension distributions (FDD), combines spectral and complexity information. In this study, we illustrate this new method by applying it to resting-state EEG data recorded from patients with subjective cognitive impairment (SCI) or dementia. We compared the performance of FDD with the performance of standard fractal dimension metrics (Higuchi and Katz FD). FDD revealed larger group differences detectable at greater numbers of EEG recording sites. Moreover, linear models using FDD features had lower AIC and higher R² than models using standard full time-course measures of the fractal dimension. FDD metrics also outperformed the full time-course metrics when comparing SCI with a subset of dementia patients diagnosed with Alzheimer’s disease. FDD offers unique information beyond traditional full time-course fractal analyses and may help to identify dementia caused by Alzheimer’s disease and dementia from other causes.

Introduction: Adopting healthy lifestyle behaviors has the potential to slow cognitive decline in older adults by reducing risks associated with dementia. Curriculum-based group health coaching may aid in establishing behavior change centered for dementia risk factors. Methods: In this pilot clinical care patient group study (n = 6), we examined the effects of a six-month online Cognitive Health Program combined with a weekly telehealth support group led by the course creator, and personalized health optimization by a collaborating physician, in older adults with subjective cognitive decline. Cognition was assessed at baseline and post-intervention using a computerized battery. Results: Cognitive changes were estimated with nonparametric tests and effect sizes (Cohen’s d). Results showed significant improvements in global cognition (p < 0.03, d = 1.6), spatial planning (p < 0.01, d = 2.3), and visuospatial processing (p < 0.05, d = 1.1) compared to baseline. Participants reported high levels of satisfaction with the virtual group format and online curriculum. Conclusions: This small pilot study suggests that a virtual six-month personalized health coaching group with self-paced online health education is feasible and potentially efficacious for improving cognition in participants with subjective cognitive complaints. This format may facilitate behavior change to slow cognitive decline. Future studies should include a control group, a larger, more diverse sample as well as assessing mood and other subjective measures.