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Background: Detecting clinically meaningful changes in instrumental activities of daily living (IADL) at the earliest stages of Alzheimer’s disease (AD) is critical. Objective: The objective of this exploratory study was to examine the cross-sectional relationship between a performance-based IADL test, the Harvard Automated Phone Task (APT), and cerebral tau and amyloid burden in cognitively normal (CN) older adults. Methods: Seventy-seven CN participants underwent flortaucipir tau and Pittsburgh Compound B amyloid PET. IADL were assessed using the three Harvard APT tasks: prescription refill (APT-Script), health insurance company call (APT-PCP), and bank transaction (APT-Bank). Linear regression models were used to determine associations between each APT task and entorhinal cortex, inferior temporal, or precuneus tau with or without an interaction with amyloid. Results: Significant associations were found between APT-Bank task rate and interaction between amyloid and entorhinal cortex tau, and APT-PCP task and interactions between amyloid and inferior temporal and precuneus tau. No significant associations were found between the APT tasks and tau or amyloid alone. Conclusion: Our preliminary findings suggest an association between a simulated real-life IADL test and interactions of amyloid and several regions of early tau accumulation in CN older adults. However, some analyses were underpowered due to the small number of participants with elevated amyloid, and findings should be interpreted with caution. Future studies will further explore these associations cross-sectionally and longitudinally in order to determine whether the Harvard APT can serve as a reliable IADL outcome measure for preclinical AD prevention trials and ultimately in the clinic setting.

A crucial aspect of any clinical trial is using the right outcome measure to assess treatment efficacy. Compared to the rapidly evolved understanding and measurement of pathophysiology in preclinical and early symptomatic stages of Alzheimer's disease (AD), relatively less progress has been made in the evolution of clinical outcome assessments (COAs) for those stages. The current paper aims to provide a benchmark for the design and evaluation of COAs for use in early AD trials. We discuss lessons learned on capturing cognitive changes in predementia stages of AD, including challenges when validating novel COAs for those early stages and necessary evidence for their implementation in clinical trials. Moving forward, we propose a multi-step framework to advance the use of more effective COAs to assess clinically meaningful changes in early AD, which will hopefully contribute to the much-needed consensus around more appropriate outcome measures to assess clinical efficacy of putative treatments. HIGHLIGHTS: We discuss lessons learned on capturing cognitive changes in predementia stages of AD. We propose a framework for the design and evaluation of performance based cognitive tests for use in early AD trials. We provide recommendations to facilitate the implementation of more effective cognitive outcome measures in AD trials.

Background and ObjectivesAlzheimer disease (AD) clinical trials are moving earlier in the disease process according to emerging signs of β-amyloid (Aβ) and tau pathology. If early treatment is the right time for intervention, it is critical to find the right test to optimize cognitive outcome measures for clinical trials. We sought to identify cognitive measures associated with the earliest detectable signs of emerging Aβ and tau pathology.MethodsOne hundred twelve clinically normal adults with longitudinal Pittsburgh compound B (PiB)-PET, 18F-flortaucipir (FTP)-PET, and cognitive data for ≥7 years were included from the Harvard Aging Brain Study (HABS). Analyses assessed those initially classified as PiB− (less than Centiloid [CL] 20) and then expanded to include PiB+ individuals up to CL40, the approximate threshold beyond which neocortical tau proliferation begins. Separate linear mixed-effects models assessed the effects of emerging global Aβ (PiB slope) and tau (baseline FTP level and FTP slope) in the entorhinal and inferior temporal (IT) cortices on multiple cognitive tasks and the Preclinical Alzheimer's Cognitive Composite (PACC) over time.ResultsSteeper PiB slopes were associated with declining processing speed (Digit Symbol Substitution Test [DSST], Trail Making Test Part A) in those CL40).DiscussionEarly, Aβ-mediated cognitive slowing was detected for processing speed measures, while early memory retrieval declines were associated with emerging Aβ and tau pathology. Composites of these measures may help determine whether anti-Aβ or anti-tau therapies administered at the first signs of pathology might preserve cognitive function.Classification of EvidenceThis study provides Class I evidence that in clinically normal older adults, emerging PET-detected AD pathology is associated with declining processing speeds and memory retrieval.

Background and ObjectivesThe goal of this work was to investigate the neuroimaging correlates of the Stages of Objective Memory Impairment (SOMI) system operationalized with the Free and Cued Selective Reminding Test (FCSRT), a widely used episodic memory measure.MethodsThe FCSRT begins with a study phase in which items (e.g., grapes) are identified in response to unique semantic cues (e.g., fruit) that are used in the test phase to prompt recall of items not retrieved by free recall. There are 3 test trials of the 16 items (maximum 48). Data from 4,484 cognitively unimpaired participants from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) study were used. All participants had amyloid PET imaging, and a subset of 1,262 β-amyloid (Aβ)–positive had structural MRIs. We compared the Aβ mean cortical standardized uptake value ratio (SUVR) and volumetric measures of hippocampus, parahippocampal gyrus, entorhinal cortex, and inferior temporal cortex between the 5 SOMI stages.ResultsParticipants had a mean age of 71.3 (SD 4.6) years; 40.6% were male; and 34.6% were APOE ε4 positive. Half had no memory impairment; the other half had retrieval deficits, storage limitations, or both. Analysis of covariance in the entire sample while controlling for age, sex, education, and APOE ε4 showed that individuals in higher SOMI stages had higher global amyloid SUVR (p < 0.001). Both SOMI-4 and -3 subgroups had higher amyloid SUVR than SOMI-0 and SOMI-1 subgroups. Individuals in higher SOMI stages had smaller hippocampal volume (p = 0.003), entorhinal cortex (p < 0.05), and inferior temporal lobes (p < 0.05), but there was no difference between parahippocampal gyrus volume of different SOMI stages. Pairwise comparison of SOMI subgroups showed that the SOMI-4, -3, and -2 subgroups had smaller hippocampal volume than the SOMI-0 and -1 subgroup. The SOMI-4 subgroup had significantly smaller entorhinal cortex and smaller inferior temporal lobe compared to all other groups.DiscussionPresence of Alzheimer disease pathology is closely related to memory impairment according to SOMI stages in the cognitively unimpaired sample of A4. Results from structural MRIs suggest that memory storage impairment (SOMI-3 and -4) is present when there is widespread medial temporal lobe atrophy.Trial Registration InformationClinicalTrials.gov identifier: NCT02008357.Classification of EvidenceThis study provides Class I evidence that, in normal older individuals, higher stages of memory impairment assessed with FCSRT were associated with higher amyloid imaging burden and lower volume of hippocampus, entorhinal cortex, and inferior temporal lobes.

Remote and unsupervised cognitive testing using smartphones may improve sensitivity to detect preclinical Alzheimer’s disease (AD). In particular, cognitive testing at-home enables the evaluation of the potentially more sensitive long-term delayed memory retrieval, which is commonly not feasible in a clinical setting.MethodHere, we investigated the association between remote and unsupervised smartphone-based cognitive assessments and in-clinic cognitive measurement in older participants (CDR = 0, MMSE = 29.2, age = 77). The sample (non-demented at age 70) was derived from the Swedish population-based Gothenburg H70 Birth Cohort Studies. In a subsample of participants, the retrospective correlation with cerebrospinal fluid (CSF) biomarkers analyzed at age 70 was further explored. To this point, 177 H70-participants have consented and were enrolled into the smartphone sub-study. They completed an “Object-in-Room Recall Test“ (ORR) remotely and unsupervised using own mobile devices, and the recall session was initiated 24 hours after the initial learning phase. Available previously assessed CSF measures included the Aβ42/Aβ40-ratio, t-tau, p-tau, neurofilament light (NFL), and neurogranin, available in-clinic cognitive tests included the Rey Auditory Verbal Learning Test (RAVLT), Semantic Fluency, Digit-Symbol-Coding, and Mini Mental State Examination. The above-mentioned cognitive tests were used to derive the Preclinical Alzheimer's Cognitive Composite (PACC5), a composite designed to be sensitive to cognitive change in preclinical AD. All associations were examined using Pearson correlation coefficient.ResultPreliminary analyses in a subset of participants yielded relatively strong positive correlations between PACC5 (R = .50, p

Early detection of Alzheimer’s disease is required to identify patients suitable for disease-modifying medications and to improve access to non-pharmacological preventative interventions. Prior research shows detectable changes in speech in Alzheimer’s dementia and its clinical precursors. The current study assesses whether a fully automated speech-based artificial intelligence system can detect cognitive impairment and amyloid beta positivity, which characterize early stages of Alzheimer’s disease. Two hundred participants (age 54–85, mean 70.6; 114 female, 86 male) from sister studies in the UK (NCT04828122) and the USA (NCT04928976), completed the same assessments and were combined in the current analyses. Participants were recruited from prior clinical trials where amyloid beta status (97 amyloid positive, 103 amyloid negative, as established via PET or CSF test) and clinical diagnostic status was known (94 cognitively unimpaired, 106 with mild cognitive impairment or mild Alzheimer’s disease). The automatic story recall task was administered during supervised in-person or telemedicine assessments, where participants were asked to recall stories immediately and after a brief delay. An artificial intelligence text-pair evaluation model produced vector-based outputs from the original story text and recorded and transcribed participant recalls, quantifying differences between them. Vector-based representations were fed into logistic regression models, trained with tournament leave-pair-out cross-validation analysis to predict amyloid beta status (primary endpoint), mild cognitive impairment and amyloid beta status in diagnostic subgroups (secondary endpoints). Predictions were assessed by the area under the receiver operating characteristic curve for the test result in comparison with reference standards (diagnostic and amyloid status). Simulation analysis evaluated two potential benefits of speech-based screening: (i) mild cognitive impairment screening in primary care compared with the Mini-Mental State Exam, and (ii) pre-screening prior to PET scanning when identifying an amyloid positive sample. Speech-based screening predicted amyloid beta positivity (area under the curve = 0.77) and mild cognitive impairment or mild Alzheimer’s disease (area under the curve = 0.83) in the full sample, and predicted amyloid beta in subsamples (mild cognitive impairment or mild Alzheimer’s disease: area under the curve = 0.82; cognitively unimpaired: area under the curve = 0.71). Simulation analyses indicated that in primary care, speech-based screening could modestly improve detection of mild cognitive impairment (+8.5%), while reducing false positives (−59.1%). Furthermore, speech-based amyloid pre-screening was estimated to reduce the number of PET scans required by 35.3% and 35.5% in individuals with mild cognitive impairment and cognitively unimpaired individuals, respectively. Speech-based assessment offers accessible and scalable screening for mild cognitive impairment and amyloid beta positivity.

Studies are increasingly examining research questions across multiple cohorts using data from the preclinical Alzheimer cognitive composite (PACC). Our objective was to use modern psychometric approaches to develop a harmonized PACC.We used longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Harvard Aging Brain Study (HABS), and Australian Imaging, Biomarker and Lifestyle Study of Ageing (AIBL) cohorts (Baseline (BL) scores for the zPACC were centered on zero, by definition. The harmonized lPACC did not define a common mean of zero and demonstrated differences in baseline ability levels across the cohorts. Baseline lPACC slightly outperformed zPACC in the prediction of progression to dementia. Longitudinal change in the lPACC was more constrained and less variable relative to the zPACC. In combined-cohort analyses, longitudinal lPACC slightly outperformed longitudinal zPACC in its association with baseline β-amyloid status.This study proposes procedures for harmonizing the PACC that make fewer strong assumptions than the zPACC, facilitating robust multicohort analyses. This implementation of item response theory lends itself to adapting across future cohorts with similar composites. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Animal and human imaging research reported that the presence of cortical Alzheimer's Disease's (AD) neuropathology, beta-amyloid and neurofibrillary tau, is associated with altered neuronal activity and circuitry failure, together facilitating clinical progression. The locus coeruleus (LC), one of the initial subcortical regions harboring pretangle hyperphosphorylated tau, has widespread connections to the cortex modulating cognition. Here we investigate whether LC's in-vivo neuronal activity and functional connectivity (FC) are associated with cognitive decline in conjunction with beta-amyloid. We combined functional MRI of a novel versus repeated face-name paradigm, beta-amyloid-PET and longitudinal cognitive data of 128 cognitively unimpaired older individuals. We show that LC activity and LC-FC with amygdala and hippocampus was higher during novelty. We also demonstrated that lower novelty-related LC activity and LC-FC with hippocampus and parahippocampus were associated with steeper beta-amyloid-related cognitive decline. Our results demonstrate the potential of LC's functional properties as a gauge to identify individuals at-risk for AD-related cognitive decline.Older individuals exhibiting diminished function of the locus coeruleus while learning new information show faster cognitive decline that is typical for Alzheimer's disease.

ObjectiveTo identify the hippocampal subregions linking initial amyloid and tau pathology to memory performance in clinically normal older individuals, reflecting preclinical Alzheimer disease (AD).MethodsA total of 127 individuals from the Harvard Aging Brain Study (mean age 76.22 ± 6.42 years, 68 women [53.5%]) with a Clinical Dementia Rating score of 0, a flortaucipir tau-PET scan, a Pittsburgh compound B amyloid-PET scan, a structural MRI scan, and cognitive testing were included. From these images, we calculated neocortical, hippocampal, and entorhinal amyloid pathology; entorhinal and hippocampal tau pathology; and the volumes of 6 hippocampal subregions and total hippocampal volume. Memory was assessed with the selective reminding test. Mediation and moderation analyses modeled associations between regional markers and memory. Analyses included covariates for age, sex, and education.ResultsNeocortical amyloid, entorhinal tau, and presubiculum volume univariately associated with memory performance. The relationship between neocortical amyloid and memory was mediated by entorhinal tau and presubiculum volume, which was modified by hippocampal amyloid burden. With other biomarkers held constant, presubiculum volume was the only marker predicting memory performance in the total sample and in individuals with elevated hippocampal amyloid burden.ConclusionsThe presubiculum captures unique AD-related biological variation that is not reflected in total hippocampal volume. Presubiculum volume may be a promising marker of imminent memory problems and can contribute to understanding the interaction between incipient AD-related pathologies and memory performance. The modulation by hippocampal amyloid suggests that amyloid is a necessary, but not sufficient, process to drive neurodegeneration in memory-related regions.

Highlights • We examined the markers that optimally predict progression from normal to MCI. • A LASSO Cox model was used to determine the minimum set of markers. • Entorhinal thickness, Aβ burden, default network connectivity, and hippocampal volume predicted progression. • These markers may enhance risk stratification in clinically normal adults., Objective To identify a parsimonious set of markers that optimally predicts subsequent clinical progression from normal to mild cognitive impairment (MCI). Methods 250 clinically normal adults (mean age = 73.6 years, SD = 6.0) from the Harvard Aging Brain Study were assessed at baseline on a wide set of markers, including magnetic resonance imaging markers of gray matter thickness and volume, white matter lesions, fractional anisotropy, resting state functional connectivity, positron emission tomography markers of glucose metabolism and β-amyloid (Aβ) burden, and a measure of vascular risk. Participants were also tested annually on a battery of clinical and cognitive tests (median follow-up = 5.0 years, SD = 1.66). We applied least absolute shrinkage and selection operator (LASSO) Cox models to determine the minimum set of non-redundant markers that predicts subsequent clinical progression from normal to MCI, adjusting for age, sex, and education. Results 23 participants (9.2%) progressed to MCI over the study period (mean years of follow-up to diagnosis = 3.96, SD = 1.89). Progression was predicted by several brain markers, including reduced entorhinal thickness (hazard ratio, HR = 1.73), greater Aβ burden (HR = 1.58), lower default network connectivity (HR = 1.42), and smaller hippocampal volume (HR = 1.30). When cognitive test scores were added to the model, the aforementioned neuroimaging markers remained significant and lower striatum volume as well as lower scores on baseline memory and processing speed tests additionally contributed to progression. Conclusion Among a large set of brain, vascular and cognitive markers, a subset of markers independently predicted progression from normal to MCI. These markers may enhance risk stratification by identifying clinically normal individuals who are most likely to develop clinical symptoms and would likely benefit most from therapeutic intervention.

Background: Computerized cognitive assessments may improve Alzheimer’s disease (AD) secondary prevention trial efficiency and accuracy. However, they require validation against standard outcomes and relevant biomarkers. Objective: To assess the feasibility and validity of the tablet-based Computerized Cognitive Composite (C3). Design: Cross-sectional analysis of cognitive screening data from the A4 study (Anti-Amyloid in Asymptomatic AD). Setting: Multi-center international study. Participants: Clinically normal (CN) older adults (65-85; n=4486). Measurements: Participants underwent florbetapir-Positron Emission Tomography for Aβ+/- classification. They completed the C3 and standard paper and pencil measures included in the Preclinical Alzheimer’s Cognitive Composite (PACC). The C3 combines memory measures sensitive to change over time (Cogstate Brief Battery-One Card Learning) and measures shown to be declining early in AD including pattern separation (Behavioral Pattern Separation Test- Object- Lure Discrimination Index) and associative memory (Face Name Associative Memory Exam- Face-Name Matching). C3 acceptability and completion rates were assessed using qualitative and quantitative methods. C3 performance was explored in relation to Aβ+/- groups (n=1323/3163) and PACC. Results: C3 was feasible for CN older adults to complete. Rates of incomplete or invalid administrations were extremely low, even in the bottom quartile of cognitive performers (PACC). C3 was moderately correlated with PACC (r=0.39). Aβ+ performed worse on C3 compared with Aβ- [unadjusted Cohen’s d=-0.22 (95%CI: -0.31,-0.13) p

Background Story recall is a simple and sensitive cognitive test that is commonly used to measure changes in episodic memory function in early Alzheimer disease (AD). Recent advances in digital technology and natural language processing methods make this test a candidate for automated administration and scoring. Multiple parallel test stimuli are required for higher-frequency disease monitoring. Objective This study aims to develop and validate a remote and fully automated story recall task, suitable for longitudinal assessment, in a population of older adults with and without mild cognitive impairment (MCI) or mild AD. Methods The “Amyloid Prediction in Early Stage Alzheimer’s disease” (AMYPRED) studies recruited participants in the United Kingdom (AMYPRED-UK: NCT04828122) and the United States (AMYPRED-US: NCT04928976). Participants were asked to complete optional daily self-administered assessments remotely on their smart devices over 7 to 8 days. Assessments included immediate and delayed recall of 3 stories from the Automatic Story Recall Task (ASRT), a test with multiple parallel stimuli (18 short stories and 18 long stories) balanced for key linguistic and discourse metrics. Verbal responses were recorded and securely transferred from participants’ personal devices and automatically transcribed and scored using text similarity metrics between the source text and retelling to derive a generalized match score. Group differences in adherence and task performance were examined using logistic and linear mixed models, respectively. Correlational analysis examined parallel-forms reliability of ASRTs and convergent validity with cognitive tests (Logical Memory Test and Preclinical Alzheimer’s Cognitive Composite with semantic processing). Acceptability and usability data were obtained using a remotely administered questionnaire. Results Of the 200 participants recruited in the AMYPRED studies, 151 (75.5%)—78 cognitively unimpaired (CU) and 73 MCI or mild AD—engaged in optional remote assessments. Adherence to daily assessment was moderate and did not decline over time but was higher in CU participants (ASRTs were completed each day by 73/106, 68.9% participants with MCI or mild AD and 78/94, 83% CU participants). Participants reported favorable task usability: infrequent technical problems, easy use of the app, and a broad interest in the tasks. Task performance improved modestly across the week and was better for immediate recall. The generalized match scores were lower in participants with MCI or mild AD (Cohen d=1.54). Parallel-forms reliability of ASRT stories was moderate to strong for immediate recall (mean rho 0.73, range 0.56-0.88) and delayed recall (mean rho=0.73, range=0.54-0.86). The ASRTs showed moderate convergent validity with established cognitive tests. Conclusions The unsupervised, self-administered ASRT task is sensitive to cognitive impairments in MCI and mild AD. The task showed good usability, high parallel-forms reliability, and high convergent validity with established cognitive tests. Remote, low-cost, low-burden, and automatically scored speech assessments could support diagnostic screening, health care, and treatment monitoring.

BACKGROUNDStory recall is a simple and sensitive cognitive test commonly used to measure changes in episodic memory function in early Alzheimer’s disease (AD). Recent advances in digital technology and natural language processing methods make this test a candidate for automated administration and scoring. Convenient and low-burden daily assessments may provide more reliable data than one-off lengthy assessments and be suitable for longer-term disease monitoring.OBJECTIVESDevelop and validate a remote and fully automated story recall task, suitable for longitudinal assessment, in a population of older adults with and without mild cognitive impairment (MCI) or mild AD.METHODSParticipants from AMYPRED-UK (NCT04828122) and AMYPRED-US (NCT04928976) studies were asked to complete optional daily self-administered assessments remotely on their smart devices over 7-8 days. Assessments included immediate and delayed recall of three stories from the Automatic Story Recall Task (ASRT), a test with multiple parallel stimuli (18 short stories, and 18 long stories) balanced for key linguistic and discourse metrics. Verbal responses were recorded and securely transferred from participants’ personal devices, and automatically transcribed and scored using text similarity metrics between the source text and retelling to derive a generalised matching score (G-match). Adherence and task performance differences were examined with logistic mixed models and linear mixed models, respectively. Correlational analysis examined parallel forms reliability of ASRTs, and convergent validity with established cognitive tests (Logical Memory Test, and Preclinical Alzheimer’s Cognitive Composite with semantic processing (PACC5)). Acceptability and usability data were obtained via remotely administered questionnaire.RESULTSOut of 200 participants recruited into the AMYPRED studies, a total of 151 participants (75.5%, 78 cognitively unimpaired (CU), 73 MCI/mild AD) engaged in optional remote assessments. In these participants, adherence to daily assessment was moderate, did not decline over time, but was higher in cognitively unimpaired participants (66% MCI/mild AD and 78% CU participants completed at least one ASRT story per day). Participants reported favourable task usability: few technical problems, that the application was easy to use, and the tasks were broadly interesting. Task performance improved modestly across the week and was better for immediate recall. G-match scores were lower in participants with MCI/mild AD. Parallel forms reliability of ASRTs were moderate to strong for immediate recall (mean rho=0.73), and delayed recall (mean rho=0.73). ASRTs showed moderate convergent validity with established cognitive tests.CONCLUSIONSThe unsupervised, self-administered ASRT task is sensitive to cognitive impairments in MCI/mild AD. The task shows good usability, high parallel forms reliability and convergent validity with established cognitive tests. Remote, low cost, low burden and automatically scored speech assessments could be used to support diagnostic screening, healthcare and treatment monitoring.

The 2020 COVID-19 pandemic has disrupted Alzheimer’s disease (AD) clinical studies worldwide. Digital technologies may help minimize disruptions by enabling remote assessment of subtle cognitive and functional changes over the course of the disease. The EU/US Clinical Trials in Alzheimer’s Disease (CTAD) Task Force met virtually in November 2020 to explore the opportunities and challenges associated with the use of digital technologies in AD clinical research. While recognizing the potential of digital tools to accelerate clinical trials, improve the engagement of diverse populations, capture clinically meaningful data, and lower costs, questions remain regarding the stability, validity, generalizability, and reproducibility of digital data. Substantial concerns also exist regarding regulatory acceptance and privacy. Nonetheless, the Task Force supported further exploration of digital technologies through collaboration and data sharing, noting the need for standardization of digital readouts. They also concluded that while it may be premature to employ remote assessments for trials of novel experimental medications, remote studies of non-invasive, multi-domain approaches may be feasible at this time.

Several autopsy studies recognize the locus coeruleus (LC) as the initial site of hyperphosphorylated TAU aggregation, and as the number of LC neurons harboring TAU increases, TAU pathology emerges throughout the cortex. By conjointly using dedicated MRI measures of LC integrity and TAU and amyloid PET-imaging, we aimed to address the question whether in vivo LC measures relate to initial cortical patterns of Alzheimer’s disease (AD) fibrillar proteinopathies or cognitive dysfunction in 174 cognitively unimpaired and impaired older individuals with longitudinal cognitive measures. To guide our interpretations, we verified these associations in autopsy data from 1524 Religious Orders Study and Rush Memory and Aging Project and 2145 National Alzheimer’s Coordinating Center cases providing three different LC measures (pigmentation, tangle density and neuronal density), Braak staging, beta-amyloid and longitudinal cognitive measures. Lower LC integrity was associated with elevated TAU deposition in the entorhinal cortex among unimpaired individuals, consistent with postmortem correlations between LC tangle density and successive Braak staging. LC pigmentation ratings correlated with LC neuronal density but not with LC tangle density, and were particularly worse at advanced Braak stages. In the context of elevated beta-amyloid, lower LC integrity and greater cortical tangle density were associated with greater TAU burden beyond the medial temporal lobe and retrospective memory decline. These findings support neuropathologic data in which early LC TAU accumulation relates to disease progression, and identify LC integrity as a promising indicator of initial AD-related processes and subtle changes in cognitive trajectories of preclinical AD.

Animal and human imaging research reported that the presence of cortical Alzheimer's Disease's (AD) neuropathology, beta-amyloid and neurofibrillary tau, is associated with altered neuronal activity and circuitry failure, together facilitating clinical progression. The locus coeruleus (LC), one of the initial subcortical regions harboring pretangle hyperphosphorylated tau, has widespread connections to the cortex modulating cognition. Here we investigate whether LC's in-vivo neuronal activity and functional connectivity (FC) are associated with cognitive decline in conjunction with beta-amyloid. We combined functional MRI of a novel versus repeated face-name paradigm, beta-amyloid-PET and longitudinal cognitive data of 128 cognitively unimpaired older individuals. We show that LC activity and LC-FC with amygdala and hippocampus was higher during novelty. We also demonstrated that lower novelty-related LC activity and LC-FC with hippocampus and parahippocampus were associated with steeper beta-amyloid-related cognitive decline. Our results demonstrate the potential of LC's functional properties as a gauge to identify individuals at-risk for AD-related cognitive decline.

ObjectiveTo compare how structural MRI, fluorodeoxyglucose (FDG), and flortaucipir (FTP) PET signals predict cognitive decline in high-amyloid vs low-amyloid participants with the goal of determining which biomarker combination would result in the highest increase of statistical power for prevention trials.MethodsIn this prospective cohort study, we analyzed data from clinically normal adults from the Harvard Aging Brain Study with MRI, FDG, FTP, and Pittsburgh compound B (PiB)-PET acquired within a year and prospective cognitive evaluations over a mean 3-year follow-up. We focused analyses on predefined regions of interest: inferior temporal, isthmus cingulate, hippocampus, and entorhinal cortex. Cognition was assessed with the Preclinical Alzheimer's Cognitive Composite. We evaluated the association between biomarkers and cognitive decline using linear mixed-effect models with random intercepts and slopes, adjusting for demographics. We generated power curves simulating prevention trials.ResultsData from 131 participants (52 women, age 73.98 ± 8.29 years) were analyzed in the study. In separate models, most biomarkers had a closer association with cognitive decline in the high-PiB compared to the low-PiB participants. A backward stepwise regression including all biomarkers demonstrated that only neocortical PiB, entorhinal FTP, and entorhinal FDG were independent predictors of subsequent cognitive decline. Power analyses revealed that using both high PiB and low entorhinal FDG as inclusion criteria reduced 3-fold the number of participants needed in a hypothetical trial compared to using only high PiB.DiscussionIn preclinical Alzheimer disease, entorhinal hypometabolism is a strong and independent predictor of subsequent cognitive decline, making FDG a potentially useful biomarker to increase power in clinical trials.Classification of EvidenceThis study provides Class II evidence that in people with preclinical Alzheimer disease, entorhinal hypometabolism identified by FDG-PET is predictive of subsequent cognitive decline.

Background Instrumental activities of daily living (IADL) impairment and apathy occur in early-stage Alzheimer's disease (AD) and are associated with regional atrophy and hypometabolism in vivo and greater tau burden at autopsy. Objective To explore the association between IADL impairment, apathy, and in vivo regional tau in mild cognitive impairment (MCI) and AD dementia. Methods Forty participants (24 MCI, 16 AD dementia) underwent assessments of IADL (Functional Activities Questionnaire, FAQ) and apathy (Apathy Evaluation Scale Informant report, AES-I). Regional tau was assessed using flortaucipir positron emission tomography (PET) and amyloid using Pittsburgh Compound B PET. Regions with unadjusted associations of p≤0.01 were entered into regression models assessing the relationship between tau and FAQ or AES-I, adjusting for age, sex, and cognition, with/without a tau by amyloid interaction. Results Unadjusted IADL impairment but not apathy was associated with greater tau in multiple regions. After adjusting for covariates, for medial orbitofrontal and entorhinal cortex the interaction between tau and amyloid was associated with IADL impairment and for anterior cingulate it was not but independent associations with both tau and amyloid were retained. With whole brain analyses, similar results were seen for IADL, while for apathy tau in small clusters within the right anterior cingulate and dorsolateral prefrontal cortices were seen, which were more pronounced in individuals with greater amyloid. Conclusions This exploratory study suggests that IADL impairment in AD is associated with medial temporal and frontal tau, especially in individuals with elevated amyloid, while apathy may be associated with right frontal tau.

Objective:Alzheimer’s disease (AD) studies are increasingly targeting earlier (pre)clinical populations, in which the expected degree of observable cognitive decline over a certain time interval is reduced as compared to the dementia stage. Consequently, endpoints to capture early cognitive changes require refinement. We aimed to determine the sensitivity to decline of widely applied neuropsychological tests at different clinical stages of AD as outlined in the National Institute on Aging – Alzheimer’s Association (NIA-AA) research framework.Method:Amyloid-positive individuals (as determined by positron emission tomography or cerebrospinal fluid) with longitudinal neuropsychological assessments available were included from four well-defined study cohorts and subsequently classified among the NIA-AA stages. For each stage, we investigated the sensitivity to decline of 17 individual neuropsychological tests using linear mixed models.Results:1103 participants (age = 70.54 ± 8.7, 47% female) were included: n = 120 Stage 1, n = 206 Stage 2, n = 467 Stage 3 and n = 309 Stage 4. Neuropsychological tests were differentially sensitive to decline across stages. For example, Category Fluency captured significant 1-year decline as early as Stage 1 (β = −.58, p < .001). Word List Delayed Recall (β = −.22, p < .05) and Trail Making Test (β = 6.2, p < .05) became sensitive to 1-year decline in Stage 2, whereas the Mini-Mental State Examination did not capture 1-year decline until Stage 3 (β = −1.13, p < .001) and 4 (β = −2.23, p < .001).Conclusions:We demonstrated that commonly used neuropsychological tests differ in their ability to capture decline depending on clinical stage within the AD continuum (preclinical to dementia). This implies that stage-specific cognitive endpoints are needed to accurately assess disease progression and increase the chance of successful treatment evaluation in AD.

There is a pressing need to capture and track subtle cognitive change at the preclinical stage of Alzheimer's disease (AD) rapidly, cost‐effectively, and with high sensitivity. Concurrently, the landscape of digital cognitive assessment is rapidly evolving as technology advances, older adult tech‐adoption increases, and external events (i.e., COVID‐19) necessitate remote digital assessment. Here, we provide a snapshot review of the current state of digital cognitive assessment for preclinical AD including different device platforms/assessment approaches, levels of validation, and implementation challenges. We focus on articles, grants, and recent conference proceedings specifically querying the relationship between digital cognitive assessments and established biomarkers for preclinical AD (e.g., amyloid beta and tau) in clinically normal (CN) individuals. Several digital assessments were identified across platforms (e.g., digital pens, smartphones). Digital assessments varied by intended setting (e.g., remote vs. in‐clinic), level of supervision (e.g., self vs. supervised), and device origin (personal vs. study‐provided). At least 11 publications characterize digital cognitive assessment against AD biomarkers among CN. First available data demonstrate promising validity of this approach against both conventional assessment methods (moderate to large effect sizes) and relevant biomarkers (predominantly weak to moderate effect sizes). We discuss levels of validation and issues relating to usability, data quality, data protection, and attrition. While still in its infancy, digital cognitive assessment, especially when administered remotely, will undoubtedly play a major future role in screening for and tracking preclinical AD.

Introduction Unsupervised digital cognitive testing is an appealing means to capture subtle cognitive decline in preclinical Alzheimer's disease (AD). Here, we describe development, feasibility, and validity of the Boston Remote Assessment for Neurocognitive Health (BRANCH) against in‐person cognitive testing and amyloid/tau burden. Methods BRANCH is web‐based, self‐guided, and assesses memory processes vulnerable in AD. Clinically normal participants (n = 234; aged 50–89) completed BRANCH; a subset underwent in‐person cognitive testing and positron emission tomography imaging. Mean accuracy across BRANCH tests (Categories, Face‐Name‐Occupation, Groceries, Signs) was calculated. Results BRANCH was feasible to complete on participants’ own devices (primarily smartphones). Technical difficulties and invalid/unusable data were infrequent. BRANCH psychometric properties were sound, including good retest reliability. BRANCH was correlated with in‐person cognitive testing (r = 0.617, P