Determining clinically meaningful decline in preclinical Alzheimer disease

Validation of a Remote and Fully Automated Story Recall Task to Assess for Early Cognitive Impairment in Older Adults: Longitudinal Case-Control Observational Study

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.

Clinically Relevant Changes for Cognitive Outcomes in Preclinical and Prodromal Cognitive Stages: Implications for Clinical Alzheimer Trials

BACKGROUND AND OBJECTIVES

Identifying a clinically meaningful change in cognitive test score is essential when using cognition as an outcome in clinical trials. This is especially relevant because clinical trials increasingly feature novel composites of cognitive tests. Our primary objective was to establish minimal clinically important differences (MCIDs) for commonly used cognitive tests, using anchor-based and distribution-based methods, and our secondary objective was to investigate a composite cognitive measure that best predicts a minimal change in the Clinical Dementia Rating-Sum of Boxes (CDR-SB).

METHODS

From the Swedish BioFINDER cohort study, we consecutively included cognitively unimpaired (CU) individuals with and without subjective or mild cognitive impairment (MCI). We calculated MCIDs associated with a change of ≥0.5 or ≥1.0 on CDR-SB for Mini-Mental State Examination (MMSE), ADAS-Cog delayed recall 10-word list, Stroop, Letter S Fluency, Animal Fluency, Symbol Digit Modalities Test (SDMT) and Trailmaking Test (TMT) A and B, and triangulated MCIDs for clinical use for CU, MCI, and amyloid-positive CU participants. For investigating cognitive measures that best predict a change in CDR-SB of ≥0.5 or ≥1.0 point, we conducted receiver operating characteristic analyses.

RESULTS

Our study included 451 cognitively unimpaired individuals, 90 with subjective cognitive decline and 361 without symptoms of cognitive decline (pooled mean follow-up time 32.4 months, SD 26.8, range 12-96 months), and 292 people with MCI (pooled mean follow-up time 19.2 months, SD 19.0, range 12-72 months). We identified potential triangulated MCIDs (cognitively unimpaired; MCI) on a range of cognitive test outcomes: MMSE -1.5, -1.7; ADAS delayed recall 1.4, 1.1; Stroop 5.5, 9.3; Animal Fluency: -2.8, -2.9; Letter S Fluency -2.9, -1.8; SDMT: -3.5, -3.8; TMT A 11.7, 13.0; and TMT B 24.4, 20.1. For amyloid-positive CU, we found the best predicting composite cognitive measure included gender and changes in ADAS delayed recall, MMSE, SDMT, and TMT B. This produced an AUC of 0.87 (95% CI 0.79-0.94, sensitivity 75%, specificity 88%).

DISCUSSION

Our MCIDs may be applied in clinical practice or clinical trials for identifying whether a clinically relevant change has occurred. The composite measure can be useful as a clinically relevant cognitive test outcome in preclinical AD trials.

Determining the Minimal Important Change of Everyday Functioning in Dementia: Pursuing Clinical Meaningfulness

BACKGROUND AND OBJECTIVES

Decline in everyday functioning is a key clinical change in Alzheimer disease and related disorders (ADRD). An important challenge remains the determination of what constitutes a clinically meaningful change in everyday functioning. We aimed to investigate this by establishing the minimal important change (MIC): the smallest amount of change that has a meaningful effect on patients' lives. We retrospectively investigated meaningful change in a memory clinic cohort.

METHODS

In the first, qualitative part of the study, community-recruited informal caregivers of patients with ADRD and memory clinic clinicians completed a survey in which they judged various situations representing changes in everyday functioning. Their judgments of meaningful change were used to determine thresholds for MIC, both for decline and improvement, on the Amsterdam Instrumental Activities of Daily Living (IADL) Questionnaire. In the second, quantitative part, we applied these values in an independent longitudinal cohort study of unselected memory clinic patients.

RESULTS

MIC thresholds were established at the average threshold of caregivers (N = 1,629; 62.4 ± 9.5 years; 77% female) and clinicians (N = 13): -2.2 points for clinically meaningful decline and +5.0 points for clinically meaningful improvement. Memory clinic patients (N = 230; 64.3 ± 7.7 years; 39% female; 60% dementia diagnosis) were followed for 1 year, 102 (45%) of whom showed a decline larger than the MIC, after a mean of 6.7 ± 3.5 months. Patients with a dementia diagnosis and more atrophy of the medial temporal lobe had larger odds (odds ratio [OR] = 3.4, 95% CI [1.5-7.8] and OR = 5.0, 95% CI [1.2-20.0], respectively) for passing the MIC threshold for decline than those with subjective cognitive complaints and no atrophy.

DISCUSSION

We were able to operationalize clinically meaningful decline in IADL by determining the MIC. The usefulness of the MIC was supported by our findings from the clinical sample that nearly half of a sample of unselected memory clinic patients showed a meaningful decline in less than a year. Disease stage and medial temporal atrophy were predictors of functional decline greater than the MIC. Our findings provide guidance in interpreting changes in IADL and may help evaluate treatment effects and monitor disease progression.

Brain Metabolism and Amyloid Load in Individuals With Subjective Cognitive Decline or Pre-Mild Cognitive Impairment

BACKGROUND AND OBJECTIVE

This was a multicenter study aimed at investigating the characteristics of cognitive decline, neuropsychiatric symptoms, and brain imaging in individuals with subjective cognitive decline (SCD) and subtle cognitive decline (pre-mild cognitive impairment [pre-MCI]).

METHODS

Data were obtained from the Network-AD project (NET-2011-02346784). The included participants underwent baseline cognitive and neurobehavioral evaluation, FDG-PET, and amyloid PET. We used principal component analysis (PCA) to identify independent neuropsychological and neuropsychiatric dimensions and their association with brain metabolism.

RESULTS

A total of 105 participants (SCD = 49, pre-MCI = 56) were included. FDG-PET was normal in 45% of participants and revealed brain hypometabolism in 55%, with a frontal-like pattern as the most frequent finding (28%). Neuropsychiatric symptoms emerging from the Neuropsychiatric Inventory and the Starkstein Apathy Scale were highly prevalent in the whole sample (78%). An abnormal amyloid load was detected in the 18% of the participants who underwent amyloid PET (n = 60). PCA resulted in 3 neuropsychological factors: (1) executive/visuomotor, correlating with hypometabolism in frontal and occipital cortices and basal ganglia; (2) memory, correlating with hypometabolism in temporoparietal regions; and (3) visuospatial/constructional, correlating with hypometabolism in frontoparietal cortices. Two factors emerged from the neuropsychiatric PCA: (1) affective, correlating with hypometabolism in orbitofrontal and cingulate cortex and insula; (2) hyperactive/psychotic, correlating with hypometabolism in frontal, temporal, and parietal regions.

DISCUSSION

FDG-PET evidence suggests either normal brain function or different patterns of brain hypometabolism in SCD and pre-MCI. These results indicate that SCD and pre-MCI represent heterogeneous populations. Different neuropsychological and neuropsychiatric profiles emerged, which correlated with neuronal dysfunction in specific brain regions. Long-term follow-up studies are needed to assess the risk of progression to dementia in these conditions.

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer's Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer's disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.

Categorical predictive and disease progression modeling in the early stage of Alzheimer's disease

BACKGROUND

A preclinical stage of Alzheimer's disease (AD) precedes the symptomatic phases of mild cognitive impairment (MCI) and dementia, which constitutes a window of opportunities for preventive therapies or delaying dementia onset.

NEW METHOD

We propose to use categorical predictive models based on survival analysis with longitudinal data which are capable of determining subsets of markers to classify cognitively unimpaired (CU) subjects who progress into MCI/dementia or not. Subsequently, the proposed combination of markers was used to construct disease progression models (DPMs), which reveal long-term pathological trajectories from short-term clinical data. The proposed methodology was applied to a population recruited by the ADNI.

RESULTS

A very small subset of standard MRI-based data, CSF markers and cognitive measures was used to predict CU-to-MCI/dementia progression. The longitudinal data of these selected markers were used to construct DPMs using the algorithms of growth models by alternating conditional expectation (GRACE) and the latent time joint mixed effects model (LTJMM). The results show that the natural history of the proposed cognitive decline classifies the subjects well according to the clinical groups and shows a moderate correlation between the conversion times and their estimates by the algorithms.

COMPARISON WITH EXISTING METHODS

Unlike the training of the DPM algorithms without preselection of the markers, here, it is proposed to construct and evaluate the DPMs using the subsets of markers defined by the categorical predictive models.

CONCLUSIONS

The estimates of the natural history of the proposed cognitive decline from GRACE were more robust than those using LTJMM. The transition from normal to cognitive decline is mostly associated with an increase in temporal atrophy, worsening of clinical scores and pTAU/Aβ. Furthermore, pTAU/Aβ, Everyday Cognition score and the normalized volume of the entorhinal cortex show alterations of more than 20% fifteen years before the onset of cognitive decline.

Association of β-Amyloid Accumulation With Executive Function in Adults With Unimpaired Cognition

BACKGROUND AND OBJECTIVES

The neuropathologic changes underlying Alzheimer disease (AD) start before overt cognitive symptoms arise, but it is not well-known how they relate to the first subtle cognitive changes. The objective for this study was to examine the independent associations of the AD hallmarks β-amyloid (Aβ), tau, and neurodegeneration with different cognitive domains in cognitively unimpaired (CU) individuals.

METHODS

In this cross-sectional study, CU participants from the prospective BioFINDER-2 study were included. All had CSF biomarkers (Aβ42 and phosphorylated tau [p-tau]181), MRI (cortical thickness of AD-susceptible regions), Aβ-PET (neocortical uptake), tau-PET (entorhinal uptake), and cognitive test data for memory, executive function, verbal function, and visuospatial function. Multivariable linear regression models were performed using either CSF Aβ42, p-tau181, and cortical thickness or Aβ-PET, tau-PET, and cortical thickness as predictors of cognitive function. The results were validated in an independent cohort (Alzheimer's Disease Neuroimaging Initiative [ADNI]).

RESULTS

A total of 316 CU participants were included from the BioFINDER-2 study. Abnormal Aβ status was independently associated with the executive measure, regardless of modality (CSF Aβ42, β = 0.128, p = 0.024; Aβ-PET, β = 0.124, p = 0.049), while tau was independently associated with memory (CSF p-tau181, β = 0.132, p = 0.018; tau-PET, β = 0.189, p = 0.002). Cortical thickness was independently associated with the executive measure and verbal fluency in both models (p = 0.005-0.018). To examine the relationships in the earliest stage of preclinical AD, only participants with normal biomarkers of tau and neurodegeneration were included (n = 217 CSF-based; n = 246 PET-based). Again, Aβ status was associated with executive function (CSF Aβ42, β = 0.189, p = 0.005; Aβ-PET, β = 0.146, p = 0.023), but not with other cognitive domains. The results were overall replicated in the ADNI cohort (n = 361).

DISCUSSION

These findings suggest that Aβ is independently associated with worse performance on an executive measure but not with memory performance, which instead is associated with tau pathology. This may have implications for early preclinical AD screening and outcome measures in AD trials targeting Aβ pathology.

Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020.

METHODS

We identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion.

RESULTS

Disease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity.

DISCUSSION

ADNI has had a profound impact in improving clinical trials for AD.

Combining plasma phospho-tau and accessible measures to evaluate progression to Alzheimer's dementia in mild cognitive impairment patients

BACKGROUND

Up to now, there are no clinically available minimally invasive biomarkers to accurately identify mild cognitive impairment (MCI) patients who are at greater risk to progress to Alzheimer's disease (AD) dementia. The recent advent of blood-based markers opens the door for more accessible biomarkers. We aimed to identify which combinations of AD related plasma biomarkers and other easily accessible assessments best predict progression to AD dementia in patients with mild cognitive impairment (MCI).

METHODS

We included patients with amnestic MCI (n = 110) followed prospectively over 3 years to assess clinical status. Baseline plasma biomarkers (amyloid-β 42/40, phosphorylated tau217 [p-tau217], neurofilament light and glial fibrillary acidic protein), hippocampal volume, APOE genotype, and cognitive tests were available. Logistic regressions with conversion to amyloid-positive AD dementia within 3 years as outcome was used to evaluate the performance of different biomarkers measured at baseline, used alone or in combination. The first analyses included only the plasma biomarkers to determine the ones most related to AD dementia conversion. Second, hippocampal volume, APOE genotype and a brief cognitive composite score (mPACC) were combined with the best plasma biomarker.

RESULTS

Of all plasma biomarker combinations, p-tau217 alone had the best performance for discriminating progression to AD dementia vs all other combinations (AUC 0.84, 95% CI 0.75-0.93). Next, combining p-tau217 with hippocampal volume, cognition, and APOE genotype provided the best discrimination between MCI progressors vs. non-progressors (AUC 0.89, 0.82-0.95). Across the few best models combining different markers, p-tau217 and cognition were consistently the main contributors. The most parsimonious model including p-tau217 and cognition had a similar model fit, but a slightly lower AUC (0.87, 0.79-0.95, p = 0.07).

CONCLUSION

We identified that combining plasma p-tau217 and a brief cognitive composite score was strongly related to greater risk of progression to AD dementia in MCI patients, suggesting that these measures could be key components of future prognostic algorithms for early AD.

TRIAL REGISTRATION

NCT01028053 , registered December 9, 2009.

The amyloid hypothesis in Alzheimer disease: new insights from new therapeutics

Many drugs that target amyloid-β (Aβ) in Alzheimer disease (AD) have failed to demonstrate clinical efficacy. However, four anti-Aβ antibodies have been shown to mediate the removal of amyloid plaque from brains of patients with AD, and the FDA has recently granted accelerated approval to one of these, aducanumab, using reduction of amyloid plaque as a surrogate end point. The rationale for approval and the extent of the clinical benefit from these antibodies are under intense debate. With the aim of informing this debate, we review clinical trial data for drugs that target Aβ from the perspective of the temporal interplay between the two pathognomonic protein aggregates in AD - Aβ plaques and tau neurofibrillary tangles - and their relationship to cognitive impairment, highlighting differences in drug properties that could affect their clinical performance. On this basis, we propose that Aβ pathology drives tau pathology, that amyloid plaque would need to be reduced to a low level (~20 centiloids) to reveal significant clinical benefit and that there will be a lag between the removal of amyloid and the potential to observe a clinical benefit. We conclude that the speed of amyloid removal from the brain by a potential therapy will be important in demonstrating clinical benefit in the context of a clinical trial.

Trials and Treatments for Vascular Brain Health: Risk Factor Modification and Cognitive Outcomes

There is robust evidence linking vascular health to brain health, cognition, and dementia. In this article, we present evidence from trials of vascular risk factor treatment on cognitive outcomes. We summarize findings from randomized controlled trials of antihypertensives, lipid-lowering medications, diabetes treatments (including antidiabetic drugs versus placebo, and intensive versus standard glycemic control), and multidomain interventions (that target several domains simultaneously such as control of vascular and metabolic factors, nutrition, physical activity, and cognitive stimulation etc). We report that evidence on the efficacy of vascular risk reduction interventions is promising, but not yet conclusive, and several methodological limitations hamper interpretation. Evidence mainly comes from high-income countries and, as cognition and dementia have not been the primary outcomes of many trials, evaluation of cognitive changes have often been limited. As the cognitive aging process occurs over decades, it is unclear whether treatment during the late-life window is optimal for dementia prevention, yet older individuals have been the target of most trials thus far. Further, many trials have not been powered to explore interactions with modifiers such as age, race, and apolipoprotein E, even though sub-analyses from some trials indicate that the success of interventions differs depending on patient characteristics. Due to the complex multifactorial etiology of dementia, and variations in risk factors between individuals, multidomain interventions targeting several risk factors and mechanisms are likely to be needed and the long-term sustainability of preventive interventions will require personalized approaches that could be facilitated by digital health tools. This is especially relevant during the coronavirus disease 2019 (COVID-19) pandemic, where intervention strategies will need to be adapted to the new normal, when face-to-face engagement with participants is limited and public health measures may create changes in lifestyle that affect individuals’ vascular risk profiles and subsequent risk of cognitive decline.

Association Between Late-Life Neuropsychiatric Symptoms and Cognitive Decline in Relation to White Matter Hyperintensities and Amyloid Burden

BACKGROUND

Neuropsychiatric symptoms (NPS) among cognitively normal older adults are increasingly recognized as risk factors for cognitive decline and impairment. However, the underlying mechanisms remain unclear.

OBJECTIVE

To examine whether biomarkers of Alzheimer's disease (amyloid burden) and cerebrovascular disease (white matter hyperintensity (WMH) volume) modify the association between NPS and cognitive decline among cognitively unimpaired older adults.

METHODS

Analyses included 193 cognitively unimpaired participants (M age = 70 years) from the BIOCARD study, including 148 with PET amyloid and WMH biomarker data. NPS were measured with Neuropsychiatric Inventory and Geriatric Depression Scale scores. Linear mixed effects models were used to examine the association between baseline NPS and longitudinal cognitive trajectories (M follow-up = 3.05 years), using separate models for global, episodic memory, and executive function cognitive composite scores. In a subset of individuals with biomarker data, we evaluated whether WMH or cortical amyloid burden modified the relationship between NPS and cognitive change (as indicated by the NPS×biomarker×time interactions).

RESULTS

Higher baseline NPS were associated with lower executive function scores, but not a faster rate of decline in executive function. NPS symptoms were unrelated to the global or episodic memory composite scores, and there was little evidence of a relationship between NPS symptoms and cognitive change over time. The associations between NPS and cognitive decline did not differ by amyloid or WMH burden, and NPS were unrelated to amyloid and WMH burden.

CONCLUSION

These results suggest that the effect of neuropsychiatric symptoms on executive dysfunction may occur through mechanisms outside of amyloid and cerebrovascular disease.

Retaining Participants in Longitudinal Studies of Alzheimer's Disease

BACKGROUND

Retention of study participants is essential to advancing Alzheimer's disease (AD) research and developing therapeutic interventions. However, recent multi-year AD studies have lost 10% to 54% of participants.

OBJECTIVE

We surveyed a random sample of 443 participants (Clinical Dementia Rating [CDR]≤1) at four Alzheimer Disease Research Centers to elucidate perceived facilitators and barriers to continued participation in longitudinal AD research.

METHODS

Reasons for participation were characterized with factor analysis. Effects of perceived fulfillment of one's own goals and complaints on attendance and likelihood of dropout were estimated with logistic regression models. Open-ended responses suggesting study improvements were analyzed with a Latent Dirichlet Allocation topic model.

RESULTS

Factor analyses revealed two categories, personal benefit and altruism, as drivers of continued participation. Participants with cognitive impairment (CDR > 0) emphasized personal benefits more than societal benefits. Participants with higher trust in medical researchers were more likely to emphasize broader social benefits. A minority endorsed any complaints. Higher perceived fulfillment of one's own goals and fewer complaints were related to higher attendance and lower likelihood of dropout. Facilitators included access to medical center support and/or future treatment, learning about AD and memory concerns, and enjoying time with staff. Participants' suggestions emphasized more feedback about individual test results and AD research.

CONCLUSION

The results confirmed previously identified facilitators and barriers. Two new areas, improved communication about individual test results and greater feedback about AD research, emerged as the primary factors to improve participation.

Integrated Alzheimer's Disease Rating Scale: Clinically meaningful change estimates

Introduction

The Integrated Alzheimer's Disease Rating Scale (iADRS) has been used to detect differences in disease progression in early Alzheimer's disease (AD). The objectives of this study were to enhance understanding of iADRS point changes within the context of clinical trials, and to establish a minimal clinically important difference (MCID) on the iADRS.

Methods

Data from AMARANTH and EXPEDITION3 were analyzed using various approaches, including anchor‐based, distribution‐based, regression analyses, and cumulative distribution function (CDF) plots. Three potential anchors were examined, including the Clinical Dementia Rating—Sum of Boxes, Mini‐Mental State Examination, and Functional Activities Questionnaire. Triangulation of all results was used to determine the MCID for participants with mild cognitive impairment (MCI) due to AD and AD with mild dementia.

Results

All three anchors met criteria for “sufficiently associated” (|r| = 0.4–0.7). Cumulatively, results from anchor‐based and distribution‐based results converged to suggest an iADRS MCID of 5 points for MCI due to AD and 9 points for AD with mild dementia. Regression analyses and CDF plots supported these values.

Discussion

These findings suggest the iADRS can be used in clinical trials to detect a clinically meaningful outcome of AD progression.

Clinical Trial Endpoints and Their Clinical Meaningfulness in Early Stages of Alzheimer's Disease

As the focus of Alzheimer's disease (AD) therapeutic development shifts to the early stages of the disease, the clinical endpoints used in drug trials, and how these might translate into clinical practice, are of increasing importance. The clinical meaningfulness of trial outcome measures is often unclear, with a lack of conclusive evidence as to how these measures correlate to changes in disease progression and treatment response. Clarifying this would benefit all, including patients, care partners, primary care providers, regulators, and payers, and would enhance our understanding of the relationship between clinical trial endpoints and assessments used in everyday practice. At present, there is a wide range of assessment tools used in clinical trials for AD and substantial variability in measures selected as endpoints across these trials. The aim of this review is to summarize the most commonly used assessment tools for early stages of AD, describe their use in clinical trials and clinical practice, and discuss what might constitute clinically meaningful change in these measures in relation to disease progression and treatment response.

Amyloid and tau PET-positive cognitively unimpaired individuals are at high risk for future cognitive decline

A major unanswered question in the dementia field is whether cognitively unimpaired individuals who harbor both Alzheimer's disease neuropathological hallmarks (that is, amyloid-β plaques and tau neurofibrillary tangles) can preserve their cognition over time or are destined to decline. In this large multicenter amyloid and tau positron emission tomography (PET) study (n = 1,325), we examined the risk for future progression to mild cognitive impairment and the rate of cognitive decline over time among cognitively unimpaired individuals who were amyloid PET-positive (A⁺) and tau PET-positive (T⁺) in the medial temporal lobe (A⁺T_MTL⁺) and/or in the temporal neocortex (A⁺T_NEO-T⁺) and compared them with A⁺T^- and A^-T^- groups. Cox proportional-hazards models showed a substantially increased risk for progression to mild cognitive impairment in the A⁺T_NEO-T⁺ (hazard ratio (HR) = 19.2, 95% confidence interval (CI) = 10.9-33.7), A⁺T_MTL⁺ (HR = 14.6, 95% CI = 8.1-26.4) and A⁺T^- (HR = 2.4, 95% CI = 1.4-4.3) groups versus the A^-T^- (reference) group. Both A⁺T_MTL⁺ (HR = 6.0, 95% CI = 3.4-10.6) and A⁺T_NEO-T⁺ (HR = 7.9, 95% CI = 4.7-13.5) groups also showed faster clinical progression to mild cognitive impairment than the A⁺T^- group. Linear mixed-effect models indicated that the A⁺T_NEO-T⁺ (β = -0.056 ± 0.005, T = -11.55, P < 0.001), A⁺T_MTL⁺ (β = -0.024 ± 0.005, T = -4.72, P < 0.001) and A⁺T^- (β = -0.008 ± 0.002, T = -3.46, P < 0.001) groups showed significantly faster longitudinal global cognitive decline compared to the A^-T^- (reference) group (all P < 0.001). Both A⁺T_NEO-T⁺ (P < 0.001) and A⁺T_MTL⁺ (P = 0.002) groups also progressed faster than the A⁺T^- group. In summary, evidence of advanced Alzheimer's disease pathological changes provided by a combination of abnormal amyloid and tau PET examinations is strongly associated with short-term (that is, 3-5 years) cognitive decline in cognitively unimpaired individuals and is therefore of high clinical relevance.

Bleeding Risk of Dual Antiplatelet Therapy after Minor Stroke or TIA

OBJECTIVE

To identify the risk of bleeding events and potential risk factors within 90 days in patients carried CYP2C19 loss-of-function alleles and received dual antiplatelet therapy after minor stroke or transient ischemic attack.

METHODS

A total of 6,412 patients were enrolled from the Clopidogrel with aspirin in High-risk patients with Acute Non-disabling Cerebrovascular Events II (CHANCE-2) trial. The main outcome was any bleeding within 90 days defined by the criteria from Global Utilisation of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries (GUSTO).

RESULTS

A total of 250 (3.9%) bleeding events were reported, which occurred mainly within the 21 days of dual antiplatelet therapy (200 cases, 3.1%). Minor bleeding of the skin bruises, epistaxis, and gum bleeding was most frequent. Multivariate analysis showed that treatment with ticagrelor-aspirin compared with clopidogrel-aspirin was associated with increased bleeding (hazard ratio [HR], 2.21; 95% confidence interval [CI], 1.68-2.89; P<0.001). Current smoking was associated with a lower risk of bleeding (HR, 0.70; 95% CI, 0.52-0.95; P=0.02). Additionally, ticagrelor-aspirin compared with clopidogrel-aspirin was associated with higher risk of bleeding in patients aged <65 years (HR, 2.87; 95% CI, 1.95-4.22) and those without diabetes mellitus (HR, 2.65; 95% CI, 1.88-3.73) (P for interaction=0.04 and 0.03, respectively).

INTERPRETATION

Bleeding events mostly occurred within the 21-day dual antiplatelet therapy stage and were generally mild. The risk of bleeding was greater in non-smoking patients, and was associated with treatment with ticagrelor-aspirin compared with clopidogrel-aspirin particularly in aged <65 years and non-diabetic patients. This article is protected by copyright. All rights reserved.

Longitudinal Cognitive Performance of Older Adults With ADHD Presenting to a Cognitive Neurology Clinic: A Case Series of Change Up to 21 Years

Background: The neuropsychological features of older adults with ADHD are largely unknown. This retrospective chart review aims to elucidate their cognitive trajectories using a case series of six older adults with ADHD presenting with memory complaints to a cognitive neurology clinic, whom we argue are a particularly relevant group to study due to their potential to mimic neurodegenerative syndromes.

Methods: Participants were included if they were age 40 or older at intake, had ADHD based on DSM-5 criteria, and had cognitive data collected prior to 2014 with follow-up at least 5 years later.

Results: Five men and one woman were included (M = 53.8 years at intake) and had an average of 135.0 months of follow-up data available. Despite notable between- and within-subject variability, cognition generally improved or remained stable across visits. Two participants experienced notable memory decline, but a global consideration of their performance in other domains suggests these deficits may be frontally-mediated.

Conclusion: In this small sample, cognition remained generally unchanged across 5–21 years. Isolated impairments likely reflect substantial intra-individual variability across time and measures.

DeepAtrophy: Teaching a neural network to detect progressive changes in longitudinal MRI of the hippocampal region in Alzheimer's disease

Measures of change in hippocampal volume derived from longitudinal MRI are a well-studied biomarker of disease progression in Alzheimer's disease (AD) and are used in clinical trials to track therapeutic efficacy of disease-modifying treatments. However, longitudinal MRI change measures based on deformable registration can be confounded by MRI artifacts, resulting in over-estimation or underestimation of hippocampal atrophy. For example, the deformation-based-morphometry method ALOHA (Das et al., 2012) finds an increase in hippocampal volume in a substantial proportion of longitudinal scan pairs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, unexpected, given that the hippocampal gray matter is lost with age and disease progression. We propose an alternative approach to quantify disease progression in the hippocampal region: to train a deep learning network (called DeepAtrophy) to infer temporal information from longitudinal scan pairs. The underlying assumption is that by learning to derive time-related information from scan pairs, the network implicitly learns to detect progressive changes that are related to aging and disease progression. Our network is trained using two categorical loss functions: one that measures the network's ability to correctly order two scans from the same subject, input in arbitrary order; and another that measures the ability to correctly infer the ratio of inter-scan intervals between two pairs of same-subject input scans. When applied to longitudinal MRI scan pairs from subjects unseen during training, DeepAtrophy achieves greater accuracy in scan temporal ordering and interscan interval inference tasks than ALOHA (88.5% vs. 75.5% and 81.1% vs. 75.0%, respectively). A scalar measure of time-related change in a subject level derived from DeepAtrophy is then examined as a biomarker of disease progression in the context of AD clinical trials. We find that this measure performs on par with ALOHA in discriminating groups of individuals at different stages of the AD continuum. Overall, our results suggest that using deep learning to infer temporal information from longitudinal MRI of the hippocampal region has good potential as a biomarker of disease progression, and hints that combining this approach with conventional deformation-based morphometry algorithms may lead to improved biomarkers in the future.

Sleep and longitudinal cognitive performance in preclinical and early symptomatic Alzheimer's disease

Sleep monitoring may provide markers for future Alzheimer's disease; however, the relationship between sleep and cognitive function in preclinical and early symptomatic Alzheimer's disease is not well understood. Multiple studies have associated short and long sleep times with future cognitive impairment. Since sleep and the risk of Alzheimer's disease change with age, a greater understanding of how the relationship between sleep and cognition changes over time is needed. In this study, we hypothesized that longitudinal changes in cognitive function will have a non-linear relationship with total sleep time, time spent in non-REM and REM sleep, sleep efficiency and non-REM slow wave activity. To test this hypothesis, we monitored sleep-wake activity over 4-6 nights in 100 participants who underwent standardized cognitive testing longitudinally, APOE genotyping, and measurement of Alzheimer's disease biomarkers, total tau and amyloid-β42 in the CSF. To assess cognitive function, individuals completed a neuropsychological testing battery at each clinical visit that included the Free and Cued Selective Reminding test, the Logical Memory Delayed Recall assessment, the Digit Symbol Substitution test and the Mini-Mental State Examination. Performance on each of these four tests was Z-scored within the cohort and averaged to calculate a preclinical Alzheimer cognitive composite score. We estimated the effect of cross-sectional sleep parameters on longitudinal cognitive performance using generalized additive mixed effects models. Generalized additive models allow for non-parametric and non-linear model fitting and are simply generalized linear mixed effects models; however, the linear predictors are not constant values but rather a sum of spline fits. We found that longitudinal changes in cognitive function measured by the cognitive composite decreased at low and high values of total sleep time (P < 0.001), time in non-REM (P < 0.001) and REM sleep (P < 0.001), sleep efficiency (P < 0.01) and <1 Hz and 1-4.5 Hz non-REM slow wave activity (P < 0.001) even after adjusting for age, CSF total tau/amyloid-β42 ratio, APOE ε4 carrier status, years of education and sex. Cognitive function was stable over time within a middle range of total sleep time, time in non-REM and REM sleep and <1 Hz slow wave activity, suggesting that certain levels of sleep are important for maintaining cognitive function. Although longitudinal and interventional studies are needed, diagnosing and treating sleep disturbances to optimize sleep time and slow wave activity may have a stabilizing effect on cognition in preclinical or early symptomatic Alzheimer's disease.

Genetic effects on longitudinal cognitive decline during the early stages of Alzheimer's disease

Cognitive decline in early-stage Alzheimer's disease (AD) may depend on genetic variability. In the Swedish BioFINDER study, we used polygenic scores (PGS) (for AD, intelligence, and educational attainment) to predict longitudinal cognitive change (measured by mini-mental state examination (MMSE) [primary outcome] and other cognitive tests) over a mean of 4.2 years. We included 260 β-amyloid (Aβ) negative cognitively unimpaired (CU) individuals, 121 Aβ-positive CU (preclinical AD), 50 Aβ-negative mild cognitive impairment (MCI) patients, and 127 Aβ-positive MCI patients (prodromal AD). Statistical significance was determined at Bonferroni corrected p value < 0.05. The PGS for intelligence (beta = 0.1, p = 2.9e-02) was protective against decline in MMSE in CU and MCI participants regardless of Aβ status. The polygenic risk score for AD (beta =  - 0.12, p = 9.4e-03) was correlated with the rate of change in MMSE and was partially mediated by Aβ-pathology (mediation effect 20%). There was no effect of education PGS on cognitive measures. Genetic variants associated with intelligence mitigate cognitive decline independent of Aβ-pathology, while effects of genetic variants associated with AD are partly mediated by Aβ-pathology.

Personalized prediction of progression in pre-dementia patients based on individual biomarker profile: A development and validation study

INTRODUCTION

The prognosis of patients at the pre-dementia stage is difficult to define. The aim of this study is to develop and validate a biomarker-based continuous model for predicting the individual cognitive level at any future moment. In addition to personalized prognosis, such a model could reduce trial sample size requirements by allowing inclusion of a homogenous patient population.

METHODS

Disease-progression modeling of longitudinal cognitive scores of pre-dementia patients (baseline Clinical Dementia Rating ≤ 0.5) was used to derive a biomarker profile that was predictive of patient's cognitive progression along the dementia continuum. The biomarker profile model was developed and validated in the MEMENTO cohort and externally validated in the Alzheimer's Disease Neuroimaging Initiative.

RESULTS

Of nine candidate biomarkers in the development analysis, three cerebrospinal fluid and two magnetic resonance imaging measures were selected to form the final biomarker profile. The model-based prognosis of individual future cognitive deficit was shown to significantly improve when incorporating biomarker information on top of cognition and demographic data. In trial power calculations, adjusting the primary analysis for the baseline biomarker profile reduced sample size requirements by ≈10%. Compared to conventional cognitive cut-offs, inclusion criteria based on biomarker-profile cut-offs resulted in up to 28% reduced sample size requirements due to increased homogeneity in progression patterns.

DISCUSSION

The biomarker profile allows prediction of personalized trajectories of future cognitive progression. This enables accurate personalized prognosis in clinical care and better selection of patient populations for clinical trials. A web-based application for prediction of patients' future cognitive progression is available online.

Association of Sleep and β-Amyloid Pathology Among Older Cognitively Unimpaired Adults

IMPORTANCE

Disrupted sleep commonly occurs with progressing neurodegenerative disease. Large, well-characterized neuroimaging studies of cognitively unimpaired adults are warranted to clarify the magnitude and onset of the association between sleep and emerging β-amyloid (Aβ) pathology.

OBJECTIVE

To evaluate the associations between daytime and nighttime sleep duration with regional Aβ pathology in older cognitively unimpaired adults.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study, screening data were collected between April 1, 2014, and December 31, 2017, from healthy, cognitively unimpaired adults 65 to 85 years of age who underwent florbetapir F 18 positron emission tomography (PET), had APOE genotype information, scored between 25 and 30 on the Mini-Mental State Examination, and had a Clinical Dementia Rating of 0 for the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease (A4) Study. Data analysis was performed from December 1, 2019, to May 10, 2021.

EXPOSURES

Self-reported daytime and nighttime sleep duration.

MAIN OUTCOMES AND MEASURES

Regional Aβ pathology, measured by florbetapir PET standardized uptake value ratio.

RESULTS

Amyloid PET and sleep duration information was acquired on 4425 cognitively unimpaired participants (mean [SD] age, 71.3 [4.7] years; 2628 [59.4%] female; 1509 [34.1%] tested Aβ positive). Each additional hour of nighttime sleep was associated with a 0.005 reduction of global Aβ standardized uptake value ratio (F1, 4419 = 5.0; P = .03), a 0.009 reduction of medial orbitofrontal Aβ (F1, 4419 = 17.4; P < .001), and a 0.011 reduction of anterior cingulate Aβ (F1, 4419 = 15.9; P < .001). When restricting analyses to participants who tested Aβ negative, nighttime sleep was associated with a 0.006 reduction of medial orbitofrontal Aβ (F1,2910 = 16.9; P < .001) and a 0.005 reduction of anterior cingulate Aβ (F1,2910 = 7.6; P = .03). Daytime sleep was associated with a 0.013 increase of precuneus Aβ (F1,2910 = 7.3; P = .03) and a 0.024 increase of posterior cingulate Aβ (F1,2910 = 14.2; P = .001) in participants who tested Aβ negative.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, the increased risk of Aβ deposition with reduced nighttime sleep duration occurred early, before cognitive impairment or significant Aβ deposition. Daytime sleep may be associated with an increase in risk for early Aβ accumulation and did not appear to be corrective for loss of nighttime sleep, demonstrating a circadian rhythm dependence of sleep in preventing Aβ accumulation. Treatments that improve sleep may reduce early Aβ accumulation and aid in delaying the onset of cognitive dysfunction associated with early Alzheimer disease.

Building clinically relevant outcomes across the Alzheimer's disease spectrum

Demonstrating that treatments are clinically meaningful across the Alzheimer's disease (AD) continuum is critical for meeting our goals of accelerating a cure by 2025. While this topic has been a focus of several Alzheimer's Association Research Roundtable (AARR) meetings, there remains no consensus as to what constitutes a "clinically meaningful outcome" in the eyes of patients, clinicians, care partners, policymakers, payers, and regulatory bodies. Furthermore, the field has not come to agreement as to what constitutes a clinically meaningful treatment effect at each stage of disease severity. The AARR meeting on November 19-20, 2019, reviewed current approaches to defining clinical meaningfulness from various perspectives including those of patients and care partners, clinicians, regulators, health economists, and public policymakers. Participants discussed approaches that may confer clinical relevance at each stage of the disease continuum and fostered discussion about what should guide us in the future.

Plasma biomarkers of Alzheimer's disease improve prediction of cognitive decline in cognitively unimpaired elderly populations

Plasma biomarkers of amyloid, tau, and neurodegeneration (ATN) need to be characterized in cognitively unimpaired (CU) elderly individuals. We therefore tested if plasma measurements of amyloid-β (Aβ)42/40, phospho-tau217 (P-tau217), and neurofilament light (NfL) together predict clinical deterioration in 435 CU individuals followed for an average of 4.8 ± 1.7 years in the BioFINDER study. A combination of all three plasma biomarkers and basic demographics best predicted change in cognition (Pre-Alzheimer's Clinical Composite; R2 = 0.14, 95% CI [0.12-0.17]; P < 0.0001) and subsequent AD dementia (AUC = 0.82, 95% CI [0.77-0.91], P < 0.0001). In a simulated clinical trial, a screening algorithm combining all three plasma biomarkers would reduce the required sample size by 70% (95% CI [54-81]; P < 0.001) with cognition as trial endpoint, and by 63% (95% CI [53-70], P < 0.001) with subsequent AD dementia as trial endpoint. Plasma ATN biomarkers show usefulness in cognitively unimpaired populations and could make large clinical trials more feasible and cost-effective.

Prediction of future Alzheimer's disease dementia using plasma phospho-tau combined with other accessible measures

A combination of plasma phospho-tau (P-tau) and other accessible biomarkers might provide accurate prediction about the risk of developing Alzheimer's disease (AD) dementia. We examined this in participants with subjective cognitive decline and mild cognitive impairment from the BioFINDER (n = 340) and Alzheimer's Disease Neuroimaging Initiative (ADNI) (n = 543) studies. Plasma P-tau, plasma Aβ42/Aβ40, plasma neurofilament light, APOE genotype, brief cognitive tests and an AD-specific magnetic resonance imaging measure were examined using progression to AD as outcome. Within 4 years, plasma P-tau217 predicted AD accurately (area under the curve (AUC) = 0.83) in BioFINDER. Combining plasma P-tau217, memory, executive function and APOE produced higher accuracy (AUC = 0.91, P < 0.001). In ADNI, this model had similar AUC (0.90) using plasma P-tau181 instead of P-tau217. The model was implemented online for prediction of the individual probability of progressing to AD. Within 2 and 6 years, similar models had AUCs of 0.90-0.91 in both cohorts. Using cerebrospinal fluid P-tau, Aβ42/Aβ40 and neurofilament light instead of plasma biomarkers did not improve the accuracy significantly. The clinical predictions by memory clinic physicians had significantly lower accuracy (4-year AUC = 0.71). In summary, plasma P-tau, in combination with brief cognitive tests and APOE genotyping, might greatly improve the diagnostic prediction of AD and facilitate recruitment for AD trials.

Clinical diagnosis of Alzheimer's disease: recommendations of the International Working Group

In 2018, the US National Institute on Aging and the Alzheimer's Association proposed a purely biological definition of Alzheimer's disease that relies on biomarkers. Although the intended use of this framework was for research purposes, it has engendered debate and challenges regarding its use in everyday clinical practice. For instance, cognitively unimpaired individuals can have biomarker evidence of both amyloid β and tau pathology but will often not develop clinical manifestations in their lifetime. Furthermore, a positive Alzheimer's disease pattern of biomarkers can be observed in other brain diseases in which Alzheimer's disease pathology is present as a comorbidity. In this Personal View, the International Working Group presents what we consider to be the current limitations of biomarkers in the diagnosis of Alzheimer's disease and, on the basis of this evidence, we propose recommendations for how biomarkers should and should not be used for diagnosing Alzheimer's disease in a clinical setting. We recommend that Alzheimer's disease diagnosis be restricted to people who have positive biomarkers together with specific Alzheimer's disease phenotypes, whereas biomarker-positive cognitively unimpaired individuals should be considered only at-risk for progression to Alzheimer's disease.

Simultaneous modeling of Alzheimer's disease progression via multiple cognitive scales

Analyzing the progression of Alzheimer's disease (AD) is challenging due to lacking sensitivity in currently available measures. AD stages are typically defined based on cognitive cut-offs, but this results in heterogeneous patient groups. More accurate modeling of the continuous progression of the disease would enable more accurate patient prognosis. To address these issues, we propose a new multivariate continuous-time disease progression (MCDP) model. The model is formulated as a nonlinear mixed-effects model that aligns patients based on their predicted disease progression along a continuous latent disease timeline. The model is evaluated using long-term follow-up data from 2152 participants in the Alzheimer's Disease Neuroimaging Initiative. The MCDP model was used to simultaneously model three cognitive scales; the Alzheimer's Disease Assessment Scale-cognitive subscale, the Mini-Mental State Examination, and the Clinical Dementia Rating scale-sum of boxes. Compared with univariate modeling and previously proposed multivariate disease progression models, the MCDP model showed superior ability to predict future patient trajectories. Finally, based on the multivariate disease timeline estimated using the MCDP model, the sensitivity of the individual items of the cognitive scales along the different stages of disease was analyzed. The analysis showed that delayed memory recall items had the highest sensitivity in the early stages of disease, whereas language and attention items were sensitive later in disease.

Current advances in plasma and cerebrospinal fluid biomarkers in Alzheimer's disease

PURPOSE OF REVIEW

This review provides a concise overview of recent advances in cerebrospinal fluid (CSF) and blood-based biomarkers of Alzheimer's disease lesions.

RECENT FINDINGS

Important recent advances for CSF Alzheimer's disease biomarkers include the introduction of fully automated assays, the development and implementation of certified reference materials for CSF Aβ42 and a unified protocol for handling of samples, which all support reliability and availability of CSF Alzheimer's disease biomarkers. Aβ deposition can be detected using Aβ42/Aβ40 ratio in both CSF and plasma, though a much more modest change is seen in plasma. Tau aggregation can be detected using phosphorylated tau (P-tau) at threonine 181 and 217 in CSF, with similar accuracy in plasma. Neurofilament light (NfL) be measured in CSF and shows similar diagnostic accuracy in plasma. Though total tau (T-tau) can also be measured in plasma, this measure is of limited clinical relevance for Alzheimer's disease in its current immunoassay format.

SUMMARY

Alzheimer's disease biomarkers, including Aβ, P-tau and NfL can now be reliably measured in both CSF and blood. Plasma-based measures of P-tau show particular promise, with potential applications in both clinical practice and in clinical trials.

The accumulation rate of tau aggregates is higher in females and younger amyloid-positive subjects

The development of tau-PET allows paired helical filament tau pathology to be visualized in vivo. Increased knowledge about conditions affecting the rate of tau accumulation could guide the development of therapies halting the progression of Alzheimer’s disease. However, the factors modifying the rate of tau accumulation over time in Alzheimer’s disease are still largely unknown. Large-scale longitudinal cohort studies, adjusting for baseline tau load, are needed to establish such risk factors. In the present longitudinal study, 419 participants from four cohorts in the USA (Avid 05e, n = 157; Expedition-3, n = 82; ADNI, n = 123) and Sweden (BioFINDER, n = 57) were scanned repeatedly with tau-PET. The study participants were cognitively unimpaired (n = 153), or patients with mild cognitive impairment (n = 139) or Alzheimer’s disease dementia (n = 127). Participants underwent two to four tau-PET (¹⁸F-flortaucipir) scans with a mean (± standard deviation) of 537 (±163) days between the first and last scan. The change in tau-PET signal was estimated in temporal meta- and neocortical regions of interest. Subject specific tau-PET slopes were predicted simultaneously by age, sex, amyloid status (determined by amyloid-β PET), APOE ε4 genotype, study cohort, diagnosis and baseline tau load. We found that accelerated increase in tau-PET signal was observed in amyloid-β-positive mild cognitive impairment (3.0 ± 5.3%) and Alzheimer’s disease dementia (2.9 ± 5.7%), respectively, when compared to either amyloid-β-negative cognitively unimpaired (0.4 ± 2.7%), amyloid-β-negative mild cognitive impairment (−0.4 ± 2.3%) or amyloid-β-positive cognitively unimpaired (1.2 ± 2.8%). Tau-PET uptake was accelerated in females (temporal region of interest: t = 2.86, P = 0.005; neocortical region of interest: t = 2.90, P = 0.004), younger individuals (temporal region of interest: t = −2.49, P = 0.013), and individuals with higher baseline tau-PET signal (temporal region of interest: t = 3.83, P < 0.001; neocortical region of interest: t = 5.01, P < 0.001). Tau-PET slopes decreased with age in amyloid-β-positive subjects, but were stable by age in amyloid-β-negative subjects (age × amyloid-β status interaction: t = −2.39, P = 0.018). There were no effects of study cohort or APOE ε4 positivity. In a similar analysis on longitudinal amyloid-β-PET (in ADNI subjects only, n = 639), we found significant associations between the rate of amyloid-β accumulation and APOE ε4 positivity, older age and baseline amyloid-β positivity, but no effect of sex. In conclusion, in this longitudinal PET study comprising four cohorts, we found that the tau accumulation rate is greater in females and younger amyloid-β-positive individuals, while amyloid-β accumulation is greater in APOE ε4 carriers and older individuals. These findings are important considerations for the design of clinical trials, and might improve our understanding of factors associated with faster tau aggregation and spread.

Amyloid PET Imaging in Self-Identified Non-Hispanic Black Participants of the Anti-Amyloid in Asymptomatic Alzheimer's Disease (A4) Study

OBJECTIVE

To examine whether amyloid PET in cognitively normal (CN) individuals screened for the Anti-Amyloid in Asymptomatic Alzheimer's Disease (A4) study differed across self-identified non-Hispanic White and Black (NHW and NHB) groups.

METHODS

We examined 3,689 NHW and 144 NHB participants who passed initial screening for the A4 study and underwent amyloid PET. The effect of race on amyloid PET was examined using logistic (dichotomous groups) and linear (continuous values) regression controlling for age, sex, and number of APOE ε4 and APOE ε2 alleles. Associations between amyloid and genetically determined ancestry (reflecting African, South Asian, East Asian, American, and European populations) were tested within the NHB group. Potential interactions with APOE were assessed.

RESULTS

NHB participants had lower rates of amyloid positivity and lower continuous amyloid levels compared to NHW participants. This race effect on amyloid was strongest in the APOE ε4 group. Within NHB participants, those with a lower percentage of African ancestry had higher amyloid. A greater proportion of NHB participants did not pass initial screening compared to NHW participants, suggesting potential sources of bias related to race in the A4 PET data.

CONCLUSION

Reduced amyloid was observed in self-identified NHB participants who passed initial eligibility criteria for the A4 study. This work stresses the importance of investigating AD biomarkers in ancestrally diverse samples as well as the need for careful consideration regarding study eligibility criteria in AD prevention trials.

Association Between Apolipoprotein E ε2 vs ε4, Age, and β-Amyloid in Adults Without Cognitive Impairment

Importance

Although the most common recent approach in Alzheimer disease drug discovery is to directly target the β-amyloid (Aβ) pathway, the high prevalence of apolipoprotein E ε4 (APOE ε4) in Alzheimer disease and the ease of identifying ε4 carriers make the APOE genotype and its corresponding protein (apoE) an appealing therapeutic target to slow Aβ accumulation.

Objective

To determine whether the ε2 allele is protective against Aβ accumulation in the presence of the ε4 allele and evaluate how age and the APOE genotype are associated with emerging Aβ accumulation and cognitive dysfunction.

Design, Setting, and Participants

This cross-sectional study used screening data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease Study (A4 Study) collected from April 2014 to December 2017 and analyzed from November 2019 to July 2020. Of the 6943 participants who were a part of the multicenter clinical trial screening visit, 4432 were adults without cognitive impairment aged 65 to 85 years who completed a fluorine 18-labeled (18F)-florbetapir positron emission tomography scan, had APOE genotype information, and had a Clinical Dementia Rating of 0. Participants who were taking a prescription Alzheimer medication or had a current serious or unstable illness that could interfere with the study were excluded.

Main Outcomes and Measures

Aβ pathology, measured by 18F-florbetapir positron emission tomography and cognition, measured by the Preclinical Alzheimer Cognitive Composite.

Results

A total of 4432 participants were included (mean [SD] age, 71.3 [4.7] years; 2634 women [59.4%]), with a mean (SD) of 16.6 (2.8) years of education and 1512 (34.1%) with a positive Aβ level. APOE ε2 was associated with a reduction in both the overall (standardized uptake value ratio [SUVR], ε24, 1.11 [95% CI, 1.08-1.14]; ε34, 1.18 [95% CI, 1.17-1.19]) and the age-dependent level of Aβ in the presence of ε4, with Aβ levels in the APOE ε24 group (n = 115; ε24, 0.005 SUVR increase per year of age) increasing at less than half the rate with respect to increasing age compared with the APOE ε34 group (n = 1295; 0.012 SUVR increase per year of age; P = .04). The association between Aβ and decreasing Preclinical Alzheimer Cognitive Composite scores did not differ by APOE genotype, and the reduced performance on the Preclinical Alzheimer Cognitive Composite in APOE ε4 carriers compared with noncarriers was completely mediated by Aβ (unadjusted difference in composite scores between ε4 carriers and noncarriers = -0.084, P = .005; after adjusting for 18F-florbetapir = -0.006, P = .85; after adjusting for 18F-florbetapir and cardiovascular scores = -0.009, P = .78).

Conclusions and Relevance

These findings suggest that the protective outcome of carrying an ε2 allele in the presence of an ε4 allele against Aβ accumulation is important for potential treatments that attempt to biochemically mimic the function of the ε2 allele in order to facilitate Aβ clearance in ε4 carriers. Such a treatment strategy is appealing, as ε4 carriers make up approximately two-thirds of patients with Alzheimer disease dementia. This strategy could represent an early treatment option, as many ε4 carriers begin to accumulate Aβ in early middle age.

Association of serial position scores on memory tests and hippocampal-related neuropathologic outcomes

OBJECTIVE

To determine whether serial position scores in verbal memory differentiate hippocampal-related neuropathologic outcomes, we examined these associations in a sample of older adults without dementia who underwent autopsy.

METHODS

We used data from the Rush Memory and Aging Project, a longitudinal clinical-pathologic cohort study of community-dwelling adults. A total of 701 participants (mean age 82.7, 71.2% female) completed baseline cognitive evaluations and underwent brain autopsy to identify pathologic Alzheimer disease (AD), TDP-43 inclusions (defining limbic-predominant age-related TDP-43 encephalopathy [LATE]), and hippocampal sclerosis. The Consortium to Establish a Registry for Alzheimer's Disease word list memory test immediate recall trials provided serial position scores, which index the proportion of words recalled from the beginning (primacy scores) and end (recency scores) of a word list. Binary and ordinal logistic regressions examined associations between serial position scores and neuropathologic outcomes. Secondary outcomes included Alzheimer dementia and mild cognitive impairment proximate to death.

RESULTS

Primacy and recency scores were uncorrelated (r = 0.07). Each SD of better primacy score was associated with lower likelihood of neuropathologic changes (24% lower LATE, 31% lower pathologic AD, 37% lower hippocampal sclerosis). For pathologic AD, better baseline primacy scores were associated with a 36% lower likelihood of comorbidity with LATE or hippocampal sclerosis. Primacy scores better discriminated between clinical diagnoses proximate to death, including those with mild cognitive impairment compared to no impairment. Recency scores showed weaker or no associations.

CONCLUSIONS

Primacy scores may be particularly sensitive markers of AD and related hippocampal neuropathologies. The differential predictive value of serial position scores suggests they offer complementary information about disease outcomes in addition to the routinely used total recall scores.

Pain management and cognitive function among older adults: an exploratory study of the China Health and Retirement Longitudinal Study

BACKGROUND

Chronic pain and cognitive decline are common age-related conditions affecting a large segment of older populations. Little is known about the pathway of cognitive functioning during the course of pain management in older adults.

AIMS

The study aimed to examine the association between chronic body pain management and cognitive function over time among Chinese older adults.

METHODS

A total of 792 respondents aged 60 and above from urban and rural households in 28 provinces, 150 counties/districts, and 450 communities were selected from the China Health and Retirement Longitudinal Study (2013-2015). Cognitive function was measured in three domains: episodic memory, mental status, and global cognitive function. Difference-in-differences approach and mixed-effects linear regression models were employed to assess the association between chronic body pain management and cognitive function over time.

RESULTS

Scores of mental status were found to decline slower by 0.49 unit (SE = 0.22, p < 0.05) in respondents who received pain management using analgesics, complementary and alternative medicine, or both from 2013 to 2015 after controlling for basic demographic and health confounders.

CONCLUSION

Chronic pain management was associated with slower decline in domain-specific cognitive function, mental status over time. Findings of the study may contribute to understanding the mechanism of change in diverse cognitive abilities attributable to pain symptoms. More research is needed to elucidate the mediating effect of pain on cognitive decline, which could lead to testing of the impact of pain management on cognitive function among older population in both clinical and community settings.

Association of β-Amyloid Level, Clinical Progression, and Longitudinal Cognitive Change in Normal Older Individuals

OBJECTIVE

To determine the effect of β-amyloid (Aβ) level on progression risk to mild cognitive impairment (MCI) or dementia and longitudinal cognitive change in cognitively normal (CN) older individuals.

METHODS

All CN from the Australian Imaging Biomarkers and Lifestyle study with Aβ PET and ≥3 years follow-up were included (n = 534; age 72 ± 6 years; 27% Aβ positive; follow-up 5.3 ± 1.7 years). Aβ level was divided using the standardized 0-100 Centiloid scale: <15 CL negative, 15-25 CL uncertain, 26-50 CL moderate, 51-100 CL high, >100 CL very high, noting >25 CL approximates a positive scan. Cox proportional hazards analysis and linear mixed effect models were used to assess risk of progression and cognitive decline.

RESULTS

Aβ levels in 63% were negative, 10% uncertain, 10% moderate, 14% high, and 3% very high. Fifty-seven (11%) progressed to MCI or dementia. Compared to negative Aβ, the hazard ratio for progression for moderate Aβ was 3.2 (95% confidence interval [CI] 1.3-7.6; p < 0.05), for high was 7.0 (95% CI 3.7-13.3; p < 0.001), and for very high was 11.4 (95% CI 5.1-25.8; p < 0.001). Decline in cognitive composite score was minimal in the moderate group (-0.02 SD/year, p = 0.05), while the high and very high declined substantially (high -0.08 SD/year, p < 0.001; very high -0.35 SD/year, p < 0.001).

CONCLUSION

The risk of MCI or dementia over 5 years in older CN is related to Aβ level on PET, 5% if negative vs 25% if positive but ranging from 12% if 26-50 CL to 28% if 51-100 CL and 50% if >100 CL. This information may be useful for dementia risk counseling and aid design of preclinical AD trials.

Enriching the design of Alzheimer's disease clinical trials: Application of the polygenic hazard score and composite outcome measures

INTRODUCTION

Selecting individuals at high risk of Alzheimer's disease (AD) dementia and using the most sensitive outcome measures are important aspects of trial design.

METHODS

We divided participants from Alzheimer's Disease Neuroimaging Initiative at the 50th percentile of the predicted absolute risk of the polygenic hazard score (PHS). Outcome measures were the Alzheimer's Disease Assessment Schedule-Cognitive Subscale (ADAS-Cog), ADNI-Mem, Clinical Dementia Rating-Sum of Boxes (CDR SB), and Cognitive Function Composite 2 (CFC2). In addition to modeling, we use a power analysis compare numbers needed with each technique.

RESULTS

Data from 188 cognitively normal and 319 mild cognitively impaired (MCI) participants were analyzed. Using the ADAS-Cog to estimate sample sizes, without stratification over 24 months, would require 930 participants with MCI, while using the CFC2 and restricting participants to those in the upper 50th percentile would require only 284 participants.

DISCUSSION

Combining stratification by PHS and selection of a sensitive combined outcome measure in a cohort of patients with MCI can allow trial design that is more efficient, potentially less burdensome on participants, and more cost effective.

The pathway to secondary prevention of Alzheimer's disease

Alzheimer's disease (AD) is a continuum consisting of a preclinical stage that occurs decades before symptoms appear. As researchers make advances in investigating the continuum, the importance of developing drugs for secondary prevention is garnering increased discussion. For efficacious drug development for secondary prevention it is important to define what are the earliest biological stages of AD. The Alzheimer's Association Research Roundtable convened November 27 to 28, 2018 to focus on pre-clinical AD. This review will address the biological approach to defining pre-clinical AD, detection, identification of at-risk individuals, and lessons learned from trials such as A4 and TOMMORROW.

Statistical Disease Progression Modeling in Alzheimer Disease

Background: The characterizing symptom of Alzheimer disease (AD) is cognitive deterioration. While much recent work has focused on defining AD as a biological construct, most patients are still diagnosed, staged, and treated based on their cognitive symptoms. But the cognitive capability of a patient at any time throughout this deterioration reflects not only the disease state, but also the effect of the cognitive decline on the patient's pre-disease cognitive capability. Patients with high pre-disease cognitive capabilities tend to score better on cognitive tests that are sensitive early in disease relative to patients with low pre-disease cognitive capabilities at a similar disease stage. Thus, a single assessment with a cognitive test is often not adequate for determining the stage of an AD patient. Repeated evaluation of patients' cognition over time may improve the ability to stage AD patients, and such longitudinal assessments in combinations with biomarker assessments can help elucidate the time dynamics of biomarkers. In turn, this can potentially lead to identification of markers that are predictive of disease stage and future cognitive decline, possibly before any cognitive deficit is measurable.

Methods and Findings: This article presents a class of statistical disease progression models and applies them to longitudinal cognitive scores. These non-linear mixed-effects disease progression models explicitly model disease stage, baseline cognition, and the patients' individual changes in cognitive ability as latent variables. Maximum-likelihood estimation in these models induces a data-driven criterion for separating disease progression and baseline cognition. Applied to data from the Alzheimer's Disease Neuroimaging Initiative, the model estimated a timeline of cognitive decline that spans ~15 years from the earliest subjective cognitive deficits to severe AD dementia. Subsequent analyses demonstrated how direct modeling of latent factors that modify the observed data patterns provides a scaffold for understanding disease progression, biomarkers, and treatment effects along the continuous time progression of disease.

Conclusions: The presented framework enables direct interpretations of factors that modify cognitive decline. The results give new insights to the value of biomarkers for staging patients and suggest alternative explanations for previous findings related to accelerated cognitive decline among highly educated patients and patients on symptomatic treatments.

The preclinical amyloid sensitive composite to determine subtle cognitive differences in preclinical Alzheimer's disease

Recently, the focus of Alzheimer's disease (AD) research has shifted from the clinical stage to the preclinical stage. We, therefore, aimed to develop a cognitive composite score that can detect the subtle cognitive differences between the amyloid positive (Aβ+) and negative (Aβ-) status in cognitively normal (CN) participants. A total of 423 CN participants with Aβ positron emission tomography images were recruited. The multiple-indicators multiple-causes model found the latent mean difference between the Aβ+ and Aβ- groups in the domains of verbal memory, visual memory, and executive functions. The multivariate analysis of covariance (MANCOVA) showed that the Aβ+ group performed worse in tests related to the verbal and visual delayed recall, semantic verbal fluency, and inhibition of cognitive inference within the three cognitive domains. The Preclinical Amyloid Sensitive Composite (PASC) model we developed using the result of MANCOVA and the MMSE presented a good fit with the data. The accuracy of the PASC score when applied with age, sex, education, and APOE ε4 for distinguishing between Aβ+ and Aβ- was adequate (AUC = 0.764; 95% CI = 0.667-0.860) in the external validation set (N = 179). We conclude that the PASC can eventually contribute to facilitating more prevention trials in preclinical AD.

Unsupervised assessment of cognition in the Healthy Brain Project: Implications for web-based registries of individuals at risk for Alzheimer's disease

INTRODUCTION

Web-based platforms are used increasingly to assess cognitive function in unsupervised settings. The utility of cognitive data arising from unsupervised assessments remains unclear. We examined the acceptability, usability, and validity of unsupervised cognitive testing in middle-aged adults enrolled in the Healthy Brain Project.

METHODS

A total of 1594 participants completed unsupervised assessments of the Cogstate Brief Battery. Acceptability was defined by the amount of missing data, and usability by examining error of test performance and the time taken to read task instructions and complete tests (learnability).

RESULTS

Overall, we observed high acceptability (98% complete data) and high usability (95% met criteria for low error rates and high learnability). Test validity was confirmed by observation of expected inverse relationships between performance and increasing test difficulty and age.

CONCLUSION

Consideration of test design paired with acceptability and usability criteria can provide valid indices of cognition in the unsupervised settings used to develop registries of individuals at risk for Alzheimer's disease.

The A4 study: β-amyloid and cognition in 4432 cognitively unimpaired adults

Objective

To clarify the preclinical stage of Alzheimer’s disease by estimating when β‐amyloid accumulation first becomes associated with changes in cognition.

Methods

Here we studied a large group (N = 4432) of cognitively unimpaired individuals who were screened for inclusion in the A4 trial (age 65–85) to assess the effect of subthreshold levels of β‐amyloid on cognition and to identify which cognitive domains first become affected.

Results

β‐amyloid accumulation was linked to significant cognitive dysfunction in cognitively unimpaired participants with subthreshold levels of β‐amyloid in multiple measures of memory (Logical Memory Delayed Recall, P = 0.03; Free and Cued Selective Reminding Test, P < 0.001), the Preclinical Alzheimer’s Cognitive Composite (P = 0.01), and was marginally associated with decreased executive function (Digit Symbol Substitution, P = 0.07). Significantly, decreased cognitive scores were associated with suprathreshold levels of β‐amyloid, across all measures (P < 0.05). The Free and Cued Selective Reminding Test, a list recall memory test, appeared most sensitive to β‐amyloid ‐related decreases in average cognitive scores, outperforming all other cognitive domains, including the narrative recall memory test, Logical Memory.

Interpretation

Clinical trials for cognitively unimpaired β‐amyloid‐positive individuals will include a large number of individuals where mechanisms downstream from β‐amyloid pathology are already activated. These findings have implications for primary and secondary prevention of Alzheimer’s disease.

Amyloid β influences the relationship between cortical thickness and vascular load

INTRODUCTION

Cortical thickness has been proposed as a biomarker of Alzheimer's disease (AD)- related neurodegeneration, but the nature of its relationship with amyloid beta (Aβ) deposition and white matter hyperintensity volume (WMHV) in cognitively normal adults is unclear.

METHODS

We investigated the influences of Aβ status (negative/positive) and WMHV on cortical thickness in 408 cognitively normal adults aged 69.2 to 71.9 years who underwent 18F-Florbetapir positron emission tomography (PET) and structural magnetic resonance imaging (MRI). Two previously defined Alzheimer's disease (AD) cortical signature regions and the major cortical lobes were selected as regions of interest (ROIs) for cortical thickness.

RESULTS

Higher WMHV, but not Aβ status, predicted lower cortical thickness across all participants, in all ROIs. Conversely, when Aβ-positive participants were considered alone, higher WMHV predicted higher cortical thickness in a temporal AD-signature region.

DISCUSSION

WMHV may differentially influence cortical thickness depending on the presence or absence of Aβ, potentially reflecting different pathological mechanisms.

The age-related effect on cognitive performance in cognitively healthy elderly is mainly caused by underlying AD pathology or cerebrovascular lesions: implications for cutoffs regarding cognitive impairment

Background

As research in treatments for neurocognitive diseases progresses, there is an increasing need to identify cognitive decline in the earliest stages of disease for initiation of treatment in addition to determining the efficacy of treatment. For early identification, accurate cognitive tests cutoff values for cognitive impairment are essential.

Methods

We conducted a study on 297 cognitively healthy elderly people from the BioFINDER study and created subgroups excluding people with signs of underlying neuropathology, i.e., abnormal cerebrospinal fluid [CSF] β-amyloid or phosphorylated tau, CSF neurofilament light (neurodegeneration), or cerebrovascular pathology. We compared cognitive test results between groups and examined the age effect on cognitive test results.

Results

In our subcohort without any measurable pathology (n = 120), participants achieved better test scores and significantly stricter cutoffs for cognitive impairment for almost all the examined tests. The age effect in this subcohort disappeared for all cognitive tests, apart from some attention/executive tests, predominantly explained by the exclusion of cerebrovascular pathology.

Conclusion

Our study illustrates a new approach to establish normative data that could be useful to identify earlier cognitive changes in preclinical dementias. Future studies need to investigate if there is a genuine effect of healthy aging on cognitive tests or if this age effect is a proxy for higher prevalence of preclinical neurodegenerative diseases.

Suppementary informationl

Supplementary information accompanies this paper at 10.1186/s13195-020-00592-8.