Cross-validation of optimized composites for preclinical Alzheimer's disease

Mid-to-Late Life Healthy Lifestyle Modifies Genetic Risk for Longitudinal Cognitive Aging among Asymptomatic Individuals

IMPORTANCE

Genetic and lifestyle factors contribute to an individual's risk of developing Alzheimer's disease. However, it is unknown whether and how adherence to healthy lifestyles can mitigate the genetic risk of Alzheimer's.

OBJECTIVE

The aim of this study is to investigate whether adherence to healthy lifestyles can modify the impact of genetic predisposition to Alzheimer's disease on later-life cognitive decline.

DESIGN SETTING AND PARTICIPANTS

This prospective cohort study included 891 adults of European ancestry, aged 40 to 65, who were without dementia and had complete healthy-lifestyle and cognition data during the follow-up. Participants joined the Wisconsin Registry for Alzheimer's Prevention (WRAP) beginning in 2001. We conducted replication analyses using a subsample with similar baseline age range from the Health and Retirement Study (HRS).

EXPOSURES

We assessed participants' exposures using a continuous non-APOE polygenic risk score for Alzheimer's, a binary indicator for APOE-ε4 carrier status, and a weighted healthy-lifestyle score, including factors such as no current smoking, regular physical activity, healthy diet, light to moderate alcohol consumption, and frequent cognitive activities.

MAIN OUTCOMES AND MEASURES

We z-standardized cognitive scores for global (Preclinical Alzheimer's Cognitive Composite score 3 - PACC3) and domain-specific assessments (delayed recall and immediate learning).

RESULTS

We followed 891 individuals for up to 10 years (mean [SD] baseline age, 58 [6] years, 31% male, 38% APOE-ε4 carriers). After false discovery rate (FDR) correction, we found statistically significant PRS × lifestyle × age interactions on preclinical cognitive decline but the evidence is stronger among APOE-ε4 carriers. Among APOE-ε4 carriers, PRS-related differences in overall and memory-related domains between people scoring 0-1 and 4-5 regarding healthy lifestyles became evident around age 67 after FDR correction. These findings were robust across several sensitivity analyses and were replicated in the population-based HRS.

CONCLUSION

A favorable lifestyle can mitigate the genetic risk associated with current known non-APOE genetic variants for longitudinal cognitive decline, and these protective effects are particularly pronounced among APOE-ε4 carriers.

Longitudinal normative standards for cognitive tests and composites using harmonized data from two Wisconsin AD-risk-enriched cohorts

INTRODUCTION

Published norms are typically cross-sectional and often are not sensitive to preclinical cognitive changes due to dementia. We developed and validated demographically adjusted cross-sectional and longitudinal normative standards using harmonized outcomes from two Alzheimer's disease (AD) risk-enriched cohorts.

METHODS

Data from the Wisconsin Registry for Alzheimer's Prevention and the Wisconsin Alzheimer's Disease Research Center were combined. Quantile regression was used to develop unconditional (cross-sectional) and conditional (longitudinal) normative standards for 18 outcomes using data from cognitively unimpaired participants (N = 1390; mean follow-up = 9.25 years). Validity analyses (N = 2456) examined relationships between percentile scores (centiles), consensus-based cognitive statuses, and AD biomarker levels.

RESULTS

Unconditional and conditional centiles were lower in those with consensus-based impairment or biomarker positivity. Similarly, quantitative biomarker levels were higher in those whose centiles suggested decline.

DISCUSSION

This study presents normative standards for cognitive measures sensitive to pre-clinical changes. Future directions will investigate potential clinical applications of longitudinal normative standards.

HIGHLIGHTS

Quantile regression was used to construct longitudinal norms for cognitive tests. Poorer percentile scores were related to concurrent diagnosis and Alzheimer's disease biomarkers. A ShinyApp was built to display test scores and norms and flag low performance.

Apolipoprotein E moderates the association between non-APOE polygenic risk score for Alzheimer's disease and aging on preclinical cognitive function

INTRODUCTION

Variation in preclinical cognitive decline suggests additional genetic factors related to Alzheimer's disease (eg, a non-APOE polygenic risk score [PRS]) may interact with the APOE ε4 allele to influence cognitive decline.

METHODS

We tested the PRS × APOE ε4 × age interaction on preclinical cognition using longitudinal data from the Wisconsin Registry for Alzheimer's Prevention. All analyses were fitted using a linear mixed-effects model and adjusted for within individual/family correlation among 1190 individuals.

RESULTS

We found statistically significant PRS × APOE ε4 × age interactions on immediate learning (P = 0.038), delayed recall (P < 0.001), and Preclinical Alzheimer's Cognitive Composite 3 score (P = 0.026). PRS-related differences in overall and memory-related cognitive domains between people with and without APOE ε4 emerge around age 70, with a much stronger adverse PRS effect among APOE ε4 carriers. The findings were replicated in a population-based cohort.

DISCUSSIONS

APOE ε4 can modify the association between PRS and cognition decline.

HIGHLIGHTS

APOE ε4 can modify the association between polygenic risk scores (PRSs) and longitudinal cognition decline, with the modifying effects more pronounced when the PRS is constructed using a conservative P threshold (eg, P < 5e-8 ). The adverse genetic effect caused by the combined effect of the currently known genetic variants is more detrimental among APOE ε4 carriers around age 70. Individuals who are APOE ε4 carriers with high PRSs are the most vulnerable to the harmful effects caused by genetic burden.

Impact of asthma on the brain: evidence from diffusion MRI, CSF biomarkers and cognitive decline

Chronic systemic inflammation increases the risk of neurodegeneration, but the mechanisms remain unclear. Part of the challenge in reaching a nuanced understanding is the presence of multiple risk factors that interact to potentiate adverse consequences. To address modifiable risk factors and mitigate downstream effects, it is necessary, although difficult, to tease apart the contribution of an individual risk factor by accounting for concurrent factors such as advanced age, cardiovascular risk, and genetic predisposition. Using a case-control design, we investigated the influence of asthma, a highly prevalent chronic inflammatory disease of the airways, on brain health in participants recruited to the Wisconsin Alzheimer's Disease Research Center (31 asthma patients, 186 non-asthma controls, aged 45-90 years, 62.2% female, 92.2% cognitively unimpaired), a sample enriched for parental history of Alzheimer's disease. Asthma status was determined using detailed prescription information. We employed multi-shell diffusion weighted imaging scans and the three-compartment neurite orientation dispersion and density imaging model to assess white and gray matter microstructure. We used cerebrospinal fluid biomarkers to examine evidence of Alzheimer's disease pathology, glial activation, neuroinflammation and neurodegeneration. We evaluated cognitive changes over time using a preclinical Alzheimer cognitive composite. Using permutation analysis of linear models, we examined the moderating influence of asthma on relationships between diffusion imaging metrics, CSF biomarkers, and cognitive decline, controlling for age, sex, and cognitive status. We ran additional models controlling for cardiovascular risk and genetic risk of Alzheimer's disease, defined as a carrier of at least one apolipoprotein E (APOE) ε4 allele. Relative to controls, greater Alzheimer's disease pathology (lower amyloid-β42/amyloid-β40, higher phosphorylated-tau-181) and synaptic degeneration (neurogranin) biomarker concentrations were associated with more adverse white matter metrics (e.g. lower neurite density, higher mean diffusivity) in patients with asthma. Higher concentrations of the pleiotropic cytokine IL-6 and the glial marker S100B were associated with more salubrious white matter metrics in asthma, but not in controls. The adverse effects of age on white matter integrity were accelerated in asthma. Finally, we found evidence that in asthma, relative to controls, deterioration in white and gray matter microstructure was associated with accelerated cognitive decline. Taken together, our findings suggest that asthma accelerates white and gray matter microstructural changes associated with aging and increasing neuropathology, that in turn, are associated with more rapid cognitive decline. Effective asthma control, on the other hand, may be protective and slow progression of cognitive symptoms.

Apolipoprotein E moderates the association between Non-APOE Polygenic Risk Score for Alzheimer's Disease and Aging on Preclinical Cognitive Function

INTRODUCTION

Variation in preclinical cognitive decline suggests additional genetic factors related to Alzheimer's disease (e.g., a non-APOE polygenic risk scores [PRS]) may interact with the APOE ε4 allele to influence cognitive decline.

METHODS

We tested the PRS×APOE ε4×age interaction on preclinical cognition using longitudinal data from the Wisconsin Registry for Alzheimer's Prevention. All analyses were fitted using a linear mixed-effects model and adjusted for within individual/family correlation among 1,190 individuals.

RESULTS

We found statistically significant PRS×APOE ε4×age interactions on immediate learning (P=0.038), delayed recall (P<0.001), and Preclinical Alzheimer's Cognitive Composite 3 score (P=0.026). PRS-related differences in overall and memory-related cognitive domains between people with and without APOE ε4 emerge around age 70, with a much stronger adverse PRS effect among APOE ε4 carriers. The findings were replicated in a population-based cohort.

DISCUSSION

APOE ε4 can modify the association between PRS and cognition decline.

Mayo-PACC: A parsimonious preclinical Alzheimer's disease cognitive composite comprised of public-domain measures to facilitate clinical translation

INTRODUCTION

We aimed to define a Mayo Preclinical Alzheimer's disease Cognitive Composite (Mayo-PACC) that prioritizes parsimony and use of public domain measures to facilitate clinical translation.

METHODS

Cognitively unimpaired participants aged 65 to 85 at baseline with amyloid PET imaging were included, yielding 428 amyloid negative (A-) and 186 amyloid positive (A+) individuals with 7 years mean follow-up. Sensitivity to amyloid-related cognitive decline was examined using slope estimates derived from linear mixed models (difference in annualized change across A+ and A- groups). We compared differences in rates of change between Mayo-PACC and other composites (A+ > A- indicating more significant decline in A+).

RESULTS

All composites showed sensitivity to amyloid-related longitudinal cognitive decline (A+ > A- annualized change p < 0.05). Comparisons revealed that Mayo-PACC (AVLT sum of trials 1-5+6+delay, Trails B, animal fluency) showed comparable longitudinal sensitivity to other composites.

DISCUSSION

Mayo-PACC performs similarly to other composites and can be directly translated to the clinic.

Why a clinical trial is as good as its outcome measure: A framework for the selection and use of cognitive outcome measures for clinical trials of Alzheimer's disease

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.

Effect of Pathway-specific Polygenic Risk Scores for Alzheimer's Disease (AD) on Rate of Change in Cognitive Function and AD-related Biomarkers among Asymptomatic Individuals

Background

Genetic scores for late-onset Alzheimer's disease (LOAD) have been associated with preclinical cognitive decline and biomarker variations. Compared with an overall polygenic risk score (PRS), a pathway-specific PRS (p-PRS) may be more appropriate in predicting a specific biomarker or cognitive component underlying LOAD pathology earlier in the lifespan.

Objective

In this study, we leveraged 10 years of longitudinal data from initially cognitively unimpaired individuals in the Wisconsin Registry for Alzheimer's Prevention and explored changing patterns in cognition and biomarkers at various age points along six biological pathways.

Methods

PRS and p-PRSs with and without apolipoprotein E ( APOE ) were constructed separately based on the significant SNPs associated with LOAD in a recent genome-wide association study meta-analysis and compared to APOE alone. We used a linear mixed-effects model to assess the association between PRS/p-PRSs and global/domain-specific cognitive trajectories among 1,175 individuals. We also applied the model to the outcomes of cerebrospinal fluid biomarkers for beta-amyloid 42 (Aβ42), Aβ42/40 ratio, total tau, and phosphorylated tau in a subset. Replication analyses were performed in an independent sample.

Results

We found p-PRSs and the overall PRS can predict preclinical changes in cognition and biomarkers. The effects of p-PRSs/PRS on rate of change in cognition, beta-amyloid, and tau outcomes are dependent on age and appear earlier in the lifespan when APOE is included in these risk scores compared to when APOE is excluded.

Conclusion

In addition to APOE , the p-PRSs can predict age-dependent changes in beta-amyloid, tau, and cognition. Once validated, they could be used to identify individuals with an elevated genetic risk of accumulating beta-amyloid and tau, long before the onset of clinical symptoms.

Effect of Pathway-Specific Polygenic Risk Scores for Alzheimer's Disease (AD) on Rate of Change in Cognitive Function and AD-Related Biomarkers Among Asymptomatic Individuals

BACKGROUND

Genetic scores for late-onset Alzheimer's disease (LOAD) have been associated with preclinical cognitive decline and biomarker variations. Compared with an overall polygenic risk score (PRS), a pathway-specific PRS (p-PRS) may be more appropriate in predicting a specific biomarker or cognitive component underlying LOAD pathology earlier in the lifespan.

OBJECTIVE

In this study, we leveraged longitudinal data from the Wisconsin Registry for Alzheimer's Prevention and explored changing patterns in cognition and biomarkers at various age points along six biological pathways.

METHODS

PRS and p-PRSs with and without APOE were constructed separately based on the significant SNPs associated with LOAD in a recent genome-wide association study meta-analysis and compared to APOE alone. We used a linear mixed-effects model to assess the association between PRS/p-PRSs and cognitive trajectories among 1,175 individuals. We also applied the model to the outcomes of cerebrospinal fluid biomarkers in a subset. Replication analyses were performed in an independent sample.

RESULTS

We found p-PRSs and the overall PRS can predict preclinical changes in cognition and biomarkers. The effects of PRS/p-PRSs on rate of change in cognition, amyloid-β, and tau outcomes are dependent on age and appear earlier in the lifespan when APOE is included in these risk scores compared to when APOE is excluded.

CONCLUSION

In addition to APOE, the p-PRSs can predict age-dependent changes in amyloid-β, tau, and cognition. Once validated, they could be used to identify individuals with an elevated genetic risk of accumulating amyloid-β and tau, long before the onset of clinical symptoms.

Asthma amplifies dementia risk: Evidence from CSF biomarkers and cognitive decline

Introduction

Evidence from epidemiology, neuroimaging, and animal models indicates that asthma adversely affects the brain, but the nature and extent of neuropathophysiological impact remain unclear.

Methods

We tested the hypothesis that asthma is a risk factor for dementia by comparing cognitive performance and cerebrospinal fluid biomarkers of glial activation/neuroinflammation, neurodegeneration, and Alzheimer's disease (AD) pathology in 60 participants with asthma to 315 non-asthma age-matched control participants (45-93 years), in a sample enriched for AD risk.

Results

Participants with severe asthma had higher neurogranin concentrations compared to controls and those with mild asthma. Positive relationships between cardiovascular risk and concentrations of neurogranin and α-synuclein were amplified in severe asthma. Severe asthma also amplified the deleterious associations that apolipoprotein E ε4 carrier status, cardiovascular risk, and phosphorylated tau181/amyloid beta42 have with rate of cognitive decline.

Discussion

Our data suggest that severe asthma is associated with synaptic degeneration and may compound risk for dementia posed by cardiovascular disease and genetic predisposition.

Highlights

Those with severe asthma showed evidence of higher dementia risk than controls evidenced by: higher levels of the synaptic degeneration biomarker neurogranin regardless of cognitive status, cardiovascular or genetic risk, and controlling for demographics.steeper increase in levels of synaptic degeneration biomarkers neurogranin and α-synuclein with increasing cardiovascular risk.accelerated cognitive decline with higher cardiovascular risk, genetic predisposition, or pathological tau.

NIA-AA Alzheimer's Disease Framework: Clinical Characterization of Stages

BACKGROUND

To operationalize the National Institute on Aging - Alzheimer's Association (NIA-AA) Research Framework for Alzheimer's Disease 6-stage continuum of clinical progression for persons with abnormal amyloid.

METHODS

The Mayo Clinic Study of Aging is a population-based longitudinal study of aging and cognitive impairment in Olmsted County, Minnesota. We evaluated persons without dementia having 3 consecutive clinical visits. Measures for cross-sectional categories included objective cognitive impairment (OBJ) and function (FXN). Measures for change included subjective cognitive impairment (SCD), objective cognitive change (ΔOBJ), and new onset of neurobehavioral symptoms (ΔNBS). We calculated frequencies of the stages using different cutoff points and assessed stability of the stages over 15 months.

RESULTS

Among 243 abnormal amyloid participants, the frequencies of the stages varied with age: 66 to 90% were classified as stage 1 at age 50 but at age 80, 24 to 36% were stage 1, 32 to 47% were stage 2, 18 to 27% were stage 3, 1 to 3% were stage 4 to 6, and 3 to 9% were indeterminate. Most stage 2 participants were classified as stage 2 because of abnormal ΔOBJ only (44-59%), whereas 11 to 21% had SCD only, and 9 to 13% had ΔNBS only. Short-term stability varied by stage and OBJ cutoff points but the most notable changes were seen in stage 2 with 38 to 63% remaining stable, 4 to 13% worsening, and 24 to 41% improving (moving to stage 1).

INTERPRETATION

The frequency of the stages varied by age and the precise membership fluctuated by the parameters used to define the stages. The staging framework may require revisions before it can be adopted for clinical trials. ANN NEUROL 2021;89:1145-1156.

Identifying Sensitive Measures of Cognitive Decline at Different Clinical Stages of Alzheimer's Disease

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.

One-year Outcome of Shanghai Mild Cognitive Impairment Cohort Study

BACKGROUND & OBJECTIVE

The purpose of this study is to identify the risk factors associated with the conversion from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) dementia for the early detection of AD.

METHODS

The study comprised a prospective cohort study that included 400 MCI subjects with annual follow-ups for 3 years.

RESULTS

During the first 12 months' follow-up, 42 subjects converted to Alzheimer's dementia (21 probable AD and 21 possible AD), two subjects converted to other types of dementia and 56 subjects lost follow. The factors associated with a greater risk of conversion from MCI to AD included gender, whole brain volume, and right hippocampal volume (rt. HV), as well as scores on the Revised Chinese version of the Alzheimer's Disease Assessment Scale-Cognitive subscale 13 (ADAS-Cog-C), Clock Drawing Test (CDT), Symbol Digit Modalities Test (SDMT), and Rey-Osterrieth Complex Figure Test (ROCFT). The risk classification of the combined ADAS-Cog-C and Alzheimer Cognitive Composite (ACC) score with the rt. HV and left Entorhinal Cortex Volume (lt. ECV) showed a conversion difference among the groups.

CONCLUSION

Early detection of AD and potential selection for clinical trial design should utilize the rt. HV, as well as neuropsychological test scores, including those of the ADAS-Cog-C and ACC.

Cognition at age 70: Life course predictors and associations with brain pathologies

OBJECTIVE

To investigate predictors of performance on a range of cognitive measures including the Preclinical Alzheimer Cognitive Composite (PACC) and test for associations between cognition and dementia biomarkers in Insight 46, a substudy of the Medical Research Council National Survey of Health and Development.

METHODS

A total of 502 individuals born in the same week in 1946 underwent cognitive assessment at age 69-71 years, including an adapted version of the PACC and a test of nonverbal reasoning. Performance was characterized with respect to sex, childhood cognitive ability, education, and socioeconomic position (SEP). In a subsample of 406 cognitively normal participants, associations were investigated between cognition and β-amyloid (Aβ) positivity (determined from Aβ-PET imaging), whole brain volumes, white matter hyperintensity volumes (WMHV), and APOE ε4.

RESULTS

Childhood cognitive ability was strongly associated with cognitive scores including the PACC more than 60 years later, and there were independent effects of education and SEP. Sex differences were observed on every PACC subtest. In cognitively normal participants, Aβ positivity and WMHV were independently associated with lower PACC scores, and Aβ positivity was associated with poorer nonverbal reasoning. Aβ positivity and WMHV were not associated with sex, childhood cognitive ability, education, or SEP. Normative data for 339 cognitively normal Aβ-negative participants are provided.

CONCLUSIONS

This study adds to emerging evidence that subtle cognitive differences associated with Aβ deposition are detectable in older adults, at an age when dementia prevalence is very low. The independent associations of childhood cognitive ability, education, and SEP with cognitive performance at age 70 have implications for interpretation of cognitive data in later life.

Design and sample size considerations for Alzheimer's disease prevention trials using multistate models

BACKGROUND/AIMS

Clinical trials for Alzheimer's disease have been aimed primarily at persons who have cognitive symptoms at enrollment. However, researchers are now recognizing that the pathophysiological process of Alzheimer's disease begins years, if not decades, prior to the onset of clinical symptoms. Successful intervention may require intervening early in the disease process. Critical issues arise in designing clinical trials for primary and secondary prevention of Alzheimer's disease including determination of sample sizes and follow-up duration. We address a number of these issues through application of a unifying multistate model for the preclinical course of Alzheimer's disease. A multistate model allows us to specify at which points during the long disease process the intervention exerts its effects.

METHODS

We used a nonhomogeneous Markov multistate model for the progression of Alzheimer's disease through preclinical disease states defined by biomarkers, mild cognitive impairment and Alzheimer's disease dementia. We used transition probabilities based on several published cohort studies. Sample size methods were developed that account for factors including the initial preclinical disease state of trial participants, the primary endpoint, age-dependent transition and mortality rates and specifications of which transition rates are the targets of the intervention.

RESULTS

We find that Alzheimer's disease prevention trials with a clinical primary endpoint of mild cognitive impairment or Alzheimer's disease dementia will require sample sizes of the order many thousands of individuals with at least 5 years of follow-up, which is larger than most Alzheimer's disease therapeutic trials conducted to date. The reasons for the large trial sizes include the long and variable preclinical period that spans decades, high rates of attrition among elderly populations due to mortality and losses to follow-up and potential selection effects, whereby healthier subjects enroll in prevention trials. A web application is available to perform sample size calculations using the methods reported here.

CONCLUSION

Sample sizes based on multistate models can account for the points in the disease process when interventions exert their effects and may lead to more accurate sample size determinations. We will need innovative strategies to help design Alzheimer's disease prevention trials with feasible sample size requirements and durations of follow-up.

Measuring longitudinal cognition: Individual tests versus composites

Introduction

Longitudinal cohort studies of cognitive aging must confront several sources of within-person variability in scores. In this article, we compare several neuropsychological measures in terms of longitudinal error variance and relationships with biomarker-assessed brain amyloidosis (Aβ).

Methods

Analyses used data from the Wisconsin Registry for Alzheimer's Prevention. We quantified within-person longitudinal variability and age-related trajectories for several global and domain-specific composites and their constituent scores. For a subset with cerebrospinal fluid or amyloid positron emission tomography measures, we examined how Aβ modified cognitive trajectories.

Results

Global and theoretically derived composites exhibited lower intraindividual variability and stronger age × Aβ interactions than did empirically derived composites or raw scores from single tests. For example, the theoretical executive function outperformed other executive function scores on both metrics.

Discussion

These results reinforce the need for careful selection of cognitive outcomes in study design, and support the emerging consensus favoring composites over single-test measures.

•

Identifying early cognitive change requires tests with low error variance.

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In a middle-aged sample, composites were less noisy than single tests.

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Global and theory-driven composites outperformed data-driven composites.

EU/US/CTAD Task Force: Lessons Learned from Recent and Current Alzheimer's Prevention Trials

At a meeting of the EU/US/Clinical Trials in Alzheimer's Disease (CTAD) Task Force in December 2016, an international group of investigators from industry, academia, and regulatory agencies reviewed lessons learned from ongoing and planned prevention trials, which will help guide future clinical trials of AD treatments, particularly in the pre-clinical space. The Task Force discussed challenges that need to be addressed across all aspects of clinical trials, calling for innovation in recruitment and retention, infrastructure development, and the selection of outcome measures. While cognitive change provides a marker of disease progression across the disease continuum, there remains a need to identify the optimal assessment tools that provide clinically meaningful endpoints. Patient- and informant-reported assessments of cognition and function may be useful but present additional challenges. Imaging and other biomarkers are also essential to maximize the efficiency of and the information learned from clinical trials.

Optimizing the preclinical Alzheimer's cognitive composite with semantic processing: The PACC5

Introduction

Amyloid-related decline in semantic memory was recently shown to be observable in the preclinical period of Alzheimer's disease. Cognitive composites designed to be sensitive to cognitive change in preclinical Alzheimer's disease (e.g., preclinical Alzheimer's cognitive composite [PACC]) and currently used in secondary prevention trials do not currently integrate measures of semantic processing. Our objective was to determine whether a standard semantic measure (i.e., category fluency [CAT] to animals, fruits, and vegetables) adds independent information above and beyond Aβ-related decline captured by the PACC.

Methods

Clinically normal older adults from the Harvard Aging Brain Study were identified at baseline as Aβ+ (n = 70) or Aβ- (n = 209) using Pittsburgh compound B-positron emission tomography imaging and followed annually with neuropsychological testing for 3.87 ± 1.09 years. The relationships between PACC, CAT, and variations of the PACC including/excluding CAT were examined using linear mixed models controlling for age, sex, and education. We additionally examined decline on CAT by further grouping Aβ+ participants into preclinical stage 1 and stage 2 on the basis of neurodegeneration markers.

Results

CAT explained unique variance in amyloid-related decline, with Aβ+'s continuing to decline relative to Aβ-'s in CAT even after controlling for overall PACC decline. In addition, removal of CAT from the PACC resulted in a longitudinal Aβ+/- effect size reduction of 20% at 3-year follow-up and 12% at 5-year follow-up. Finally, both stage 1 and stage 2 participants declined on CAT in comparison with stage 0, suggesting CAT declines early within the preclinical trajectory.

Conclusion

Addition of CAT to the PACC provides unique information about early cognitive decline not currently captured by the episodic memory, executive function, and global cognition components and may therefore improve detection of early Aβ-related cognitive decline.

Power analysis to detect treatment effects in longitudinal clinical trials for Alzheimer's disease

INTRODUCTION

Assessing cognitive and functional changes at the early stage of Alzheimer's disease (AD) and detecting treatment effects in clinical trials for early AD are challenging.

METHODS

Under the assumption that transformed versions of the Mini-Mental State Examination, the Clinical Dementia Rating Scale-Sum of Boxes, and the Alzheimer's Disease Assessment Scale-Cognitive Subscale tests'/components' scores are from a multivariate linear mixed-effects model, we calculated the sample sizes required to detect treatment effects on the annual rates of change in these three components in clinical trials for participants with mild cognitive impairment.

RESULTS

Our results suggest that a large number of participants would be required to detect a clinically meaningful treatment effect in a population with preclinical or prodromal Alzheimer's disease. We found that the transformed Mini-Mental State Examination is more sensitive for detecting treatment effects in early AD than the transformed Clinical Dementia Rating Scale-Sum of Boxes and Alzheimer's Disease Assessment Scale-Cognitive Subscale. The use of optimal weights to construct powerful test statistics or sensitive composite scores/endpoints can reduce the required sample sizes needed for clinical trials.

CONCLUSION

Consideration of the multivariate/joint distribution of components' scores rather than the distribution of a single composite score when designing clinical trials can lead to an increase in power and reduced sample sizes for detecting treatment effects in clinical trials for early AD.