An empirically derived composite cognitive test score with improved power to track and evaluate treatments for preclinical Alzheimer's disease

Alzheimer disease biomarkers are associated with decline in subjective memory, attention, and spatial navigation ability in clinically normal adults

OBJECTIVE

Subtle changes in memory, attention, and spatial navigation abilities have been associated with preclinical Alzheimer disease (AD). The current study examined whether baseline AD biomarkers are associated with self- and informant-reported decline in memory, attention, and spatial navigation.

METHOD

Clinically normal (Clinical Dementia Rating Scale (CDR®) = 0) adults aged 56-93 (N = 320) and their informants completed the memory, divided attention, and visuospatial abilities (which assesses spatial navigation) subsections of the Everyday Cognition Scale (ECog) annually for an average of 4 years. Biomarker data was collected within (±) 2 years of baseline (i.e., cerebrospinal fluid (CSF) p-tau181/Aβ42 ratio and hippocampal volume). Clinical progression was defined as CDR > 0 at time of final available ECog.

RESULTS

Self- and informant-reported memory, attention, and spatial navigation significantly declined over time (ps < .001). Baseline AD biomarkers were significantly associated with self- and informant-reported decline in cognitive ability (ps < .030), with the exception of p-tau181/Aβ42 ratio and self-reported attention (p = .364). Clinical progression did not significantly moderate the relationship between AD biomarkers and decline in self- or informant-reported cognitive ability (ps > .062). Post-hoc analyses indicated that biomarker burden was also associated with self- and informant-reported decline in total ECog (ps < .002), and again clinical progression did not significantly moderate these relationships (ps > .299).

CONCLUSIONS

AD biomarkers at baseline may indicate risk of decline in self- and informant-reported change in memory, attention, and spatial navigation ability. As such, subjectively reported decline in these domains may have clinical utility in tracking the subtle cognitive changes associated with the earliest stages of AD.

Efficacy and safety of short-term edaravone or nerve growth factor add-on therapy for alcohol-related brain damage: A multi-centre randomised control trial

AIMS

To measure the therapeutic effect of an anti-oxidant, edaravone (EDV), or neurotrophic treatment with nerve growth factor (NGF) as an add-on treatment for alcohol-related brain damage (ARBD).

DESIGN

Multi-centre, randomised, single-blinded, comparative clinical trial.

SETTING AND PARTICIPANTS

One hundred and twenty-two inpatients recruited from seven hospitals in different regions of China, all diagnosed with ARBD and aged 18 to 65 years old; among them, only two were female.

INTERVENTION AND COMPARATOR

Patients were randomly assigned to receive one of three treatments for 2 weeks: 40 patients, treatment as usual (TAU: a combination of intramuscular injections of thiamine, intravenous infusions of other B vitamins with vitamin C and oral medication with vitamin E per day); 40, EDV add-on treatment to TAU (intravenous infusion with 30 mg of EDV twice per day); and 42, NGF add-on treatment to TAU (intramuscular injection of 20 μg of NGF per day). The patients underwent follow-up for 24 weeks.

MEASUREMENTS

The primary outcome was the composite score of executive cognitive function in the 2nd week after treatment, which was measured as the mean of the Z scores of the assessments, including the digit symbol substitute test (DSST), digit span memory test-forward (DST-F), digit span memory test-reverse (DST-R) and space span memory test (SSMT). The secondary outcomes were the composite scores at later follow-ups, the score for each component of cognitive function, global cognitive function measured by the Montreal Cognitive Assessment (MoCA), craving for alcohol and the safety of the therapies.

FINDINGS

EDV add-on treatment improved the composite score of executive cognitive function better than TAU in the 2nd week (adjusted mean difference: 0.24, 95% confidence interval 0.06 to 0.41; P = 0.008), but NGF add-on treatment did not (adjusted mean difference: 0.07, 95% confidence interval -0.09 to 0.24; P = 0.502). During the follow-up to 24 weeks, EDV add-on treatment improved the composite score of executive cognitive function and DST-R score better than TAU (both P < 0.01). Craving for alcohol was relieved in all three groups. No severe adverse events were observed.

CONCLUSION

The short-term addition of edaravone to supplementary therapy treatment for alcohol-related brain damage (ARBD) improved executive cognitive function in patients with ARBD.

Cognitive training for children with ADHD: composite cognitive score outcome in a randomized controlled trial

PURPOSE OF THE ARTICLE

Cognitive training for Attention Deficit/Hyperactivity Disorder (ADHD) has shown promising, although mixed results. In post-hoc analyses, we evaluate effects of cognitive training using a novel composite cognition score as the outcome for children attending at least 16 sessions of training, dose-response of training and associations between symptoms and cognitive functioning.

MATERIALS AND METHODS

Children (age 6-13) with ADHD were randomized to intervention (n = 26) or control (n = 34). For the current analysis, we restricted the intervention group to children, who completed at least 16 sessions of cognitive training (n = 26) and examined a dose response within that group.

RESULTS

Cognition improved significantly in the intervention, but not control group. Amount of the completed training sessions correlated significantly with the amount of cognitive improvement.

CONCLUSION

Variations in dose and frequency of training may be an important source of the variance in previous studies.

Longitudinal changes in qualitative aspects of semantic fluency in presymptomatic and prodromal genetic frontotemporal dementia

BACKGROUND

The semantic fluency test is one of the most widely used neuropsychological tests in dementia diagnosis. Research utilizing the qualitative, psycholinguistic information embedded in its output is currently underexplored in presymptomatic and prodromal genetic FTD.

METHODS

Presymptomatic MAPT (n = 20) and GRN (n = 43) mutation carriers, and controls (n = 55) underwent up to 6 years of neuropsychological assessment, including the semantic fluency test. Ten mutation carriers became symptomatic (phenoconverters). Total score and five qualitative fluency measures (lexical frequency, age of acquisition, number of clusters, cluster size, number of switches) were calculated. We used multilevel linear regression modeling to investigate longitudinal decline. We assessed the co-correlation of the qualitative measures at each time point with principal component analysis. We explored associations with cognitive decline and grey matter atrophy using partial correlations, and investigated classification abilities using binary logistic regression.

RESULTS

The interrater reliability of the qualitative measures was good (ICC = 0.75-0.90). There was strong co-correlation between lexical frequency and age of acquisition, and between clustering and switching. At least 4 years pre-phenoconversion, GRN phenoconverters had fewer but larger clusters (p < 0.001), and fewer switches (p = 0.004), correlating with lower executive function (r = 0.87-0.98). Fewer switches was predictive of phenoconversion, correctly classifying 90.3%. Starting at least 4 years pre-phenoconversion, MAPT phenoconverters demonstrated an increase in lexical frequency (p = 0.009) and a decline in age of acquisition (p = 0.034), correlating with lower semantic processing (r = 0.90). Smaller cluster size was predictive of phenoconversion, correctly classifying 89.3%. Increase in lexical frequency and decline in age of acquisition were associated with grey matter volume loss of predominantly temporal areas, while decline in the number of clusters, cluster size, and switches correlated with grey matter volume loss of predominantly frontal areas.

CONCLUSIONS

Qualitative aspects of semantic fluency could give insight into the underlying mechanisms as to why the "traditional" total score declines in the different FTD mutations. However, the qualitative measures currently demonstrate more fluctuation than the total score, the measure that seems to most reliably deteriorate with time. Replication in a larger sample of FTD phenoconverters is warranted to identify if qualitative measures could be sensitive cognitive biomarkers to identify and track mutation carriers converting to the symptomatic stage of FTD.

Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson's disease

Introduction

Cognitive decline is common in Parkinson's disease (PD). Calculating personalized risk of cognitive decline in PD would allow for appropriate counseling, early intervention with available treatments, and inclusion in disease-modifying trials.

Methods

Data were from the Parkinson's Progression Markers Initiative de novo cohort. Baseline scores were calculated for Lifestyle for Brain Health (LIBRA) and the Montreal Parkinson Risk of Dementia Scale (MoPaRDS) per prior literature and preliminary Parkinson's disease Risk Estimator for Decline In Cognition Tool (pPREDICT) by attributing a point for fourteen posited risk factors. Baseline and 5-year follow-up composite cognitive scores (CCSs) were calculated from a neuropsychological battery and used to define cognitive decliners (PD-decline) versus maintainers (PD-maintain).

Results

The PD-decline group (n = 44) had higher LIBRA (6.76 ± 0.57, p < 0.05), MoPaRDS (2.45 ± 1.41, p < 0.05) and pPREDICT (4.52 ± 1.66, p < 0.05) scores compared to the PD-maintain group (n = 263; LIBRA 4.98 ± 0.20, MoPaRDS 1.68 ± 1.16, pPREDICT 3.38 ± 1.69). Area-under-the-curve (AUC) for LIBRA was 0.64 (95% confidence interval [CI], 0.55-0.73), MoPaRDS was 0.66 (95% CI, 0.58-0.75) and for pPREDICT was 0.68 (95% CI, 0.61-0.76). In linear regression analyses, LIBRA (p < 0.05), MoPaRDS (p < 0.05) and pPREDICT (p < 0.05) predicted change in CCS. Only age stratified by sex (p < 0.05) contributed significantly to the model for LIBRA. Age and presence of hallucinations (p < 0.05) contributed significantly to the model for MoPaRDS. Male sex, older age, excessive daytime sleepiness, and moderate-severe motor symptoms (all p < 0.05) contributed significantly to the model for pPREDICT.

Conclusion

Although MoPaRDS is a PD-specific tool for predicting cognitive decline relying on only clinical features, it does not focus on potentially modifiable risk factors. LIBRA does focus on potentially modifiable risk factors and is associated with prediction of all-cause dementia in some populations, but pPREDICT potentially demonstrates improved performance in cognitive decline risk calculation in individuals with PD and may identify actionable risk factors. As pPREDICT incorporates multiple potentially modifiable risk factors that can be obtained easily in the clinical setting, it is a first step in developing an easily assessable tool for a personalized approach to reduce dementia risk in people with PD.

A robust harmonization approach for cognitive data from multiple aging and dementia cohorts

INTRODUCTION

Although many cognitive measures have been developed to assess cognitive decline due to Alzheimer's disease (AD), there is little consensus on optimal measures, leading to varied assessments across research cohorts and clinical trials making it difficult to pool cognitive measures across studies.

METHODS

We used a two-stage approach to harmonize cognitive data across cohorts and derive a cross-cohort score of cognitive impairment due to AD. First, we pool and harmonize cognitive data from international cohorts of varying size and ethnic diversity. Next, we derived cognitive composites that leverage maximal data from the harmonized dataset.

RESULTS

We show that our cognitive composites are robust across cohorts and achieve greater or comparable sensitivity to AD-related cognitive decline compared to the Mini-Mental State Examination and Preclinical Alzheimer Cognitive Composite. Finally, we used an independent cohort validating both our harmonization approach and composite measures.

DISCUSSION

Our easy to implement and readily available pipeline offers an approach for researchers to harmonize their cognitive data with large publicly available cohorts, providing a simple way to pool data for the development or validation of findings related to cognitive decline due to AD.

Original research: longitudinal evaluation of cognitively demanding daily function using performance-based functional assessment highlights heterogeneous trajectories in cognitive and functional abilities in people with Parkinson's disease

Background

Longitudinal assessment of functional abilities in Parkinson's disease (PD) is needed to determine the efficacy of cognitive interventions in providing meaningful improvements in daily life. Additionally, subtle changes in instrumental activities of daily living may precede a clinical diagnosis of dementia and could aid earlier detection of and intervention for cognitive decline.

Objective

The primary goal was to validate the longitudinal application of the University of California San Diego Performance-Based Skills Assessment (UPSA). An exploratory secondary goal was to determine whether UPSA may identify individuals at higher risk of cognitive decline in PD.

Methods

Seventy participants with PD completed the UPSA with at least one follow-up visit. Linear mixed effects modeling was used to identify associations between baseline UPSA score and cognitive composite score (CCS) over time. Descriptive analysis of four heterogeneous cognitive and functional trajectory groups and individual case examples was performed.

Results

Baseline UPSA score predicted CCS at each timepoint for functionally impaired and unimpaired groups (p < 0.01) but did not predict the rate change in CCS over time (p = 0.83). Participants displayed heterogenous trajectories in both UPSA and CCS during the follow-up period. Most participants maintained both cognitive and functional performance (n = 54), though some displayed cognitive and functional decline (n = 4), cognitive decline with functional maintenance (n = 4), and functional decline with cognitive maintenance (n = 8).

Conclusion

The UPSA is a valid measure of cognitive functional abilities over time in PD. Given the heterogeneity of functional and cognitive trajectories, this performance-based assessment did not predict cognitive decline with this relatively short follow-up. Further work is needed to understand longitudinal functional assessments in PD-associated cognitive impairment.

Unsupervised high-frequency smartphone-based cognitive assessments are reliable, valid, and feasible in older adults at risk for Alzheimer's disease

OBJECTIVE

Smartphones have the potential for capturing subtle changes in cognition that characterize preclinical Alzheimer's disease (AD) in older adults. The Ambulatory Research in Cognition (ARC) smartphone application is based on principles from ecological momentary assessment (EMA) and administers brief tests of associative memory, processing speed, and working memory up to 4 times per day over 7 consecutive days. ARC was designed to be administered unsupervised using participants' personal devices in their everyday environments.

METHODS

We evaluated the reliability and validity of ARC in a sample of 268 cognitively normal older adults (ages 65-97 years) and 22 individuals with very mild dementia (ages 61-88 years). Participants completed at least one 7-day cycle of ARC testing and conventional cognitive assessments; most also completed cerebrospinal fluid, amyloid and tau positron emission tomography, and structural magnetic resonance imaging studies.

RESULTS

First, ARC tasks were reliable as between-person reliability across the 7-day cycle and test-retest reliabilities at 6-month and 1-year follow-ups all exceeded 0.85. Second, ARC demonstrated construct validity as evidenced by correlations with conventional cognitive measures (r = 0.53 between composite scores). Third, ARC measures correlated with AD biomarker burden at baseline to a similar degree as conventional cognitive measures. Finally, the intensive 7-day cycle indicated that ARC was feasible (86.50% approached chose to enroll), well tolerated (80.42% adherence, 4.83% dropout), and was rated favorably by older adult participants.

CONCLUSIONS

Overall, the results suggest that ARC is reliable and valid and represents a feasible tool for assessing cognitive changes associated with the earliest stages of AD.

A public resource of baseline data from the Alzheimer's Prevention Initiative Autosomal-Dominant Alzheimer's Disease Trial

INTRODUCTION

The Alzheimer's Prevention Initiative Autosomal-Dominant Alzheimer's Disease (API ADAD) Trial evaluated the anti-oligomeric amyloid beta (Aβ) antibody therapy crenezumab in cognitively unimpaired members of the Colombian presenilin 1 (PSEN1) E280A kindred. We report availability, methods employed to protect confidentiality and anonymity of participants, and process for requesting and accessing baseline data.

METHODS

We developed mechanisms to share baseline data from the API ADAD Trial in consultation with experts and other groups sharing data from Alzheimer's disease (AD) prevention trials, balancing the need to protect anonymity and trial integrity with making data broadly available to accelerate progress in the field. We pressure-tested deliberate and inadvertent potential threats under specific assumptions, employed a system to suppress or mask both direct and indirect identifying variables, limited and firewalled data managers, and put forth specific principles requisite to receive data.

RESULTS

Baseline demographic, PSEN1 E280A and apolipoprotein E genotypes, florbetapir and fluorodeoxyglucose positron emission tomography, magnetic resonance imaging, clinical, and cognitive data can now be requested by interested researchers.

DISCUSSION

Baseline data are publicly available; treatment data and biological samples, including baseline and treatment-related blood-based biomarker data will become available in accordance with our original trial agreement and subsequently developed Collaboration for Alzheimer's Prevention principles. Sharing of these data will allow exploration of important questions including the differential effects of initiating an investigational AD prevention therapy both before as well as after measurable Aβ plaque deposition.

Traceability and comparability through crosswalks with the NeuroMET Memory Metric

Accurate assessment of memory ability for persons on the continuum of Alzheimer’s disease (AD) is vital for early diagnosis, monitoring of disease progression and evaluation of new therapies. However, currently available neuropsychological tests suffer from a lack of standardization and metrological quality assurance. Improved metrics of memory can be created by carefully combining selected items from legacy short-term memory tests, whilst at the same time retaining validity, and reducing patient burden. In psychometrics, this is known as “crosswalks” to link items empirically. The aim of this paper is to link items from different types of memory tests. Memory test data were collected from the European EMPIR NeuroMET and the SmartAge studies recruited at Charité Hospital (Healthy controls n = 92; Subjective cognitive decline n = 160; Mild cognitive impairment n = 50; and AD n = 58; age range 55–87). A bank of items (n = 57) was developed based on legacy short-term memory items (i.e., Corsi Block Test, Digit Span Test, Rey’s Auditory Verbal Learning Test, Word Learning Lists from the CERAD test battery and Mini Mental State Examination; MMSE). The NeuroMET Memory Metric (NMM) is a composite metric that comprises 57 dichotomous items (right/wrong). We previously reported on a preliminary item bank to assess memory based on immediate recall, and have now demonstrated direct comparability of measurements generated from the different legacy tests. We created crosswalks between the NMM and the legacy tests and between the NMM and the full MMSE using Rasch analysis (RUMM2030) and produced two conversion tables. Measurement uncertainties for estimates of person memory ability with the NMM across the full span were smaller than all individual legacy tests, which demonstrates the added value of the NMM. Comparisons with one (MMSE) of the legacy tests showed however higher measurement uncertainties of the NMM for people with a very low memory ability (raw score ≤ 19). The conversion tables developed through crosswalks in this paper provide clinicians and researchers with a practical tool to: (i) compensate for ordinality in raw scores, (ii) ensure traceability to make reliable and valid comparisons when measuring person ability, and (iii) enable comparability between test results from different legacy tests.

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.

Combining tau-PET and fMRI meta-analyses for patient-centered prediction of cognitive decline in Alzheimer’s disease

Background

Tau-PET is a prognostic marker for cognitive decline in Alzheimer’s disease, and the heterogeneity of tau-PET patterns matches cognitive symptom heterogeneity. Thus, tau-PET may allow precision-medicine prediction of individual tau-related cognitive trajectories, which can be important for determining patient-specific cognitive endpoints in clinical trials. Here, we aimed to examine whether tau-PET in cognitive-domain-specific brain regions, identified via fMRI meta-analyses, allows the prediction of domain-specific cognitive decline. Further, we aimed to determine whether tau-PET-informed personalized cognitive composites capture patient-specific cognitive trajectories more sensitively than conventional cognitive measures.

Methods

We included Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants classified as controls (i.e., amyloid-negative, cognitively normal, n = 121) or Alzheimer’s disease-spectrum (i.e., amyloid-positive, cognitively normal to dementia, n = 140), plus 111 AVID-1451-A05 participants for independent validation (controls/Alzheimer’s disease-spectrum=46/65). All participants underwent baseline ¹⁸F-flortaucipir tau-PET, amyloid-PET, and longitudinal cognitive testing to assess annual cognitive changes (i.e., episodic memory, language, executive functioning, visuospatial). Cognitive changes were calculated using linear mixed models. Independent meta-analytical task-fMRI activation maps for each included cognitive domain were obtained from the Neurosynth database and applied to tau-PET to determine tau-PET signal in cognitive-domain-specific brain regions. In bootstrapped linear regression, we assessed the strength of the relationship (i.e., partial R²) between cognitive-domain-specific tau-PET vs. global or temporal-lobe tau-PET and cognitive changes. Further, we used tau-PET-based prediction of domain-specific decline to compose personalized cognitive composites that were tailored to capture patient-specific cognitive decline.

Results

In both amyloid-positive cohorts (ADNI [age = 75.99±7.69] and A05 [age = 74.03±9.03]), cognitive-domain-specific tau-PET outperformed global and temporal-lobe tau-PET for predicting future cognitive decline in episodic memory, language, executive functioning, and visuospatial abilities. Further, a tau-PET-informed personalized cognitive composite across cognitive domains enhanced the sensitivity to assess cognitive decline in amyloid-positive subjects, yielding lower sample sizes required for detecting simulated intervention effects compared to conventional cognitive endpoints (i.e., memory composite, global cognitive composite). However, the latter effect was less strong in A05 compared to the ADNI cohort.

Conclusion

Combining tau-PET with task-fMRI-derived maps of major cognitive domains facilitates the prediction of domain-specific cognitive decline. This approach may help to increase the sensitivity to detect Alzheimer’s disease-related cognitive decline and to determine personalized cognitive endpoints in clinical trials.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01105-5.

Capturing Cognitive Aging in Vivo: Application of a Neuropsychological Framework for Emerging Digital Tools

As the global burden of dementia continues to plague our healthcare systems, efficient, objective, and sensitive tools to detect neurodegenerative disease and capture meaningful changes in everyday cognition are increasingly needed. Emerging digital tools present a promising option to address many drawbacks of current approaches, with contexts of use that include early detection, risk stratification, prognosis, and outcome measurement. However, conceptual models to guide hypotheses and interpretation of results from digital tools are lacking and are needed to sort and organize the large amount of continuous data from a variety of sensors. In this viewpoint, we propose a neuropsychological framework for use alongside a key emerging approach—digital phenotyping. The Variability in Everyday Behavior (VIBE) model is rooted in established trends from the neuropsychology, neurology, rehabilitation psychology, cognitive neuroscience, and computer science literature and links patterns of intraindividual variability, cognitive abilities, and everyday functioning across clinical stages from healthy to dementia. Based on the VIBE model, we present testable hypotheses to guide the design and interpretation of digital phenotyping studies that capture everyday cognition in vivo. We conclude with methodological considerations and future directions regarding the application of the digital phenotyping approach to improve the efficiency, accessibility, accuracy, and ecological validity of cognitive assessment in older adults.

Computerized paired associate learning performance and imaging biomarkers in older adults without dementia

This cross-sectional study examined whether performance on the computerized Paired Associate Learning (PAL) task from the Cambridge Neuropsychological Test Automated Battery is associated with amyloid positivity as measured by Positron Emission Tomography, regional volume composites as measured by Magnetic Resonance Imaging, and cognitive impairment. Participants from the BIOCARD Study (N = 73, including 62 cognitively normal and 11 with mild cognitive impairment; M age = 70 years) completed the PAL task, a comprehensive clinical and neuropsychological assessment, and neuroimaging as part of their annual study visit. In linear regressions covarying age, sex, years of education and diagnosis, higher PAL error scores were associated with amyloid positivity but not with medial temporal or cortical volume composites. By comparison, standard neuropsychological measures of episodic memory and global cognition were unrelated to amyloid positivity, but better performance on the verbal episodic memory measures was associated with larger cortical volume composites. Participants with mild cognitive impairment demonstrated worse cognitive performance on all of the cognitive measures, including the PAL task. These findings suggest that this computerized visual paired associate learning task may be more sensitive to amyloid positivity than standard neuropsychological tests, and may therefore be a promising tool for detecting amyloid positivity in non-demented participants.

Biomarkers used in Alzheimer's disease diagnosis, treatment, and prevention

Alzheimer's disease (AD), being the number one in terms of dementia burden, is an insidious age-related neurodegenerative disease and is presently considered a global public health threat. Its main histological hallmarks are the Aβ senile plaques and the P-tau neurofibrillary tangles, while clinically it is marked by a progressive cognitive decline that reflects the underlying synaptic loss and neurodegeneration. Many of the drug therapies targeting the two pathological hallmarks namely Aβ and P-tau have been proven futile. This is probably attributed to the initiation of therapy at a stage where cognitive alterations are already obvious. In other words, the underlying neuropathological changes are at a stage where these drugs lack any therapeutic value in reversing the damage. Therefore, there is an urgent need to start treatment in the very early stage where these changes can be reversed, and hence, early diagnosis is of primordial importance. To this aim, the use of robust and informative biomarkers that could provide accurate diagnosis preferably at an earlier phase of the disease is of the essence. To date, several biomarkers have been established that, to a different extent, allow researchers and clinicians to evaluate, diagnose, and more specially exclude other related pathologies. In this study, we extensively reviewed data on the currently explored biomarkers in terms of AD pathology-specific and non-specific biomarkers and highlighted the recent developments in the diagnostic and theragnostic domains. In the end, we have presented a separate elaboration on aspects of future perspectives and concluding remarks.

Cognitive composites for genetic frontotemporal dementia: GENFI-Cog

Background

Clinical endpoints for upcoming therapeutic trials in frontotemporal dementia (FTD) are increasingly urgent. Cognitive composite scores are often used as endpoints but are lacking in genetic FTD. We aimed to create cognitive composite scores for genetic frontotemporal dementia (FTD) as well as recommendations for recruitment and duration in clinical trial design.

Methods

A standardized neuropsychological test battery covering six cognitive domains was completed by 69 C9orf72, 41 GRN, and 28 MAPT mutation carriers with CDR® plus NACC-FTLD ≥ 0.5 and 275 controls. Logistic regression was used to identify the combination of tests that distinguished best between each mutation carrier group and controls. The composite scores were calculated from the weighted averages of test scores in the models based on the regression coefficients. Sample size estimates were calculated for individual cognitive tests and composites in a theoretical trial aimed at preventing progression from a prodromal stage (CDR® plus NACC-FTLD 0.5) to a fully symptomatic stage (CDR® plus NACC-FTLD ≥ 1). Time-to-event analysis was performed to determine how quickly mutation carriers progressed from CDR® plus NACC-FTLD = 0.5 to ≥ 1 (and therefore how long a trial would need to be).

Results

The results from the logistic regression analyses resulted in different composite scores for each mutation carrier group (i.e. C9orf72, GRN, and MAPT). The estimated sample size to detect a treatment effect was lower for composite scores than for most individual tests. A Kaplan-Meier curve showed that after 3 years, ~ 50% of individuals had converted from CDR® plus NACC-FTLD 0.5 to ≥ 1, which means that the estimated effect size needs to be halved in sample size calculations as only half of the mutation carriers would be expected to progress from CDR® plus NACC FTLD 0.5 to ≥ 1 without treatment over that time period.

Discussion

We created gene-specific cognitive composite scores for C9orf72, GRN, and MAPT mutation carriers, which resulted in substantially lower estimated sample sizes to detect a treatment effect than the individual cognitive tests. The GENFI-Cog composites have potential as cognitive endpoints for upcoming clinical trials. The results from this study provide recommendations for estimating sample size and trial duration.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-00958-0.

Altruism, Volunteering and Cognitive Performance Among Older Adults: A 2-Year Longitudinal Study

This study aims to investigate whether altruism and volunteering are associated differently with cognitive functioning in community-dwelling older adults. A 2-year longitudinal study of 291 Brazilian older adults was conducted. In the baseline analysis, altruism, but not volunteering, was associated with higher scores for the composite cognitive score, the Mini-Mental State Examination, the verbal fluency and the CERAD Recall. Concerning the longitudinal analyses, volunteering at baseline, but not altruism, was associated with verbal fluency and CERAD Word List Recall after 2 years of follow up. Same results were obtained while investigating changes in score. Altruism and volunteering were associated with cognitive tests, albeit in different ways. Volunteering, but not altruism, was associated with lower cognitive decline. However, altruism, but not volunteering, was associated with higher absolute score on these tests. These findings can further understanding of this new field of health research.

Longitudinal Amyloid Cognitive Composite in Preclinical Alzheimer's Disease

BACKGROUND

Previous studies have developed several cognitive composites in preclinical AD. However, more sensitive measures to track cognitive changes and therapeutic efficacy in preclinical Alzheimer's disease (AD) are needed considering diverse sociocultural and linguistic backgrounds. This study developed a composite score that can sensitively detect the Aβ-related cognitive trajectory of preclinical AD using Korean data.

METHODS

A total of 196 cognitively normal (CN) participants who underwent amyloid positron emission tomography were followed-up with neuropsychological assessments. We developed the Longitudinal Amyloid cognitive Composite in Preclinical AD (LACPA) using the linear mixed-effects model (LMM) and z-scores. The LMM was also used to investigate the longitudinal sensitivity of LACPA and the association between time-varying brain atrophy and LACPA.

RESULTS

Considering the group-time interaction effects of each subtest, the Seoul Verbal Learning Test-Elderly's version (SVLT-E) immediate recall/delayed recall/recognition, the Korean Trail Making Test B time, and the Korean Mini-Mental State Examination were selected as components of LACPA. LACPA exhibited a significant group-time interaction effect between the Aβ+ and Aβ- groups (t = -3.288, p = 0.001). Associations between time-varying LACPA and brain atrophy were found in the bilateral medial temporal, right lateral parietal, and right lateral frontal regions, and hippocampal volume.

CONCLUSION

LACPA may contribute to reduction in time and financial burden when monitoring Aβ-related cognitive decline and therapeutic efficacy of the disease-modifying agents specifically targeting Aβ in secondary prevention trials.

Adherence to Mediterranean Diet and Cognitive Abilities in the Greek Cohort of Epirus Health Study

The Mediterranean diet is commonly proposed as a major modifiable protective factor that may delay cognitive impairment in the elderly. The aim of the study was to investigate the cross-sectional association of adherence to the Mediterranean diet with cognitive abilities in a younger Greek population. A total of 1201 healthy adults aged 21-77 years (mean: 47.8) from the Epirus Health Study cohort were included in the analysis. Adherence to the Mediterranean diet was measured using the 14-point Mediterranean Diet Adherence Screener (MEDAS) and cognition was measured using the Trail Making Test, the Verbal Fluency test and the Logical Memory test. Statistical analysis was performed using multiple linear regression models adjusted for age, sex, education, body mass index, smoking status, alcohol consumption and physical activity. Overall, no association was found between the MEDAS score and cognitive tests, which could be explained by the young mean age and high level of education of the participants. Future studies should target young and middle-aged individuals to gain further understanding of the association between Mediterranean diet and cognition in this age group.

Exploration of Plasma Lipids in Mild Cognitive Impairment due to Alzheimer's Disease

BACKGROUND

Lipids have important structural roles in cell membranes and changes to these membrane lipids may influence β- and γ-secretase activities and thus contribute to Alzheimer's disease (AD) pathology.

OBJECTIVE

To explore baseline plasma lipid profiling in participants with mild cognitive impairment (MCI) with and without AD pathology.

METHODS

We identified 261 plasma lipids using reversed-phase liquid chromatography/mass spectrometry in cerebrospinal fluid amyloid positive (Aβ+) or negative (Aβ-) participants with MCI as compared to controls. Additionally, we analyzed the potential associations of plasma lipid profiles with performance on neuropsychological tests at baseline and after two years.

RESULTS

Sphingomyelin (SM) concentrations, particularly, SM(d43:2), were lower in MCI Aβ+ individuals compared to controls. Further, SM(d43:2) was also nominally reduced in MCI Aβ+ individuals compared to MCI Aβ-. No plasma lipids were associated with performance on primary neuropsychological tests at baseline or between the two time points after correction for multiple testing.

CONCLUSION

Reduced plasma concentrations of SM were associated with AD.

A systems-biology clinical trial of a personalized multimodal lifestyle intervention for early Alzheimer's disease

INTRODUCTION

There is an urgent need to develop effective interventional treatments for people with Alzheimer's disease (AD). AD results from a complex multi-decade interplay of multiple interacting dysfunctional biological systems that have not yet been fully elucidated. Epidemiological studies have linked several modifiable lifestyle factors with increased incidence for AD. Because monotherapies have failed to prevent or ameliorate AD, interventional studies should deploy multiple, targeted interventions that address the dysfunctional systems that give rise to AD.

METHODS

This randomized controlled trial (RCT) will examine the efficacy of a 12-month personalized, multimodal, lifestyle intervention in 60 mild cognitive impairment (MCI) and early stage AD patients (aged 50+, amyloid positivity). Both groups receive data-driven, lifestyle recommendations designed to target multiple systemic pathways implicated in AD. One group receives these personalized recommendations without coaching. The other group receives personalized recommendations with health coaching, dietary counseling, exercise training, cognitive stimulation, and nutritional supplements. We collect clinical, proteomic, metabolomic, neuroimaging, and genetic data to fuel systems-biology analyses. We will examine effects on cognition and hippocampal volume. The overarching goal of the study is to longitudinally track biological systems implicated in AD to reveal the dynamics between these systems during the intervention to understand differences in treatment response.

RESULTS

We have developed and implemented a protocol for a personalized, multimodal intervention program for early AD patients. We began enrollment in September 2019; we have enrolled a third of our target (20 of 60) with a 95% retention and 86% compliance rate.

DISCUSSION

This study presents a paradigm shift in designing multimodal, lifestyle interventions to reduce cognitive decline, and how to elucidate the biological systems being targeted. Analytical efforts to explain mechanistic or causal underpinnings of individual trajectories and the interplay between multi-omic variables will inform the design of future hypotheses and development of effective precision medicine trials.

PET evidence of preclinical cerebellar amyloid plaque deposition in autosomal dominant Alzheimer's disease-causing Presenilin-1 E280A mutation carriers

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PET evidence of cerebellar Aβ deposition in unimpaired (CU) PSEN1 E280A kindred.

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Cerebellar Aβ PET SUVR began to distinguish CU carriers from non-carriers at age 34.

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Cortical and cerebellar Aβ PET SUVR are positively associated in CU carriers.

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Cerebellar florbetapir SUVR correlated with lower composite score in CU carriers.

Background

In contrast to sporadic Alzheimer’s disease, autosomal dominant Alzheimer’s disease (ADAD) is associated with greater neuropathological evidence of cerebellar amyloid plaque (Aβ) deposition. In this study, we used positron emission tomography (PET) measurements of fibrillar Aβ burden to characterize the presence and age at onset of cerebellar Aβ deposition in cognitively unimpaired (CU) Presenilin-1 (PSEN1) E280A mutation carriers from the world’s largest extended family with ADAD.

Methods

¹⁸F florbetapir and ¹¹C Pittsburgh compound B (PiB) PET data from two independent studies – API ADAD Colombia Trial (NCT01998841) and Colombia-Boston (COLBOS) longitudinal biomarker study were included. The tracers were selected independently by the respective sponsors prior to the start of each study and used exclusively throughout. Template-based cerebellar Aβ-SUVR (standard-uptake value ratios) using a known-to-be-spared pons reference region (cerebellar SUVR_pons), to a) compare 28–56-year-old CU carriers and non-carriers; b) estimate the age at which cerebellar SUVR_pons began to differ significantly in carrier and non-carrier groups; and c) characterize in carriers associations with age, cortical SUVR_pons, delayed recall memory, and API ADAD composite score.

Results

Florbetapir and PiB cerebellar SUVR_pons were significantly higher in carriers than non-carriers (p < 0.0001). Cerebellar SUVR_pons began to distinguish carriers from non-carriers at age 34, 10 years before the carriers’ estimated age at mild cognitive impairment onset. Florbetapir and PiB cerebellar SUVR_pons in carriers were positively correlated with age (r = 0.44 & 0.69, p < 0.001), cortical SUVR_pons (r = 0.55 & 0.69, p < 0.001), and negatively correlated with delayed recall memory (r = −0.21 & −0.50, p < 0.05, unadjusted for cortical SUVR_pons) and API ADAD composite (r = −0.25, p < 0.01, unadjusted for cortical SUVR_pons in florbetapir API ADAD cohort).

Conclusion

This PET study provides evidence of cerebellar Aβ plaque deposition in CU carriers starting about a decade before the clinical onset of ADAD. Additional studies are needed to clarify the impact of using a cerebellar versus pons reference region on the power to detect and track ADAD changes, even in preclinical stages of this disorder.

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.

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.

Translational Scoring of Candidate Treatments for Alzheimer's Disease: A Systematic Approach

BACKGROUND

There are many failures in treatment development for Alzheimer's disease (AD). Some of these failures are the result of development programs that lacked critical information about candidate drugs as these were advanced from one phase of development to the next. Translational scoring (TS) has been proposed as a means of increasing the rigor with which treatment development programs are executed. Previously, these approaches were not specific to AD or to the phase of drug development. Detailed information on the characteristics needed to advance a candidate agent from one phase to the next is the basis for success in subsequent phases.

SUMMARY

The TS approach is presented with a score range of 0-25 for agents entering phases 1, 2, and 3 of development and those that have completed phase 3 and are being considered for regulatory review. Each phase has 5 essential categories scored from 0-5 indicating the completeness of the data available when the agent is being considered for promotion to the next phase. Lower scores suggest that the development program should be reexamined for missing information while higher scores increase the confidence that the agent has the potential to succeed in the next phase. Scoring guidelines are provided and examples of scores for drugs in recent development programs are provided to illustrate the principles of TS. Key Messages: Successful development of drugs for AD treatment requires disciplined informed decision-making at each phase of development. TS is a methodology for more rigorous drug development to help ensure that inadequately characterized drugs are not advanced and that the development platform at each phase is optimal to support success at the next phase.

Identification of Pre-Clinical Alzheimer's Disease in a Population of Elderly Cognitively Normal Participants

Alzheimer's disease (AD) has a long pathological process, with an approximate lead-time of 20 years. During the early stages of the disease process, little evidence of the building pathology is identifiable without cerebrospinal fluid and/or imaging analyses. Clinical manifestations of AD do not present until irreversible pathological changes have occurred. Given an opportunity to provide treatment prior to irreversible pathological change, this study aims to identify a subgroup of cognitively normal (CN) participants from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL), where subtle changes in cognition are indicative of early AD-related pathology. Using a Bayesian method for unsupervised clustering via mixture models, we define an aggregate measure of posterior probabilities (AMPP score) establishing the likelihood of pre-clinical AD. From Baseline through to 54 months, visuo-spatial function had the greatest contribution to the AMPP score, followed by attention and processing speed and visual memory. Participants with the highest AMPP scores had both increasing neo-cortical amyloid burden and decreasing hippocampus volume over 54 months, compared to those in the lowest category with stable amyloid burden and hippocampus volume. The identification of a possible pre-clinical stage in CN participants via this method, without the aid of disease specific biomarkers, represents an important step in utilizing the strength of cognitive composite scores for the early detection of AD pathology.

Development of a novel cognitive composite outcome to assess therapeutic effects of exercise in the EXERT trial for adults with MCI: The ADAS-Cog-Exec

INTRODUCTION

Use of cognitive composites as primary outcome measures is increasingly common in clinical trials of preclinical and prodromal Alzheimer's disease (AD). Composite outcomes can decrease intra-individual variability, resulting in improved sensitivity to detect longitudinal change and increased statistical power. We developed a novel composite outcome, the ADAS-Cog-Exec, for use in the EXERT trial-a Phase 3 randomized, controlled, 12-month exercise intervention in mild cognitive impairment (MCI).

METHODS

Three combinations of cognitive measures selected from the Alzheimer's Disease Assessment Scale-Cognitive Subscale version 13 (ADAS-Cog13), tests of executive function, and the Clinical Dementia Rating (CDR) were created based on previously documented sensitivity to longitudinal change in MCI and to the effects of exercise. Optimally weighted composites of each combination were modeled using data from the ADNI-1 MCI cohort. Ten-fold cross-validation was performed to obtain a bias-corrected mean to standard deviation ratio (MSDR). The cognitive composites were assessed for their sensitivity to detect 12-month change in MCI.

RESULTS

The MSDR of 12-month change for each of the composite outcomes tested exceeded that of the ADAS-Cog13 total score. The composite with the highest MSDR (MSDR = 0.48) and associated statistical power included scores on ADAS-Cog13 Word Recall, Delayed Word Recall, Orientation, and Number Cancellation subtests; Trail-Making Tests A & B, Digit Symbol Substitution and Category Fluency; and cognitive components of the CDR (Memory, Orientation, Judgement & Problem Solving).

DISCUSSION

An optimally weighted cognitive composite measure was identified and validated for use in EXERT. This composite contained selected subtests from the ADAS-Cog13, additional measures of executive function, and box scores for cognitive components of the CDR. Because this composite score demonstrated high sensitivity to longitudinal change in MCI it will be used as the primary outcome measure for the EXERT trial.

BHA-CS: A novel cognitive composite for Alzheimer's disease and related disorders

INTRODUCTION

Composite scores based on psychometrically rigorous cognitive assessments are well suited for early diagnosis and disease monitoring.

METHODS

We developed and cross-validated the Brain Health Assessment-Cognitive Score (BHA-CS), based on a brief computerized battery, in 451 cognitively normal (CN) and 399 cognitively impaired (mild cognitive impairment [MCI] or dementia) older adults. We investigated its long-term reliability and reliable change indices at longitudinal follow-up (N = 340), and the association with amyloid beta (Aβ) burden in the CN subgroup with Aβ positron emission tomography (N = 119).

RESULTS

The BHA-CS was accurate at detecting cognitive impairment and exhibited excellent long-term stability. Reliable decline over one year was detected in 75% of participants with dementia, 44% with MCI, and 3% of CN. Among CN, the Aβ-positive group showed worse longitudinal performance on the BHA-CS compared to the Aβ-negative group.

DISCUSSION

The BHA-CS is sensitive to cognitive decline in preclinical and prodromal neurodegenerative disease.

The Alzheimer's Prevention Initiative Composite Cognitive Test: a practical measure for tracking cognitive decline in preclinical Alzheimer's disease

Background

There is growing interest in identifying sensitive composite cognitive tests to serve as primary endpoints in preclinical Alzheimer’s disease (AD) treatment trials. We reported previously a composite cognitive test score sensitive to tracking preclinical AD decline up to 5 years prior to clinical diagnosis. Here we expand upon and refine this work, empirically deriving a composite cognitive test score sensitive to tracking preclinical AD decline up to 11 years prior to diagnosis and suitable for use as a primary endpoint in a preclinical AD trial.

Methods

This study used a longitudinal approach to maximize sensitivity to tracking progressive cognitive decline in people who progressed to the clinical stages of AD (n = 868) compared to those who remained cognitively unimpaired during the same time period (n = 989), thereby correcting for normal aging and practice effects. Specifically, we developed the Alzheimer’s Prevention Initiative Preclinical Composite Cognitive test (APCC) to measure very early longitudinal cognitive decline in older adults with preclinical AD. Data from three cohorts from Rush University were analyzed using a partial least squares (PLS) regression model to identify optimal composites within different time periods prior to diagnosis, up to 11 years prior to diagnosis. The mean-to-standard deviation ratio (MSDRs) is an indicator of sensitivity to change and was used to inform the final calculation of the composite score.

Results

The optimal composite, the APCC, is calculated: 0.26*Symbol Digit Modalities + 2.24*MMSE Orientation to Time + 2.14*MMSE Orientation to Place + 0.53*Logical Memory Delayed Recall + 1.36* Word List-Delayed Recall + 0.68*Judgment of Line Orientation + 1.39*Raven’s Progressive Matrices Matrices (subset of 9 items from A and B). The MSDR of the APCC in a population of preclinical AD individuals who eventually progress to cognitive impairment, compared to those who remained cognitively unimpaired during the same time period, was − 1.10 over 1 year.

Conclusions

The APCC is an empirically derived composite cognitive test score with high face validity that is sensitive to preclinical AD decline up to 11 years prior to diagnosis of the clinical stages of AD. The components of the APCC are supported by theoretical understanding of cognitive decline that occurs during preclinical AD. The APCC was used as a primary outcome in the API Generation Program trials.

Composite cognitive and functional measures for early stage Alzheimer's disease trials

INTRODUCTION

Composite scales have been advanced as primary outcomes in early stage Alzheimer's disease trials, and endorsed by the U.S. Food and Drug Administration (FDA) for pivotal trials. They are generally composed of several neurocognitive subscales and may include clinical and functional activity scales.

METHODS

We summarized the development of 12 composite scales intended as outcomes for clinical trials and assessed their characteristics.

RESULTS

Composite scales have been constructed from past observational and clinical trial databases by selecting components of individual neuropsychological tests previously used in clinical trials. The atheoretical approaches to combining scales into a composite scale that have often been used risk omitting clinically important measures and so may include redundant, irrelevant, or noncontributory tests. The deliberate combining of neurocognitive scales with functional activity scales provides arbitrary weightings that also may be clinically irrelevant or obscure change in a particular domain. Basic psychometric information is lacking for most of the composites.

DISCUSSION

Although composite scales are desirable for pivotal clinical trials because they, in principle, provide for a single, primary outcome combining neurocognitive and/or functional domains, they have substantial limitations, including their common derivations, inattention to basic psychometric principles, redundancy, absence of alternate forms, and, arguably, the inclusion of functional measures in some. In effect, any currently used composite is undergoing validation through its use in a trial. The assumption that a composite, by its construction alone, is more likely than an individual measure to detect an effect from any particular drug and that the effect is more clinically relevant or valid has not been demonstrated.

Developing an Executive Functioning Composite Score for Research and Clinical Trials

OBJECTIVE

Executive functioning encompasses interactive cognitive processes such as planning, organization, set-shifting, inhibition, self-monitoring, working memory, and initiating and sustaining motor and mental activity. Researchers therefore typically assess executive functioning with multiple tests, each yielding multiple scores. A single composite score of executive functioning, which summarizes deficits across a battery of tests, would be useful in research and clinical trials. This study examines multiple candidate composite scores of executive functioning using tests from the Delis-Kaplan Executive Function System (D-KEFS).

METHOD

Participants were 875 adults between the ages of 20 and 89 years from the D-KEFS standardization sample. Seven Total Achievement scores were used from three tests (i.e., Trail Making, Verbal Fluency, and Color-Word Interference) to form eight composite scores that were compared based on their psychometric properties and association with intelligence (IQ).

RESULTS

The distributions of most composite scores were mildly to severely skewed, and some had a pronounced ceiling effect. The composite scores all showed a medium positive correlation with IQ. The composite scores were highly intercorrelated in the total sample and in four IQ subgroups (i.e., IQ <89, 90-99, 100-109, 110+), with some being so highly correlated that they appear redundant.

CONCLUSIONS

This study is part of a larger research program developing a cognition endpoint for research and clinical trials with sound psychometric properties and utility across discrepant test batteries. Future research is needed to examine the reliability and ecological validity of these composite scores.

The Cognitive-Functional Composite is sensitive to clinical progression in early dementia: Longitudinal findings from the Catch-Cog study cohort

INTRODUCTION

In an attempt to capture clinically meaningful cognitive decline in early dementia, we developed the Cognitive-Functional Composite (CFC). We investigated the CFC's sensitivity to decline in comparison to traditional clinical endpoints.

METHODS

This longitudinal construct validation study included 148 participants with subjective cognitive decline, mild cognitive impairment, or mild dementia. The CFC and traditional tests were administered at baseline, 3, 6, and 12 months. Sensitivity to change was investigated using linear mixed models and r 2 effect sizes.

RESULTS

CFC scores declined over time (β = -.16, P < .001), with steepest decline observed in mild Alzheimer's dementia (β = -.25, P < .001). The CFC showed medium-to-large effect sizes at succeeding follow-up points (r 2 = .08-.42), exhibiting greater change than the Clinical Dementia Rating scale (r 2 = .02-.12). Moreover, change on the CFC was significantly associated with informant reports of cognitive decline (β = .38, P < .001).

DISCUSSION

By showing sensitivity to decline, the CFC could enhance the monitoring of disease progression in dementia research and clinical practice.

Cerebral Amyloid Angiopathy and Neuritic Plaque Pathology Correlate with Cognitive Decline in Elderly Non-Demented Individuals

BACKGROUND

Cerebral amyloid angiopathy (CAA) is a vascular neuropathology commonly reported in non-cognitively impaired (NCI), mild cognitive impairment, and Alzheimer's disease (AD) brains. However, it is unknown whether similar findings are present in non-demented elderly subjects.

OBJECTIVE

This study determined the association between CAA and cognition among elderly NCI subjects with varying levels of AD pathology.

METHODS

Data from 182 cases that received a diagnosis of NCI at their first clinical assessment were obtained from the Rush Religious Orders study (RROS). A cognitive composite score was used to measure cognitive decline. CAA was dichotomized as present or absent. Cases were also dichotomized according to CERAD neuropathological diagnosis and Braak staging. A mixed model-repeated measures analysis assessed decline on the cognitive composite score.

RESULTS

CAA, alone, was not associated with cognitive decline [-0.87 (95% CI: -3.33, 1.58), p = 0.49]. However, among those with CAA, the High CERAD group had significantly greater decline relative to the Low CERAD group [-4.08 (95% CI: -7.10, -1.06), p = 0.008]. The High and Low CERAD groups were not significantly different [-1.77 (95% CI: -6.14, 2.60), p = 0.43] in those without CAA. Composite score decline in the High and Low Braak groups with [-1.32 (95% CI: -4.40, 1.75), p = 0.40] or without [0.27 (95% CI: -4.01, 4.56), p = 0.90] CAA was not significantly different.

CONCLUSION

The current data shows that an interaction between CAA and plaque load is associated with greater decline on a cognitive composite score used to test non-cognitively impaired elderly participants in AD prevention trials.

Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease

Alzheimer's disease (AD) is characterised by a dynamic process of neurocognitive changes from normal cognition to mild cognitive impairment (MCI) and progression to dementia. However, not all individuals with MCI develop dementia. Predicting whether individuals with MCI will decline (i.e. progressive MCI) or remain stable (i.e. stable MCI) is impeded by patient heterogeneity due to comorbidities that may lead to MCI diagnosis without progression to AD. Despite the importance of early diagnosis of AD for prognosis and personalised interventions, we still lack robust tools for predicting individual progression to dementia. Here, we propose a novel trajectory modelling approach based on metric learning (Generalised Metric Learning Vector Quantization) that mines multimodal data from MCI patients in the Alzheimer's disease Neuroimaging Initiative (ADNI) cohort to derive individualised prognostic scores of cognitive decline due to AD. We develop an integrated biomarker generation- using partial least squares regression- and classification methodology that extends beyond binary patient classification into discrete subgroups (i.e. stable vs. progressive MCI), determines individual profiles from baseline (i.e. cognitive or biological) data and predicts individual cognitive trajectories (i.e. change in memory scores from baseline). We demonstrate that a metric learning model trained on baseline cognitive data (memory, executive function, affective measurements) discriminates stable vs. progressive MCI individuals with high accuracy (81.4%), revealing an interaction between cognitive (memory, executive functions) and affective scores that may relate to MCI comorbidity (e.g. affective disturbance). Training the model to perform the same binary classification on biological data (mean cortical β-amyloid burden, grey matter density, APOE 4) results in similar prediction accuracy (81.9%). Extending beyond binary classifications, we develop and implement a trajectory modelling approach that shows significantly better performance in predicting individualised rate of future cognitive decline (i.e. change in memory scores from baseline), when the metric learning model is trained with biological (r = -0.68) compared to cognitive (r = -0.4) data. Our trajectory modelling approach reveals interpretable and interoperable markers of progression to AD and has strong potential to guide effective stratification of individuals based on prognostic disease trajectories, reducing MCI patient misclassification, that is critical for clinical practice and discovery of personalised interventions.

Individualized clinical management of patients at risk for Alzheimer's dementia

INTRODUCTION

Multidomain intervention for Alzheimer's disease (AD) risk reduction is an emerging therapeutic paradigm.

METHODS

Patients were prescribed individually tailored interventions (education/pharmacologic/nonpharmacologic) and rated on compliance. Normal cognition/subjective cognitive decline/preclinical AD was classified as Prevention. Mild cognitive impairment due to AD/mild-AD was classified as Early Treatment. Change from baseline to 18 months on the modified Alzheimer's Prevention Cognitive Composite (primary outcome) was compared against matched historical control cohorts. Cognitive aging composite (CogAging), AD/cardiovascular risk scales, and serum biomarkers were secondary outcomes.

RESULTS

One hundred seventy-four were assigned interventions (age 25-86). Higher-compliance Prevention improved more than both historical cohorts (P = .0012, P < .0001). Lower-compliance Prevention also improved more than both historical cohorts (P = .0088, P < .0055). Higher-compliance Early Treatment improved more than lower compliance (P = .0007). Higher-compliance Early Treatment improved more than historical cohorts (P < .0001, P = .0428). Lower-compliance Early Treatment did not differ (P = .9820, P = .1115). Similar effects occurred for CogAging. AD/cardiovascular risk scales and serum biomarkers improved.

DISCUSSION

Individualized multidomain interventions may improve cognition and reduce AD/cardiovascular risk scores in patients at-risk for AD dementia.

Study partner types and prediction of cognitive performance: implications to preclinical Alzheimer's trials

BACKGROUND

Alzheimer's disease (AD) clinical trials require enrollment of a participant and a study partner, whose role includes assessing participant cognitive and functional performance. AD trials now investigate early stages of the disease, when participants are not cognitively impaired. This gives rise to the question of whether study partners or participants provide more information in these trials.

METHODS

We used data from the AD Cooperative Study Prevention Instrument Project (ADCS-PI) to compare participant and study partner predictions of the participant's current and future cognitive state. We used the Cognitive Function Instrument (CFI) as a measure of evaluation of the participant's cognitive status and the modified ADCS Preclinical Alzheimer's Cognitive Composite (mADCS-PACC) as an objective measure of cognition. Stratifying by cognitive status and study partner type and adjusting for other predictors of the participant's cognitive state, we used random forests along with estimated mean variable importance (eMVI) to assess how well each member of the dyad can predict cognitive state at current and later visits. We also fit linear regression models at each time point and for each scenario.

RESULTS

Participants were better at predicting future cognitive status compared to their study partners regardless of study partner type, though the difference between participants and partners was greatest for non-spousal dyads in the lowest-performing quartile. Cross-sectional assessments differed substantially by dyad type. Within the lowest cognitive performance quartile, participants having a non-spousal study partner outperformed their partners in assessing cognition at later times. Spousal partners, in contrast, outperformed participants later in the study in predicting current cognitive performance.

CONCLUSIONS

These results indicate that participants tend to be better at predicting future cognition compared to their study partners regardless of the study partner type. When assessing current cognition, however, spousal study partners perform better at later time points and non-spousal study partners do not provide as much information regarding participant cognitive state.

The "rights" of precision drug development for Alzheimer's disease

There is a high rate of failure in Alzheimer's disease (AD) drug development with 99% of trials showing no drug-placebo difference. This low rate of success delays new treatments for patients and discourages investment in AD drug development. Studies across drug development programs in multiple disorders have identified important strategies for decreasing the risk and increasing the likelihood of success in drug development programs. These experiences provide guidance for the optimization of AD drug development. The "rights" of AD drug development include the right target, right drug, right biomarker, right participant, and right trial. The right target identifies the appropriate biologic process for an AD therapeutic intervention. The right drug must have well-understood pharmacokinetic and pharmacodynamic features, ability to penetrate the blood-brain barrier, efficacy demonstrated in animals, maximum tolerated dose established in phase I, and acceptable toxicity. The right biomarkers include participant selection biomarkers, target engagement biomarkers, biomarkers supportive of disease modification, and biomarkers for side effect monitoring. The right participant hinges on the identification of the phase of AD (preclinical, prodromal, dementia). Severity of disease and drug mechanism both have a role in defining the right participant. The right trial is a well-conducted trial with appropriate clinical and biomarker outcomes collected over an appropriate period of time, powered to detect a clinically meaningful drug-placebo difference, and anticipating variability introduced by globalization. We lack understanding of some critical aspects of disease biology and drug action that may affect the success of development programs even when the "rights" are adhered to. Attention to disciplined drug development will increase the likelihood of success, decrease the risks associated with AD drug development, enhance the ability to attract investment, and make it more likely that new therapies will become available to those with or vulnerable to the emergence of AD.

Biomarker-Based Signature of Alzheimer's Disease in Pre-MCI Individuals

Alzheimer’s disease (AD) pathology begins decades before the onset of clinical symptoms. It is recognized as a clinicobiological entity, being detectable in vivo independently of the clinical stage by means of pathophysiological biomarkers. Accordingly, neuropathological studies that were carried out on healthy elderly subjects, with or without subjective experience of cognitive decline, reported evidence of AD pathology in a high proportion of cases. At present, mild cognitive impairment (MCI) represents the only clinically diagnosed pre-dementia stage. Several attempts have been carried out to detect AD as early as possible, when subtle cognitive alterations, still not fulfilling MCI criteria, appear. Importantly, pre-MCI individuals showing the positivity of pathophysiological AD biomarkers show a risk of progression similar to MCI patients. In view of successful treatment with disease modifying agents, in a clinical setting, a timely diagnosis is mandatory. In clinical routine, biomarkers assessment should be taken into consideration whenever a subject with subtle cognitive deficits (pre-MCI), who is aware of his/her decline, requests to know the cause of such disturbances. In this review, we report the available neuropsychological and biomarkers data that characterize the pre-MCI patients, thus proposing pre-MCI as the first clinical manifestation of AD.

Clinical Trials for Disease-Modifying Therapies in Alzheimer's Disease: A Primer, Lessons Learned, and a Blueprint for the Future

Alzheimer’s disease (AD) has no currently approved disease-modifying therapies (DMTs), and treatments to prevent, delay the onset, or slow the progression are urgently needed. A delay of 5 years if available by 2025 would decrease the total number of patients with AD by 50% in 2050. To meet the definition of DMT, an agent must produce an enduring change in the course of AD; clinical trials of DMTs have the goal of demonstrating this effect. AD drug discovery entails target identification followed by high throughput screening and lead optimization of drug-like compounds. Once an optimized agent is available and has been assessed for efficacy and toxicity in animals, it progresses through Phase I testing with healthy volunteers, Phase II learning trials to establish proof-of-mechanism and dose, and Phase III confirmatory trials to demonstrate efficacy and safety in larger populations. Phase III is followed by Food and Drug Administration review and, if appropriate, market access. Trial populations include cognitively normal at-risk participants in prevention trials, mildly impaired participants with biomarker evidence of AD in prodromal AD trials, and subjects with cognitive and functional impairment in AD dementia trials. Biomarkers are critical in trials of DMTs, assisting in participant characterization and diagnosis, target engagement and proof-of-pharmacology, demonstration of disease-modification, and monitoring side effects. Clinical trial designs include randomized, parallel group; delayed start; staggered withdrawal; and adaptive. Lessons learned from completed trials inform future trials and increase the likelihood of success.

Amyloid Accumulation and Cognitive Decline in Clinically Normal Older Individuals: Implications for Aging and Early Alzheimer's Disease

The aberrant accumulation of the amyloid protein is a critical and early event in the Alzheimer's disease (AD) cascade. Given the early involvement of this pathological process, it is not surprising that many clinically normal (CN) older individuals demonstrate evidence of abnormal Aβ at postmortem examination and in vivo using either CSF or PET imaging. Converging evidence across multiple research groups suggests that the presence of abnormal Aβ among CN individuals is associated with elevated risk of future clinical impairment and cognitive decline. Amyloid positivity in conjunction with biomarkers of neuronal injury offers further insight into which CN are most at risk for short-term decline. Although in its infancy, tau PET has demonstrated early increases among Aβ+ that will likely be an important indicator of risk among CN. Overall, the detection of early Aβ among CN individuals has provided an important opportunity to understand the contributions of this pathology to age-related cognitive decline and to explore early intervention with disease modifying strategies.

Assessing cognition and daily function in early dementia using the cognitive-functional composite: findings from the Catch-Cog study cohort

Background

The cognitive-functional composite (CFC) was designed to improve the measurement of clinically relevant changes in predementia and early dementia stages. We have previously demonstrated its good test-retest reliability and feasibility of use. The current study aimed to evaluate several quality aspects of the CFC, including construct validity, clinical relevance, and suitability for the target population.

Methods

Baseline data of the Capturing Changes in Cognition study was used: an international, prospective cohort study including participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), Alzheimer’s disease (AD) dementia, and dementia with Lewy bodies (DLB). The CFC comprises seven existing cognitive tests focusing on memory and executive functions (EF) and the informant-based Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q). Construct validity and clinical relevance were assessed by (1) confirmatory factor analyses (CFA) using all CFC subtests and (2) linear regression analyses relating the CFC score (independent) to reference measures of disease severity (dependent), correcting for age, sex, and education. To assess the suitability for the target population, we compared score distributions of the CFC to those of traditional tests (Alzheimer’s Disease Assessment Scale–Cognitive subscale, Alzheimer’s Disease Cooperative Study–Activities of Daily Living scale, and Clinical Dementia Rating scale).

Results

A total of 184 participants were included (age 71.8 ± 8.4; 42% female; n = 14 SCD, n = 80 MCI, n = 78 AD, and n = 12 DLB). CFA showed that the hypothesized three-factor model (memory, EF, and IADL) had adequate fit (CFI = .931, RMSEA = .091, SRMR = .06). Moreover, worse CFC performance was associated with more cognitive decline as reported by the informant (β = .61, p < .001), poorer quality of life (β = .51, p < .001), higher caregiver burden (β = − .51, p < .001), more apathy (β = − .36, p < .001), and less cortical volume (β = .34, p = .02). Whilst correlations between the CFC and traditional measures were moderate to strong (ranging from − .65 to .83, all p < .001), histograms showed floor and ceiling effects for the traditional tests as compared to the CFC.

Conclusions

Our findings illustrate that the CFC has good construct validity, captures clinically relevant aspects of disease severity, and shows no range restrictions in scoring. It therefore provides a more useful outcome measure than traditional tests to evaluate cognition and function in MCI and mild AD.

Electronic supplementary material

The online version of this article (10.1186/s13195-019-0500-5) contains supplementary material, which is available to authorized users.

A Computerized Continuous-Recognition Task for Measurement of Episodic Memory

Based on clinical observations of severe episodic memory (EM) impairment in dementia of Alzheimer’s disease (AD), a brief, computerized EM test was developed for AD patient evaluation. A continuous recognition task (CRT) was chosen because of its extensive use in EM research. Initial experience with this computerized CRT (CCRT) showed patients were very engaged in the test, but AD patients had marked failure in recognizing repeated images. Subsequently, the test was administered to audiences, and then a two-minute online version was implemented (http://www.memtrax.com). The online CCRT shows 50 images, 25 unique and 25 repeats, which subjects respectively either try to remember or indicate recognition as quickly as possible. The pictures contain 5 sets of 5 images of scenes or objects (e.g., mountains, clothing, vehicles, etc.). A French company (HAPPYneuron, SAS) provided the test for 2 years, with these results. Of 18,477 individuals, who indicated sex and age 21–99 years and took the test for the first time, 18,007 individuals performed better than chance. In this group, age explained 1.5% of the variance in incorrect responses and 3.5% of recognition time variance, indicating considerable population variability. However, when averaging for specific year of age, age explained 58% of percent incorrect variance and 78% of recognition time variance, showing substantial population variability but a major age effect. There were no apparent sex effects. Further studies are indicated to determine the value of this CCRT as an AD screening test and validity as a measure of EM impairment in other clinical conditions.

Alzheimer's Disease Clinical Trials: Moving Toward Successful Prevention

Despite major academic and industry efforts, Alzheimer's disease (AD) remains the only leading cause of death for which no disease-modifying treatment is available. Disappointing clinical trials over the last several years have led to a growing consensus on the need to intervene earlier in the disease process, before the onset of any clinical symptoms. However, drug development at this stage is challenging given the difficulty of assessing a therapeutic benefit in subjects who are, by definition, clinically healthy. The US FDA recently issued new draft guidance for trials in early AD, which revised the taxonomy of AD by recognizing four stages of the disease, including an expanded view of the predementia stage. These guidelines further advance regulatory support for clinical trials in earlier stages of AD. We discuss the basis for this change and the impact it may have on early-intervention AD trials as well as on stimulating the need for improved biomarkers and outcome measures that will be required for a disease-modifying drug to win approval.

Is there a specific memory signature associated with Aβ-PET positivity in patients with amnestic mild cognitive impairment?

Amnestic mild cognitive impairment (aMCI) is a clinical entity with various potential etiologies including but not limited to Alzheimer's disease. We examined whether a positive ([18F]Florbetapir) beta amyloid positron emission tomography scan, supporting underlying Alzheimer's disease pathophysiology, was associated with specific memory deficits in 48 patients with aMCI (33 beta amyloid positive, 15 beta amyloid negative). Memory was evaluated using an autobiographical fluency task and a word-list learning task with 2 different encoding types (shallow/incidental versus deep/intentional). Compared with 40 beta amyloid-negative controls, both aMCI subgroups demonstrated severe deficits in the global memory score and in most subscores of both tasks. Finer-grained analyses of memory tests showed subtle association with beta amyloid status, revealing a stronger impairment of the primacy effect in beta amyloid-positive patients. Structural magnetic resonance imaging showed that both aMCI subgroups exhibited comparable atrophy patterns, with similar degrees of medial temporal volume loss compared with controls. Specifically assessing the primacy effect might complement global memory scores in identifying beta amyloid-positive patients with aMCI.

Prevalence and risk of progression of preclinical Alzheimer's disease stages: a systematic review and meta-analysis

Background

Alzheimer’s disease (AD) pathology begins several years before the clinical onset. The long preclinical phase is composed of three stages according to the 2011National Institute on Aging and Alzheimer’s Association (NIA-AA) criteria, followed by mild cognitive impairment (MCI), a featured clinical entity defined as “due to AD”, or “prodromal AD”, when pathophysiological biomarkers (i.e., cerebrospinal fluid or positron emission tomography with amyloid tracer) are positive. In the clinical setting, there is a clear need to detect the earliest symptoms not yet fulfilling MCI criteria, in order to proceed to biomarker assessment for diagnostic definition, thus offering treatment with disease-modifying drugs to patients as early as possible. According to the available evidence, we thus estimated the prevalence and risk of progression at each preclinical AD stage, with special interest in Stage 3.

Methods

Cross-sectional and longitudinal studies published from April 2008 to May 2018 were obtained through MEDLINE-PubMed, screened, and systematically reviewed by four independent reviewers. Data from included studies were meta-analyzed using random-effects models. Heterogeneity was assessed by I² statistics.

Results

Estimated overall prevalence of preclinical AD was 22% (95% CI = 18–26%). Rate of biomarker positivity overlapped in cognitively normal individuals and people with subjective cognitive decline. The risk of progression increases across preclinical AD stages, with individuals classified as NIA-AA Stage 3 showing the highest risk (73%, 95% CI = 40–92%) compared to those in Stage 2 (38%, 95% CI = 21–59%) and Stage 1 (20%, 95% CI = 10–34%).

Conclusion

Available data consistently show that risk of progression increases across the preclinical AD stages, where Stage 3 shows a risk of progression comparable to MCI due to AD. Accordingly, an effort should be made to also operationalize the diagnostic work-up in subjects with subtle cognitive deficits not yet fulfilling MCI criteria. The possibility to define, in the clinical routine, a patient as “pre-MCI due to AD” could offer these subjects the opportunity to use disease-modifying drugs at best.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0459-7) contains supplementary material, which is available to authorized users.

On weighted composite scores for early Alzheimer's trials

Recent research on finding appropriate composite endpoints for preclinical Alzheimer's disease has focused considerable effort on finding "optimized" weights in the construction of a weighted composite score. In this paper, several proposed methods are reviewed. Our results indicate no evidence that these methods will increase the power of the test statistics, and some of these weights will introduce biases to the study. Our recommendation is to focus on identifying more sensitive items from clinical practice and appropriate statistical analyses of a large Alzheimer's data set. Once a set of items has been selected, there is no evidence that adding weights will generate more sensitive composite endpoints.

Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline?

Background: The discovery of early, non-invasive biomarkers for the identification of “preclinical” or “pre-symptomatic” Alzheimer's disease and other dementias is a key issue in the field, especially for research purposes, the design of preventive clinical trials, and drafting population-based health care policies. Complex behaviors are natural candidates for this. In particular, recent studies have suggested that speech alterations might be one of the earliest signs of cognitive decline, frequently noticeable years before other cognitive deficits become apparent. Traditional neuropsychological language tests provide ambiguous results in this context. In contrast, the analysis of spoken language productions by Natural Language Processing (NLP) techniques can pinpoint language modifications in potential patients. This interdisciplinary study aimed at using NLP to identify early linguistic signs of cognitive decline in a population of elderly individuals.

Methods: We enrolled 96 participants (age range 50–75): 48 healthy controls (CG) and 48 cognitively impaired participants: 16 participants with single domain amnestic Mild Cognitive Impairment (aMCI), 16 with multiple domain MCI (mdMCI) and 16 with early Dementia (eD). Each subject underwent a brief neuropsychological screening composed by MMSE, MoCA, GPCog, CDT, and verbal fluency (phonemic and semantic). The spontaneous speech during three tasks (describing a complex picture, a typical working day and recalling a last remembered dream) was then recorded, transcribed and annotated at various linguistic levels. A multidimensional parameter computation was performed by a quantitative analysis of spoken texts, computing rhythmic, acoustic, lexical, morpho-syntactic, and syntactic features.

Results: Neuropsychological tests showed significant differences between controls and mdMCI, and between controls and eD participants; GPCog, MoCA, PF, and SF also discriminated between controls and aMCI. In the linguistic experiments, a number of features regarding lexical, acoustic and syntactic aspects were significant in differentiating between mdMCI, eD, and CG (non-parametric statistical analysis). Some features, mainly in the acoustic domain also discriminated between CG and aMCI.

Conclusions: Linguistic features of spontaneous speech transcribed and analyzed by NLP techniques show significant differences between controls and pathological states (not only eD but also MCI) and seems to be a promising approach for the identification of preclinical stages of dementia. Long duration follow-up studies are needed to confirm this assumption.

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.

Cognitive composite score association with Alzheimer's disease plaque and tangle pathology

BACKGROUND

Cognitive composite scores are used as the primary outcome measures for Alzheimer's disease (AD) prevention trials; however, the extent to which these composite measures correlate with AD pathology has not been fully investigated. Since many on-going AD prevention studies are testing therapies that target either amyloid or tau, we sought to establish an association between a cognitive composite score and the underlying pathology of AD.

METHODS

Data from 192 older deceased and autopsied persons from the Rush Religious Order Study were used in this study. All participants were classified at their initial evaluations with a clinical diagnosis of no cognitive impairment (NCI). Of these individuals, 105 remained NCI at the time of their death while the remaining 87 progressed to mild cognitive impairment (MCI) or AD. A cognitive composite score composed of eight cognitive tests was used as the outcome measure. Individuals were classified into groups based on Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropathological diagnosis and Braak stage.

RESULTS

The rate of annualized composite score decline was significantly greater for the high CERAD (p < 0.001, d = 0.56) and Braak (p < 0.001, d = 0.55) groups compared with the low CERAD and Braak groups, respectively. Mixed-model repeated measure (MMRM) analyses revealed a significantly greater difference in composite score change from baseline for the high CERAD group relative to the low CERAD group after 5 years (Δ = -2.74, 95% confidence interval (CI) -5.01 to -0.47; p = 0.02). A similar analysis between low and high Braak stage groups found no significant difference in change from baseline (Δ = -0.69, 95% CI -3.03 to 1.66; p = 0.56).

CONCLUSIONS

These data provide evidence that decreased cognitive composite scores were significantly associated with increased AD pathology and provide support for the use of cognitive composite scores in AD prevention trials.