The European Prevention of Alzheimer's Dementia (EPAD) Longitudinal Cohort Study: Baseline Data Release V500.0

Continuous β-Amyloid CSF/PET Imbalance Model to Capture Alzheimer Disease Heterogeneity

BACKGROUND AND OBJECTIVES

Discordance between CSF and PET biomarkers of β-amyloid (Aβ) might reflect an imbalance between soluble and aggregated species, possibly reflecting disease heterogeneity. Previous studies generally used binary cutoffs to assess discrepancies in CSF/PET biomarkers, resulting in a loss of information on the extent of discordance. In this study, we (1) jointly modeled Aβ-CSF/PET data to derive a continuous measure of the imbalance between soluble and fibrillar pools of Aβ, (2) investigated factors contributing to this imbalance, and (3) examined associations with cognitive trajectories.

METHODS

Across 822 cognitively unimpaired (n = 261) and cognitively impaired (n = 561) Alzheimer's Disease Neuroimaging Initiative individuals (384 [46.7%] females, mean age 73.0 ± 7.4 years), we fitted baseline CSF-Aβ42 and global Aβ-PET to a hyperbolic regression model, deriving a participant-specific Aβ-aggregation score (standardized residuals); negative values represent more soluble relative to aggregated Aβ and positive values more aggregated relative to soluble Aβ. Using linear models, we investigated whether methodological factors, demographics, CSF biomarkers, and vascular burden contributed to Aβ-aggregation scores. With linear mixed models, we assessed whether Aβ-aggregation scores were predictive of cognitive functioning. Analyses were repeated in an early independent validation cohort of 383 Amyloid Imaging to Prevent Alzheimer's Disease Prognostic and Natural History Study individuals (224 [58.5%] females, mean age 65.2 ± 6.9 years).

RESULTS

The imbalance model could be fit (pseudo-R2 = 0.94) in both cohorts, across CSF kits and PET tracers. Although no associations were observed with the main methodological factors, lower Aβ-aggregation scores were associated with larger ventricular volume (β = 0.13, p < 0.001), male sex (β = -0.18, p = 0.019), and homozygous APOE-ε4 carriership (β = -0.56, p < 0.001), whereas higher scores were associated with increased uncorrected CSF p-tau (β = 0.17, p < 0.001) and t-tau (β = 0.16, p < 0.001), better baseline executive functioning (β = 0.12, p < 0.001), and slower global cognitive decline (β = 0.14, p = 0.006). In the validation cohort, we replicated the associations with APOE-ε4, CSF t-tau, and, although modestly, with cognition.

DISCUSSION

We propose a novel continuous model of Aβ CSF/PET biomarker imbalance, accurately describing heterogeneity in soluble vs aggregated Aβ pools in 2 independent cohorts across the full Aβ continuum. Aβ-aggregation scores were consistently associated with genetic and AD-associated CSF biomarkers, possibly reflecting disease heterogeneity beyond methodological influences.

Genetic characterization of the ALFA study: Uncovering genetic profiles in the Alzheimer's continuum

INTRODUCTION

In 2013, the ALzheimer's and FAmilies (ALFA) project was established to investigate pathophysiological changes in preclinical Alzheimer's disease (AD), and to foster research on early detection and preventive interventions.

METHODS

We conducted a comprehensive genetic characterization of ALFA participants with respect to neurodegenerative/cerebrovascular diseases, AD biomarkers, brain endophenotypes, risk factors and aging biomarkers. We placed particular emphasis on amyloid/tau status and assessed gender differences. Multiple polygenic risk scores were computed to capture different aspects of genetic predisposition. We additionally compared AD risk in ALFA to that across the full disease spectrum from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

RESULTS

Results show that the ALFA project has been successful at establishing a cohort of cognitively unimpaired individuals at high genetic predisposition of AD.

DISCUSSION

It is, therefore, well-suited to study early pathophysiological changes in the preclinical AD continuum. Highlights Prevalence of ε4 carriers in ALzheimer and FAmilies (ALFA) is higher than in the general European population The ALFA study is highly enriched in Alzheimer's disease (AD) genetic risk factors beyond APOE AD genetic profiles in ALFA are similar to clinical groups along the continuum ALFA has succeeded in establishing a cohort of cognitively unimpaired individuals at high genetic AD risk ALFA is well suited to study pathogenic events/early pathophysiological changes in AD.

Modifiable dementia risk factors and AT(N) biomarkers: findings from the EPAD cohort

Introduction

Modifiable risk factors account for a substantial proportion of Alzheimer's disease (AD) cases and we currently have a discrete AT(N) biomarker profile for AD biomarkers: amyloid (A), p-tau (T), and neurodegeneration (N). Here, we investigated how modifiable risk factors relate to the three hallmark AT(N) biomarkers of AD.

Methods

Participants from the European Prevention of Alzheimer's Dementia (EPAD) study underwent clinical assessments, brain magnetic resonance imaging, and cerebrospinal fluid collection and analysis. Generalized additive models (GAMs) with penalized regression splines were modeled in the AD Workbench on the NTKApp.

Results

A total of 1,434 participants were included (56% women, 39% APOE ε4+) with an average age of 65.5 (± 7.2) years. We found that modifiable risk factors of less education (t = 3.9, p < 0.001), less exercise (t = 2.1, p = 0.034), traumatic brain injury (t = -2.1, p = 0.036), and higher body mass index (t = -4.5, p < 0.001) were all significantly associated with higher AD biomarker burden.

Discussion

This cross-sectional study provides further support for modifiable risk factors displaying neuroprotective associations with the characteristic AT(N) biomarkers of AD.

Models and methods: a perspective of the impact of six IMI translational data-centric initiatives for Alzheimer's disease and other neuropsychiatric disorders

The Innovative Medicines Initiative (IMI), was a European public-private partnership (PPP) undertaking intended to improve the drug development process, facilitate biomarker development, accelerate clinical trial timelines, improve success rates, and generally increase the competitiveness of European pharmaceutical sector research. Through the IMI, pharmaceutical research interests and the research agenda of the EU are supported by academic partnership and financed by both the pharmaceutical companies and public funds. Since its inception, the IMI has funded dozens of research partnerships focused on solving the core problems that have consistently obstructed the translation of research into clinical success. In this post-mortem review paper, we focus on six research initiatives that tackled foundational challenges of this nature: Aetionomy, EMIF, EPAD, EQIPD, eTRIKS, and PRISM. Several of these initiatives focused on neurodegenerative diseases; we therefore discuss the state of neurodegenerative research both at the start of the IMI and now, and the contributions that IMI partnerships made to progress in the field. Many of the initiatives we review had goals including, but not limited to, the establishment of translational, data-centric initiatives and the implementation of trans-diagnostic approaches that move beyond the candidate disease approach to assess symptom etiology without bias, challenging the construct of disease diagnosis. We discuss the successes of these initiatives, the challenges faced, and the merits and shortcomings of the IMI approach with participating senior scientists for each. Here, we distill their perspectives on the lessons learned, with an aim to positively impact funding policy and approaches in the future.

The European Prevention of Alzheimer's Dementia Programme: An Innovative Medicines Initiative-funded partnership to facilitate secondary prevention of Alzheimer's disease dementia

INTRODUCTION

Tens of millions of people worldwide will develop Alzheimer's disease (AD), and only by intervening early in the preclinical disease can we make a fundamental difference to the rates of late-stage disease where clinical symptoms and societal burden manifest. However, collectively utilizing data, samples, and knowledge amassed by large-scale projects such as the Innovative Medicines Initiative (IMI)-funded European Prevention of Alzheimer's Dementia (EPAD) program will enable the research community to learn, adapt, and implement change.

METHOD

In the current article, we define and discuss the substantial assets of the EPAD project for the scientific community, patient population, and industry, describe the EPAD structure with a focus on how the public and private sector interacted and collaborated within the project, reflect how IMI specifically supported the achievements of the above, and conclude with a view for future.

RESULTS

The EPAD project was a €64-million investment to facilitate secondary prevention of AD dementia research. The project recruited over 2,000 research participants into the EPAD longitudinal cohort study (LCS) and included over 400 researchers from 39 partners. The EPAD LCS data and biobank are freely available and easily accessible via the Alzheimer's Disease Data Initiative's (ADDI) AD Workbench platform and the University of Edinburgh's Sample Access Committee. The trial delivery network established within the EPAD program is being incorporated into the truly global offering from the Global Alzheimer's Platform (GAP) for trial delivery, and the almost 100 early-career researchers who were part of the EPAD Academy will take forward their experience and learning from EPAD to the next stage of their careers.

DISCUSSION

Through GAP, IMI-Neuronet, and follow-on funding from the Alzheimer's Association for the data and sample access systems, the EPAD assets will be maintained and, as and when sponsors seek a new platform trial to be established, the learnings from EPAD will ensure that this can be developed to be even more successful than this first pan-European attempt.

Associations between cerebrospinal fluid markers and cognition in ageing and dementia: A systematic review

A biomarker associated with cognition in neurodegenerative dementias would aid in the early detection of disease progression, complement clinical staging and act as a surrogate endpoint in clinical trials. The current systematic review evaluates the association between cerebrospinal fluid protein markers of synapse loss and neuronal injury and cognition. We performed a systematic search which revealed 67 studies reporting an association between cerebrospinal fluid markers of interest and neuropsychological performance. Despite the substantial heterogeneity between studies, we found some evidence for an association between neurofilament-light and worse cognition in Alzheimer's diseases, frontotemporal dementia and typical cognitive ageing. Moreover, there was an association between cerebrospinal fluid neurogranin and cognition in those with an Alzheimer's-like cerebrospinal fluid biomarker profile. Some evidence was found for cerebrospinal fluid neuronal pentraxin-2 as a correlate of cognition across dementia syndromes. Due to the substantial heterogeneity of the field, no firm conclusions can be drawn from this review. Future research should focus on improving standardization and reporting as well as establishing the importance of novel markers such as neuronal pentraxin-2 and whether such markers can predict longitudinal cognitive decline.

Mediterranean diet score is associated with greater allocentric processing in the EPAD LCS cohort: A comparative analysis by biogeographical region

Background: Adherence to the Mediterranean diet (MedDiet), a primarily plant-based eating pattern, has been associated with lower dementia incidence. Much of the research has focused on Alzheimer's disease (AD) dementia and mild cognitive impairment (MCI), with less research looking at the preclinical symptomatically silent stages that pre-empt MCI and AD dementia. Although there is evidence from studies conducted globally, no studies have compared the effects of the MedDiet within and outside of the Mediterranean region in one cohort. Methods: Our study explored cross-sectional and longitudinal associations between MedDiet and cognition in the pan-European EPAD LCS, comparing those living within and outside of the Mediterranean region (as classified by European Union biogeographical definitions). After deriving MEDAS scores to quantify adherence to the MedDiet, we used linear regression and linear mixed effects models to test for associations between the MEDAS score and cognitive function measured by the Four Mountains Test (FMT) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). We additionally calculated MEDAS continuous and PYRAMID scores to provide alternative measures of MedDiet adherence. Results: We included 1826 participants, mean age 65.69 (±7.42) years, majority female (56.2%) with family history (65.8%) and minority APOEε4 carriers (38.9%). Higher MEDAS scores were associated with better performance on the FMT both cross-sectionally (n = 1,144, ß: -0.11, SE: 0.04, p = 0.007) and longitudinally (slope: 0.10, 95% CI: 0.04-0.17, p: 0.002). The effect was marginally greater in the Mediterranean region in the cross-sectional analysis, with a stronger effect emerging longitudinally. In exploratory analyses, the association between MEDAS and FMT scores was only seen in female participants. A sensitivity analysis excluding Toulouse and Perugia, as cities near, but not within, the biogeographical region, found significant associations between higher MEDAS and MEDAS continuous scores, and a number of RBANS total and index scores. Conclusion: MedDiet adherence is associated with better FMT scores, with effects seen most strongly in the Mediterranean region from longitudinal data. Our sensitivity analysis suggested a more global cognitive benefit of MedDiet adherence. This study highlights the need to further explore for whom and for what brain health outcomes the MedDiet confers benefit. This evidence would identify a window of opportunity in the life-course to maximise the benefit and better inform public health campaigns and patient-level interventions.

Disease Modelling of Cognitive Outcomes and Biomarkers in the European Prevention of Alzheimer's Dementia Longitudinal Cohort

A key challenge for the secondary prevention of Alzheimer’s dementia is the need to identify individuals early on in the disease process through sensitive cognitive tests and biomarkers. The European Prevention of Alzheimer’s Dementia (EPAD) consortium recruited participants into a longitudinal cohort study with the aim of building a readiness cohort for a proof-of-concept clinical trial and also to generate a rich longitudinal data-set for disease modelling. Data have been collected on a wide range of measurements including cognitive outcomes, neuroimaging, cerebrospinal fluid biomarkers, genetics and other clinical and environmental risk factors, and are available for 1,828 eligible participants at baseline, 1,567 at 6 months, 1,188 at one-year follow-up, 383 at 2 years, and 89 participants at three-year follow-up visit. We novelly apply state-of-the-art longitudinal modelling and risk stratification approaches to these data in order to characterise disease progression and biological heterogeneity within the cohort. Specifically, we use longitudinal class-specific mixed effects models to characterise the different clinical disease trajectories and a semi-supervised Bayesian clustering approach to explore whether participants can be stratified into homogeneous subgroups that have different patterns of cognitive functioning evolution, while also having subgroup-specific profiles in terms of baseline biomarkers and longitudinal rate of change in biomarkers.

Virtual Cohorts and Synthetic Data in Dementia: An Illustration of Their Potential to Advance Research

When attempting to answer questions of interest, scientists often encounter hurdles that may stem from limited access to existing adequate datasets as a consequence of poor data sharing practices, constraining administrative practices. Further, when attempting to integrate data, differences in existing datasets also impose challenges that limit opportunities for data integration. As a result, the pace of scientific advancements is suboptimal. Synthetic data and virtual cohorts generated using innovative computational techniques represent an opportunity to overcome some of these limitations and consequently, to advance scientific developments. In this paper, we demonstrate the use of virtual cohorts techniques to generate a synthetic dataset that mirrors a deeply phenotyped sample of preclinical dementia research participants.

Management and Quality Control of Large Neuroimaging Datasets: Developments From the Barcelonaβeta Brain Research Center

Recent decades have witnessed an increasing number of large to very large imaging studies, prominently in the field of neurodegenerative diseases. The datasets collected during these studies form essential resources for the research aiming at new biomarkers. Collecting, hosting, managing, processing, or reviewing those datasets is typically achieved through a local neuroinformatics infrastructure. In particular for organizations with their own imaging equipment, setting up such a system is still a hard task, and relying on cloud-based solutions, albeit promising, is not always possible. This paper proposes a practical model guided by core principles including user involvement, lightweight footprint, modularity, reusability, and facilitated data sharing. This model is based on the experience from an 8-year-old research center managing cohort research programs on Alzheimer’s disease. Such a model gave rise to an ecosystem of tools aiming at improved quality control through seamless automatic processes combined with a variety of code libraries, command line tools, graphical user interfaces, and instant messaging applets. The present ecosystem was shaped around XNAT and is composed of independently reusable modules that are freely available on GitLab/GitHub. This paradigm is scalable to the general community of researchers working with large neuroimaging datasets.

Value-Generating Exploratory Trials in Neurodegenerative Dementias

Drug development for Alzheimer disease and other neurodegenerative dementias, including frontotemporal dementia, has experienced a long history of phase 2 and phase 3 clinical trials that failed to show efficacy of investigational drugs. Despite differences in clinical and behavioral characteristics, these disorders have shared pathologies and face common challenges in designing early-phase trials that are predictive of late-stage success. Here, we discuss exploratory clinical trials in neurodegenerative dementias. These are generally phase 1b or phase 2a trials that are designed to assess pharmacologic effects and rely on biomarker outcomes, with shorter treatment durations and fewer patients than traditional phase 2 studies. Exploratory trials can establish go/no-go decision points, support proof of concept and dose selection, and terminate drugs that fail to show target engagement with suitable exposure and acceptable safety profiles. Early failure saves valuable resources including opportunity costs. This is especially important for programs in academia and small biotechnology companies but may be applied to high-risk projects in large pharmaceutical companies to achieve proof of concept more rapidly at lower costs than traditional approaches. Exploratory studies in a staged clinical development program may provide promising data to warrant the substantial resources needed to advance compounds through late-stage development. To optimize the design and application of exploratory trials, the Alzheimer's Drug Discovery Foundation and the Association for Frontotemporal Degeneration convened an advisory panel to provide recommendations on outcome measures and statistical considerations for these types of studies and study designs that can improve efficiency in clinical development.

Platform Trials to Expedite Drug Development in Alzheimer's Disease: A Report from the EU/US CTAD Task Force

A diverse range of platforms has been established to increase the efficiency and speed of clinical trials for Alzheimer's disease (AD). These platforms enable parallel assessment of multiple therapeutics, treatment regimens, or participant groups; use uniform protocols and outcome measures; and may allow treatment arms to be added or dropped based on interim analyses of outcomes. The EU/US CTAD Task Force discussed the lessons learned from the Dominantly Inherited Alzheimer's Network Trials Unit (DIAN-TU) platform trial and the challenges addressed by other platform trials that have launched or are in the planning stages. The landscape of clinical trial platforms in the AD space includes those testing experimental therapies such as DIAN-TU, platforms designed to test multidomain interventions, and those designed to streamline trial recruitment by building trial-ready cohorts. The heterogeneity of the AD patient population, AD drugs, treatment regimens, and analytical methods complicates the design and execution of platform trials, yet Task Force members concluded that platform trials are essential to advance the search for effective AD treatments, including combination therapies.

Prediction of Alzheimer's disease biomarker status defined by the 'ATN framework' among cognitively healthy individuals: results from the EPAD longitudinal cohort study

BACKGROUND

The Amyloid/Tau/Neurodegeneration (ATN) framework has been proposed as a means of evidencing the biological state of Alzheimer's disease (AD). Predicting ATN status in pre-dementia individuals therefore provides an important opportunity for targeted recruitment into AD interventional studies. We investigated the extent to which ATN-defined biomarker status can be predicted by known AD risk factors as well as vascular-related composite risk scores.

METHODS

One thousand ten cognitively healthy older adults were allocated to one of five ATN-defined biomarker categories. Multinomial logistic regression tested risk factors including age, sex, education, APOE4, family history of dementia, cognitive function, vascular risk indices (high systolic blood pressure, body mass index (BMI), high cholesterol, physical inactivity, ever smoked, blood pressure medication, diabetes, prior cardiovascular disease, atrial fibrillation and white matter lesion (WML) volume), and three vascular-related composite scores, to predict five ATN subgroups; ROC curve models estimated their added value in predicting pathology.

RESULTS

Age, APOE4, family history, BMI, MMSE and white matter lesions (WML) volume differed between ATN biomarker groups. Prediction of Alzheimer's disease pathology (versus normal AD biomarkers) improved by 7% after adding family history, BMI, MMSE and WML to a ROC curve that included age, sex and APOE4. Risk composite scores did not add value.

CONCLUSIONS

ATN-defined Alzheimer's disease biomarker status prediction among cognitively healthy individuals is possible through a combination of constitutional and cardiovascular risk factors but established dementia composite risk scores do not appear to add value in this context.

Viewpoint: Impact of the Covid-19 Outbreak on the Clinical and Research Activities of Memory Clinics: An Alzheimer's Disease Center Facing the Covid-19 Crisis

The 2020 Coronavirus pandemic is the greatest global health crisis we have had in recent decades, both by its own consequences and by the impact of the measures that have been taken by various countries to deal with it (1). The effect is major on Western health systems, affecting all areas of care and research, including research on Alzheimer’s disease and cognitive aging.

Involving research participants in a pan-European research initiative: the EPAD participant panel experience

BACKGROUND

Including participants in patient and public involvement activities is increasingly acknowledged as a key pillar of successful research activity. Such activities can influence recruitment and retention, as well as researcher experience and contribute to decision making in research studies. However, there are few established methodologies of how to set up and manage participant involvement activities. Further, there is little discussion of how to do so when dealing with collaborative projects that run across countries and operate in multiple linguistic and regulatory contexts.

METHODS

In this paper we describe the set-up, running and experiences of the EPAD participant panel. The EPAD study was a pan-European cohort study with the aim to understand risks for developing Alzheimer's disease and build a readiness cohort for Phase 2 clinical trials. Due to the longitudinal nature of this study, combined with the enrolment of healthy volunteers and those with mild cognitive impairments, the EPAD team highlighted participant involvement as crucial to the success of this project. The EPAD project employed a nested model, with local panels meeting in England, France, Scotland, Spain and The Netherlands, and feeding into a central study panel. The local panels were governed by terms of reference which were adaptable to local needs.

RESULTS

The impact of the panels has been widespread, and varies from feedback on documentation, to supporting with design of media materials and representation of the project at national and international meetings.

CONCLUSIONS

The EPAD panels have contributed to the success of the project and the model established is easily transferable to other disease areas investigating healthy or at-risk populations.

Associations Between Multimorbidity and Cerebrospinal Fluid Amyloid: A Cross-Sectional Analysis of the European Prevention of Alzheimer's Dementia (EPAD) V500.0 Cohort

BACKGROUND

Multimorbidity (the co-occurrence of multiple chronic conditions) is increasingly common, especially among people with dementia. Few neuroimaging studies have explored amyloid biomarkers in people with multimorbidity.

OBJECTIVE

We aimed to conduct the first study of the association between multimorbidity and cerebrospinal fluid amyloid-β42 (CSF Aβ).

METHOD

The European Prevention of Alzheimer's Dementia (EPAD) Longitudinal Cohort Study V500.0 dataset includes volunteers aged ≥50 years from 12 sites. Participants undergo detailed phenotyping, including CSF measures and a self-reported medical history. Using logistic and linear regression analyses, we explored the association between multimorbidity and continuous chronic condition count with CSF Aβ positivity (Aβ42 <1000pg/ml) and continuous CSF Aβ concentration. All models were adjusted for age, sex, APOE status, education, and family history of dementia.

RESULTS

Among 447 eligible participants without dementia, the mean (SD) age was 66.6 (6.6) years, 234 (52.3%) were women, and 157 (35.1%) were amyloid positive. With chronic conditions regarded as pseudo-continuous, each additional condition carried a decreased likelihood of amyloid positivity (OR = 0.82, 95% CI: 0.68-0.97; p = 0.026). With CSF Aβ as a continuous variable, each additional condition was associated with an increase of 54.2 pg/ml (95% CI: 9.9-98.5, p = 0.017). Having ≥2 conditions was inversely associated with amyloid positivity (OR 0.59, 95% CI: 0.37-0.95, p = 0.030) compared to one or none.

CONCLUSION

Our findings suggest that the established association between multimorbidity and dementia may be due to a pathway other than amyloid. However, this cross-sectional study does not allow us to make causal inferences. Longitudinal work is required to confirm the inverse association found.