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Cognitive Functions as Predictors of Alzheimer’s Disease
Biomarker Status in the European Prevention of Alzheimer’s
Dementia Cohort

“Cross-sectional and longitudinal association of sleep and Alzheimer biomarkers in cognitively unimpaired adults”

Authors: Jonathan Blackman, Laura Stankeviciute, Eider M Arenaza-Urquijo, Marc Suárez-Calvet, Gonzalo Sánchez-Benavides, Natalia Vilor-Tejedor, Alejandro Iranzo, José Luis Molinuevo, Juan Domingo Gispert, Elizabeth Coulthard, Oriol Grau-Rivera, for the European Prevention of Alzheimer’s Disease (EPAD) Consortium

Abstract:

Sleep abnormalities are prevalent in Alzheimer’s disease, with sleep quality already impaired at its preclinical stage. Epidemiological and experimental data point to sleep abnormalities contributing to the risk of Alzheimer’s disease. However, previous studies are limited by either a lack of Alzheimer’s disease biomarkers, reduced sample size or cross-sectional design. Understanding if, when, and how poor sleep contributes to Alzheimer’s disease progression is important so that therapies can be targeted to the right phase of the disease. Using the largest cohort to date, the European Prevention of Alzheimer’s Dementia Longitudinal Cohort Study, we test the hypotheses that poor sleep is associated with core Alzheimer’s disease CSF biomarkers cross-sectionally and predicts future increments of Alzheimer’s disease pathology in people without identifiable symptoms of Alzheimer’s disease at baseline. This study included 1168 adults aged over 50 years with CSF core Alzheimer’s disease biomarkers (total tau, phosphorylated tau and amyloid-beta), cognitive performance, and sleep quality (Pittsburgh sleep quality index questionnaire) data. We used multivariate linear regressions to analyse associations between core Alzheimer’s disease biomarkers and the following Pittsburgh sleep quality index measures: total score of sleep quality, binarized score (poor sleep categorized as Pittsburgh sleep quality index > 5), sleep latency, duration, efficiency and disturbance. On a subsample of 332 participants with CSF taken at baseline and after an average period of 1.5 years, we assessed the effect of baseline sleep quality on change in Alzheimer’s disease biomarkers over time. Cross-sectional analyses revealed that poor sleep quality (Pittsburgh sleep quality index total > 5) was significantly associated with higher CSF t-tau; shorter sleep duration (<7 h) was associated with higher CSF p-tau and t-tau; and a higher degree of sleep disturbance (1-9 versus 0 and >9 versus 0) was associated with lower CSF amyloid-beta. Longitudinal analyses showed that greater sleep disturbances (1-9 versus 0 and >9 versus 0) were associated with a decrease in CSF Aβ42 over time. This study demonstrates that self-reported poor sleep quality is associated with greater Alzheimer’s disease-related pathology in cognitively unimpaired individuals, with longitudinal results further strengthening the hypothesis that disrupted sleep may represent a risk factor for Alzheimer’s disease. This highlights the need for future work to test the efficacy of preventive practices, designed to improve sleep at pre-symptomatic stages of disease, on reducing Alzheimer’s disease pathology.

DOI: 10.1093/braincomms/fcac257

Published online: 3 November 2022 in the Journal Brain communications

“Data-Driven Thresholding Statistically Biases ATN Profiling across Cohort Datasets”

Authors: Y. Salimi, D. Domingo-Fernández, M. Hofmann-Apitius, C. Birkenbihl, the Alzheimer’s Disease Neuroimaging Initiative, the Japanese Alzheimer’s Disease Neuroimaging Initiative, the Alzheimer’s Disease Repository Without Borders Investigators & the European Prevention of Alzheimer’s Disease (EPAD) Consortium

Abstract:

Background: While the amyloid/tau/neurodegeneration (ATN) framework has found wide application in Alzheimer’s disease research, it is unclear if thresholds obtained using distinct thresholding methods are concordant within the same dataset and interchangeable across cohorts.

Objectives: To investigate the robustness of data-driven thresholding methods and ATN profiling across cohort datasets.

Design and Setting: We evaluated the impact of thresholding methods on ATN profiles by applying five commonly-used methodologies across cohort datasets. We assessed the generalizability of disease patterns discovered within ATN profiles by clustering individuals from different cohorts who were assigned to the same ATN profile.

Participants and Measurements: Participants with available CSF amyloid-β 1–42, phosphorylated tau, and total tau measurements were included from eleven AD cohort studies.

Results: We observed high variability among obtained ATN thresholds, both across methods and datasets that impacted the resulting profile assignments of participants significantly. Clustering participants from different cohorts within the same ATN category indicated that identified disease patterns were comparable across most cohorts and biases introduced through distinct thresholding and data representations remained insignificant in most ATN profiles.

Conclusion: Thresholding method selection is a decision of statistical relevance that will inevitably bias the resulting profiling and affect its sensitivity and specificity. Thresholds are likely not directly interchangeable between independent cohorts. To apply the ATN framework as an actionable and robust profiling scheme, a comprehensive understanding of the impact of used thresholding methods, their statistical implications, and a validation of results is crucial.

DOI: https://doi.org/10.14283/jpad.2023.100

Published online: 6 September 2023 in the Journal of Prevention of Alzheimer’s Disease

Detecting cognitive changes in preclinical Alzheimer’s disease:
A review of its feasibility

Development of interventions for the secondaryprevention of Alzheimer’s dementia: the EuropeanPrevention of Alzheimer’s Dementia (EPAD) project

Disease modelling of cognitive outcomes and biomarkers in
the European Prevention of Alzheimer’s Dementia
Longitudinal Cohort

“Eigenvector centrality dynamics are related to Alzheimer’s disease pathological changes in non-demented individuals”

Authors: Luigi Lorenzini, Silvia Ingala, Lyduine E Collij, Viktor Wottschel, Sven Haller, Kaj Blennow, Giovanni Frisoni, Gaël Chételat, Pierre Payoux, Pablo Lage-Martinez, Michael Ewers, Adam Waldman, Joanna Wardlaw, Craig Ritchie, Juan Domingo Gispert, Henk J M M Mutsaerts, Pieter Jelle Visser, Philip Scheltens, Betty Tijms, Frederik Barkhof, Alle Meije Wink

Abstract:

Amyloid-β accumulation starts in highly connected brain regions and is associated with functional connectivity alterations in the early stages of Alzheimer’s disease. This regional vulnerability is related to the high neuronal activity and strong fluctuations typical of these regions. Recently, dynamic functional connectivity was introduced to investigate changes in functional network organization over time. High dynamic functional connectivity variations indicate increased regional flexibility to participate in multiple subnetworks, promoting functional integration. Currently, only a limited number of studies have explored the temporal dynamics of functional connectivity in the pre-dementia stages of Alzheimer’s disease. We study the associations between abnormal cerebrospinal fluid amyloid and both static and dynamic properties of functional hubs, using eigenvector centrality, and their relationship with cognitive performance, in 701 non-demented participants from the European Prevention of Alzheimer’s Dementia cohort. Voxel-wise eigenvector centrality was computed for the whole functional magnetic resonance imaging time series (static), and within a sliding window (dynamic). Differences in static eigenvector centrality between amyloid positive (A+) and negative (A-) participants and amyloid-tau groups were found in a general linear model. Dynamic eigenvector centrality standard deviation and range were compared between groups within clusters of significant static eigenvector centrality differences, and within 10 canonical resting-state networks. The effect of the interaction between amyloid status and cognitive performance on dynamic eigenvector centrality variability was also evaluated with linear models. Models were corrected for age, sex, and education level. Lower static centrality was found in A+ participants in posterior brain areas including a parietal and an occipital cluster; higher static centrality was found in a medio-frontal cluster. Lower eigenvector centrality variability (standard deviation) occurred in A+ participants in the frontal cluster. The default mode network and the dorsal visual networks of A+ participants had lower dynamic eigenvector centrality variability. Centrality variability in the default mode network and dorsal visual networks were associated with cognitive performance in the A- and A+ groups, with lower variability being observed in A+ participants with good cognitive scores. Our results support the role and timing of eigenvector centrality alterations in very early stages of Alzheimer’s disease and show that centrality variability over time adds relevant information on the dynamic patterns that cause static eigenvector centrality alterations. We propose that dynamic eigenvector centrality is an early biomarker of the interplay between early Alzheimer’s disease pathology and cognitive decline.

DOI: https://doi.org/10.1093/braincomms/fcad088

Published online: 28 March 2023 in the Journal Brain Communications

Ethical Arguments Concerning the Use of Alzheimer’s Disease
Biomarkers in Individuals with No or Mild Cognitive
Impairment: A Systematic Review and Framework for
Discussion

Ethical challenges in preclinical Alzheimer’s disease
observational studies and trials: Results of the
Barcelona summit

“Ethical Frameworks for Disclosure of Alzheimer Disease Biomarkers to Research Participants: Conflicting Norms and a Nuanced Policy”

Authors: Eline M. Bunnik, Marthe Smedinga, Richard Milne, Jean Georges, Edo Richard, Maartje H. N. Schermer

Abstract: More and more frequently, clinical trials for Alzheimer disease (AD) are targeting cognitively unimpaired individuals who are at increased risk of developing the disease. It is not always clear whether AD biomarker information should be disclosed to research participants: on the one hand, research participants may be interested in learning this information because of its perceived utility, but on the other hand, learning this information may be harmful, as there are very few effective preventive or therapeutic options available for AD. In this article, we bring together three separate sets of ethical guidance literature: on the return of individual research results, on an individual’s right to access personal data, and on transparent enrollment into clinical trials. Based on these literatures, we suggest policies for the disclosure of AD biomarker test results in longitudinal observational cohort studies, clinical trials, and hybrid research projects, such as the European Prevention of Alzheimer’s Dementia (EPAD) project, in which we served as an ethics team. We also present and critically discuss recommendations for disclosure of AD biomarkers in practice. We underscore that, as long as the clinical validity of AD biomarkers remains limited, there are good reasons to avoid actively disclosing them to cognitively unimpaired research participants.

DOI: 10.1002/eahr.500146

Published online: 31 October 2022 in the Journal Ethics & Human Research