Category: Publications

The influence of diversity on the measurement of functional
impairment: An international validation of the Amsterdam
IADL Questionnaire in eight countries

“The Open-Access European Prevention of Alzheimer’s Dementia (EPAD) MRI dataset and processing workflow”

Authors: Luigi Lorenzini,Silvia Ingala, Alle Meije Wink, Joost P.A. Kuijer, Viktor Wottschel, Mathijs Dijsselhof, Carole H. Sudre, Sven Haller, Jose Luis Molinuevo, Juan Domingo Gispert, David M. Cash, David L. Thomas, Sjoerd B. Vos, Ferran Prados, Jan Petr, Robin Wolz, Alessandro Palombit, Adam J. Schwarz Gael Chetelat, Pierre Payoux, Carol Di Perri, Joanna M. Wardlaw, Giovanni B. Frisoni, Christopher Foley, Nick C. Fox, Craig Ritchie, Cyril Pernet, Adam Waldman, Frederik Barkhof, Henk J.M.M. Mutsaerts

Abstract:

The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer’s Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences. Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI preprocessing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features – i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia. The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features – Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER), and Image Quality Rate (IQR) – were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses.

DOI: 10.1016/j.nicl.2022.103106

Published online: 7 July 2022 in the Journal NeuroImage: Clinical

The Rationale Behind the New Alzheimer’s Disease
Conceptualization: Lessons Learned During the Last
Decades

The relation between APOE genotype and cerebral
microbleeds in cognitively unimpaired middle- and old-aged
individuals

“Using LC-MS/MS to Determine Salivary Steroid Reference Intervals in a European Older Adult Population”

Authors: Sarah Gregory, Scott G Denham, Patricia Lee, Joanna P Simpson, Natalie Z M Homer

Abstract:

A number of steroids, including glucocorticoids and sex hormones, have been associated with neurodegenerative and cardiovascular conditions common in aging populations. The application of liquid chromatography tandem mass spectrometry (LC-MS/MS) steroid analysis offers an opportunity to conduct simultaneous multiplex steroid analysis within a given sample. In this paper, we describe the application of an LC-MS/MS steroid analysis method for the assessment of reference ranges of steroids in human saliva samples (200 µL) collected from older adults (age 50 years and above) enrolled in a European cohort investigating the risk for Alzheimer’s dementia. Saliva samples were prepared using supported liquid extraction (SLE) along with a calibration curve and analysed using a Waters I-Class UPLC (Ultra Performance Liquid Chromatography) and a Sciex QTrap 6500+ mass spectrometer. Mass spectrometry parameters of steroids were optimised for each steroid and a method for the chromatographic separation of 19 steroids was developed. Lower limits of quantitation (LLOQs), linearity and other method criteria were assessed. In total, data from 125 participants (500 samples) were analysed and assessed for reference ranges (64 male, 61 female). A total of 19 steroids were detected in saliva within the range of the method. There were clear diurnal patterns in most of the steroid hormones detected. Sex differences were observed for androstenedione (A4), testosterone (T), cortisone (E) and aldosterone (Aldo). In the first sample of the day, dehydroepiandrosterone (DHEA) was significantly higher in healthy volunteers compared to those with Alzheimer’s disease biomarkers. This LC-MS/MS method is suitable for the analysis of 19 steroids in saliva in adults.

DOI: https://doi.org/10.3390/metabo13020265

Published online: 13 February 2023 in the Journal Metabolites

“Ready for What” Timing and Speculation in Alzheimer’sDisease Drug Development

“Facilitating clinical use of the Amsterdam Instrumental Activities of Daily Living Questionnaire: Normative data and a diagnostic cutoff value”

Authors: Merel C. Postema, Mark A. Dubbelman, Jürgen Claesen, Craig Ritchie, Merike Verrijp, Leonie Visser, Pieter-Jelle Visser, Marissa D. Zwan, Wiesje M. van der Flier and Sietske A.M. Sikkes

Abstract:

Objective:The Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q) is well validated and commonly used to assess difficulties in everyday functioning regarding dementia. To facilitate interpretation and clinical implementation across different European countries, we aim to provide normative data and a diagnostic cutoff for dementia.

Methods: Cross-sectional data from Dutch Brain Research Registry (N = 1,064; mean (M) age = 62 ± 11 year; 69.5% female), European Medial Information Framework-Alzheimer’s Disease 90 + (N = 63; Mage = 92 ± 2 year; 52.4% female), and European Prevention of Alzheimer’s Dementia Longitudinal Cohort Study (N = 247; Mage = 63 ± 7 year; 72.1% female) were used. The generalized additive models for location, scale, and shape framework were used to obtain normative values (Z-scores). The beta distribution was applied, and combinations of age, sex, and educational attainment were modeled. The optimal cutoff for dementia was calculated using area under receiver operating curves (AUC-ROC) and Youden Index, using data from Amsterdam Dementia Cohort (N = 2,511, Mage = 64 ± 8 year, 44.4% female).

Results: The best normative model accounted for a cubic-like decrease of IADL performance with age that was more pronounced in low compared to medium/high educational attainment. The cutoff for dementia was 1.85 standard deviation below the population mean (AUC = 0.97; 95% CI [0.97–0.98]).

Conclusion:We provide regression-based norms for A-IADL-Q and a diagnostic cutoff for dementia, which help improve clinical assessment of IADL performance across European countries.

DOI: https://doi.org/10.1017/S1355617724000031

Published online: 8 March 2024 in the Journal of the International Neuropsychological Society

“Validation of the brain health index in the European Prevention of Alzheimer’s Dementia cohort”

Authors: Jodi K. Watt, David Alexander Dickie, Frederick K. Ho, Donald M. Lyall, Jesse Dawson, Terence J. Quinn, European Prevention of Alzheimer’s Disease (EPAD) Consortium

Abstract:

Background: Brain Health Index (BHI) assimilates various MRI sequences, giving a quantitative measure of brain health. To date, BHI validation has been cross-sectional and limited to selected populations. Further large-scale validation and assessment of temporal change is required to understand its clinical utility.

Aim: Assess 1) relationships between variables associated with cognitive decline and BHI 2) associations between BHI and measures of cognition and 3) longitudinal changes in BHI and relationship with cognitive function.

Methods: BHI computation involved Gaussian mixture-model cluster analysis of T1, T2, T2*, and T2 FLAIR MRI data from participants within the European Prevention of Alzheimer’s Dementia (EPAD) cohort. Group differences (gender- and health-based) were evaluated using independent samples Welch’s t-tests. Relationships between BHI, age and cognitive tests used linear regression. Longitudinal analysis (12/24 months) utilised mixed linear regression models to examine BHI changes, and paired BHI/cognition associations.

Results: Data from N = 1496 predominantly Caucasian participants (50–88 years old, 43.32% male) were used. BHI scores were lower in those with diabetes (p < 0.001, d = 0.419), hypertension (p < 0.001, d = 0.375), hypercholesterolemia (p < 0.001, d = 0.193) and stroke (p < 0.05, d = 0.512). APOE was not significantly related to BHI scores. After correction for age, cross-sectional BHI scores were significantly associated with all measures of cognitive function in males, but only the Four Mountains Test (4MT) in females. Longitudinal change in BHI and cognition were not consistently related.

Conclusions: BHI is a valid marker of cognitive decline and relatively stable over 1-2 year follow-up periods. Further work should assess temporal changes over a longer duration and determine relationships between BHI and cognition in more diverse populations.

DOI: https://doi.org/10.1016/j.cccb.2024.100214

Published online: 5 April 2024 in the Journal Cerebral Circulation – Cognition and Behavior

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

Authors: Eddy Roccati, Aidan David Bindoff, Jessica Marie Collins, Joshua Eastgate, Jay Borchard, Jane Alty, Anna Elizabeth King, James Clement Vickers, Margherita Carboni, Chad Logan, EPAD Consortium

Abstract:

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.

DOI: https://doi.org/10.3389/fnagi.2024.1346214

Published online: 7 February 2024 in the Journal Frontiers in Aging Neuroscience