Atrophy Progression in People With a Family History of Alzheimer's disease is Shaped by Connectivity
Poster No:
1135
Submission Type:
Abstract Submission
Authors:
Christina Tremblay1,2, Shady Rahayel2, Alexandre Pastor-Bernier1, Frédéric St-Onge3, Andrew Vo1, François Rheault4, Véronique Daneault2, Filip Morys1, Natasha Rajah3, Sylvia Villeneuve3, Alain Dagher1, PREVENT-AD Research Group3
Institutions:
1Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada, 2Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Canada, 3Brain Imaging Centre, Douglas Institute Research Centre, Montreal, Canada, 4Université de Sherbrooke, Sherbrooke, Canada
First Author:
Christina Tremblay
Montreal Neurological Institute and Hospital, McGill University|Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal
Montreal, Canada|Montreal, Canada
Montreal Neurological Institute and Hospital, McGill University|Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal
Montreal, Canada|Montreal, Canada
Co-Author(s):
Shady Rahayel
Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal
Montreal, Canada
Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal
Montreal, Canada
Alexandre Pastor-Bernier
Montreal Neurological Institute and Hospital, McGill University
Montreal, Canada
Montreal Neurological Institute and Hospital, McGill University
Montreal, Canada
Véronique Daneault
Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal
Montreal, Canada
Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal
Montreal, Canada
Introduction:
Alzheimer's disease (AD) includes a long period of presymptomatic brain changes. Different risk factors are associated with AD development, including having a family history of AD (FHAD). The Braak model suggests that tau pathology in synergy with beta-amyloid (Aβ) spreads along structural connections in AD eventually leading to atrophy (Braak & Braak, 1991). However, the pattern of atrophy progression in people with a FHAD in addition to the influence of brain structural connectivity on proteins propagation and atrophy progression remain unclear. Here we used structural MRI from three databases (ADNI (Jack et al, 2008), PREVENT-AD (Breitner et al, 2016) and Montreal Adult Lifespan Study (Elshiekh et al., 2020)) to map the atrophy progression in FHAD and AD, and build group-specific connectomes.
Methods:
Longitudinal data up to 4 years enabled us to perform atrophy progression analysis in FHAD and AD compared to controls. Tau and Aβ protein distribution were quantified using [18F]AV-1451 and [18F]NAV4694 positron emission tomography processed with a standard pipeline (github.com/villeneuvelab/vlpp). Group-specific structural connectivity matrices were created using Tractoflow-ABS (Theaud et al, 2020) and Connectoflow pipelines (Rheault et al, 2021). A structural connectivity matrix from healthy adults (undamaged) was also used (Misic et al, 2015). We first derived atrophy progression maps using deformation-based morphometry (ANTs longitudinal pipeline) from three groups with similar age, education and male/female proportion at baseline (controls: N=116, FHAD: N=153, AD: N=156). The atrophy progression (group-by-age interaction) was compared between the three groups with linear mixed models (FDR corrected) controlling for sex, education, body mass index, APOe4 genotype and APOe4 interaction with age. The Cammoun atlas (448 cortical regions) was used for brain parcellation and to build the group-specific connectivity matrices (Cammoun et al., 2012). The ComBat method was applied to harmonize the multi-center imaging data (Johnson et al, 2007). For the structural connectivity analysis, Pearson's correlations with the structurally connected neighborhood regions were computed and tested against spatial null models using BrainSMASH (Burt et al., 2020).
Results:
We found similar patterns of atrophy progression in FHAD and AD, notably in the cingulate cortex, temporal, and parietal lobes (Fig.1). The extent was more widespread and severe in AD. Several regions also showed less atrophy progression (-ß) in AD (mostly in the temporal and frontal lobe), suggesting a ceiling effect. Analyses of structural connectivity indicated that the atrophy pattern and its progression were associated with existing structural connectivity in FHAD (atrophy progression: r=0.31, p-valuespin=0.03; atrophy at Bl: r=0.26, p-valuespin=0.04) (Fig.2A). In AD, only the atrophy at baseline was significantly correlated with that of structurally connected neighbors (atrophy progression: r=0.11, p-valuespin=0.26; atrophy at Bl: r=0.50, p-valuespin=0.001). Tau and Aβ protein concentration were also higher in structurally connected regions in FHAD and AD. However, when using an undamaged connectome from healthy adults (Fig.2B bottom row), an association was found with the atrophy progression in the structurally connected regions in both FHAD and AD. These results suggests that atrophy in AD continues to propagate along pre-existing connections despite current damage while, in FHAD, structural connectivity is not significantly impaired.
Conclusions:
Supporting the Braak model, in FHAD and AD, our findings showed that structural connectivity influenced the baseline distribution of tau, Aβ and atrophy. These findings also underscore the critical role of structural connectivity in the distribution of pathological markers and atrophy progression in both FHAD and AD.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s)
Lifespan Development:
Aging 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Novel Imaging Acquisition Methods:
Anatomical MRI
Diffusion MRI
Keywords:
Aging
MRI
STRUCTURAL MRI
Tractography
Other - Alzheimer's disease
1|2Indicates the priority used for review
Provide references using author date format
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