Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.neuroimage.2019.116043
Title: Multi-modal latent factor exploration of atrophy, cognitive and tau heterogeneity in Alzheimer's disease
Authors: Sun, Nanbo
Mormino, Elizabeth C
Chen, Jianzhong 
Sabuncu, Mert R
Yeo, BT Thomas 
Keywords: Science & Technology
Life Sciences & Biomedicine
Neurosciences
Neuroimaging
Radiology, Nuclear Medicine & Medical Imaging
Neurosciences & Neurology
Bayesian model
Canonical correlation analysis
Executive function
Language
Typical late-onset Alzheimer's disease
SURFACE-BASED ANALYSIS
FUNCTIONAL ARCHITECTURE
GEOMETRICALLY ACCURATE
CONNECTIVITY NETWORKS
HYPOTHETICAL MODEL
DEFINED SUBTYPES
COMPOSITE SCORE
SPATIAL MAP
PET
ASSOCIATION
Issue Date: 1-Nov-2019
Publisher: ACADEMIC PRESS INC ELSEVIER SCIENCE
Citation: Sun, Nanbo, Mormino, Elizabeth C, Chen, Jianzhong, Sabuncu, Mert R, Yeo, BT Thomas (2019-11-01). Multi-modal latent factor exploration of atrophy, cognitive and tau heterogeneity in Alzheimer's disease. NEUROIMAGE 201. ScholarBank@NUS Repository. https://doi.org/10.1016/j.neuroimage.2019.116043
Abstract: © 2019 Elsevier Inc. Individuals with Alzheimer's disease (AD) dementia exhibit significant heterogeneity across clinical symptoms, atrophy patterns, and spatial distribution of Tau deposition. Most previous studies of AD heterogeneity have focused on atypical clinical subtypes, defined subtypes with a single modality, or restricted their analyses to a priori brain regions and cognitive tests. Here, we considered a data-driven hierarchical Bayesian model to identify latent factors from atrophy patterns and cognitive deficits simultaneously, thus exploiting the rich dimensionality within each modality. Unlike most previous studies, our model allows each factor to be expressed to varying degrees within an individual, in order to reflect potential multiple co-existing pathologies. By applying our model to ADNI-GO/2 AD dementia participants, we found three atrophy-cognitive factors. The first factor was associated with medial temporal lobe atrophy, episodic memory deficits and disorientation to time/place (“MTL-Memory”). The second factor was associated with lateral temporal atrophy and language deficits (“Lateral Temporal-Language”). The third factor was associated with atrophy in posterior bilateral cortex, and visuospatial executive function deficits (“Posterior Cortical-Executive”). While the MTL-Memory and Posterior Cortical-Executive factors were discussed in previous literature, the Lateral Temporal-Language factor is novel and emerged only by considering atrophy and cognition jointly. Several analyses were performed to ensure generalizability, replicability and stability of the estimated factors. First, the factors generalized to new participants within a 10-fold cross-validation of ADNI-GO/2 AD dementia participants. Second, the factors were replicated in an independent ADNI-1 AD dementia cohort. Third, factor loadings of ADNI-GO/2 AD dementia participants were longitudinally stable, suggesting that these factors capture heterogeneity across patients, rather than longitudinal disease progression. Fourth, the model outperformed canonical correlation analysis at capturing associations between atrophy patterns and cognitive deficits. To explore the influence of the factors early in the disease process, factor loadings were estimated in ADNI-GO/2 mild cognitively impaired (MCI) participants. Although the associations between the atrophy patterns and cognitive profiles were weak in MCI compared to AD, we found that factor loadings were associated with inter-individual regional variation in Tau uptake. Taken together, these results suggest that distinct atrophy-cognitive patterns exist in typical Alzheimer's disease, and are associated with distinct patterns of Tau depositions before clinical dementia emerges.
Source Title: NEUROIMAGE
URI: https://scholarbank.nus.edu.sg/handle/10635/167722
ISSN: 10538119
10959572
DOI: 10.1016/j.neuroimage.2019.116043
Appears in Collections:Staff Publications
Elements

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Sun_Main_190621.pdf1.86 MBAdobe PDF

OPEN

Post-printView/Download

SCOPUSTM   
Citations

17
checked on May 13, 2022

WEB OF SCIENCETM
Citations

9
checked on Oct 7, 2021

Page view(s)

204
checked on May 12, 2022

Download(s)

3
checked on May 12, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.