TY - JOUR
T1 - Visualizing modules of coordinated structural brain atrophy during the course of conversion to Alzheimer's disease by applying methodology from gene co-expression analysis
AU - Sato, Kenichiro
AU - Mano, Tatsuo
AU - Matsuda, Hiroshi
AU - Senda, Michio
AU - Ihara, Ryoko
AU - Suzuki, Kazushi
AU - Arai, Hiroyuki
AU - Ishii, Kenji
AU - Ito, Kengo
AU - Ikeuchi, Takeshi
AU - Kuwano, Ryozo
AU - Toda, Tatsushi
AU - Iwatsubo, Takeshi
AU - Iwata, Atsushi
N1 - Funding Information:
This research was supported by AMED under Grant Numbers: 16dk0207020h, 16dk0207028h, 19dk0207048h0001 and Japan Society for the Promotion of Science grant 17K09794 .
Publisher Copyright:
© 2019 The Authors
PY - 2019
Y1 - 2019
N2 - Objective: We aimed to identify modularized structural atrophy of brain regions with a high degree of connectivity and its longitudinal changes associated with the progression of Alzheimer's disease (AD) using weighted gene co-expression network analysis (WGCNA), which is an unsupervised hierarchical clustering method originally used in genetic analysis. Methods: We included participants with late mild cognitive impairment (MCI) at baseline from the Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) study. We imputed normalized and Z-transformed structural volume or cortical thickness data of 164 parcellated brain regions/structures based on the calculations of the FreeSurfer software. We applied the WGCNA to extract modules with highly interconnected structural atrophic patterns and examined the correlation between the identified modules and clinical AD progression. Results: We included 204 participants from the baseline dataset, and performed a follow-up with 100 in the 36-month dataset of MCI cohort participants from the J-ADNI. In the univariate correlation or variable importance analysis, baseline atrophy in temporal lobe regions/structures significantly predicted clinical AD progression. In the WGCNA consensus analysis, co-atrophy modules associated with MCI conversion were first distributed in the temporal lobe and subsequently extended to adjacent parietal cortical regions in the following 36 months. Conclusions: We identified coordinated modules of brain atrophy and demonstrated their longitudinal extension along with the clinical course of AD progression using WGCNA, which showed a good correspondence with previous pathological studies of the tau propagation theory. Our results suggest the potential applicability of this methodology, originating from genetic analyses, for the surrogate visualization of the underlying pathological progression in neurodegenerative diseases not limited to AD.
AB - Objective: We aimed to identify modularized structural atrophy of brain regions with a high degree of connectivity and its longitudinal changes associated with the progression of Alzheimer's disease (AD) using weighted gene co-expression network analysis (WGCNA), which is an unsupervised hierarchical clustering method originally used in genetic analysis. Methods: We included participants with late mild cognitive impairment (MCI) at baseline from the Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) study. We imputed normalized and Z-transformed structural volume or cortical thickness data of 164 parcellated brain regions/structures based on the calculations of the FreeSurfer software. We applied the WGCNA to extract modules with highly interconnected structural atrophic patterns and examined the correlation between the identified modules and clinical AD progression. Results: We included 204 participants from the baseline dataset, and performed a follow-up with 100 in the 36-month dataset of MCI cohort participants from the J-ADNI. In the univariate correlation or variable importance analysis, baseline atrophy in temporal lobe regions/structures significantly predicted clinical AD progression. In the WGCNA consensus analysis, co-atrophy modules associated with MCI conversion were first distributed in the temporal lobe and subsequently extended to adjacent parietal cortical regions in the following 36 months. Conclusions: We identified coordinated modules of brain atrophy and demonstrated their longitudinal extension along with the clinical course of AD progression using WGCNA, which showed a good correspondence with previous pathological studies of the tau propagation theory. Our results suggest the potential applicability of this methodology, originating from genetic analyses, for the surrogate visualization of the underlying pathological progression in neurodegenerative diseases not limited to AD.
KW - Alzheimer's disease module
KW - Brain atrophy
KW - Connectivity
KW - Hierarchical clustering
KW - Mild cognitive impairment
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U2 - 10.1016/j.nicl.2019.101957
DO - 10.1016/j.nicl.2019.101957
M3 - Article
C2 - 31400633
AN - SCOPUS:85070214499
VL - 24
JO - NeuroImage: Clinical
JF - NeuroImage: Clinical
SN - 2213-1582
M1 - 101957
ER -