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Assessing cognitive impairment and disability in older adults through the lens of whole brain white matter patterns

Authors
Roh, HW  | Chauhan, N | Seo, SW | Choi, SH | Kim, EJ | Cho, SH | Kim, BC | Choi, JW  | An, YS  | Park, B  | Lee, SM  | Moon, SY  | Nam, YJ  | Hong, S  | Son, SJ  | Hong, CH  | Lee, D
Citation
Alzheimer's & dementia, 20(9). : 6032-6044, 2024
Journal Title
Alzheimer's & dementia
ISSN
1552-52601552-5279
Abstract
INTRODUCTION: This study aimed to explore the potential of whole brain white matter patterns as novel neuroimaging biomarkers for assessing cognitive impairment and disability in older adults. METHODS: We conducted an in-depth analysis of magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) scans in 454 participants, focusing on white matter patterns and white matter inter-subject variability (WM-ISV). RESULTS: The white matter pattern ensemble model, combining MRI and amyloid PET, demonstrated a significantly higher classification performance for cognitive impairment and disability. Participants with Alzheimer's disease (AD) exhibited higher WM-ISV than participants with subjective cognitive decline, mild cognitive impairment, and vascular dementia. Furthermore, WM-ISV correlated significantly with blood-based biomarkers (such as glial fibrillary acidic protein and phosphorylated tau-217 [p-tau217]), and cognitive function and disability scores. DISCUSSION: Our results suggest that white matter pattern analysis has significant potential as an adjunct neuroimaging biomarker for clinical decision-making and determining cognitive impairment and disability. Highlights: The ensemble model combined both magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) and demonstrated a significantly higher classification performance for cognitive impairment and disability. Alzheimer's disease (AD) revealed a notably higher heterogeneity compared to that in subjective cognitive decline, mild cognitive impairment, or vascular dementia. White matter inter-subject variability (WM-ISV) was significantly correlated with blood-based biomarkers (glial fibrillary acidic protein and phosphorylated tau-217 [p-tau217]) and with the polygenic risk score for AD. White matter pattern analysis has significant potential as an adjunct neuroimaging biomarker for clinical decision-making processes and determining cognitive impairment and disability.
Keywords

MeSH

DOI
10.1002/alz.14094
PMID
39001624
Appears in Collections:
Journal Papers > School of Medicine / Graduate School of Medicine > Psychiatry & Behavioural Sciences
Journal Papers > School of Medicine / Graduate School of Medicine > Radiology
Journal Papers > School of Medicine / Graduate School of Medicine > Nuclear Medicine & Molecular Imaging
Journal Papers > School of Medicine / Graduate School of Medicine > Biomedical Informatics
Journal Papers > School of Medicine / Graduate School of Medicine > Neurology
Ajou Authors
남, 유진  |  노, 현웅  |  문, 소영  |  박, 범희  |  손, 상준  |  안, 영실  |  이, 선민  |  최, 진욱  |  홍, 선화  |  홍, 창형
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