%0 Journal Article
%T Assessing cognitive impairment and disability in older adults through the lens of whole brain white matter patterns.
%A Roh HW
%A Chauhan N
%A Seo SW
%A Choi SH
%A Kim EJ
%A Cho SH
%A Kim BC
%A Choi JW
%A An YS
%A Park B
%A Lee SM
%A Moon SY
%A Nam YJ
%A Hong S
%A Son SJ
%A Hong CH
%A Lee D
%J Alzheimers Dement
%V 0
%N 0
%D 2024 Jul 12
%M 39001624
%F 16.655
%R 10.1002/alz.14094
%X <B>BACKGROUND: </B>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.<BR><B>METHODS: </B>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).<BR><B>RESULTS: </B>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.<BR><B>CONCLUSIONS: </B>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.<BR><B>CONCLUSIONS: </B>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.