Assessing cognitive impairment and disability in older adults through the lens of whole brain white matter patterns
- Authors
- Hyun Woong Roh; Nishant Chauhan; Sang Won Seo; Seong Hye Choi; Eun-Joo Kim; Soo Hyun Cho; Byeong C. Kim; Jin Wook Choi; Young-Sil An; Bumhee Park; Sun Min Lee; So Young Moon; You Jin Nam; Sunhwa Hong; Sang Joon Son; Chang Hyung Hong; Lee, Dongha
- Issue Date
- Jul-2024
- Publisher
- Elsevier BV
- Keywords
- cognitive impairment; functional disability; MRI and PET imaging; neurodegeneration; white matter pattern
- Citation
- Alzheimer’s & Dementia
- Journal Title
- Alzheimer’s & Dementia
- URI
- http://scholarworks.bwise.kr/kbri/handle/2023.sw.kbri/1183
- DOI
- 10.1002/alz.14094
- ISSN
- 1552-5260
1552-5279
- Abstract
- INTRODUCTIONThis 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.METHODSWe 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).RESULTSThe 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.DISCUSSIONOur 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.
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