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Assessing cognitive impairment and disability in older adults through the lens of whole brain white matter patterns
Hyun Woong Roh1, Nishant Chauhan2, Sang Won Seo3
1Department of Psychiatry, Ajou University School of Medicine, Suwon, Republic of Korea.
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.
