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Updated: Aug 15, 2026

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
Published on: April 14, 2014
Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors
Xiuchao Sui1, Jagath C Rajapakse1, 1
1School of Computer Science and Engineering, Nanyang Technological University, 639798, Singapore.
Abstract:
The clinical presentation of Alzheimer's disease (AD) is not unitary as heterogeneity exists in the disease's clinical and anatomical characteristics. MRI studies have revealed that heterogeneous gray matter atrophy patterns are associated with specific traits of cognitive decline. Although white matter (WM) impairment also contributes to AD pathology, its heterogeneity remains unclear. The Latent Dirichlet Allocation (LDA) method is a suitable framework to study heterogeneity and allows to identify latent impairment factors of AD instead of simply mapping an overall disease effect. By exploring whole brain WM skeleton images by using LDA, three latent factors were revealed in AD: a temporal-frontal impairment factor (temporal and frontal lobes, especially hippocampus and para-hippocampus), a parietal factor (parietal lobe, especially precuneus), and a long fibre bundle factor (corpus callosum and superior longitudinal fasciculus). As revealed by longitudinal analysis, the latent factors have distinct impact on cognitive decline: for executive function (EF), the temporal-frontal factor was more strongly associated with baseline EF compared with the parietal factor, while the long-fibre bundle factor was most associated with decline rate of EF; for memory, the three factors showed almost equal effect on the baseline memory and decline rate. For each participant, LDA estimates his/her composition profile of latent impairment factors, which indicates disease subtype. We also found that the APOE genotype affects the AD subtype. Specifically, APOE ε4 was more associated with the long fibre bundle factor and APOE ε2 was more associated with temporal-frontal factor. By investigating heterogeneity and subtypes of AD through white matter impairment factors, our study could facilitate precision medicine.
Insights
Alzheimer's disease (AD) white matter impairment shows distinct subtypes, impacting cognitive decline differently. APOE genotype influences these subtypes, paving the way for precision medicine in AD treatment.
Area of Science:
- Neuroimaging
- Neurodegenerative Diseases
- Computational Biology
Background:
- Alzheimer's disease (AD) exhibits heterogeneous clinical and anatomical features.
- While gray matter atrophy is studied, white matter (WM) heterogeneity in AD remains unclear.
- Latent Dirichlet Allocation (LDA) can identify underlying factors of disease heterogeneity.
Purpose of the Study:
- To investigate white matter (WM) heterogeneity in Alzheimer's disease (AD) using Latent Dirichlet Allocation (LDA).
- To identify distinct WM impairment factors and their association with cognitive decline and APOE genotype.
- To explore AD subtypes based on WM impairment profiles for precision medicine.
Main Methods:
- Exploration of whole-brain WM skeleton images using Latent Dirichlet Allocation (LDA).
- Longitudinal analysis to assess the impact of identified WM factors on cognitive functions (executive function and memory).
- Correlation analysis between WM impairment factors, APOE genotype, and AD subtypes.
Main Results:
- Three latent WM impairment factors were identified in AD: temporal-frontal, parietal, and long fibre bundle.
- These factors differentially impact executive function and memory decline.
- APOE genotype influences AD subtype association, with APOE ε4 linked to the long fibre bundle factor and APOE ε2 to the temporal-frontal factor.
Conclusions:
- WM impairment in AD is heterogeneous, characterized by distinct latent factors.
- These factors are associated with specific cognitive decline patterns and influence AD subtypes.
- Understanding WM heterogeneity and its genetic underpinnings can advance precision medicine for Alzheimer's disease.
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