Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
Diffusion MRI reveals amyloid plaque-associated cellular signatures through spatial transcriptomic integration.
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Han Xinyue, Hu Rui, Ping Xingjie, Chen Jie, Liu Juan, Liu Zhuoheng, Jin Xiaoming, Gao Xiang, Lin Mingquan, Zhao Yi, Wang Nian
Аннотация
INTRODUCTION: Amyloid plaque deposition is a defining feature of Alzheimer's disease (AD), yet how plaque-associated cellular alterations are reflected in noninvasive imaging remains unclear.
METHODS: We integrated high-resolution diffusion magnetic resonance imaging (dMRI) with spatial transcriptomics (ST) in an AD mouse model. Spatial correlations were assessed across the whole brain and in disease-control and plaque-non-plaque comparisons. Neural network models were trained to predict AD-associated cell types from dMRI metrics.
RESULTS: dMRI metrics showed moderate spatial correlations (r = -0.41 to 0.36) with oligodendrocyte- and neuron-related gene expression. Disease-control comparisons revealed region-specific MRI-derived microstructural alterations aligned with transcriptional changes in microglia, astrocytes, oligodendrocytes, and neurons. Plaque-rich regions exhibited distinct diffusion and susceptibility signatures associated with oligodendrocyte and microglial expression. Neural networks predicted spatial distributions of AD-associated cell types with 80%-86% accuracy.
DISCUSSION: dMRI captures plaque-associated cellular pathology and supports biologically informed interpretation of imaging contrasts in AD.
METHODS: We integrated high-resolution diffusion magnetic resonance imaging (dMRI) with spatial transcriptomics (ST) in an AD mouse model. Spatial correlations were assessed across the whole brain and in disease-control and plaque-non-plaque comparisons. Neural network models were trained to predict AD-associated cell types from dMRI metrics.
RESULTS: dMRI metrics showed moderate spatial correlations (r = -0.41 to 0.36) with oligodendrocyte- and neuron-related gene expression. Disease-control comparisons revealed region-specific MRI-derived microstructural alterations aligned with transcriptional changes in microglia, astrocytes, oligodendrocytes, and neurons. Plaque-rich regions exhibited distinct diffusion and susceptibility signatures associated with oligodendrocyte and microglial expression. Neural networks predicted spatial distributions of AD-associated cell types with 80%-86% accuracy.
DISCUSSION: dMRI captures plaque-associated cellular pathology and supports biologically informed interpretation of imaging contrasts in AD.