Report: Revealing White Matter Changes Associated with Tau in Early Alzheimer’s Disease through Fixel-based Analysis

Research Background

Alzheimer’s Disease (AD) is generally thought to primarily affect the grey matter (GM), but more and more evidence shows that the white matter (WM) also experiences abnormalities. Current research largely relies on Diffusion Tensor Imaging (DTI) to non-invasively investigate white matter integrity in AD. However, there are methodological limitations with DTI in describing white matter changes, leading to inconsistent research results. For example, some studies show DTI revealed white matter changes are related to beta-amyloid (Amyloid-beta, Aβ) pathology, while other studies show contrasting results or no correlation found.

Research Origin

The paper is written by scholars including Khazar Ahmadi from Lund University, Ruhr University, Karolinska Institutet, Harvard Medical School, and other academic institutes. The paper was published in ‘Journal of Neuroscience’ on 1st May, 2024.

Research Method

The research uses an advanced Fixel-based analysis (FBA) in combination with conventional DTI, free-water corrected DTI (FW-DTI), and diffusion kurtosis imaging (DKI) to assess micro and macro changes in Fiber Density (FD) and Fiber Cross-section (FC) of white matter in early AD patients. The study involved 393 subjects (212 females), divided into Cognitively Unimpaired (CU) and Mild Cognitive Impairment (MCI) groups, and further divided into Amyloid-beta-negative (Aβ-negative) and -positive (Aβ-positive) categories.

Experimental Process

1. Participant Screening: CU and MCI patients in the Swedish BioFINDER-2 study were enrolled, Aβ-negative and -positive groups were determined based on cerebrospinal fluid Aβ42/40 ratio. After excluding 91 individuals due to motion artifacts, severe vascular complications, and high white matter signals, a total of 393 individuals were included.

2. Cognitive Evaluation: AD assessment scale cognitive subset (ADAS-cog), visual object and space perception battery (VOSP), and trail making test (TMT) were used to evaluate different cognitive domains.

3. MRI & PET Data Collection: 3T magnetic resonance imaging (MRI) was used to obtain whole-brain T1-weighted, T2-weighted, and diffusion-weighted imaging (dMRI) data, Aβ-PET and Tau-PET images were collected using a GE Discovery MI scanner, Standardized Uptake Value Ratios (SUVR) were used to calculate global Aβ and Tau burden.

4. Data Preprocessing & Analysis: A variety of tools were used to denoise, correct, and offset field corrections of the dMRI data. MRtrix3 software was used for FBA processing to calculate FA, MD, MK, FD indices, and whole-brain probabilistic tractography was performed. Subsequent GLM models and multivariate regression analysis were used to assess correlations with AD pathology and cognitive performance.

Result Acquisition

1. White Matter Changes: By comparing the FBA and DTI derived indices among Aβ-negative CU, Aβ-positive CU, and Aβ-positive MCI groups, it was found that in Aβ-positive MCI patients, FD, FC, and FDC were significantly reduced in bilateral cingulum, hippocampal part, forceps major, anterior thalamic radiation, and minor force. Although the DTI indices (FA, MD) demonstrated a larger range of white matter abnormalities, FBA showed higher sensitivity at the microscopic level.

2. Tau-related White Matter Changes and Cognitive Performance: Found that fiber cross-section area (FC) in the hippocampal part was significantly correlated with Tau PET uptake in the same region, and this relationship remained significant after correcting for global Aβ load. Further analysis showed that various white matter changes were significantly related to memory domains of cognitive performance, but not with other cognitive domains.

3. Key Discoveries: Though DTI indices showed a greater range of white matter abnormalities in MCI patients, FBA appeared more sensitive and specific, capturing Tau pathology related white matter degeneration more early. Also, the study found no correlation between Aβ load and any diffusion MRI indices, suggesting early Tau-related white matter changes may be based on macrostructure changes rather than microstructure.

Conclusion and Implication

The research for the first time systematically revealed Tau-aggregation-related white matter changes in early AD, supporting FBA as a potential biomarker for early detection and monitoring of Tau-related progression in AD. This discovery is of great significance for understanding the pathology of AD and its cognitive impacts, providing a new direction for the initiation of effective disease-modifying therapies. Future research should consider using FBA more widely and further validate its effectiveness and specificity in predicting