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. 2020 May 1;143(5):1341-1349.
doi: 10.1093/brain/awaa089.

Relationship Between Cortical Iron and Tau Aggregation in Alzheimer's Disease

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Free PMC article

Relationship Between Cortical Iron and Tau Aggregation in Alzheimer's Disease

Nicola Spotorno et al. Brain. .
Free PMC article

Abstract

A growing body of evidence suggests that the dysregulation of neuronal iron may play a critical role in Alzheimer's disease. Recent MRI studies have established a relationship between iron accumulation and amyloid-β aggregation. The present study provides further insight demonstrating a relationship between iron and tau accumulation using magnetic resonance-based quantitative susceptibility mapping and tau-PET in n = 236 subjects with amyloid-β pathology (from the Swedish BioFINDER-2 study). Both voxel-wise and regional analyses showed a consistent association between differences in bulk magnetic susceptibility, which can be primarily ascribed to an increase in iron content, and tau-PET signal in regions known to be affected in Alzheimer's disease. Subsequent analyses revealed that quantitative susceptibility specifically mediates the relationship between tau-PET and cortical atrophy measures, thus suggesting a modulatory effect of iron burden on the disease process. We also found evidence suggesting the relationship between quantitative susceptibility and tau-PET is stronger in younger participants (age ≤ 65). Together, these results provide in vivo evidence of an association between iron deposition and both tau aggregation and neurodegeneration, which help advance our understanding of the role of iron dysregulation in the Alzheimer's disease aetiology.

Keywords: Alzheimer’s disease; iron; quantitative susceptibility mapping; tau; tau-PET.

Figures

Figure 1
Figure 1
Whole grey matter QSM voxel-wise regression results. Clusters display the t-values for the significant results (P < 0.01 FWE) of the positive voxel-wise association: absolute-QSM ∼ tau-SUVR + age. The results are displayed in radiological convention. For visualization purposes the results have been warped to MNI space (Montreal Neurological Institute template) 152 using ANTs routines and displayed over the study-wise anatomical template.
Figure 2
Figure 2
Regional analysis for the full study cohort. (A) Regional pattern of significant Pearson Product-Moment correlation (FDR corrected P < 0.05) between signed-QSM and tau-PET signal. The colour scale represents the Pearson correlation coefficient. (B) Signed-QSM plotted as a function of mean normalized tau-PET tracer uptake in the inferior temporal gyrus. The translucent area around the regression line represents the 95% CI for the regression estimate. (C) Flow chart illustration of the mediation analysis results (each model includes age sex and cognitive group as covariates); c represents the direct association strength between tau-PET signal and cortical thickness [β = −0.107, P < 0.0001, CI: −0.13 to −0.08]; c’ is the association strength between tau-PET signal and cortical thickness accounting for the effect of QSM [β = −0.089, P < 0.001, CI: −0.12 to −0.06]; c-c’ is therefore the mediation effect of QSM [β = −0.018, P < 0.001, CI: −0.03 to −0.01, QSM can explain 17% (βratio) of the effect of tau-PET signal on cortical thickness].
Figure 3
Figure 3
Regional analyses for younger and older groups. (AC) Results for the younger group (n =40). (A) Regional pattern of significant Pearson’s correlation between signed-QSM and tau-PET signal (FDR corrected P < 0.05). The colour scale represents the Pearson correlation coefficient. (B) Covariation of signed-QSM with respect to tau-PET values extracted from the inferior temporal gyrus. The translucent area around the regression line represents the 95% CI for the regression estimate. (C) Flow chart representing the mediation analysis (each model includes age sex and cognitive group as covariates). c = direct association between tau-PET signal and cortical thickness [β = −0.14, P < 0.001, CI: −0.20 to −0.10]; c’ = association between tau-PET signal and cortical thickness accounting for the effect of QSM [β = −0.087, P < 0.005, CI: −0.145 to −0.03]; c-c’ = mediation effect of QSM [β = −0.053, P < 0.005, CI: −0.104 to −0.02, QSM explains 38% (βratio) of the effect of tau-PET signal on cortical thickness]. (DF) Results for the older group (n =196). (D) Regions in which the Pearson Product-Moment correlation between signed-QSM and tau-PET signal survived FDR correction for multiple comparisons (P < 0.05). The colour scale represents the Pearson correlation coefficient. (E) Correlation between signed-QSM and tau-PET signal in the inferior temporal gyrus. The translucent area around the regression line represents the 95% CI for the regression estimate. (F) Chart representing the mediation analysis (each model includes age sex and cognitive group as covariates). c = direct association between tau-PET signal and cortical thickness [β = −0.096, P < 0.001, CI: −0.128 to −0.07]; c’ = association between tau-PET signal and cortical thickness accounting for the effect of QSM [β = −0.084, P < 0.001, CI: −0.116 to −0.05]; c-c’ = mediation effect of QSM [β = −0.012, P < 0.01, CI: −0.023 to 0, QSM mediate the 13% (βratio) of the effect of tau-PET signal on cortical thickness].

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