Quantitative susceptibility mapping of the brain is associated with inflammatory changes in Alzheimer's disease related areas

Abstract

Accumulation of paramagnetic substances in brain tissue may constitute a feature of Alzheimer's disease (AD) associated with inflammatory processes. This study employed MRI quantitative susceptibility mapping (QSM), as an index of paramagnetic load, to assess its association with brain Aβ and tau aggregates, as well as inflammatory biomarkers. We assessed QSM and T1-weighted MRI scans from 315 participants in the TRIAD cohort, including young-controls and individuals across the AD spectrum. Imaging was performed at baseline, with follow-up assessments at 12 and 24 months. Mean-cortical and subcortical susceptibility values were measured, and correlations with AD-relevant plasma and CSF inflammatory biomarkers. At baseline, AD patients had significantly greater QSM than age-matched controls in the posterior cingulate cortex, precuneus, and basal ganglia. After 24 months, QSM increased in the anterior cingulate in MCI, while dementia cases showed increase in the pallidum and hippocampus. Multiple comparison analysis indicated correlation between QSM and immune biomarkers IL-10RB, PD-L1, SCF, TWEAK, CSF-1, CXCL9, HGF, and CD40, but not with brain Aβ or tau-related biomarkers. Our findings reveal that the magnitude of tissue susceptibility load, as measured by QSM, reflects tissue inflammation rather than protein aggregation. QSM provides new insights into tissue dysfunction, with potential applications in AD therapeutic development.

Keywords: Alzheimer’s disease; QSM; brain’ susceptibility; immune biomarkers; neuroinflammation.

Figure 1.

The full study schema. Figure 1 was created in BioRender (https://BioRender.com/r61a349).

Figure 2.

Regional QSM (values reported in ppm relative to CSF) differences across diagnostic groups were examined using ANCOVA, including age as a covariate. Post-hoc pairwise comparisons were conducted using Tukey’s HSD test. To control for type I error across multiple ROIs, p values were adjusted using the FDR method, with q < 0.05 considered statistically significant (only regions exhibiting significant ANCOVA p values are represented). Some brain region (a, b) showed significant differences due to AD (CU vs AD) and no region (c, d) showed significant differences between MCI versus AD or CU versus MCI. ANCOVA: analysis of covariance; HSD: honestly significant difference.

Figure 3.

Longitudinal changes over 2-year follow-up. After 2 years of follow-up different brain regions (values reported in ppm) demonstrated distinct alteration in MCI and AD group comparing to CU (Y) and/or CU participants (a). Based on this figure, at least 2-year follow-up is warranted to capture the abnormal change of brain’s susceptibility due to AD. The MCI group exhibited increases only in the Rostral anterior cingulate (b; β = 7.79 ± 2.72; p < 0.001). Pallidum (c; β = 14.29 ± 5.80; p = 0.02) and hippocampus (e; β = 8.54 ± 3.18; p = 0.04) showed QSM increases only for the dementia group, whereas the CU (Y) and CU groups showed no changes during the same observation period (a–f). In complementary interaction analyses, limited group differences were detectable at 12 months: MCI showed a greater increase than CU in the hippocampus (β = 0.32 ± 0.11; p = 0.003), while CU (Y) differed from CU across several regions, including the pallidum (β = 0.41 ± 0.14; p = 0.004), posterior cingulate cortex (β = 0.27 ± 0.10; p = 0.009), precuneus (β = 0.25 ± 0.10; p = 0.014), hippocampus (β = 0.29 ± 0.10; p = 0.006), and parahippocampal gyrus (β = 0.31 ± 0.11; p = 0.005). No 12-month differences were observed between AD and CU. At 24 months, AD showed a significantly greater increase than CU in the hippocampus (β = 0.58 ± 0.19; p = 0.002), with no additional significant contrasts for MCI or CU (Y).

Figure 4.

Stronger brain’s atrophy is correlated with higher brain’s magnetic susceptibility. Significant correlations were observed between the volume and QSM values (values reported in ppm) of various brain regions (a–d).

Figure 5.

Associations between plasma immune markers and regional brain susceptibility (QSM). (a) Heatmap displaying Spearman correlation coefficients between plasma immune-related biomarkers and QSM values across different brain regions. Rows represent regions, and columns represent biomarkers, with hierarchical clustering applied to both axes. Warm colors indicate positive correlations, while cool colors indicate negative correlations. (b) Volcano plot showing the distribution of correlations between individual plasma biomarkers and regional mean QSM values. The x-axis shows the Spearman correlation coefficient, and the y-axis represents statistical significance as −log₁₀ (p value). (c) correlation analysis across Braak stages revealed that the spatial distribution of QSM alterations aligns with brain regions typically implicated in Braak staging.

Figure 6.

Voxel-based linear regression analyses identified cortical regions where the top 8 inflammation-related biomarkers showed the strongest associations with QSM measures (a–h). Warmer colors indicate higher t-values, highlighting areas linked to early (Braak I–II) and late (Braak V–VI) stages of AD pathology. All models were adjusted for age, sex, and APOE4 and significance was determined using random field theory correction (p < 0.001).