Relationships between abdominal adipose tissue and neuroinflammation with diffusion basis spectrum imaging in midlife obesity

Abstract

Objective: This study investigated how obesity, BMI ≥ 30 kg/m², abdominal adiposity, and systemic inflammation relate to neuroinflammation using diffusion basis spectrum imaging.

Methods: We analyzed data from 98 cognitively normal midlife participants (mean age: 49.4 [SD 6.2] years; 34 males [34.7%]; 56 with obesity [57.1%]). Participants underwent brain and abdominal magnetic resonance imaging (MRI), blood tests, and amyloid positron emission tomography (PET) imaging. Abdominal visceral and subcutaneous adipose tissue (VAT and SAT, respectively) was segmented, and Centiloids were calculated. Diffusion basis spectrum imaging parameter maps were created using an in-house script, and tract-based spatial statistics assessed white matter differences in high versus low BMI values, VAT, SAT, insulin resistance, systemic inflammation, and Centiloids, with age and sex as covariates.

Results: Obesity, high VAT, and high SAT were linked to lower axial diffusivity, reduced fiber fraction, and increased restricted fraction in white matter. Obesity was additionally associated with higher hindered fraction and lower fractional anisotropy. Also, individuals with high C-reactive protein showed lower axial diffusivity. Higher restricted fraction correlated with continuous BMI and SAT particularly in male individuals, whereas VAT effects were similar in male and female individuals.

Conclusions: The findings suggest that, at midlife, obesity and abdominal fat are associated with reduced brain axonal density and increased inflammation, with visceral fat playing a significant role in both sexes.

FIGURE 1

Workflow for processing of DBSI data. The acquired DBSI images were corrected for eddy current and motion correction, and then a MATLAB script was used for creating DBSI maps, followed by skull removal. The TBSS method was used for creating a “mean” and an “all” FA skeleton, by using maps of all participants. The mean FA skeleton was then used as the reference for comparing TBSS results. For other DBSI metrics (i.e., fiber fraction, restricted fraction [RF], hindered fraction, axial diffusivity, radial diffusivity), a TBSS non‐FA command was used to create “all” skeletons of these metrics. Note that the all‐RF map has been shown as an example, and the same workflow has been applied to all of the DBSI maps. The design matrices for each comparison (for instance, with obesity vs. without obesity) was applied to the “all” skeletons for each of the DBSI metrics. DBSI, diffusion basis spectrum imaging; EPI, echo planar imaging; FA, fractional anisotropy; TBSS, tract‐based spatial statistics. [Color figure can be viewed at wileyonlinelibrary.com]

FIGURE 2

Tract‐based spatial statistics (TBSS) analysis in individuals with versus without obesity based on diffusion basis spectrum imaging. Green color represents the normal white matter skeleton, whereas yellow color shows the white matter tract showing differences between groups. (A) Higher restricted fraction in individuals with obesity at TFCE of 0.95; (B) higher hindered fraction in individuals with obesity at TFCE of 0.95; (C) lower fiber fraction in individuals with obesity at TFCE of 0.995; (D) lower axial diffusivity in individuals with obesity at TFCE of 0.99; and (E) lower fractional anisotropy in individuals with obesity at TFCE of 0.95. TFCE, threshold‐free cluster enhancement. [Color figure can be viewed at wileyonlinelibrary.com]

FIGURE 3

Tract‐based spatial statistics (TBSS) analysis in individuals with high versus low VAT based on diffusion basis spectrum imaging. Green color represents the normal white matter skeleton, whereas yellow color shows the white matter tract showing differences between groups. (A) Higher restricted fraction in individuals with high VAT at TFCE of 0.95; (B) lower fiber fraction in individuals with high VAT at TFCE of 0.95; (C) and lower axial diffusivity in individuals with high VAT at TFCE of 0.95. TFCE, threshold‐free cluster enhancement; VAT, visceral adipose tissue. [Color figure can be viewed at wileyonlinelibrary.com]

FIGURE 4

Tract‐based spatial statistics (TBSS) analysis in individuals with high versus low SAT based on diffusion basis spectrum imaging. Green color represents the normal white matter skeleton, whereas yellow color shows the white matter tract showing differences between groups. (A) Higher restricted fraction in individuals with high SAT at TFCE of 0.95; (B) lower fiber fraction in individuals with high SAT at TFCE of 0.95; (C) and lower axial diffusivity in individuals with high SAT at TFCE of 0.95. SAT, subcutaneous adipose tissue; TFCE, threshold‐free cluster enhancement. [Color figure can be viewed at wileyonlinelibrary.com]

FIGURE 5

Tract‐based spatial statistics (TBSS) analysis in individuals with high versus low CRP based on diffusion basis spectrum imaging. Green color represents the normal white matter skeleton, whereas yellow color shows the white matter tract showing differences between groups. The figure represents lower axial diffusivity in individuals with high CRP at TFCE of 0.95. CRP, C‐reactive protein; TFCE, threshold‐free cluster enhancement. [Color figure can be viewed at wileyonlinelibrary.com]