The association between diffusion MRI metrics in the brain and blood markers of inflammation
Poster No:
1281
Submission Type:
Abstract Submission
Authors:
Lucy Hui1, Georgia Hodes2, Nasreen Khatri1, Jean Chen1
Institutions:
1Rotman Research Institute, Baycrest, Toronto, Ontario, 2Virgina Polyechnique Institute, Blacksburg, VA
First Author:
Co-Author(s):
Introduction:
Converging evidence portrays a close link between depression and inflammation, both peripherally and within the brain. Research studies have observed higher levels of systemic inflammatory markers, such as C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) in individuals with depression (1–3). These markers can be part of normal aging, obesity, and other pathologies. Neuro-glia and neuroimmune interactions have been linked to the development and progression of depression (4). Increased numbers and activity of microglia have been identified in postmortem tissue from patients with depression. Neuroinflammation can affect the functioning of neurotransmitters, such as serotonin, dopamine, and norepinephrine (5), which play crucial roles in mood regulation. However, to date there has been no non-invasive way to map neuroinflammation. Thoughthe potential of diffusion MRI (DWI) has been suggested as a possible mapping solution (6), the specificity of DWI metrics to inflammation is unknown. This study investigated the association between blood markers of systemic inflammation and DWI metrics.
Methods:
The study cohort was taken from the Canadian Biomarker Integration Network in Depression (CANBIND-1)(7). The cohort included individuals with major depressive disorder (MDD) and controls, whose distributions and data types were summarized in Fig. 1a. This work addressed the molecular (blood) and imaging markers only. The blood markers included cytokine and chemokines, while the imaging markers were derived from single-shell DWI data. We obtained mean diffusivity (MD) and fractional anisotropy (FA) using FSL. We also obtained free-water corrected FA (FAt) and MD (MDt) as well free-water signal fraction (F) using free-water elimination (fwDTI) (8). Additionally, we computed the correlated diffusion index (CDI) based on our recent work (8,9). Inflammatory modules were first extracted from the blood markers using weighted gene-correlation network analysis (WGCNA), separately for MDD and controls, implemented in R. These modules were in turn correlated with the DWI metrics in grey matter and white matter parcellations, obtained using FreeSurfer and the JHU atlas, respectively. The statistically significant correlations, corrected for FDR, were mapped to both the cortical and subcortical parcellations.
·Figure 1. The cohort, inflammatory modules and associations with cortical DWI.
Results:
In the MDD group, the brown and green modules were majority pro-inflammatory, while the blue module was mostly anti-inflammatory (Fig. 1b). The MDD modules (consensus modules between sexes) were different from the control modules (Fig. 1c). Compared to the controls, the DWI parameter from the MDD group showed much stronger correlations with inflammatory modules. While CDI and MDt were more specifically associated with the brown and green modules, FAt was indiscriminately associated with all modules (Fig. 1d). In the MDD group, CDI showed the highest association to the brown module (r^2=-0.23), while CDI, MD and F showed the highest sensitivity to the green module (Fig. 2). Most commonly implicated are the frontal, superior-parietal and middle-temporal regions. Negligible associations were found in subcortical white matter DWI metrics.
·Figure 2. DWI associations with inflammatory modules, mapped to the cortical surface.
Conclusions:
Study results demonstrated differences between the inflammatory modules generated from the MDD and control groups. Also, the MDD group showed stronger regional associations between DWI metrics and inflammatory modules. Specifically, MD and F showed consistently strong associations with one of the two pro-inflammatory modules, while CDI showed strong associations with both modules. As such, these were the most promising correlates of inflammation. Interestingly, the grey matter, instead of the white matter, was associated with the majority of inflammatory associations.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis 1
Multivariate Approaches
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Novel Imaging Acquisition Methods:
Diffusion MRI
Keywords:
Blood
MRI
Psychiatric Disorders
Statistical Methods
1|2Indicates the priority used for review
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