Associations between COVID-19 and neuroinflammation: A diffusion basis spectrum imaging study.
Poster No:
2356
Submission Type:
Abstract Submission
Authors:
Wei Zhang1, Aaron Gorelik1, Qing Wang1, Sara Norton1, Tmara Hershey1, Arpana Agrawal1, Ryan Bogdan1, Janine Bijsterbosch1
Institutions:
1Washington University in St. Louis, Saint Louis, MO
First Author:
Co-Author(s):
Introduction:
COVID-19 remains a significant international public health concern1. Yet, its underlying mechanisms have not been fully elucidated. Recent studies suggest that the SARS-CoV-2 infection may induce prolonged inflammation within the central nervous system, contributing to various "brain frog" symptoms2. However, the evidence so far primarily stems from limited small-scale case investigations3. To address this gap, the current study capitalized a longitudinal imaging dataset and a novel and non-invasive imaging technique to examine the associations between COVID-19 and neuroinflammation. We hypothesize that SARS-CoV-2 infection will be associated with non-invasively measured neuroinflammation markers of cellularity (indicative of increase in inflammatory cell fraction) and edema (extracellular accumulation of fluid).
Methods:
This study used longitudinal data from the UK Biobank that included longitudinal neuroimaging data from a cohort of 416 individuals (Mage=58.6; n=244 female), including pre- and post-infection scans from n=224 COVID-19 cases (Mage=59.1; n=122 females). Putative neuroinflammation markers including restricted fraction (RF) indexing cellularity and hindered fraction (HF) indexing vasogenic edema were generated using the Diffusion Basis Spectrum Imaging (DBSI) technique4.
Regions of interest for gray matter structures were defined using FreeSurfer with automatic subcortical segmentation and Desikan-Killiany cortical atlases5, and for white matter tracts using a probabilistic tractography atlas (JHU-ICBM-tracts6) with a threshold of 25%, resulting in 14 and 66 bilateral subcortical and cortical structures, as well as 20 white matter tracts.
We conducted a series of linear regression analyses to model the putative neuroinflammation markers assessed after COVID-19 (i.e., at scan2) as a function of case-control membership, while accounting for the baseline neuroinflammation markers (i.e., at scan1), as well as confounding effects of sex, race, and changes in age, body mass index and smoking frequency. False discovery rate (FDR) was applied to account for multiple testing.
Regions of interest for gray matter structures were defined using FreeSurfer with automatic subcortical segmentation and Desikan-Killiany cortical atlases5, and for white matter tracts using a probabilistic tractography atlas (JHU-ICBM-tracts6) with a threshold of 25%, resulting in 14 and 66 bilateral subcortical and cortical structures, as well as 20 white matter tracts.
We conducted a series of linear regression analyses to model the putative neuroinflammation markers assessed after COVID-19 (i.e., at scan2) as a function of case-control membership, while accounting for the baseline neuroinflammation markers (i.e., at scan1), as well as confounding effects of sex, race, and changes in age, body mass index and smoking frequency. False discovery rate (FDR) was applied to account for multiple testing.
Results:
After FDR corrections, COVID-19 was significantly associated with changes in DBSI-HF values in the pre- and post-central gyri, as well as the caudal middle frontal gyrus after FDR corrections (β's>0.3, FDR p's=0.03; Figure 1). Furthermore, a set of cortical regions and white matter tracts exhibited nominally significant associations, such as bilateral superior frontal gyrus, bilateral pars triangularis, and right cingulum bundle (β's>0.15, uncorrected p's<0.05).
Conversely, COVID-19 was not associated with any changes in DBSI-RF values across all regional gray matter regions and white matter tracts apart from several trend-level associations (|β|'s>0.13, uncorrected p's<0.05; Figure 2).
Conversely, COVID-19 was not associated with any changes in DBSI-RF values across all regional gray matter regions and white matter tracts apart from several trend-level associations (|β|'s>0.13, uncorrected p's<0.05; Figure 2).
Conclusions:
In line with our hypothesis, we found significant associations between increased vasogenic edema and SARS-CoV-2 infection. Interestingly, brain regions showing these associations also exhibited aberrant connectivity patterns7, and increased brain activity at rest8 in individuals with SARS-CoV-2 infection. Our results are also in line with evidence from a recent PET study showing increased [11C]PBR28 signal (i.e., indicative of microglia activation or neuroinflammation) in the same brain regions for individuals with long-COVID symptoms9. However, we did not find significant associations between COVID-19 and inflammation-related cellularity index, suggesting the vasogenic edema index as a more sensitive neuroinflammation marker to SARS-CoV-2 infection. This also broadly align with previous studies showing the associations of free water or extracellular water with other neuroinflammation-related disorders such as the Alzheimer Disease and obesity10. As this study lacks symptomology data, future research is warranted to explore the potential symptom-dependent neuroinflammatory relationship with SARS-CoV-2 infection.
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis 2
Novel Imaging Acquisition Methods:
Diffusion MRI 1
Keywords:
MRI
STRUCTURAL MRI
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - DBSI, neuroinflammation, COVID-19
1|2Indicates the priority used for review
Provide references using author date format
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