Imaging Predictors
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 5U19AG076581-02
Grant search
Key facts
Disease
COVID-19Start & end year
20232028Known Financial Commitments (USD)
$520,049Funder
National Institutes of Health (NIH)Principal Investigator
PETER FOXResearch Location
United States of AmericaLead Research Institution
UNIVERSITY OF TEXAS HLTH SCIENCE CENTERResearch Priority Alignment
N/A
Research Category
Clinical characterisation and management
Research Subcategory
Prognostic factors for disease severity
Special Interest Tags
N/A
Study Type
Clinical
Clinical Trial Details
Not applicable
Broad Policy Alignment
Pending
Age Group
Older adults (65 and older)
Vulnerable Population
Individuals with multimorbidityOther
Occupations of Interest
Unspecified
Abstract
The overall goal of this project is to discover neural signatures of COVID-19-associated cognitive impairment at the group-contrast level using volumetric, surface-based, and tract-based metrics. The overall hypothesis is that COVID-19-associated dementia will exhibit unique neural signatures discoverable through multi-modality neuroimaging. As our first foray, we will employ group-wise analytic strategies measuring: 1) gray-matter functional alterations using functional MRI (fMRI); 2) gray-matter atrophy using structural MRI (sMRI); and, 3) white-matter abnormalities using sMRI. Preliminary data (de Erasquin et al., in review) indicate that ~50% of post-COVID-19 enrollees over 60 years of age will be cognitively impaired, providing a balanced sample (demented:non-demented∷1:1). It is known that changes will be chronic - lasting at least 6 months - but it is not yet known whether cognitive impairment will be recuperative, progressive, or mixed. Aim 1: Gray-matter Functional Signature & Connectomics. Gray-matter functional alterations will be evaluated using voxel-based physiological (VBP) metrics computed from BOLD fMRI times series. BOLD-based VBP metrics will be supplemented by fMRI blood flow (BF) in all cohorts and PET measures of glucose metabolic rate (MRglu) in the Texas cohort, for cross validation. Connectomic alterations will be assessed by group independent components analysis (GICA) and structural equation modeling (SEM) of T2* BOLD time series. Aim 2: Gray-matter Structural Signature. Gray-matter structural alterations (atrophy and hypertrophy) will be evaluated using both volumetric and surface-based analyses. Aim 3: White-matter Structural Signature. White matter integrity will be evaluated using tract-based, volumetric and lesion-counting analytics. Aim 4 Exploratory analyses. Features discovered through group-wise contrasts (Aims 1-3) will be tested for overlap with known patterns (e.g., AD/MCI, healthy aging, metabolic syndrome, immune mediated, etc.). They will also be tested at the per-subject level as predictors of group membership (COVID +/-; cognitive impairment +/-) and co-analyzed as quantitative biomarkers and endophenotypes with Projects 1 and 2. Hypotheses 1: In the post-acute state of COVID-19 infection, persons with cognitive impairment will exhibit abnormalities in an EON and likely other as-yet-undefined neural signatures of CNS COVID severally defined by the above-described neuroimaging measures when contrasted either to non-impaired COVID-19 survivors or to non-COVID controls. Hypothesis 2: The strength of the neural signatures will be symptom-severity correlated, but not the pattern. Hypothesis 3: The neural signatures will be time invariant, other than due to symptom-severity variation. Hypothesis 4: The neural signatures will be cohort invariant, other than due to symptom-severity variation.