Imaging Predictors

  • Funded by National Institutes of Health (NIH)
  • Total publications:0 publications

Grant number: 5U19AG076581-02

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2023
    2028
  • Known Financial Commitments (USD)

    $520,049
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    PETER FOX
  • Research Location

    United States of America
  • Lead Research Institution

    UNIVERSITY OF TEXAS HLTH SCIENCE CENTER
  • Research 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.