This Project will link well-validated BBB to history of infection as well as measures of brain structure and function. Biomarkers were selected to probe the following mechanisms: Alzheimer’s pathology, assessed with measures of β-amyloid (Aβ40, Aβ42) and tau (pTau181, pTau217, pTau231), axonal injury and neurodegeneration indexed by neurofilament light chain protein (NfL), astrocytic activation measured with glial fibrillary acidic protein (GFAP), and neuroinflammation, measured with a comprehensive cytokine panel. We will compare biomarker profiles in those with or without a history of SARS-CoV-2 infection to examine the biological pathways that explain the association between infection and cognition at cross-section (Aim 1) and cognitive decline at follow-up (Aim 2), and to establish the prognostic utility of these biomarkers alone and in combination with other measures (e.g., genomic, neuroimaging) to predict cognitive trajectories (Aim 3). The effects of individual characteristics including sex, race/ethnicity, medical comorbidities, and measures of genetic variation will be evaluated as potential modifiers of the observed associations.
Cross-sectional: To compare the BBB profiles of individuals with and without a history of SV-2 infection; to identify potential biological pathways linked to cognitive outcomes.
Longitudinal: To identify the biomarker profiles that predict cognitive trajectories and incident mild cognitive impairment (MCI) or dementia, contrasting participants with or without a history of SV-2 infection.
To integrate aims with components of the U19 study by examining the association of BBB with clinical data, neuroimaging, gene x environment, and their effect on cognition in those with and without exposure to SV-2 infection. Specifically, we will identify the independent and joint predictive value of BBB in combination with other clinical, neuroimaging and genetic data for the prediction of cognitive status and decline.
The AC oversees sharing study resources with external investigators, promoting collaborations. Resource transfer agreements are managed through the Data Management & Statistics Core and deposited in NIH-maintained repositories, including NACC, NCRAD, and NIAGADS.