Investigator:Kamil A. Grajski, PhD
Title:Medial temporal lobe (MTL) – default-mode network (DMN) functional connectivity disruption in Autosomal Dominant Alzheimer’s Disease (ADAD) progression in a Dominantly Inherited Alzheimer Network (DIAN) cohort
Date of Request:05/01/2022
ID:DIAN-D2211
Aim 1:Reprocess DIAN MRI data with FreeSurfer 7 and confirm progression of cortical thickness and subcortical volume results reported in McKay, N. S., et al. (2022).
Aim 2:Process rsfMRI data to characterize the progression of disruption in functional connectivity in the Default-Mode Network and related structures using an hybrid a priori and data-driven identification of ROI pairs of interest using a combination of AFNI and “home-grown” analytics.
Aim 3:Identify the subpopulation of DIAN patients for whom both MRI and rsfMRI data pass stringent quality criteria for inclusion. Establish the temporal correspondence of morphological and functional connectivity changes. For example, Grajski & Bressler (2019) showed in an ADNI cohort that functional connectivity changes may be detected prior to detection of morphological changes. Will the same, similar, or other hold for DIAN cohort(s)?
Aim 4Explore the clinical applicability of rsfMRI as a biomarker of Alzheimer's Disease progression. McKay, N. S., et al. (2022), noted a key benefit of the DIAN population is its relative absence of age-related and other comorbidities such as observed with sporadic Alzheimer's Disease. Explore viability of rsfMRI as a biomarker through machine learning-based approach to classification of MRI and rsfMRI data by DIAN clinical group.