Connectome-based predictive modeling of brain pathology and cognition in Autosomal Dominant Alzheimer’s Disease

Abstract

AbstractINTRODUCTIONAutosomal Dominant Alzheimer’s Disease (ADAD) through genetic mutations can result in near complete expression of the disease. Tracking AD pathology development in an ADAD cohort of Presenilin-1 (PSEN1)E280A carriers’ mutation has allowed us to observe incipient tau tangles accumulation as early as 6 years prior to symptom onset.METHODSResting-state functional Magnetic Resonance Imaging (fMRI) and Positron-Emission Tomography (PET) scans were acquired in a group ofPSEN1carriers (n=32) and non-carrier family members (n=35). We applied Connectome-based Predictive Modeling (CPM) to examine the relationship between the participant’s functional connectome and their respective tau/amyloid-β levels and cognitive scores (word list recall).RESULTSCPM models strongly predicted tau concentrations and cognitive scores within the carrier group. The connectivity patterns between the temporal cortex, default mode network, and other memory networks were the most informative of tau burden.DISCUSSIONThese results indicate that resting-state fMRI methods can complement PET methods in early detection and monitoring of disease progression in ADAD.