Functional Connectome Architecture of Alzheimer’s Disease, Mild Cognitive Impairment and Behavioral Variant of Frontotemporal Dementia: A Graph Analysis Study (P4.028)

Objective: To investigate functional brain network architecture in late-onset (LO) and early-onset (EO) Alzheimer’s disease (AD), mild cognitive impairment (MCI), and behavioral variant of frontotemporal dementia (bvFTD). Background: Graph theory provides a powerful tool to describe quantitatively the topological organization of brain connectivity. A better understanding of network disruption in AD and other neurodegenerative diseases may provide non-invasive biomarkers for dementia differential diagnosis and disease monitoring. Methods: The study involved 122 AD patients, 61 MCI patients, and 51 age-matched controls. 35 EOAD patients were also compared with 29 bvFTD patients and 35 age-matched controls. All subjects underwent 3D T1-weighted and resting state functional MRI. Network nodes were defined parcellating the AAL atlas into 262 regions with equal size. Graph theory analysis was used to measure the global topological properties of functional brain networks and define brain modules. Differences in regional functional networks among groups were investigated using Network-based statistic. Results: While controls showed high-densely connected modules, AD groups and bvFTD patients showed a loss of long-distance intra-module connections, involving all modules in AD and the fronto-parietal-parahippocampal module in bvFTD. Regardless the age of onset, AD patients showed altered global network measures (lower network degree and clustering coefficient, and longer path length) compared to controls and to the other patient groups. Although MCI patients did not show global network alterations, they were characterized by a decreased regional functional connectivity in the fronto-parietal connections compared with controls. A decreased regional functional connectivity was prominent in the parieto-occipital connections in EOAD and in the fronto-temporal-parietal connections in bvFTD patients. Conclusions: Graph analysis is promising to detect functional changes in the early phase of neurodegenerative diseases and to serve for a prompt differential diagnosis among dementia syndromes. Supported by: Italian Ministry of Health (#GR-2010-2303035); Alzheimer’s Drug Discovery Foundation (#20131211).