Neurodegenerative diseases, including frontotemporal lobar degeneration (FTLD) spectrum syndromes, are characterized by the accumulation of insoluble protein aggregates in the central nervous system. A common feature of these diseases is that pathological changes accumulate over time following a stereotyped spatial pattern, which contributes to the onset and progression of clinical symptoms. Until recently, the causes of such progression were still unknown. Recent pathological and neuroimaging studies have, however, suggested that insoluble and pathological protein aggregates are able to alter the conformation of neighboring proteins and spread through cell-to-cell transmission. According to this theory, called the 'brain connectome,' the brain network is established as a set of nodes, which correspond to different anatomical regions. These brain networks are highly connected to each other and their internal organization is fundamental for an efficient integration of information coming from different regions and to guarantee adequate levels of motor/cognitive performance. Thanks to magnetic resonance studies and research in the field of brain networks, it is possible to understand the pathophysiology of neurodegenerative diseases and reveal the connectivity profiles associated with different clinical outcomes. The main objective of this project is to explore the mechanisms of neurodegeneration associated with the different FTLD spectrum syndromes, and in particular the hypothesis that the neurodegenerative process is driven by the structural architecture of the brain 'connectome'. The ultimate goal is to apply mathematical models to structural and functional connectivity data to predict the evolution of the neurodegenerative process in sporadic and genetic forms of Frontotemporal Lobar Degeneration Disease. This study aims to investigate the spatiotemporal progression of neurodegeneration in frontotemporal lobar degeneration (FTLD) using advanced neuroimaging and connectomics. 360 patients with sporadic FTLD (including bvFTD, semantic and nonfluent PPA, PSPs, CBS, and ALS) and 65 patients with genetic FTLD (MAPT, GRN, and C9orf72 mutati will be enrolled. The study also plans to enroll 120 subjects who are members of families carrying FLTD-associated mutations (including 60 mutation carriers). Finally, 100 healthy controls will also be enrolled, including 50 young healthy controls and 50 healthy controls comparable with patients by sex and age. Participants will undergo clinical, neuropsychological, and behavioral assessments, blood and Cerebrospinal fluid (CSF) collection, and multimodal 3Tesla Magnetic Resonance Imaging MRI at baseline and every 6 months for up to 2 years. Primary objectives include mapping longitudinal changes in structural and functional brain networks, developing predictive models of network degeneration and clinical decline, and characterizing protein-specific patterns of network degeneration. Secondary aims include identifying early network biomarkers in presymptomatic carriers and correlating network changes with biological markers.
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Longitudinal change in the structural connectome via Neurite Orientation Dispersion and Density Imaging (NODDI)
Timeframe: 6 months, 12 months, 18 months, 24 months
Longitudinal change in the structural connectome via Diffusion Tensor Imaging (DTI)
Timeframe: 6 months, 12 months, 18 months, 24 months
Longitudinal change in brain functional connectome via functional MRI
Timeframe: 6 months, 12 months, 18 months, 24 months
Prediction of pathological spreading through the structural connectome
Timeframe: 6 months, 12 months, 18 months, 24 months