Prioni, Sara

Abstract Background Stepwise functional connectivity (SFC) detects whole‐brain functional couplings of a selected region of interest at increasing link‐step topological distances. Objective This study applied SFC to test the hypothesis that stepwise architecture propagating from the disease epicenter would shape patterns of brain atrophy in patients with progressive supranuclear palsy–Richardson's syndrome (PSP‐RS). Methods Thirty‐six patients with PSP‐RS and 44 age‐matched healthy control subjects underwent brain magnetic resonance imaging on a 3‐T scanner. The disease epicenter was defined as the peak of atrophy observed in an independent cohort of 13 cases with postmortem confirmation of PSP pathology and used as seed region for SFC analysis. First, we explored SFC rearrangements in patients with PSP‐RS, as compared with age‐matched control subjects. Subsequently, we tested SFC architecture propagating from the disease epicenter as a determinant of brain atrophy distribution. Results The disease epicenter was identified in the left midbrain tegmental region. Compared with age‐matched control subjects, patients with PSP‐RS showed progressively widespread decreased SFC of the midbrain with striatal and cerebellar regions through direct connections and sensorimotor cortical regions through indirect connections. A correlation was found between average link‐step distance from the left midbrain in healthy subjects and brain volumes in patients with PSP‐RS ( r = 0.38, P < 0.001). Conclusions This study provides comprehensive insights into the topology of functional network rearrangements in PSP‐RS and demonstrates that the brain architectural topology, as described by SFC propagating from the disease epicenter, shapes the pattern of atrophic changes in PSP‐RS. Our findings support the view of a network‐based pathology propagation in this primary tauopathy. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Abstract Genetic forms of frontotemporal dementia are most commonly due to mutations in three genes, C9orf72, GRN or MAPT, with presymptomatic carriers from families representing those at risk. While cerebral blood flow shows differences between frontotemporal dementia and other forms of dementia, there is limited evidence of its utility in presymptomatic stages of frontotemporal dementia. This study aimed to delineate the cerebral blood flow signature of presymptomatic, genetic frontotemporal dementia using a voxel-based approach. In the multicentre GENetic Frontotemporal dementia Initiative (GENFI) study, we investigated cross-sectional differences in arterial spin labelling MRI-based cerebral blood flow between presymptomatic C9orf72, GRN or MAPT mutation carriers (n = 107) and non-carriers (n = 113), using general linear mixed-effects models and voxel-based analyses. Cerebral blood flow within regions of interest derived from this model was then explored to identify differences between individual gene carrier groups and to estimate a timeframe for the expression of these differences. The voxel-based analysis revealed a significant inverse association between cerebral blood flow and the expected age of symptom onset in carriers, but not non-carriers. Regions included the bilateral insulae/orbitofrontal cortices, anterior cingulate/paracingulate gyri, and inferior parietal cortices, as well as the left middle temporal gyrus. For all bilateral regions, associations were greater on the right side. After correction for partial volume effects in a region of interest analysis, the results were found to be largely driven by the C9orf72 genetic subgroup. These cerebral blood flow differences first appeared approximately 12.5 years before the expected symptom onset determined on an individual basis. Cerebral blood flow was lower in presymptomatic mutation carriers closer to and beyond their expected age of symptom onset in key frontotemporal dementia signature regions. These results suggest that arterial spin labelling MRI may be a promising non-invasive imaging biomarker for the presymptomatic stages of genetic frontotemporal dementia.