Atrophy patterns in sporadic and genetic behavioral variant frontotemporal dementia reflect brain network architecture. (December 2021)

• Record Type: Journal Article
• Authors: Shafiei, Golia; Bazinet, Vincent; Dadar, Mahsa; Manera, Ana Laura; Collins, Louis; Dagher, Alain; Bocchetta, Martina; Todd, Emily G.; Peakman, Georgia; Cash, David M.; Convery, Rhian S.; Russell, Lucy L.; Thomas, David L.; Iglesias, Juan Eugenio; van Swieten, John C.; Jiskoot, Lize C.; Seelaar, Harro; Borroni, Barbara; Galimberti, Daniela; Sanchez‐Valle, Raquel; Laforce, Robert; Moreno, Fermin; Synofzik, Matthis; Graff, Caroline; Masellis, Mario; Tartaglia, Maria Carmela; Rowe, James B.; Vandenberghe, Rik; Finger, Elizabeth; Tagliavini, Fabrizio; Mendonca, Alexandre; Santana, Isabel; Butler, Christopher; Gerhard, Alexander; Danek, Adrian; Levin, Johannes; Otto, Markus; Sorbi, Sandro; Ber, Isabelle Le; Pasquier, Florence; Rohrer, Jonathan D.; Bratislav, Misic; Ducharme, Simon;
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 4
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.051221
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Connections among brain regions allow pathological perturbations to spread from a single source node to multiple nodes. Patterns of neurodegeneration in multiple diseases, including behavioral variant of frontotemporal dementia (bvFTD), resemble the network architecture (Seeley et al., 2009, Neuron ), but how bvFTD‐related atrophy patterns relate to the network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture, such that connected regions display similar atrophy patterns. Method: Deformation‐based morphometry (DBM) was used to estimate regional changes in tissue volume density from T1‐weighted magnetic resonance images of 75 genetic bvFTD patients and 247 healthy controls (GENFI, http://genfi.org.uk/). We used linear mixed effects model to obtain a bvFTD‐related atrophy map, controlling for age, sex and aquision site. Structural and functional connectivity (SC and FC), derived from an independent sample of 70 healthy participants (Griffa et al., 2019, Zenodo ), were used to estimate mean neighbor atrophy values of each region. Relationship between node and neighbor atrophy was examined by correlating neighbor atrophy with nodal atrophy. Statistical significance of the analyses was assessed using a spatial autocorrelation‐preserving null model. Analyses were replicated in an independent dataset (FTLDNI, AG032306) with 70 sporadic bvFTD patients and 123 healthy controls. Result: Distributed atrophy patterns were observed in bvFTD, mainly targeting areas associated with limbic intrinsic network and insular cytoarchitectonic class (Fig 1a). A node's atrophy was significantly correlated with atrophy of its connected neighbors (e.g. high resolution: r=0.58, p=0.006 and r=0.54, p=0.0006, for SC‐ and FC‐ defined neighbors respectively) (Fig 2c). Relationship between node and neighbor atrophy was consistent across resolutions and greater in empirical networks compared to null networks. While a number of frontotemporal regions were identified as potential disease epicenters, anterior insula was the most likely one. Results were consistent in the sporadic cohort (Fig 1b&2d). Conclusion: Using connectivity models and rigorous statistical analyses that account for spatial autocorrelation, we demonstrate that bvFTD‐related neurodegeneration is conditioned by connectome architecture, accounting for 30‐40% of variance in atrophy. Atrophy is most profound in regions associated with insular cortex.