Structural brain splitting is a hallmark of Granulin-related frontotemporal dementia

Stefano Gazzina, Mario Grassi, Genetic FTD Initiative (GENFI), Enrico Premi, Antonella Alberici, Alberto Benussi, Silvana Archetti, Roberto Gasparotti, Martina Bocchetta, David M. Cash, Emily G. Todd, Georgia Peakman, Rhian S. Convery, John C. van Swieten, Lize C. Jiskoot, Harro Seelaar, Raquel Sanchez-Valle, Fermin Moreno, Robert Laforce, Caroline GraffMatthis Synofzik, Daniela Galimberti, James B. Rowe, Mario Masellis, Maria Carmela Tartaglia, Elizabeth Finger, Rik Vandenberghe, Alexandre de Mendonça, Fabrizio Tagliavini, Chris R. Butler, Isabel Santana, Alexander Gerhard, Isabelle Le Ber, Florence Pasquier, Simon Ducharme, Johannes Levin, Adrian Danek, Sandro Sorbi, Markus Otto, Jonathan D. Rohrer, Barbara Borroni*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Frontotemporal dementia associated with granulin (GRN) mutations presents asymmetric brain atrophy. We applied a Minimum Spanning Tree plus an Efficiency Cost Optimization approach to cortical thickness data in order to test whether graph theory measures could identify global or local impairment of connectivity in the presymptomatic phase of pathology, where other techniques failed in demonstrating changes. We included 52 symptomatic GRN mutation carriers (SC), 161 presymptomatic GRN mutation carriers (PSC) and 341 non-carriers relatives from the Genetic Frontotemporal dementia research Initiative cohort. Group differences of global, nodal and edge connectivity in (Minimum Spanning Tree plus an Efficiency Cost Optimization) graph were tested via Structural Equation Models. Global graph perturbation was selectively impaired in SC compared to non-carriers, with no changes in PSC. At the local level, only SC exhibited perturbation of frontotemporal nodes, but edge connectivity revealed a characteristic pattern of interhemispheric disconnection, involving homologous parietal regions, in PSC. Our results suggest that GRN-related frontotemporal dementia resembles a disconnection syndrome, with interhemispheric disconnection between parietal regions in presymptomatic phases that progresses to frontotemporal areas as symptoms emerge.

Original languageEnglish
Pages (from-to)94-104
Number of pages11
JournalNeurobiology of Aging
Volume114
DOIs
Publication statusPublished - Jun 2022

Bibliographical note

Funding Information:
This work is supported by JPND grant “GENFI-prox” (to MS, JvS, MO, CG, JR, and BB), the Centre d'Investigation Clinique (ICM, France), the Centre pour l'Acquisition et le Traitement des Images platform (CATI, France), the UK Medical Research Council, and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, a Canadian Institutes of Health Research operating grant, Fundació Marató de TV3, Spain. JBR is supported by the Medical Research Council (SUAG/051 101400) and NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

Funding Information:
This work is supported by JPND grant ?GENFI-prox? (to MS, JvS, MO, CG, JR, and BB), the Centre d'Investigation Clinique (ICM, France), the Centre pour l'Acquisition et le Traitement des Images platform (CATI, France), the UK Medical Research Council, and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, a Canadian Institutes of Health Research operating grant, Fundaci? Marat? de TV3, Spain. JBR is supported by the Medical Research Council (SUAG/051 101400) and NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The authors thank our participant volunteers and their families for their participation; the radiographers/technologists and research nurses from all centers involved in this study for their invaluable support in data acquisition.

Publisher Copyright:
© 2022

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