Authors

Sonja Schönecker, Ludwig-Maximilians-Universität München
Francisco J. Martinez-Murcia, Instituto Andaluz Interuniversitario en Data Science and Computational Intelligence
Boris Stephan Rauchmann, Institute for Clinical Radiology
Nicolai Franzmeier, Institute for Stroke and Dementia Research
Catharina Prix, Ludwig-Maximilians-Universität München
Elisabeth Wlasich, Ludwig-Maximilians-Universität München
Sandra V. Loosli, Ludwig-Maximilians-Universität München
Katja Bochmann, Ludwig-Maximilians-Universität München
Juan Manuel Gorriz Saez, Instituto Andaluz Interuniversitario en Data Science and Computational Intelligence
Robert Laforce, Clinique Interdisciplinaire de Mémoire (CIME)
Simon Ducharme, McConnell Brain Imaging Centre
Maria Carmela Tartaglia, Tanz Centre for Research in Neurodegenerative Diseases
Elizabeth Finger, Western UniversityFollow
Alexandre De Mendonça, Faculdade de Medicina, Universidade de Lisboa
Isabel Santana, University of Coimbra, Center for Neuroscience and Cell Biology
Raquel Sanchez-Valle, Institut d'Investigacions Biomèdiques August Pi i Sunyer - IDIBAPS
Fermin Moreno, Donostio University Hospital
Sandro Sorbi, Biodonostia Health Research Institute
Fabrizio Tagliavini, Fondazione Don Carlo Gnocchi
Barbara Borroni, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan
Markus Otto, Università degli Studi di Brescia
Matthis Synofzik, Martin-Universität Halle-Wittenberg
Daniela Galimberti, German Center of Neurodegenerative Diseases
Rik Vandenberghe, Università degli Studi di Milano
John Van Swieten, KU Leuven– University Hospital Leuven
Christopher Butler, Erasmus MC
Alexander Gerhard, Imperial College London
Caroline Graff, Universitätsklinikum Essen
Adrian Danek, Ludwig-Maximilians-Universität München
Jonathan D. Rohrer, Karolinska Universitetssjukhuset

Document Type

Article

Publication Date

9-6-2022

Journal

Neurology

Volume

99

Issue

10

First Page

E1032

Last Page

E1044

URL with Digital Object Identifier

10.1212/WNL.0000000000200828

Abstract

Background and ObjectivesFrontotemporal dementia (FTD) is a highly heritable disorder. The majority of genetic cases are caused by autosomal dominant pathogenic variants in the chromosome 9 open reading frame 72 (c9orf72), progranulin (GRN), and microtubule-associated protein tau (MAPT) gene. As motor disorders are increasingly recognized as part of the clinical spectrum, the current study aimed to describe motor phenotypes caused by genetic FTD, quantify their temporal association, and investigate their regional association with brain atrophy.MethodsWe analyzed baseline visit data of known carriers of a pathogenic variant in the c9orf72, GRN, or MAPT gene from the Genetic Frontotemporal Dementia Initiative cohort study. Principal component analysis with varimax rotation was performed to identify motor sign clusters that were compared with respect to frequency and severity between groups. Associations with cross-sectional atrophy patterns were determined using voxel-wise regression. We applied linear mixed effects models to assess whether groups differed in the association between motor signs and estimated time to symptom onset.ResultsA total of 322 pathogenic variant carriers were included in the analysis: 122 c9orf72 (79 presymptomatic), 143 GRN (112 presymptomatic), and 57 MAPT (43 presymptomatic) pathogenic variant carriers. Principal component analysis revealed 5 motor clusters, which we call progressive supranuclear palsy (PSP)-like, bulbar amyotrophic lateral sclerosis (ALS)-like, mixed/ALS-like, Parkinson disease (PD) like, and corticobasal syndrome-like motor phenotypes. There was no significant group difference in the frequency of signs of different motor phenotypes. However, mixed/ALS-like motor signs were most frequent, followed by PD-like motor signs. Although the PSP-like phenotype was associated with mesencephalic atrophy, the mixed/ALS-like phenotype was associated with motor cortex and corticospinal tract atrophy. The PD-like phenotype was associated with widespread cortical and subcortical atrophy. Estimated time to onset, genetic group and their interaction influenced motor signs. In c9orf72 pathogenic variant carriers, motor signs could be detected up to 25 years before expected symptom onset.DiscussionThese results indicate the presence of multiple natural clusters of motor signs in genetic FTD, each correlated with specific atrophy patterns. Their motor severity depends on time and the affected gene. These clinicogenetic associations can guide diagnostic evaluations and the design of clinical trials for new disease-modifying and preventive treatments.

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