Atrophy in behavioural variant frontotemporal dementia spans multiple large-scale prefrontal and temporal networks

Author:

Eldaief Mark C1234,Brickhouse Michael1,Katsumi Yuta1ORCID,Rosen Howard5,Carvalho Nicole1,Touroutoglou Alexandra12,Dickerson Bradford C123

Affiliation:

1. Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School , Boston, MA 02114 , USA

2. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital , Charlestown, MA 02129 , USA

3. Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School , Boston, MA 02114 , USA

4. Center for Brain Sciences, Harvard University , Cambridge, MA 02138 , USA

5. Department of Neurology, Memory and Aging Center, University of California, San Francisco , San Francisco, CA 94158 , USA

Abstract

Abstract The identification of a neurodegenerative disorder’s distributed pattern of atrophy—or atrophy ‘signature’—can lend insights into the cortical networks that degenerate in individuals with specific constellations of symptoms. In addition, this signature can be used as a biomarker to support early diagnoses and to potentially reveal pathological changes associated with said disorder. Here, we characterized the cortical atrophy signature of behavioural variant frontotemporal dementia (bvFTD). We used a data-driven approach to estimate cortical thickness using surface-based analyses in two independent, sporadic bvFTD samples (n = 30 and n = 71, total n = 101), using age- and gender-matched cognitively and behaviourally normal individuals. We found highly similar patterns of cortical atrophy across the two independent samples, supporting the reliability of our bvFTD signature. Next, we investigated whether our bvFTD signature targets specific large-scale cortical networks, as is the case for other neurodegenerative disorders. We specifically asked whether the bvFTD signature topographically overlaps with the salience network, as previous reports have suggested. We hypothesized that because phenotypic presentations of bvFTD are diverse, this would not be the case, and that the signature would cross canonical network boundaries. Consistent with our hypothesis, the bvFTD signature spanned rostral portions of multiple networks, including the default mode, limbic, frontoparietal control and salience networks. We then tested whether the signature comprised multiple anatomical subtypes, which themselves overlapped with specific networks. To explore this, we performed a hierarchical clustering analysis. This yielded three clusters, only one of which extensively overlapped with a canonical network (the limbic network). Taken together, these findings argue against the hypothesis that the salience network is preferentially affected in bvFTD, but rather suggest that—at least in patients who meet diagnostic criteria for the full-blown syndrome—neurodegeneration in bvFTD encompasses a distributed set of prefrontal, insular and anterior temporal nodes of multiple large-scale brain networks, in keeping with the phenotypic diversity of this disorder.

Funder

US National Institute of Deafness and Communication Disorders

National Institute on Aging

Athinoula A. Martinos Center for Biomedical Imaging at the MGH

Center for Functional Neuroimaging Technologies

P41 Biotechnology Resource Grant

National Institute of Biomedical Imaging and Bioengineering

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Neurology (clinical)

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