title: Gray matter network differences between behavioral variant frontotemporal dementia and Alzheimer's disease.
abstract: We set out to study whether single-subject gray matter (GM) networks show disturbances that are specific for Alzheimer's disease (AD; n = 90) or behavioral variant frontotemporal dementia (bvFTD; n = 59), and whether such disturbances would be related to cognitive deficits measured with mini-mental state examination and a neuropsychological battery, using subjective cognitive decline subjects as reference. AD and bvFTD patients had a lower degree, connectivity density, clustering, path length, betweenness centrality, and small world values compared with subjective cognitive decline. AD patients had a lower connectivity density than bvFTD patients (F = 5.79, p = 0.02; mean ± standard deviation bvFTD 16.10 ± 1.19%; mean ± standard deviation AD 15.64 ± 1.02%). Lasso logistic regression showed that connectivity differences between bvFTD and AD were specific to 23 anatomical areas, in terms of local GM volume, degree, and clustering. Lower clustering values and lower degree values were specifically associated with worse mini-mental state examination scores and lower performance on the neuropsychological tests. GM showed disease-specific alterations, when comparing bvFTD with AD patients, and these alterations were associated with cognitive deficits.
authors.affiliation: Alzheimer Centre and Department of Neurology, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, the Netherlands; Department of Neurology, Haga Ziekenhuis, The Hague, the Netherlands. Electronic address: E.Vijverberg@vumc.nl.
authors.forename: E G B
authors.initials: EGB
authors.lastname: Vijverberg
authors.affiliation: Alzheimer Centre and Department of Neurology, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, the Netherlands.
authors.forename: B M
authors.initials: BM
authors.lastname: Tijms
authors.affiliation: Alzheimer Centre and Department of Neurology, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, the Netherlands.
authors.forename: J
authors.initials: J
authors.lastname: Dopp
authors.affiliation: Alzheimer Centre and Department of Neurology, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, the Netherlands.
authors.forename: Y J
authors.initials: YJ
authors.lastname: Hong
authors.affiliation: Department of Clinical Chemistry, VU University Medical Center, Amsterdam, the Netherlands.
authors.forename: C E
authors.initials: CE
authors.lastname: Teunissen
authors.affiliation: Department of Radiology, VU University Medical Centre, Amsterdam, the Netherlands; Department of Radiology, Institutes of Neurology and Healthcare Engineering, UCL, London, UK.
authors.forename: F
authors.initials: F
authors.lastname: Barkhof
authors.affiliation: Alzheimer Centre and Department of Neurology, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, the Netherlands.
authors.forename: P
authors.initials: P
authors.lastname: Scheltens
authors.affiliation: Alzheimer Centre and Department of Neurology, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, the Netherlands.
authors.forename: Y A L
authors.initials: YAL
authors.lastname: Pijnenburg
mesh_terms: D000368:Aged; D000544:Alzheimer Disease / Q000473:pathology* / Q000523:psychology*; D003071:Cognition; D005260:Female; D057180:Frontotemporal Dementia / Q000473:pathology* / Q000503:physiopathology*; D066128:Gray Matter / Q000473:pathology* / Q000503:physiopathology*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009483:Neuropsychological Tests
keywords: Alzheimer's disease; Behavioral variant frontotemporal dementia; Cognition; Single-subject gray matter networks; Structural networks