| Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer's disease. | |
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MedLine Citation:
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PMID: 20410145 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Resting-state or intrinsic connectivity network functional magnetic resonance imaging provides a new tool for mapping large-scale neural network function and dysfunction. Recently, we showed that behavioural variant frontotemporal dementia and Alzheimer's disease cause atrophy within two major networks, an anterior 'Salience Network' (atrophied in behavioural variant frontotemporal dementia) and a posterior 'Default Mode Network' (atrophied in Alzheimer's disease). These networks exhibit an anti-correlated relationship with each other in the healthy brain. The two diseases also feature divergent symptom-deficit profiles, with behavioural variant frontotemporal dementia undermining social-emotional function and preserving or enhancing visuospatial skills, and Alzheimer's disease showing the inverse pattern. We hypothesized that these disorders would exert opposing connectivity effects within the Salience Network (disrupted in behavioural variant frontotemporal dementia but enhanced in Alzheimer's disease) and the Default Mode Network (disrupted in Alzheimer's disease but enhanced in behavioural variant frontotemporal dementia). With task-free functional magnetic resonance imaging, we tested these ideas in behavioural variant frontotemporal dementia, Alzheimer's disease and healthy age-matched controls (n = 12 per group), using independent component analyses to generate group-level network contrasts. As predicted, behavioural variant frontotemporal dementia attenuated Salience Network connectivity, most notably in frontoinsular, cingulate, striatal, thalamic and brainstem nodes, but enhanced connectivity within the Default Mode Network. Alzheimer's disease, in contrast, reduced Default Mode Network connectivity to posterior hippocampus, medial cingulo-parieto-occipital regions and the dorsal raphe nucleus, but intensified Salience Network connectivity. Specific regions of connectivity disruption within each targeted network predicted intrinsic connectivity enhancement within the reciprocal network. In behavioural variant frontotemporal dementia, clinical severity correlated with loss of right frontoinsular Salience Network connectivity and with biparietal Default Mode Network connectivity enhancement. Based on these results, we explored whether a combined index of Salience Network and Default Mode Network connectivity might discriminate between the three groups. Linear discriminant analysis achieved 92% clinical classification accuracy, including 100% separation of behavioural variant frontotemporal dementia and Alzheimer's disease. Patients whose clinical diagnoses were supported by molecular imaging, genetics, or pathology showed 100% separation using this method, including four diagnostically equivocal 'test' patients not used to train the algorithm. Overall, the findings suggest that behavioural variant frontotemporal dementia and Alzheimer's disease lead to divergent network connectivity patterns, consistent with known reciprocal network interactions and the strength and deficit profiles of the two disorders. Further developed, intrinsic connectivity network signatures may provide simple, inexpensive, and non-invasive biomarkers for dementia differential diagnosis and disease monitoring. |
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Authors:
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Juan Zhou; Michael D Greicius; Efstathios D Gennatas; Matthew E Growdon; Jung Y Jang; Gil D Rabinovici; Joel H Kramer; Michael Weiner; Bruce L Miller; William W Seeley |
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Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't Date: 2010-04-21 |
Journal Detail:
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Title: Brain : a journal of neurology Volume: 133 ISSN: 1460-2156 ISO Abbreviation: Brain Publication Date: 2010 May |
Date Detail:
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Created Date: 2010-04-26 Completed Date: 2010-05-17 Revised Date: 2011-07-28 |
Medline Journal Info:
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Nlm Unique ID: 0372537 Medline TA: Brain Country: England |
Other Details:
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Languages: eng Pagination: 1352-67 Citation Subset: AIM; IM |
Affiliation:
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Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA 94117, USA. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Aged Alzheimer Disease / diagnosis, physiopathology*, psychology* Behavior* Female Frontotemporal Dementia / diagnosis, physiopathology*, psychology* Gyrus Cinguli / physiopathology Hippocampus / physiopathology Humans Magnetic Resonance Imaging Male Middle Aged Nerve Net / physiopathology* Occipital Lobe / physiopathology Parietal Lobe / physiopathology Raphe Nuclei / physiopathology Severity of Illness Index |
| Grant Support | |
ID/Acronym/Agency:
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K08 AG027086/AG/NIA NIH HHS; K23 AG031861-04/AG/NIA NIH HHS; K23-AG031861/AG/NIA NIH HHS; K23NS048302/NS/NINDS NIH HHS; P01 AG19724/AG/NIA NIH HHS; P50 AG1657303-75271/AG/NIA NIH HHS; R01-AG027859/AG/NIA NIH HHS |
| Comments/Corrections | |
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