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Structural connectivity centrality changes mark the path towards Alzheimer's disease

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Structural connectivity centrality changes mark the path towards Alzheimer's disease

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dc.contributor.author Peraza, Luis R. es_ES
dc.contributor.author Díaz-Parra, Antonio es_ES
dc.contributor.author Kennion, Oliver es_ES
dc.contributor.author Moratal, David es_ES
dc.contributor.author Taylor, John-Paul es_ES
dc.contributor.author Kaiser, Marcus es_ES
dc.contributor.author Bauer, Roman es_ES
dc.date.accessioned 2020-10-29T04:32:28Z
dc.date.available 2020-10-29T04:32:28Z
dc.date.issued 2019-01-18 es_ES
dc.identifier.uri http://hdl.handle.net/10251/153471
dc.description.abstract [EN] Introduction: The pathophysiological process of Alzheimer's disease is thought to begin years before clinical decline, with evidence suggesting prion-like spreading processes of neurofibrillary tangles and amyloid plaques. Methods: Using diffusion magnetic resonance imaging data from the Alzheimer's Disease Neuroimaging Initiative database, we first identified relevant features for dementia diagnosis. We then created dynamic models with the Nathan Kline Institute-Rockland Sample database to estimate the earliest detectable stage associated with dementia in the simulated disease progression. Results: A classifier based on centrality measures provides informative predictions. Strength and closeness centralities are the most discriminative features, which are associated with the medial temporal lobe and subcortical regions, together with posterior and occipital brain regions. Our model simulations suggest that changes associated with dementia begin to manifest structurally at early stages. Discussion: Our analyses suggest that diffusion magnetic resonance imaging-based centrality measures can offer a tool for early disease detection before clinical dementia onset. es_ES
dc.description.sponsorship The authors would like to thank Peter N. Taylor and Yujiang Wang for their stimulating feedback and suggestions. Funding: A.D.-P. was supported by grant FPU13/01475 from the Spanish Ministerio de Educacion, Cultura y Deporte (MECD). This work was supported in part by the Spanish Ministerio de Economıa y Competitividad (MINECO) and FEDER funds under grant BFU2015- 64380-C2-2-R. L.R.P. and J.-P.T. were supported by the NIHR Newcastle Biomedical Research Center awarded to the Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University. M.K. and R.B. were supported by the Engineering and Physical Sciences Research Council of the United Kingdom (EP/K026992/1). R.B. was also supported by (EP/S001433/1) and the Medical Research Council of the United Kingdom (MR/N015037/1). Data collection and sharing for this project was funded by the Alzheimer s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2- 0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and generous contributions from the following organizations: AbbVie, Alzheimer s Association; Alzheimer s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Alzheimer s disease es_ES
dc.subject Diffusion MRI es_ES
dc.subject Structural brain connectivity es_ES
dc.subject Network centrality es_ES
dc.subject Computational modeling es_ES
dc.subject Machine learning es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Structural connectivity centrality changes mark the path towards Alzheimer's disease es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.dadm.2018.12.004 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UKRI//EP%2FK026992%2F1/GB/Modelling Human Brain Development/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UKRI//MR%2FN015037%2F1/GB/Computational modeling of retinal development/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UKRI//EP%2FS001433%2F1/GB/Innovation Fellowship: Computational modelling of cryopreservation of biological tissue/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NIH//U01AG024904/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MECD//FPU13%2F01475/ES/FPU13%2F01475/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//BFU2015-64380-C2-2-R/ES/ANALISIS DE TEXTURAS EN IMAGEN CEREBRAL MULTIMODAL POR RESONANCIA MAGNETICA PARA UNA DETECCION TEMPRANA DE ALTERACIONES EN LA RED Y BIOMARCADORES DE ENFERMEDAD/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Peraza, LR.; Díaz-Parra, A.; Kennion, O.; Moratal, D.; Taylor, J.; Kaiser, M.; Bauer, R. (2019). Structural connectivity centrality changes mark the path towards Alzheimer's disease. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring. 11:98-107. https://doi.org/10.1016/j.dadm.2018.12.004 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.dadm.2018.12.004 es_ES
dc.description.upvformatpinicio 98 es_ES
dc.description.upvformatpfin 107 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 11 es_ES
dc.identifier.eissn 2352-8729 es_ES
dc.identifier.pmid 30723773 es_ES
dc.identifier.pmcid PMC6350419 es_ES
dc.relation.pasarela S\405838 es_ES
dc.contributor.funder UK Research and Innovation es_ES
dc.contributor.funder U.S. Department of Defense es_ES
dc.contributor.funder National Institutes of Health, EEUU es_ES
dc.contributor.funder Medical Research Council, Reino Unido es_ES
dc.contributor.funder National Institute for Health Research, Reino Unido es_ES
dc.contributor.funder Engineering and Physical Sciences Research Council, Reino Unido es_ES
dc.contributor.funder Ministerio de Educación, Cultura y Deporte es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
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