Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

Progressive diseases tend to be heterogeneous in their underlying aetiology mechanism, disease manifestation, and disease time course. Here, Young and colleagues devise a computational method to account for both phenotypic heterogeneity and temporal heterogeneity, and demonstrate it using two neurod...

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Autores principales: Alexandra L Young, Razvan V Marinescu, Neil P Oxtoby, Martina Bocchetta, Keir Yong, Nicholas C Firth, David M Cash, David L Thomas, Katrina M Dick, Jorge Cardoso, John van Swieten, Barbara Borroni, Daniela Galimberti, Mario Masellis, Maria Carmela Tartaglia, James B Rowe, Caroline Graff, Fabrizio Tagliavini, Giovanni B Frisoni, Robert Laforce, Elizabeth Finger, Alexandre de Mendonça, Sandro Sorbi, Jason D Warren, Sebastian Crutch, Nick C Fox, Sebastien Ourselin, Jonathan M Schott, Jonathan D Rohrer, Daniel C Alexander, The Genetic FTD Initiative (GENFI), The Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2018
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Science
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Acceso en línea:https://doaj.org/article/edb6d5c8fa064af8b4704e322938446c
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Sumario:Progressive diseases tend to be heterogeneous in their underlying aetiology mechanism, disease manifestation, and disease time course. Here, Young and colleagues devise a computational method to account for both phenotypic heterogeneity and temporal heterogeneity, and demonstrate it using two neurodegenerative disease cohorts.

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