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

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 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 and Daniel C Alexander
Additional contact information
Alexandra L Young: University College London
Razvan V Marinescu: University College London
Neil P Oxtoby: University College London
Martina Bocchetta: University College London
Keir Yong: University College London
Nicholas C Firth: University College London
David M Cash: University College London
David L Thomas: University College London
Katrina M Dick: University College London
Jorge Cardoso: University College London
John Swieten: Erasmus Medical Center
Barbara Borroni: Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia
Daniela Galimberti: University of Milan, Centro Dino Ferrari
Mario Masellis: Sunnybrook Health Sciences Centre, University of Toronto
Maria Carmela Tartaglia: Centre for Research in Neurodegenerative Diseases, University of Toronto, ON
James B Rowe: University of Cambridge, Department of Clinical Neurosciences
Caroline Graff: Karolinska Institutet
Fabrizio Tagliavini: Istituto Neurologico Carlo Besta
Giovanni B Frisoni: University Hospitals and University of Geneva
Robert Laforce: Université Laval
Elizabeth Finger: University of Western Ontario
Alexandre de Mendonça: Faculdade de Medicina, Universidade de Lisboa
Sandro Sorbi: Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence
Jason D Warren: University College London
Sebastian Crutch: University College London
Nick C Fox: University College London
Sebastien Ourselin: University College London
Jonathan M Schott: University College London
Jonathan D Rohrer: University College London
Daniel C Alexander: University College London

Nature Communications, 2018, vol. 9, issue 1, 1-16

Abstract: Abstract The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique—Subtype and Stage Inference (SuStaIn)—able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer’s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 × 10−4) or temporal stage (p = 3.96 × 10−5). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-05892-0

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DOI: 10.1038/s41467-018-05892-0

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