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

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.

journal_name

Nat Commun

journal_title

Nature communications

authors

Young AL,Marinescu RV,Oxtoby NP,Bocchetta M,Yong K,Firth NC,Cash DM,Thomas DL,Dick KM,Cardoso J,van Swieten J,Borroni B,Galimberti D,Masellis M,Tartaglia MC,Rowe JB,Graff C,Tagliavini F,Frisoni GB,Laforce R Jr,Fin

doi

10.1038/s41467-018-05892-0

subject

Has Abstract

pub_date

2018-10-15 00:00:00

pages

4273

issue

1

issn

2041-1723

pii

10.1038/s41467-018-05892-0

journal_volume

9

pub_type

杂志文章

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