Key work during the first reporting period:
– Data collation/analysis plans (& best practice guidelines) in each neurological application
– Developed a suite of new state of the art data-driven disease progression modelling tools, including simulation framework for validation
– Prototyped a unified modelling framework
– Prototyped a software system for clinical use (dementia)
– Normal ageing models to inform disease models
– First models of disease progression in multiple sclerosis (MS), prion disease, and neurodevelopment
Key work during the second reporting period:
– Open-source software toolbox
– Enhancement of models: computational and technical
– Extensive evaluation of our model enhancements
– New models of MS progression
– Organised TADPOLE Challenge for forecasting Alzheimer’s: unique prospective design; £30K prize money; encouraged participation with live public webinars, open-source code, and an online community.
Key results during the third reporting period:
– Evaluated TADPOLE submissions (~90 worldwide). Allocated prizes. Marinescu, et al., (2020)
– Methodological updates extending capability of event-based models to handle high-dimensional imaging data (enabling automatic feature discovery)
– Characterised effects of fixed variables on Alzheimer’s progression and normal ageing
– Ageing-informed model for improved predictive inference in Alzheimer’s
– New model-based subtypes of MS, demonstrating utility for improving clinical trials: Eshaghi et al., Nature Communications (2021)
– New insight into prion diseases by revealing and characterising previously unknown subtype-specific differences in the spread of lesions
Key results during the fourth reporting period:
– Delivered an international workshop: CompAge2020 Computational approaches for ageing and age-related diseases. Content freely available at europond.github.io/compage2020
– New model-based subtypes of Alzheimer’s pathology: an international collaboration accepted in Vogel et al., Nature Medicine (2021). Potentially redefines the disease staging paradigm to in vivo (previously post-mortem) and to include subtyping. Provides mechanistic insight to inform drug development.
– Tested our clinical prototype with neurologists on real-world hospital data.
– Prototype software system for drug development in dementia, and for MS.
– Demonstrated translational utility of our models by training on research data and testing on hospital data (dementia).
– Delivered multiple data-driven models (and a web app) of normal ageing that characterise, for the first time, fixed-variable effects, model-based subtypes, and prediction of dementia cases in an asymptomatic population.
– Invented topological profiles of neurological disease, a characteristic combination of brain network descriptors that best describes pathology propagation. Provides new insight into biological mechanisms of Alzheimer’s, normal ageing, and MS.
– Delivered advanced models of prion disease progression that revealed important differences between traditional and model-based subtypes based on MRI, and generated mechanistic insight using spreading models.
– Delivered advanced models of neurodevelopment suggesting that: preterm birth causes a unique signature of both delayed and slowed brain growth; and that brain scans may not be a necessary component of patient management in preterm-born children and adolescents.
