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Molecular reclassification of the spectrum of Alzheimer’s disease: Multi-omic, multi-modal models for diagnosis, risk stratification and prognosis prediction

Lead supervisor:  Dr Ivan Koychev 

Co-supervisor: Prof. Vanessa Raymont

Commercial partner: CFDX Ltd 

 

Neurodegenerative diseases are the 7th leading cause of death globally, and the number one cause of mortality in the UK. The lack of effective diagnostics has led to poor allocation of social support, disease management, and the failure of meaningful therapeutic development. As such neurodegeneration research is a key priority for the MRC.

The project will leverage two Oxford-based projects of international significance currently gathering biomarker data in Alzheimer’s disease (AD) and the current appetite for NHS memory clinic service change. The READ OUT programme will establish the real-world clinical utility of blood biomarkers in Memory Clinic populations (2024-2029). The complementary Deep and Frequent Phenotyping (DFP) study (completing in 2025) will provide a comprehensive biomarker dataset of early prodromal AD (blood, tau and amyloid PET, MRI, cerebrospinal fluid, EEG, retinal imaging, wearables). The PhD student will collaborate with cfdx, a company aiming to develop artificial intelligence (AI) based algorithms for the identification and prediction of progression of neurodegenerative diseases. cfdx has access to rich AI analysis pipelines and associated real-world clinical datasets, which will be used to maximise the READ OUT and DFP output.

The objectives of this project are to:

1. Establish a suite of advanced AI models to unify multi-omic, multi-modal biomarkers in the context of AD

2. Validate high-accuracy disease representations of AD, specifically involving:
    a. Multi-omic signatures of disease: blood-based proteomic and epigenetic markers alongside genetic risk factors.

     b. Multi-modal signatures of disease: comprehensive clinical and cognitive scores and frameworks, within advanced biomedical language AI tools

     c. Multi-modal algorithms of progression: generation of blood-based proteomic and epigenetic biomarkers against trajectories of gold-standard AD biomarkers (PET, MRI, Ab42/40 and ptau cerebrospinal fluid)

3. Translate the insights gained from objectives 1 and 2 to design a clinical validation framework and direct care pathway change that will support all those with AD, including those with complex presentations and comorbidities.

 

Apply using course: DPhil in Psychiatry

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