Translational Neuroscience & Dementia Research
The Translational Neuroscience and Dementia Research Group undertake translational research ranging from mechanisms to drug development, and from discovery to qualification of molecular and imaging biomarkers in both Alzheimer’s disease and Parkinson’s disease and in related dementia disorders. The group, led by Professor Noel Buckley, comprises molecular and cellular biology scientists, computational biologists and informaticians working with molecular, clinical and imaging datasets. We have three main areas of activity, all aiming towards secondary prevention of dementia. By understanding disease mechanisms we seek potential therapeutics; through discovery of biomarkers we hope to enable preventative trials, and with informatics we utilise large biological and clinical datasets in the support of translational neuroscience.
From mechanisms to drug development
Dementia is one of the largest unmet health needs of the 21st century. Over 50M people suffer from dementia, a figure that is predicted to rise to 150M by 2050 while the global cost is rising to over $1000B. Alzheimer's disease represents the most common cause of dementia, accounting for an estimated 60% to 80% of cases and as yet, we have no disease modifying therapies. To address this lacuna we focus on constructing a range of human stem cell models of neurodegeneration using iPSC technology, CRISPR-cas9 and CRISPRa/i related approaches and apply a range of multi-omics and image-based phenotype analysis (increasingly aided by AI-based analysis) to uncover underlying disease mechanism and construct novel therapeutic screens.
Blood based biomarkers to enable clinical trials
Alzheimer’s disease has a long prodromal period – a time when the pathological process is active in the brain but not yet causing substantial, if any, symptoms. If we could identify people in this pre-clinical phase then there might be a ‘window or opportunity’ whereby drugs would be more likely to be effective than later when the disease was more fully established and neurons were being lost. In this window of opportunity a disease modification that was effective would be in effect a preventative therapy. However, in order to identify people in this phase of disease for clinical trials and one day for intervention, then biomarkers are needed. We have chosen to focus our attention on searching for blood based biomarkers to complement the work of many other groups that has been so successful in identifying spinal fluid markers and using imaging, including PET imaging, as markers of disease. A blood based marker would be less invasive and more readily available than CSF or PET imaging. Using a range of approaches we and our collaborators have looked for such a biomarker in the proteome, the transcriptome, the epigenome and the metabolome. We have used a range of approaches in all of these studies in discovery and then replication and validation phase. Perhaps the most important contribution we have made is not just in the actual findings, many of which have been replicated by others, but also in the design of studies as we have moved away from a case-control and more towards an ‘endophenotype’ approach whereby we search for a biomarker in comparison to a continuous and quantitative indication of disease status. Using these technologies and this design we have got close to a set of markers to be used as a biomarker, most likely in combination with other specific markers of pathology.
informatics in translational research
Our informatics focus is on the applications of neural networks and bioinformatics to mental health care. In both our mechanisms and biomarkers work, we are analysing large datasets using a range of statistical approaches including machine learning. As a consequence of this informaticians and statisticians have come to play an extremely important role in the group. Our group has access to large datasets from population cohorts and other research studies as well as from routine care and are using these data to advance experimental medicine seeking preventative strategies for dementia.
The main technologies that we apply and develop in our informatics team are bioinformatics, artificial intelligence and high-performance computing. These methods are applied to data from experimental sources (i.e. genetics, transcriptomics, proteomics and metabolomics from human samples and iPSC cells) and hospitals or GP practices (i.e. Electronic Health Records and cohorts of volunteer patients). Bioinformatics and neural networks methods allow us to know which are the metabolic processes associated with neurological diseases, such that appropriate pharmaceutical targets and drugs can be developed.
Using hospital and GP data, artificial intelligence and neural networks allow us to extract from the text notes written by doctors what are the diagnoses, medications, symptoms and medical test results of millions of patients, which in turn can be analysed to evaluate the most efficient treatment per patient (personalised medicine), or whether certain drugs are serendipitously ameliorating psychiatric conditions (drug repurposing). By combining experimental and clinical data to validate laboratory results with real-world evidence, target or treatments have increased chances of succeeding in the final stages of clinical trials.
Over the coming year, our group will seek to accelerate work towards disease modification of dementia including:
- Expansion of the Deep and Frequent Phenotyping study; a very detailed multimodal biomarker study to identify markers of progression in preclinical dementia, alongside other trials focused on identifying and tracking earlier disease (New Therapeutics in Alzheimer’s Disease (NTAD) and MIcroglial CSF1R in Alzheimer’s disease (MICAD) studies)
- Further drug development programmes building on successful compound identification in primary and secondary screens
- Use of AI and novel CRISPR approaches to identify molecular mechanisms and cellular phenotypes driven by Alzheimer’s Disease risk genes.
- Validation and then qualification of blood-based biomarkers of dementia and preclinical disease
- Identification and replication of blood-based biomarkers for Parkinson’s disease
- Working to support the renewal of the Dementias Platform UK, as we are leading on the trial delivery framework and informatics components
- Developing a follow on to the European Prevention of Alzheimer’s Disease public private consortium and building on the European Medical Information Framework; a data aggregation and access programme
- Using medical informatics from electronic medical records to understand the role of inflammation in dementia aetiology
OXFORD DRUG DISCOVERY INSTITUTE
Alzheimer's Research UK funding for a multi-million pound Institute to accelerate progress towards new and effective treatments for Alzheimer’s disease and other dementias. Part of a network of Drug Discovery Institutes across the UK, Oxford Drug Discovery Institute develops novel targets for therapeutic intervention in neurodegenerative disease.
To find out more about the Oxford Drug Discovery Institute work please visit the website.
THE BRAIN HEALTH CENTRE
Oxford’s new Brain Health Centre, part of the Oxford Health Biomedical Research Centre, is an integrated research and clinical environment aiming to improve the diagnosis and management of mental health disorders. It is currently piloting high quality brain health assessments, using state of the art techniques such as MRI scans. Patients referred to the Brain Health Centre are routinely informed about research opportunities and their interest in taking part is recorded. There are plans to formalise the networking of similar Brain Health clinics around the country with the express purpose of reducing dementia incidence at scale.
To find out more please visit the Brain Health Centre website here.
CHAMPIONING DEMENTIA RESEARCH
Oxford Dementia and Ageing Research (OxDARE) is a collaboration of researchers and clinicians who champion research locally by encouraging public engagement and participation as well as researcher collaboration.
The ‘Friends of OxDARE registry’ is a list of members of the public who have expressed an interest in participating in future research. The OxDARE team are also happy to discuss ideas for public engagement activities. Researchers interested in accessing the register for research participants, or Patient and Public Involvement representatives, should email firstname.lastname@example.org.
VOLUNTEERING FOR RESEARCH
How to sign up to a register that lets researchers know you might be interested in taking part in their research:
To find out more about studies in Oxford and the Thames Valley, visit our site here
To find out more about nationwide studies, visit our site here
GSK / Oxford UK Functional Genomics Capability Build
University of Oxford and GSK have partnered to exploit functional genomics to transform our understanding of how genetics influences disease and enable the identification of novel and high quality genetically validated targets. We are using AI to identify AD cellular phenotype using gene-edited iPSC neural cells and to use these signatures to identify disease altering interventions.
King Abdullah University (KAU-OX)
In a large funding initiative from King Abdullah University, our department is working with the Drug Discovery Institute and the Big Data Institute to understand the epidemiology and the genomic risks of disorders that are common to South Arabia. This includes cardiovascular disease, diabetes and dementia, among others. We are developing new methods based on deep learning and machine learning.
John Black Charitable Fund and Rosetrees (JBCF)
In a project funded by Rosetrees and JBCF, we are using neural networks and bioinformatics to find novel genetic associations of Parkinson’s Disease, and better understand the patho-physiological mechanisms. This includes developing novel techniques able to train neural networks on very large datasets such as UK Biobank.
EMIF and EPAD
Innovative Medicines Initiative funding for investigating disease mechanisms: together the European Medical Information Framework (EMIF) and European Prevention of Alzheimer's Dementia (EPAD) consortia have provided the largest ever early disease cohort, which we are planning to extend in various forms.
Dementias Platform UK
Dementias Platform UK funding linking researchers with drug companies in sharing data to develop new ways to detect dementia in its early stages and conducting studies to measure the effects and effectiveness of new treatments.
Parkinson’s UK (MAP2PD)
Parkinson's UK Award to discover biomarkers for Parkinson's Disease to inform the development of new therapies, through the use of proteomics (the measurement of proteins) in people with PD.
Wellcome Trust (NIMA)
Wellcome Trust Strategic Award in neuroinflammation investigating how inflammation affects the course of Alzheimer's disease, and the potential for adapting anti-inflammatory drugs to help those affected by this form of dementia.
Virtual Brain Cloud (EU H2020)
In a large European consortium led by the Charité Universitätsmedizin Berlin, we are investigating how computational simulations and methods can be used to diagnose patients with Alzheimer's disease. Our role is to further investigate biomarkers of Alzheimer's disease, such that these can be incorporated into the simulations designed by collaborators in the consortium.
Miocrobiome in depression (NIH U19)
In a large consortium led by colleagues at Duke University, we are investigating the role of microbiome in depression, anxiety and sleep perturbations. Our role focuses on the use of neural networks applied to the multi-omics datasets gathered by the consortium, as well as providing further proteomics cohorts.
Metabolomics in dementia (MOVE-AD)
This is another large consortium led by Duke University, where we are investigating the metabolomics of dementia, and its intersection with inflammation and cardiovascular disease. Our task is to bring machine learning and neural networks to the pool of methods used by the consortium.
Janssen Pharmaceutical (Mandarin)
This is a large collaboration between Janssen Pharmaceutical and the University of Oxford. In a network of key studies between the Big Data Institute and the Department of Psychiatry, we are pioneering novel neural network methods to decode the information present in full genome sequences from 150,000 UK Biobank patients.