Computational and Molecular Neuroscience
- Alzheimer's
- Clinical trial
- Dementia
- Dopamine
- Genetics
- Neuroscience
- Parkinson's
The Computational and Molecular Neuroscience Research Group is a multidisciplinary laboratory specialized on the intersection of computational and molecular methods to study neurodegenerative diseases. The computational methods entail mainly Artificial Intelligence and Bioinformatics, while the molecular side brings state of the art multi-culture iPSC models of disease and high throughput screening. We are especially interested in Alzheimer's and Parkinson’s disease, and how we can use the computational and molecular methods mentioned above to find new drug targets and therapies. We have three main areas of activity: better understanding disease to identify new therapies; discovering biomarkers to enable preventative trials; and validating findings in advanced cell models of disease.
Our Research
From mechanisms to drug development
Dementia is one of the largest unmet health needs of the twenty first 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.
Planned research
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
Our Team
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Noel Buckley
Professor of Neurobiology
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Alejo J Nevado-Holgado
Associate Professor
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Simon Lovestone
Professor of Translational Neuroscience; Senior Fellow in Innovation and Development
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Laura Winchester
Associate Professor
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Helen Rowland
Postdoctoral Researcher
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Andrey Kormilitzin
Senior Research Scientist
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Nathaniel Gould
Guarantors of Brain Non-Clinical Research Fellow
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Buddhiprabha Erabadda
Postdoctoral Researcher
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Upamanyu Ghose
DPhil Student
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Joshua Sammet
DPhil Student
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Qiang Liu
Honorary research scientist
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William Sproviero
Oxford-Janssen Human Genomics Fellow
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Vanessa Raymont
Associate Professor, R&D Director Oxford Health NHS Foundation Trust
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Ivan Koychev
Senior Clinical Researcher
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Niall Taylor
Bioinformatics Research Assistant
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Karen Mansfield
Senior Postdoctoral Researcher
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Nyla Haque
Trial Manager
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Jemma Pitt
DPhil Student
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Jasmine Blane
DPhil Student
CLU trafficking
COLLABORATIONS
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.
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 nationwide studies, visit our site here
Selected FUNDing
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.
Scripta Therapeutics
Michael J Fox Foundation
Alzheimer's Research UK