Capital award for UK DRI at Imperial College London
Lead Research Organisation:
Imperial College London
Department Name: UNLISTED
Abstract
Alongside significant co-investment from Imperial College London, the expected outcome of this funding is the concluded refurbishment of a floor in the new Michael Uren with space for 64+ researchers. An interim solution at the Burlington Danes facility at Hammersmith campus is being used before completion of the final location at the Michael Uren, ready for occupancy by September 2019.
Additionally, £1.5m for procurement of capital equipment is being provided to assist the UK DRI in implementing its first scientific programmes (funding provided separately).
Together, the building and equipment will provide the location for, in the initial stages of 5 programmes, and then to grow significantly in number in subsequent years. The UK DRI as a whole will help to cement the UK’s world-leading position by also promoting innovate approaches and forging much closer collaboration and integration of on-going UK research efforts. The new institute has been established to lead the UK’s dementia research effort and forms a core part of achieving the Prime Minister’s Challenge on Dementia 2020.
Additionally, £1.5m for procurement of capital equipment is being provided to assist the UK DRI in implementing its first scientific programmes (funding provided separately).
Together, the building and equipment will provide the location for, in the initial stages of 5 programmes, and then to grow significantly in number in subsequent years. The UK DRI as a whole will help to cement the UK’s world-leading position by also promoting innovate approaches and forging much closer collaboration and integration of on-going UK research efforts. The new institute has been established to lead the UK’s dementia research effort and forms a core part of achieving the Prime Minister’s Challenge on Dementia 2020.
Technical Summary
The aim of this award is to support Imperial College London with capital investment for setting-up of one of six UK Dementia Research Institute (UK DRI) centres; in particular, the capital required for building, refurbishment and the procurement of equipment.
At present, 5 programmes have been selected planned for the UK DRI at Imperial College London and with scientific and operational leadership provided by its associate director, Professor Paul Matthews. The project at Imperial College London will involve refurbishment of a floor in the new Michael Uren with space for 64+ researchers. An interim solution at the Burlington Danes facility at Hammersmith campus is being used before completion of the final location at the Michael Uren, ready for eventual occupancy by September 2019.
The approach of the institute as a whole, of which the UK DRI at Imperial College London forms a core part, is to amplify and enhance, not replace, current dementia research efforts in the UK. The UK DRI will help to cement the UK’s world-leading position by supplying vital new funding for research, coupled to promoting innovate approaches and forging much closer collaboration and integration of on-going UK research efforts.
There is a gap in our knowledge of how the healthy brain functions and what leads to its degeneration. The UK DRI will fill this crucial gap that exists at the start of the dementia research journey. It will study the healthy brain and neurodegeneration in order to build new knowledge and understanding that will lead to new treatments. It will also proactively connect to existing clinical and population-level dementia initiatives – for example as being undertaken by the MRC Dementias Platform UK and through the NIHR TRC-D – to catalyse a unique national and strategic approach to confronting the dementia challenge.
In particular, the present research at the UK DRI at Imperial College London plans to look at the innovation theme, including: Individual variation in dementia within populations; Metabolic factors, microbiome and role of sleep; Glial-neuronal interactions; Novel bioelectronics technologies to modulate neurons and glia in sleep, neuroprotection and cognition Funding to these science programmes is provided separately.
At present, 5 programmes have been selected planned for the UK DRI at Imperial College London and with scientific and operational leadership provided by its associate director, Professor Paul Matthews. The project at Imperial College London will involve refurbishment of a floor in the new Michael Uren with space for 64+ researchers. An interim solution at the Burlington Danes facility at Hammersmith campus is being used before completion of the final location at the Michael Uren, ready for eventual occupancy by September 2019.
The approach of the institute as a whole, of which the UK DRI at Imperial College London forms a core part, is to amplify and enhance, not replace, current dementia research efforts in the UK. The UK DRI will help to cement the UK’s world-leading position by supplying vital new funding for research, coupled to promoting innovate approaches and forging much closer collaboration and integration of on-going UK research efforts.
There is a gap in our knowledge of how the healthy brain functions and what leads to its degeneration. The UK DRI will fill this crucial gap that exists at the start of the dementia research journey. It will study the healthy brain and neurodegeneration in order to build new knowledge and understanding that will lead to new treatments. It will also proactively connect to existing clinical and population-level dementia initiatives – for example as being undertaken by the MRC Dementias Platform UK and through the NIHR TRC-D – to catalyse a unique national and strategic approach to confronting the dementia challenge.
In particular, the present research at the UK DRI at Imperial College London plans to look at the innovation theme, including: Individual variation in dementia within populations; Metabolic factors, microbiome and role of sleep; Glial-neuronal interactions; Novel bioelectronics technologies to modulate neurons and glia in sleep, neuroprotection and cognition Funding to these science programmes is provided separately.
People |
ORCID iD |
| Paul Matthews (Principal Investigator) |
Publications
Smith AM
(2022)
Diverse human astrocyte and microglial transcriptional responses to Alzheimer's pathology.
in Acta neuropathologica
Venkataraman AV
(2021)
Boosting the diagnostic power of amyloid-ß PET using a data-driven spatially informed classifier for decision support.
in Alzheimer's research & therapy
Ward H
(2023)
Design and Implementation of a National Program to Monitor the Prevalence of SARS-CoV-2 IgG Antibodies in England Using Self-Testing: The REACT-2 Study.
in American journal of public health
Elliott P
(2023)
Design and Implementation of a National SARS-CoV-2 Monitoring Program in England: REACT-1 Study
in American Journal of Public Health
Climaco Pinto R
(2022)
Finding Correspondence between Metabolomic Features in Untargeted Liquid Chromatography-Mass Spectrometry Metabolomics Datasets.
in Analytical chemistry
He S
(2017)
tranSMART-XNAT Connector tranSMART-XNAT connector-image selection based on clinical phenotypes and genetic profiles.
in Bioinformatics (Oxford, England)
Eales O
(2022)
SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2.
in BMC infectious diseases
Gafson AR
(2020)
Neurofilaments: neurobiological foundations for biomarker applications.
in Brain : a journal of neurology
Datta G
(2017)
Neuroinflammation and its relationship to changes in brain volume and white matter lesions in multiple sclerosis.
in Brain : a journal of neurology
Faergeman SL
(2020)
A novel neurodegenerative spectrum disorder in patients with MLKL deficiency.
in Cell death & disease
Levin M
(2021)
Prioritizing the Role of Major Lipoproteins and Subfractions as Risk Factors for Peripheral Artery Disease
in Circulation
Wong N
(2022)
Machine learning to support visual auditing of home-based lateral flow immunoassay self-test results for SARS-CoV-2 antibodies
in Communications Medicine
Matthews PM
(2020)
E-health and multiple sclerosis.
in Current opinion in neurology
Evangelou E
(2021)
Alcohol consumption in the general population is associated with structural changes in multiple organ systems.
in eLife
Ramakrishnan NK
(2021)
Preclinical evaluation of (S)-[18F]GE387, a novel 18-kDa translocator protein (TSPO) PET radioligand with low binding sensitivity to human polymorphism rs6971.
in European journal of nuclear medicine and molecular imaging
Coffey S
(2017)
Protocol and quality assurance for carotid imaging in 100,000 participants of UK Biobank: development and assessment.
in European journal of preventive cardiology
Bishop CA
(2018)
Semi-Automated Analysis of Diaphragmatic Motion with Dynamic Magnetic Resonance Imaging in Healthy Controls and Non-Ambulant Subjects with Duchenne Muscular Dystrophy.
in Frontiers in neurology
Supratak A
(2018)
Remote Monitoring in the Home Validates Clinical Gait Measures for Multiple Sclerosis.
in Frontiers in neurology
Salloum RG
(2022)
Developing Capacity in Dissemination and Implementation Research in the Eastern Mediterranean Region: Evaluation of a Training Workshop.
in Global implementation research and applications
Ntusi NAB
(2019)
Cardiovascular magnetic resonance characterization of myocardial and vascular function in rheumatoid arthritis patients.
in Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese
Kolbeinsson A
(2021)
Tensor Dropout for Robust Learning
in IEEE Journal of Selected Topics in Signal Processing
Tarroni G
(2019)
Learning-Based Quality Control for Cardiac MR Images.
in IEEE transactions on medical imaging
Dong H
(2018)
Mixed Neural Network Approach for Temporal Sleep Stage Classification
in IEEE Transactions on Neural Systems and Rehabilitation Engineering
Nie L
(2017)
Inferring functional connectivity in fMRI using minimum partial correlation
in International Journal of Automation and Computing
Hällqvist J
(2023)
A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning.
in International journal of molecular sciences
Robinson R
(2019)
Automated quality control in image segmentation: application to the UK Biobank cardiovascular magnetic resonance imaging study.
in Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Wilman H. R.
(2017)
Characterisation of liver fat in the UK biobank cohort
in JOURNAL OF HEPATOLOGY
Lema A
(2017)
A Comparison of Magnetization Transfer Methods to Assess Brain and Cervical Cord Microstructure in Multiple Sclerosis.
in Journal of neuroimaging : official journal of the American Society of Neuroimaging
Datta G
(2017)
11 C-PBR28 and 18 F-PBR111 Detect White Matter Inflammatory Heterogeneity in Multiple Sclerosis
in Journal of Nuclear Medicine
Zuber V
(2021)
Leveraging Genetic Data to Elucidate the Relationship Between COVID-19 and Ischemic Stroke
in Journal of the American Heart Association
Georgiou AN
(2023)
Appraising the Causal Role of Risk Factors in Coronary Artery Disease and Stroke: A Systematic Review of Mendelian Randomization Studies.
in Journal of the American Heart Association
Meena D
(2024)
Body Mass Index and Hypertension as Mediators of the Association Between Age at Menarche and Subclinical Atherosclerosis: A Sex-Specific Mendelian Randomization Analysis.
in Journal of the American Heart Association
Lally PJ
(2021)
Unbalanced SSFP for super-resolution in MRI.
in Magnetic resonance in medicine
Calsolaro V
(2021)
Astrocyte reactivity with late-onset cognitive impairment assessed in vivo using 11C-BU99008 PET and its relationship with amyloid load.
in Molecular psychiatry
Matthews PM
(2017)
Advanced MRI measures like DTI or fMRI should be outcome measures in future clinical trials - NO.
in Multiple sclerosis (Houndmills, Basingstoke, England)
LaRocca NG
(2018)
The MSOAC approach to developing performance outcomes to measure and monitor multiple sclerosis disability.
in Multiple sclerosis (Houndmills, Basingstoke, England)
Gafson A
(2017)
Personalised medicine for multiple sclerosis care.
in Multiple sclerosis (Houndmills, Basingstoke, England)
Datta G
(2017)
Translocator positron-emission tomography and magnetic resonance spectroscopic imaging of brain glial cell activation in multiple sclerosis.
in Multiple sclerosis (Houndmills, Basingstoke, England)
Giovannoni G
(2017)
Is multiple sclerosis a length-dependent central axonopathy? The case for therapeutic lag and the asynchronous progressive MS hypotheses.
in Multiple sclerosis and related disorders
Meyer HV
(2020)
Genetic and functional insights into the fractal structure of the heart.
in Nature
Sargurupremraj M
(2020)
Cerebral small vessel disease genomics and its implications across the lifespan.
in Nature communications
Francis CM
(2022)
Genome-wide associations of aortic distensibility suggest causality for aortic aneurysms and brain white matter hyperintensities.
in Nature communications
Ward H
(2022)
Population antibody responses following COVID-19 vaccination in 212,102 individuals
in Nature Communications
Whitaker M
(2022)
Persistent COVID-19 symptoms in a community study of 606,434 people in England.
in Nature communications
Whitaker M
(2022)
Variant-specific symptoms of COVID-19 in a study of 1,542,510 adults in England.
in Nature communications
| Title | scFlow |
| Description | Open source pipeline for automated scRNASeq analysis |
| Type Of Material | Technology assay or reagent |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Acceleration of analyses |
| URL | https://nf-co.re/scflow |
| Title | Additional file 1 of A comprehensive study of genetic regulation and disease associations of plasma circulatory microRNAs using population-level data |
| Description | Additional file 1: Table S1. The list of 2,083 miRNAs characterised in this study (including 591 were well-expressed). Table S2. Baseline characteristics of study participants. Table S3. Genome-wide significant miR-eQTLs identified in this study. Table S4. miR-eQTLs explaining high proportion of variation in miRNA level. Table S5. Multi-SNP joint analysis for conditionally independent associations from GCTA-COJO. Table S6. Replicated miR-eQTLs in Nikpay et al. Table S7. Summary of replication of miR-eQTLs. Table S8. List of 4,310 replicated miR-eQTLs. Table S9. Functional annotation of miR-eQTLs. Table S10. List of 22 loci, miRNAs, and corresponding genes, and 19 loci harbored miRNAs with replicated miR-eQTLs across cohorts. Table S11. SNPs in miRNA genes that also affected miRNA levels. Table S12. miR-eQTLs located in the promoter region of miRNAs. Table S13. SNP-based heritability estimates for 2,083 miRNAs. Table S14. Overlap between cis-miR-eQTLs and gene expression QTLs (eQTLs). Table S15. Colocalisation analysis between plasma miRNAs and gene expression in whole blood (eQTLGen) and across tissues (GTEx). Table S16. miRNAs with shared eQTLs with their putative target genes. Table S17. Overlap and colocalisation analysis between cis-miR-eQTLs and pQTLs. Table S18. Overlap between trans-miR-eQTLs and pQTLs. Table S19. Overlap between trans-miR-eQTLs and pQTLs in Olink. Table S20. Overlap of miR-eQTLs, met-QTLs, linear regression, and colocalisation analysis. Table S21. GWAS traits associated with miR-eQTLs. Table S22. Association between miR-eQTLs in locus in chr9:136128546-136296530 and other omics/phenotypes. Table S23. Genetic instruments for miRNAs (FDR<0.1) for PheWAS and MR analysis. Table S24. FDR-significant association for PheWAS using single variant and cis-GRS. Table S25. Cis and extended-GRS for 17 significant associations in MR-PheWAS. Table S26. Full results for cis-MR analyses. Table S27. Full results for extended-MR analyses. Table S28. Full results for replication using large GWAS summary statistics. Table S29. Reverse-MR to test association between obesity-related traits and miR-543 and miR-329-3p. Table S30. Target genes of miR-543 and miR-329-3p associated with BMI or WHR. Table S31. Univariable MR analysis on the associations between miR-1908-5p and metabolites (Metabolon platform). Table S32. Univariable MR analysis on the associations between 12 candidate metabolites and the risk of benign neoplasm of colon. Table S33. MR-Bayesian Model Averaging to identify most likely causal metabolites using a range of prior probabilities. Table S34. Mediation analysis to quantify the proportion of miR-1908-5p on the risk of benign neoplasm of colon mediated by 1-palmitoyl-2-linoleoyl-GPE. Table S35. Multivariable MR between miR-1908-5p and candidate metabolites on benign neoplasm of colon. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| URL | https://springernature.figshare.com/articles/dataset/Additional_file_1_of_A_comprehensive_study_of_g... |
| Description | Biogen MiSL Study Collaboration |
| Organisation | Biogen Idec |
| Country | United States |
| Sector | Private |
| PI Contribution | Study design, analysis of data, interpretation |
| Collaborator Contribution | Study design, interpretation, funding of scanning |
| Impact | Ongoing |
| Start Year | 2019 |
| Description | Biogen MiSL Study Collaboration |
| Organisation | Invicro |
| Country | United States |
| Sector | Private |
| PI Contribution | Study design and clinical recruitment |
| Collaborator Contribution | Conduct of PET and analysis |
| Impact | Ongoing |
| Start Year | 2019 |
| Description | Biogen REM2 snRNASeq Collaboration |
| Organisation | Biogen Idec |
| Country | United States |
| Sector | Private |
| PI Contribution | Ascertainment and sequencing of nuclei from TREM2var brains |
| Collaborator Contribution | Bioinformatics for snRNASeq analysis |
| Impact | Pending |
| Start Year | 2019 |
| Description | Edmond J Safra Foundation and Lily Safra |
| Organisation | Edmond J Safra Foundation |
| Country | Liechtenstein |
| Sector | Charity/Non Profit |
| PI Contribution | Continuing dialogue with a major funder for clinical neuroscience research |
| Collaborator Contribution | Funding of my chair and junior research fellowships, two of which have been awarded to people who will become part of UK DRI |
| Impact | All of my outputs since 2015 should be attributed |
| Start Year | 2014 |
| Description | Nodthera Inflammasome Collaboration |
| Organisation | NodThera |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Assessment of novel potential therapeutics |
| Collaborator Contribution | Joint development of research design |
| Impact | None yet |
| Start Year | 2018 |