NIHRDataInsights/HRCSData huggingface dataset:
Title: CoEN5028 Can a dysfunction of the basal ganglia and related low level nociceptive network underlie some central neuropathic pain symptoms in..
Funder: Medical Research Council

Abstract: Central neuropathic pain is a common symptom of Parkinson's Disease (PD), which can improve after deep brain stimulation of the subthalamic nucleus (DBS-STN). Both the reason why central neuropathic pain is so common in PD and why DBS-STN helps at alleviating them remains unclear. Our preliminary data suggest that the STN and the nociceptive network to which this structure is linked are dysfunctional, which could contribute to some unexplained central neuropathic pain symptoms in PD. The aim of this project is to assess the involvement of this nociceptive network in central neuropathic pain symptoms in PD as well as elucidating the effect of DBS-STN on this network. For that purpose, we will use a combination of clinical and pre-clinical approaches, namely 1) visualize (fMRI) and quantify (behaviour and electrophysiology) the consequences of painful stimuli in humans (PD patients' vs controls) and rodents (PD rat models vs sham rats) on this network; 2) study the consequences of DBS-STN and optogenetic manipulation of the STN on nociceptive perception and responses in rodents. We expect these complementary technical approaches to address a critical shortcoming in the existing knowledge on underlying mechanisms for pain as one of the most troublesome non-motor symptoms in PD.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: NEUROLOGICAL
Title: CoEN5020 Advancing adaptive deep brain stimulation for gait disturbances and freezing of gait in Parkinson's disease
Funder: Medical Research Council

Abstract: Episodic gait disturbances such as Freezing of Gait (FoG) are difficult to treat because they have a complex pathophysiology involving an interplay between motor and cognitive functions that remains poorly understood. A major roadblock to progress is that conventional treatments including continuous high-frequency STN-DBS treat gait disturbances as a relatively steady-state problem, with treatments being applied chronically with fixed stimulation parameters over long timescales. Such an approach is poorly adapted to the actual complexity of gait disturbances, which are multifactorial, episodic, and highly context or state-dependent over short timescales. We hypothesize that automatically modifying DBS parameters to match state-dependent locomotor demands could be a promising strategy for treating gait disturbances. We posit that a novel STN stimulation regime that promotes physiological, alternating patterns of activity within the STN will serve to reinforce the automaticity of gait, and protect against gait disturbances. We also propose that early detection of FoG will allow a shift to another stimulation regime that specifically terminates FoG. By potentially triggering two distinct stimulation regimes, one during gait to support a more physiological pattern and another at the onset of FoG, we can afford to utilise stimulation parameters that might not be optimal outside of gait.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: NEUROLOGICAL
Title: Elucidating the role of manganese in brain physiology and disease
Funder: Medical Research Council

Abstract: Aim: My work aims to establish the role of manganese (Mn) in neuronal physiology and disease with the view to identify novel therapeutic targets and treatments for Mn related disorders. Objectives: 1. Determine how Mn dyshomeostasis impairs brain activity and identify the neuronal subtypes affected by Mn imbalance. 2. Identify key molecular targets underlying Mn dyshomeostasis and elucidate hierarchical interactions between them. 3. Develop a Mn specific chelator with oral bioavailability that can reverse Mn neurotoxicity. Methodologies: 1. Study of Mn transporter mutant zebrafish (slc39a14-/- and slc39a8-/-) as models of Mn overload and deficiency: Whole-brain neuronal activity, neuroanatomy and neurochemistry mapping, in vivo calcium imaging, retinal immunohistochemistry, LA-ICP-MS, single-cell RNA sequencing and CRISPR/Cas9 genome editing. 2. Subtype-specific neuronal cultures from mutant zebrafish using FAC sorting of transgenic lines: study of the effect of Mn on cell biology (neuronal morphology, cytotoxicity, Mn distribution, Ca2+ homeostasis, oxidative stress, mitochondrial physiology, bulk RNA sequencing). Complementary in vivo analysis of mutant zebrafish using fluorescent probes, transgenic lines, and pathway inhibitors to assess their effect on the locomotor phenotype. 3. Preformulation studies of Mn chelators and prodrugs to design clinically relevant formulations. Neuropathological and behavioural characterisation of Slc30a10-/- mice to develop phenotypic readouts of Mn neurotoxicity and assessing the effects of compounds with suitable physiochemical and biopharmaceutical properties on neurological markers. Scientific and medical opportunities: This work will provide a clear understanding of the effects of Mn dyshomeostasis on key neuronal functions and its role in disease processes. The data on novel Mn ligands will be essential for the translation into preclinical studies and clinical trials.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: NEUROLOGICAL
Title: Developing a mechanistic rationale for alpha-synuclein targeting therapies in Parkinson's disease
Funder: Medical Research Council

Abstract: Parkinson's disease is the second most common cause of neurodegeneration with increasing prevalence but no cure. Accumulation and aggregation of a presynaptic protein called alpha-synuclein is causatively linked to neurodegeneration. Through a multifaceted study of human models of alpha-synuclein aggregation using transcriptomics, functional studies with CRISPR and spatial localisation with fluorescent probes, we aim to decipher how human neurons clear aggregates, counteract their damaging effects or communicate with other resident brain cells that survey the environment for toxins such as microglia. We will delineate how aggregated alpha-synuclein is targeted for degradation by ubiquitination in human neurons and investigate the interplay between alpha-synuclein degradation pathways under physiological and pathological conditions. We have generated iPSC-based co-cultures to model the interaction between microglia and neurons and found that human iPSC-derived microglia promote the clearance of intraneuronal alpha-synuclein aggregates. We will decipher whether this involves phagocytosis of aggregate-containing neuronal subcompartments or uptake and degradation of neuronally released aggregates. We will employ single cell RNASeq to identify the relevant microglial activation state responsible for this beneficial effect and the neuronal response to aggregation. We will combine CRISPRi or CRISPRa gene targeting and iPSC-modelling to systematically assess genes identified in our transcriptomic and biochemical studies and determine whether they modify the toxic effects of alpha-synuclein aggregates. Lastly, we will measure their expression in post-mortem Parkinson's brain using RNAScope to demonstrate relevance to the human condition. By improving our understanding of Parkinson's pathogenesis using human models of pathology we ultimately aim to identify new therapeutic targets to slow disease progression in patients.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: NEUROLOGICAL
Title: Genomic determinants of Multiple Sclerosis susceptibility in an ethnically diverse population
Funder: Medical Research Council

Abstract: Multiple Sclerosis (MS) is a complex autoimmune disease characterised by inflammatory neurodegeneration of the brain and spinal cord. Despite advances in our understanding of the pathobiology of MS and the advent of rationally-designed monoclonal antibody therapies, there is no cure for MS nor is there any effective strategy available for preventing the onset of disease. Consortium efforts have revealed over 200 autosomal loci which collectively explain a large proportion of MS heritability in individuals of European descent. However, it remains to be clarified whether the same genetic architecture accounts for MS susceptibility among individuals from other ethnic backgrounds. We intend to perform the largest genetic association study of MS in individuals of non-European descent in the UK. The main goal of the study is to delineate the genetic architecture of MS in a diverse UK population, which we expect will reveal both substantial overlap with, and interesting divergence from the architecture described in Europeans. We will achieve this goal by recruiting from multiple collaborating academic centres, the UK MS Register, the UK MS Society, and via specific patient-led groups. We will use control data from the diverse East London Genes and Health project, UK Biobank, and ALSPAC. To estimate ethnicity-specific effects of genetic variants on MS risk, we will use the complementary approaches of admixture mapping and GWAS controlling for local ancestry. We will interpret these findings using standard annotation techniques, polygenic risk score profiling, and mendelian randomisation. Altogether, we hope to extend the understanding of MS genetics in a diverse UK population, which has important biological and clinical applications for the understanding of disease pathogenesis, development of prediction algorithms, and overall for the representation of previously marginalised groups in contemporary genetic research.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;2.4 SURVEILLANCE AND DISTRIBUTION
Health categories: NEUROLOGICAL
Title: Piloting A Secure, Scalable, Infrastructure for AI Dementia Research On Routinely Collected Data
Funder: Medical Research Council

Abstract: AI approaches promise a revolution in healthcare diagnosis, prognosis, disease monitoring and predicting medication response. Indeed, and a wide range of approaches have been used in research (Pellegrini et al., 2018; Borchert et al., 2021). However, a gulf exists in the need for well curated 'clean' datasets in AI research, and the heterogeneous 'noisy' clinical and imaging datasets typical of healthcare. This fundamental disconnection between AI technology developers and the frontline of healthcare is a key roadblock preventing real-world impact. The solution is to connect developers with routinely collected data. Memory clinics represent the frontline of dementia healthcare services and are the ideal setting for prototyping solutions. Broadly speaking there are two approaches to facilitating AI analysis for healthcare: centralised and decentralised. We prototype and test one of each: a DICOM router for anonymising and exporting data from PACS to a centralised analysis platform, and a federated learning system that takes the algorithms to the data, working inside the NHS in a decentralised manner.


Research activity codes: 2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: NEUROLOGICAL
Title: Identification of therapeutic targets in C9orf72-linked FTD and MND
Funder: Medical Research Council

Abstract: The most common genetic cause of Motor Neuron Disease (MND) and frontotemporal dementia (FTD) are mutations in the gene C9orf72. Although the two pathologies share the same genetic cause, they trigger two very different diseases. Nevertheless, due to their common genetic cause, C9orf72-linked MND and FTD are modelled in vitro and in vivo as a single disease. The challenge is understanding how the same mutation leads to two different pathologies, whether the underlying driving mechanisms are the same and, therefore, can be targeted with the same therapeutic approaches. To solve this challenge, Dr Ferraiuolo's team at SITraN and Cerevance have come together to share complementary expertise and technologies. Dr Ferraiuolo has developed a human cell reprogramming protocol that retains important and distinct aspects of the two diseases and, therefore, likely to be a suitable model for target validation and drug discovery. Cerevance has optimised cutting-edge NETSseq (Nuclear Enriched Transcript Sort sequencing) technology to unravel disease mechanisms at the cell type specific level and developed novel drug development strategies. The consortium between Dr Ferraiuolo and Cerevance, through the secondment of Dr Myszczynska, aims to: 1. Use NETSseq to perform deep transcriptomic analysis of cortical and spinal tissue of glia and neurons from C9orf72 MND & FTD patients and controls, as well as C9orf72 MND & FTD patient and control reprogrammed astrocytes and cortical and motor neurons. 2. Apply bioinformatic analysis of said datasets showing impact of disease on specific cell types and network function / dysfunction 3. Use this information to select targets as potential novel therapeutic interventions 4. Biologically validate these targets using human derived disease relevant cellular systems 5. Pharmacologically validate these targets as potential approaches for novel therapeutic intervention.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;5.1 PHARMACEUTICALS
Health categories: NEUROLOGICAL
Title: ACT-PD: Accelerating clinical treatments for Parkinson's disease
Funder: Medical Research Council

Abstract: The wealth of mechanistic data that has emerged from genetics and experimental medicine has revealed dozens of new targets and drugs with promise as potential Parkinson's disease modifying therapies (DMTs); to evaluate these rapidly and efficiently is essential by avoiding the slow sequential trials and late stage failures seen to date. Trial designs that rapidly facilitate drug discovery/patient benefit have been achieved in cancer (STAMPEDE), infectious diseases (COVID-RECOVERY) and neurological diseases. A consortium of partners with requisite experience has been created to provide a solution for PD; UCL MDC, providing a large patient/clinician base and experience in trials; University of Plymouth, that has generated key research and UCL MRC Clinical trials unit that has successfully delivered the type of trials envisaged. The Cure Parkinson's Trust (CPT) having previously funded work at Plymouth to develop the proposal is an integral part of the consortium. International collaboration has been established by CPT with its International Linked Clinical Trials program; experts in PD meet annually to identify and rank candidates for clinical testing (Brundin & Wyse, 2019). They are then taken into clinical trials by CPT, involving multiple funding sources. Candidates tested in MAMS are thus evaluated, prioritized and endorsed by the global PD community. The application is for support to second a dedicated individual from CPT to continue to facilitate input and embed skills developed for the future. (MAMS)= multiple treatments tested in parallel arms compared against a single placebo control arm. At checkpoints, analyses determine whether treatments are safe and show enough promise to continue evaluation; if not removed/replaced. Three-year workplan, 3 key objectives: Infrastructure for a MAMS neuroprotective trial in PD: stakeholders build framework. Protocol - encompassing design, selection, biomarkers, outcomes Initiate MAMS in PD: a 'proof of concept'


Research activity codes: 5.1 PHARMACEUTICALS;6.1 PHARMACEUTICALS
Health categories: NEUROLOGICAL
Title: Building on Brains for Dementia Research (BDR): A UK Nervous Tissue Network (UKNTN) for the Twenty-first Century
Funder: Medical Research Council

Abstract: This network will pilot providing deeply phenotyped, multi-modal, integrated tissue and data, including linked in vivo clinical and biosample, autopsy and derived hiPSC, genomic and organoid data, from donors with diverse mental health and neurological diseases (and controls) from across the life course Work package 1 (participants from mental health and neurology) and WP2 (repeat CSF and blood biosamples) will use well-established methods we have delivered before. In WP3 the neuropathology reporting again follows established methods and will pilot provision of extra-CNS nervous tissue. WP4&5 extend current practices in BDR and existing work on improving tissue access which are not technically difficult In WP6 fresh human brain tissue from neurosurgery will be transported for immediate slicing for acute electrophysiology (whole cell patch recordings or MEA/calcium imaging). Other slices are preserved using an interface organotypic culture method. AAV transduction will be carried out on day 0. Slices can then be removed from the incubator at intervals for electrophysiology/immunohistochemistry studies, currently up to 28 days in vitro In WP7 we will generate hiPSCs and brain organoids from a set of well-characterised donors, selecting lines from 4 deeply-phenotyped healthy controls for extensive functional and genomic characterisation at multiple time-points. We will undertake cell-type-specific genomic analyses on matching organoid and post-mortem autopsy samples, enabling a unique comparison of transcriptional and epigenetic signatures. Furthermore, using DNA modification signatures of different neural cell-types we will determine the cellular origin of brain-derived cell-free DNA (cfDNA) using fluid biosamples (WP2) and post-mortem CSF WP8 (integrated informatics platform providing one-stop-shop for all network data) again extends existing expertise and techniques, including those being established for NHS Electronic Health Records linkage, for UKNTN subjects


Research activity codes: 1.5 RESOURCES AND INFRASTRUCTURE (UNDERPINNING);2.6 RESOURCES AND INFRASTRUCTURE (AETIOLOGY)
Health categories: NEUROLOGICAL
Title: Using artificial intelligence to mitigate scanner bias in brain disorders
Funder: Medical Research Council

Abstract: In 2017 brain-based disorders represented 14% of the global burden of disease. Imaging-based analyses have the potential to provide reliable diagnostic and prognostic markers for brain-related disorders. A number of successful applications to brain disorders have been reported. However, a critical challenge in bringing these machine learning applications to clinical practice is that the use of different scanners and acquisition protocols results in inconsistent measures of the brain. In some cases, scanner-related variability can blur or even eliminate clinically relevant information from the scans. A number of methods for mitigating inter-scanner bias, commonly known as data harmonisation, have been proposed. However, the consolidated harmonisation methods have limited translational value as they do not allow the harmonisation of individual images coming from a new unseen scanner, which is essential for a real-world application of machine learning. They typically need a statistically significant sample as a reference, therefore they cannot be implemented in a cross-validation design. To overcome this challenge, we developed Neuroharmony, a tool that can harmonise single images from unseen/unknown scanners based on a set of image quality metrics (e.g. intrinsic characteristics like signal-to-noise ratio, contrast-to-noise ratio, etc.) which can be extracted from individual images without requiring a statistically representative sample from each new scanner of interest. Neuroharmony was proven effective in reducing systematic scanner-related bias from the distribution of brain volumes of healthy controls. However, its generalizability to patient data is yet to be examined. In this project, we aim to demonstrate that Neuroharmony can be used to harmonise data collected from clinical samples while preserving disease-related variability.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES;4.5 RESOURCES AND INFRASTRUCTURE (DETECTION)
Health categories: NEUROLOGICAL
Title: Software with artificial intelligence-derived algorithms for analysing CT brain scans in people with a suspected acute stroke [DAP56]
Funder: Department of Health and Social Care

Abstract: Stroke is a serious life-threatening medical condition caused by severely compromised blood supply to the brain. Restriction or stopping of the blood flow to the brain causes limited flow of oxygen and nutrients to the brain leading to the death of brain cells. Two main stroke types can be distinguished i.e., ischaemic (caused by arterial blockage, e.g. atherosclerotic plaque or blood clot) and haemorrhagic (bleeding into the brain, caused by the rupture of a blood vessel). Ischaemic and haemorrhagic strokes account for 87.1% and 12.5% of all strokes in the United Kingdom (UK), respectively. In the year 2018-2019, there were 224,172 stroke hospital admissions in the UK. Initial assessment includes computed tomography (CT) brain imaging, to identify patients with ischaemic stroke who may benefit from rapid treatment with clot-busting drugs or thrombectomy (surgical removal of the clot)._x000D_ _x000D_ Timely and effective management of the patients with suspected stroke substantially impacts patients’ outcomes. Patients should be managed by trained medical staff preferably in designated specialised stroke units. However, some patients may initially be seen in setting where some treatment options (e.g. thrombectomy and neurosurgery) are not available._x000D_ _x000D_ Artificial intelligence (AI) derived software currently exists which is intended to facilitate the review of CT images of the brain in conditions such as stroke. This assessment will consider the clinical- and cost-effectiveness of using AI-derived software to assist with the review of CT brain scans compared with unassisted CT brain scan review by a neuroradiologist or other healthcare practitioner, to inform diagnoses and treatment decisions for patients presenting to or attending secondary care with a suspected acute stroke.

Lay abstract: The overall objective of this assessment is to evaluate the clinical and cost effectiveness of using AI-derived software to support the review of CT brain scans in acute stroke, in the NHS setting.

Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: NEUROLOGICAL