NIHRDataInsights/HRCSData huggingface dataset:
Title: Spinal cord stimulation for gait dysfunction in Parkinson's disease
Funder: Medical Research Council

Abstract: Gait dysfunction and postural instability are one of the main causes of morbidity and mortality in Parkinson's disease (PD). They lead to falls and loss of independence, and are a major milestone of disease progression in PD. They are often unresponsive to dopamine replacement therapy and treatment options are limited. It is thought that degeneration of cholinergic brainstem nuclei may be responsible for PD gait dysfunction, but attempts to enhance brainstem cholinergic pathway using cholinesterase inhibitors or pedunculopontine nucleus deep brain stimulation have produced mixed outcome. Spinal cord stimulation (SCS) is an established treatment for chronic back/neuropathic pain. It has been noted that PD patients with back pain experienced an improvement in their gait after SCS. A small number of PD patients without back pain have since received SCS, and beneficial effects were reported in some of them. However, these studies were small and unblinded, and there were many unanswered questions including optimal stimulation parameters, appropriate outcome measures, mechanisms of actions, and potential placebo effects. In this pilot study, I aim to study 5 PD patients with treatment resistant gait dysfunction and offer them SCS. These patients will receive either sham stimulation or a range of stimulation parameters over a 12-month period. The patients and assessors will both be blinded to this. These patients will undergo detailed multi-modal quantitative gait analysis to study the effects of intervention. They will also receive transcranial magnetic stimulation and electroencephalogram (EEG) to study the neural effects of spinal cord stimulation, including cortical excitability and brain oscillations.


Research activity codes: 6.4 SURGERY
Health categories: NEUROLOGICAL
Title: Retromer Recycling in Neuronal Plasticity Maintenance
Funder: Medical Research Council

Abstract: Neurons of the central nervous system must maintain, over protracted periods, a careful balance between morphological stability and synaptic plasticity. Chimaerins (CHNs) are proteins that constrain neuronal morphology plasticity via inhibition of the GTPase Rac1. We have identified that CHNs may work in conjunction with the intracellular protein complex retromer, to support synaptic function. Retromer regulates intracellular sorting of cell surface receptors, and is linked to the pathogenesis of both Parkinson's and Alzheimer's diseases. Our data suggest that a1-CHN drives accumulation of the retromer subunit VPS35 in an endosomal compartment, suggesting a link between CHN function and retromer-recycling of synaptic receptors. We propose a model in which a CHN-retromer pathway both internalises active signalling membrane from cell surface, and recycles membrane back to synapses in association with synaptic receptors. By this twin functionality - pruning weak connections and consolidating relevant synapses - a CHN-retromer mechanism would embody the characteristic behaviour of a healthy learning network, and also support long term synaptic function. We plan an exploration of the proposed interaction between a1-CHN and retromer, focusing on the molecules involved, and the functional consequences of the mechanism. Using cell culture, super-resolution microscopy and biochemical techniques, we will examine: - The biological relevance of the complex, confirming that what we have documented in preliminary data is a real and relevant interaction. - The molecular components of the putative CHN-retromer complex, including specific retromer components (VPS35, VPS26, VPS29) and sorting nexins. - Any interaction of the complex with the actin polymerising WASH complex and the functional role of this interaction. These studies will lay the foundations for a future wider examination of retromer involvement in neurodegenerative diseases.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: NEUROLOGICAL
Title: AI gets real: using routine clinical data and Artificial Intelligence to predict worsening of Multiple Sclerosis despite treatment (AIMS)
Funder: Medical Research Council

Abstract: Multiple Sclerosis (MS) is a common cause of disability in the developed world. Despite progress in MS treatments, significant variability in disability accumulation remains. Prediction of long term outcomes and best use of all data acquired in clinical practice to define the profile of patients at risk for disability and cognitive impairment accrual, are both unmet needs. This project draws on the neurobiological heterogeneity of people with MS and aims to use computational models to identify specific profiles of people with MS who fare worse over the long term despite first-line treatment. We propose a time to event analysis for predicting progression of MS by comparing three different models and incorporating AI state-of-the-art techniques. We will exploit available real world data using AI and build on the experience of research groups at NIHR Nottingham BRC and the Nottingham AI program. We will use deep learning techniques (convolutional neural networks) to extract whole-image features from baseline MRI scans of more than 800 patients with MS, members of the Nottingham MS Society Register. We will use a classical machine learning based regression model, a deep learning model and compare their predictive accuracy with a classical statistical frequentist model incorporating clinical and classical MRI features. After internal validation, we will then externally validate the models in two large independent data sets of which one is a RCT which examines response to moderate versus high potency treatments in MS (DELIVER-MS). The results will help apply for further funding for large deep phenotype collecting (genetics,microbiome) biomarker studies targeted to these biotypes, and explore how they can be integrated into routine clinical practice.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: NEUROLOGICAL
Title: Development of a stratification tool to predict Disease Modifying Treatment response in Paediatric Onset Multiple Sclerosis
Funder: Medical Research Council

Abstract: 14 disease-modifying treatments (DMTs) for multiple sclerosis (MS) are approved in UK, but most have not been trialled in children. The only paediatric trial so far identified benefits and risks different from those in adults. My aim, by partnering with Prof Ciccarelli, is to identify individual predictors of treatment response in Paediatric MS and correlate the response with long-term age-expected cognitive outcome. This, together with knowledge of side effects, will help individuals choose the best medication for them. The project will comprise i)a prospective cohort of 80 children (with 700 adults) with MS between 10-17y (studied over 24months)who initiate any DMT in England. Demographic and life-style factors (nicotine and UV exposure, diet and obesity) will be recorded, clinical examination, serological (PBMCs, Vitamin D) and immune markers (neurofilament-light chain (NfL) levels in serum (and CSF if possible), MRI scans and cognitive profile will be collected. Genetic factors will be obtained ii)a retrospective cohort of 150 children with MS on DMTs (with 1700 adults). Analysis of their clinical, paraclinical, genetic (HLA-DRB1*15) and MRI markers will provide predictors into individual treatment response. Neuropsychology assessment is assessed every 2 years as standard of care. The secure database OPTIMISE (Optimisation of Prognosis and Treatment in MultIple SclErosis), will be used to import patient information and clinical scans. Treatment response will be assessed by both "No Evidence of Disease Activity" on MRI and also by the presence or absence of a clinical relapse. Pharmacovigilance data will be captured by presence or absence of a serious adverse event from the DMT. This will be analysed together with patient demographics and genetic factors. Outputs will be i) identification of factors that predict both a specific treatment response and a worse cognitive outcome ii) a registry and iii) evidence based guidelines for treatment choice in Paediatric MS


Research activity codes: 6.1 PHARMACEUTICALS
Health categories: NEUROLOGICAL
Title: Computational models for clinical trial design in Huntington's disease
Funder: Medical Research Council

Abstract: A major barrier to successful disease modifying therapy (DMT) development in Huntington's disease (HD) is its biological and phenotypic heterogeneity, which makes it difficult to define suitable biomarkers and inclusion criteria for clinical trials. Recent advances in the fields of machine learning and computational modelling have made it possible to infer patient-specific information from large and varied datasets. Such information has the potential to improve clinical trial design, and hence accelerate the development of a DMT for HD. This project will use a large multi-modal imaging and clinical patient dataset, to: i) construct a baseline array of computational models for patient stratification, using standard statistical and machine learning methods; ii) use more advanced machine learning methods to identify potential disease subtypes and model patient-specific trajectories of key macro-scale biomarkers for early-stage clinical trial design; iii) define subtype-specific models of micro-scale protein dynamics in HD for DMT design. Specifically, this project will develop methods in subtyping, deep probabilistic modelling, and trajectory modelling that have been successfully used in Alzheimer's disease. This project will use the largest combined multi-modal HD dataset - comprised of three separate cohort studies - to evaluate the potential of machine learning techniques in multi-centre studies, which are essential for DMT verification in a rare disease like HD. The proposed framework will naturally extend to Phase 3 trials, and different types of disease, making it a model for next-generation clinical trial design.


Research activity codes: 2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: NEUROLOGICAL
Title: MRC Transition Support. CDA. Jill O'Reilly.
Funder: Medical Research Council

Abstract: The research in the CDA aims to develop a computational characterization of the roles of different brain systems in the formation and tuning of predictive models of the environment, which preidcts signals measurable with human neuroimaging. The challenges involved in the research were: [Step 1] to design suitable tasks and models for which the necessary computations could be clearly defined at an algorithmic level; [Step 2] to posit circuit-level mechanisms that could underlie the computations; [Step 3] to build physiologically specified (biophysical) models of those mechanisms; [Step 4] to conduct drug studies that are safe, ethical and sufficiently powered to test the hypotheses. So far, we have made good progress with steps 1-3, establishing a variety of paradigms and models in which predictions at the cells-and-circuits level can really be tested in human neuroimaging, and we have found some interesting results. However, we have only recently started to attempt drug manipulations (mid-data collection for one study; two more studies planned). Although in some respects I have made good progress (one joint first-author paper in Science and one last author paper in eLife), I do not quite have enough last-author papers to secure a major research grant to follow on from the CDA. However, a further three major last-author studies are in the data analysis/write-up stage. Once these studies are published, I would hope to be in a much better position to apply for further funding. My lab has experienced significant disruption over the CDA period including three moves of location (two involuntary) and two periods of maternity leave (for me). The crucial benefits of Transition Funding would be to protect 50% of my time for research (I have a permanent contract but it will involve a lot of teaching), so I can be present in the lab and focus on completing projects and writing grants, and to allow me to retain my post doc which is essential for continuity.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: NEUROLOGICAL
Title: Developing novel neuroimaging approaches to investigate the neural antecedents of tics and brain correlates of premonitory urges in Tourette syndrome
Funder: Medical Research Council

Abstract: TS is a neurological condition characterised by motor and vocal tics. Many (~90%) individuals with TS report that their tics are preceded by 'premonitory sensory/urge phenomena' (PU) that are described as uncomfortable bodily sensations that precede the execution of a tic and are experienced as a strong urge-to-tic. We consider it timely and also highly important to investigate the functional anatomy and pathophysiology of the urge to tic in TS using novel neuroimaging approaches that overcome the difficulties associated with trying to study the neural antecedents of movement (tics) in scanning environments in which movement is typically avoided at all costs. Most TS patients can suppress their tics quite effectively, although tic suppression is associated with increasing levels of discomfort which is experienced as a strong urge-to-tic. This suggests that we might successfully scan many TS patients during tic suppression, however this would make investigating the neural antecedents of tics challenging. Our solution to this will be to develop: (a) an approach termed 'Multi-echo Sparse Paradigm Free Mapping' (ME-SPFM) in which we obtain fMRI BOLD measurements associated with PU that occur in TS without the necessity for tic expression. Unlike in conventional fMRI studies, ME-SPFM can detect the onset and spatial distribution of BOLD events in the brain without the need for prior timing information. Using this approach, we will accurately and reliably identify functional brain activity that is associated with the occurrence of PU in circumstances where tics are effectively suppressed (i.e. there is no tic to use as an external timing event). (b) an approach to imaging the neural antecedents of tics in TS, based upon novel, 'wearable', MEG technology developed at the University of Nottingham. This has the advantage that MEG signals, measured at the millisecond scale, can be reliably recorded - even when an individual is executing large movements


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: NEUROLOGICAL
Title: The brainstem signals dual motivational valence following ingestion
Funder: Medical Research Council

Abstract: Hunger is an unpleasant need state which increases arousal and appetitive behaviours. Thus, it is hypothesised that part of the reason we are motivated to eat is to remove the negative emotional valence. In addition, we normally eat until we are sated, which provides a feeling of pleasant "fullness" (positive motivational valence). Thus, in behavioural terms, the termination of a meal is dependent on both negative (the reduction of negative valence) and positive (the increase in positive valence) reinforcement. Alternatively, we can lose our appetite and stop eating in other circumstances, such as when we feel ill or nauseous, which also produce a negative motivational valence. We have shown that artificial stimulation of brainstem neurones can induce positive or negative valence depending on which projections are activated. We will demonstrate the importance of parallel pathway using both gain of function and loss of function studies. Since we have already identified brainstem neurones which respond to different modes of gut signalling, we believe that we will be able to map the different pathways to states of satiation, nausea and gastric illness. We also predict that these pathways will converge on the tegmental-striatal system, and so we will measure dopamine transients in the striatum using the latest "dLight1" technology. Furthermore, using fibre photometry to record neuronal activity in freely behaving mice, we can see that gut-derived satiation signals switch off "hunger-inducing" AgRP neurones in the hypothalamic arcuate nucleus, whereas signals which cause aversion do not. We will investigate these pathways by chemogenetically controlling brainstem neurones while recording the activity of AgRP neurones in vivo.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: NEUROLOGICAL
Title: Dysregulated WNT signaling as a driver of motor neuron loss in Amyotrophic Lateral Sclerosis
Funder: Medical Research Council

Abstract: Amyotrophic Lateral Sclerosis (ALS) (also known as motor neuron disease), is a fatal neurodegenerative disease characterized by a loss of motor neurons (MNs). Understanding why these neurons die is critical if we hope to develop therapeutics to halt or reverse the relentless neurodegeneration in ALS patients. My preliminary work using in vitro ALS models have uncovered a role of WNT signalling in causing ALS MN death. This proposal will detail the mechanism of how WNT dysregulation in ALS MNs leads to MN death. I will also explore the role of WNT in MN homeostasis and investigate whether targeting WNT is a viable approach to improve MN function in ALS. Although, most ALS cases are sporadic, ~10% of cases have a genetic basis with mutations found in genes with diverse functions including SOD1(free radical scavenger) and FUS(RNA processing). SOD1 is the second most common cause of genetic ALS, while recent evidence has uncovered shared pathological links between FUS ALS and sporadic ALS. I have developed in vitro models of ALS-associated MN dysfunction using induced pluripotent stem cells (iPSCs) derived from ALS patients with mutations in SOD1 and FUS. My preliminary work utilizing these models uncovered that canonical WNT signalling is activated in both SOD1 and FUS MNs. Using bioinformatics analysis of independent gene expression datasets from familial FUS and TDP43 ALS MNs as well as sporadic ALS MNs, I uncovered that WNT activation may be a common theme in ALS. I will use the iPSC-based models I have developed to gain a mechanistic understanding into how WNT activation disrupts MN homeostasis and leads to MN dysfunction or death in ALS. These investigations will advance our understanding of the underlying cause of MN death in ALS and highlight WNT as a potential target to develop ALS therapeutics.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: NEUROLOGICAL
Title: Post-transcriptional regulation in motor and cognitive disorders
Funder: Medical Research Council

Abstract: Genome-wide analyses revealed that defects in control of alternative splicing are most frequently linked with human diseases. We recently uncovered the essential nuclear and cytoplasmic roles of the splicing factor SFPQ in motor circuit development and degeneration and found a novel type of splicing regulation, the cryptic last exon (CLE), normally repressed by SFPQ. This aberrant splicing event, often achieved at the expense of the normal variants, produces stable short transcripts, some of these encoding interfering proteins, perfect candidates to carry pathologies typical of neurodegenerative processes. Our initial study showed strong evidence for a key role of SFPQ in Amyotrophic Lateral Sclerosis/Fronto-temporal dementia (ALS/FTD) neurodegenerative processes. In the past months, unambiguous findings show that loss of SFPQ is an early hallmark across sporadic and familial ALS patient iPSC-derived motor neurons in culture, putting this protein at the centre of motor degenerative mechanisms. Our ongoing studies of newly identified "SFPQ patients" indicates that the protein is likely to be at the core of a wider variety of degenerative disorders, including neurodevelopmental syndromes. We therefore propose to use our unique animal models to understand how loss - or mutations - of SFPQ protein during neuronal maturation and in adult circuits, generates these CLE transcripts and identify the molecular and cellular consequence of CLE short transcripts on developing and adult neurons. These are of direct importance to develop early therapeutic avenues against neurodegeneration, targeting key pathogenic CLEs. In addition, better understand the CLE-generating novel splicing regulation is likely to have implications on a wider set of splicing-dependent pathologies such as some cancers.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: NEUROLOGICAL
Title: Magnetoencephalographic telemetry in epilepsy using OP-MEG sensors
Funder: Medical Research Council

Abstract: Currently, scalp electroencephalography (EEG) is the key non-invasive investigation in the diagnosis and treatment of epilepsy. However, it has a number of significant limitations, including spatial and temporal filtering and susceptibility to artefacts from muscle and movement. Magnetoencephalography (MEG) is an alternative non-invasive brain scanning technique that gives a unique window into whole brain function. MEG offers specific advantages over scalp EEG, including superior source localization accuracy and better immunity to muscle artefact. However current limitations of conventional (superconducting) MEG are 1) it is a one-size-fits-all scanner, which means sub-optimal sensitivity in a number of people 2) the scanner environment is unnatural and claustrophobic and subjects must remain still, a significant factor when considering epilepsy 3) Due to the restrictive environment, recording time for clinical MEG studies are briefer than EEG (1-2 hours) meaning that MEG recording of seizures, the most useful electrophysiological data for surgical planning, are rare 4) MEG systems are expensive and support intensive, as a result there are only 10 systems in the UK. As such the clinical benefit of superconducting MEG systems has been limited. The aim here is to bring a new type of MEG system (OP-MEG), which will be worn on the subject's head (allowing them to move freely whilst being scanned) into clinical practice. We expect OP-MEG to identify common electrophysiological abnormalities (e.g. epileptic spikes) with greater spatiotemporal accuracy than scalp EEG, and have much better immunity to muscle and motion artefact when recording seizures. OP-MEG will also make prolonged MEG recording of patients over several hours a possibility, a property not readily associated with traditional MEG. This technology has the potential to revolutionise how brain neurophysiology is performed in future.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: NEUROLOGICAL