NIHRDataInsights/HRCSData huggingface dataset:
Title: MICA: New combination therapy against MDR TB targeting the respiratory chain
Funder: Medical Research Council

Abstract: Our strategy is to validate a new combination therapy approach that targets components of the M. tuberculosis (Mtb) respiratory chain, specifically cytochromes bcc and bd, ndh2 dehydrogenase and ATP synthase. Targeting the respiratory chain has been shown by us and by others, to be effective in killing both replicating and dormant Mtb, leading to sterilization of cultures in vitro, as well as cure of TB-infected animals and clinical efficacy. Because there is no known pre-existing resistance due to mutations in genes encoding respiratory chain components, drugs targeting these enzymes would be effective against MDR-TB. Bedaquiline, a new TB drug targeting ATP synthase, demonstrates bactericidal activity in MDR TB patients, providing clinical validation for ATP synthase and respiratory targets more broadly. TB treatment always consists of multi-drug regimens, to maximize efficacy and minimize emergence of resistance to individual drugs. Recent data, including our own, indicates that simultaneous targeting of more than one component of the respiratory chain, can result in a synergistic and dramatic bactericidal effect. Through our medicinal chemistry programs, we have identified several compounds that inhibit each respiratory chain component. With our collaborators, we have also developed predictive in vitro and in vivo assays, which comprise an ideal tool box for evaluation of this combination-targeting concept. We propose to leverage our unique domain expertise, combination of tools and compounds to identify the most promising target pairs or groups and to provide critical pharmacological validation. We will also use pharmacokinetic-pharmacodynamic modelling to determine whether synergistic/additive anti-Mtb activity we demonstrate, is predicted to lead to clinically measurable benefits. Finally, we will evaluate whether the described combination strategy has the potential to overcome existing resistance mechanisms and reduce the emergence of de novo resistance.


Research activity codes: 5.1 PHARMACEUTICALS
Health categories: RESPIRATORY
Title: The role of aberrant membrane trafficking in pulmonary fibrosis
Funder: Medical Research Council

Abstract: Idiopathic pulmonary fibrosis is a chronic fibrosing parenchymal lung disorder that is uniformly fatal. Because early events in disease pathogenesis are not understood, current therapies are targeted to downstream pathways and are of limited efficacy. A mechanistic understanding of the disease from studying rare familial cases offers the potential to identify initiating events and ultimately novel targets for drug development. Mutations in surfactant protein-C (SFTPC) are an important cause of familial disease. My work suggests that the commonest pathogenic mutant, SFTPC-I73T, mislocalises to the cell surface and into recycling endosomes. This is due to failure of ubiquitination which targets wild-type SFTPC to the multivesicular body (MVB) for internalisation and cleavage. Expression of SFTPC-I73T also alters the structure of MVBs and thus may affect trafficking of other plasma membrane proteins relevant to pulmonary fibrosis pathogenesis. This research aims to provide a mechanistic understanding of the protein mistrafficking and cellular dysfunction caused by mutant forms of SFTPC including the common I73T mutant. I wish to explain the mechanism of ubiquitination failure and abnormal MVB biogenesis and understand the trafficking dynamics of SFTPC-I73T. I shall explore the functional consequences of MVB dysfunction on global endocytic trafficking, the plasma membrane proteome and their downstream signalling pathways. I shall test the physiological relevance of these findings by developing models of endogenous SFTPC-I73T expression using iPSC-derived type 2 pneumocytes and organoids derived from primary murine tissue. Taken together, the experiments outlined will elucidate the mechanisms by which mutant SFTPC impacts on membrane trafficking in type 2 pneumocytes and the functional consequences of this. I anticipate identification of previously unrecognised aberrant signaling pathways will be of relevance in furthering our understanding of sporadic disease.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: RESPIRATORY
Title: Non-communicable lung disease in Kenya: from burden and early life determinants to participatory inter-disciplinary solutions
Funder: Medical Research Council

Abstract: The Kenya National Strategy for non-communicable diseases highlights the impact of the non-communicable lung diseases asthma and chronic obstructive pulmonary disease (COPD) and makes their prevention and control national priorities. Studies in Africa reveal a high prevalence of COPD in adults unattributable to smoking. It is generally accepted that COPD in Africa is driven by pollution from biomass fuels, however the evidence is conflicting. Consensus in high income countries is that asthma and COPD originate in early life, being manifestations of reduced childhood lung function tracking into later life. It remains to be seen in Africa whether reduced adult lung function is a consequence of tracking of reduced childhood lung function and if so which factors reduce childhood lung function. We propose a cross sectional survey in two communities in Nairobi, Kenya. 1000 children aged 5-18years will be studied in the informal settlement of Mukuru and 1000 in the adjacent affluent Bura Bura. We will investigate whether air pollution, low birth weight and early life respiratory tract infections are adversely associated with lung function in children whose lungs are developing and highly vulnerable to environmental insults. Novel participatory methods will embed the study in the communities in order to give communities ownership and say over design, conduct and dissemination. Fieldworkers will administer questionnaires for respiratory symptoms, demographics, indoor/outdoor air pollution sources. Birth weight, and respiratory tract infections will be obtained from Child Health Cards. Spirometry will be conducted before and after a 6 minute run. In 100 children from each community, 24 hour personal air quality monitoring will be conducted. Pollution exposures for all children will be modelled. We anticipate this study will demonstrate that a substantial proportion of African children have reduced lung function, the age this is first evident and associated risk factors.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: RESPIRATORY
Title: bREATH-EASy: UNDERSTANDING THE ROLE OF INFECTION & EXTRACELLULAR MATRIX IN IDIOPATHIC PULMONARY FIBROSIS USING STEM CELL DERIVED ALVEOLAR CELLS
Funder: Medical Research Council

Abstract: In the UK 1 in 4 people die from respiratory disease, costing the NHS more than any other disease area. Poor access to lung samples, an inability to culture lung cells and a lack of animal models that faithfully reproduce human lung disease has left us with an inadequate understanding of how to diagnose and treat lung disease. These issues are exemplified by idiopathic pulmonary fibrosis (IPF), a disease where rapid scarring reduces lung function leading to death within an average of 3 years. Here we propose to apply our recently published stem-cell-based lung differentiation platform to model IPF and address 3 interlinked objectives: 1) Generate a hIPSC model of IPF to understand how SFTPC mutations affect cellular phenotype and gene expression in AE2 cells; no mutations have been described that cause IPF, however mutations in surfactant protein-C (SFTPC) lead to familial IPF. There are currently few robust human specific models to study familial IPF and the mechanism causing fibrosis remains elusive. 2) Model respiratory infection in-vitro to understand the effect of infection on AE2 cells carrying SFTPC mutation; Familial IPF patients have more frequent respiratory infections and have a 90% mortality rate per infection, how bacterial infection impacts and exacerbates the SFTPC phenotype is not well understood. 3) Model change in ECM composition to understand how ECM impacts cell phenotype; as IPF progresses the ECM changes dramatically, negatively impacting respiratory function. How these changes influence cellular behaviour and a potential pro-fibrotic feed-forward loop is not well characterised. Together, these objectives will address the poorly understood issues related to genetic risk factors, respiratory infection and ECM and how they individually and collectively impact the prognosis of IPF. This will provide opportunities for identification of novel diagnostic and prognostic markers as well as development of new therapies for IPF.


Research activity codes: 5.2 CELLULAR AND GENE THERAPIES
Health categories: RESPIRATORY
Title: UNICORN (Unified Cohorts Research Network): Disaggregating asthma
Funder: Medical Research Council

Abstract: The development of new methodologies for improving causal inference in epidemiological studies creates an opportunity for a step change in understanding mechanisms underlying asthma development. We propose that the best way to scale up research in asthma is to integrate unselected birth cohorts with patient cohorts and randomised controlled trials (RCTs) for joint analyses, as these different settings provide complementary windows on distinct aspects of understanding disease aetiology. UNICORN will form an alliance between the STELAR consortium of 5 birth cohorts aimed at studying asthma and allergies (in total >15000 participants), and patient cohorts with large numbers of carefully phenotyped patients with asthma (Breathing Together consortium, U-BIOPRED, RBH Severe Asthma cohort). In Workstream 1, we will build on earlier investments (eLab, tranSMART/eTRIX) to develop efficient scalable informatics solutions enabling integration, management, harmonisation and secure co-analysis of birth cohorts, patient cohorts, and RCTs. The development of an integrated data management and analysis platform at the heart of the UNICORN research engine will be a unique resource for the UK health science and will provide a template for implementation in other complex non-communicable disease areas where data integration provides the only realistic prospect of solving the complex and heterogeneous biology of these conditions. Workstream 2 will extend the detailed information collected from ante-natal period to adulthood in STELAR cohorts, with a routinely acquired data in primary care and hospital records, facilitating more sophisticated analyses. In Workstream 3, in an iterative discovery process, we will capitalise on a unique combination of expertise, well characterised birth and patient cohorts, and our novel research engine to promote the discovery of asthma endotypes, and identify and understand mechanisms underpinning such endotypes, thereby advancing stratified medicine.


Research activity codes: 2.4 SURVEILLANCE AND DISTRIBUTION
Health categories: RESPIRATORY
Title: DEFINING THE ROLE OF ZEB1-DEPENDENT EPITHELIAL-MESENCHYMAL CROSSTALK IN LUNG FIBROSIS
Funder: Medical Research Council

Abstract: The contribution of epithelial-mesenchymal transition (EMT) to human fibrogenesis is controversial. EMT, a dynamic and reversible biological process by which epithelial cells lose their cell polarity and down-regulate cadherin-mediated cell-cell adhesion to gain migratory properties, is involved in embryonic development, wound healing, cancer and fibrosis. Although studies have clearly shown co-localisation of epithelial and mesenchymal markers in fibrotic disease, the number of fibroblasts arising from epithelial cells was small in some lineage tracing studies, and so any pathogenetic role for EMT in fibrosis has been uncertain. It was recently reported that rather than contributing directly to the mesenchymal population, ZEB1-dependent EMT of alveolar epithelial type II (ATII) cells contributes to fibrosis via aberrant epithelial-fibroblast crosstalk. In addition to facilitate TGFbeta-induced myofibroblast differentiation, unpublished data suggest that ZEB1-dependent paracrine signalling also drives the recruitment of lung fibroblasts. This proposal aims to map the global protein network changes in fibroblasts crosstalking with ATII cells undergoing EMT, and identify the paracrine factor(s) responsible for the fibroblast recruitment. Building on the preliminary data from the custom siRNA screen establishing STK11/LKB1 as a key regulator of ZEB1 expression, the consequences of its knockdown or activation in ATII cells, and the impact on epithelial-fibroblast crosstalk will be determined. I will use disease models involving the established RAS-induced EMT model in ATII cells, primary human ATII cells, and primary human lung fibroblasts from IPF patients or control donors together with proteomics profiling combined with bioinformatics. The findings will be important for elucidating the mechanisms controlling the ZEB1-dependent epithelial-mesenchymal crosstalk, and for understanding how fibrotic disease, including idiopathic pulmonary fibrosis (IPF), arises.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: RESPIRATORY
Title: MICA: Korea-UK PRISM consortium: Establishing Precision Medicine in severe asthma
Funder: Medical Research Council

Abstract: Severe asthma is a heterogeneous disease where current treatments do not control asthma symptoms and exacerbations. An unmet need is an understanding of the phenotypes and mechanisms. Blood eosinophil count is used to identify suitability for Type-2 (T2)-targeted biologic therapies. The Korea-UK PRISM consortium will bring precision medicine to severe asthma by (i) validating the molecular phenotypes in UK and Korean cohorts (ii) defining the biomarkers in blood and exhaled breath that predict these molecular phenotypes (iii) determining responders to anti-T2 therapies and (iv) discovering therapeutic targets for T2-low pateints and testing targeted-antibody therapies. In 400 severe asthma patients, we will determine phenotype according to the biomarker/biomarker signatures obtained from U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes) cohort and expression of mechanistic pathways over 3 visits over one year. We will collect blood, exhaled breath condensate and sputum samples for multi-omics platforms, and in Korea, bronchial brushings. We will define the trajectory of molecular phenotypes and pathways using the transcriptomic-associated clusters in sputum transcriptome, and gene set variation analysis. In those receiving T2-targeted biologic therapies, we will find the best molecular signatures that predicting response to individual therapies. We will use model-based mixture models, or hierarchical/k-means clustering and trajectory classification to define phenotypic clusters grouping together patients sharing similar clinical traits. In studies in Korea, the predictor biomarker/biomarker signature for targeted anti-T2-high therapy will be confirmed and the effect of anti-T2-low antibody therapies in those with high levels of these cytokines/pathways will be examined. The PRISM Consortium will bring the right treatment to the right patient and newer effective treatments to severe asthma.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: RESPIRATORY
Title: The Role of the Extracellular Immunoproteasome in Acute Respiratory Distress Syndrome
Funder: Medical Research Council

Abstract: Inflammatory cell recruitment to sites of infection is a common and necessary process to remove bacteria in the lung. In some cases of disease, neutrophils arrive in significant numbers to the lung, and other organ sites, not as result of infection but as a result of a poorly-defined inflammatory process. In the case of acute lung inflammation, excessive inflammatory cell recruitment can lead to damage, which is mediated, in part, by the neutrophil. We have uncovered a recently described protein, the Extracellular Immunoproteasome, which may play role in bringing, or attracting, damaging levels of these inflammatory cells to the lung. We now wish to confirm further the role of Extracellular Immunoproteasome in inflammatory cell recruitment and lung injury using a novel Immunoproteasome inhibitor, QUB1034, in models of acute lung inflammation. We will also confirm a role for protease activated receptors (PARs) as a target for Extracellular Immunoproteasome-mediated inflammatory cell recruitment and injury using specific PAR antagonists. The very clear application of this study is in the targeting of Extracellular Immunoproteasome to regulate inflammatory and injury in disease, particularly lung disease, although there is a potential role for this Extracellular Immunoproteasome-mediated pathway in other inflammatory disease processes. Future studies looking at the evaluation of the Extracellular Immunoproteasome QUB1034 inhibitor in lung disease in collaboration is a very real possibility as we are set-up to carry out such studies in Queen's Belfast as part of the UK Respiratory Translational Research Partnership.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: RESPIRATORY
Title: Detecting clinical deterioration in respiratory hospital patients using machine learning
Funder: Medical Research Council

Abstract: Background and aims: Early warning scores are composite scores based on routinely measured clinical observations such as pulse, blood pressure and respiratory rate. They are designed to detect deteriorating patients in hospital but currently used scoring systems lack sensitivity and specificity in patients with respiratory conditions. We aim to understand how early warning scores perform in a real-world setting in respiratory patients, and to develop and validate an improved scoring system for this patient group. Research methods: Stage 1: We will survey all alerts triggered by a high early warning score in respiratory in-patients at Nottingham University Hospitals NHS Trust over a 3-month period. We will determine through case note review what investigations and interventions were performed as a result of the referrals. This will be used to develop a coding system for common events and interventions. Stage 2: Clinical observation data will be extracted from hospital systems for the approximately 22,000 admissions to adult respiratory medicine services from 2015-19. 1000 cases in which the emergency team was called at least once will be clinically annotated with reference to the case notes to capture clinically significant events requiring an intervention. The cases will be anonymised and split into a training dataset (750 cases) and a validation dataset (250 cases). Stage 3: The training dataset will be analysed using machine learning methods including logistic regression, support vector machines and anomaly detection in order to develop novel diagnostic models for detecting clinical deterioration in respiratory patients. The best performing diagnostic models will be tested using the validation dataset and their performance compared with the currently used National Early Warning Score. The area under the receiver operating characteristic curve will be the primary measure of diagnostic accuracy.


Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: RESPIRATORY
Title: Evaluating the burden of climate-related respiratory disease using high resolution spatiotemporal models
Funder: Medical Research Council

Abstract: The Earth's climate is changing and temperature levels across the globe are rising as anthropogenic factors including greenhouse gas (GHG) emissions from transportation, power generation and other uses of fossil fuels warm the planet. Changes in temperature could aggravate respiratory diseases directly or by exacerbating the effects of factors such as ozone that are associated with these diseases. Recent projections of future GHG emissions predict a mean temperature increase between 1.1 and 6.4C by the end of the 21st century. Most previous studies have focused on mortality using aggregated data. They employed time series models using temperature projections at low geographical resolution, ignoring local temperature fluctuations such as the effect of urban heat islands in which urban areas are warmer than their surroundings. In addition, the health impact and costs of climate-sensitive diseases have received hardly any attention so far. The aim of this project is to develop a framework of analysis based on high-resolution Bayesian spatiotemporal models and economics to estimate the climate-related respiratory disease burden. In particular, I will use nationwide respiratory health data and daily spatially-resolved temperature to estimate the effect of extreme temperatures on respiratory health in the UK. I will also quantify the future burden of temperature-related respiratory health using Bayesian evidence synthesis methods, while propagating the different sources of uncertainty, such as future GHG emission scenarios. Lastly, I will develop a web application to communicate the resulting maps and costs to public health experts and stakeholders. The impact of the project is manifold: it provides a better understanding of the climate-related respiratory disease burden, proposes a methodology that can be extended to other drivers of global disease and pays particular attention to disseminating the results through user-friendly web-applications.


Research activity codes: 2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT
Health categories: RESPIRATORY
Title: MICA: iTraXS (intra Tracheal Multiplexed Sensing): an optical sensor equipped endotracheal tube
Funder: Medical Research Council

Abstract: Incorrect endotracheal tube (ETT) cuff inflation pressure causes a number of significant problems for intubated patients. If pressure is too high this can result in tracheal injury. Around 3% of intensive care patients intubated for >48hrs suffer tracheal stenosis due to the cuff impairing mucosal perfusion, resulting in 1900 tracheal resections/yr (UK). Tracheal inflammation by the same mechanism results in moderate to severe sore throat and voice change in ~50% of all intubated patients (0.5m/yr UK). If cuff pressure is too low this causes harm through increased pulmonary aspiration of fluid materials, a major contributing factor in ventilator associated pneumonia (VAP). Tracheal pressure injury is avoidable if contact pressure and its effect on mucosal perfusion are monitored, enabling appropriate cuff inflation and personalised care. We prototyped the world's first optical fibre sensor equipped tracheal tube: iTraXS to address this unmet clinical need. We successfully demonstrated simultaneous measurement of mucosal contact pressure and perfusion in animals and conscious human volunteers using sensors incorporated into an ETT. Contact pressure and ischaemia were measurable for different cuff inflation levels. The prototype comprises: a disposable sensorized tube measuring pressure and perfusion at a single position; an electronic unit containing light sources and signal interrogators; a display/user interface and operating software. The system has MHRA no objection but is not fully CE compliant with medical device regulations or usable by clinicians independent of engineer support. Our aim is to develop this device to be ready for clinical trials. This project will expand the number and functionality of sensors; develop regulatory compliant software and hardware; investigate mass manufacturing processes; validate performance in the laboratory and an animal model; obtain MHRA no objection; develop health economic and commercial models; and capture additional IP


Research activity codes: 5.3 MEDICAL DEVICES
Health categories: RESPIRATORY