NIHRDataInsights/HRCSData huggingface dataset:
Title: Understanding non-communicable diseases (NCD) and the role of infection in Africa: building a partnership to generate big data
Funder: Medical Research Council

Abstract: Global burden of disease estimates suggest NCD are overtaking infectious disease as the leading cause of adult mortality in Africa. Obesity, diabetes, hypertension and associated lifestyle risk factors are rising in urban and rural settings as populations age and urbanise. HIV-related cancers and those of infectious aetiology including liver and cervix, are highly prevalent, representing a higher fraction of total NCD burden in Africa than elsewhere. In future, cancers such as breast, lung and colon, will be increasingly important as countries undergo demographic transition. This is a critical time point to understand the epidemiology, phenotypes and determinants of NCD. NCD data from LMIC are predominantly from small studies using differing methods. Evidence from adequately powered, "big" data platforms, of population-level data, is urgently needed to understand the burden, distribution and determinants of NCD and the intersection with HIV and other important infectious diseases. We propose to set up an African Non-communicable Disease Longitudinal data Alliance (ANDLA) to address this gap: working with policy makers and experienced research partners; bringing together partners with NCD data collected in demographic surveillance sites to address important questions relevant to our setting. This will enable a greater understanding of the current status of chronic NCD, provide evidence for future prevention and management strategies and build a platform for multi-site intervention development, monitoring and evaluation and health systems research. Longitudinal data are key to understanding disease progression, trends and contribution of risk factors to mortality. We will analyse markers of cardio-metabolic mortality risk; develop and validate risk scores; and conduct analyses of HIV-related cancer mortality. Scientific advisory groups will inform future work which may include asthma, chronic kidney disease, disabilities, injuries, epilepsy and mental health.


Research activity codes: 2.4 SURVEILLANCE AND DISTRIBUTION
Health categories: GENERIC HEALTH RELEVANCE
Title: Towards an Integrated Global Transport and Health Assessment Tool (TIGTHAT)
Funder: Medical Research Council

Abstract: Urban land transport has positive (physical activity) and negative (road traffic injuries, noise and air pollutants) side effects. Studies in high income cities found substantial population health benefits from mode shift to active travel, with physical activity (PA) dominating. However, our work in Brazil, India, and Malaysia identifies a more varied picture, with a larger burden and trickier trade-offs. In this project we lay the basis for a globally applicable stochastic synthesis engine with a user friendly interface, to support evidence based decision making on transport and health. A key challenge is data comparability and quality. Our international, multidisciplinary team will assess what data is available and develop approaches for mapping (calibrating) available to desired data, while representing propagated uncertainty. We will undertake integrated health impact simulation modelling for 3 Indian cities and Sao Paulo, Brazil, using sensitivity analysis to inform future empirical work. We will test counterfactual scenarios assuming changes to mode choice and land use. We will evaluate travel behaviour data for future modelling studies in further Latin American, India, and sub-Saharan settings. We will query the Google Street View (GSV) API to estimate ratio(s) of traffic modes in several cities. We will build an ecological model to predict travel time mode split and self-report PA from GSV data, and explore mapping to objective PA. The applicants have previously combined and imputed data to estimate RTIs by mode at the national level. We will now do this at the urban level. For AP we will develop a simple method for estimating the transport's contribution to AP using global databases and compare this to detailed analysis in several cities. This project lays the foundation for an analytic modelling framework to estimate multiple outcomes of interest under counterfactual scenarios with respect to a major determinant of population health.


Research activity codes: 2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS;3.2 INTERVENTIONS TO ALTER PHYSICAL AND BIOLOGICAL ENVIRONMENTAL RISKS
Health categories: GENERIC HEALTH RELEVANCE
Title: Assessing health risks associated with exposure to household and ambient air pollution in rural and urban China
Funder: Medical Research Council

Abstract: Air pollution (comprising household [HAP] and ambient air pollution [AAP]) is a major cause of premature death globally. In China and other low- and middle-income countries (LMICs), HAP has decreased gradually, but AAP has increased significantly from rapid industrialisation and urbanisation. Existing estimates of air pollution on health risk in LMICs have been extrapolated from studies in Western populations where the source and patterns of exposures differ substantially. Reliable of health effects of air population should include changing exposure patterns (from HAP to AAP) and time delay from exposure to disease onset, which will be best addressed by large prospective cohorts with detailed lifestyle (e.g. smoking), high quality air pollution data and linkage to disease outcomes. Our long-term plan is to apply cutting-edge approaches to enhance exposure data already collected in 0.5M China Kadoorie Biobank (CKB) adults to assess the health effects of air pollution across 10 diverse urban and rural areas in China. We propose a 2 year collaborative feasibility study to evaluate enhancements in exposure assessment before scaling up across all of CKB. We will measure real-time ambient and household fine particulate (PM2.5) and carbon monoxide, using wearable and static devices, for 300 CKB participants from 3 (2 rural, 1 urban) regions, each for two 5-day periods at different times of the year. We will develop methods to assign individual ambient PM2.5 levels in 1 urban region (Suzhou) by linking geocodes of residential addresses to an exposure model constructed using national air monitoring and satellite remote sensing data. Such data will be related through individual-based time-series analyses to a range of disease outcomes to yield initial evidence about health risks of air pollution. Data collected and experience gained should provide the basis for a large-scale and long-term research programme into the hazards of air pollution in China and other LMICs.


Research activity codes: 2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT
Health categories: GENERIC HEALTH RELEVANCE
Title: MEthods and Tools for Assessing the Health Impacts of Transport: modelling study (METAHIT)
Funder: Medical Research Council

Abstract: Urban land transport has positive (physical activity) and negative (road traffic injuries, noise and air pollutants) side effects. Studies in high income settings have found substantial population health benefits from mode shift to active travel, with physical activity dominating. In this project we will develop the methods that will lay the basis for the next generation health impact assessment (HIA) tools. Our experience developing and applying the Integrated Transport and Health Impact Modelling Tool (ITHIM) has highlighted many of the gaps in the field, which we will work to fill in this project. Central to the project is our development of an open source stochastic integrated simulation framework within which we can use uncertainty methods such as value of information to investigate how uncertainty around input parameters and model structure impact policy relevant results. This will be used to guide future empirical studies. We will develop and integrate new health impact pathways (noise, nitrogen dioxide (NO2) air pollution) and improve methods for existing pathways of physical activity, particulate matter air pollution, and road traffic injuries. We will develop methods to generate more realistic counterfactual scenarios, based on which trips have the highest propensity to shift mode. We will use individual-level data to better capture between-individual heterogeneity in the scenarios and evaluate wider range of outcomes. We will compare simpler and more advanced chronic disease modelling methods, and investigate the potential for applying calibration factors to the simpler, but more generalisable, method. The framework will be implemented on a case study for England, with estimates on travel patterns, physical activity, injury risk, air pollution, noise exposures, and disease burdens estimated down to the local authority level. We will collaborate with stakeholders to disseminate findings and methods, and test them in other locations.


Research activity codes: 1.4 METHODOLOGIES AND MEASUREMENTS;2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT
Health categories: GENERIC HEALTH RELEVANCE
Title: Open-cohort designs for cluster-randomised trials in institutional settings: A methodology bolt-on to DCM-EPIC
Funder: Medical Research Council

Abstract: Our aim is to improve the information from, and efficiency of, randomised trials of complex health and social care interventions in care homes, inpatient wards and clinics treating patients with chronic conditions. We will develop practical guidelines and supporting documents (including training material) for trialists wishing to design an open-cohort cluster-randomised trial (OC-CRT) in an institutional setting. Although there are examples of its use, the statistical literature on OC-CRTs is extremely sparse. To facilitate comparisons, Feldman and McKinlay suggested a "unified model", encompassing closed-cohort and cross-sectional CRTs. However, this makes strong assumptions, the impact of which is unclear, particularly if applied to open-cohorts with informative entry and exiting. For example, it assumes constant correlation among repeated measurements, one time scale (time from randomisation), independent Gaussian random effects with common variance, stability of intervention effects across time, uninformative cluster sizes and a target population with a steady state. Methods for handling missing data are also unclear. Building on literature relating to epidemiological studies, which tends to assume survival outcomes, we will analytically derive multilevel linear models that progressively relax the assumptions made by Feldman and McKinlay, exploring the inferences possible from these models. We will consider different methods for handling missing data arising from discharge or death (unconditional, pattern-mixture or joint outcome models or regressions conditioning on being alive) for OC-CRTs where data collection is continuous or at discrete follow-ups. We will derive formulae for calculating the sample size required for a range of illustrative examples. Next, we will perform simulation studies evaluating our methods in terms of bias and precision. Finally, we will address potential barriers to the uptake of these designs, alongside methods developments.


Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES;8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: Identifying and Measuring Knowledge Spillovers of Health Service Delivery Interventions: A Network Analysis Approach
Funder: Medical Research Council

Abstract: Health care policies may have spillover effects beyond their intended objectives. For example, a financial penalty policy intended to reduce readmission rates for acute myocardial infarction, heart failure, and pneumonia in the US Medicare was associated with reductions in readmission rates for conditions that were not targeted by the policy, and a payment incentive scheme to improve quality of care in the North West of England was associated with improvements in the quality of care for patient groups that were not targeted by the scheme. Although the existence of such spillover effects is increasingly being recognised, there is a lack of understanding of the mechanisms by which such spillover effects occur, and how spillovers can be measured and identified empirically. This proposal takes a novel approach to the identification and measurement of knowledge spillovers by integrating the economic analysis of knowledge spillovers, social network analysis and state of the art methods for social network mapping that have made it possible to map social networks using administrative data sources only without the need for a costly qualitative data collection. The proposed research develops a methodology for identifying and measuring knowledge spillovers of health service delivery and policy interventions at the level of the health care professional. Using two recurrent empirical examples of quality improvement incentive schemes, the project 1) Characterises intra- and inter-organisational networks of health care professionals using administrative data to identify testable mechanisms of knowledge spillovers. 2) Tests these mechanisms by measuring spillover effects and estimating the determinants of knowledge spillovers in social networks of health care professionals, and 3) Analyses the implications of knowledge spillovers for programme evaluation of long term effects


Research activity codes: 8.2 HEALTH AND WELFARE ECONOMICS;8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE
Health categories: GENERIC HEALTH RELEVANCE
Title: Defining the function of histone ADP-ribosylation in DNA repair and genome integrity
Funder: Medical Research Council

Abstract: We address three outstanding questions regarding ADP-ribosylation of histones in regulation of double strand break (DSB) repair: a) Which histones are modified in response to DSBs in vivo and at what sites? b) What is the consequence of defective histone ADP-ribosylation on DSB repair? c) What factors interact with ADP-ribosylated histones and how do they regulate DNA repair in humans? A major bottle-neck for the ADP-ribosylation field is the lack of an experimental model in which ADP-ribosylation sites can be mutated at endogenous histone loci to decipher the molecular basis of how these modifications regulate DNA repair. The ability to manipulate histone genes in Dictyostelium offers a unique platform to address these questions. Established mass spectrometry (MS) approaches will identify specific sites on Dictyostelium histones ADP-ribosylated in response to DSBs in vivo. Gene replacement technology will introduce mutations at these sites identified by MS into endogenous histone genes, to generate histone ADP-ribosylation defective strains. The ability of these strains to perform DSB repair will be assessed using standard assays including plasmid integration assays to determine NHEJ and HR efficiencies, sensitivity to DNA damage, enrichment of repair factors at damage sites. These strains offer a rigorously controlled platform to identify factors that interact with ADP-ribosylated histones, which can then be extended to humans. Immunoprecipitation of nucleosome complexes from wild-type and histone ADP-ribosylation defective strains will identify factors that specifically interact with ADP-ribosylated histones by comparative MS. The orthologues of novel proteins identified in Dictyostelium will be verified by enrichment at DSBs in human cells, disrupted by CRISPR/Cas9 genome editing, and the functional consequences on human DSB repair assessed using standard assays, including repair efficiencies, enrichment of repair factors at DSBs etc.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: GENERIC HEALTH RELEVANCE
Title: Elucidating the mechanisms that govern replication restart efficiency and fidelity
Funder: Medical Research Council

Abstract: Replication stress is a major cause of genomic instability that drives tumorigenesis and other pathological states. Exactly what the stress entails, and how this results in genomic instability, is the subject of intense investigation, with altered patterns of replication origin firing, aberrant processing of replication forks stalled at barriers, and genomic instability wrought by recombination-dependent replication thought to be major contributory factors. Despite their importance, our understanding of the molecular basis of these processes is still rudimentary and far from complete. In pioneering work, we have established a unique set of tools to investigate the processing of perturbed replication forks at site-specific barriers in the model eukaryote fission yeast. Using these tools, together with state-of-the-art in vivo biochemistry, advanced microscopy and cutting-edge high-throughput single molecule DNA fibre (HTDF) analysis, we aim to deliver a comprehensive description of the factors that influence the processing of a blocked replication fork through its collapse, restart by recombination, and progression as a restarted fork. In particular we will focus on identifying the factors that affect the efficiency and fidelity of these processes, and determine whether they are similarly required for processing broken replication forks. Replication fork failure is thought to trigger the firing of nearby dormant replication origins to aid the timely completion of genome duplication. However, it is unclear whether this is an active or passive process, and whether it depends on wide-scale induction of a checkpoint response or can be triggered locally by the collapse of a single fork. By HTDF analysis we will answer these important questions, establishing the pattern of replication origin firing in response to site-specific collapsed and broken replication forks, and determining whether recombination dysfunction alters the patterns observed both locally and genome-wide.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Integrin control of epithelial polarity and glandular tissue morphogenesis
Funder: Medical Research Council

Abstract: Cell polarity is a defining feature for all epithelia, required for accurate cell division, differentiation and morphogenesis. In glandular organs polarization of epithelia results in the formation of lumens, which are essential for tissue function. Using the mammary gland we previously showed that cell interactions with the basement membrane through beta1 integrin is essential for the orientation of apicobasal polarity and lumen formation. Much of our understanding into mechanisms of lumen formation, come from the use of isotropic epithelial organoids, which incompletely reflect tissue organization in vivo. All secretory tissues are bi-layered with epithelia surrounded by myoepithelia and a basement membrane. How epithelia integrate signals from their microenvironment composed of other cell types to orient their polarity axis is poorly understood. We will focus on dissecting the role of integrins in tissue polarity from the different mammary cell lineages and establish how they synergize to achieve full function. To achieve this beta1 integrin gene function will be perturbed from each mammary compartment in vivo, using Cre-Lox technology and tissue architecture will be analysed in 3D using lightsheet imaging. Mammary organoid cocultures that recapitulate in vivo tissue architecture more accurately will validate in vivo data and will be used to deconstruct the mechanism further. Live imaging will be used to understand how integrins control correct positioning of the two mammary lineages. Downstream of polarity orientation we will define integrin pathways involved in lumen expansion by exploring beta1 integrin function in fluid transport through regulation of ion transporters, tight junctions and membrane permeability. By elucidating how BM signals regulate tissue organization we will contribute significantly to solving key questions about integrin control of cell polarity and potentially expose integrins as biomarkers that may be altered within precancerous tissue.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Decoding differentiation of cell lineages in the early human liver for application in stem cell differentiation and cell programming
Funder: Medical Research Council

Abstract: Human liver cell lineages are urgently needed in regenerative medicine and for drug safety assessment. Great interest has focused on differentiating human pluripotent stem cells (PSCs) or directly reprogramming fibroblasts in vitro. However, PSC-derived cells deviate from normal by the equivalent of early liver development. Reprogramming cell fate is still in its infancy, with a strong sense that we do yet have all the optimised factors. We hypothesise that in depth knowledge of early human liver development will transform these challenges. Our objective is to provide comprehensive molecular understanding of the different hepatic lineages and how they arise. We will do this by defining a framework of early human liver development with key markers; highly practical new information for benchmarking PSC-derived cells in vitro. The markers will inform our next goal: to discover the full molecular phenotype of the critical liver cell-types as they arise. This will include the full repertoire of growth factors from the perihepatic mesenchyme and the first detailed knowledge of native human hepatoblasts, early hepatocytes, ductal plate cells and cholangiocytes. We will do this by single cell RNA-seq and computational biology and expect to discover distinct cell sub-populations currently unaccounted for in PSC differentiation protocols. Based on previous experience, we expect the data to lead us to mechanistic understanding and critical transcription factors for reprogramming. By the end of the project, we will have discovered and disseminated the first molecular basis for lineage differentiation within the human embryonic liver. We will have pilot-tested some of the emergent key factors in our comprehensive platforms of PSC differentiation and cell reprogramming. Together, we hope our freely available knowledge will act as a watershed that unlocks major improvements in PSC-to-liver and hepatic reprogramming research amongst the international community.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE