NIHRDataInsights/HRCSData huggingface dataset:
Title: Identifying relevant studies for systematic reviews and health technology assessments using text mining
Funder: Medical Research Council

Abstract: There are two main components to this study: 1) a retrospective analysis of data from existing reviews; and 2) a prospective analysis involving the use of text mining in ongoing reviews. These analyses will be used to evaluate two new methods: screening prioritisation and automatic classification. As the use of these technologies and the development of validated methods for their use are in their infancy, an important part of the project is outreach: to build interest, capacity and enthusiasm for their use in the future. The retrospective analyses will simulate the conduct of screening using text mining utilising data from six completed EPPI-Centre reviews and subsequently from between five and eight ongoing reviews. Learning from the retrospective simulation studies will inform the parameters selected for the prospective studies and also to develop tools and metrics to evaluate their performance. Both text mining techniques will be available for prospective evaluation in EPPI-Centre reviews over the period of this project and by arrangement with reviews conducted by external organisations too. In selected reviews, searches will be more extensive than usual and we will also maintain a record of the studies that would have been identified using standard search techniques for comparison. In a systematic review we are less interested in predictive performance (the standard way of evaluating a classifier), but in the ability of the system - including human interaction - to identify all relevant studies as efficiently as possible. Wallace and colleagues have suggested two additional parameters, which we propose to use in addition to standard metrics: yield (the proportion of relevant studies identified) and burden (the total number manually screened). In reviews that screen everything manually, yield and burden are 100%. Successful automated approaches will reduce the burden of manual screening whilst retaining a yield of 100%.


Research activity codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: Probing the dynamics of agonist drug interaction with Cys-loop channels by single-molecule recording
Funder: Medical Research Council

Abstract: We will carry out ultra-low noise single channel recording of recombinant glycine channels activated by a series of agonists (with and without appropriate channel mutations). Kinetic analysis by time course idealization and global fitting of detailed activation mechanisms will be used to obtain microscopic equilibrium and rate constants, including the agonist microscopic affinity for the different states of the receptor. We will use in silico computational modelling, both to help us choose the agonists and the mutations to be tested and to interpret our results. Our homology model will be based on the structure of GluCl, a nematode channel 34% homologous to the glycine channel. We will use molecular dynamics to explore the conformational behaviour of the receptor, particularly the binding site. We will also dock series of ligands to the receptor to examine the conformational dependence of the bound states. Docking trials, whole-cell recordings and maximum open probability measurements will be used to select agonists suitable for full characterization, focussing on series of compounds, each series introducing small systematic structural differences in one moiety of the agonist molecule. If contaminated by glycine, agonists will be purified before experimental use. We will also mutate the channel, choosing, from the literature and our in silico work, binding site residues likely to interact with specific parts of the agonist molecules, and repeat the agonist experiments with these mutant channels. Thermodynamic cycle analysis will be carried out on equilibrium dissociation constant values obtained by single channel recording to map the direct interactions between agonist molecule and channel at rest and after activation. Should a particularly informative agonist or mutation give rise to data beyond experimental bandwidth, we shall engineer appropriate compensating background mutations in domains distant from the binding site to allow data collection.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;5.1 PHARMACEUTICALS
Health categories: GENERIC HEALTH RELEVANCE
Title: Role of DNA methylation in imprint maintenance in differentiated human cells
Funder: Medical Research Council

Abstract: Imprinted genes are exemplars of epigenetic control and are highly dependent on DNA methylation for their regulation. Abberant imprints are the cause of a number of human growth and neurodevelopmental syndromes and are a frequent occurrence in cancer. Despite this, functional assessment of the role of the maintenance methyltransferase in regulating imprints in humans has been lacking. By using stably integrated small hairpin RNA targeting the DNMT1 gene in hTERT-immortalised cells we appear to have generated the first normal human cell lines lacking imprinting at both paternally and maternally methylated ICR due to targeted loss of methylation. These provide a unique resource for examining the effects of loss of maintenance methylation on imprinted genes. We aim to characterise these cells more fully using genome-wide assays of DNA methylation and gene expression, a bank of targeted pyrosequencing assays designed specifically to interrogate the imprinted loci and the use of chromatin immunoprecipitation. This should greatly inform the clinical and research community as to the effects of loss of maintenance methylation in normal cells and help to establish if imprinted disorders are primarily caused by chromatin or DNA methylation changes. Additionally, we will use these cells to benchmark 5'-aza-2'-deoxcytidine (Aza) treatment with the effects of DNMT1 depletion in a normal cell line, of direct clinical relevance for the treatment of myelodysplastic syndromes and potentially for other disorders. Further hypomorphic cell lines will be created to determine if cells from different tissues share a common response to loss of maintenance methylation: we will also attempt to re-establish methylation at an imprinted locus in these and other imprint-free cells by rescue experiments. Finally, the experiments may identity novel imprinted regions in humans.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Investigation into sexual dimorphisms in autosomal gene expression due to sex chromosome complement effects rather than phenotypic sex
Funder: Medical Research Council

Abstract: Differences between males and females are normally attributed to developmental and hormonal differences between the sexes. We have recently demonstrated differences between males and females in gene silencing using a heterochromatin-sensitive reporter gene in vivo. Using 'sex-reversal' mouse models with varying sex chromosome complements, we found that this differential gene silencing was determined by X chromosome dosage, rather than sex. Genome-wide transcription profiling showed that the expression of hundreds of autosomal genes was also sensitive to sex chromosome complement. These genome-wide analyses also uncovered a novel role for Sry in modulating autosomal gene expression in a sex chromosome complement-specific manner. The identification of this additional layer in the establishment of sexual differences has important implications for understanding sexual dimorphisms in physiology and disease. This proposal will employ transgenic tools combined with high-throughput sequencing and bioinformatic analyses to unravel the molecular basis for this novel system. We will investigate the hypotheses that the sex chromosome effect on heterochromatin silencing and autosomal gene expression is due to: 1) the inactive X chromosome acting as a sink for heterochromatin factors and 2) overexpression of genes that escape X chromosome inactivation. Moreover, we have found significant enrichment within the subset of sex chromosome sensitive genes for genes that are also sensitive to the dosage of a key component of heterochromatin, HP1. These genes cluster in regions along the chromosome and bioinformatic analysis indicates that particular repetitive sequence motifs are enriched in their vicinity. We will investigate whether these genes are 'responders' to the sex-chromosome complement effect and whether the mechanism of response involves classical features of heterochromatin nucleated by repetitive sequences.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Investigating the biology of mitochondrial DNA disease transmission to enable affected families to have healthy children
Funder: Medical Research Council

Abstract: Either mitophagy (recycling of mitochondria) or clonal proliferation of mtDNA subpopulations may underlie the unpredictable transmission of mutant mtDNA. We propose that mtDNA turnover by mitophagy can be modulated to enhance purifying selection of normal mtDNA during early development. We will determine whether: 1) mitochondrial function influences mtDNA content of: a) "spare" human preimplantation embryos becoming available from families with mtDNA disease undergoing in vitro fertilisation b) mouse oocytes with impaired mitochondrial function 2) mtDNA synthesis occurs in: a) mouse and human oocytes maturating in vitro b) mouse and donated human preimplantation embryos using BrdU pulse labelling. This may reveal any contribution of clonal proliferation of mtDNA to "purifying selection"3) Modulators of mitochondrial recycling by mitophagy can be developed to enhance purifying selection. We will investigate and quantitate mitophagy in mouse pre-implantation embryos using transgenics with fluorescent organelles. We will cross mice with GFP targeted to LC3 in the autophagosomes against mice with DS-red targeted to mitochondria. Mitophagy is apparent by co-localisation of red and green signals in offspring (and this can be quantitated in cell lines using Imagestream, a technique combining flow cytometry and fluorescence microscopy, fig1). We will use this model to determine whether mitophagy: a) occurs in mouse oocytes and pre-implantation embryos b) can be driven by exogenous treatments c) is exacerbated in mouse models expected to modulate mitophagy, such as OPA1 knock down (required for mitochondrial fusion). 4) Purifying selection of wild type mtDNA in pluripotent cell cultures, heteroplasmic for pathogenic mtDNA mutants, can be driven by agents identified in (3). Ultimately we will use the mouse with fluorescent autophagosomes to investigate mitophagy in: a) nuclear and cytoplasmic transfer b) multiple disease model


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: GENERIC HEALTH RELEVANCE
Title: Tackling child health inequalities: a longitudinal cross-cohort and cross-country analysis of contemporary data to inform policy development
Funder: Medical Research Council

Abstract: Cross-sectional associations between socio-economic circumstances (SECs) and child health have been widely documented; however, there is a paucity of research exploiting the longitudinal data of contemporary cohort studies to explore how SECs and health relate over time, and the pathways through which SECs influence child health. Cross-cohort and cross-country comparisons also offer potential for understanding when and why inequalities in health emerge. Furthermore, little is known about the role of policy in reducing or exacerbating health inequalities, due in part to the general unsuitability of experimental research designs for evaluating policy effects. This study seeks to address these gaps. Data from two large and contemporary cohorts will be used to explore and contrast the social patterning of child health from birth to age 11 in the UK and Australia, using longitudinal methods. Absolute and relative inequalities will be estimated across the social gradient, for a number of SECs measures and several aspects of health (allowing for the interplay between physical and mental health). Then, focusing on a reduced number of health measures which are highly prevalent or socially distributed, I will examine and compare pathways through which SECs influence children's health in the two countries. Data from a contemporary women's cohort in the UK, which has collected data prior to and during pregnancy and information on outcomes in infancy, will be used to investigate why health inequalities emerge early on. Finally, the differences observed between the UK and Australia in the social distribution of health throughout childhood, and the mediators explaining them, will be used to consider the potential role of policy in shaping child health inequalities and to develop an analytical plan to test this. Findings will be used to inform UK and international policy development, including the timing and nature of interventions, for the reduction of child health inequalities.


Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES;8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE
Health categories: GENERIC HEALTH RELEVANCE
Title: M-PHiL Study - Mental and Physical Health in Lambeth
Funder: Medical Research Council

Abstract: SLAM Information Governance group Clinical Data Linking Service (CDLS) will act as the Trusted Third Party. A bespoke dataset will be pulled within LDN and transferred to CDLS via the NHS 3N network. The BRC-ID, a pseudonymised identifier, links to patient identifiers in a secure database outside CRIS accessible to CDLS. Using identifiers present in both datasets CDLS will attach appropriate BRC-IDs to LDN cases known to CRIS. A column containing an anonymised ID that applies to all LDN cases will be created ("LDNID"). All identifying data in LDN will then be destroyed. This "new" dataset will be stored securely on a CDLS server behind the SLAM firewall. For approved projects researchers will send CRIS data to CDLS who will pull in LDN data linked by the BRC-ID to create a project-specific dataset, each case having a project-specific ID. The BRC-ID then removed, the final dataset becomes fully anonymised. [1] CRIS patients with an SMI diagnosis & a Lambeth GP will be identified and compared to LDN patients on the SMI case register. We will describe factors associated with having care from only one service or joint care. [2] A cohort of SMI patients known to both services in 2009 will be established. Physical healthcare received 2009-12(e.g. diabetes, smoking cessation, screening for cervical cancer) will be compared with other LDN patients. Individual, disease-related and systemic factors associated with both good and poor physical healthcare will be identified. [3]New cases of SMI on CRIS will be examined for information on physical illness and prescribed medications. This will be compared to that in LDN. LDN and CRIS data will be used to assess the effect of incomplete information on physical health in CRIS. Application: Our results will generate potential interventions, both clinical and at policy level. Our collaboration means these could be quickly implemented locally. Repeated linkages will allow the results to be observed almost in 'real time'.


Research activity codes: 2.6 RESOURCES AND INFRASTRUCTURE (AETIOLOGY);8.5 RESOURCES AND INFRASTRUCTURE (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: Insights on the natural history of problem drug user (PDU) offending
Funder: Medical Research Council

Abstract: Initial hypotheses about the natural history of PDU offending will be generated via a systematic review of the quantitative and qualitative evidence base. This will access a wide selection of electronic databases, e.g. MEDLINE, EMBASE, PsycINFO etc. A narrative summary will be supplemented by pooling quantitative findings in a meta-analysis should sufficiently similar outcomes be identified. The systematic review will inform a further hypothesis generating stage involving analysis of linked data within the drug Data Warehouse (DDW); this resource contains information about substance misusers identified between 2005 and 2009 via treatment and the criminal justice system, linking data from multiple sources with recorded offending histories from the Police National Computer (PNC). Common patterns of offending and PDU status will be explored using predictive modelling and data mining techniques, such as logistic regression (utilising regression shrinkage and variable selection via the lasso [25] method) and Classification and Regression Trees (CART) [26]. Model validation will be based on bootstrap sampling [22,23,28]. This stage will be based on groups of criminally active PDUs (n=67,966) and criminally active non-PDUs (n=163,200) sampled from the DDW on the basis of information about drug tests performed on arrest. Longitudinal modelling, such as General Linear Mixed Model (GLMM), will describe the rate of offending for PDUs and non-PDUs over an offending life-course. This work will examine whether the type, and rate, of offending changes following PDU onset. The model will be expanded by including factors that might mediate or moderate these relationships; such as age at start of drug use, polydrug use, ethnicity, or gender.


Research activity codes: 2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS
Health categories: GENERIC HEALTH RELEVANCE
Title: Multivariate meta-analysis of multiple correlated outcomes: development and application of methods, with empirical investigation of clinical impact
Funder: Medical Research Council

Abstract: Following a systematic review, multiple meta-analyses are often performed because multiple outcomes are of interest. For example, in meta-analyses of cancer trials the treatment effect on both overall survival and disease-free survival is important. Such multiple outcomes are not independent; e.g. a patient's time to recurrence often occurs shortly before their time of death, and so disease-free and overall survival are positively correlated. Most reviewers ignore this correlation and simply use a 'univariate' meta-analysis of each outcome independently. Alternatively, multivariate meta-analysis methods can jointly synthesise the outcomes and properly account for their correlation. This allows meta-analysis results for, say, outcome A to be informed by evidence from studies reporting outcome A and - crucially - also from studies reporting only correlated outcome B. Compared to univariate meta-analysis, this greater use of available information leads to summary results with improved statistical properties and potentially even different clinical conclusions. This project aims to facilitate the use of multivariate meta-analysis in practice, by showing its clinical impact and overcoming methodology challenges. We will examine how multivariate meta-analyses changes existing clinical inferences within Cochrane Pregnancy and Childbirth Reviews, where correlated outcomes are common. We will derive statistical measures that reveal the impact of utilising correlation and thus 'flag' when multivariate meta-analysis is important. We will then develop and extend methods for estimating the correlation between outcomes, which are needed to apply the multivariate approach; situations involving individual patient data and only summary data will be considered for binary, continuous, and survival outcomes. Finally, we will develop methods for meta-analysing correlated adverse (rare) outcomes, for which within-study distributions other than multivariate normality are needed.


Research activity codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES);2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE
Title: Variability in mitochondrial genetics and functionality and its cell physiological effects
Funder: Medical Research Council

Abstract: This project will address the existing disconnect between experimental and theoretical understanding of mitochondrial systems by using existing and novel statistical modelling approaches to describe sources of mitochondrial variability, and combining this with computational models to explore mitochondrial effects on downstream processes. A birth-death-mutation model incorporating stochastic partitioning effects will be developed to statistically describe the time evolution of the mitochondrial makeup of cells. A model for oxidative damage, including oxidative phosphorylation and ROS production, mtDNA mutation, cardiolipin and protein damage, will be developed to provide a systems-level view of mitochondrial time behaviour. These models will be parameterised using recent advances in statistical inference for stochastic kinetic systems, notably from approximate Bayesian computation. This part of the project will be the first example of a rigorously parameterised statistical description of mitochondrial damage and quality control, enabling quantitative statements and predictions to be made about damage buildup and subsequent disease onset. Existing control theory-based models for ATP homeostasis will be examined and adapted with input from new computational models of mitochondria and oxidative phosphorylation to model the effects of mitochondrial variability on the ATP content of cells. Existing inferential techniques for stochastic kinetic models will be adapted to allow the statistical inference of rate parameters that may vary with time, to incorporate the possibility of varying ATP levels in cellular models. Combining these approaches, terms representing mitochondrial variability will be incorporated into existing mathematical models for stem cell differentiation and TRAIL response to explore the implications of mitochondrial variability in these systems of medical interest.


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