NIHRDataInsights/HRCSData huggingface dataset:
Title: Regulation of DNA repair by histone ADP-ribosylation
Funder: Medical Research Council

Abstract: We will address three critically important question regarding how ADP-ribosylation couples DNA repair and cell cycle progression: a) Which histone H3 variants regulate DNA double strand break repair? b) How does H3 ADP-ribosylation regulate mitotic entry following DNA damage? c) What factors interact with ADP-ribosylated histones and how do they regulate DNA repair? A bottle-neck for the ADP-ribosylation field is the lack of an experimental model in which ADP-ribosylation sites can be mutated in histone genes to decipher how these modifications regulate DNA repair. The ability to manipulate histone genes in Dictyostelium, in addition to our mutation strategy that separates the function of serine ADP-ribosylation and phosphorylation, will address this deficiency. Dictyostelium H3 variants (H3a; H3b) are ADP-ribosylated in response to DSBs. Gene replacement technology will knock-in mutations at these sites, alone or in combinations, to generate histone ADP-ribosylation defective strains. DSB repair efficiency will be assessed using plasmid integration (NHEJ/HR efficiency), DNA damage sensitivity, and enrichment of repair factors at damage sites. Mitotic entry/progression in Dictyostelium and human cells will be assessed using cell synchronisation and live cell imaging, whilst immunofluorescence will assess markers of mitotic progression in different genetic backgrounds. Histone ADP-ribosylation defective strains offer a rigorously controlled platform to identify factors that interact with ADP-ribosylated histones. Immunoprecipitation of nucleosomes from wild-type and histone ADP-ribosylation defective strains will identify factors that interact with ADP-ribosylated histones by mass spectrometry. The orthologues of proteins identified in Dictyostelium will be disrupted by CRISPR/Cas9 using genome editing in human cells and the consequences on DSB repair assessed using standard assays, including repair efficiencies, enrichment of repair factors at DSBs etc.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Live imaging and genetic dissection of immunothrombosis in Drosophila
Funder: Medical Research Council

Abstract: Drosophila has become a widely used model system to understand the mechanisms controlling blood coagulation, epithelial repair, and inflammation. However, each of these processes are normally studied in isolation. Here we will holistically investigate how coagulation, inflammation and tissue repair are mechanistically and functionally coordinated as it is increasingly evident that clotting reactions cannot be disentangled from other aspects of the repair process. We have recently revealed that the clot reaction can be live imaged in fruit fly embryos. As this embryonic repair model is also amenable to dissecting inflammatory cell recruitment and epithelial repair, this gives us the unique capacity to examine the coordination of these responses. We will first characterise the dynamics of clotting using fluorescently tagged clot components, and determine the temporal relationship of coagulation with inflammation and epithelial repair. We will subsequently exploit the genetic tractability of fruit flies to determine the mechanisms controlling clot induction, including the role of the myriad of hypothesised clotting factors and enzymes, as well as the well-characterised repair response pathways. Finally, we will examine the ability of the coagulatory cascade to control inflammatory cell recruitment, epithelial repair, and systemic wound responses, by examining tissue repair when clot components are perturbed. As many wound response signals and coagulatory factors are conserved in higher organisms, this work will provide an understanding of the unappreciated coordination between these processes with the future goal of intervening and modulating the wound repair process.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: A single-cell multiomic approach in planarians to understand regeneration.
Funder: Medical Research Council

Abstract: Regeneration is the ability to replace tissues and organs lost to injury. The planarian Schmidtea mediterranea is a convenient lab model that regenerates any body part in a matter of days. A pluripotent stem cell population underlies the process. Dozens of cell types have been described, present throughout the body intermingled in a complex pattern. Despite extensive studies, it is still unknown how each tissue instructs the regenerative cells to integrate in the blastema, what are the signals that they use, and how do regenerative cells respond to these signals. Partly, this is because common techniques such as RNA-sequencing lack cellular resolution. Recently, single-cell techniques have revolutionised biology as they offer unprecedented cellular resolution combined with a very high throughput and will therefore be key to answer these questions. We previously used these methods to reconstruct all differentiation trajectories of planarian stem cells into a single differentiation tree. We have already optimised a novel single-cell transcriptomic approach that will allow us to obtain many more cells, with replicates to obtain statistical power and knockdown samples to obtain mechanistic information. With this method we will then elucidate in each cell type a) the quantitative changes in abundance, b) the timing of differentiation in regeneration and c) the quantitative changes in gene expression. To obtain mechanistic information, we will perform knockdown experiments with regeneration regulators. Altogether, these experiments will allow us to analyse the contribution of each cell type to regeneration in an unprecedented quantitative way and at the single-cell level, allowing us to better understand planarian regeneration and lead the way in the study of animal regeneration in other animals. Understanding animal regeneration will provide key information that will inform the deployment of human regenerative medicine.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Enhancing the transparency and reporting of randomised trials: update of the SPIRIT 2013 and CONSORT 2010 Statements
Funder: Medical Research Council

Abstract: Well-designed and properly executed randomised trials provide the most reliable evidence on the efficacy of healthcare interventions; however, there is overwhelming evidence that the quality of trial reporting is not always optimal. The SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) and CONSORT (CONsolidated Standards Of Reporting Trials) Statements are widely adopted standards for reporting protocols and results of randomised trials. They provide authors with a standard reporting structure, facilitating completeness and transparency, and aiding in their critical appraisal and interpretation and are endorsed of by hundreds of medical journals and organisations worldwide. It is important SPIRIT and CONSORT are kept up-to-date and relevant to the end user(s); reflecting new evidence and emerging perspectives. It has been over 10 years since CONSORT was last updated in 2010 and 8 since publication of SPIRIT in 2013. The aim of this study is to enhance the transparency and reporting of randomised trials by updating the SPIRIT 2013 and CONSORT 2010 Statements, including integration of key extensions, and through development of implementation strategies to promote adherence. We will use established methods for development of health research reporting guidelines. We will: (1) conduct a scoping review of the literature; (2) conduct a Delphi survey to identify changes to existing SPIRIT and CONSORT checklist items and adding of new items; (3) organise a meeting of key stakeholders to establish consensus on items included in the updated SPIRIT and CONSORT checklists; (4) develop the SPIRIT and CONSORT guidance Statements and accompanying Explanation and Elaboration documents; (5) disseminate and implement the updated SPIRIT and CONSORT Statements, including a new joint SPIRIT-CONSORT website, online training modules and new patient-facing trial portal.


Research activity codes: 6.9 RESOURCES AND INFRASTRUCTURE (TREATMENT EVALUATION)
Health categories: GENERIC HEALTH RELEVANCE
Title: Standards for Rapid Evaluation and Appraisal Methods (STREAM)
Funder: Medical Research Council

Abstract: Timeliness has been highlighted as a key factor influencing the utility of research and evaluation findings in healthcare. This became more evident during the COVID-19 pandemic, where high quality rapid research methods were of the essence to develop an evidence-based response. A wide range of rapid evaluation, assessment and appraisal approaches have been developed to make findings available when they are most needed, but challenges in their design and implementation have raised concerns regarding their rigour and the validity of the findings. One way to improve the transparency and completeness of reporting and increase the quality of studies is through the development of reporting standards. There are no published and validated standards or guidelines for rapid evaluations, assessments and appraisals. The aim of this project will be to develop the Standards for Rapid Evaluation and Appraisal Methods (STREAM) so these can be used as: 1) guidelines for the design and implementation of rapid evaluations, assessments and appraisals in healthcare, 2) reporting templates, and 3) a quality assessment tool. We will follow established guidance for the development of health research reporting guidelines by: (1) conducting a systematic review; (2) an e-Delphi consensus study; and (3) two workshops with stakeholders to finalise the set of standards and complete piloting exercises. Our main outputs will be two peer reviewed publications (systematic review and agreed standards); a manual; and a visual toolkit in English, Spanish and French to promote accessibility and use of the methods. We will establish a plan to review STREAM regularly and make adjustments.


Research activity codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: QUAREP-LiMi. Development of quality control tools and methodologies for light microscopy: improving image data quality, reliability & reproducibility.
Funder: Medical Research Council

Abstract: Standardisation for fluorescence microscopy is poorly practised in the scientific community: a recent UK survey and an ELMI survey we conducted highlighted the inconsistencies when it comes to choosing which microscope Quality Control (QC) procedures to perform and how frequently they are carried out. Understanding microscope performance is essential when deriving quantitative data from captured images, but there are no standards for reporting such QC information. We have established an international consortium: QUality Assessment and REProducibility for Instruments & Images in Light Microscopy, QUAREP-LiMi, made up of microscopists, manufacturers, funding bodies, publishers and standard-setting organisations. The aim is to develop a set of microscope QC samples, tests and define quality assessment procedures that should be performed on light microscopes at regular intervals. These we will target, promote and make applicable to both inexperienced and experienced microscopists with the intention of gaining widespread adoption by anyone using a microscope. We have split QUAREP-LiMi into individual working groups each focussing on an identified aspect of microscope or micrograph QC. Working with publishers, QUAREP-LiMi aims to influence policy, to ensure that at the point of publishing microscopy data, the 'quality' of that data is defined with respect to the instrument used to make those observations. QUAREP-LiMi has 277 members from across the globe, all of which are providing their time and effort voluntarily. Membership is split between academia (66%) and industry (26%) with participation from Standard-setting bodies, funders and publishers. Organising and managing a large and disparate group is becoming difficult, and with this funding we will employ a technical administrative person to oversee, manage and effectively communicate the work of QUAREP-LiMi both internally and externally. This will enable us to expand, and more effectively support our objectives.


Research activity codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: Environment-adjusted genetic analysis methods for cardiometabolic traits in African populations
Funder: Medical Research Council

Abstract: Our five aims address the high genetic diversity of African ancestries and their environmental exposures (e.g. infection markers of malaria) that likely impact the variability of disease-related traits. Current methods for detecting genetic associations and fine-mapping do not account for environmental exposures; such adjustments should improve both detection power of genetic associations and improve fine-mapping resolution. Our proposed methods only need genome-wide association studies (GWAS) summary data and will be accompanied by software. The proposed environment-adjusted meta-regression of GWAS includes covariates that account for differences in environmental exposures and genetic background allele between ancestries. This framework allows testing each variant for association across all GWAS, and to also identify any heterogeneity of effects among the cohorts. Fine-mapping of genetic associations relies on a representative LD matrix. There has not yet been an assessment of the appropriateness of the common strategy of using an LD matrix based on the 1000 Genomes African ancestries. We propose an alternative LD matrix based on East, West, and South African ancestral cohorts and consider two different approaches to its construction. Upon identifying loci that have genetic associations with at least one trait, we proceed to fine-mapping, adjusted for environmental exposures - two single-trait fine-mapping approaches are proposed (i) stepwise conditioning; (ii) Bayesian variable selection. For loci that have genetic associations from multiple traits, we propose an environment-adjusted multi-trait fine-mapping approach in a Bayesian framework. Genetic risk scores based on these results are expected to provide more precision over those that do not adjust for environment exposure and are based on single traits. Performance of methods will be assessed by simulation studies, and they will be applied to cardiometabolic traits from unique African ancestral cohorts.


Research activity codes: 2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE
Title: Statistical methods for interrupted clinical trials
Funder: Medical Research Council

Abstract: The SARS-CoV-2 pandemic has led to the disruption of thousands of ongoing clinical trials. For most of these trials a decision needs to be made between restarting the trial, continuing to recruit additional patients, and stopping the trial, analysing the data already observed. This decision and the resulting statistical analysis in either case, raise statistical challenges. These will be addressed by this project, providing methods for trials interrupted by the pandemic and by other causes in the future. If an interrupted trial restarts, changes in population, assessment or intervention might lead to treatment effect heterogeneity. We will explore data analysis methods allowing for this heterogeneity, for example based on meta-analysis approaches. We will extend Bayesian borrowing methods to allow down-weighting of earlier data depending on the extent to which they are discordant with later data. Simulation studies will assess and compare methods with particular focus on power and type I error rate control. To ensure that methods proposed are accepted as widely as possible we will hold consensus workshops with key stakeholders. We will also explore approaches based on group sequential methods to allow the trial to be restarted only if results from data already collected are unclear. If a trial is stopped it is desirable for the analysis to make best use of all available data. This may include baseline data, or in trials with long term follow up, early outcome data, for patients for whom the final endpoint is not observed. Methods exist to use these data to improve the precision of the analysis. We will assess these methods, extending them where necessary to allow use of all early data and time to event outcomes. We will illustrate methods proposed or developed using real case studies and determine the range of settings in which stopping and analysing the trial might be preferable to restarting leading to practical guidance for funders and trialists.


Research activity codes: 6.9 RESOURCES AND INFRASTRUCTURE (TREATMENT EVALUATION)
Health categories: GENERIC HEALTH RELEVANCE
Title: ROBEST: Ensuring robustness of evidence in public health research for increased policy impact: widened use of advanced causal inference techniques
Funder: Medical Research Council

Abstract: Often, questions that motivate studies in the health, social and behavioral sciences are causal but tend to be answered using classical statistical methods. However, causal inference methods are needed when causality cannot be guaranteed by design (i.e., observational studies) or when randomisation fails and does not provide the required balance in trials. Over the years, rapid ongoing advances in the field of causal inference for observational data have resulted in several algorithms to estimate the causal effects of a treatment on an outcome. Recently, data-adaptive estimation using machine learning techniques has been incorporated in the development of causal inference estimators. One of these algorithms is the targeted maximum likelihood estimation (TMLE). TMLE is a semiparametric double-robust, efficient substitution estimator allowing for data-adaptive estimation while obtaining valid statistical inference. In addition to being double-robust, TMLE allows the inclusion of machine learning algorithms that minimise the risk of model misspecification, a problem that persists for competing estimators. Nonetheless, TMLE rests on relatively complex statistical and mathematical concepts that need to be demystified for wider adoption. Furthermore, some questions remain for statistical inference in non-parametric settings (i.e., confidence intervals nominal coverage). This is an area of ongoing work where cross-validation is used to overcome TMLE issues in non-parametric settings (i.e., Donsker class condition). The Donsker class condition refers to the smoothness needed in finite samples to assume asymptotic linearity and implement statistical inference based on the influence function. We plan to extend a previous Stata implementation of TMLE we developed to implement the most recent theoretical advances: i) to produce robust statistical inference in finite samples, and ii) to include other functionalities making the package readily accessible for applied researchers.


Research activity codes: 8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE;8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: HRQ:Reevaluating the Remote: a realist evaluation of the practical, epistemological and ethical status of remote qualitative data collection in health
Funder: Medical Research Council

Abstract: This project will use qualitative evidence synthesis combined with realist evaluation and embedded co-production to produce stakeholder informed programme theories capable of explaining the conditions and circumstances under which remote data collection methods produce high quality and trustworthy qualitative data. These programme theories will be transformed into a framework of principles and recommendations to guide researchers in the future design and implementation of remote qualitative studies. A systematic evidence synthesis will firstly be conducted, of studies directly comparing in-person and remote qualitative methods. The studies will be appraised, and methods compared both within and between papers along core dimensions (structure, epistemology, ethics, interactional differences) that relate to data validity and trustworthiness. The quality of the resulting review will be assessed using the CERQual approach to ensure rigour. From the evidence synthesis, initial programme theories will be iteratively developed and tested within a realist review of researcher experience literature, and published guidelines on remote data collection. Evidence will be included in this review based on relevance to emerging theories, and synthesised. The programme theories will be further interrogated and finalised through 30 remote interviews with qualitative researchers, research participants and seldom heard voices, purposively sampled for maximum diversity. Finally, in co-production with a PPI panel, a framework of guidance will be developed from the final set of programme theories. This framework will be ratified through a stakeholder consensus conference, where complex or contentious recommendations will be deliberated. The final framework will be disseminated through teaching, training, health research networks, an animated video and a web resource. It will be used to guide the design, and conduct, of remote qualitative data collection for future research.


Research activity codes: 6.9 RESOURCES AND INFRASTRUCTURE (TREATMENT EVALUATION);8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: GO annotation: maximizing the potential of Drosophila research to benefit human health
Funder: Medical Research Council

Abstract: The aim of this proposal is to employ curation of gene function with the Gene Ontology (GO) to enhance the immediacy and utility of data from Drosophila research papers. GO provides a unifying and controlled vocabulary for describing gene product function across species and databases. We will utilize four parallel approaches. First, we will continue to prioritize research papers describing the functions of previously uncharacterized genes, as this information propagates to all other species with orthologs of that gene. Increased coverage of gene annotation benefits the interpretation of big data studies, such as Genome-Wide Association Studies and single-cell RNAseq. Second, we will further develop the use of GO to link the function of molecules together. Comprehensive curation of ligand-receptor interactions, enzyme-substrate, and transcription factor-target relationships will be captured, thus allowing computational derivation of cellular pathways, as exemplified by the bioinformatics tools that identify signaling and receiving cells from expression of ligands and receptors in single cell RNAseq data. Third, we will apply focused curation and ontology revision to topical biological processes. These include processes often disrupted in neuropathologies, such as mitochondrial processes and localized mRNA translation, and those disrupted in metastatic cancer, such as cell adhesion, cell migration and planar cell polarity. We will also focus on research using Drosophila to study virus-host interactions, given the spread of zika virus and SARS-CoV-2. Fourth, we will continue to develop new tools and pipelines to improve the capture of gene function data with GO and the use of this data in biomedical discovery. As members of the FlyBase, GO and Alliance of Genome Resources consortia we are well-positioned to present these data in intuitive and accessible ways to the wider research community, thus maximizing the impact of Drosophila research on biomedical advances.


Research activity codes: 1.5 RESOURCES AND INFRASTRUCTURE (UNDERPINNING);2.6 RESOURCES AND INFRASTRUCTURE (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE