NIHRDataInsights/HRCSData huggingface dataset:
Title: The functional requirement for epigenetic systems in development and disease
Funder: Medical Research Council

Abstract: Epigenetics can be defined as an alteration in gene activity that is mitotically stable in the absence of a change in DNA sequence. In practice it represents a combination of observations and suggested mechanisms that are thought to functionally organize the genome to regulate gene expression, preserve genome integrity, propagate cell identity and govern transcriptional responses to external stimuli. Our aim is to determine the molecular mechanisms of epigenetic gene regulation that are associated with DNA modification in development and by implication in disease model systems Recent work (including our own) in mouse embryonic stem cells (ESCs) suggests that signal transduction pathways determine epigenetic states and not vice-versa. Most surprisingly we find that cell transition states in ESCs (primed to ground state and vice versa) are independent of global DNA methylation status. This work resulted in system with which we can directly investigate the mechanisms involved in over-riding the repressive effects of DNA methylation at target promoters, which will have important implications for understanding how activation and silencing of DNA methylated genes (and endogenous retroviruses (ERVs)) occurs in development and disease. Our previous analysis suggested that general aberrant promoter hypermethylation in cancer does not necessarily directly promote tumorigenesis, but instead reinforces transcription repression inherited from pre-cancerous tissue. Our work in ESCs has led us to develop new models to explain the molecular basis of this observation, which potentially de-links de novo methylation of promoters as a direct driver of disease processes and perhaps physiologic states (ageing). We have also observed that global DNA methylation states impacts on Polycomb Repression Complexes (PRC1 and 2) dependent chromatin compaction in the nucleus of embryonic stems cells (ESCs). Currently we are investigating the molecular models involved in facilitating DNA methylation directed changes in higher order chromatin organisation and its relevance to developmental gene regulation. We use various ESC models and in vitro models for early development to address how defects in defined aspects of the DNA methylation machinery influence the transition of stem cells to more committed cell fates. Increased understanding of these basic processes underpins the interpretation and relevance of altered epigenetic profiles in disease, ageing, drug screening programs and environmental exposure.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: The role of spatial nuclear organisation in genome function
Funder: Medical Research Council

Abstract: The regulation of gene expression is controlled by enhancers that are often located at very large genomic distance from their target genes. Mutation of enhancers underlies many cases of severe human developmental disorders and common sequence variation at enhancers contributes to a large proportion of complex genetic disease and quantitative traits. Functional interpretation of the DNA sequence variation revealed by large-scale whole human genome sequencing efforts requires a much better understanding of how enhancers work and is a major challenge in human genomics. We will probe mechanisms of chromosome folding linked to enhancer function and to spatial positioning in the nucleus. To gain mechanistic insight into the molecular events required to activate a gene from a distance, we will use multi-disciplinary approaches – from high-throughput chromatin profiling to advanced optical imaging - integrated with synthetic biology tools that allow us to dissect cause/consequence relationships between chromatin organisation and genome function. We will test models of enhancer-promoter communication and will determine what factors are required to bind at enhancers in order to instigate the different steps of transcription. We will focus on exemplar loci that are paradigms for long-range cis-regulation (e.g. Shh and Pax6) but, with collaborators, will also help drive the functional follow-up of loci identified by genome-wide association studies (GWAS) and that involve common genetic variation at enhancers.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Post-transcriptional regulation of Gene Expression
Funder: Medical Research Council

Abstract: Gene expression is extensively regulated at the post-transcriptional level. RNAs associate with RNA-binding proteins (RBPs) to form ribonucleoprotein (RNP) complexes. There is a great variety of RBPs, each with unique RNA-binding activity that have a profound impact on gene expression networks, affecting processes as diverse as transcription, RNA splicing, microRNA (miRNA) biogenesis and function and mRNA translation. The major aim of this programme is to study the mechanisms of post-transcriptional regulation of gene expression. We will address important questions concerning the role of RNA-binding proteins (RBPs) in Gene Expression at different levels during the RNA processing cascade from splicing in the nucleus to translation in the cytoplasm. This proposal will illustrate how alterations in RBP-mediated gene regulation can contribute to human disease. We will study different aspects of RNA processing, including - The Nonsense-mediated decay (NMD) pathway is a surveillance mechanism that selectively degrades mRNAs harbouring premature termination codons (PTCs), preventing the synthesis of truncated proteins. This pathway also controls the expression of naturally occurring transcripts and acts to modulate the phenotypic outcome of many inherited genetic disorders that arise as consequence of a frameshift or mutations that generate PTCs. Most studies to date have focused on cytoplasmic NMD; however, it is largely unknown how this mechanism operates on transcripts encoding secreted or ER-resident proteins. We have uncovered evidence that suggests the existence of an NMD pathway dedicated to Endoplasmic Reticulum (ER)-localised mRNAs, which involves two NMD factors that localize to the ER, NBAS and SEC13. We will focus on the functional characterisation of the ER-NMD pathway. We will use a variety of cells in culture, and will rely in cell biological, single molecule and biochemical approaches. - Alternative splicing (AS) is a major contributor to protein isoform diversity. We will study the regulation of AS, in particular related to its coupling to transcription. We will focus on the role of RNA Polymerase II elongation rate in the regulation of Gene Expression and Alternative splicing in development and during differentiation. We will use mouse models and mouse embryonic stem cells (ESCs), both in an undifferentiated state and during neuronal differentiation. - Due to the central role of miRNAs in the regulation of gene expression, their levels must be tightly controlled, since dysregulated miRNA expression can result in grossly aberrant gene expression and lead to human disease. We will investigate how RBPs influence miRNA biogenesis and will focus on the role of genetic variation in the production of miRNAs in human populations.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Composition of a regulatory locus and the impact on phenotype and disease
Funder: Medical Research Council

Abstract: Genome wide association studies (GWAS) highlight SNPs (single nucleotide polymorphisms) in noncoding DNA associated with disease traits for complex or common diseases. Undoubtedly, cis-regulatory mutations cause multiple human congenital defects which show a direct association of regulatory mutations with effects on gene expression. Enhancer adoption and recently, ectopic enhancer activity were shown to occur in patients with chromosomal deletions or duplications that remove TAD boundaries. Hence, examination of the mechanisms by which regulatory mutations perturb gene expression is fundamental to understanding the basis of congenital defects. We showed that disrupted gene regulation of the signalling molecule SHH is responsible for skeletal abnormalities and others have shown involvement in brain and craniofacial defects. Mutations in the Shh limb-specific cis-regulator, the ZRS, cause appendicular skeletal defects which has subsequently, led to the categorization of a broad spectrum of defects into the ‘ZRS associated syndromes’. Our studies range from defining causative mutations to attempting to identify regulatory processes involved in disease, focusing on causative mechanisms and investigating general principles that underlie long range gene activation. We showed that dominant regulatory mutations result from both gain and loss of transcription factor binding capacity. One series of point mutations in human hijacks the normal regulatory machinery involved in setting the Shh expression boundary to generate ectopic expression and skeletal defects. In addition we are investigating the role that chromatin organization plays in supporting enhancer activity and controlling gene expression. In general, we are investigation the overall architectural components required for cis-regulators to operate over large genomic distances. Known chromatin organizers such as CTCF binding sites are being surveyed to understand their direct role on gene expression and their contribution to the phenotype of the developing mouse. Systematic removal of CTCF sites in the large Shh regulatory domain results in change in 3D chromatin organization and one site underlies the appearance of the holoprosencephaly (craniofacial and brain defects) spectrum in mouse. We are presently developing imaging techniques to map chromatin changes that occur during developmental gene activation and to observe the dynamics in live cells. Our pursuit of long-range regulatory mechanisms are important in understanding developmental gene activation, and the contribution of non-coding mutations to congenital abnormalities.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Mendelian randomization to hypothesis-free causal inference
Funder: Medical Research Council

Abstract: Background: The MRC Integrative Epidemiology Unit (MRC-IEU) has pioneered the Mendelian randomization (MR) approach, which is now showing exponential growth in terms of breadth of application and number of publications. This has been fuelled by the coalescence of four trends (1) the rapid increase in the number of identified genetic variants related to exposures of interest to clinical investigators; (2) the maturation of UK Biobank and other large-scale population studies with accessible data, including from genome wide association study (GWAS) analysis; (3) the expansion in available data from GWAS consortia; and (4) the popularization of 2-sample MR analyses (2SMR), which allow causal estimates to be made from summary level data. We have developed a range of new methods that allow stronger inference to be drawn from MR studies and released a platform (MR-Base) for high-throughput 2SMR analysis. Both have been rapidly taken up by the scientific community. Our aims will considerably expand the range of questions that MR can address, include: Aim 1: To increase the clinical utility of MR by conducting studies of disease progression, which will provide MR evidence that speaks directly to disease treatment Aim 2: To develop approaches that subject the MR assumptions to further scrutiny through negative controls and the assessment of pleiotropy, together with developing structural equation modelling as a flexible strategy for analysis of MR studies Aim 3: To conduct MR studies in family based data, which provides additional robustness checks, and allows estimation of maternal and paternal influences on offspring outcomes Methods: The three aims will be advanced in parallel, within a programme that will utilise simulation, substantive analysis, replication and triangulation of evidence. Translation will be facilitated by the new NIHR Bristol Biomedical Research Centre (Davey Smith Scientific Director) and through expanding our collaborations with industry.


Research activity codes: 2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY);2.6 RESOURCES AND INFRASTRUCTURE (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE
Title: Pleiotropy robust Mendelian randomization
Funder: Medical Research Council

Abstract: The explosion in publicly available data from genome-wide association studies is accelerating the use of Mendelian randomization (MR) in bio-medicine. Summary data estimates of genetic association from large numbers of variants are now being synthesised for causal inference within the two-sample framework. Over the coming years, cohort studies such as UK Biobank will also provide a rich individual-level data resource for MR investigations. In a short time, the field has seen, and will continue to see, a dramatic rise in the power for testing causal hypotheses. There is a justified concern that when large numbers of genetic variants are included in MR analyses, with many lacking a firm biological basis for their association with the exposure, a sizeable proportion of these variants are likely to be invalid instrumental variables. A chief concern is that genetic variants may exert an effect on the outcome not through the exposure of interest - which is referred to as horizontal pleiotropy. This programme will focus on the development of statistical methods for MR in the presence of pleiotropy and other associated biases. Building upon recent methodological advancements in this field, we will develop analysis tools that: • Provide natural robustness to pleiotropy; • Adjust for non-random selection into (or out of) cohort studies used for MR; • Novel methods for data visualisation and analysis will be incorporated into statistical software platforms such as MR-Base This programme links key players in methodological research around the world to leading biomedical scientists at the Integrative Epidemiology Unit. It will develop the tools to enable epidemiological researchers to fully capitalise on emerging large-scale data sources whilst preserving the principles and rigour of causal inference.


Research activity codes: 1.4 METHODOLOGIES AND MEASUREMENTS;2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE
Title: Statistical Methods for Improving Causal Analyses
Funder: Medical Research Council

Abstract: Aim: The aim of this programme is to develop methods for causal inference that are robust to missing data and can investigate change over time, in order to draw unbiased conclusions about realistic problems, using complex observational data. Importance: Causal inference methods - in particular instrumental variable (IV) and Mendelian randomization (MR) methods - are now straightforward to implement, can be used with summary data, and are widely used by epidemiologists and medical researchers. However, the majority of real-world clinical research settings are more complex than the standard methods allow: data are missing; samples are selected; exposures and outcomes evolve jointly over time; and data from a wide variety of sources need to be integrated. Methods for causal inference, including IV, may be biased by missing data, including individuals missing due to sample selection. Standard IV methods are not able to address complex (and possibly time-varying) relationships between exposure, covariates and outcome. Multiple studies may provide information about the same causal effect, or about different paths in a network of causal effects, and we need to develop better methods to integrate evidence from different study types in order to draw causal inferences. Objectives: 1. Develop methods to minimise bias due to missing data 2. Develop methods to model complex exposures and outcomes 3. Develop IV methods to examine causal influences of multiple exposures 4. Integrate evidence to improve causal models Research plans: Part 1 of this programme will develop methods to use study information, and information external to the study, to infer the missing data structure, to inform all types of causal analyses. We will then focus on methods to maximise the robustness of IV methods to different types of missing data. We will pay particular attention to two cases: two-sample IV (using individual or summary data), and the investigation of disease prognosis. Part 2 will extend current methods for modelling trajectories and variability of exposures and outcomes. We will then focus on overcoming some of the current limitations of IV methods, by using structural equation modelling (SEM) and multivariable IV to examine impacts of time-varying exposures. Finally, we will maximise the use of all research data by extending methods to combine and use external information to inform causal models and sensitivity analyses.


Research activity codes: 2.4 SURVEILLANCE AND DISTRIBUTION;8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: Data mining epidemiological relationships: integration of causal analysis with published evidence
Funder: Medical Research Council

Abstract: Background: The increasing availability of complex, high-dimensional epidemiological data necessitates innovative and scalable approaches to harness this power to address research questions of biomedical importance. Aims: Motivated by the widespread adoption of Mendelian randomization and the opportunities to integrate multiple data sources for the triangulation of evidence in epidemiological research, this programme will develop and apply novel data mining approaches in integrative epidemiology. We will also develop and implement a software platform to enable research questions of major epidemiological importance to be addressed rapidly and at scale. The programme will focus on (a) integration of cutting edge statistical methods under development in the MRC Integrative Epidemiology Unit (MRC-IEU) with extensive data in a graph database; (b) development of subgraph searching algorithms; and (c) identification of causal mechanistic pathways to disease. EpiGraphDB will be a resource of extensive value to the programme, the MRC-IEU and the wider research community. Research plans: The programme will implement a data mining approach by developing a new graph database (EpiGraphDB) that will integrate cutting edge causal analysis evidence with comprehensive data on relationships between traits, risk factors, biomarkers, intervention targets and diseases. These data will originate from Mendelian randomization, genetic and observational correlation from epidemiological studies, relationships mined from the literature, and a wide array of bioinformatics sources describing molecular relationships. EpiGraphDB will enable aetiological hypotheses to be generated and explored. Data sharing and health applications: The database, software and results generated by this programme will be made openly available to the wider scientific community for application to a range of potential health questions (eg identifying causal risk factors for disease, identifying side-effects of interventions, etc).


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: GENERIC HEALTH RELEVANCE
Title: Epigenetic Epidemiology
Funder: Medical Research Council

Abstract: Background: To maximally exploit the rapid pace of change, including the accrual of large-scale data, in the field of epigenetic epidemiology, we will develop innovative methods for the robust scientific interrogation of population-based epigenetic data and apply them to research questions of scientific and medical importance, structured around four domains: Aim 1: We will explore the genetic architecture of epigenetic traits and use this information to understand the role that DNA methylation variation plays in health and disease. Aim 2: We will develop and make readily accessible the causal analysis methods and tools and apply Mendelian randomization (MR) to epigenetic questions. Aim 3: We will use DNA methylation as an index of past exposures to improve our prediction of disease risk and prognosis. Aim 4: From neurodevelopment to cancer, there are a multitude of settings in which we can apply epigenetic epidemiology to understand disease mechanisms and predict disease. Methods: We will utilize multiple data sources; from in-house studies, via collaborations and consortia, and through publicly accessible repositories. Our primary focus will be on the analysis of DNA methylation, as this continues to be the most readily available source of epigenetic data in population-based studies. However, we will integrate these data with newly generated and publicly available epigenomic and transcriptomic data, tissue-specific data and histone modification data. A wide range of methods will be applied. These include mQTL analysis, functional annotation and machine learning approaches, such as penalized regression, support vector machines, and neural networks. We will test for mediation using MR and apply our prediction methods in disease relevant datasets. Translation: The output arising from this programme will be used to develop biomarkers of disease risk and disease prognosis. It will also shed light on the genetic architecture of DNA methylation and the causal role this molecular phenotype plays in development and disease, which will in turn inform future interventions.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;2.6 RESOURCES AND INFRASTRUCTURE (AETIOLOGY);4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: GENERIC HEALTH RELEVANCE