Early life DNA methylation patterns linking intra-uterine events to adverse cardiometabolic outcomes

Complex diseases are typically caused by a mixture of genetic, environmental and epigenetic effects. A number of prenatal risk factors, including intra-uterine growth restriction (IUGR) and gestational diabetes mellitus (GDM), have been shown to determine signatures in the blood methylome. However, most studies on this topic fall short are underpowered, or fail to take genetic effects into account to investigate causality. Birth cohorts with multiple tissue samples and deep phenotyping offer an opportunity to investigate the interplay of genetics, epigenetics and the environment affecting foetal and child growth. Moreover, my project aims to specifically determine which changes in DNA methylation are causal to subsequent disease states by combining genetic and epigenetic data in Mendelian Randomization experiments. The discovered results can then be used to develop biological tools to detect children at risk stratify risk groups and develop prevention strategies.

The work I propose to undertake follows on from my recent research in cross-sectional epigenome-wide association studies (EWAS) for T2D and obesity In adults (Wahl*, Drong* et al. under review). However, I have found previously that most of the strongest signals of methylations associations display a reverse causal relationship. I am thus interested to investigate the influence of early-life events, such as foetal growth and gestational diabetes (GDM) on patterns of DNA methylation. To achieve this, I aim to employ quantitative skills to develop robust methodology to take into effect confounding effects from experimental confounders (mixture of foetal/maternal tissues), maternal/paternal genotypes and to develop a robust, reusable pipeline for Mendelian Randomization in birth cohorts. Ultimately, I aim to link epigenetic markers both identified for GDM and IUGR with future health outcomes, and develop biomarkers for the effects.

Firstly, I aim to apply my analysis methodology to utilise the rich data sets curated by the proposed research sponsors to detect associations of DNA methylation with a number of phenotypes. I will perform a large scale EWAS case/control studies for GDM. Secondly, I will lead for the analysis of epigenetic data from biological samples for IGUR in the INTERBIO-21 study. This includes development of the experimental designs for large-scale epigenome-wide association scans. Lastly, I will be utilizing genetic variants as instrumental variables in two-step Mendelian Randomization to determine whether epigenetic markers are in causal pathways linking intra-uterine events to the child's phenotypes. Thus I will apply an informed approach about causality to separately detect genetic associations to avoid bias and will be able to detect maternal genetic and epigenetic confounding.

This will allow me to be in a unique position by extending the scope of simple cross-sectional EWAS to include not only causal analysis, but also a robust characterisation with respect to biological and technical confounders.
By focussing my hypothesis on causal pathways, my work can filter out reverse-causal confounders facilitate personalised prevention and novel drug target discovery. If successful, my research will provide accurate tools to guide childhood interventions through early biomarkers of the intrauterine environment.

In the early stages of the fellowship, I will perform the largest to-date EWAS case/control study for GDM (N=600/600 in subjects originating from Tianjin, China. Subsequently, I will replicate/validate my findings in an independent set of GDM samples (N=200/800). Association testing will be carried out by fitting probe-wise linear models, with adjustments for biological and technical confounders (control probe principal components). The relevance of DNA methylation hits can be tested by robust pathway enrichment tests of genes associated with the differentially methylated CpG sites with functional ontologies using custom developed scripts that adjust for probe coverage bias (goseq). Overlaying relevant Roadmap Epigenome data by performing permutation tests utilizing random sampling of matched CpG sites. I expect this work to identify specific DNA methylation sites, with a detectable and predominant association with GDM.

In the later stages of the fellowship, I will lead the experimental design for the methylation experiments by performing large-scale epigenome-wide association scans. This will include detecting associations of IUGR/SGA with methylation by using cases and controls recruited at delivery (N=600/600) and finding methylation marker associated with foetal growth in a longitudinal study (N~2,500) with multiple anthropometric measurements throughout pregnancy. The multi-ethnic design of this study will also allow me to establish transethnic effects. Lastly, I will be utilizing genetic variants as instrumental variables in two-step Mendelian Randomization to determine whether epigenetic markers are in causal pathways downstream to intra-uterine events.

1. Clinical and Societal Impact

On the clinical side, we currently have very limited means to identify children who will present or maintain poor cardiometabolic phenotypes later in life, which impedes any efforts for tailored active prevention in early life. Capabilities to accurately profile children for future risks could be a vital tool to help millions of individuals and revolutionise current preventive strategies, thus giving rise to substantial clinical and societal impact over the longer time scale.

Through the combined genetic and epigenetic approach outlined in the proposal, I aim to find biomarkers that link conditions in the intra-uterine environment, as observed through intra-uterine growth restriction (IUGR) and gestational diabetes mellitus (GDM). The work in this proposal will provide a unique opportunity for identifying novel biomarkers of GDM/IUGR exposure and its sequelae, as well as biomarkers to predict the success of an early childhood lifestyle intervention on children with prenatal GDM/IUGR. By combining available data from existing and newly set up resources in my novel methodology, the research will be the only study of GDM/IUGR children can achieve adequate power for methylomics discovery.

By evaluating the effects of adverse environmental and nutritional factors (and other biomarkers), which possibly interact with genetic factors and the epigenome
This can lead to better clinical management of pregnancies and newborn complications. In turn, this will contribute to the selection of more effective preventive interventions and screening strategies by improving their specificity, so as to facilitate the development of targeted interventions and screening strategies in pregnancy and early infant life.

2. Global Impact
In the mid-term, I will further reach out to other research groups and previous and newly established collaborations, to test the generalisability of my findings birth cohorts with similar methylomic and phenotype data. This will confirm that findings my are extendable to other racially diverse populations to generate impact across a range of societies worldwide and establish the UK as a hub for researchers of GDM and IUGR.

3. Researcher Career Development
Moreover, I plan to contribute to the economic competitiveness of the UK through enhancement of researcher career development. I aim to actively participate in teaching new incoming students on the Genomic Medicine and Statistics course hosted by the Medical Sciences Graduate School. This includes a taught course in R and statistics and voluntary tutorial sessions, where I will be able to communicate my research interests to the next generation of scientists. The focus on the development of skills in the MRC Quantitative Skills Fellowship will set an excellent backdrop for me to consolidate the skills learnt through teaching.

4. Track Record
I have recently participated in the Wellcome Trust Centre Public Engagement Training course, which discussed different approaches towards to public engagements, such as online, talks, debates, stalls at festivals, along with the various pre-existing support structures existing within the Wellcome Trust Centre for Human Genetics.