Early life DNA methylation patterns linking intra-uterine events to adverse cardiometabolic outcomes
Lead Research Organisation:
University of Oxford
Department Name: Wellcome Trust Centre for Human Genetics
Abstract
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.
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.
Technical Summary
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.
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.
Planned Impact
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.
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.
People |
ORCID iD |
Alexander Drong (Principal Investigator / Fellow) |
Publications
Wahl S
(2017)
Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity.
in Nature
Rahmioglu N
(2017)
Variability of genome-wide DNA methylation and mRNA expression profiles in reproductive and endocrine disease related tissues.
in Epigenetics
Description | RNAseq lecutre |
Geographic Reach | Multiple continents/international |
Policy Influence Type | Influenced training of practitioners or researchers |
Impact | In November 2016, I voluntarily held a one-hour lecture on epigenetic and noncoding-RNA based therapeutics. This was part of the Biological Therapeutics short course, which is one week long and involved participants who were senior clinicians, as well as leader in research & development in the pharmaceutical industry. |
Title | Parent-of-Origin Effect |
Description | During my award, I worked on a pipeline to |
Type Of Material | Data analysis technique |
Year Produced | 2016 |
Provided To Others? | Yes |
Impact | This pipeline can be used on any trio data and builds on phased data using SHAPEIT duohmm. The pipeline was first used for the analysis of expression data available in the Lindgren group at Oxford, and has also been applied to ALSPAC data as part of the collaboration. I further shared the pipeline with our collaborator Christine Hansen, who is using it to analyse methylation data from trios curated by the Serum Statens Institut, Denmark |
URL | https://github.com/dronga/poe |
Title | UKB Analysis Pipeline |
Description | I wrote a collection of scripts (pipeline) for the efficient analysis of UK Biobank data, which at the moment spans genetic data from 150,000. My script perform some quality control and splits the data up into smaller chunk, which are then automatically run on a specialised cluster. |
Type Of Material | Data analysis technique |
Year Produced | 2017 |
Provided To Others? | Yes |
Impact | With the develoment of this software, the genetic and multivariate analysis is sped up from 2 weeks in the worst case using a single thread and chromosome-wide unfiltered data, to being able to run 100s of jobs in parallel and thus cut the time down to up to a day. I have made the software publically available and have shared it with colleagues at Oxford and abroad |
URL | https://github.com/dronga |
Description | Baccarelli |
Organisation | Columbia University |
Department | Department of Environmental Health Sciences |
Country | United States |
Sector | Academic/University |
PI Contribution | I have provided guidance during phone conferences on the input on the experimental deign of the methylation case control study. |
Collaborator Contribution | Andrea Baccarelli will provide the key dataset for my research, has appointed me as lead analyst on the analysis of the Tianjin cohort (case-control for gestational diabetes) as outlined in the research proposal. In addition, Andrea will be hosting me at Columbia University, NY, USA for half a year starting in June 2017. |
Impact | The outputs from this collaboration have been in the planning phase so far, with fully collected data sets available mid June 2017 |
Start Year | 2016 |
Description | Collaboration with Nic Timpson and Caroline Relton |
Organisation | University of Bristol |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | As part of this collaboration, I undertook two day-long research visits to Bristol, I was given access to the local supercomputer and implemented a pipeline for the analysis of of parent-of-origion effects in newly established ALSPAC trios. As part of the collaboration, I will stay in Bristol for one month April/May 2017 |
Collaborator Contribution | Supervision by Dr Nic Timpson and Prof Caroline Relton was provided during my visits to Bristol. In addition, they introduced me to members of the ALSPAC team and helped me gather the data necessary to analyse methylation, expression and genetic data as part of newly available ALSPAC trios. |
Impact | Computational Pipeline for the parent-of-origin analysis of expression/methylation data Manuscript on miRNA eQTLs in ALSPAC in progress |
Start Year | 2016 |
Description | Ronald Ma |
Organisation | Chinese University of Hong Kong |
Department | Jockey Club Institute of Ageing |
Country | Hong Kong |
Sector | Academic/University |
PI Contribution | I attended telephone conferences relating to the analysis of two DNA methylation datasets related to the GDM birth cohorts in Hong Kong highlighted in the fellowship. In addition, I provided advice on a dataset related to diabetic complications in a case/control cohort on the Illuina 450k array (1000/1000) |
Collaborator Contribution | Ronald Ma has provided me with access to his cluster in Hong Kong to analyse my data, as well as access to the GDM and diabetic complications cohort. |
Impact | A manuscript relating to the outcomes is in preparation |
Start Year | 2015 |
Description | ASHG VANCOUVER |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | I presented my research as a poster at the American Society for Human Genetics in Vancouver. This meeting is one of the largest genetics conferences in the world, with over 6,000 attendants |
Year(s) Of Engagement Activity | 2016 |
Description | Gender Equality Committee |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | I joined the Wellcome Trust Centre for Human Genetics Gender Equality Committee (GEC) in order to provide input from a male perspective as well to help organising the activities. The GEC meets every three months, and the topic discussed included gender pay gaps, work life balance, women and families in science, as well as activities such as a family fun days and career talks. |
Year(s) Of Engagement Activity | 2017 |
URL | http://www.well.ox.ac.uk/gender-equality |
Description | Gene Day |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | The British Society for Gene and Cell Therapy runs a day of talks and activities for A-level students (16/17 year olds) at the Oxford University Museum of Natural History. From 11.30 - 1pm the students are given the chance to wander around stalls, chatting to real researchers. As this is in the public area of the museum, members of the public taking part. It's an event with a nice combination of interested members of the public, and young people with reasonably deep knowledge of the area. We're looking for people to staff our stall, using activities we already have. |
Year(s) Of Engagement Activity | 2017 |
Description | RNAseq lecture |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | In November 2016, I voluntarily held a one-hour lecture on epigenetic and noncoding-RNA based therapeutics. This was part of the Biological Therapeutics short course, which is one week long and involved participants who were senior clinicians, as well as leader in research & development in the pharmaceutical industry. |
Year(s) Of Engagement Activity | 2016 |