Projects

Five project areas have been set out and will be overseen by members of the Executive Committee. These areas reflect the types of available datasets, analysis methods and data interpretation.

All active projects are described below. It is hoped that these projects will be highly collaborative with joint contributions from all. Hence, eligible cohorts meeting the entry criteria are encouraged to participate in these projects. For details on how to join specific projects please see the information below.

Equally, as the aim of GoDMC is to support and expedite research within the field of epigenetics, all members are encouraged to establish and lead their own analysis projects; either genome-wide meta-analyses or targeted replication studies. For details on how to establish new projects please see the Information page.

SNPs and DNA Methylation Variation

Structural Variants and DNA Methylation Variation

Tissue Specificity and Ethnic Differences In DNA Methylation

Variation In DNA Methylation Profiles Across The Lifecourse

Integrating Methylation with Other ‘Omics’: Evidence For Shared Genetic Mechanisms

Proposing new analyses

Because the pipeline harmonises the data from many cohorts into a single framework, it is our hope that this can be a resource that the community of researchers within the consortium can use to conduct further work involving genetic, methylation and phenotypic data. Members can propose new projects that fall under two different categories:

  1. Using the results that are already generated by the pipeline from existing modules (Summary Stats Proposal Form)
  2. Writing new modules to perform extended analyses (New Analysis Proposal Form)

Approved Data Access requests

1. Investigating Causality in the association between Type 2 Diabetes and DNA methylation via Mendelian Randomization methods. Diana Juvinao-Quintero, University of Bristol

2. SNPs of methylation derived neutrophil to lymphocyte ratio (mdNLR): a measure of systemic inflammation. Srikant Ambatipudi, University of Bristol

3. Association analysis of genetic inversions and DNA methylation and their role on BMI and height. Carlos Ruiz-Arenas, ISGlobal, Centre for Research in Environmental Epidemiology (CREAL)

4. Smoking, methylation and the function of F2RL3/PAR4 thrombin receptor: searching for mQTLs for two-sample MR investigation. Amy Taylor, University of Bristol

5. Associations of glycemic traits with methylation levels in blood cells - CHARGE consortium. Alexia Cardona, University of Cambridge

6. DNA methylation in the MC1R region as a potential risk factor for melanoma. Carolina Bonilla, University of Bristol

7. Two-sample Mendelian randomization of sex-specific autosomal DNA methylation and later life health outcomes. Ryan Arathimos, University of Bristol

8. Mapping of the shared genetic architecture of the human blood multi-omics phenotypes at disease risk loci. Mahsa Sheikhali Babaei, University of Bristol

9. Causal consequences of smoking induced methylation changes on cardio-metabolic phenotypes. Teri North, University of Bristol

10. Using two-sample MR we aim to assess the causal effect of changes in DNA methylation on complex traits (and vice versa). Tom Richardson, University of Bristol

11. DNA methylation signatures of polygenic risk scores for neuropsychiatric, neurodegenerative and metabolic phenotypes. Eilis Hannon, University of Exeter

12. Genome-wide analysis of selection and methylation, Charlie Hatcher, University of Bristol

13. Exploration of genetic effects at candidate metastable epialleles, Juan Castillo-Fernandez, Kings College London

14. Adverse socioeconomic conditions in early life, gene regulation and adult inflammation: a test for the pro-inflammatory phenotype, Cristian Carmeli, Lausanne University Hospital

15. Integrative approaches to fine-mapping causal loci in heritable disease, with focus on atopic dermatitis (AD), eczema, Maria Sobczyk, University of Bristol

16. Mendelian randomization study elucidates CpG sites as mediators for genetic influences on glioma risk, Amy Howell, Jie Zheng, University of Bristol

17. Identify genetic variants associated with smoking behavior using GWAS meta-analysis, IBSc dissertation, University of Bristol