Using genetic and epigenetic data to understand basic mechanisms of inflammation.
We are interested in the genetic and epigenetic determinants of inter-individual variation in immune responses. Our work is supported primarily by the Wellcome Trust and CRUK. We’ve also received valuable support from the Academy for Medical Sciences.
Our current projects are as detailed below:
Context specific EQTL
The functional properties of a genetic polymorphism depend upon the cell type analysed and the state that the cell is in. Thus to understand the genetics of gene expression in immune cells we need to explore specific populations of cells in defined environmental contexts. We are using bulk and single cell RNA sequencing to explore the interplay between divergent immune stimuli and genetic variation across multiple cell types. All data from this study will be made openly accessible via a web portal.
Inflammation and methylation
We are exploring the effect of immune stimuli on DNA methylation in human primary immune cells with reference to underlying genetic variation. DNA methylation is intricately involved with the ageing process and an individual’s age can be accurately inferred form their DNA methylation status. We are using these observations to define the transcriptional and functional consequences of age acceleration (premature biological ageing as defined by methylation state) in the innate immune system.
Genomics guided cancer treatment
Immunotherapy forms the main line of treatment in metastatic melanoma and shows superior outcomes to conventional chemotherapy and small molecular inhibitors in the treatment of metastatic renal cell cancer, non-small cell lung cancer and metastatic head and neck cancer.
Key research objectives are the identification of parameters that define clinical benefits and predict adverse responses – which are typically autoimmune in nature. Given the response to immunotherapy is predicated upon immune mediate recognition and clearance of tumours, we hypothesise that information as to outcome can be determined through the sampling of peripheral blood samples. To do this we are using sequencing data from circulating plasma DNA, cell subset transcriptomics and germline genetics in samples from patients with metastatic melanoma who are undergoing treatment with checkpoint inhibitor therapies.