Translational genomics in critical care medicine

We are a cross-disciplinary translational research group focused on using genomics and transcriptomics to better understand and treat critical illness. The fundamental problem that we focus on is the lack of treatments to stop people dying from severe infections - a syndrome known as sepsis. We believe that a functional genomics approach can lead us to biological processes that might be amenable to treatment. Much of our work focuses on specific infections, such as influenza, or critical illness caused by non-infectious injuries, such as pancreatitis.

We develop and apply computational tools, and use in vitro and in vivo models to generate and test hypotheses. We are based in the Roslin Institute, University of Edinburgh and Intensive Care Unit, Royal Infirmary Edinburgh.

Read a summary of our approach in this perspective article:

Pairwise coexpression networks derived from GWAS results. Each coloured ball indicates a transcription start region containing a GWAS-associated variant. Red - significantly coexpressed by network density analysis. Light blue - all other transcription region containing GWAS-associated variants for this phenotype. (3d visualisation by vasturiano)

Coexpression of GWAS hits

Applications of computational biology in critical care medicine.

Stratified medicine

Throughout the history of medicine, progress has been made by recognizing patterns of disease, or syndromes. When new technologies are invented, they can reveal observable characteristics that have close relationships to disease trajectories, outcomes, and most importantly of all, response to therapy. Genomics and transcriptomics have these properties, but raise an additional challenge: the scale of the data is such that detecting relevant signals is a substantial computational and mathematical challenge.

Gene set hypothesis testing.

Gene set hypothesis testing

FANTOM5 coexpression network