Wellcome Sanger Institute
Genomic and expression signatures of glycaemic traits
Glycaemic traits are used to diagnose and monitor diabetes, are associated with cardiovascular complications, and can inform pathophysiology in type 2 diabetes. Within MAGIC (Meta-Analysis of Glucose and Insulin-related traits Consortium) we have analysed large-scale genetic data (exome-array and standard genome-wide array) across five ancestries (71% European, 13% East Asian, 7% Hispanic, 6% African-American and 3% South Asian) relating to four glycaemic traits (fasting glucose, fasting insulin, 2h glucose and HbA1c). Combining genetic results with additional genomic datasets (genomic feature annotation and expression datasets) has provided insights into genomic and expression signatures of each glycaemic trait. In my talk I will present results relating to the similarities and differences observed between glycaemic traits, insights gained from trans-ethnic fine-mapping, and pathway and gene set analysis. These data provide additional biological insights relating to glycaemic traits, and can provide mechanistic insights into type 2 diabetes pathophysiology.
Big Data Institute, University of Oxford
Mapping the genetic architecture of common human diseases from routine healthcare data
Population-scale analysis of genomic variation linked to individual-level data on disease, treatment and response, has the potential to answer many key questions in biomedical research. However, the analysis of medical data obtained from routine sources and through self-reporting has many challenges. I will describe work using the UK Biobank data to characterise the genetic architecture and heterogeneity of common human diseases.