Abstract

Fat, Sugar and Metabolomics – Understanding How Diabetes Arises at the Population Level

Jules Griffin, Director, Metabolic Profiling Forum University of Cambridge

The majority of genes thus far identified as associated with T2DM are from rare monozygotic forms, and do not model the complex interactions between genotype and environment. Metabolomics may be used to address this in genome wide association studies (GWAS) as the metabolome is downstream of the genome and interacts with diet, pathophysiology and environment. We are applying GC-MS, LC-MS and DI-MS to profile cohorts to explore these interactions. These studies require robust and high-throughput approaches, and include the largest analysis of fatty acids by GC-MS to examine the interaction between diet and T2DM risk using the European Prospective Investigation into Cancer and Nutrition cohort, DI-MS to monitor intact lipid profiles in the Fenland (with Nick Wareham, MRC Epidemiology; 1500 individuals) and Pakistan Risk of Myocardial Infarction Study (with John Danesh, Cambridge and Danish Saleheen, UPENN; 5400 individuals) cohorts and quantify aqueous metabolites and polar lipids using the Biocrates kit in the Fenland cohort (11500 individuals). These studies highlight the role of de novo lipogensis in generating triglycerides associated with an increased risk of T2DM. Finally we will update on a lipidomic study of the INTERVAL cohort, looking at relative risk of cardiovascular disease in 50,000 individuals (with John Danesh).