Clinical Characterisation of a Broad Spectrum of Genetic Variation in the General Population (360G-Wellcome-203810_Z_16_A)

Inborn errors of metabolism (IEM) are severe and extreme changes in metabolism caused by mutations in a single gene. Recent large-scale human studies have shown that genes causal for IEM are associated with nutrients, or ‘metabolites’, in the blood. However, whether these associations cause disease or adverse health outcomes is unknown. In this project, I will use IEM genes identified in these studies to link genetic variation to clinical features in a large human population. To do this, I will assemble a list of IEM genes of interest that were identified in the literature and in large population datasets. I will then test for associations between the variants I find in these genes and a wide range of clinical features found in open-access population datasets. As the IEM genes used in this study have been associated with blood metabolites previously, linking variants in these genes to clinical features will shed light on the molecular mechanisms underlying genes and disease in the general population. Understanding how genetic variation affects disease will help identify novel therapeutic targets and enable health professionals to better manage disease risk.