Genetical genomics and molecular phenotyping in epidemiological studies
Our group is interested how genetic, molecular, and environmental information from epidemiological-scale studies can be integrated to understand the aetiology of complex traits such as endometriosis, and how this information ultimately can be used to find biomarkers for disease and surrogate markers for treatment effectiveness studies.
We have previously been involved in molecular phenotype variability studies part of the EU-funded MolPAGE programme to investigate the biological and experimental variability of data in 60 female twin pairs derived from a variety of molecular phenotyping platforms, including: gene expression transcriptomics; mass-spectrometry and microarray-based proteomics; and mass-spectrometry and NMR-based metabonomics. A number of publications have arisen from this work: e.g. PubMed 21931564; 21878913; 20141636.
In a separate study of 299 female twins, in collaboration with the Dept of Twin Research & Genetic Epidemiology at King's College (Tim Spector) and Lon Cardon at GSK Ltd, we investigated the potential to utilise gene expression information to find associations between clinical phenotypes and genetic variants: PubMed 21789213.
Our group is currently collaborating in the MuTHER study, a large-scale research programme designed to understand the relationships between genome sequence variation, methylation status, mRNA expression and disease phenotypes (e.g. PubMed IDs: 21304890, 22941192, 24183450