MRC-GSK pilot programme to identify new targets and biomarkers from genetic association studies

The rising prevalence of obesity and related metabolic diseases is a major public health problem requiring a broad spectrum of approaches to enhanced prevention and treatment. One element of this is the generation of greater understanding about how our genetic make up and lifestyles interact to bring about these disorders. Previously progress in this area had been limited by our approaches to trying to understand the genetic basis of common disorders like obesity and type 2 diabetes. However, recently it has become possible beyond the former approach of studying the association with disease of single gene variants identified on the basis of prior knowledge of possible biological pathways. New approaches based on studying many hundreds of thousands of variants at once have become possible because of technological advances following the human genome project. However, the downside of this increase in the scale of genetic information is that studies have had to involve many more participants since the chance of an association being found simply by chance is considerable if studies are too small. Therefore, in this study, we will create a collaborative network between research groups to combine existing genetic data from large population-based cohort studies in order to study the genetic basis of 5 common metabolic traits. Following this initial analytical stage, we will confirm the findings in other large studies to reduce the possibility of false discovery and then undertake further work to pinpoint exactly where in the genome the genetic signal is coming from. In this way, we will contribute to discovering new variants underlying the distribution of these common metabolic traits which in turn will contribute to the development of novel preventive and therapeutic strategies.

The public health importance of obesity and related disorders is unquestionable and improved understanding of the molecular basis of these disorders is an important part of a broader strategic approach to enhanced prevention and treatment. Recent studies have shown that genome-wide association (GWA) studies are an effective strategy for identifying novel genetic risk factors for complex diseases. GWA studies of quantitative traits provides a powerful research framework to examine the aetiology of metabolic disease, providing greater statistical resolution than the assessment of discrete traits for equivalent sample sizes. However, because genetic variants are likely to only explain a very small proportion of the variation in a biomarker trait or risk factor, the identification of reliable statistical associations requires large samples sizes. In this project we will bring together existing genome-wide association data from two population based cohorts (EPIC and Lausanne), in order to create an initial starting point for the analysis of quantitative metabolic traits. We will undertake a meta-analysis of GWA studies for five trait areas; obesity traits, lipids, blood pressure, glucose and insulin and age at menarche. Additional phenotypic areas will be considered at a later date, but we will consolidate our initial efforts on these five areas. Using a network of population-based cohort studies, we will undertake large scale replication of initial positive associations in order to select loci to take forward to a third stage of detailed refinement of the source of the association signal. Finally we will examine the association between confirmed loci and intermediate biomarkers that are more proximal on the putative causal pathway. This stage will necessitate the selection and measurement in specific cohorts of informative biomarkers. In turn, this will feed into the design of new analyses of GWA data and separately to studies of the function of the newly identified variants.