What lies behind the causal impact of body mass index level and change on human health? Added value from complementary study design and deep metabolom

This project aims to better understand how body mass index (BMI) exerts an effect on human health and disease using metabolomics in complementary study designs and through applied genetic epidemiology.

Rationale
There is strong evidence that BMI causally influences a wide range of health outcomes, but there is little understanding of the mechanisms driving BMI effects and at the level of the population we are limited in our ability to alter BMI.

Targeted lifestyle and pharmaceutical interventions have failed to deliver large reductions in BMI and the only effective intervention is surgery.

The proposal here is that metabolomic measurements can be used to understand the mechanisms by which BMI contributes to disease.

Circulating metabolites are the product of genetic and non-genetic factors and are a useful read-out of physiological function. Despite the similarity of metabolites to complex health outcomes, it remains possible to map metabolites to genotypes and translatable biological pathways. Consequently, identifying metabolites important in the link between BMI and disease is a promising approach to further understanding BMI as a risk factor.

Aims and Objectives
To better understand how BMI exerts an effect on human health and disease using metabolomics in complementary study designs and through applied genetic epidemiology.

This PhD will be coodrinated with a Wellcome Trust funded programme of research that explicitly seeks to use the most contemporary and powerful study designs, metabolic data capture and analytical techniques to explore BMI as a risk factor.

Methods
We will address five key research questions by testing the hypotheses that:
1. Specific circulating metabolites are affected by BMI change
2. BMI has a causal effect on the human metabolite response to feeding
3. BMI has a causal effect on the on the human faecal microbiome
4. It is possible to causally map the human faecal microbiome onto the metabolome to extend the study of the microbiome
5. Metabolites identified through population based causal analysis of BMI, intervention studies of BMI change, the effect of BMI on metabolic response and investigation of the microbiome ("BMI-metabolites") have a causal effect on disease risk.

Research summary
BMI, a measure of adiposity, is observationally associated with health outcomes including all-cause mortality, CVD, T2D, and cancer. We do not yet know the full story of why BMI is a risk factor, and altering BMI at the population level is challenging.

Metabolic differences are present across BMI levels and this is reflected in circulating metabolites. The result of genetic and non-genetic factors, circulating metabolites provide information on physiological function and can be used to identify links between BMI and disease.