Change in appetite and weight are core symptoms of depression, but little is known about the relationship between them and their biological underpinnings. The genetic contribution to most mental health disorders and human behaviour is polygenic, with many genetic variants contributing, each having a small impact on risk of disease or to defining behaviour. This genetic underpinning can be captured in a polygenic score, which give a continuous measure of genetic liability. In this project, we will dissect the relationship between low mood, major depression and eating behaviours, through secondary analysis of existing study data.
Training will establish the student as a multi-disciplinary researcher in mental health, statistics, and genetics. The project allows for specialisation according to the student’s interests. Statistics and genetic analysis are skills shortage areas with many postdoctoral research opportunities available in academia and industry.
Year1: Data access to TEDS and UK Biobank. Defining and harmonising phenotypic measures. Training: R statistical analysis, latent class analysis using DataCamp, in-house courses.
Year2: Constructing polygenic scores for depression and eating behaviours, establishing the relationships between them through genetic correlations. Training: genetic association studies, attending Boulder genetics course and peer-to-peer learning.
Year3: Integrating genetics with multivariate measures of mood and eating behaviours to identify the core genetic relationships between them. Training: Multivariate statistical and genetic methods such as MTAG, GenomicSEM. Maudsley Forum.
Year4: Assessing the relationship between depression as a psychiatric disorder and measures of appetite and weight change, building on insights from previous. Training: Thesis preparation.