Project ID NS-MH2024_43


Co Supervisor 1A Institute of Psychiatry, Psychology & Neuroscience, School of Mental Health & Psychological Sciences, Social, Genetic & Developmental Psychiatry CentreWebsite

Co Supervisor 1B Institute of Psychiatry, Psychology & Neuroscience, School of Mental Health & Psychological Sciences, Social, Genetic & Developmental Psychiatry CentreWebsite

Mood and food: exploring the genetic and phenotypic relationships between depression symptoms, appetite and weight

Change in appetite and weight are core symptoms of depression, but we know little about their relationship and their biological underpinnings. The genetic contributions to mental health disorders and human behaviour are polygenic, with many genetic variants contributing, each having a small impact. This genetic component can be measured in a polygenic score, giving a single number that captures genetic liability. In this PhD, you will dissect the relationship between eating behaviours, low mood, and major depression, using rich clinical, dietary, and mental health data from existing studies.
You will be able to focus the PhD according to your interests, enabling you to develop into an interdisciplinary researcher with skills in mental health, statistics and genetics. These are skills shortage areas, with many postdoctoral research opportunities available, inside and outside academia.
Year 1: What data are available on eating behaviours and depressive symptoms? Database search, literature review, data access and preliminary analysis of Twins Early Development study (TEDS) and UK Biobank. Defining and harmonising phenotypic measures. Training: R statistical analysis, latent class analysis using DataCamp, in-house courses.
Year 2: Are depression symptoms associated with eating behaviours? Using data resources from Year 1, you will establish the relationships between variables, using tools such as phenotypic and genetic correlations, and polygenic scores. Training: genetic association studies, attending Boulder genetics course and peer-to-peer learning with research team colleagues.
Year 3: Do eating behaviours and depressive symptoms share their genetic architecture? Integrating genetics with multivariate measures of mood and eating behaviours to identify the core genetic relationships. Training: Multivariate statistical and genetic methods such as MTAG, GenomicSEM. Attend Maudsley Forum.
Year 4: What are the impacts of eating behaviours and depressive symptoms on weight change? Assessing the relationships between depression as a psychiatric disorder, eating behaviours and weight change considering mediation, interactions and causal associations. Training: Epidemiology, Thesis preparation.

Representative Publications

Lewis CM, Vassos E: Polygenic Scores in Psychiatry: On the Road From Discovery to Implementation. Am. J Psychiatry. 2022. 179(11):800-806 (Review and Overview). doi: 10.1176/appi.ajp.20220795 .

McIntosh AM, Sullivan PF, Lewis CM. Uncovering the Genetic Architecture of Major Depression. Neuron. 2019 Apr 3;102(1):91-103. doi: 10.1016/j.neuron.2019.03.022. Review. PMID: 30946830

Arathimos R, Fabbri C, Vassos E, Davis KAS, Pain O, Gillett A, Coleman JRI, Hanscombe K, Hagenaars S, Jermy B, Corbett A, Ballard C, Aarsland D, Creese B, Lewis CM. Latent subtypes of manic and/or irritable episode symptoms in two population-based cohorts. Br J Psychiatry. 2022 Jan 4:1-10. doi: 10.1192/bjp.2021.184.

Herle M, Pickles A, Pain O, Viner R, Pingault JB, De Stavola BL. Could interventions on physical activity mitigate genomic liability for obesity? Applying the health disparity framework in genetically informed studies. Eur J Epidemiol. 2023;38(4):403-412. doi:10.1007/s10654-023-00980-y

Herle M, Abdulkadir M, Hübel C, et al. The genomics of childhood eating behaviours [published correction appears in Nat Hum Behav. 2021 Feb 16;:]. Nat Hum Behav. 2021;5(5):625-630. doi:10.1038/s41562-020-01019-y

Herle MP, Kan C, Jayaweera K, et al. The association between emotional eating and depressive symptoms: a population-based twin study in Sri Lanka. Glob Health Epidemiol Genom. 2019;4:e4. Published 2019 May 8. doi:10.1017/gheg.2019.3