Population Health Projects

Please find the details of the available projects for the Population Health theme outlined below. Full project descriptions can be downloaded by following the link in the project title. A full list of our available projects can be downloaded here.

For details on how to apply, please head back to our How to Apply page. Our application form can be found here.

 

Fetal-maternal genetic interactions and the effects of maternal age at first pregnancy on breast cancer susceptibility
A woman’s age at her first full-term pregnancy affects her life-long breast cancer risk. Pregnancy before the age of 20 induces a genomic expression profile in breast tissue that is still identifiable years later. This PhD will examine the epigenetic factors influencing fetal gene expression and their impact on maternal mammary gland development.
Supervisor: Dr Adele Murrell.
Lead Institution: Bath.

Targeting the Ubiquitin-Proteasome System in Glioblastoma
The Ubiquitin-Proteasome System (UPS), which mediates protein degradation in cells, is an exciting source of novel therapeutic targets for cancer. This project will build on our discovery that a novel E3 ubiquitin ligase enzyme, which is overexpressed in glioblastoma, is important for cancer cell growth and proliferation.
Supervisor: Dr Julien Licchesi.
Lead Institution: Bath.

Preconception Health Improvement: Intervention development to target multiple modifiable risk factors for multiple adverse perinatal outcomes
This PhD aims to develop a new intervention for women and men to improve health before pregnancy. The student will use mixed-methods: a systematic review, a large survey and in-depth interviews with women, men, heath professionals and policy makers. The student will co-create an intervention to test in a later trial to see if it improves health.
Supervisor: Dr Ruth Kipping.
Lead Institution: Bristol.

Causal mediation analysis for molecular mediators
Big data and causal analysis methods to identify potentially modifiable intermediate variables to limit the detrimental health consequences of hard-to-change exposures. Developing methods to uncover the degree to which high-dimensional molecular data (e.g. metabolomics, epigenetics) mediate the relationship between exposures and health outcomes.
Supervisor: Dr Laura Howe.
Lead Institution: Bristol.

Gene-environment interplay in the generation of health inequalities
This project will advance understanding of gene-environment interactions in the generation of health inequalities. Combining methods from genetics and social science, it will test whether privileged environments protect against genetic susceptibility to risky health behaviours, using ‘natural experiments’ to deal with unmeasured confounding.
Supervisor: Dr Stephanie von Hinke.
Lead Institution: Bristol.

Network Meta-Analysis and Extrapolation of Survival Outcome Data
National recommendations for whether to use expensive drugs on the NHS rely on robust estimates of life expectancy. Methods will be developed to combine evidence on multiple treatments from multiple RCTs and registry data. Methods combine network meta-analysis, flexible survival models, and adjustment for treatment switching.
Supervisor: Dr Nicky Welton.
Lead Institution: Bristol.

Use of linked clinical and genotypic databases to understand the genetic contributions to clinical outcomes in individuals with HIV
This project will investigate genetic predictors of response to antiretroviral treatment for HIV infection, based on high density genotyping of 5200 individuals (HIV NIHR BioResource), linked to phenotypic data from the UK Collaborative HIV Cohort Study and UK HIV Drug Resistance Database, two of the world’s most productive HIV cohort studies.
Supervisor: Professor Jonathan Sterne.
Lead Institution: Bristol.

Sowing the seed of mental health – The effect of paternal alcohol use before conception
There is growing interest on pre-conception effects of paternal exposures (eg alcohol) on offspring mental health, but scant evidence from human studies.  This study aims at investigating the nature of such paternal effects, by applying powerful methods to disentangle causation from correlation to data from a network of birth cohort studies.
Supervisor: Dr Luisa Zuccolo.
Lead Institution: Bristol.

Suicides among primary and secondary school teachers: psycho-social autopsy study, quantitative analysis of risk factors for self-harm and suicidal thoughts and qualitative investigation of potential preventive interventions
The project will use qualitative and quantitative methods to explore risk factors for suicide among teachers and potential interventions, specifically: psycho-social autopsy case study, secondary analysis of Office for National Statistics data, collection and analysis of teacher survey data, and qualitative focus groups with teachers.
Supervisor: Dr Judi Kidger.
Lead Institution: Bristol.

Tortoise and hare: Physical activity profiles and their impact on cardiometabolic disease risk
This project is a unique opportunity for a student with very strong quantitative skills to investigate the risk relationships between different ‘physical activity profiles’ and cardiometabolic disease outcomes. This project will help develop individualised prevention strategies, inform future policy and assist with technological innovation.
Supervisor: Dr Miranda Armstrong.
Lead Institution: Bristol.

Using human genetics to reveal novel molecular pathways involved in mediating protective skeletal responses to exercise and mechanical loading
The skeleton’s adaptive response to mechanical loading is compromised in osteoporosis, causing bone fractures. The project identifies molecular mechanisms underlying mechanical responses of the skeleton, implicated in osteoporosis. Cutting edge technologies involving human genetics and 3D models for studying bone mechanoresponses will be used.
Supervisor: Dr Deborah Mason.
Lead Institution: Cardiff.

Influence of lower limb musculature on tibial stress during running: An interdisciplinary approach
The muscles in the lower leg influence bone stress during running, but there is debate about whether this is protective or detrimental. To improve understanding of the interaction between muscles and bone, an interdisciplinary approach will be taken, integrating human movement biomechanics with mathematical modelling and finite element analyses.
Supervisor: Dr Hannah Rice.
Lead Institution: Exeter.

Exploring the molecular mechanisms underlying pre-diagnostic thrombocytosis in lung cancer patients and evaluating its diagnostic value
An investigation of the link between thrombocytosis (raised platelet count) and lung cancer diagnosis involving an epidemiological study and a biomedical study of the effect of lung cancer cells on platelet number and function. This multidisciplinary project will clarify the links between lung cancer and thrombocytosis to expedite cancer diagnosis.
Supervisor: Professor Willie Hamilton.
Lead Institution: Exeter.

Accelerometry data analysis: what are the best methodologies to support the analysis of accelerometry data for population health
Physical activity (PA) is important for health. Much research focuses on improving the amount of PA that people do and this is usually measured with an accelerometer (or wearable) device. How best to analyse the rich data from these devices is an open question. This PhD will explore different analytical approaches for handling accelerometry data.
Supervisor: Dr Mark Kelson.
Lead Institution: Exeter.

Using birth cohorts to understand the impact of urban green space on child health and wellbeing
This interdisciplinary project will investigate the impact of the environments in which children grow up on their health and wellbeing. It will use systematic review, geographical and epidemiological methods, and two UK birth cohorts to investigate the role of urban green space in shaping child and adolescent physical and mental health.
Supervisor: Dr Benedict Wheeler.
Lead Institution: Exeter.

Joint modelling of adverse events and drug response in electronic health record databases
Clinical decisions about drug therapy require an understanding of whether treatments are safe and effective. For some medications, patients who respond well may also be at increased risk of side-effects. Cutting-edge statistical methods will be developed to study this potential link using electronic health record data for type 2 diabetes therapies.
Supervisor: Professor William Henley.
Lead Institution: Exeter.

Body mass index and obesity: investigating gene-environment interactions
This studentship will investigate gene environment interactions in obesity. The student will use genotype and phenotype data from world leading resources including 500,000 individuals in the UK Biobank and 20,000 from the ALSPAC cohort. The student will develop computational, bioinformatics, statistical and epidemiological skills.
Supervisor: Professor Timothy Frayling.
Lead Institution: Exeter.

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