Summary
Multimorbidity (two or more chronic conditions affecting an individual) is a growing global health concern associated with higher healthcare usage, costs, and mortality.
Many common patterns of multimorbidity exist; often a first (index) condition will predispose you to others - for example, hypertension (high blood pressure) is a risk factor for multiple comorbidities (including type 2 diabetes, coronary artery disease, heart failure, and chronic kidney disease).
Multimorbidity is associated with demographic characteristics (e.g. age, sex, socioeconomic status), environment, lifestyle, and individuals' genetic predisposition to diseases.
Many co-occurring conditions may be caused by shared upstream risk factors, and combining genetics and health record data can help to identify such factors. Past research from the lab interrogated the extent to which the relationship between sleep apnoea and cardiovascular disease (CVD) is mediated by adiposity, and there are many more such relationships to study.
Project aims
The goal of the project is to find molecules (lipid fractions, metabolites, proteins) and pathways that underlie different patterns of multimorbidity involving CVDs, identifying novel risk factors and therapeutic targets.
The project will leverage multi-omic and health record datasets from departmental cohorts (INTERVAL, BELIEVE) and those from external datasets (e.g. UK Biobank, AllOfUs, Our Future Health).
Genetic methods such as polygenic scores, gene x environment interaction studies, Mendelian randomization, mediation analyses, and machine learning methods applied to health care record data will be used with a range of conditions to study (the student will have some flexibility in choice).
The supervisory team for this project will also include other senior PIs from the Cardiovascular Epidemiology Unit and likely involve collaborations with external institutions.
Contact details
Dr Samuel Lambert - sl925@medschl.cam.ac.uk
Opportunities
This project is open to applicants who want to do a:
- PhD