Genetic and non-genetic risk factors for dementia
Currently, 50 million individuals live with dementia worldwide with this number expected to treble to 150 million by 2050. Despite this, there is growing evidence from longitudinal cohort studies that dementia could be prevented or delayed through the targeting of modifiable risk factors.
However, the evidence base is mixed and has primarily been derived from studies with a small number of cases, a limited range of phenotypic data or short follow-up periods. UK Biobank (UKB) addresses these limitations by consisting of half a million extensively phenotyped women and men followed up for incident diseases, such as dementia, through ongoing linkage to medical records (currently up to 15 years).
Furthermore, 100,000 UKB participants are undergoing neuroimaging, with at least 10,000 participants undergoing repeat imaging. This presents an unprecedented opportunity to explore the neurological and neurovascular mechanisms that underlie any observed relationships between modifiable risk factors and dementia.
The availability of genome-wide genotyping in UKB will enable the candidate to explore whether relationships are modified by genetic risk either through APOE-e4 or polygenic risk of dementia.
Opportunities to conduct complementary analyses in other cohorts or datasets, such as CPRD, will be explored.
RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING
The overarching aim of the project is to build upon previous research on potentially modifiable risk factors for dementia utilising the UKB cohort, and elucidating potential mechanisms using neuroimaging measures available in the dataset.
The exact project will be shaped by the student with the supervisors. The student should identify risk factors which are well characterised in UKB and can either focus on a particular area (i.e. vascular factors) or take a broader approach (i.e. a combination of factors). The project should use the diverse data available in UKB to address novel questions not possible in other cohorts, with a particular focus on exploring mechanistic pathways using the neuroimaging data. The student will be encouraged to explore the use of other cohort studies to complement analyses conducted in UKB.
FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING
The student will be actively encouraged to attend relevant training courses, for example on the usage of statistical software packages and advanced statistical analyses techniques. Whilst fieldwork is not anticipated, the usage of other non-UKB cohorts might require the student to attend other locations where the data is stored.
This project will suit a student with a keen interest in identifying ways to prevent dementia, and who is looking to expand their skills and experience in epidemiological design and statistical analysis, who would like to work with large-scale, complex epidemiological datasets and gain experience with genetic data.