Modifiable risk factors for late-onset dementia
Currently, 50 million individuals live with dementia worldwide with this number expected to treble to 150 million by 2050. Whilst there are a lack of disease modifying treatments, 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 14 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 DPhil project: 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 supervisory team have experience conducting systematic reviews, so the first phase of the DPhil (Year 1) could consist of a review of the literature, followed by epidemiological analyses using UKB (Years 2 and 3). 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.
RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING
This project will provide the student with the opportunity to work with large-scale, diverse, epidemiological data, including the largest and most diverse neuroimaging dataset currently available. The student will develop advanced statistical skills in the analysis of cross-sectional and longitudinal data, and learn to perform systematic reviews and meta-analyses. The project will provide the opportunity to work within a strong multidisciplinary team whilst encouraging the development of internal and external collaborations. The student will receive experience in presenting at international conferences and writing up research findings for publication in peer-reviewed journals.
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, and who would like to work with large-scale, complex epidemiological datasets.