Causal determinants of dementia with a vascular component (DVC-RISK)

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Dementia is the leading cause of death in England and Wales. It is characterised by memory loss and visuospatial problems (e.g. becoming lost in a familiar environment) and is an extremely distressing disease for both the affected patients and their families. There are currently no treatments able to halt or delay progression, and we know very little about what causes it. Vascular dementia (VaD) is the second most common dementia type after Alzheimer's disease (AD), estimated to affect 1-5% of over 65s. However, studies examining VaD prevalence include only 'pure' cases; meaning patients with other types of dementia are excluded. In reality, over 70% of dementia cases are 'mixed', meaning multiple pathologies exist in the same patient to varying degrees. Thus, the true prevalence of dementia with a vascular component (DVC) is likely much higher than previously estimated. Huge progress has been made in understanding genetic contributions to AD, with large genome-wide association studies (GWAS) on post-mortem and living cohorts identifying 30 genetic markers. This has enabled researchers, including myself, to investigate causal environmental risk factors for AD using state-of-the-art analytical approaches. However, research for DVC has severely lagged. AD GWAS have excluded patients with cerebrovascular disease, and published GWAS for VaD contain only "pure" cases, meaning samples are small (~100s of cases) and also less clinically representative, because pure VaD cases are relatively rare. VaD GWAS also contain only living cohorts, making diagnosis imprecise. During this fellowship, I will genotype 7,000 people from the MRC UK Brain Bank Network (meaning the whole of the brain bank is genotyped), and generate the Brain Genetics Platform, bringing together from across the globe existing post-mortem brain banks that have linked genetic data, to establish the worlds' largest such resource for the scientific community (minimum 16,500 samples). Collating these data is important because existing consortia are small and contain very limited (or no) genetic data, making large-scale genetic analyses unfeasible. I will then conduct the first ever genetic study of DVC, which is not only novel, but is much more clinically relevant than studying 'pure' VaD. This work will expand upon previous genetic studies of AD, which has been conducted primarily in living patients. I will use highly characterised post-mortem samples to dramatically improve precision of diagnosis. I will also use cutting-edge genetic epidemiology methods to boost power for detecting cerebrovascular signals even in the presence of multiple pathologies, enabling the identification of novel DVC genes, providing insights into the shared and distinct aetiologies of AD and VaD. Once the genetic study is conducted, I will develop 'polygenic risk scores (PRSs)' (which measure a person's genetic susceptibility to a disease) for DVC, harnessing the power of additional information from PRSs for vascular traits to help improve prediction. These PRSs will help identify individuals who may be more at risk of DVC. I will compare trajectories of cognitive function across the life course in people with a high vs a low genetic risk for DVC to see if they decline at an earlier age, or at a faster rate than people with lower genetic risk. Finally, I will identify modifiable causal determinants of DVC. These modifiable targets will inform drug prioritisation strategies for the UK pharmaceutical industry (for both chemoprevention and treatment), and will be used to develop public health interventions for dementia prevention. In summary, the proposed research will transform our understanding of the causes and mechanistic pathways of an overlooked, but very prevalent, form of dementia. This, in turn, will improve translation into public health policies for interventions and identify potential therapeutic targets, with the overriding goal of reducing the burden of dementia.