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

痴呆症是英格兰和威尔士的主要死因。它的特征是记忆力丧失和视觉空间问题（例如在熟悉的环境中迷路），对受影响的患者及其家人来说都是一种非常痛苦的疾病。血管性痴呆（Vascular dementia，VaD）是继阿尔茨海默病（Alzheimer's disease，AD）之后的第二大常见痴呆类型，估计65岁以上的老年人中有1-5%会受到影响。然而，检查VaD患病率的研究仅包括“纯”病例;这意味着排除了其他类型痴呆症的患者。事实上，超过70%的痴呆症病例是“混合型”的，这意味着同一患者在不同程度上存在多种病理。因此，具有血管成分的痴呆症（DVC）的真实患病率可能远高于先前的估计。在了解AD的遗传贡献方面取得了巨大进展，对死后和活体队列的大型全基因组关联研究（GWAS）确定了30个遗传标记。这使得包括我在内的研究人员能够使用最先进的分析方法来调查AD的因果环境风险因素。然而，对DVC的研究严重滞后。AD GWAS排除了脑血管疾病患者，并且已发表的VaD GWAS仅包含“纯”病例，这意味着样本较小（约100例病例），并且临床代表性也较低，因为纯VaD病例相对罕见。VaD GWAS也只包含活的队列，使得诊断不精确。在这个奖学金期间，我将对来自MRC英国脑库网络的7,000人进行基因分型（这意味着整个脑库都进行基因分型），并建立脑遗传学平台，将来自地球仪的现有死后脑库与遗传数据相关联，为科学界建立世界上最大的此类资源（至少16,500个样本）。整理这些数据很重要，因为现有的财团规模很小，包含的遗传数据非常有限（或没有），使得大规模的遗传分析不可行。然后，我将进行有史以来第一次DVC的遗传研究，这不仅是新颖的，而且比研究“纯”VaD更具临床相关性。这项工作将扩大以前的AD遗传研究，主要是在活的患者中进行的。我将使用高度特征化的尸检样本来显著提高诊断的精确度。我还将使用尖端的遗传流行病学方法来提高检测脑血管信号的能力，即使在存在多种病理的情况下，也能识别新的DVC基因，为AD和VaD的共同和不同病因提供见解。一旦进行了遗传研究，我将为DVC开发“多基因风险评分（PRS）”（衡量一个人对疾病的遗传易感性），利用PRS对血管特征的额外信息的力量来帮助改善预测。这些PRS将有助于识别可能更容易发生DVC的个体。我将比较DVC遗传风险高与低的人在整个生命过程中的认知功能轨迹，看看他们是否在更早的年龄下降，或者比遗传风险低的人下降得更快。最后，我将确定DVC的可修改的因果决定因素。这些可修改的目标将为英国制药业（化学预防和治疗）的药物优先战略提供信息，并将用于制定预防痴呆症的公共卫生干预措施。总之，这项研究将改变我们对一种被忽视但非常普遍的痴呆症的病因和机制途径的理解。反过来，这将有助于将干预措施转化为公共卫生政策，并确定潜在的治疗目标，其首要目标是减轻痴呆症的负担。

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.