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。它的特点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极其痛苦的疾病。目前还没有能够阻止或延缓病情发展的治疗方法，我们对其原因也知之甚少。血管性痴呆(VAD)是仅次于阿尔茨海默病(AD)的第二种最常见的痴呆类型，据估计，65岁以上的人中有1%-5%的人会受到影响。然而，研究VaD患病率的研究只包括“纯”病例；这意味着排除了其他类型的痴呆症患者。事实上，超过70%的痴呆症病例是混合的，这意味着同一患者存在不同程度的多种病理。因此，血管成分痴呆(DVC)的真实患病率可能比之前估计的要高得多。在理解遗传对阿尔茨海默病的贡献方面取得了巨大的进展，对死后和活着的队列进行的大规模全基因组关联研究确定了30个遗传标记。这使得研究人员，包括我自己，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 GWA排除了脑血管疾病患者，发表的VaD GWA只包含“纯”病例，这意味着样本很小(约100例)，临床代表性也较低，因为纯VaD病例相对较少。VAD Gwas也只包含活的队列，使得诊断不准确。在这次研究期间，我将从MRC UK脑库网络中对7,000人进行基因分型(这意味着整个脑库都是分型的)，并生成脑遗传学平台，将全球现有的已连接遗传数据的尸检脑库汇集在一起，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，因为现有的联盟规模很小，包含的基因数据非常有限(或根本没有)，这使得大规模的基因分析变得不可行。然后，我将进行有史以来第一次DVC的遗传学研究，这不仅是新的，而且比研究“纯”VaD更具有临床意义。这项工作将在先前主要在活体患者中进行的阿尔茨海默病遗传学研究的基础上进行扩展。我将使用高度特色化的尸检样本来显著提高诊断的准确性。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情况下也是如此，从而能够识别新的DVC基因，为AD和VAD共同和不同的病因提供见解。一旦进行了基因研究，我将为DVC开发“多基因风险评分(PRSS)”(衡量一个人对某种疾病的遗传易感性)，利用PRSS提供的关于血管特征的额外信息来帮助改进预测。这些PRS将有助于识别可能更有DVC风险的个人。我将比较DVC遗传风险高的人和低遗传风险的人整个生命过程中认知功能的轨迹，看看它们是在更早的年龄下降，还是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，并将用于开发预防痴呆症的公共卫生干预措施。总而言之，这项拟议的研究将改变我们对一种被忽视但非常普遍的痴呆症的原因和机制的理解。反过来，这将促进将干预措施转化为公共卫生政策，并确定潜在的治疗目标，最重要的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.