Defining and diagnosing neurodegenerative Movement Disorders through integrated analysis of Genetics And neuroPathology (MD-GAP)

我们正在进入这样一个时代：治疗退行性疾病，如帕金森病和阿尔茨海默病，将直接针对潜在的蛋白质病理学。大多数进行性迟发性神经系统疾病涉及异常不溶性蛋白聚集沉积，例如帕金森病的路易体和阿尔茨海默病的淀粉样斑块。现在有越来越多的针对蛋白质病理学的实验性疗法，例如涉及抗体和基于基因的疗法。遗传学在很大程度上基于对临床诊断患者的研究，为神经系统疾病提供了巨大的见解。神经病理学是诊断神经系统疾病的“黄金标准”，MRC和英国慈善机构已经投资开发了MRC英国脑库网络（BBN），以便更好地了解这些疾病。在这里，我们将把高通量遗传分析与神经病理学结合起来，以提高对神经疾病的诊断和理解。早期诊断：是提供有效治疗的主要障碍。在疾病的早期阶段，典型的疾病特征可能不明显。例如，运动迟缓（帕金森氏症）可能是由多种不同的疾病引起的，包括帕金森氏病，在确定临床病程和治疗反应之前，明确的诊断可能不会变得明显。我们将研究病理诊断病例的遗传变异数据，以提高早期诊断。我们相信，基于分析多个遗传标记（多基因风险）的诊断算法将改善临床诊断。改进的病例-对照分析：将通过将患有病理证实的疾病（如帕金森病）的个体与未患神经系统疾病的对照组进行比较来实现。这将消除临床误诊对神经系统疾病分析的影响。疾病异质性：是帕金森病等疾病的一个重要特征。一些患者会发展为痴呆并迅速进展，而另一些患者则会有更良性、更轻微的病程。我们认为这种异质性是由不同的神经病理学驱动的。例如，帕金森氏症的痴呆与阿尔茨海默氏症的共病理（淀粉样斑块和神经原纤维缠结）有关。我们将直接研究共同病理的遗传驱动因素，并将其与临床异质性分析相结合，以解码神经系统疾病的不同模式，最终可能对不同的治疗产生反应。改善资源：BBN被世界各地的研究人员用于研究神经系统疾病。人们越来越需要了解遗传风险因素的影响，而最直接的方法之一就是观察有或没有遗传风险因素的个体的脑组织。这些基因数据将提供给真正的研究人员，这将加快这一过程，并允许研究人员选择感兴趣的组织和样本，最大限度地利用这些患者组织档案。

We are entering an era in which therapies for degenerative diseases such as Parkinson's and Alzheimer's will be directed towards the underlying protein pathology. Most progressive later onset neurological diseases involve the deposition of abnormal insoluble proteins as aggregates, for example Lewy bodies in Parkinson's and amyloid plaques in Alzheimer's. There are now an increasing number of experimental therapies which are directed towards protein pathology, for example involving antibodies and gene based therapies. Genetics has provided tremendous insights into neurological disease, largely based on studies in clinically diagnosed patients. Neuropathology is the "gold standard" for the diagnosis of neurological diseases, and the MRC and UK charities have invested in developing the MRC UK Brain Banks Network (BBN) to enable better understanding of these conditions. Here, we will integrate high throughput genetic analysis with neuropathology to improve the diagnosis and understanding of neurological disease. Early diagnosis: is a major barrier to the delivery of effective treatment. At the earliest disease stages typical disease features may not be apparent. For example, slowness of movement (Parkinsonism) can be due to multiple different diseases including Parkinson's disease, and a definite diagnosis may not become apparent until the clinical course and response to treatment are established. We will study genetic variant data from pathologically diagnosed cases to improve early diagnosis. We believe that diagnostic algorithms based on analyzing many genetic markers (polygenic risk) will improve the clinical diagnosis. Improved case-control analysis: will be achieved by comparing individuals with pathologically proven diseases such as Parkinson's with controls unaffected by neurological disease. This will remove the effect of clinical misdiagnosis in the analysis of neurological disease. Disease heterogeneity: is an important feature of conditions such as Parkinson's. Some patients develop dementia and rapidly progressive disease whereas others have a more benign, milder disease course. We believe that this heterogeneity is driven by differential neuropathology. For example, dementia in Parkinson's is associated with Alzheimer's co-pathology (amyloid plaques and neurofibrillary tangles). We will directly study the genetic drivers of co-pathology and integrate this with analyses of clinical heterogeneity to decode the different patterns of neurological disease, which may ultimately respond to different therapies. Improving resources: The BBN is used by researchers into neurological disease from around the world. There is a growing need to understand the implications of genetic risk factors - and one of the most straightforward ways to do this is to look at brain tissue from individuals with and without the genetic risk factor. This genetic data will be made available to bona fide researchers which will speed up this process and allow researchers to select tissue and samples of interest, maximising the usefulness of these patient tissue archives.