Simple questions about neurodegenerative disease: Where? When? What?

阿尔茨海默病主要是由基因引起的，而不是生活方式因素。如果同卵双胞胎中的一个已经患有这种疾病，那么他们患这种疾病的概率是79%。通过比较患病人群和健康人的DNA，我们可以确定他们DNA中增加患病可能性的位点。近年来，已经确定人类基因组的数千个变化可能导致疾病风险。每个DNA变异只能解释疾病风险的一小部分，但数千个这样的变异可以解释个人疾病风险的大部分。这些基因座所涉及的生物学过程可以理解为与疾病有因果关系。因此，了解神经退行性疾病的机制已经成为一个统计问题：我们只需要找到将这些变异联系在一起的模式。关于神经退行性疾病有许多悬而未决的问题。事实上，对于大多数脑部疾病，我们甚至连一些看似基本的问题都没有答案：大脑的哪个部分出了问题，是在什么年龄发生的？对于神经退行性疾病，直到晚年才出现症状，人们很容易认为疾病引起的变化发生在晚年：几条证据表明，情况可能并非完全如此，大脑发育早期发生的变化可能与此有关。近年来，我利用遗传学来确定导致精神分裂症的细胞类型，并解释为什么它的发病年龄发生在成年早期。这是通过表明导致疾病的变异优先影响在特定细胞中起作用的基因来实现的。使用类似的方法，我发表了第一篇论文，表明阿尔茨海默氏症的基因在一种被称为“小胶质细胞”的细胞中表达丰富，这种细胞被认为是大脑的免疫系统。这一发现对该领域来说是一个惊喜，因为阿尔茨海默病传统上被认为是一种神经元疾病。与这一预期相反，在神经元中没有发现阿尔茨海默病风险基因的富集。最近，我将这种方法扩展到帕金森病：对于这种疾病，结果证实了疾病机制的主要理论（显示多巴胺能神经元的富集），但也涉及一种称为少突胶质细胞的细胞，这种细胞以前从未与该疾病相关。该项目的第一部分将涉及进一步调查这两个差异：神经元与阿尔茨海默氏症无关，少突胶质细胞与帕金森症有关吗？一旦我们确定了导致神经退化的细胞类型，我们就可以解决疾病发生的年龄问题。我们知道细胞的行为在整个生命周期中会发生变化，但我们不知道这是如何或为什么在分子上发生的。首先，我们将绘制出因果细胞类型变化的“图谱”，然后我们将测试与疾病相关的基因变异是否与发育或老年更相关。我们真正需要知道的是：细胞内部发生了什么导致疾病？一旦我们了解了这一点，我们就可以开发药物来逆转这一过程。我们可以再次使用统计数据进行调查（尽管我们将再次需要大量数据来描述相关细胞类型内的生物调节过程）。众所周知，导致疾病的遗传变异主要是通过破坏DNA和蛋白质/RNA之间的分子相互作用来起作用的。DNA上其他分子结合的位点往往有不同的序列：我们可以从公开可用的数据集中了解这些序列，然后预测遗传变异对分子相互作用的影响。然后，我们可以用统计数据来测试，是否某种特定类型的分子相互作用（例如，特定转录因子的结合）被破坏了。一旦确定，我们就可以开始尝试逆转对这些结合位点的疾病影响。

Alzheimer's disease is largely caused by genetics, rather than lifestyle factors. The probability of an identical twin developing the disease, if their co-twin already has is ~79%. By comparing the DNA of people who develop a disease against healthy people, we can identify sites in their DNA which increase the likelihood of getting the disease. In recent years it has been established that thousands of changes to the human genome can contribute to disease risk. Each DNA variant explains only a tiny part of the disease risk, but thousands of these variants can explain much of an individual's disease risk. Biological processes implicated by these loci can be understood as being causally involved in the disease. Understanding the mechanisms of neurodegenerative diseases has thus become a statistical problem: we just need to find the patterns that link the variants together.There are many open questions about neurodegenerative diseases. Indeed, for most brain diseases, we do not even have answers to seemingly basic questions: which part of the brain has gone wrong, and at which age did this occur? For neurodegenerative diseases, which do not show symptoms until late life, it would be easy to assume that the disease causing changes occur in late life: several lines of evidence suggest that this may not be entirely the case though, and that changes which occur early in brain development may be involved.In recent years I used genetics to identify the cell types which cause schizophrenia and to explain why it's age of onset occurs in early adulthood. This was done by showing that the variants which cause the disease preferentially affect genes which act in particular cells. Using a similar approach, I published the first paper showing that Alzheimer's genes have enriched expression in a type of cell called 'microglia' which are thought of as the immune system of the brain. This finding was a surprise to the field as Alzheimer's had traditionally been considered a neuronal disease. Contrary to this expectation, no enrichment of Alzheimer's risk genes has been found in neurons. Recently I extended the approach to Parkinson's disease: for this disease, the results confirmed the dominant theory of disease mechanism (showing an enrichment in dopaminergic neurons) but also implicated a type of cell known as oligodendrocytes, which had never previously been associated with the disease. The first part of this project will involve further investigating these two discrepancies: are neurons not involved in Alzheimer's, and are oligodendrocytes involved in Parkinson's?Once we have identified the cell types which cause neurodegeneration, we can address the issue of the age at which the disease acts. We know that the behaviour of cells changes across the lifespan, but we don't know how or why this occurs molecularly. First we will develop a 'map' of the changes which occur in the causal cell types, then we'll test whether the disease associated genetic variants are more associated with development or old age.What we really need to know is: what happens within a cell to cause the disease? Once we understand this, we can develop drugs to reverse this process. We can investigate this using statistics again (although we will again need plenty of data describing biological regulatory processes within the relevant cell types). Genetic variants which cause disease are known to mostly act by disrupting molecular interactions between DNA and proteins/RNA. Sites on DNA where other molecules bind tend to have distinct sequences: we can learn these sequences from publicly available datasets, then predict the effect of genetic variants on molecular interactions. We can then test statistically, whether a particular type of molecular interaction (for instance, the binding of a particular transcription factor) has been disrupted. Once identified, we can begin attempts to reverse disease effects on these binding sites.