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

阿尔茨海默病主要是由遗传因素引起的，而不是生活方式因素。同卵双胞胎患上这种疾病的可能性，如果他们的双胞胎已经患上了的话，大约是79%。通过将患病者的DNA与健康人的DNA进行比较，我们可以确定他们DNA中增加患病可能性的位点。近年来，人们已经确定，人类基因组的数千种变化可能会导致疾病风险。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体的大部分疾病风险。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学问题：我们只需要找到将变异联系在一起的模式。事实上，对于大多数脑部疾病，我们甚至无法回答看似基本的问题：大脑的哪个部分出了问题，以及这是在哪个年龄发生的？对于神经退行性疾病，直到晚年才表现出症状，很容易假设导致疾病的变化发生在晚年：几条证据表明，这可能并不完全是这种情况，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。这是通过证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称为“小胶质细胞”的细胞中丰富表达，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，因为阿尔茨海默氏症传统上被认为是一种神经疾病。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，我扩展了帕金森病的方法：对于这种疾病，结果证实了疾病机制的主导理论（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这种疾病相关。这个项目的第一部分将涉及进一步调查这两个差异：神经元不参与阿尔茨海默氏症，少突胶质细胞参与帕金森氏症？一旦我们确定了导致神经变性的细胞类型，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，但我们不知道这种变化在分子水平上是如何发生的，也不知道为什么会发生。首先，我们将绘制出致病细胞类型发生变化的“地图”，然后我们将测试疾病相关的遗传变异是否与发育或衰老更相关。我们真正需要知道的是：细胞内发生了什么导致疾病？一旦我们理解了这一点，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学来研究这一点（尽管我们仍然需要大量数据来描述相关细胞类型中的生物调节过程）。已知导致疾病的遗传变异主要通过破坏DNA和蛋白质/RNA之间的分子相互作用来起作用。DNA上与其他分子结合的位点往往具有不同的序列：我们可以从公开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，我们可以用统计学方法来检验某种特定类型的分子相互作用（例如，某种特定转录因子的结合）是否被破坏了。一旦确定，我们就可以开始尝试逆转疾病对这些结合位点的影响。

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.