MICA: Whole genome sequencing in multiple sclerosis

多发性硬化症（MS）是一种免疫系统攻击并损害大脑和脊髓的疾病。英国有超过10万人患有这种疾病，其中大多数人患有慢性和日益严重的残疾。仔细的流行病学分析表明，多种遗传因素影响患该病的风险，每一种因素对风险的影响都不大。尽管人类遗传密码包含超过30亿个元素，但现代DNA分析使我们能够识别出近200个相关区域。这些区域中的每一个都包含一个遗传因素，即密码的变化，这会增加患这种疾病的风险。不幸的是，这些区域中的每一个还包含数百个其他不相关的遗传变异。由于缺乏解决方案，很难将这些基因发现转化为对疾病如何发展的见解。然而，相关区域遗传密码的性质表明，大多数因果变异通过改变至关重要的免疫细胞类型中关键基因的表达来发挥作用。在这个项目中，我们将使用一种称为“精细映射”的方法来克服目前缺乏分辨率的问题。在这个项目中，我们将从研究1万名患者的遗传密码开始，并将其与之前MS遗传研究的等效信息以及英国生物银行已经分析的40万名对照受试者相结合。功率计算表明，总的来说，这个庞大的数据集将使我们能够将一半以上地区的潜在因果变量列表减少到<10。然后，我们将把遗传分析中每个短列表的变异与附近基因的表达水平联系起来。利用这些已建立的“表观遗传”数据，我们期望能够在许多地区将可能的变异数量减少到<5。因此，在这个项目中，我们不仅将确定因果变异，而且还将确定相关的关键基因和参与疾病发展的至关重要的免疫细胞类型。我们还将利用其他自身免疫性疾病的数据和其他相关特征，如免疫细胞计数；通过比较、对比和结合这些相关性状的数据，我们将能够进一步完善已建立的关联。据报道，在英国生物银行内，超过50,000人患有某种形式的免疫介导的炎症性疾病（IMID），这为潜在治疗策略的可能交叉性状效应提供了实质性的提升和见解。迄今为止，用于寻找遗传效应的方法只考虑了基因组中一小部分变异。因此，这些方法有可能会遗漏一些重要的、不太常见的变异，而这些变异基本上只存在于受影响的个体中。为了克服这一点，我们将排序所有的变化在一个子集的情况下。全基因组测序也将在英国生物银行进行。因此，上述分析也将扩展到包括使用基因分型芯片遗漏的所有变体。我们已经确定的每一种遗传关联都是了解多发性硬化症如何以及为什么发生的线索，因此每一种关联都有可能导致有效合理治疗的发展，甚至可能提出预防策略。我们的项目将克服限制这些发现转化为相关生物学见解的挫折。我们将产生的知识不仅将改变我们对MS的理解，更重要的是将极大地促进安全有效的合理治疗的发展。

Multiple sclerosis (MS) is a disease in which the immune system attacks and damages the brain and spinal cord. There are over 100,000 people with the disease in the UK, the majority of whom suffer chronic and increasingly severe disability. Careful epidemiological analysis has shown that multiple genetic factors influence the risk of developing the disease, each only conferring a modest effect on risk. Despite the fact that the human genetic code contains more than 3 billion elements modern DNA analysis has allowed us to identify almost 200 relevant regions. Each of these regions contains a genetic factor, a change in the code, which increase the risk of developing the disease. Unfortunately, each of these regions also contains many hundreds of other irrelevant genetic variants. Because of this lack of resolution, it has been hard to translate these genetic discoveries into insights about how the disease develops. However, the nature of the genetic code in the associated regions indicates that most of the causal variants exert their effects by altering the expression of key genes in critically important immune cell types. In this project, we will overcome the current lack of resolution using an approach called "fine mapping".In this project, we will start by studying the genetic code from 10,000 patients and combining this with equivalent information from previous genetic studies of MS and with the 400,000 control subjects already analysed in the UK Biobank. Power calculations indicate that in aggregate this enormous data set will enable us to reduce the list of potentially causal variants to <10 in more than half the regions. We will then correlate each of the short-listed variants from the genetic analysis with the level of expression of nearby genes. Using these established "epigenetic" data we expect to be able to reduce the number of plausible variants to <5 in many regions. In this project we will thus not only define causal variants but will also identify the key genes of relevance and the critically important immune cell types involved in the development of the disease. We will also utilise data from other autoimmune diseases and other relevant traits such as immune cell counts; many of these traits are influenced by the same genetic variants that determine susceptibility to MS. By comparing, contrasting and combining data from these related traits, we will be able to further refine the established associations. Within the UK Biobank more than 50,000 individuals are reported to have some form of immune mediated inflammatory disease (IMID) providing a substantial boost in power and insights into likely cross trait effects of potential therapeutic strategies.To date the methods used to look for genetic effects only consider a fraction of the variants in the genome. These approaches therefore run the risk of missing important less common variants that are essentially only found in affected individuals. To overcome this we will sequence all the variation in a subset of the cases. This whole genome sequencing is also to be undertaken in the UK Biobank. So the analysis described above will also be extended to include all those variants that are missed using genotyping chips.Each of the genetic associations we have identified is a clue to how and why MS develops, and each thus has the potential to lead to the development of an effective rational treatment, and might even suggest preventative strategies. Our project will overcome the frustrations that have limited the translation of these discoveries into relevant biological insights. The knowledge we will generate will not only transform our understanding of MS but more importantly will significantly promote the development of safe and effective rational therapy.