MICA: Whole genome sequencing in multiple sclerosis

MICA：多发性硬化症的全基因组测序

• 批准号: MR/V034391/1
• 负责人: Stephen Sawcer
• 金额: $ 50.71万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FV034391%2F1
• 关键词: MICA; Whole; genome; sequencing; multiple

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.

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上这种疾病的风险，每种因素对风险的影响都很小。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，这会增加患上这种疾病的风险。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，相关区域中遗传密码的性质表明，大多数致病变体通过改变关键基因在至关重要的免疫细胞类型中的表达来发挥其作用。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，我们将首先研究10，000名患者的遗传密码，并将其与之前MS遗传研究的等效信息以及英国生物库中已经分析的400，000名对照受试者相结合。功效计算表明，总的来说，这一庞大的数据集将使我们能够在一半以上的地区将潜在的因果变异列表减少到<10。然后，我们将从遗传分析中筛选出的每个变体与附近基因的表达水平相关联。使用这些已建立的“表观遗传”数据，我们期望能够在许多地区将合理变异的数量减少到<5。因此，在这个项目中，我们不仅将定义致病变异，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。我们还将利用来自其他自身免疫性疾病和其他相关性状（如免疫细胞计数）的数据;这些性状中的许多都受到决定MS易感性的相同遗传变异的影响。在英国生物样本库中，有超过50，000人被报道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增强和见解。迄今为止，用于寻找遗传效应的方法只考虑了基因组中的一小部分变异。因此，这些方法存在遗漏重要的不太常见的变异的风险，这些变异基本上只在受影响的个体中发现。为了克服这一点，我们将在一个子集的情况下的所有变化的顺序。全基因组测序也将在英国生物库进行。因此，上述分析也将扩展到包括所有那些使用基因分型芯片遗漏的变异。我们已经确定的每一个遗传关联都是MS如何以及为什么发展的线索，因此每一个都有可能导致有效的合理治疗的发展，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，更重要的是将显着促进安全有效的合理治疗的发展。