The genetic basis of progression in multiple sclerosis

这项提案将寻求识别和表征调节疾病活动和 多发性硬化症的进展。该项目建立在一个假设的基础上，即等位基因变异影响 疾病轨迹可以通过足够强大的、无偏见的基因筛查来明确识别，并将 从而采用多维统计分析来确定关键基因网络和生物过程 潜在的疾病进展。为了将临时波动造成的混乱影响降至最低 多发性硬化症早期的特点是复发性炎症活动导致的残疾。 该项目的发现阶段将只关注患有长期疾病的老年受试者(年龄至少55岁) 期限(&gt；10年)。由于通常只有不到1/7的患者符合这些标准，因此该方法仅 可能是因为国际多发性硬化症拥有巨大的生物标本资源 遗传学联合会(IMSGC)(&gt；62,000例)。我们将使用多发性硬化严重程度评分(MSSS)作为 我们对进展的测量；一个顺序的十进制分数，表明患者的扩展残疾状况 与病程相同的其他患者相比，该量表(EDSS)排名靠前。IMSGC有DNA 来自近9000名年龄较大、病程较长的患者，这些患者至少有一项MSSS测量。对于最大值 效率我们将与卡罗林斯卡研究所的同事合作筛查这9000个病例 瑞典。复制的结果将立即在细胞特定路径和TOP的上下文中进行分析 随后将探索候选基因的相互作用，包括它们的功能验证。 具体地说，在目标1中，我们将使用最新一代的基因分型对4,000名患者进行GWAS 芯片，这将使我们能够评估7000多万个变种。在具体目标2中，我们将 然后在剩余的5,000个样本中复制目标1中确定的最相关的标记，进行 在至少两个以上独立样本群体中的额外重复，荟萃分析，并执行 生物信息学和最有希望的关联的实验验证。将两个数据库中的数据合并 这些努力将提供力量来识别仅占MSSS变异0.5%的变异。这个 疾病表达的遗传修饰物的识别将对 对多发性硬化症的理解和管理，特别是对于进展性多发性硬化症，目前最令人残疾和 无法治愈的疾病形式。

This proposal will seek to identify and characterize the genetic factors that modulate disease activity and progression in multiple sclerosis (MS). The project builds on the hypothesis that allelic variants affecting disease trajectory are eminently identifiable through adequately powered unbiased genetic screens, and will thus employ a multi-dimensional statistical analysis to identify key gene networks and biological processes underlying disease progression. In order to minimize the confounding influence of the temporary fluctuations in disability that result from the relapsing inflammatory activity that characterizes the early stages of MS the discovery phase of this project will focus exclusively on older subjects (aged at least 55) with a long disease duration (>10 years). Since typically less than 1 in 7 patients satisfy these criteria this approach is only possible because of the enormous bio-specimen resource available to the International Multiple Sclerosis Genetics Consortium (IMSGC) (>62,000 cases). We will use the Multiple Sclerosis Severity Score (MSSS) as our measure of progression; an ordinal decile score that indicates how a patient's Expanded Disability Status Scale (EDSS) ranks in comparison with other patients with the same duration of disease. The IMSGC has DNA from almost 9,000 older long disease duration patients that have at least one MSSS measure. For maximal efficiency we will screen these 9,000 cases in collaboration with our colleagues from the Karolinska Institute in Sweden. Replicated results will be immediately analyzed in the context of cell-specific pathways and top candidates will be subsequently explored for genetic interactions, including their functional validation. Specifically, in Aim 1 we will conduct a GWAS on 4,000 patients using the latest generation of genotyping chips, which through imputation will allow us to assess more than 70 million variants. In Specific Aim 2 we will then replicate the most associated markers identified in aim 1 in the remaining 5,000 samples, conduct additional replications in at least two more independent sample populations, a meta-analysis, and perform bioinformatics and experimental validation of the most promising associations. Combining the data across both efforts will provide power to identify variants accounting for as little as 0.5% of variances in MSSS. The identification of genetic modifiers of disease expression will have profound translational implications for the understanding and management of MS, and in particular for progressive MS, the most disabling and currently untreatable form of the disease.