The genetic basis of progression in multiple sclerosis

多发性硬化症进展的遗传基础

• 批准号: 10084323
• 负责人: SERGIO E BARANZINI
• 金额: $ 44.28万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-30 至 2022-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10084323
• 关键词: Accounting; Address; Affect; Age; Benign; Bioinformatics; Biological Assay; Biological Process; Cells; Central Nervous System Diseases; Clinical; Collaborations; Country; DNA; Data; Data Set; Development; Disease; Disease Progression; Face; Future; Generations; Genes; Genetic; Genetic Determinism; Genetic Screening; Genotype; Goals; In Vitro; Individual; Inflammatory; Institutes; International; Joints; Masks; Measures; Meta-Analysis; Multiple Sclerosis; Nerve Degeneration; Nervous System Physiology; Outcome; Pathogenesis; Pathway Analysis; Pathway interactions; Patients; Phase; Play; Population; Probability; Prognosis; Relapse; Research; Resources; Running; Sampling; Severities; Statistical Data Interpretation; Subgroup; Sweden; System; Therapeutic; Tissues; Validation; Variant; aged; bioinformatics pipeline; cell type; cohort; cost effective; design; disability; genetic information; genetic variant; genome wide association study; genome-wide; illness length; in silico; individual patient; innovation; insight; interest; multiple sclerosis patient; patient population; prognostic; programs; screening; success

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.

该提案将寻求识别和表征调节疾病活动的遗传因素和 多发性硬化症 (MS) 的进展。该项目建立在等位基因变异影响的假设之上 通过足够有力的公正基因筛查可以清楚地识别疾病轨迹，并且将 因此采用多维统计分析来识别关键基因网络和生物过程 潜在的疾病进展。为了尽量减少暂时波动的混杂影响 由复发性炎症活动导致的残疾，这是多发性硬化症早期阶段的特征 该项目的发现阶段将专门关注患有长期疾病的老年受试者（至少 55 岁） 持续时间（>10 年）。由于通常只有不到七分之一的患者满足这些标准，因此这种方法仅适用于 之所以可能，是因为国际多发性硬化症组织拥有大量的生物样本资源 遗传学联盟 (IMSGC)（>62,000 例）。我们将使用多发性硬化症严重程度评分 (MSSS) 作为 我们衡量进步的标准；顺序十分位数分数，表明患者的扩展残疾状态如何 与具有相同病程的其他患者相比，量表（EDSS）排名。 IMSGC 拥有 DNA 来自近 9,000 名至少有一项 MSSS 测量的老年长病程患者。对于最大 我们将与卡罗林斯卡学院的同事合作筛查这 9,000 个病例，以提高效率 瑞典。复制的结果将立即在细胞特异性途径和顶部的背景下进行分析 随后将探索候选者的遗传相互作用，包括其功能验证。 具体来说，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，通过估算，我们可以评估超过 7000 万个变体。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进行额外重复、荟萃分析，并执行 最有希望的关联的生物信息学和实验验证。合并两者的数据 这些努力将有助于识别仅占 MSSS 0.5% 差异的变异。这 疾病表达的遗传修饰物的鉴定将对疾病产生深远的转化影响 对多发性硬化症的理解和管理，特别是进展性多发性硬化症，这是目前最严重的致残性疾病 该疾病的无法治疗的形式。