Genomics of childhood acute lymphoblastic leukemia in the Childhood Cancer and Leukemia International Consortium

项目摘要/摘要 在全球范围内，急性淋巴细胞白血病(ALL)是0-14岁儿童最常见的癌症，具有 估计每年有7.4万起事件。每年有近1500,000年的生命因此而丧失； 由于年轻人口众多，所有人的负担都集中在南部、东南部和东部 亚洲；中东和北非；撒哈拉以南非洲。这些趋势突显了研究的必要性 解决全球人口中需求最大的所有人面临的风险。ALL的发病率也显示出明显的 按血统分类的图案。在美国，拉丁裔的风险最高，其次是欧洲人和亚太地区 岛上的儿童，而非洲裔美国儿童的比例到目前为止最低。有理由相信这些 模式可能至少部分地基于遗传学。例如，童年的发病率都是在散居海外的人中发生的 美国的人口在很大程度上概括了国际发病模式。种系遗传学 到目前为止披露的所有风险的体系结构表明，所有风险都具有更强的风险组件，原因是 在成人癌症中发现的常见多态变异，以及全基因组关联研究(GWAS) 已确定15种与B细胞前体ALL(B-ALL)相关的常见变体，约占85% 所有病例)，它们共同描述了最低端和最高端之间风险的近10倍的差异 多基因风险分数的分布。然而，这些研究在很大程度上检查了欧洲的基因组。这个 儿童癌症和白血病国际联合会(CLIC)非常适合于了解基因组 在许多祖先的孩子身上存在着所有风险的架构。CLIC的集体基因组数据集包括约12,000个 来自五大洲的儿童，使其成为世界上最大和最多样化的此类数据集。 此外，CLIC的大多数基因组数据都嵌入了流行病学研究，而不是纯粹的临床研究 到目前为止的研究。有了这一资源，样本量增加了一倍多，我们建议 1)使用基于SNP的方法估计不同人群中所有人的遗传力，包括非洲人/非洲人- 美国人(AFR)、混血美国人(即拉丁裔；AMR)、东亚人(EAS)、欧洲人(EUR)、中东人 东非/北非(MENA)、南亚(SAS)和东南亚(SEA)；2)进行全面的 全基因组和局部发现与ALL相关的变异；以及3)创建特定于群体的多基因 风险评分，并检查其与CLIC内统一的流行病学数据的关系。在……结束时 这项研究，CLIC将阐明比目前存在的更全面的所有遗传流行病学 在代表地球上大多数儿童的人口中；并将首次同时考虑 非遗传风险因素。我们将进一步确定功能验证的候选变体的优先顺序，并构建 强大的基础设施，用于未来分析CLIC的基因组数据集。

PROJECT SUMMARY/ABSTRACT Globally, acute lymphoblastic leukemia (ALL) is the most common cancer in children 0-14 years of age, with an estimated 74,000 incident cases each year. Nearly 1,500,000 years of life are lost due to the disease annually; and because of their large, young populations, the burden of ALL is centered within south, southeast, and east Asia; the middle east and north Africa; and sub-Saharan Africa. These trends highlight the need for research addressing risk for ALL in global populations where the need is greatest. Incidence of ALL also shows distinct patterns by ancestry. In the United States, risk is highest in Latinos, followed by European and Asian/Pacific Islander children, while African-American children have by far the lowest rates. There is reason to believe these patterns may be based at least partially on genetics. For instance, incidence of childhood ALL among diaspora populations in the United States largely recapitulates international patterns of incidence. The germline genetic architecture of ALL risk revealed to date suggests that ALL has a stronger risk component accounted for by common polymorphic variants than is found in adult cancers, with genomewide association studies (GWAS) having identified over 15 common variants associated with B-cell precursor ALL (B-ALL, comprising ~85% of ALL cases), which together describe nearly a 10-fold difference in risk between the lowest and highest ends of distribution of polygenic risk score. However, these studies have largely examined European genomes. The Childhood Cancer and Leukemia International Consortium (CLIC) is ideally suited to understanding the genomic architecture of ALL risk in children of many ancestries. CLIC’s collective genomic datasets comprise ~12,000 children with ALL from five continents, making them both the largest and most diverse such datasets worldwide. Moreover, most of CLIC’s genomic data is embedded within epidemiologic studies, unlike the purely clinical studies to date. With this resource, which more than doubles the sample size over previous GWAS, we propose to: 1) estimate heritability of ALL using SNP-based methods in diverse populations including Africans/African- Americans (AFR), admixed Americans (i.e. Latinos; AMR), East Asians (EAS), Europeans (EUR), Middle Eastern/North Africans (MENA), South Asians (SAS), and Southeast Asians (SEA); 2) conduct comprehensive genomewide and local discovery for variants associated with ALL; and 3) create population-specific polygenic risk scores and examine their relationship to harmonized epidemiologic data within CLIC. At the conclusion of this study, CLIC will have articulated a far more comprehensive genetic epidemiology of ALL than exists today in populations that represent most of the children on earth; and, for the first time, will simultaneously consider non-genetic risk factors. We further will have prioritized candidate variants for functional validation and built a robust infrastructure for future analyses of CLIC’s genomic datasets.