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

项目总结/摘要 在全球范围内，急性淋巴细胞白血病（ALL）是0-14岁儿童中最常见的癌症， 估计每年有74，000起事故。每年有近150万年的生命因这种疾病而丧失; 由于这些地区人口众多且年轻，ALL的负担主要集中在南部、东南部和东部 亚洲;中东和北非;以及撒哈拉以南非洲。这些趋势凸显了研究的必要性 在需求最大的全球人群中应对ALL风险。ALL的发病率也显示出明显的 祖先的模式。在美国，拉丁美洲人的风险最高，其次是欧洲人和亚太人 岛民儿童，而非洲裔美国儿童的比例最低。有理由相信这些 模式可以至少部分地基于遗传学。例如，散居国外者中儿童急性淋巴细胞白血病的发病率 美国人群的发病率在很大程度上概括了国际发病率模式。生殖系遗传 迄今为止揭示的ALL风险架构表明，ALL具有更强的风险成分， 与成人癌症相比，常见的多态性变体，全基因组关联研究（GWAS） 已经确定了超过15种与前体B细胞ALL相关的常见变异（B-ALL，包括约85%的 所有病例），这些病例共同描述了最低和最高风险之间的近10倍差异。 多基因风险评分分布。然而，这些研究在很大程度上研究了欧洲人的基因组。的 儿童癌症和白血病国际联盟（CLIC）非常适合了解基因组 在许多祖先的儿童中，ALL风险的结构。CLIC的集体基因组数据集包括约12，000个 来自五大洲的ALL儿童，使其成为全球最大和最多样化的此类数据集。 此外，CLIC的大部分基因组数据都嵌入流行病学研究，不像纯粹的临床研究。 研究至今。有了这个资源，样本量比以前的GWAS增加了一倍多，我们建议 目的：1）使用基于SNP的方法在不同人群（包括非洲人/非洲- 美国人（AFR）、混血美国人（即拉丁美洲人; AMR）、东亚人（EAS）、欧洲人（EUR）、中东人 东部/北非人（MENA），南亚人（SAS）和东南亚人（SEA）; 2）进行全面的 全基因组和局部发现与ALL相关的变异;和3）创建群体特异性多基因 风险评分，并检查其与CLIC内统一流行病学数据的关系。结束时 通过这项研究，CLIC将阐明一个比现在更全面的ALL遗传流行病学 在代表地球上大多数儿童的人口中， 非遗传风险因素。我们还将对候选变体进行功能验证的优先级排序，并构建一个 为CLIC基因组数据集的未来分析提供强大的基础设施。

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.