Human copy number polymorphism and severe malaria

描述(由申请人提供)：这是一个由PI发起的、协作的病例/控制项目，旨在系统地识别与严重疟疾贫血(SMA)和其他形式的严重疟疾相关的人类拷贝数多态(CNP)。CnP代表基因组中的区域，通常是1kb，在种群内正常个体之间的数量不同，以及在给定种群中1%或更多的人群中出现的区域。CnP富含具有免疫功能的基因，现在有许多CnP与感染性和自身免疫性疾病相关。到目前为止，还没有对疟疾的CNP进行大规模研究，尽管编目的影响疟疾的大量突变仍然无法解释预期的变异。我们将使用合作开发的定制设计进行阵列比较基因组杂交(ACGH)，该设计密集探测人类基因组中数千个已知的CNP，使我们能够准确地量化它们的拷贝数，并确定它们是否与SMA相关。该项目旨在回答CNP是否占增加SMA风险的遗传变异的很大一部分的问题。为了确保我们研究人群中的CNP得到很好的代表，我们将首先进行标准阵列比较基因组杂交发现实验。我们将使用商业上可用的高密度平铺微阵列(基因组中的420万个探针)来分析72个个体，代表相同数量的病例和对照。这将确定以前代表性不足的人群中的CNP，例如在东非发现的那些在对其他人类群体的研究中可能没有发现的CNP。然后，我们将使用包括新发现的CNP在内的最新一组已知CNP来更新我们的定制微阵列。有了这个阵列，我们将在SMA病例(800例)和匹配对照(800例)中输入6000个CNP，这些CNP来自NIH和欢迎信托/MalariaGEN资助的基于人群的严重疟疾研究。我们将准确地确定每个个体的CNP拷贝数，并挖掘这些数据以寻找个体CNP与疾病状态之间的关联。这些CNP的有效性将通过对其他SMA病例和对照样本集进行重复基因定位测试来确认，这些发现的普适性将通过测试来自其他形式的严重疟疾(脑型疟疾和急性呼吸窘迫)患者的额外DNA样本来评估。通过这一新方法获得的独特见解有望填补我们对人类疟疾遗传易感性的理解方面的重大空白，这将有助于旨在从全球根除疟疾的疟疾疫苗设计战略。

DESCRIPTION (provided by applicant): This is a PI-initiated, collaborative, case/control project to systematically identify human copy number polymorphisms (CNPs) that are associated with severe malaria anemia (SMA) and other forms of severe malaria. CNPs represent regions in the genome typically >1kb that differ in the number between normal individuals within the population and that occur in 1% or more of a given population. CNPs are enriched for genes with immune function and there are now a number CNPs associations that have been shown for infectious and autoimmune diseases. To date there has been no large scale study of CNPs for malaria, despite the fact that the extensive number of mutations cataloged affecting malaria still cannot account for the expected variation. We will use a collaboratively developed custom design for array comparative genomic hybridization (aCGH) that densely probes thousands of known CNPs within the human genome allowing us to accurately quantify their copy number and determine if they are associated with SMA. This project is designed to answer the question of whether CNPs account for a significant portion of the genetic variation that increase risk for SMA. To ensure that CNPs in our study populations are well represented, we will first conduct standard array comparative genomic hybridization discovery experiments. We will analyze 72 individuals, representing an equal number of cases and controls, using a commercially-available, high-density tiling microarray (4.2 million probes across the genome). This will identify CNPs within previously under- represented populations such as those found in East Africa that may have not been detected in studies of other human populations. We will then update our custom microarray with the latest set of known CNPs including the newly discovered CNPs. With this array we will type six thousand CNPs in SMA cases (800) and matched controls (800) from NIH and Welcome Trust/MalariaGen funded population-based studies of severe malaria. We will accurately determine CNP copy numbers in each individual and mine this data for associations between individual CNPs and disease status. The validity of these CNPs will be confirmed by replicate locus-specific testing in additional SMA cases and controls sample sets and the generalizability of these findings will be evaluated by testing additional DNA samples from patients with other forms of severe malaria (cerebral malaria and acute respiratory distress). The unique insights gained by this novel approach are expected to fill significant gaps in our understanding of human genetic susceptibility to malaria that will benefit malaria vaccine design strategies aiming to eradicate malaria from the globe.