Human Genetic risk factors for Disseminated Coccidioidomycosis (DCM)

科学项目3：播散性球孢子菌病（DCM）的人类遗传风险因素 摘要 该项目将重点阐明使个体易患DCM的人类宿主遗传风险变异。为 在过去的80年里，流行病学研究表明，某些特定的种族和族裔群体， 更有可能进展为严重的播散性球孢子菌病，虽然许多这些观察结果 这些流行病背后的潜在机制和遗传发病机制， 观察结果尚未得到充分评价。这些类型的基因组研究存在几个主要障碍， 研究宿主遗传背景与环境（此处为感染）之间的关系：1）小- 大多数研究的样本量; 2）处理TB级基因组数据的挑战; 3）有限的测序数据， 非欧洲人群;以及4）识别相关功能读数以确认变体的影响 相关模型系统。在这个U19提案中，项目3汇集了600多个现有的外显子组和基因组 测序数据集，并建议收集和测序超过500个额外的病例和对照。这将是 迄今为止最大规模的球孢子菌病遗传研究。这个数据分析的关键是专家在这个建议 他们的专业知识使我们能够处理TB级的数据，并使用特定于祖先的方法进行分析。 我们将探讨两个主要的假设：构成祖先特异性方法的常见变体 DCM的种族和种族特异性差异或关键免疫信号通路中的罕见遗传变异 增加DCM风险。这两种假设不一定相互排斥，可以解释一些 已经观察到的疾病关联。除了识别DNA变异，我们还将 ATAC-seq，RNA测序研究，以在功能上验证非编码和剪接引起的变化， 编码基因变异该项目的一个关键方面是它能够迅速与项目1和2相结合， 核心C，以验证新的遗传变异及其对免疫途径的影响。它将允许我们直接 弥合鉴定的遗传变异和临床功能之间的差距。

Scientific Project 3: Human Genetic Risk Factors for Disseminated Coccidioidomycosis (DCM) ABSTRACT This project will focus on elucidating human host genetic risk variants that predispose individuals to DCM. For the past 80 years, epidemiological studies have demonstrated that certain specific racial and ethnic groups were more likely to progress towards severe disseminated Coccidioidomycosis, While many of these observations have held up over, the underlying mechanistic and genetic pathogenesis underlying these epidemiological observation have not been fully evaluated. There have been several major barriers to these types of genomic studies where the relationship between host-genetic background and environment (here infection): 1) small- sample sizes for most studies; 2) challenge of handling terabytes of genomic data; 3) limited sequencing data for non-european populations;and 4) identifying relevant functional readouts to confirm the effect of variants in relevant model systems. In this U19 proposal, project 3 brings together over 600 existing exome and genome sequencing datasets and proposes to collect and sequence over 500 additional cases and controls. This will be the largest genetic study of coccidioidomycosis to date. Key to this data analysis is the experts in this proposal whose expertise enables us to handle Terabytes of data and to analyze it using ancestry-specific approaches. We will explore two major hypotheses: that common variants that make up ancestry-specific approaches underly race and ethnicity specific differences in DCM or that rare genetic variants in key immune signaling pathways increase risk of DCM. Both hypotheses are not necessarily mutually exclusive and may explain some of the disease associations that have been observed. In addition to identifying the DNA variants, we will perform ATAC-seq, RNA-sequencing studies to functionally validate non-coding and splicing changes caused by non- coding genetic variants. A key aspect of this project is its ability to rapidly integrate with projects 1 and 2 and Core C in order to validate novel genetic variants and their effects on immune pathways. It will allow us to directly bridge the gap between identified genetic variants and clinical function.