Copy Number Variation Identification and Association Study on Alzheimer's Disease Whole Genome Sequencing Data

总结 阿尔茨海默病（AD）是一种破坏性的神经退行性疾病， 痴呆症的原因大约有600万美国人患有AD， 这使得AD成为世界人口最紧迫的公共卫生问题之一 继续老化。目前，没有已知的有效预防或治愈存在，并且当前AD 药物只能缓解症状或减缓衰退速度。AD药物试验的前景是 阴郁。一个可能的原因是，AD是一种异质性疾病，但试验设计 把它当作一种单一的疾病来对待。虽然生活方式和环境风险因素明显影响 AD，遗传影响的首要地位表明，应根据遗传基础进行分类， 在制定有效的干预措施方面优先考虑。遗传学可以提供风险预测的见解， 疾病机制和新的治疗靶点。AD的遗传率估计范围为49- 79%， 但迄今为止鉴定的常规单核苷酸变异（SNV）仅占 AD遗传性多项研究强调了拷贝数变异（CNV）在AD中的作用。 我们假设，在全谱（即， 大小有小有大，频率有常见有罕见，基因组有编码有非编码 全基因组测序（WGS）的区域）可以进一步增强AD的知识 病因和风险。利用阿尔茨海默病测序项目的丰富资源 （ADSP），我们建议关注由AD组成的大型多种族WGS样本（n> 17，000） 病例和正常健康老年对照，以及（1）检测来自WGS的CNV并进行基因分型， ADSP病例-对照样本;（2）进行关联分析，以确定CNV的基因组区域 导致AD;以及（3）进行跨种族关联研究，以找到种族共享或 种族独特的AD相关CNV。成功完成我们的目标将提供（i）第一个 使用WGS数据进行AD遗传学的大规模CNV调查;（ii）新的CNV调用方法， 基于当前最佳实践的WGS;（iii）解决问题的新CNV关联策略 断点不对齐和增强联想的力量;（四）多民族的特点， AD的共享和独特的CNV风险因素;和（v）优化的计算管道， 源代码和发布的标准化图像（例如，Docker镜像和Bioconductor包） 这是很容易部署在其他大规模的WGS协会项目。

SUMMARY Alzheimer's disorder (AD) is a devastating neurodegenerative disease and the most common cause of dementia. There are approximately six million Americans with AD and 29.8 million worldwide, making AD one of the most pressing public health issues as the world's population continues to age. Presently, there is no known effective prevention or cure exists, and current AD medications only alleviate symptoms or slow decline rates. The landscape of AD drug trials is gloomy. One possible reason is that AD is a heterogeneous disorder but trials are designed treating it as a monolithic disease. Although lifestyle and environmental risk factors clearly affect AD, the primacy of genetic influences suggests that categorization by genetic basis should be prioritized in developing effective interventions. Genetics can offer insights on risk prediction, disease mechanism, and new therapeutic targets. Heritability of AD estimates range from 49-79%, but the conventional single nucleotide variants (SNVs) identified to date only account for <50% of AD heritability. Multiple studies have highlighted the roles of copy number variants (CNVs) in AD. We hypothesize that a systematic investigation of genome-wide CNVs at the full spectrum (i.e. small and large in size, common and rare in frequency, and coding and no-coding in genomic regions) from whole-genome sequencing (WGS) can further enhance the knowledge of AD etiology and risk. Leveraging the rich resources from the Alzheimer's Disease Sequencing Project (ADSP), we propose to focus on a large multi-ethnic WGS sample (n>17,000) composed of AD cases and normal healthy elderly controls, and to (1) detect and genotype CNVs from WGS for ADSP case-control samples; (2) perform association analysis to identify genome regions of CNVs contributing to AD; and (3) conduct cross-ethnic association studies to find ethnic-shared or ethnic-unique AD-associated CNVs. Successful completion of our aims will provide (i) the first large-scale CNV investigation of AD genetics using WGS data; (ii) new CNV calling method for WGS based on the current best practices; (iii) new CNV association strategies to address issue of breakpoint non-alignment and enhance association power; (iv) multi-ethnic characterization of shared and unique CNV risk factors for AD; and (v) optimized computational pipelines with open- source code and released standardized images (e.g., Docker images and Bioconductor packages) that are easily deployable in other large-scale WGS association projects.