Multi-omic networks associated with COPD progression in TOPMed Cohorts

项目总结 慢性阻塞性肺病(COPD)是美国第四大死因。虽然 COPD主要发生在吸烟者中，目前尚不清楚为什么只有少数吸烟者(~20%-40%) 出现慢性气流受限或远端空间破坏(肺气肿)。区别在于 对烟草烟雾的易感性可以通过基因或环境的差异来解释，这些差异 导致激活或抑制在肿瘤的发生和发展过程中起重要作用的通路 慢性阻塞性肺疾病（慢阻肺）。高通量组学(全基因组测序、DNA甲基化、 RNA-Seq，蛋白质组学和代谢组学)应用于NHLBI队列现在允许全面的 对易感患者的分子图谱进行评估。这项提议将使用稀疏倍数 典型相关网络分析(SmCCNet)，以整合来自三个国家的现有组学数据 NHLBI队列：COPD基因、杰克逊心脏研究和SPIROMICS。三个独立的队列 将允许复制特定的分子网络，这些网络可用于靶向新疗法或更多 向个人提供准确的预后信息(即，精准医学)。这些队列中的前两个 有大量的非裔美国人受试者，他们在组学研究中的代表性不足。我们会 进行特定于种群的分析，这将使我们能够确定哪些分子特征和 途径可能是特定于非裔美国人的。

PROJECT SUMMARY Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the US. Although COPD occurs predominantly in smokers, it is unknown why only a minority of smokers (~20-40%) develop chronic airflow limitation or destruction of distal airspaces (emphysema). The difference susceptibility to tobacco smoke could be explained by differences in genetics or environment, which lead to activation or repression of pathways that are important in the pathogenesis and progression of COPD. Recent advances in high throughput omics (whole genome sequencing, DNA methylation, RNA-Seq, proteomics and metabolomics) applied to NHLBI cohorts now permits a comprehensive assessment of the molecular profiles of susceptible patients. This proposal will use sparse multiple canonical correlation network analysis (SmCCNet) to integrate these existing -omics data from three NHLBI cohorts: COPDGene, Jackson Heart Study, and SPIROMICS. The three independent cohorts will allow replication of specific molecular networks which can be used to target new therapies or more precise prognostic information to individuals (i.e., precision medicine). The first two of these cohorts have large numbers of African American subjects, who are underrepresented in omics studies. We will perform population specific analyses, which will allow us to determine which molecular signatures and pathways might be specific to African Americans.