Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Room 451, Boston, MA, 02115, USA.
Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Respir Res. 2018 Mar 22;19(1):46. doi: 10.1186/s12931-018-0744-9.
Genome-wide association studies have identified several genetic risk loci for severe chronic obstructive pulmonary disease (COPD) and emphysema. However, these studies do not fully explain disease heritability and in most cases, fail to implicate specific genes. Integrative methods that combine gene expression data with GWAS can provide more power in discovering disease-associated genes and give mechanistic insight into regulated genes.
We applied a recently described method that imputes gene expression using reference transcriptome data to genome-wide association studies for two phenotypes (severe COPD and quantitative emphysema) and blood and lung tissue gene expression datasets. We further tested the potential causality of individual genes using multi-variant colocalization.
We identified seven genes significantly associated with severe COPD, and five genes significantly associated with quantitative emphysema in whole blood or lung. We validated results in independent transcriptome databases and confirmed colocalization signals for PSMA4, EGLN2, WNT3, DCBLD1, and LILRA3. Three of these genes were not located within previously reported GWAS loci for either phenotype. We also identified genetically driven pathways, including those related to immune regulation.
An integrative analysis of GWAS and gene expression identified novel associations with severe COPD and quantitative emphysema, and also suggested disease-associated genes in known COPD susceptibility loci.
NCT00608764 , Registry: ClinicalTrials.gov, Date of Enrollment of First Participant: November 2007, Date Registered: January 28, 2008 (retrospectively registered); NCT00292552 , Registry: ClinicalTrials.gov, Date of Enrollment of First Participant: December 2005, Date Registered: February 14, 2006 (retrospectively registered).
全基因组关联研究已经确定了几个严重慢性阻塞性肺疾病(COPD)和肺气肿的遗传风险位点。然而,这些研究并不能完全解释疾病的遗传性,而且在大多数情况下,不能确定具体的基因。将基因表达数据与 GWAS 相结合的综合方法可以提供发现疾病相关基因的更大能力,并深入了解调节基因的机制。
我们应用了一种最近描述的方法,该方法使用参考转录组数据来对两个表型(严重 COPD 和定量肺气肿)以及血液和肺组织基因表达数据集进行全基因组关联研究。我们进一步使用多变量共定位来测试单个基因的潜在因果关系。
我们确定了七个与严重 COPD 显著相关的基因,以及五个与全血或肺组织中定量肺气肿显著相关的基因。我们在独立的转录组数据库中验证了结果,并确认了 PSMA4、EGLN2、WNT3、DCBLD1 和 LILRA3 的共定位信号。其中三个基因不在先前报道的这两种表型的 GWAS 位点中。我们还确定了与免疫调节相关的遗传驱动途径。
GWAS 和基因表达的综合分析确定了与严重 COPD 和定量肺气肿的新关联,并提示了已知 COPD 易感性位点中的疾病相关基因。
NCT00608764,注册机构:ClinicalTrials.gov,首例参与者入组日期:2007 年 11 月,注册日期:2008 年 1 月 28 日(回顾性注册);NCT00292552,注册机构:ClinicalTrials.gov,首例参与者入组日期:2005 年 12 月,注册日期:2006 年 2 月 14 日(回顾性注册)。