Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
EBioMedicine. 2019 May;43:576-586. doi: 10.1016/j.ebiom.2019.03.072. Epub 2019 Mar 29.
The causes of poor respiratory function and COPD are incompletely understood, but it is clear that genes and the environment play a role. As DNA methylation is under both genetic and environmental control, we hypothesised that investigation of differential methylation associated with these phenotypes would permit mechanistic insights, and improve prediction of COPD. We investigated genome-wide differential DNA methylation patterns using the recently released 850 K Illumina EPIC array. This is the largest single population, whole-genome epigenetic study to date.
Epigenome-wide association studies (EWASs) of respiratory function and COPD were performed in peripheral blood samples from the Generation Scotland: Scottish Family Health Study (GS:SFHS) cohort (n = 3781; 274 COPD cases and 2919 controls). In independent COPD incidence data (n = 149), significantly differentially methylated sites (DMSs; p < 3.6 × 10) were evaluated for their added predictive power when added to a model including clinical variables, age, sex, height and smoking history using receiver operating characteristic analysis. The Lothian Birth Cohort 1936 (LBC1936) was used to replicate association (n = 895) and prediction (n = 178) results.
We identified 28 respiratory function and/or COPD associated DMSs, which mapped to genes involved in alternative splicing, JAK-STAT signalling, and axon guidance. In prediction analyses, we observed significant improvement in discrimination between COPD cases and controls (p < .05) in independent GS:SFHS (p = .016) and LBC1936 (p = .010) datasets by adding DMSs to a clinical model.
Identification of novel DMSs has provided insight into the molecular mechanisms regulating respiratory function and aided prediction of COPD risk. Further studies are needed to assess the causality and clinical utility of identified associations. FUND: Wellcome Trust Strategic Award 10436/Z/14/Z.
呼吸功能不佳和 COPD 的病因尚不完全清楚,但显然基因和环境都起了作用。由于 DNA 甲基化受遗传和环境的双重控制,我们假设对与这些表型相关的差异甲基化进行研究,将有助于深入了解其机制,并提高对 COPD 的预测能力。我们使用最近发布的 850K Illumina EPIC 阵列,研究了全基因组差异 DNA 甲基化模式。这是迄今为止最大的单一人群、全基因组表观遗传学研究。
在苏格兰家庭健康研究(GS:SFHS)队列的外周血样本中,对呼吸功能和 COPD 进行了全基因组关联研究(EWASs)(n=3781;274 例 COPD 病例和 2919 例对照)。在独立的 COPD 发病数据(n=149)中,使用受试者工作特征分析(ROC 分析)评估显著差异甲基化位点(DMS;p<3.6×10)在添加到包括临床变量、年龄、性别、身高和吸烟史的模型中的预测能力。洛锡安出生队列 1936 年(LBC1936)用于复制关联(n=895)和预测(n=178)结果。
我们确定了 28 个与呼吸功能和/或 COPD 相关的 DMS,这些 DMS 映射到参与可变剪接、JAK-STAT 信号转导和轴突导向的基因。在预测分析中,我们观察到在独立的 GS:SFHS(p=0.016)和 LBC1936(p=0.010)数据集,通过将 DMS 添加到临床模型中,显著改善了 COPD 病例和对照之间的区分(p<0.05)。
鉴定新的 DMS 为调节呼吸功能的分子机制提供了深入的了解,并有助于预测 COPD 的风险。需要进一步的研究来评估鉴定关联的因果关系和临床实用性。
惠康基金会战略奖 10436/Z/14/Z。