Laboratory of Respiratory Diseases, Department of Chronic Diseases, Metabolism, and Ageing, KU Leuven, Leuven, Belgium.
Section of Pulmonary, Critical Care, and Sleep Medicine, Yale University, New Haven, Connecticut, USA.
Thorax. 2019 Feb;74(2):132-140. doi: 10.1136/thoraxjnl-2018-211929. Epub 2018 Oct 26.
Idiopathic pulmonary fibrosis (IPF) is a severe lung disease characterised by extensive pathological changes. The objective for this study was to identify the gene network and regulators underlying disease pathology in IPF and its association with lung function.
Lung Tissue Research Consortium dataset with 262 IPF and control subjects (GSE47460) was randomly divided into two non-overlapping groups for cross-validated differential gene expression analysis. Consensus weighted gene coexpression network analysis identified overlapping coexpressed gene modules between both IPF groups. Modules were correlated with lung function (diffusion capacity, DL; forced expiratory volume in 1 s, FEV; forced vital capacity, FVC) and enrichment analyses used to identify biological function and transcription factors. Module correlation with miRNA data (GSE72967) identified associated regulators. Clinical relevance in IPF was assessed in a peripheral blood gene expression dataset (GSE93606) to identify modules related to survival.
Correlation network analysis identified 16 modules in IPF. Upregulated modules were associated with cilia, DNA replication and repair, contractile fibres, B-cell and unfolded protein response, and extracellular matrix. Downregulated modules were associated with blood vessels, T-cell and interferon responses, leucocyte activation and degranulation, surfactant metabolism, and cellular metabolic and catabolic processes. Lung function correlated with nine modules (eight with DL, five with FVC). Intermodular network of transcription factors and miRNA showed clustering of fibrosis, immune response and contractile modules. The cilia-associated module was able to predict survival (p=0.0097) in an independent peripheral blood IPF cohort.
We identified a correlation gene expression network with associated regulators in IPF that provides novel insight into the pathological process of this disease.
特发性肺纤维化（IPF）是一种严重的肺部疾病，其特征是广泛的病理变化。本研究的目的是确定 IPF 疾病病理学的基因网络和调控因子及其与肺功能的关联。
使用包含 262 例 IPF 和对照受试者的肺组织研究联盟数据集（GSE47460），随机分为两组进行交叉验证差异基因表达分析。共识加权基因共表达网络分析确定了两组之间重叠的共表达基因模块。模块与肺功能（弥散能力，DL；1 秒用力呼气量，FEV；用力肺活量，FVC）相关，并进行富集分析以识别生物学功能和转录因子。模块与 miRNA 数据（GSE72967）的相关性鉴定了相关的调控因子。在一个外周血基因表达数据集（GSE93606）中评估了 IPF 的临床相关性，以确定与生存相关的模块。
相关性网络分析确定了 16 个 IPF 模块。上调的模块与纤毛、DNA 复制和修复、收缩纤维、B 细胞和未折叠蛋白反应以及细胞外基质有关。下调的模块与血管、T 细胞和干扰素反应、白细胞活化和脱颗粒、表面活性剂代谢以及细胞代谢和分解代谢过程有关。肺功能与九个模块相关（八个与 DL，五个与 FVC）。转录因子和 miRNA 的模块间网络显示纤维化、免疫反应和收缩模块聚类。纤毛相关模块能够预测独立的外周血 IPF 队列的生存（p=0.0097）。
我们确定了 IPF 中与相关调控因子相关的关联基因表达网络，为该疾病的病理过程提供了新的见解。
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