Second Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Genes Immun. 2024 Oct;25(5):389-396. doi: 10.1038/s41435-024-00292-5. Epub 2024 Aug 22.
Oxidative stress (OS) is crucial in idiopathic pulmonary fibrosis (IPF) pathogenesis, with its genes potentially acting as both causes and consequences of the disease. We identified OS-related genes from GeneCards and performed a meta-analysis on pulmonary transcriptome datasets to discover differentially expressed genes (DEGs) related to OS in IPF. We integrated this data with the largest available IPF GWAS summaries, expression quantitative trait loci (eQTLs), and DNA methylation QTLs (mQTLs) from blood. This approach aimed to identify blood OS genes and regulatory elements linked to IPF risk, incorporating the latest pulmonary eQTLs and bronchoalveolar lavage fluid microbial QTLs (bmQTLs) for a comprehensive view of gene-lung microbiota interactions through SMR and colocalization analyses. Sensitivity analyses were conducted using two additional mendelian randomization (MR) methods. Meta-analysis revealed 1090 differentially expressed OS genes between IPF patients and controls. Integration with IPF GWAS, eQTL, and mQTL data identified key genes and regulatory elements involved in IPF pathogenesis, highlighting the role of specific genes such as KCNMA1 and SLC22A5 in modulating IPF risk through epigenetic mechanisms. Colocalization analysis further identified potential interactions between gene expression and lung microbiota. Our findings elucidate the complex interplay between OS genes and IPF, suggesting potential therapeutic targets and highlighting the importance of considering epigenetic and microbial interactions in the disease's etiology and progression.
氧化应激（OS）在特发性肺纤维化（IPF）发病机制中至关重要，其基因可能既是疾病的原因又是疾病的结果。我们从 GeneCards 中识别 OS 相关基因，并对肺转录组数据集进行荟萃分析，以发现与 IPF 中 OS 相关的差异表达基因（DEGs）。我们将此数据与最大的可用 IPF GWAS 摘要、来自血液的表达数量性状基因座（eQTLs）和 DNA 甲基化 QTLs（mQTLs）进行整合。这种方法旨在识别与 IPF 风险相关的血液 OS 基因和调节元件，通过 SMR 和 colocalization 分析纳入最新的肺 eQTLs 和支气管肺泡灌洗液微生物 QTLs（bmQTLs），以全面了解基因-肺部微生物群相互作用。使用另外两种孟德尔随机化（MR）方法进行敏感性分析。荟萃分析显示，IPF 患者和对照之间有 1090 个差异表达的 OS 基因。与 IPF GWAS、eQTL 和 mQTL 数据的整合确定了参与 IPF 发病机制的关键基因和调节元件，突出了特定基因（如 KCNMA1 和 SLC22A5）通过表观遗传机制调节 IPF 风险的作用。colocalization 分析进一步鉴定了基因表达和肺部微生物群之间的潜在相互作用。我们的研究结果阐明了 OS 基因与 IPF 之间的复杂相互作用，表明了潜在的治疗靶点，并强调了在疾病的病因和进展中考虑表观遗传和微生物相互作用的重要性。
