Lin Ya, Zhang Xiaoxiao, Zuo Ziyi, Xiao Yijia
Division of Pulmonary Medicine, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Department of Pulmonary and Critical Care Medicine, University of South China Affiliated Changsha Central Hospital, Changsha, 410004, Hunan, China.
AMB Express. 2025 Aug 18;15(1):119. doi: 10.1186/s13568-025-01930-5.
Evidence from observational studies and clinical trials has reported that gut microbiota (GM) was associated with chronic lung diseases (CLDs). However, the causal relationships between GM and CLDs have yet to be fully ascertained. The Mendelian randomization (MR) based causal analysis was performed using the genome-wide association study (GWAS) summary statistics from the MiBioGen and FinnGen consortium. GM served as exposure, and CLDs were taken for outcomes. Inverse variance weighted, MR-Egger, and weighted median methods were utilized to examine the causal association between GM and CLDs. The sensitivity analyses were then conducted to validate the robustness of the results. Further, the reverse MR analysis was performed to evaluate the possibility of reverse causation. Finally, the in-silico in-situ microbiota resequencing (ISSMR) of high-throughput sequencing data was utilized as a supplement to dissect the role of microbiota spatial distribution disturbance on the onset of idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD). This study revealed that GM had causal associations with CLDs. Conversely, reverse MR analysis suggested that the presence of COPD and IPF may causally influence the abundance of specific GM. And ISSMR further provided clues to the interaction of intra-tissue as well as gut microbe disturbance in IPF and COPD from synergistic or independent perspectives. In short, the MR analysis revealed a causal relationship between GM and CLDs from a host genetic perspective, and ISSMR extended the host-microbe regulatory modality from a microbe genetic perspective, thus together providing novel insights into the gut microbiota-mediated development mechanism of CLDs.
观察性研究和临床试验的证据表明，肠道微生物群（GM）与慢性肺部疾病（CLD）有关。然而，GM与CLD之间的因果关系尚未完全确定。使用来自MiBioGen和FinnGen联盟的全基因组关联研究（GWAS）汇总统计数据进行基于孟德尔随机化（MR）的因果分析。以GM为暴露因素，以CLD为结局。采用逆方差加权法、MR-Egger法和加权中位数法检验GM与CLD之间的因果关联。然后进行敏感性分析以验证结果的稳健性。此外，进行反向MR分析以评估反向因果关系的可能性。最后，利用高通量测序数据的计算机原位微生物群重测序（ISSMR）作为补充，剖析微生物群空间分布紊乱在特发性肺纤维化（IPF）和慢性阻塞性肺疾病（COPD）发病中的作用。本研究表明，GM与CLD存在因果关联。相反，反向MR分析表明，COPD和IPF的存在可能因果性地影响特定GM的丰度。ISSMR进一步从协同或独立的角度为IPF和COPD中组织内相互作用以及肠道微生物紊乱提供了线索。简而言之，MR分析从宿主基因角度揭示了GM与CLD之间的因果关系，ISSMR从微生物基因角度扩展了宿主-微生物调节模式，从而共同为CLD的肠道微生物群介导的发育机制提供了新的见解。
