Dissecting the role of gut microbiota heterogeneity in the onset of chronic lung diseases.

IF 3.7 3区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Ya Lin, Xiaoxiao Zhang, Ziyi Zuo, Yijia Xiao
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引用次数: 0

Abstract

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.

剖析肠道微生物群异质性在慢性肺部疾病发病中的作用。
来自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(CLDs)有关。然而,GM和CLDs之间的因果关系尚未完全确定。基于孟德尔随机化(MR)的因果分析使用来自MiBioGen和FinnGen联盟的全基因组关联研究(GWAS)汇总统计数据进行。GM作为暴露,CLDs作为结果。采用反方差加权、MR-Egger和加权中位数方法来检验GM和CLDs之间的因果关系。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in-silico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。本研究揭示转基因与CLDs有因果关系。相反,反向MR分析提示COPD和IPF的存在可能对特异性GM的丰度产生因果关系。ISSMR进一步从协同或独立的角度为IPF和COPD中组织内和肠道微生物紊乱的相互作用提供了线索。总之,MR分析从宿主遗传角度揭示了转基因与CLDs之间的因果关系,而ISSMR从微生物遗传角度扩展了宿主-微生物调控模式,从而共同为肠道微生物介导的CLDs发展机制提供了新的见解。
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来源期刊
AMB Express
AMB Express BIOTECHNOLOGY & APPLIED MICROBIOLOGY-
CiteScore
7.20
自引率
2.70%
发文量
141
审稿时长
13 weeks
期刊介绍: AMB Express is a high quality journal that brings together research in the area of Applied and Industrial Microbiology with a particular interest in ''White Biotechnology'' and ''Red Biotechnology''. The emphasis is on processes employing microorganisms, eukaryotic cell cultures or enzymes for the biosynthesis, transformation and degradation of compounds. This includes fine and bulk chemicals, polymeric compounds and enzymes or other proteins. Downstream processes are also considered. Integrated processes combining biochemical and chemical processes are also published.
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