Wang W, Wang F R, Guo Y, Zhang H B, Jiang F F
Department of Respiratory Medicine, Beijing Chaoyang Hospital of Capital Medical University, Beijing100020, China.
Zhonghua Jie He He Hu Xi Za Zhi. 2024 Dec 12;47(12):1121-1129. doi: 10.3760/cma.j.cn112147-20241015-00611.
To study the characteristics of the airway microbiome co-occurrence network in patients with type 2 and non-type 2 asthma. In a prospective study based on a cohort of asthma patients, respiratory induced sputum samples were collected from 55 asthma patients [25 males and 30 females, with a median age of 47.7 years (age range 34.3-63.0 years)] admitted to the Department of Respiratory and Critical Care, Beijing Chaoyang Hospital, Capital Medical University and 12 healthy controls from the Physical Examination Centre of Beijing Chaoyang Hospital, Capital Medical University, from May 2021 to May 2022. According to the level of exhaled breath nitric oxide (FeNO), the asthma patients were divided into 22 cases in the high FeNO group (FeNO≥40 ppb, , type 2 asthma group) and 33 cases in the low FeNO group (FeNO<40 ppb, i.e., non-type 2 asthma group). All induced sputum samples were subjected to second-generation macrogenomic sequencing and bioinformatic analyses of microbial community diversity, compositional characteristics, symbiotic network characteristics and metabolic function prediction. The Kruskal-Wallis rank sum test was used for between-group comparisons, and the linear discriminant analysis (LEfSe) method was used to compare the differences in flora composition between groups. The R language was used for microbial network analysis. In addition, PICRUSt was used to predict the metabolic-functional characteristics of the microbial communities. The microbial communities in the healthy control group had a lower proportion of and than asthma patients, 29% and 21%, respectively; 37% and 33% in the low FeNO group and 42% and 26% in the high FeNO group. The microbial network in the low FeNO group had 64 pairs of edges forming 16 communities, and about 75% of the nodes had eigenvector centrality values between 0 and 0.05, and 25% of the nodes had eigenvector centrality values between 0.10 and 0.45. There were four layers of κ-nucleosynthesis, and about 42% of the vertices were in the centre of the two layers. The microbial network of the high-FeNO group had 80 pairs of edges forming 18 clusters, and 81% of the nodes had eigenvector centrality values between 0 and 0.05, and 19% of the nodes had eigenvector centrality values between 0.10 and 0.35. The κ-nucleus decomposition had eight layers, and 21% of the vertices were located in the centre's two layers. The main functional differences between the low and high FeNO groups were shown in metabolic pathways (including sugar, lipid, amino acid, and energy metabolism), drug resistance, biofilm transport, signalling, intercellular communication, and cellular repair. Compared with non-type 2 asthmatics, type 2 asthmatics had a higher alpha diversity of respiratory microbiota, lower levels of microorganisms in the , and a more aggregated microbial network. There was a significant difference in the predicted metabolic function of the two endotypes of asthmatics.
研究2型和非2型哮喘患者气道微生物共生网络的特征。在一项基于哮喘患者队列的前瞻性研究中,于2021年5月至2022年5月期间,从首都医科大学附属北京朝阳医院呼吸与危重症医学科收治的55例哮喘患者[25例男性和30例女性,中位年龄47.7岁(年龄范围34.3 - 63.0岁)]以及首都医科大学附属北京朝阳医院体检中心的12名健康对照者中采集呼吸道诱导痰样本。根据呼出一氧化氮(FeNO)水平,将哮喘患者分为高FeNO组(FeNO≥40 ppb,即2型哮喘组)22例和低FeNO组(FeNO<40 ppb,即非2型哮喘组)33例。对所有诱导痰样本进行二代宏基因组测序,并对微生物群落多样性、组成特征、共生网络特征及代谢功能预测进行生物信息学分析。组间比较采用Kruskal - Wallis秩和检验,采用线性判别分析(LEfSe)方法比较组间菌群组成差异。使用R语言进行微生物网络分析。此外,使用PICRUSt预测微生物群落的代谢功能特征。健康对照组微生物群落中[具体微生物名称未给出]的比例分别低于哮喘患者,分别为29%和21%;低FeNO组为37%和33%,高FeNO组为42%和26%。低FeNO组的微生物网络有64对边,形成16个群落,约75%的节点特征向量中心性值在0至0.05之间,25%的节点特征向量中心性值在0.10至0.45之间。有四层κ - 核合成,约42%的顶点位于两层的中心。高FeNO组的微生物网络有80对边,形成18个簇,81%的节点特征向量中心性值在0至0.05之间,19%的节点特征向量中心性值在0.10至0.35之间。κ - 核分解有八层,21%的顶点位于中心的两层。低FeNO组和高FeNO组之间的主要功能差异体现在代谢途径(包括糖、脂质、氨基酸和能量代谢)、耐药性、生物膜转运、信号传导、细胞间通讯和细胞修复方面。与非2型哮喘患者相比,2型哮喘患者呼吸道微生物群的α多样性更高,[具体微生物名称未给出]中的微生物水平更低,且微生物网络更聚集。两种哮喘内型的预测代谢功能存在显著差异。