Zhang Xiao-Xian, He Zhen-Feng, He Jia-Hui, Chen Zhao-Ming, Pan Cui-Xia, Lin Zhen-Hong, Cen Lai-Jian, Li Hui-Min, Huang Yan, Shi Ming-Xin, Guan Wei-Jie
Department of Allergy and Clinical Immunology, Department of Respiratory and Critical Care Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China.
Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China.
Arch Bronconeumol. 2025 Jul;61(7):417-426. doi: 10.1016/j.arbres.2025.01.002. Epub 2025 Jan 6.
To investigate the microbiota and metabolome of patients with ABO compared with bronchiectasis and asthma, and determine the relevance with clinical characteristics, inflammatory endotype and exacerbation risks.
In this prospective cohort study, patients underwent comprehensive assessments, including sputum differential cell count, and sputum collection at baseline. Sputum microbiota was profiled via 16S rRNA gene sequencing and metabolome via liquid chromatography/mass spectrometry. Shannon-Wiener Diversity Index (SWDI) was used to reflect dysbiosis. Patients were followed-up to record exacerbations. ABO patients were stratified by the SWDI and sputum eosinophilia to determine the exacerbation risks.
Two hundred forty-seven patients were recruited, including 99 ABO (median age: 53.2 years, 65.7% female), 61 asthma (median age: 39.5 years, 50.8% female) and 87 bronchiectasis patients (median age: 52.3 years, 55.2% female). Both microbiota compositions and metabolites differed among asthma, ABO and bronchiectasis, and between eosinophilic and non-eosinophilic ABO at steady-state. Baseline SWDI of microbiota was highest in asthma, followed by ABO. Both Pseudomonadaceae and Rothia most effectively discriminated ABO from asthma and bronchiectasis. Pseudomonas exhibited a more pronounced negative correlation with other taxa in nonEos-ABO. ABO patients with low SWDI with sputum eosinophilia, or those with high SWDI without sputum eosinophilia, had a shorter time to the first exacerbation. Metabolomic compositions in Eos-ABO separated from nonEos-ABO. The relative abundance of Enterobacteriaceae correlated negatively with 15-hydroxylated eicosatetraenoic acid, whose concentrations were higher in Eos-ABO.
Integrating microbiota and metabolome profiles, together with eosinophilic inflammatory endotyping, can inform exacerbation risk and personalized management of ABO.
与支气管扩张症和哮喘患者相比,研究ABO患者的微生物群和代谢组,并确定其与临床特征、炎症内型和急性加重风险的相关性。
在这项前瞻性队列研究中,患者接受了全面评估,包括痰液细胞分类计数,并在基线时采集痰液。通过16S rRNA基因测序分析痰液微生物群,通过液相色谱/质谱分析代谢组。采用香农-维纳多样性指数(SWDI)反映生态失调。对患者进行随访以记录急性加重情况。ABO患者根据SWDI和痰液嗜酸性粒细胞增多情况进行分层,以确定急性加重风险。
共招募了247例患者,包括99例ABO患者(中位年龄:53.2岁,65.7%为女性)、61例哮喘患者(中位年龄:39.5岁,50.8%为女性)和87例支气管扩张症患者(中位年龄:52.3岁,55.2%为女性)。哮喘、ABO和支气管扩张症之间,以及稳态时嗜酸性粒细胞性和非嗜酸性粒细胞性ABO之间的微生物群组成和代谢物均存在差异。微生物群的基线SWDI在哮喘中最高,其次是ABO。假单胞菌科和罗氏菌属最能有效区分ABO与哮喘和支气管扩张症。在非嗜酸性粒细胞性ABO中,假单胞菌与其他分类群的负相关性更为明显。SWDI低且有痰液嗜酸性粒细胞增多的ABO患者,或SWDI高但无痰液嗜酸性粒细胞增多的患者,首次急性加重的时间较短。嗜酸性粒细胞性ABO的代谢组组成与非嗜酸性粒细胞性ABO不同。肠杆菌科的相对丰度与15-羟基二十碳四烯酸呈负相关,其浓度在嗜酸性粒细胞性ABO中较高。
整合微生物群和代谢组谱,以及嗜酸性粒细胞性炎症内型,可为ABO的急性加重风险和个性化管理提供依据。