Zou Xiaohui, Yan Mengwei, Wang Yeming, Ni Yawen, Zhao Jiankang, Lu Binghuai, Liu Bo, Cao Bin
National Center for Respiratory Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, National Clinical Research Center for Respiratory Diseases, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, 100029, China.
Department of Clinical Microbiology, Pulmonary and Critical Care Medicine, Zibo City Key Laboratory of Respiratory Infection and Clinical Microbiology, Zibo City Engineering Technology Research Center of Etiology Molecular Diagnosis, Zibo Municipal Hospital, Zibo, 255400, China.
Adv Sci (Weinh). 2025 Feb;12(6):e2405087. doi: 10.1002/advs.202405087. Epub 2024 Dec 18.
Lower respiratory tract infections (LRTIs) diagnosis is challenging because noninfectious diseases mimic its clinical features. The altered host response and respiratory microbiome following LRTIs have the potential to differentiate LRTIs from noninfectious respiratory diseases (non-LRTIs). Patients suspected of having LRTIs are retrospectively enrolled and a clinical metatranscriptome test is performed on bronchoalveolar lavage fluid (BALF). Transcriptomic and metagenomic analysis profiled the host response and respiratory microbiome in patients with confirmed LRTI (n = 126) or non-LRTIs (n = 75). Patients with evidenced LRTIs exhibited enhanced pathways on chemokine and cytokine response, neutrophile recruitment and activation, along with specific gene modules linked to LRTIs status and key blood markers. Moreover, LRTIs patients exhibited reduced diversity and evenness in the lower respiratory microbiome, likely driven by an increased abundance of bacterial pathogens. Host marker genes are selected, and classifiers are developed to distinguish patients with LRTIs, non-LRTIs, and indeterminate status, achieving an area under the receiver operating characteristic curve of 0.80 to 0.86 and validated in a subsequently enrolled cohort. Incorporating respiratory microbiome features further enhanced the classifier's performance. In summary, a single metatranscriptome test of BALF proved detailed profiles of host response and respiratory microbiome, enabling accurate LRTIs diagnosis.
下呼吸道感染(LRTIs)的诊断具有挑战性,因为非感染性疾病会模仿其临床特征。LRTIs后宿主反应和呼吸道微生物群的改变有可能将LRTIs与非感染性呼吸道疾病(非LRTIs)区分开来。对疑似患有LRTIs的患者进行回顾性纳入,并对支气管肺泡灌洗液(BALF)进行临床宏转录组测试。转录组学和宏基因组学分析描绘了确诊为LRTI(n = 126)或非LRTIs(n = 75)患者的宿主反应和呼吸道微生物群。有证据表明患有LRTIs的患者在趋化因子和细胞因子反应、中性粒细胞募集和激活方面表现出增强的途径,以及与LRTIs状态和关键血液标志物相关的特定基因模块。此外,LRTIs患者下呼吸道微生物群的多样性和均匀度降低,这可能是由细菌病原体丰度增加所致。选择宿主标记基因,并开发分类器以区分患有LRTIs、非LRTIs和不确定状态的患者,在受试者工作特征曲线下面积达到0.80至0.86,并在随后纳入的队列中得到验证。纳入呼吸道微生物群特征进一步提高了分类器的性能。总之,对BALF进行单次宏转录组测试可提供宿主反应和呼吸道微生物群的详细概况,从而实现准确的LRTIs诊断。