A multicenter prospective study of comprehensive metagenomic and transcriptomic signatures for predicting outcomes of patients with severe community-acquired pneumonia

一项关于综合宏基因组和转录组特征预测严重社区获得性肺炎患者预后的多中心前瞻性研究

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作者:Jingya Zhao, Xiangyan He, Jiumeng Min, Rosary Sin Yu Yao, Yu Chen, Zhonglin Chen, Yi Huang, Zhongyi Zhu, Yanping Gong, Yusang Xie, Yuping Li, Weiwei Luo, Dongwei Shi, Jinfu Xu, Ao Shen, Qiuyue Wang, Ruixue Sun, Bei He, Yang Lin, Ning Shen, Bin Cao, Lingling Yang, Danyang She, Yi Shi, Jiali Zhou, Xin

Background

Severe community-acquired pneumonia (SCAP)

Methods

In this study, we applied a combined metagenomic and transcriptomic screening approach to clinical specimens gathered from 275 SCAP patients of a multicentre, prospective study. Findings: We found that 30-day mortality might be independent of pathogen category or microbial diversity, while significant difference in host gene expression pattern presented between 30-day mortality group and the survival group. Twelve outcome-related clinical characteristics were identified in our study. The underlying host response was evaluated and enrichment of genes related to cell activation, immune modulation, inflammatory and metabolism were identified. Notably, omics data, clinical features and parameters were integrated to develop a model with six signatures for predicting 30-day mortality, showing an AUC of 0.953 (95% CI: 0.92-0.98). Interpretation: In summary, our study linked clinical characteristics and underlying multi-omics bio-signatures to the differential outcomes of patients with SCAP. The establishment of a comprehensive predictive model will be helpful for future improvement of treatment strategies and prognosis with SCAP. Funding: National Natural Science Foundation of China (No. 82161138018), Shanghai Municipal Key Clinical Specialty (shslczdzk02202), Shanghai Top-Priority Clinical Key Disciplines Construction Project (2017ZZ02014), Shanghai Key Laboratory of Emergency Prevention, Diagnosis and Treatment of Respiratory Infectious Diseases (20dz2261100).

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