Application of metagenomic next-generation sequencing in the diagnosis of pulmonary invasive fungal disease

作者：Chengtan Wang, Zhiqing You, Juan Fu, Daiwen Chen, Di Bai, Hui Zhao, Pingping Song, Xiuqin Jia, Xiaoju Yuan, Wenbin Xu, Qigang Zhao, Feng Pang · 发表于：Frontiers in Cellular and Infection Microbiology · 年份：2022 · DOI：10.3389/fcimb.2022.949505 · 被引用次数：52 · 研究领域：Antifungal resistance and susceptibility、Fungal Infections and Studies、Actinomycetales infections and treatment

Background: Metagenomic next-generation sequencing (mNGS) is increasingly being used to detect pathogens directly from clinical specimens. However, the optimal application of mNGS and subsequent result interpretation can be challenging. In addition, studies reporting the use of mNGS for the diagnosis of invasive fungal infections (IFIs) are rare. Objective: We critically evaluated the performance of mNGS in the diagnosis of pulmonary IFIs, by conducting a multicenter retrospective analysis. The methodological strengths of mNGS were recognized, and diagnostic cutoffs were determined. Methods: A total of 310 patients with suspected pulmonary IFIs were included in this study. Conventional microbiological tests (CMTs) and mNGS were performed in parallel on the same set of samples. Receiver operating characteristic (ROC) curves were used to evaluate the performance of the logarithm of reads per kilobase per million mapped reads [lg(RPKM)], and read counts were used to predict true-positive pathogens. Result: The majority of the selected patients (86.5%) were immunocompromised. Twenty species of fungi were detected by mNGS, which was more than was achieved with standard culture methods. Peripheral blood lymphocyte and monocyte counts, as well as serum albumin levels, were significantly negatively correlated with fungal infection. In contrast, C-reactive protein and procalcitonin levels showed a significant positive correlation with fungal infection. ROC curves showed that mNGS [and...