Metagenomic next-generation sequencing for detecting Aspergillosis pneumonia in immunocompromised patients: a retrospective study.

ABSTRACT

Purpose: The identification of Aspergillus by metagenomic next-generation sequencing (mNGS) remains a challenging task due to the difficulty of nucleic acid extraction. The objective of this study was to determine whether mNGS could provide an accurate and efficient method for detecting invasive pulmonary aspergillosis (IPA) in immunocompromised patients (ICP). Methods: A total of 133 ICP admitted to the ICU between January 2020 and September 2022 were enrolled in the study, of which 46 were diagnosed with IPA and 87 were non-IPA cases. The bronchoalveolar lavage fluid (BALF) was analyzed for the presence of Aspergillosis and other co-pathogens using mNGS, and its diagnostic performance was compared to conventional microbial tests (CMTs) that included smear, cultures, serum and BALF galactomannan (GM) test. Clinical composite diagnosis was used as the reference standard. Results: mNGS had a sensitivity, specificity, and accuracy of 82.6%, 97.7%, and 92.5%, respectively, in diagnosing IPA. These findings were comparable to those of the combination of multiple CMTs. Interestingly, the sensitivity of mNGS was superior to that of any single CMT method, as demonstrated by comparisons with smears (8.7%, P < 0.001), culture (39.1%, P < 0.001), serum GM (23.9%, P < 0.001) and BALF GM (69.6%, P = 0.031). mNGS was capable of accurately distinguish strains of Aspergillus genus, with a consistency of 77.8% with culture. Furthermore, mNGS also identified A. fumigatus, A. flavus, A. terrestris, A. oryzae and Mucor spp. in culture-negative cases. The sequencing reads of Aspergillus by mNGS exhibited extensive variation, ranging from 11 to1702. A positive correlation was observed between the optical density index of BALF GM and unique reads by mNGS (r = 0.607, P = 0.001) in BALF-GM positive patients. Notably, mNGS was able to diagnose 35 out of 37 cases with mixed infection, with P. jirovecii and cytomegalovirus being the most common co-pathogens. Conclusions: mNGS presents a feasible and remarkably sensitive approach for detecting Aspergillus in ICP, thereby serving as a valuable adjunctive tool to CMT. Furthermore, mNGS's ability to accurately identify fungal species and co-pathogens can assist in guiding appropriate antimicrobial therapy.