Integrated host/microbe metagenomics enables accurate lower respiratory tract infection diagnosis in critically ill childrenEran Mick, Alexandra Tsitsiklis, Jack Kamm, Katrina L Kalantar, Saharai Caldera, Amy Lyden, Michelle Tan 1, Angela M Detweiler 1, Norma Neff 1, Christina M Osborne 5, Kayla M Williamson 6, Victoria Soesanto 6, Matthew Leroue 5, Aline B Maddux 5, Eric Af Simões 5, Todd C Carpenter 5, Brandie D Wagner 5 6, Joseph L DeRisi 1 7, Lilliam Ambroggio 5, Peter M Mourani 5 8, Charles R Langelier
JCI, 2023Abstract: Lower respiratory tract infection (LRTI) is a leading cause of death in children worldwide. LRTI diagnosis is challenging because noninfectious respiratory illnesses appear clinically similar and because existing microbiologic tests are often falsely negative or detect incidentally carried microbes, resulting in antimicrobial overuse and adverse outcomes. Lower airway metagenomics has the potential to detect host and microbial signatures of LRTI. Whether it can be applied at scale and in a pediatric population to enable improved diagnosis and treatment remains unclear. We used tracheal aspirate RNA-Seq to profile host gene expression and respiratory microbiota in 261 children with acute respiratory failure. We developed a gene expression classifier for LRTI by training on patients with an established diagnosis of LRTI (n equals 117) or of noninfectious respiratory failure (n equals 50). We then developed a classifier that integrates the host LRTI probability, abundance of respiratory viruses, and dominance in the lung microbiome of bacteria/fungi considered pathogenic by a rules-based algorithm.
