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Background: Lower respiratory tract infection (LRTI) is a leading cause of morbidity and mortality among children admitted to paediatric intensive care units (PICUs). Accurate diagnosis is complicated by the breadth the broad spectrum of pathogens involved and the overlap of symptoms with non-infectious respiratory problems, often leading to diagnostic delays. This study aimed to identify early diagnostic biomarkers and characterise microbial-host interactions in paediatric LRTI. Methods: We re-analysed a metagenomic next-generation sequencing (mNGS) dataset from 261 PICU patients with acute respiratory failure, combining microbial and host transcriptomic profiles using differential expression, network, and machine-learning approaches. Candidate biomarkers were validated in an independent prospective cohort of 100 critically ill children (RASCALS), with non-bronchoscopic bronchoalveolar lavage (mini-BAL), blood cytokine profiling, and pathogen detection. Findings: Respiratory syncytial virus (RSV) and Haemophilus influenzae were the most enriched pathogens in LRTI cases. Host transcriptomics revealed activation of cytokine and chemokine signalling pathways. A seven-gene panel (IRF7, FFAR3, GZMB, FABP4, FN1, CXCL5, BCAR1) achieved high diagnostic accuracy, comparable to a published 14-gene model. In RASCALS, RSV detection combined with mini-BAL IL-8 or blood IL-4:TRAIL ratio improved diagnostic accuracy (71%) and correlated with ventilator-free days. Plasma C-reactive protein (CRP) and IL-6 further discriminated bacterial from non-bacterial infections (AUC 0.81 and 0.74, respectively). Interpretation: Integrating host and microbial markers provides a feasible route to early, accurate diagnosis of paediatric LRTI. The identified 7-gene panel and cytokine markers could be translated into PCR- or ELISA-based bedside assays to support rapid clinical decision-making and antimicrobial stewardship in PICU.