Update publication information. Despite efforts made to reveal the underlying cause for differences in host responses and severity to Rrespiratory syncytial virus (RSV) infectionis an important pathogen causing pneumonia in children, few studies have used multi-omics data to investigate the pathogenies of RSV pneumonia. Here, metabolomics was first used to identify potential biomarkers for RSV diagnosis. In the training cohort, serum from 36 healthy controls (HCs), 45 RSV pneumonia children with respiratory syncytial virus pneumonia (RSVs), and 32 other infectious disease controls (IDCs) were recruited. After multivariate analyses, 283 metabolites were differently expressed in RSV compared to the HC and IDC groups. Among them, 6 metabolites were shown to have potential diagnostic values. Using an independent cohort of 49 subjects, 2 potential biomarkers (neuromedin N and histidylproline diketopiperazine) were validated. Next, a combination of multi-omics analysisproteomics and metabolomics were applied to analyze the pathogenies of protein-metabolite crosstalk in RSV pneumonia. Accumulation of collagen in the serum of RSVs indicated that RSV infection could lead to increased levels of soluble collagen, which may help to stimulate airway remodeling of the lungs. Additionally, activation of the complement system and the inflammatory responseimbalance in lipid metabolism were also observed in RSV patients. Finally, an imbalance in lipid metabolism, including glycerolipids, glycerophospholipids, sphingolipids, and prenol lipids, accompanied with apolipoprotein abnormalities were suggested to be involved in the pathogenesis of RSV pneumonia. The multi-omics analysis presented in our study here revealed the signature protein and metabolite changes in serum caused by RSV infection. This data provides essential diagnostic and therapeutic information in the fight against RSV infection in children.