Multi-omics Analysis Reveals Underlying Host Responses in Pediatric Respiratory Syncytial Virus Pneumonia

Overview

Journal iScience

Publisher Cell Press

Date 2023 Mar 27

PMID 36968072

Authors

Xiaolan Huang

Fang Li

Yi Wang

Xinbei Jia

Nan Jia

Fei Xiao

Chunrong Sun

Jin Fu

Min Chen

Xiaodai Cui

Dong Qu

Laurence Don Wai Luu

Jun Tai

Jieqiong Li

Affiliations

Soon will be listed here.

Abstract

Respiratory syncytial virus (RSV) is 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, and 32 infectious disease controls (IDCs) were recruited. After analyses, six metabolites had potential diagnostic value. Using an independent cohort of 49 subjects, two biomarkers (neuromedin N and histidyl-proline diketopiperazine) were validated. Next, multi-omics analysis were applied to analyze the pathogenies of RSV pneumonia. Accumulation of collagen in the serum of RSVs indicated that RSV infection could lead to increased levels of soluble collage. Activation of the complement system and imbalance in lipid metabolism were also observed in RSV patients. The multi-omics analysis presented here revealed the signature protein and metabolite changes in serum caused by RSV infection.

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