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Multi-omics analysis reveals underlying host responses in pediatric respiratory syncytial virus pneumonia

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
Source :
iScience, Vol 26, Iss 4, Pp 106329- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Summary: 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.

Details

Language :
English
ISSN :
25890042
Volume :
26
Issue :
4
Database :
Directory of Open Access Journals
Journal :
iScience
Publication Type :
Academic Journal
Accession number :
edsdoj.fffa886bf6414a8a82294893da3e7bc8
Document Type :
article
Full Text :
https://doi.org/10.1016/j.isci.2023.106329