ORIGINAL RESEARCH article
Front. Microbiol.
Sec. Infectious Agents and Disease
Volume 16 - 2025 | doi: 10.3389/fmicb.2025.1595521
This article is part of the Research TopicMechanisms and Innovations in Combating Intracellular InfectionsView all articles
Proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe Mycoplasma pneumoniae pneumonia
Provisionally accepted
- 1Hubei Maternal and Child Health Hospital, Wuhan, China
- 2SpecAlly Life Technology Co. Ltd, Wuhan, Hebei Province, China
- 3School of Laboratory Medicine, Hubei University of Chinese Medicine, Wuhan, Hubei Province, China
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Objectives: Mycoplasma pneumoniae pneumonia (MPP), particularly macrolide-resistant MPP has undergone a prolonged nonseasonal epidemic in China since the lifting of non-pharmaceutical interventions in 2023. This study aimed to identify novel biomarkers to predict disease severity in children with MPP and to develop a predictive model.Methods: In this study, bronchoalveolar lavage fluid (BALF) samples were collected from 30 children, including 15 with mild and 15 with severe MPP, for quantitative proteomic analysis. The two groups were compared and differentially expressed proteins (DEPs) were identified. Core proteins associated with MPP severity were identified using least absolute shrinkage and selection operator (LASSO) analysis. Logistic regression analysis was used to develop a predictive model.Results: A total of 154 DEPs were identified, of which 57 were upregulated in the severe group. Upregulated signaling was found to be mainly involved in the immune response and inflammatory signaling. Thirteen proteins were selected as core proteins associated with MPP severity. CD209, CHM, PBRM1, and SCAMP1 were the most influential predictors and a predictive model using these four proteins predicted MPP severity.Conclusions: A predictive model was developed to assess the potential of using the identified biomarkers to predict disease severity. This model provides insights into the pathogenesis of M. pneumoniae infection.
Keywords: Mycoplasma pneumoniae pneumonia, Quantitative Proteomics, Differentially expressed proteins, Bronchoalveolar Lavage Fluid, predictive model
Received: 18 Mar 2025; Accepted: 25 Apr 2025.
Copyright: © 2025 Liang, Zhu, Wu, Zhang, He, Wang, Wu and Xia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Chunchen Wu, Hubei Maternal and Child Health Hospital, Wuhan, China
Jianbo Xia, Hubei Maternal and Child Health Hospital, Wuhan, China
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