Proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe Mycoplasma pneumoniae pneumonia

ObjectivesMycoplasma 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...

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Main Authors: Ao Liang, Yaqi Zhu, Xiaoxue Wu, Qingyan Zhang, Yafang He, Anbang Wang, Chunchen Wu, Jianbo Xia
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Microbiology
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Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2025.1595521/full
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author Ao Liang
Yaqi Zhu
Xiaoxue Wu
Qingyan Zhang
Yafang He
Anbang Wang
Anbang Wang
Chunchen Wu
Chunchen Wu
Jianbo Xia
Jianbo Xia
Jianbo Xia
author_facet Ao Liang
Yaqi Zhu
Xiaoxue Wu
Qingyan Zhang
Yafang He
Anbang Wang
Anbang Wang
Chunchen Wu
Chunchen Wu
Jianbo Xia
Jianbo Xia
Jianbo Xia
author_sort Ao Liang
collection DOAJ
description ObjectivesMycoplasma 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.MethodsIn 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.ResultsA 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.ConclusionA 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.ImportanceDifferences in the proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe Mycoplasma pneumoniae pneumonia (MPP) were identified, revealing the role of lung-specific immunologic and inflammatory response in the pathogenesis of MPP. Given the increasing incidence of severe MPP in children in recent years and the emergence of macrolide-resistant M. pneumoniae infection in some regions, our findings provided valuable knowledge and insights into the pathogenesis of M. pneumoniae infection.
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spelling doaj-art-b4ddf0d67d19473f8a7124adb0f0f4782025-08-20T01:52:11ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2025-05-011610.3389/fmicb.2025.15955211595521Proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe Mycoplasma pneumoniae pneumoniaAo Liang0Yaqi Zhu1Xiaoxue Wu2Qingyan Zhang3Yafang He4Anbang Wang5Anbang Wang6Chunchen Wu7Chunchen Wu8Jianbo Xia9Jianbo Xia10Jianbo Xia11Department of Laboratory Medicine, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Pediatrics, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaSpecAlly Life Technology Co., Ltd., Wuhan, ChinaDepartment of Laboratory Medicine, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Laboratory Medicine, Hubei University of Chinese Medicine, Wuhan, ChinaDepartment of Laboratory Medicine, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaHubei Provincial Center for the Prevention and Treatment of Pediatric Infectious Diseases, Wuhan, ChinaDepartment of Laboratory Medicine, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Laboratory Medicine, Hubei University of Chinese Medicine, Wuhan, ChinaHubei Provincial Center for the Prevention and Treatment of Pediatric Infectious Diseases, Wuhan, ChinaObjectivesMycoplasma 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.MethodsIn 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.ResultsA 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.ConclusionA 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.ImportanceDifferences in the proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe Mycoplasma pneumoniae pneumonia (MPP) were identified, revealing the role of lung-specific immunologic and inflammatory response in the pathogenesis of MPP. Given the increasing incidence of severe MPP in children in recent years and the emergence of macrolide-resistant M. pneumoniae infection in some regions, our findings provided valuable knowledge and insights into the pathogenesis of M. pneumoniae infection.https://www.frontiersin.org/articles/10.3389/fmicb.2025.1595521/fullMycoplasma pneumoniae pneumoniaquantitative proteomicsdifferentially expressed proteinsbronchoalveolar lavage fluidpredictive model
spellingShingle Ao Liang
Yaqi Zhu
Xiaoxue Wu
Qingyan Zhang
Yafang He
Anbang Wang
Anbang Wang
Chunchen Wu
Chunchen Wu
Jianbo Xia
Jianbo Xia
Jianbo Xia
Proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe Mycoplasma pneumoniae pneumonia
Frontiers in Microbiology
Mycoplasma pneumoniae pneumonia
quantitative proteomics
differentially expressed proteins
bronchoalveolar lavage fluid
predictive model
title Proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe Mycoplasma pneumoniae pneumonia
title_full Proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe Mycoplasma pneumoniae pneumonia
title_fullStr Proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe Mycoplasma pneumoniae pneumonia
title_full_unstemmed Proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe Mycoplasma pneumoniae pneumonia
title_short Proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe Mycoplasma pneumoniae pneumonia
title_sort proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severe mycoplasma pneumoniae pneumonia
topic Mycoplasma pneumoniae pneumonia
quantitative proteomics
differentially expressed proteins
bronchoalveolar lavage fluid
predictive model
url https://www.frontiersin.org/articles/10.3389/fmicb.2025.1595521/full
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