Abstract
Background
Mycoplasma pneumoniae (MP) is a leading causative agent of community-acquired pneumonia (CAP) in children, with the incidence of severe MP pneumonia (SMPP) increasing in recent years. This study aimed to investigate the expression of miR-222-3p in pediatric MP pneumonia (MPP) and its correlation with inflammatory factors, as well as to explore its possible relationship with SMPP.
Methods
A total of 87 children with MPP and 43 healthy controls were enrolled in the study. MiR-222-3p levels were quantified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), while serum interleukin (IL)-6 and tumor necrosis factor-alpha (TNF-α) levels were measured by enzyme-linked immunosorbent assay (ELISA). The correlation between miR-222-3p and inflammatory cytokines was analyzed, and the ability of miR-222-3p to distinguish SMPP was evaluated by receiver operating characteristic (ROC) curve analysis.
Results
The children with MPP exhibited significantly elevated levels of miR-222-3p, IL-6, and TNF-α compared to the healthy controls (P<0.05). Notably, miR-222-3p and IL-6 were observed to be differentially expressed between the SMPP and mild MPP cases. Combination of miR-222-3p and IL-6 had an area under the curve (AUC) of 0.882 for identifying SMPP. Additionally, a positive correlation was found between the miR-222-3p and IL-6 levels.
Conclusions
The expression of miR-222-3p is significantly up-regulated in pediatric MPP, and shows a correlation with disease severity, suggesting it may be a useful biomarker in the clinical assessment of SMPP.
Keywords: Expression, miR-222-3p, Mycoplasma pneumoniae pneumonia (MPP)
Highlight box.
Key findings
• The levels of miR-222-3p, interleukin (IL)-6, and tumor necrosis factor-alpha (TNF-α) were significantly elevated in the children with Mycoplasma pneumoniae pneumonia (MPP) compared to the healthy controls. Notably, miR-222-3p and IL-6 were observed to be differentially expressed between the severe MPP (SMPP) and mild MPP cases. MiR-222-3p could serve as a potential biomarker for disease severity prediction.
What is known, and what is new?
• Multiple studies have reported significantly increased serum levels of IL subtypes, particularly IL-6, IL-8, and TNF-α, during the acute phase of infection with MPP. Studies have shown that microRNAs (miRNAs) contribute to disease pathogenesis by orchestrating immune cell development and differentiation. Aberrant miRNA expression patterns have been found to be strongly correlated with disease progression.
• The current study sought to examine the expression patterns of miR-222-3p in pediatric MPP and investigate its potential regulatory functions in the inflammatory cascade associated with MPP pathogenesis.
What is the implication, and what should change now?
• Building on these findings and considering the established roles of miR-222-3p, IL-6, and TNF-α in MPP-related airway inflammation, we developed a clinical prediction model by receiver operating characteristic curve analysis. The combination of miR-222-3p and IL-6 demonstrated superior performance in the prediction of SMPP compared to either biomarker alone. This synergistic effect highlights the clinical potential of this biomarker combination for the early identification of severe cases.
Introduction
Mycoplasma pneumoniae (MP) is a predominant pathogen responsible for respiratory infections in children, particularly community-acquired pneumonia (CAP). Epidemiological studies indicate that MP pneumonia (MPP) accounts for 20–40% of pediatric CAP cases (1,2). MPP is generally self-limiting and mild; however, in recent years, there has been a concerning increase in the incidence of severe MPP (SMPP), particularly in Asia, imposing a substantial healthcare burden globally (3,4).
In July 2023, a widespread MP outbreak across China led to a sharp surge in pediatric MPP cases, predominantly affecting school-aged children (5). Notably, 23.7% of these cases progressed to SMPP (6). SMPP is associated with severe respiratory complications, including massive pleural effusion, acute respiratory distress syndrome, pulmonary fibrosis, and bronchiolitis obliterans. Additionally, it can induce extrapulmonary manifestations, significantly compromising affected children’s health and quality of life (7,8).
The precise etiology and pathogenesis of severe SMPP remain incompletely understood. Current evidence suggests that MP infection triggers an exaggerated immune response, leading to persistent injury of the respiratory epithelium and ciliary dysfunction through the activation of immune cells and subsequent release of inflammatory cytokines. Multiple studies have reported significantly increased serum levels of interleukin (IL) subtypes, particularly IL-6, IL-8, and tumor necrosis factor-alpha (TNF-α), during the acute phase of infection (9-11). However, the exact molecular mechanisms driving these pathological changes remain to be fully elucidated, constituting a critical gap in current understanding and an important focus of ongoing research.
Emerging evidence highlights the crucial regulatory roles of non-coding RNAs (ncRNAs), including microRNAs (miRNAs or miRs) and long ncRNAs, in fundamental biological processes such as gene expression modulation and cellular development (12). Among these, miRNAs have gained considerable attention as potent regulators of inflammatory pathways. These evolutionarily conserved, endogenous short ncRNAs are transcribed from non-coding genomic regions and function as key post-transcriptional modulators of gene expression. Their involvement in respiratory infectious diseases has become increasingly apparent, with a study (13) demonstrating that miRNAs contribute to disease pathogenesis by orchestrating immune cell development and differentiation. Aberrant miRNA expression patterns have been shown to be strongly correlated with disease progression.
In a seminal study, Chu et al. (14) performed a comparative analysis of peripheral blood miRNA profiles between pediatric MPP patients and healthy controls, revealing 26 differentially expressed miRNAs, including significantly up-regulated miRNA-222-3p. Building on these findings, the current study focused on miR-222-3p (which was found to be significantly differentially expressed in preliminary genomic analyses) to elucidate its expression patterns in pediatric MPP and investigate its potential regulatory functions in the inflammatory cascade associated with the pathogenesis of MPP. We present this article in accordance with the STARD reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-1-880/rc).
Methods
Study design
Study population
In total, 87 pediatric MPP patients (aged 3–12 years) admitted to the Pediatric Respiratory Department of Chengdu Women’s and Children’s Central Hospital between September 2023 and March 2024 were consecutively enrolled in this prospective study, along with 43 age-matched healthy controls recruited from the Child Health Clinic. Patients were classified into the mild MPP group or the SMPP group based on: (I) radiographic disease extent; and (II) clinical severity markers (dyspnea and respiratory distress). The healthy controls underwent rigorous screening, including: (I) MP polymerase chain reaction (PCR) testing; and (II) serum MP antibody testing. Any participants who tested positive for current or recent MP infection were excluded from the study. And all the healthy controls were consecutively recruited during the study period. They were selected from children who underwent routine blood sampling for health check-ups. The matching with the MPP group was primarily based on age, and recruitment was conducted concurrently to ensure temporal matching.
This study protocol was approved by the Chengdu Women’s and Children’s Central Hospital Institutional Review Board (No. 2022[194]). The data included did not contain any identifiable information. Consents have been obtained from the legal guardians of all research participants, and all procedures were performed in accordance with the Declaration of Helsinki and its subsequent amendments.
Inclusion criteria (15)
Patients were included in the study if they: (I) had a clinical diagnosis of pneumonia by board-certified respiratory physicians based on characteristic symptoms (e.g., fever and cough) or radiographic confirmation of pneumonia; (II) had laboratory confirmation of MP infection (defined as either positive PCR from nasopharyngeal/oral secretions, or a serum MP antibody titer ≥1:160); (III) were aged 3–12 years; (IV) had not previously received antimicrobial therapy for mycoplasma infection; and (V) had written informed consent obtained from their parents/legal guardians.
Exclusion criteria
Patients were excluded from the study if they: (I) had chronic respiratory diseases (e.g., asthma or cystic fibrosis); (II) had concurrent respiratory infections with other pathogens; (III) were immunocompromised (due to congenital/acquired immunodeficiency or connective tissue disorders); and/or (IV) had parents/guardians who refused to allow them to participate in the study.
Sample collection and processing
Venous blood samples (4 mL) were collected from each participant under aseptic conditions prior to the initiation of treatment. The samples were immediately processed as follows: (I) whole-blood aliquot preparation: 2 mL of the sample was transferred directly into an ethylenediaminetetraacetic acid (EDTA) tube and stored at −80 ℃; (II) serum preparation: the remaining 2 mL was centrifuged at 2,000 ×g for 20 minutes at 4 ℃; and (III) serum aliquot preparation: the supernatant was carefully aspirated and distributed into sterile, RNase-free Eppendorf tubes. All the samples were flash-frozen in liquid nitrogen, and subsequently maintained at −80 ℃ until analysis. Complete clinical metadata, including demographic characteristics (age and sex) and hematological parameters, were systematically recorded in our study database. Furthermore, not all enrolled patients were included in all the tests. The missing data were primarily due to insufficient plasma volume collected at enrollment or failure to pass internal quality control procedures (e.g., low RNA yield, hemolyzed samples, or out-of-range assay values). These cases were excluded from the specific analyses involving the respective missing biomarker.
RNA extraction, library preparation, and sequencing
The peripheral blood samples of three MPP cases and three healthy controls were obtained. Total RNA was extracted from these blood samples using Trizol reagent (Foregene, China) in accordance with the manufacturer’s instructions. RNA quality was then determined using an Agilent Bioanalyser 5300 (Agilent, USA) and quantified using the ND-2000 (Thermo Fisher Scientific, USA). Small RNA libraries were generated using the QIAseq miRNA Library Kit (Clontech, USA) in accordance with the manufacturer’s instructions. MiRNAs were considered to be differentially expressed if the P value was <0.05 and the false discovery rate was ≤0.05.
Reverse transcription-quantitative PCR (RT-qPCR)
Total RNA was extracted from the blood samples using Trizol reagent (Foregene) in accordance with the manufacturer’s instructions. Following RNA extraction, the concentration and purity of all the samples were quantified using the K2800 Nucleic Acid Analyzer (Kaiao Technology Development Co., Ltd., Beijing, China). Samples with A260/A280 ratios between 1.8 and 2.0 were processed for downstream analysis. RT-qPCR was performed by miRNA First Strand cDNA Synthesis (Sangon Biotech, Shanghai, China). The sequences of the primers used in the current study are set out in Table 1.
Table 1. RT-qPCR primer information.
| Primer name | Sequences |
|---|---|
| IL-6-F | AGACAGCCACTCACCTCTTCAG |
| IL-6-R | TTCTGCCAGTGCCTCTTTGCTG |
| TNF-α-F | TGTAGCCCATGTTGTAGCAAACC |
| TNF-α-R | GAGGACCTGGGAGTAGATGAGGTA |
| MiR-222-3p-F | AGCGCCTAGCTACATCTGGCT |
| MiR-222-3p-R | ATCCAGTGCAGGGTCCGAGG |
F, forward; IL-6, interleukin-6; R, reverse; RT-qPCR, reverse transcription-quantitative polymerase chain reaction; TNF-α, tumor necrosis factor-alpha.
After the finalization of the RT-qPCR experiments, the average values of the cycle threshold (Ct) of the reactions in triplicate were determined. The data analysis was performed using the 2−ΔΔCt method.
Enzyme-linked immunosorbent assay (ELISA)
The levels of IL-6 and TNF-α in the serum of the patient group and healthy children group were determined using ELISA kits (Sichuan Scientist Biotechnology Co., Ltd., Chengdu, China) in accordance with the manufacturer’s instructions. The experiment established standard wells, blank wells, and sample wells. Standard solutions, pre-processed sample liquids, reagents, and working solutions were added to their respective wells. Optical density (OD) values were measured at a 450-nm wavelength using a microplate reader. The mean OD values of the standard and sample duplicate wells were calculated and corrected by subtracting the blank well OD values. The results were fitted to a standard curve, and sample concentrations were determined by interpolating corrected OD values into this curve.
Statistical analyses
The statistical analyses were conducted using IBM SPSS Statistics for Windows, version 25.0 (IBM Corp., Armonk, NY, USA). The categorical variables are presented as the number (n) and percentage (%), and were compared using Pearson’s χ2. The normally distributed continuous variables are expressed as the mean ± standard deviation, and were compared using the t-test. The non-normally distributed continuous variables are presented as the median (lower quartile, upper quartile), and were compared using the nonparametric Mann-Whitney U test. Spearman’s correlation was used to analyze the relationships between variables. Variables with a P value <0.05 in the univariate analysis were included in the multivariate logistic regression analysis. A receiver operating characteristic (ROC) curve analysis was applied to evaluate the predictive value of the variables. The level of statistical significance was set at P<0.05.
Results
Baseline characteristics of the included patients
The comparative analysis of the clinical characteristics revealed significant differences between the disease severity groups (Table 2). The SMPP group comprised significantly older children compared to the mild MPP group (P<0.05), while no significant differences were observed in gender distribution (P>0.05). The inflammatory marker analysis demonstrated comparable levels of white blood cell (WBC) count, C-reactive protein (CRP), and procalcitonin (PCT) between the groups (P>0.05 for all). Notably, the SMPP group exhibited distinct hematological profiles characterized by significantly increased neutrophil counts (P<0.05), as well as significantly decreased lymphocyte counts (P<0.05). These findings suggest that while traditional inflammatory markers may not be able to be used to detect disease severity, specific cellular immune responses involving neutrophil-lymphocyte ratios may serve as potential indicators of disease progression.
Table 2. Demographic data and clinical characteristics of children with MP.
| Parameters | Mild group (n=38) | Severe group (n=49) | P value |
|---|---|---|---|
| Age (years) | 5.0 (3.3, 8.0) | 6.0 (6.0, 8.0) | 0.02 |
| Gender (male/female) | 20/18 | 21/28 | 0.37 |
| WBC count (×109/L) | 7.92 (6.61, 10.76) | 7.81 (5.71, 9.30) | 0.26 |
| Neutrophils (%) | 58.54±10.88 | 63.06±12.06 | 0.07 |
| Lymphocyte (%) | 31.76±11.75 | 26.58±11.39 | 0.041 |
| CRP (mg/L) | 18.30 (6.70, 31.40) | 20.20 (7.20, 37.05) | 0.62 |
| PCT (ng/mL) | 0.13 (0.07, 0.25) | 0.12 (0.08, 0.27) | 0.78 |
Data are presented as median (lower quartile, upper quartile), number, or mean ± SD. CRP, C-reactive protein; MP, Mycoplasma pneumoniae; PCT, procalcitonin; SD, standard deviation; WBC, white blood cell.
Total miRNA profiling by whole transcriptome sequencing
The comparative miRNA profiling revealed significant dysregulation in the pediatric MPP patients compared to the healthy controls. A total of 30 serum miRNAs were found to be differentially expressed (i.e., had a fold change greater than 2) (Figure 1), of which 13 were up-regulated and 17 were down-regulated. Notably, miR-222-3p was significantly up-regulated in the MPP cohort, suggesting its potential involvement in disease pathogenesis. Thus, miR-222-3p was prioritized as a candidate for subsequent RT-qPCR validation, owing to its statistical significance and biological relevance.
Figure 1.
Volcano plot of the differentially expressed miRNAs. Of all the differentially expressed miRNAs, 13 miRNAs were up-regulated and 17 miRNAs were down-regulated. FC, fold change; miRNA, microRNA; N, normal; P, patient.
Differential expression of IL-6, TNF-α, and serum miR-222-3p between the MPP and control groups
The serum levels of IL-6, TNF-α, and miR-222-3p were significantly higher in the children with MPP than in the healthy controls (Figure 2A-2C).
Figure 2.
Differential expression of IL-6, TNF-α, and miR-222-3p in the children with MPP. (A) The expression of IL-6 in the MPP group (n=87) and control group (n=43). (B) The expression of TNF-α in the MPP group (n=71) and control group (n=43). (C) The expression of miR-222-3p in the MPP group (n=80) and control group (n=43). ***, P<0.001. IL-6, interleukin-6; MPP, Mycoplasma pneumoniae pneumonia; TNF-α, tumor necrosis factor-alpha.
Differential expression of IL-6, TNF-α, and serum miR-222-3p between the mild MPP and SMPP groups
To evaluate the clinical utility of inflammatory mediators in detecting disease severity, we performed comparative analyses between the mild MPP and SMPP cases. The results demonstrated that both IL-6 (P=0.04) and miR-222-3p (P<0.001) were significantly differentially expressed in the SMPP patients compared to the mild MPP patients (Figure 3A-3C). These findings suggest their potential value as severity biomarkers in pediatric MPP. Conversely, TNF-α levels showed no significant variation between the severity groups (P=0.62), indicating its limited utility for disease stratification.
Figure 3.
Differential expression of IL-6, TNF-α, and miR-222-3p in the children with MMPP and SMPP. (A) The expression of IL-6 in the MMPP group (n=38) and SMPP group (n=49). (B) The expression of TNF-α in the MMPP group (n=32) and SMPP group (n=39). (C) The expression of miR-222-3p in the MMPP group (n=33) and SMPP group (n=47). *, P<0.05; ***, P<0.001; ns, not significant (P>0.05). IL-6, interleukin-6; MMPP, mild Mycoplasma pneumoniae pneumonia; SMPP, severe Mycoplasma pneumoniae pneumonia; TNF-α, tumor necrosis factor-alpha.
Correlation between serum IL-6, TNF-α, and serum miR-222-3p
To examine the potential role of miR-222-3p in the pathogenesis of MPP, we conducted comprehensive correlation analyses between serum miR-222-3p levels and key inflammatory parameters, including cytokine levels (IL-6 and TNF-α) and systemic inflammatory markers (WBC count, CRP, and PCT). Our analysis revealed a statistically significant positive correlation between the miR-222-3p and IL-6 expression levels (Table 3). However, no significant correlations were observed between miR-222-3p and the TNF-α, WBC count, CRP, or PCT levels (all P>0.05).
Table 3. Correlation between serum miR-222-3p and airway inflammatory factors.
| Parameters | MiR-222-3p | IL-6 | TNF-α | WBC count | CRP | PCT |
|---|---|---|---|---|---|---|
| MiR-222-3p | – | <0.001 | 0.38 | 0.38 | 0.74 | 0.46 |
| IL-6 | <0.001 | – | <0.001 | 0.03 | 0.03 | 0.63 |
| TNF-α | 0.38 | <0.001 | – | 0.88 | 0.96 | 0.21 |
| WBC count | 0.38 | 0.03 | 0.88 | – | 0.002 | 0.42 |
| CRP | 0.07 | 0.03 | 0.96 | 0.002 | – | 0.75 |
| PCT | 0.46 | 0.63 | 0.21 | 0.42 | 0.75 | – |
Data are presented as P value. CRP, C-reactive protein; IL-6, interleukin-6; PCT, procalcitonin; TNF-α, tumor necrosis factor-alpha; WBC, white blood cell.
Predictive value of serum miR-222-3p and inflammatory factors
A ROC curve analysis was conducted to evaluate the diagnostic potential of serum miR-222-3p and inflammatory factors for SMPP. The results revealed that serum miR-222-3p had excellent predictive value with an area under the curve (AUC) of 0.836 [95% confidence interval (CI): 0.741–0.931; P<0.001], while IL-6 had moderate predictive value (AUC =0.645; 95% CI: 0.518–0.773; P=0.03). Notably, the combination of miR-222-3p and IL-6 displayed superior diagnostic accuracy with an AUC of 0.882 (95% CI: 0.803–0.961; P<0.001), a sensitivity of 87.2%, and a specificity of 81.8%. These findings suggest that the combined biomarker panel may serve as a valuable clinical tool for the early identification of SMPP (Figure 4).
Figure 4.
ROC curves of IL-6 and miR-222-3p in the diagnosis of SMPP in children. IL-6, interleukin-6; ROC, receiver operating characteristic; SMPP, severe Mycoplasma pneumoniae pneumonia.
Discussion
MPP represents a prevalent form of pediatric lower respiratory tract infection. While typically self-limiting, the emergence of antibiotic-resistant strains and evolving epidemic variants has led to a concerning increase in the incidence of SMPP. This epidemiological shift underscores the critical need for reliable early predictors of disease severity to guide clinical management and improve outcomes.
MiRNAs have emerged as important immunomodulators in respiratory infections. Several miRNAs have been implicated in the pathogenesis of MPP. Research has shown that miR-29c and miR-146a can serve as diagnostic biomarkers (16), miR-1323 plays a role in inflammatory regulation (10), and miR-34a can serve as a severity indicator (17). However, the role of miR-222-3p—a pivotal inflammatory network regulator—remains insufficiently characterized in MPP.
Our findings extend the work of Chu et al. (14), who reported elevated miR-222-3p and decreased CD4 levels in pediatric MPP. We confirmed these observations and further demonstrated that: (I) miR-222-3p was significantly higher in the MPP patients than the healthy controls; (II) the expression of miR-222-3p was progressively higher in SMPP than mild MPP cases; and (III) miR-222-3p was correlated with systemic inflammatory responses. These results position miR-222-3p as a dual-purpose biomarker capable of both MPP detection and severity stratification; thus, it may have novel clinical utility in pediatric respiratory medicine.
Previous research has established IL-6 and TNF-α as pivotal mediators of airway inflammation (18). Accumulating evidence suggests that these cytokines play crucial roles in MP pulmonary infection, with their dysregulation significantly contributing to the pathogenesis of MPP (19,20). Clinical studies have demonstrated the diagnostic potential of these inflammatory markers. Some reports identified elevated IL-6 levels as a predictive indicator for pediatric MPP (21,22), while other investigators reported significantly increased TNF-α concentrations in MPP patients (23). Our findings corroborated and extended these observations by demonstrating that: (I) the serum levels of both IL-6 and TNF-α were significantly increased in the children with MPP compared to the healthy controls; and (II) the concentrations of IL-6 were significantly higher in the SMPP cases than the mild MPP cases. Importantly, TNF-α expression did not differ significantly between the severity groups; however, the marked elevation of IL-6 in severe cases suggests its particular utility as a severity stratification biomarker. These collective findings position IL-6 as a dual-purpose biomarker for both MPP diagnosis and severity assessment, while TNF-α may be more relevant for initial diagnosis.
To elucidate the mechanistic relationship between miR-222-3p and key inflammatory mediators, we performed comprehensive correlation analyses. Our results revealed a significant positive correlation between circulating miR-222-3p levels and IL-6 concentrations, suggesting their coordinated involvement in the pathogenesis of MPP. This association indicates that miR-222-3p may participate in the inflammatory cascade through regulatory interactions with IL-6-mediated pathways.
Building on these findings and considering the established roles of miR-222-3p, IL-6, and TNF-α in MPP-related airway inflammation, we developed a clinical prediction model by ROC curve analysis. The combination of miR-222-3p and IL-6 demonstrated superior performance in the prediction of SMPP compared to either biomarker alone. This synergistic effect highlights the clinical potential of this biomarker combination for the early identification of severe cases.
Although our study identified miR-222-3p as a promising biomarker for pediatric MPP severity stratification, several limitations must be acknowledged. The single-center design and modest sample size might affect the generalizability of our findings, while the observational nature of this research precluded any definitive conclusions being drawn in relation to causal relationships. Most significantly, the lack of mechanistic investigations limits our understanding of the precise role of miR-222-3p in inflammatory regulation. To address these gaps, we propose an integrated research strategy encompassing: (I) in vitro functional studies using antisense oligonucleotide-mediated miR-222-3p inhibition in respiratory epithelial cells and macrophages to delineate its immunomodulatory effects; (II) large-scale multicenter validation studies to confirm the clinical utility of our biomarker panel; and (III) therapeutic exploration of miR-222-3p as a potential intervention target for SMPP. These investigations will not only elucidate the mechanistic basis of the pathogenesis of MPP but may also facilitate the development of novel diagnostic and therapeutic strategies for severe pediatric cases.
Conclusions
Collectively, our findings indicate that serum levels of miR-222-3p are elevated in pediatric MPP patients and show further upregulation in severe cases. These results suggest that miR-222-3p may have potential as a diagnostic biomarker to aid in distinguishing between MMPP and SMPP. Moreover, the observed strong correlation between miR-222-3p and inflammatory factors such as IL-6 supports its association with airway inflammation in MPP. Notably, the combination of miR-222-3p and IL-6 showed improved ability in identifying SMPP compared to either marker alone, indicating its possible utility in clinical assessment for early risk stratification. Overall, this study provides clinical evidence linking miR-222-3p expression to disease severity in pediatric MPP, highlighting its potential relevance for further investigation into the pathophysiology and clinical management of SMPP.
Supplementary
The article’s supplementary files as
Acknowledgments
None.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study protocol was approved by the Chengdu Women’s and Children’s Central Hospital Institutional Review Board (No. 2022[194]). The data included did not contain any identifiable information. Consents have been obtained from the legal guardians of all research participants, and all procedures were performed in accordance with the Declaration of Helsinki and its subsequent amendments.
Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-1-880/rc
Funding: This work was supported by the Natural Science Foundation of Sichuan Province, China (No. 23NSFSC5420).
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-1-880/coif). The authors have no conflicts of interest to declare.
(English Language Editor: L. Huleatt)
Data Sharing Statement
Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-1-880/dss
References
- 1.Yan C, Sun H, Zhao H. Latest Surveillance Data on Mycoplasma pneumoniae Infections in Children, Suggesting a New Epidemic Occurring in Beijing. J Clin Microbiol 2016;54:1400-1. 10.1128/JCM.00184-16 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Meyer Sauteur PM, Jacobs BC, Spuesens EB, et al. Antibody responses to Mycoplasma pneumoniae: role in pathogenesis and diagnosis of encephalitis? PLoS Pathog 2014;10:e1003983. 10.1371/journal.ppat.1003983 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Huang F, Lu L, Jiang W, et al. The epidemiology and clinical features of Mycoplasma pneumoniae infection in neonates. Braz J Infect Dis 2016;20:374-8. 10.1016/j.bjid.2016.04.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Izumikawa K. Clinical Features of Severe or Fatal Mycoplasma pneumoniae Pneumonia. Front Microbiol 2016;7:800. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Zhu X, Liu P, Yu H, et al. An outbreak of Mycoplasma pneumoniae in children after the COVID-19 pandemic, Shanghai, China, 2023. Front Microbiol 2024;15:1427702. 10.3389/fmicb.2024.1427702 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Li Y, Wu M, Liang Y, et al. Mycoplasma pneumoniae infection outbreak in Guangzhou, China after COVID-19 pandemic. Virol J 2024;21:183. 10.1186/s12985-024-02458-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Mărginean CO, Meliţ LE, Simu I, et al. The Association Between Mycoplasma pneumoniae and Chlamydia pneumoniae, a Life-Threatening Condition in Small Children-A Case Report and a Review of the Literature. Front Pediatr 2020;8:558941. 10.3389/fped.2020.558941 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Tsai TA, Tsai CK, Kuo KC, et al. Rational stepwise approach for Mycoplasma pneumoniae pneumonia in children. J Microbiol Immunol Infect 2021;54:557-65. 10.1016/j.jmii.2020.10.002 [DOI] [PubMed] [Google Scholar]
- 9.Wang Z, Chu C, Ding Y, et al. Clinical significance of serum microRNA-146a and inflammatory factors in children with Mycoplasma pneumoniae pneumonia after azithromycin treatment. J Pediatr (Rio J) 2024;100:108-15. 10.1016/j.jped.2023.06.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Yin L, Ma Y, Wang W, et al. The critical function of miR-1323/Il6 axis in children with Mycoplasma pneumoniae pneumonia. J Pediatr (Rio J) 2021;97:552-8. 10.1016/j.jped.2020.11.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Bao X, Wang Q, Geng H, et al. Correlation of prognostic values of IL-6 and PCT levels with the severity of pneumonia caused by Mycoplasma pneumoniae in children. Pak J Med Sci 2025;41:1305-10. 10.12669/pjms.41.5.10448 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Correia de Sousa M, Gjorgjieva M, Dolicka D, et al. Deciphering miRNAs’ Action through miRNA Editing. Int J Mol Sci 2019;20:6249. 10.3390/ijms20246249 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Foster PS, Plank M, Collison A, et al. The emerging role of microRNAs in regulating immune and inflammatory responses in the lung. Immunol Rev 2013;253:198-215. 10.1111/imr.12058 [DOI] [PubMed] [Google Scholar]
- 14.Chu C, Lei X, Li Y, et al. High expression of miR-222-3p in children with Mycoplasma pneumoniae pneumonia. Ital J Pediatr 2019;45:163. 10.1186/s13052-019-0750-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Søndergaard MJ, Friis MB, Hansen DS, et al. Clinical manifestations in infants and children with Mycoplasma pneumoniae infection. PLoS One 2018;13:e0195288. 10.1371/journal.pone.0195288 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Wang J, Guo C, Yang L, et al. Peripheral blood microR-146a and microR-29c expression in children with Mycoplasma pneumoniae pneumonia and its clinical value. Ital J Pediatr 2023;49:119. 10.1186/s13052-023-01500-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Li M, Lu L, Xu H. Diagnostic value of miR-34a in Mycoplasma pneumoniae pneumonia in children and its correlation with rehabilitation effect. J Cardiothorac Surg 2024;19:507. 10.1186/s13019-024-02992-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Yu JS, Jin J, Li YY. The physiological functions of IKKs-selective substrate identification and their critical roles in diseases. STEMedicine 2020;1:e49. [Google Scholar]
- 19.Fan H, Lu B, Yang D, et al. Distribution and Expression of IL-17 and Related Cytokines in Children with Mycoplasma pneumoniae Pneumonia. Jpn J Infect Dis 2019;72:387-93. 10.7883/yoken.JJID.2019.113 [DOI] [PubMed] [Google Scholar]
- 20.Tian F, Chen LP, Yuan G, et al. Differences of TNF-α, IL-6 and Gal-3 in lobar pneumonia and bronchial pneumonia caused by mycoplasma pneumoniae. Technol Health Care 2020;28:711-9. 10.3233/THC-192011 [DOI] [PubMed] [Google Scholar]
- 21.Fan F, Lv J, Yang Q, et al. Clinical characteristics and serum inflammatory markers of community-acquired mycoplasma pneumonia in children. Clin Respir J 2023;17:607-17. 10.1111/crj.13620 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Dong X, Li R, Zou Y, et al. Co-detection of respiratory pathogens in children with Mycoplasma pneumoniae pneumonia: a multicenter study. Front Pediatr 2025;13:1482880. 10.3389/fped.2025.1482880 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Chen ZR, Zhang GB, Wang YQ, et al. Soluble B7-H3 elevations in hospitalized children with Mycoplasma pneumoniae pneumonia. Diagn Microbiol Infect Dis 2013;77:362-6. 10.1016/j.diagmicrobio.2013.09.006 [DOI] [PubMed] [Google Scholar]