Low expression of miR-126 constitutes a risk factor for perioperative respiratory adverse events among pediatric patients under general anesthesia

Abstract

Aim

This study aims to investigate the diagnostic value of miR-126 in Perioperative respiratory adverse events (PRAEs).

Methods

This study included 228 pediatric patients undergoing anesthesia and surgery, who were divided into two groups based on the occurrence of PRAEs. RT-qPCR was used to detect miR-126 levels, the CCK-8 assay was employed to evaluate cell proliferation capacity, and ELISA kits were utilized to measure TNF-α, IL-6, and IL-13 concentrations. The diagnostic value of miR-126 was assessed through receiver operating characteristic curve analysis.

Results

miR-126 is significantly downregulated in the serum of children with PAREs. Low expression of miR-126 is one of the risk factors for PRAEs occurrence. miR-126 level shows a negative correlation with the inflammatory levels in children with PRAEs. Overexpression of miR-126 promotes cell proliferation activity.

Conclusion

miR-126 may contribute to the suppression of PRAEs by regulating proliferation and inflammatory responses in BEAS-2B cells and may serve as a diagnostic biomarker.

Introduction

General anesthesia is the primary anesthetic approach for pediatric surgery, with its safety and efficacy remaining key focuses of clinical research. Following induction, children receive artificial ventilation via methods such as endotracheal intubation or laryngeal mask airway (LMA) [1]. However, due to the narrow anatomy of the pediatric airway, delicate mucosa, high oxygen consumption rate, and limited respiratory compensatory capacity, perioperative respiratory adverse events (PRAEs) are highly prevalent during general anesthesia [2]. PRAEs are one of the common complications following pediatric anesthesia, often presenting with symptoms such as airway obstruction, laryngospasm, and hypoxemia. Severe cases may lead to asphyxia or even death [3, 4]. Previous studies have indicated that risk factors for PRAEs include younger age, history of reactive airway disease, upper respiratory tract infection, obesity, and obstructive sleep apnea [5, 6]. Although these factors aid in surgical risk stratification, they cannot serve as ideal diagnostic criteria. Therefore, identifying specific diagnostic biomarkers is crucial for preventing the occurrence of PRAEs.

The regulatory role of microRNAs (miRNA) in disease has become a hot topic of research in recent years. For example, miR-24 alleviates airway inflammatory responses in chronic obstructive pulmonary disease (COPD) by targeting the S100A8 protein [7]. Research confirms that miR-126 is associated with multiple respiratory diseases. It is downregulated in lung injury and effectively suppresses inflammatory responses [8]. Clinically, serum miR-126 levels serve as a specific diagnostic marker for pulmonary infection following traumatic brain injury [9] and exhibit a negative correlation with inflammatory cytokine levels in patients with obstructive sleep apnea [10]. It also restores immune balance in airway tissues by suppressing inflammatory mediators, thereby improving allergic respiratory diseases such as asthma and rhinitis [11]. Given that airway inflammation and underlying respiratory pathology are risk factors for PRAEs, we speculate that miR-126 levels may be involved in the development and progression of PRAEs.

In summary, we decided to include PRAEs patients and investigate the relationship between serum miR-126 levels and clinical indicators. Additionally, we conducted cell co-culture experiments to explore the mechanism by which miR-126 regulates PRAEs.

Methods

Patient enrollment

A total of 228 children (3–12 years old) undergoing general anesthesia surgery were enrolled in this study. They were divided into the control group (n = 108) and the PRAEs group (n = 120) based on the occurrence of PRAEs. All children underwent anesthesia and surgery at Affiliated Hospital of Gansu Medical College from April 2023 to April 2025. Inclusion criteria for the PRAEs group included the presence of one or more of the following symptoms: Persistent cough (≥ 3 consecutive coughing episodes within 30 min of extubation, each lasting ≥ 15 s or comprising ≥ 3 coughs), hypoxemia (SpO₂ <92% lasting ≥ 60 s), apnea (cessation of respiratory flow for ≥ 20 s), irregular breathing (more than 3 abnormal respiratory rhythms per minute), partial airway obstruction (auscultation of wheezing or inspiratory dyspnea, with abnormal or absent end-tidal carbon dioxide waveforms persisting for ≥ 30 s), laryngospasm (accompanied by signs of upper airway obstruction, with a sudden drop or disappearance of end-tidal carbon dioxide levels requiring positive-pressure ventilation), and bronchospasm (expiratory dyspnea, diffuse wheezing on auscultation, “shark fin” pattern in end-tidal carbon dioxide waveform, and persistent decline in SpO₂). Exclusion criteria were as follows: (1) thoracic trauma or hepatic and renal insufficiency; (2) history of pulmonary infection or chronic lung disease; (3) congenital metabolic disorders or congenital heart disease; (4) hypersensitivity to anesthetics; (5) incomplete clinical data. This study was approved by the Ethics Committee of Affiliated Hospital of Gansu Medical College, and the guardians of all patients signed the informed consent form.

Sampling and anesthetic management

Venous blood samples were collected prior to general anesthesia. After centrifugation to obtain serum, the samples were stored at -80 °C for subsequent experiments. Hemolyzed samples were recollected, and the number of freeze-thaw cycles was limited to no more than two.

Children were required to fast for 6–8 h and abstain from fluids for 2 h prior to surgery. All patients received an intramuscular injection of penehyclidine hydrochloride at a dose of 0.1 mg/kg or an intravenous injection at 0.01 mg/kg preoperatively. Non-invasive arterial blood pressure, heart rate, and oxygen saturation of patients were monitored continuously. Anesthesia induction was performed with 8% sevoflurane inhalation. After loss of consciousness, the sevoflurane concentration was adjusted to 3%–4%, and assisted or mechanical ventilation was initiated. Postoperatively, medications such as propofol and remifentanil were administered based on the patient’s condition, and all children were transferred to the post-anesthesia care unit (PACU) for continuous observation. The following indicators were recorded: ASA grade, anesthesia time, surgery time, and pain score.

Cell culture

BEAS-2B bronchial epithelial cells (SCSP-5067) and THP-1 macrophages (SCSP-567) cells were purchased from the National Collection of Authentical Cell Cultures in China. BEAS-2B were cultured in DMEM and THP-1 cells in RPMI-1640‌ supplemented with 10% FBS and 1% penicillin-streptomycin at 37 °C with 5% CO₂.

Cell transfection

miR-126 mimic, mimic NC, miR-126 inhibitor, and inhibitor NC designed and synthesized by GenePharma were transfected into BEAS-2B cells using Lipofectamine 2000 (Invitrogen, CA, USA). In short, mix the synthesized miRNA with Lipofectamine 2000 reagent at room temperature, stir, and incubate for 20 min to form a complex. Subsequently, add this complex to cells in the logarithmic growth phase and continue incubation for 6 h.

RT-qPCR

Total RNA was extracted from serum and cells using Trizol reagent (Thermo Fisher, USA), respectively. cDNA was synthesized with the SuperScript Ⅲ First-Strand Synthesis System (Thermo Fisher). The reaction system for RT-qPCR was prepared using the One Step TB Green^® RT-PCR Kit (Takara, Japan), and the detection was performed on a 7300 RT-PCR System (Applied Biosystems, USA). The final levels were calculated by the 2^⁻ΔΔCT method. The primer sequences of miR-126 were as follows: forward (F): 5’-GGGTGAGAACTGAATTCCA-3’; reverse (R): 5’-CAGGTGGCGTCGTGG ATG-3’.

Cell proliferation

BEAS-2B cells were seeded at a density of 5 × 10³ cells per well in a 96-well cell culture plate. After incubation for 48 h, 10 µl of CCK-8 solution (Thermo Fisher Scientific, USA) was added to each well and incubated at 37 °C for 4 h. Optical density (OD) was measured at 450 nm using an iMark microplate reader (Bio-Rad, USA). Cell viability was determined by calculating the absorbance values against a standard curve.

ELISA

TNF-α ELISA Kit (88-7346-88, Thermo Fisher), IL-6 ELISA Kit (EH2IL6, Thermo Fisher), and IL-13 ELISA Kit (88-7439-88, Thermo Fisher) were used to detect the concentrations of TNF-α, IL-6, and IL-13 in serum and cells. Add 50 µL of standard and 5-fold diluted samples to the wells of the microplate. Subsequently, add 100 µL of enzyme-labeled reagent to each well and incubate at 37 °C for 60 min. After washing, add freshly prepared substrate solution and incubate the plate in the dark at 37 °C for 30 min. Upon reaction termination, measure the absorbance at 450 nm.

Cell co-culture

THP-1 cells were differentiated into macrophage-like cells by treating with 100 ng/mL Phorbol 12-myristate 13-acetate (PMA, Sigma-Aldrich, St. Louis, MO) for 24 h, followed by 24 h of culture in serum-free DMEM medium. Fused BEAS-2B cells were seeded at a density of 1 × 10⁵ cells per well into Transwell chambers with a 0.4 μm pore size and cultured for 24 h to form a monolayer. The chamber was then transferred to a 24-well plate, and 5 × 10⁴ differentiated THP-1 macrophages were seeded into the bottom wells for co-culture. LPS was added at preset concentrations for 24-hour induction. All experiments were performed in triplicate for both technical and biological replicates. Cells and supernatants were subsequently collected for subsequent assays.

Statistical analyses

Data were analyzed using SPSS 23.0 and GraphPad Prism 9 software. Intergroup differences were determined by Student’s t-test (for two groups) and one-way analysis of variance (ANOVA, for multiple groups), while the chi-square test was applied for categorical data comparisons. All experiments were independently repeated three times. Pearson correlation analysis was performed to evaluate the correlations between the concentrations of TNF-α, IL-6, IL-13 and the level of miR-126. Multivariate logistic regression analysis was conducted to identify the risk factors for PRAEs. Receiver operating characteristic (ROC) curve analysis was used to assess the clinical diagnostic value of serum miR-126 for PRAEs. P < 0.05 was considered statistically significant.

Results

Comparison of patients’ clinical information

Table 1 compares clinical characteristics between PRAEs patients (n = 120) and the control group (n = 108). No significant differences were observed between the two groups in age (P = 0.230), gender (P = 0.241) or type of surgery (P = 0.111). However, the PRAEs group exhibited a higher obesity rate (P = 0.029), higher ASA grade (P = 0.015), longer anesthesia time (P = 0.021), longer surgery time (P = 0.010), and higher pain score (P = 0.046). Preoperative airway disease was more common in PRAEs patients, but did not reach statistical significance (P = 0.062).

Table 1.

Clinical characteristics of PRAEs patients and controls individuals

Feature	Controls (n = 108)	PAREs patients (n = 120)	P value
Age (years)	6.21 ± 2.51	6.61 ± 2.97	0.230
Gender			0.241
male	51	66
female	57	54
Obesity			0.029
No	82	75
Yes	26	45
ASA grade			0.015
I-II	72	61
III	36	59
Preoperative airway disease			0.062
No	75	69
Yes	33	51
Anesthesia time			0.021
< 1 h	82	74
≥ 1 h	26	46
Surgery time
< 30 min	86	77	0.010
≥ 30 min	22	43
Pain score			0.046
I-II	75	68
III	33	52
Type of surgery			0.111
Minor/General surgery	60	54
ENT/Airway surgery	48	66

PRAEs perioperative respiratory adverse events, ASA American society of anesthesiologists

Relationship between miR-126 Levels and the clinical characteristics of PRAEs

We detected the serum miR-126 levels in patients. Compared with the control group, the serum miR-126 levels in the PRAEs group were significantly decreased (Fig. 1A). Taking the mean value of serum miR-126 levels in PRAEs patients as the cutoff value, we divided these patients into the high-expression group and the low-expression group. In addition, we analyzed the correlation between miR-126 levels and clinical characteristics using the chi-square test. The results demonstrated that miR-126 levels were not significantly correlated with age (P = 0.163) or gender (P = 0.388), but were significantly associated with obesity (P = 0.042), ASA grade (P = 0.001), preoperative airway disease (P = 0.021), anesthesia time (P = 0.001), surgery time (P = 0.005), pain score (P = 0.035), and Type of surgery (P = 0.049) (Table 2).

Fig. 1.

Expression and diagnostic value of miR-126 in PRAEs. A miR-126 is downregulated in PRAE. B miR-126 demonstrates excellent diagnostic value for PRAEs. C miR-126 levels are negatively correlated with inflammatory cytokine concentrations. *** P < 0.001

Table 2.

Association between miR-126 and clinical features of PRAEs patients

Feature	Cases (n = 120)	miR-126		P value
		Low expression (n = 63)	High expression (n = 57)
Age (years)				0.163
< 7	69	40	29
≥ 7	51	23	28
Gender
male	66	37	29	0.388
female	54	26	28
Obesity				0.042
No	75	34	41
Yes	45	29	16
ASA grade				0.001
I-II	61	23	38
III	59	40	19
Preoperative airway disease				0.021
No	69	30	39
Yes	51	33	18
Anesthesia time (hour)				0.001
< 1	74	28	46
≥ 1	46	35	11
Surgery time
< 30 min	77	33	44	0.005
≥ 30 min	43	30	13
Pain score				0.035
I-II	68	30	38
III	52	33	19
Type of surgery
Minor/General surgery	54	23	31	0.049
ENT/Airway surgery	66	40	26

PRAEs perioperative respiratory adverse events, ASA American society of anesthesiologists

Diagnostic value of miR-126 for PRAEs

miR-126 showed potential value in the diagnosis of PRAEs. ROC curve analysis demonstrated that miR-126 exhibited excellent diagnostic performance for PRAEs, with an area under the curve (AUC) of 0.892, the cutoff value is 0.695, corresponding to a sensitivity of 76.9% and a specificity of 88.9% (Fig. 1B). Multivariate logistic regression analysis was conducted to explore the independent association between miR-126 and PRAEs. All baseline variables in Table 1 were incorporated into the model as covariates. The results in Table 3 showed that obesity (P = 0.032), ASA grade (P = 0.016), anesthesia time (P = 0.033), surgery time (P = 0.012), Type of surgery (P = 0.031) and miR-126 levels were all risk factors for the occurrence of PRAEs. After multivariate adjustment, miR-126 expression remained independently correlated with PRAEs (OR = 0.052, 95% CI: 0.025–0.111, P < 0.001) (Table 3). Inflammatory markers were important indicators for the detection of PRAEs. Results from ELISA assays showed that serum miR-126 levels were negatively correlated with proinflammatory cytokine concentrations: TNF-α (r = − 0.665, P < 0.001), IL-6 (r = − 0.753, P < 0.001), and IL-13 (r = − 0.760, P < 0.001) (Fig. 1C).

Table 3.

Logistic regression analysis of risk factors for PRAEs

Variable	OR	95% CI for OR		P value
		Lower	Upper
Age	1.824	0.869	3.830	0.112
Gender	0.735	0.360	1.500	0.398
Obesity	2.334	1.074	5.075	0.032
ASA grade	2.490	1.184	5.234	0.016
Preoperative airway disease	2.049	0.954	4.400	0.066
Anesthesia time	2.354	1.074	5.161	0.033
Surgery time	2.794	1.252	6.235	0.012
Pain score	1.800	0.864	3.750	0.117
Type of surgery	2.244	1.078	4.670	0.031
miR-126	0.046	0.021	0.101	< 0.001

PRAEs perioperative respiratory adverse events, ASA American society of anesthesiologists

The effect of miR-126 on the co-culture cell model

Clinical trial results indicate that miR-126 may hold significant diagnostic value in predicting the occurrence of PRAEs. To validate the damaging effects of inflammation on lung cells, we established an inflammatory model by treating BEAS-2B cells with LPS. As LPS concentration increased, miR-126 levels significantly decreased (Fig. 2A), and cell proliferation capacity was markedly suppressed (Fig. 2B). A final LPS concentration of 2.0 µg/mL was selected to induce BEAS-2B cells for the cellular model. Subsequent transfection experiments demonstrated that LPS treatment significantly suppressed miR-126 levels. Transfection with a miR-126 mimic up-regulated miR-126 levels, whereas transfection with a miR-126 inhibitor down-regulated its expression (Fig. 3A). LPS treatment inhibited BEAS-2B cell proliferation, while miR-126 mimics partially restored proliferative capacity and miR-126 inhibitors further suppressed cell growth (Fig. 3B). To more authentically mimic the pulmonary environment, we established an LPS-induced co-culture model of BEAS-2B and THP-1 cells. Results demonstrated that LPS induction significantly elevated intracellular inflammatory factor levels. Overexpression of miR-126 suppressed inflammatory responses, whereas miR-126 inhibitor produced the opposite effect (Fig. 3C).

Fig. 2.

Establishment of the inflammatory cell model. A Changes in miR-126 levels with increasing LPS concentration. B BEAS-2B cell proliferation varies with LPS concentration. * P < 0.05, ** P < 0.01, *** P < 0.001

Fig. 3.

Regulation of Proliferation and Inflammation by miR-126. A Changes in miR-126 levels after transfection. B miR-126 mimic promotes BEAS-2B cell viability. C Overexpression of miR-126 suppresses the concentrations of TNF-α, IL-6, and IL-13. ***P < 0.001 vs. control; ^##P < 0.01, ^###P < 0.001 vs. LPS+ mimic NC; ^&&P < 0.01, ^&&&P < 0.001 vs. LPS+ inhibitor NC

Discussion

PRAE is a relatively common complication in pediatric general anesthesia. Its occurrence is associated with multiple factors, including physiological immaturity, susceptibility to fear, and inflammatory stress responses, posing a serious threat to perioperative safety in pediatric patients [12–14]. In recent years, clinicians have actively explored various perioperative strategies to reduce the incidence of PRAEs, including risk factor identification, comparison of laryngeal masks versus endotracheal intubation, prophylactic use of salbutamol, modified extubation techniques, mental status assessment, and specialized nursing care [15–17]. Nevertheless, the probability of PRAEs occurrence and its potentially severe consequences remains a significant concern. Therefore, developing specific diagnostic biomarkers and exploring the molecular mechanisms underlying PRAEs are of paramount importance.

Numerous studies have confirmed that multiple miRNAs serve as diagnostic biomarkers for respiratory diseases. For instance, miR-320c and miR-200c-3p are significantly upregulated in the serum of patients with COPD, demonstrating high diagnostic value with an AUC value of 0.89 [18]. In pneumonia patients, miR-492 levels positively correlate with TNF-α, IL-6, and IL-18. Overexpression of miR-492 may exacerbate pneumonia severity by increasing proinflammatory cytokine concentrations in macrophages [19]. miR-181a and miR-199a also serve as diagnostic biomarkers for obstructive sleep apnea [20]. This study confirms that serum miR-126 levels are significantly downregulated in children with PRAEs and negatively correlated with proinflammatory factors such as TNF-α and IL-6, suggesting that miR-126 may interfere with PRAEs progression by suppressing inflammatory responses. As a potential diagnostic biomarker, miR-126 demonstrated an excellent area under the ROC curve (AUC = 0.892), with its high sensitivity and specificity compensating for the lack of specificity in traditional clinical indicators. Furthermore, miR-126 levels showed significant correlations with risk factors, including obesity, ASA classification, and preoperative airway disease. Low miR-126 levels also constitute a risk factor for PRAEs occurrence. Furthermore, to exclude the confounding effects of baseline clinical characteristics, we performed multivariable logistic regression adjusted for all variables with P < 0.10 in Table 1, including obesity, ASA classification, anesthesia duration, surgical duration, pain score, and surgical type. After full adjustment, serum miR-126 level remained independently and significantly associated with PRAEs. These findings confirm that the downregulation of miR-126 is not merely an epiphenomenon of preoperative baseline inflammation and stress status, but an independent predictive biomarker for PRAEs in children.

Existing research has demonstrated that the presence of pulmonary diseases such as lung inflammation and atelectasis significantly increases the probability of PRAEs occurrence [5]. Concurrently, inflammation serves as a key indicator of pulmonary disease. The BEAS-2B cell line retains the core functional characteristics of normal bronchial epithelial cells while possessing the advantage of long-term in vitro passage inherent to immortalized cells, making it a commonly used model for airway inflammation and injury [21]. THP-1 cells can be induced to differentiate into functionally mature macrophages or dendritic cells [22]. Notably, LPS stimulation mainly induces endotoxin-related inflammatory responses, which differ from the sterile inflammation triggered by surgical trauma and anesthetic stress in clinical PRAEs. Therefore, this cell model was used only to explore the general anti-inflammatory and proliferative regulatory functions of miR-126 in airway-related cells, rather than fully simulating the pathological microenvironment of clinical perioperative respiratory adverse events. We established a co-culture system of BEAS-2B and THP-1 cells to mimic the human upper airway microenvironment, and applied LPS stimulation to construct an airway inflammatory cell model for exploring the regulatory role of miR-126 in inflammation and cell proliferation [23]. Modelling results indicate that as LPS concentration increases, miR-126 levels decrease while cell proliferation is inhibited, mimicking the pathological state of PRAEs. Following transfection with miR-126 mimic, cell proliferation partially recovered and inflammatory responses were suppressed, confirming that miR-126 may mitigate inflammatory injury by regulating interactions between airway epithelial cells and macrophages. This mechanism may be related to the targeted regulation of the PI3K/AKT signalling pathway by miR-126. Previous studies have demonstrated that miR-126 alleviates LPS-induced acute lung injury by directly targeting HMGB1, thereby inhibiting activation of the PI3K/AKT inflammatory signalling pathway and reducing proinflammatory cytokine release [24]. Furthermore, miR-126 promotes M2 anti-inflammatory phenotype conversion by regulating macrophage polarization and decreasing proinflammatory cytokine secretion, thus maintaining airway homeostasis [25]. Similar to the findings in this study, miR-18a-5p exacerbates airway epithelial injury by inhibiting AEC-II cell proliferation, promoting apoptosis, and enhancing inflammatory responses [26]. Collectively, these studies suggest that miR-126 may influence PRAEs progression by regulating the physiological and inflammatory states of BEAS-2B and THP-1 cells.

This study has several limitations that warrant consideration. First, the single-center sample origin may introduce selection bias, necessitating validation through large-scale, multicenter studies. Second, the specific target genes and signalling pathways regulated by miR-126 in PRAEs remain unclear, requiring further exploration of the molecular mechanisms. Finally, the LPS-induced cellular model represents endotoxin-driven inflammation, whereas clinical PRAEs typically involve sterile inflammation caused by mechanical stimulation or anesthetics. Although this LPS-based cell model reveals the general anti-inflammatory effects of miR-126 in airway epithelial cells and macrophages, it cannot fully recapitulate the sterile inflammatory microenvironment induced by surgical and anesthetic stress in clinical PRAEs. Further validation using animal models simulating perioperative sterile airway inflammation is still required to confirm the clinical translational value of our findings.

In summary, miR-126 level is downregulated in the serum of pediatric patients with PRAEs and demonstrates excellent diagnostic performance. Furthermore, miR-126 demonstrates anti-inflammatory and pro-proliferative effects in airway epithelial cells, suggesting a potential protective mechanism that may contribute to reducing PRAEs risk. Although baseline clinical characteristics such as obesity, ASA status, and surgical factors may jointly affect systemic inflammatory status and PRAEs risk, preoperative serum miR-126 level retains independent predictive value after multivariate adjustment. It may serve as a promising adjunct predictive biomarker for risk stratification of pediatric PRAEs in clinical practice.

Authors' contributions

WJL, KLL and ZQF conceptualized and designed the study. WJL, KLL, XTH, XNM and ML collected, organized, and drafted the information. WJL and KLL analyzed the data. WJL and JL wrote the manuscript. ZQF performed manuscript revision. All the authors have read and approved the manuscript.

Funding

No funding was received to assist with the preparation of this manuscript.

Data availability

All data generated or analyzed during this study are included in this article. Further enquiries can be directed to the corresponding author.

Declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee of Affiliated Hospital of Gansu Medical College and received informed consent from the guardians of the children’s patients. The procedures used in this study adhere to the tenets of the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.