This prospective cohort study was conducted at a quaternary academic pediatric medical center. The study was approved by the Institutional Review Board of Boston Children's Hospital (Protocol number IRB-P00033314, approval date 02/18/2020). Written informed consent for participation was obtained from a parent or legal guardian.

All patients scheduled for CHD with CPB at our center were considered for inclusion. We excluded patients who had active infections, were on chronic steroid therapy, had immunodeficiencies, HIV, or a history of malignancy. The study period spanned from May 31, 2022, to February 22, 2023. Included patients received general anesthesia with endotracheal intubation and had arterial and central venous lines placed. Following surgical dissection, they were heparinized and cannulated for CPB. The CPB circuit was primed with red blood cells (RBC) and fresh frozen plasma (FFP) to maintain a hematocrit level above 30%, following our institutional protocol. RBC priming was selectively applied to patients with anticipated hemodilution risk, particularly those under 10 kg. All transfused RBC units were pre-storage leukocyte-depleted and used within 7 days of collection to minimize storage-related inflammatory activation. Circulatory arrest, regional perfusion, temperature management, and modified ultrafiltration (MUF) were used as needed. Platelet and cryoprecipitate were administered for non-surgical microvascular bleeding. Typically, neonates and infants did not receive FFP post-CPB in our institution. At the conclusion of surgery, patients were either extubated or remained intubated based on the anesthesiologist's decision and transferred to the ICU for further care.

For the analysis of clinical data, we extracted a comprehensive range of data from electronic medical records. This included demographic details, comorbidities, diagnoses, surgical procedures, laboratory results, specifics of CPB, and details of postoperative complications. Additionally, data on mechanical ventilatory support, vital signs, and the duration of ICU and hospital stays were collected. It has been increasingly recognized that morbidity and mortality in the ICU are due to multiple organ failure (9). Frequently used methods to assess pediatric severity of illness in the pediatric ICUs include the Pediatric Logistic Organ Dysfunction score (PELOD), the Pediatric Risk of Mortality score (PRISM III), and the Pediatric Index of Mortality score (PIM2) (10–13). The comparison of the three scoring systems for mortality prediction demonstrated that the receiver operating characteristic curve (ROC) was 0.98 for PELOD (12), 0.900 for PIM-2 (11) and 0.82 for PRISM3 (9). In addition, PELOD has been used widely in pediatric CHD population (14). Accordingly, we used PELOD in this study to score organ function. PELOD-2 score was manually calculated as previously described (15). We also utilized the Society of Thoracic Surgeons—European Association for Cardio-Thoracic Surgery Congenital Heart Surgery Mortality Categories (STAT Mortality Categories) to examine the risk of morbidity associated with surgical procedures. Postoperative complication was defined as organ dysfunction/injury or thrombosis. We adopted the criteria for organ dysfunction as previously described in pediatric critical illness (16) along with PELOD-2 as described above. Thrombosis was defined as the presence of any vascular thrombosis detected using ultrasound diagnostic imaging.

Blood samples were drawn from patients via existing central venous catheters at two distinct time points: (1) immediately after the induction of anesthesia, serving as the baseline, and (2) upon admission to the ICU. The volume of blood collected at each time point adhered to the guidelines specified in the “Protection of Human Subjects” document, totaling 1.8 ml for both collections (900 µl each). After sample collection, blood was immediately transported to the laboratory for assays. For each time point, 100 µl was used for flow cytometry analysis, and 800 µl was subjected to plasma and neutrophil purification. Flow cytometry analysis and RNA sequencing experiment methods are included in Supplementary document.

Plasma cytokine levels, including TNF-α, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, and IL-13, were measured using V-plex proinflammatory panel 1 human kit (Meso Scale Discovery; Gaithersburg, Maryland), in accordance with the manufacturer's protocol.

For the analysis of clinical data, we utilized IBM SPSS Statistics, Version 30.0 (IBM Corp., NY, USA). Categorical variables were presented as numbers and percentages, while continuous variables were summarized as means and standard deviations for normally distributed variables, or medians and interquartile ranges for skewed distributions. The normality of variables was assessed using the Shapiro–Wilk test. Categorical variables were compared using chi-square test, Fisher exact test, or Kruskal–Wallis test as appropriate. Continuous variables were analyzed using Student's t test or Mann–Whitney U test, depending on their distribution. Logistic regression models were constructed to assess whether the association between myo5c expression (at baseline or ICU admission) and postoperative complications was confounded by clinical variables. Variables with a p-value <0.05 in univariable analysis were included in the models as potential confounders. For correlation analysis, Pearson or Spearman correlation coefficient was determined based on the normality of the data. Laboratory data were analyzed as outlined in the corresponding figure legends. Statistical significance was set at p value < 0.05. All statistical analyses were performed using Prism 10 software (GraphPad Software, La Jolla, CA, USA).

We enrolled 50 patients undergoing congenital cardiac surgery with CPB between May 31, 2022–February 22, 2023. Table 1 presents the demographic data and baseline characteristics of the patient cohort. Median age was 5.8 months with 42% being male.

Among these patients, 16 individuals (32%) developed postoperative complications (Table 2). These complications were predominantly respiratory (n = 10, 20%) and cardiovascular in nature (n = 9, 18%). Notably, eight patients (16%) exhibited multi-system involvement, indicating the complexity of these complications. A significantly higher proportion of patients with complications were in STAT mortality category ≥3 (62.5% vs. 26.5%, p = 0.027). RBC transfusion during CPB were administered to 37.5% of patients in the complication group (6 of 16) and 29.4% in the non-complication group (10 of 34) (p = 0.57). Postoperative lactate levels tended to be higher in patients with complications (4.1 vs. 2.8), with the difference approaching statistical significance (p = 0.055) (Table 2). Additionally, patients with complications had remarkably longer periods of mechanical ventilation (71.0 h vs. 28.0 h, p = 0.013), extended ICU stays (166.0 h vs. 72.0 h, p < 0.0001), and prolonged hospital stays (14.9 days vs. 8.9 days, p = 0.01). These patients exhibited higher PEdiatric Logistic Organ Dysfunction-2 (PELOD-2) scores on postoperative day 2 (4.5 vs. 2.0, p < 0.001), indicating a greater overall severity of organ dysfunction (Table 3).

Neutrophils are the first responders to inflammation/ stress during the perioperative phase, exhibiting an increase in numbers and activation in response to surgical triggers and associated inflammatory stimuli. Given this physiological response, we posited that variations in neutrophil RNA transcription might distinguish patients with postoperative complications from those without. To test this hypothesis, we performed RNA sequencing (RNA-seq) analysis of neutrophils, both at baseline and upon admission to the ICU.

In our RNA-seq analysis, we utilized the Uniform Manifold Approximation and Projection (UMAP) technique to visualize the complex gene expression data in high dimensions. The resulting UMAP plot (Figure 1A) distinctly delineated clusters between the baseline and ICU admission time points, indicating significant alterations in RNA expression patterns attributed to the cardiac surgery and CPB procedure.

The bulk RNA-seq analysis identified a total of 58,622 transcripts. We used criteria of an absolute log₂ fold change >0.58 and a statistically significant adjusted p-value < 0.05 to determine DEGs at ICU admission compared to baseline. The volcano plot illustrated the 749 upregulated and 207 downregulated DEGs (Figure 1B). Further exploration on these DEGs included GO enrichment analysis, primarily focusing on GO Biological Processes (GO-BP). Within the top 20 enriched GO-BP terms associated with upregulated DEGs, we observed notable enrichment in various inflammatory processes, such as apoptotic processes, innate immune responses, and the regulation of nuclear factor-kappa B (NFκB) transcription factor activity (Figure 1C). Conversely, the adaptive immune response appeared to be downregulated in the early postoperative period (Figure 1D). Our KEGG pathway analysis further demonstrated the upregulated DEGs involved several inflammatory signaling pathways and apoptosis, encompassing pathways such as mitogen-activated protein kinase (MAPK), Ras-associated protein-1 (Rap 1), hypoxia-inducible factor (HIF)-1 and tumor necrosis factor (TNF) signaling pathways (Figure 1F). These findings substantiate the presence of robust inflammatory responses in the neutrophils during the early postoperative period following congenital cardiac surgery with CPB.

To delineate the association between neutrophil mRNA expression and postoperative complications, we employed the PELOD-2 score as a surrogate marker for postoperative complications, capitalizing on its well-established correlation with pediatric organ dysfunction and its ability to provide a broader range for a more nuanced understanding of complications (15). Among several candidate genes identified from the RNA sequencing dataset, myo5c was the only transcript that consistently correlated with indicators of postoperative organ dysfunction, including PELOD-2 scores. Although the scores were assessed for both postoperative days 1 and 2, the association with myo5c expression was more pronounced and statistically significant on day 2, which was therefore prioritized in our analysis. Our analysis showed a notable reduction in myo5c expression at a PELOD-2 score on postoperative day 2 of 6, with levels also lower at a score of 7 (Figure 2A). Additionally, we demonstrated a strong negative correlation between myo5c expressions upon ICU admission and PELOD-2 scores on postoperative day 2 (r = −0.6393, p < 0.0001) (Figure 2B). Myo5c expression also negatively correlated with the ICU length of stay (r = −0.3030, p = 0.0325) (Figure 2C). The receiver operating characteristic (ROC) curve showed an acceptable discriminatory ability of myo5c expression upon ICU admission in relation to PELOD-2 score on postoperative day 2 (AUROC = 0.6754, 95% CI 0.56–0.79, p = 0.0025) (Supplementary Figure S2).

We further assessed whether myo5c expression declined after surgery by comparing baseline and ICU admission levels within each group. No significant within-group differences were found in either the complication or non-complication group (Supplementary Figure S3). Additionally, logistic regression models were constructed to assess whether the association between myo5c expression and postoperative complications was confounded by other clinical variables. In all models, only STAT category ≥3 emerged as a significant independent predictor of complications, while myo5c expression was not statistically significant (Supplementary Tables S1, S2).

In addition, we performed subgroup analyses to determine whether myo5c expression was influenced by lesion type or surgical complexity. Patients were stratified by cyanotic vs. acyanotic CHD, as well as by STAT mortality category. No significant differences in myo5c expression were observed between cyanotic and acyanotic groups at either baseline or ICU admission (Supplementary Figure S4). Similarly, no consistent trend was identified across the full range of STAT categories (1–5) (Supplementary Figure S5). In contrast, when patients were grouped by STAT mortality category <3 vs. ≥3, myo5c expression at ICU admission showed a downward trend in the STAT ≥3 group, though this did not reach statistical significance (Supplementary Figure S6).

However, given the limited sample size in higher STAT categories, these results are considered exploratory and require validation in larger, stratified cohort.

To further elucidate the association between myo5c expression and the inflammatory response, we conducted an analysis examining the correlation of myo5c expression levels with various parameters, including cytokine release, neutrophil and platelet activation, as well as neutrophil and platelet counts.

Our analysis revealed a statistically significant negative correlation between myo5c expression and organ injury marker, IL-6 levels upon ICU admission (r = −0.4993, p = 0.0094) (Figure 3). Additionally, elevated myo5c expression was significantly associated with less activation of both neutrophils (at T2, m24 vs. myo5c, r = −0.4284, p + 0.0024) and platelets (at T2, PAC1 vs. myo5c, r = −0.4190, p = 0.0027) (Figure 4A). However, neutrophil and platelet counts did not exhibit a statistically significant correlation (Figure 4B). These findings supported the hypothesis that myo5c potentially play a substantial role in the regulation of systemic inflammatory response following CPB.

The observed downregulation of the neutrophil myo5c gene in patients with elevated PELOD-2 scores suggested its potential involvement in postoperative complications. To determine the functional role of myo5c, we performed its deletion in HL60 cells using CRISPR/Cas9. Our investigation into NET formation in HL60 cells with myo5c knockout phenotypes revealed enhanced NET formation in the absence of myo5cprotein following PMA stimulation (Figure 5), suggesting that myo5c would be a functionally important molecule. This experimental evidence supported our initial hypothesis, strengthening the association between myo5c, systemic inflammation, and NET formation.