Background Congenital heart disease (CHD) is resulted from the interaction of genetic aberration and environmental factors. Imprinted genes, which are regulated by epigenetic modifications, are essential for the normal embryonic development. However, the role of imprinted genes in the etiology of CHD remains unclear. Methods After the samples were treated with bisulfate salt, imprinted genes methylation were measured by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. T test and One-way ANOVA were performed to evaluate the differences among groups. Odds ratios (ORs) were performed to evaluate the incidence risk of CHD in relation to methylation levels. Results We investigated the alterations of imprinted gene germline differential methylation regions (gDMRs) methylation in patients with CHD. Eighteen imprinted genes that are known to affect early embryonic development were selected and the methylation modification genes were detected by massarray in 27 CHD children and 28 healthy children. Altered gDMR methylation level of 8 imprinted genes was found, including 2 imprinted genes with hypermethylation of GRB10 and MEST and 6 genes with hypomethylation of PEG10, NAP1L5, INPP5F, PLAGL1, NESP and MEG3. Stratified analysis showed that the methylation degree of imprinted genes was different in different types of CHD. Risk analysis showed that 6 imprinted genes, except MEST and NAP1L5, within a specific methylation level range were the risk factors for CHD Conclusion Altered methylation of imprinted genes is associated with CHD and varies in different types of CHD. Further experiments are warranted to identify the methylation characteristics of imprinted genes in different types of CHD and clarify the etiologies of imprinted genes in CHD.

Congenital heart disease (CHD) with extracardiac malformations (EM) is the most common multiple malformation, resulting from the interaction between genetic abnormalities and environmental factors. Most studies have attributed the causes of CHD with EM to chromosomal abnormalities. However, multi‐system dysplasia is usually caused by both genetic mutations and epigenetic dysregulation. The epigenetic mechanisms underlying the pathogenesis of CHD with EM remain unclear. In this study, we investigated the mechanisms of imprinting alterations, including those of the Small nuclear ribonucleoprotein polypeptide N (SNRPN), PLAG1 like zinc finger 1 (ZAC1) and inositol polyphosphate‐5‐phosphatase F (INPP5F) genes, in the pathogenesis of CHD with EM. The methylation levels of SNRPN, ZAC1, and INPP5F genes were analysed by the MassARRAY platform in 24 children with CHD with EM and 20 healthy controls. The expression levels of these genes were detected by real‐time polymerase chain reaction (PCR). The correlation between methylation regulation and gene expression was confirmed using 5‐azacytidine (5‐Aza) treated cells. The methylation levels of SNRPN and ZAC1 genes were significantly increased in CHD with EM, while that of INPP5F was decreased. The methylation alterations of these genes were negatively correlated with expression. Risk analysis showed that abnormal hypermethylation of SNRPN and ZAC1 resulted in 5.545 and 7.438 times higher risks of CHD with EM, respectively, and the abnormal hypomethylation of INPP5F was 8.38 times higher than that of the control group. We concluded that abnormally high methylation levels of SNRPN and ZAC1 and decreased levels of INPP5F imply an increased risk of CHD with EM by altering their gene functions. This study provides evidence of imprinted regulation in the pathogenesis of multiple malformations.

No abstract

Background: Congenital heart disease (CHD) is resulted from the interaction of genetic aberration and environmental factors. Imprinted genes, which are regulated by epigenetic modifications, are essential for the normal embryonic development. However, the role of imprinted genes in the etiology of CHD remains unclear. Results: We investigated the alterations of imprinted gene germline differential methylation regions (gDMRs) methylation in patients with CHD. Eighteen imprinted genes that are known to affect early embryonic development were selected and the methylation modification genes were detected by massarray in 27 CHD children and 28 healthy children. Altered gDMR methylation level of 8 imprinted genes was found, including 2 imprinted genes with hypermethylation of GRB10 and MEST and 6 genes with hypomethylation of PEG10, NAP1L5, INPP5F, PLAGL1, NESP and MEG3. Stratified analysis showed that the methylation degree of imprinted genes was different in different types of CHD. Risk analysis showed that 6 imprinted genes, except MEST and NAP1L5, within a specific methylation level range were the risk factors for CHDConclusion: Altered methylation of imprinted genes is associated with CHD and varies in different types of CHD. Further experiments are warranted to identify the methylation characteristics of imprinted genes in different types of CHD and clarify the etiologies of imprinted genes in CHD.

Background：Prolonged mechanical ventilation in children undergoing cardiac surgery is related to the decrease of cardiac output during the postoperative intense care time, which often induced serious complications. Pressure Recording Analytical Method (PRAM) is a minimally invasive system for continuous hemodynamic monitoring, which can timely record the presence of lower cardiac function. This study is aimed to evaluate the predictive value of the several hemodynamic parameters for the duration of mechanical ventilation (DMV).Methods：This retrospective study included 60 children under 1-year-old who underwent cardiac surgery between 2017 and 2021. CI, CCE and dp/dt max derived from PRAM was documented in each patient 0, 4, 8 and 12 hours (T0, T1,T2, T3 and T4 respectively) after admission to the intensive care unit (ICU). A linear mixed model were used to deal with the repeated measurement on hemodynamic data. Correlation analysis and Receiver operating characteristic (ROC) curves were used to show the predictive value. XGBoost machine learning-based mode which produces a decision tree-heat map was used to find the key characteristics of the data in predicting the outcome. Results：There were 35(58%) children in DMV≤24 h group and 25(42%) were in DMV>24h. Prolonged DMV caused longer ICU stays and postoperative hospital stays. Linear mixed model revealed significant time and group effect in CI and dp/dt max. Prolonged DMV also have negative correlations with age, weight, CI at T2 and dp/dt max at T2. dp/dt max outweighing CI were the strongest predictors of prolonged DMV(AUC of ROC: 0.978 vs 0.811, respectively, p<0.01). The XGboost based learning machine model (Balance Accuracy=0.92, AUC of ROC=0.856) suggested that dp/dt max at T2 ≤1.049 or >1.049 in combination with CI at T0 ≤2 or > 2 can predict prolonged DMV.Conclusions：Hemodynamic monitoring in infants with PRAM after the cardiac surgery shows that the cardiac function can predict the prolonged duration of mechanical ventilation. CI measured by PRAM immediately after ICU admission and dp/dt max that 8h later are 2 key factors in predicting prolonged DMV with the application of XGboost based machine learning model.