Fetal Congenital Heart Disease Research Articles

Delivery room and early postnatal management of neonates with congenital heart disease.

Advancements in prenatal detection have improved postnatal outcomes for patients with congenital heart disease (CHD). Detailed diagnosis during pregnancy allows for preparation for the delivery and immediate postnatal care for the newborns with CHD. Most CHDs do not result in hemodynamic instability at the time of birth and can be stabilized following the guidelines of the neonatal resuscitation program (NRP). Critical CHD that requires intervention immediately after birth is recommended to be delivered in facilities where immediate neonatal and cardiology care can be provided. Postnatal stabilization and resuscitation for these defects warrant deviation from the standardized NRP. For neonatal providers, knowing the diagnosis of fetal CHD allows for preparation for the anticipated instability in the delivery room. Prenatal detection fosters collaboration between fetal cardiology, cardiology specialists, obstetrics, and neonatology, improving outcomes for neonates with critical CHD.

Interaction between clinicians and artificial intelligence to detect fetal atrioventricular septal defects on ultrasound: how can we optimize collaborative performance?

Artificial intelligence (AI) has shown promise in improving the performance of fetal ultrasound screening in detecting congenital heart disease (CHD). The effect of giving AI advice to human operators has not been studied in this context. Giving additional information about AI model workings, such as confidence scores for AI predictions, may be a way of further improving performance. Our aims were to investigate whether AI advice improved overall diagnostic accuracy (using a single CHD lesion as an exemplar), and to determine what, if any, additional information given to clinicians optimized the overall performance of the clinician-AI team. An AI model was trained to classify a single fetal CHD lesion (atrioventricular septal defect (AVSD)), using a retrospective cohort of 121 130 cardiac four-chamber images extracted from 173 ultrasound scan videos (98 with normal hearts, 75 with AVSD); a ResNet50 model architecture was used. Temperature scaling of model prediction probability was performed on a validation set, and gradient-weighted class activation maps (grad-CAMs) produced. Ten clinicians (two consultant fetal cardiologists, three trainees in pediatric cardiology and five fetal cardiac sonographers) were recruited from a center of fetal cardiology to participate. Each participant was shown 2000 fetal four-chamber images in a random order (1000 normal and 1000 AVSD). The dataset comprised 500 images, each shown in four conditions: (1) image alone without AI output; (2) image with binary AI classification; (3) image with AI model confidence; and (4) image with grad-CAM image overlays. The clinicians were asked to classify each image as normal or AVSD. A total of 20 000 image classifications were recorded from 10 clinicians. The AI model alone achieved an accuracy of 0.798 (95% CI, 0.760-0.832), a sensitivity of 0.868 (95% CI, 0.834-0.902) and a specificity of 0.728 (95% CI, 0.702-0.754), and the clinicians without AI achieved an accuracy of 0.844 (95% CI, 0.834-0.854), a sensitivity of 0.827 (95% CI, 0.795-0.858) and a specificity of 0.861 (95% CI, 0.828-0.895). Showing a binary (normal or AVSD) AI model output resulted in significant improvement in accuracy to 0.865 (P < 0.001). This effect was seen in both experienced and less-experienced participants. Giving incorrect AI advice resulted in a significant deterioration in overall accuracy, from 0.761 to 0.693 (P < 0.001), which was driven by an increase in both Type-I and Type-II errors by the clinicians. This effect was worsened by showing model confidence (accuracy, 0.649; P < 0.001) or grad-CAM (accuracy, 0.644; P < 0.001). AI has the potential to improve performance when used in collaboration with clinicians, even if the model performance does not reach expert level. Giving additional information about model workings such as model confidence and class activation map image overlays did not improve overall performance, and actually worsened performance for images for which the AI model was incorrect. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Comparison of Different Ultrasonic Screening Methods and Analysis of High Risk Factors for Fetal Cardiac Malformation in Second Trimester of Pregnancy.

Current study aims to compare the application of two-dimensional (2D) color doppler ultrasound (CDU) and four-dimensional (4D) ultrasound spatiotemporal image correlation (STIC) in fetal congenital heart disease in the second trimester of pregnancy and to analyze the high risk factors of the disease. From August 2019 to July 2021, 135 second-trimester patients with highly suspected congenital heart malformations were selected who underwent prenatal screening at South Taihu Hospital Affiliated to Huzhou University. 2D-CDU, 4D STIC, and postnatal examination were completed in all patients. 2D-CDU, 4D STIC and 2D-CDU combined with 4D STIC were used to detect fetal cardiac malformations and classify cardiac malformations. The sensitivity, specificity, positive predictive value, negative predictive value and coincidence rate of 2D-CDU, 4D STIC and 2D-CDU combined with 4D STIC were compared. The results of 2D-CDU, 4D STIC and 2D-CDU combined with 4D STIC screening were analyzed for consistency using the results of postpartum diagnosis as the gold standard. Moreover, effects of maternal gestational factors on fetal cardiac malformations by univariate and multivariate analysis. 2D-CDU combined with 4D STIC showed significantly higher section display number than 2D-CDU or 4D STIC in the view of ductal arch, aortic arch, and aortic short-axis. A total of 45 cases of fetal congenital heart malformation were detected in 135 patients in the second trimester, 40, 38 or 42 cases were detected by 2D-CDU, 4D STIC or 2D-CDU combined with 4D STIC, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and coincidence rate of 2D-CDU combined with 4D ultrasound in congenital heart malformation screening were higher than those of 2D-CDU or 4D STIC. Kappa agreement analysis showed that the diagnostic results of 4D STIC and 2D-CDU combined with 4D ultrasound in fetuses with suspected congenital heart malformation were in excellent agreement (κ > 0.75), while 2D-CDU was in good agreement with postpartum diagnosis (κ < 0.75). Univariate and multivariate regression analysis revealed that maternal age ≥ 35, drinking during pregnancy, and history of adverse pregnancy and childbirth were all independent risk factors for fetal cardiac malformations, while folic acid supplementation was an independent protective factor for fetal cardiac malformations. 2D-CDU combined with 4D echocardiography may be superior to single 2D-CDU or 4D STIC in the screening of fetal congenital heart malformation in the second trimester. In order to reduce the incidence of fetal heart anomalies, we should strengthen the screening of pregnancy anomalies in high-risk pregnant women and control the risk factors.

Is there an increased risk of genetic abnormalities in fetuses with congenital heart disease in the setting of growth restriction?

To determine if the presence of fetal growth restriction (FGR) is associated with an increased risk of genetic abnormalities in the setting of congenital heart disease (CHD). This was a retrospective cohort study involving pregnancies that met the following criteria: (i) prenatal diagnosis of CHD, (ii) singleton live-birth, and (iii) genetic testing was performed either pre- or postnatally. Genetic results were reviewed by a clinical geneticist for updated variant classification. Fetal growth was stratified as appropriate for gestational age (AGA) or FGR. Of the total of 445 fetuses that met the study criteria, 325 (73.0%) were AGA and 120 (27.0%) were FGR. Genetic abnormalities were detected in 131 (29.4%) pregnancies. There was a higher rate of genetic abnormalities (36.7% vs. 26.8%, p=0.04), which was driven by aneuploidies (20.8% vs. 8.9%, p=0.0006) in the FGR population. Early onset growth restriction was associated with a higher rate of genetic abnormalities (44.5% vs. 25.9%, p=0.03). The rate of genetic abnormalities was significantly higher in the shunt category as compared to remainder of the cardiac anomalies (62.5% in shunt lesions vs. 24.7%, p<0.00001). The rates of FGR (40.9% vs. 21.4%, p<0.0001) and genetic abnormalities (52% vs. 20.4%, p<0.0001) were significantly higher in the presence of extra-cardiac anomalies (ECA). The presence of FGR in fetal CHD population was associated with underlying genetic abnormalities, specifically aneuploidies. Patients should be appropriately counseled regarding the higher likelihood of a genetic condition in the presence of FGR, early onset FGR, shunt lesions and ECA.

Efficiency of copy number variation sequencing combined with karyotyping in fetuses with congenital heart disease and the following outcomes

BackgroundBoth copy number variant-sequencing (CNV-seq) and karyotype analysis have been used as powerful tools in the genetic aetiology of fetuses with congenital heart diseases (CHD). However, CNV-seq brings clinicians more confusions to interpret the detection results related to CHD with or without extracardiac abnormalities. Hence, we conducted this study to investigate the clinical value of CNV-seq in fetuses with CHD.ResultsA total of 167 patients with fetal CHD including 36 single CHD (sCHD), 41 compound CHD (cCHD) and 90 non-isolated CHD (niCHD) were recruited into the study. 28 cases (16.77%, 28/167) were revealed with chromosomal abnormalities at the level of karyotype. The pathogenic detection rate (DR) of CNV-seq (23.17%, 19/82) was higher than that of karyotyping (15.85%, 13/82) in 82 cases by CNV-seq and karyotyping simultaneously. The DR of pathogenic copy number variations (PCNVs) (31.43%) was higher in niCHD subgroup than that in sCHD and cCHD (9.52% and 23.08%). Conotruncal defect (CTD) was one of the most common heart malformations with the highest DR of PCNVs (50%) in 7 categories of CHD. In terms of all the pregnancy outcomes, 67 (40.12%) cases were terminated and 100 (59.88%) cases were live neonates. Only two among 34 cases with a pathogenic genetic result chose to continue the pregnancy.ConclusionsCNV-seq combined with karyotyping is a reliable and accurate prenatal technique for identifying pathogenic chromosomal abnormalities associated with fetal CHD with or without extracardiac abnormalities, which can assist clinicians to perform detailed genetic counselling with regard to the etiology and related outcomes of CHD.

Interdependence of placenta and fetal cardiac development.

The placenta and fetal heart undergo development concurrently during early pregnancy, and, while human studies have reported associations between placental abnormalities and congenital heart disease (CHD), the nature of this relationship remains incompletely understood. Evidence from animal studies suggests a plausible cause and effect connection between placental abnormalities and fetal CHD. Biomechanical models demonstrate the influence of mechanical forces on cardiac development, whereas genetic models highlight the role of confined placental mutations that can cause some forms of CHD. Similar definitive studies in humans are lacking; however, placental pathologies such as maternal and fetal vascular malperfusion and chronic deciduitis are frequently observed in pregnancies complicated by CHD. Moreover, maternal conditions such as diabetes and pre-eclampsia, which affect placental function, are associated with increased risk of CHD in offspring. Bridging the gap between animal models and human studies is crucial to understanding how placental abnormalities may contribute to human fetal CHD. The next steps will require new methodologies and multidisciplinary approaches combining innovative imaging modalities, comprehensive genomic testing, and histopathology. These studies may eventually lead to preventative strategies for some forms of CHD by targeting placental influences on fetal heart development.

The combination of deep learning and pseudo-MS image improves the applicability of metabolomics to congenital heart defect prenatal screening

To investigate the metabolic alterations in maternal individuals with fetal congenital heart disease (FCHD), establish the FCHD diagnostic models, and assess the performance of these models, we recruited two batches of pregnant women. By metabolomics analysis using Ultra High-performance Liquid Chromatography-Mass/Mass (UPLC-MS/MS), a total of 36 significantly altered metabolites (VIP >1.0) were identified between FCHD and non-FCHD groups. Two logistic regression models and four support vector machine (SVM) models exhibited strong performance and clinical utility in the training set (area under the curve (AUC) = 1.00). The convolutional neural network (CNN) model also demonstrated commendable performance and clinical utility (AUC = 0.89 in the training set). Notably, in the validation set, the performance of the CNN model (AUC = 0.66, precision = 0.714) exhibited better robustness than the six models above (AUC≤0.50). In conclusion, the CNN model based on pseudo-MS images holds promise for real-world and clinical applications due to its better repeatability.

Association of maternal weight gain in early pregnancy with congenital heart disease in offspring: a China birth cohort study

ObjectivesLittle study has reported the association of maternal weight gain in early pregnancy with fetal congenital heart disease (CHD). We aimed to explore the potential relationship based on a China...

Placental Pathology Contributes to Impaired Volumetric Brain Development in Neonates With Congenital Heart Disease.

Neonates with congenital heart disease are at risk for impaired brain development in utero, predisposing children to postnatal brain injury and adverse long-term neurodevelopmental outcomes. Given the vital role of the placenta in fetal growth, we assessed the incidence of placental pathology in fetal congenital heart disease and explored its association with total and regional brain volumes, gyrification, and brain injury after birth. Placentas from 96 term singleton pregnancies with severe fetal congenital heart disease were prospectively analyzed for macroscopic and microscopic pathology. We applied a placental pathology severity score to relate placental abnormalities to neurological outcome. Postnatal, presurgical magnetic resonance imaging was used to analyze brain volumes, gyrification, and brain injuries. Placental analyses revealed the following abnormalities: maternal vascular malperfusion lesions in 46%, nucleated red blood cells in 37%, chronic inflammatory lesions in 35%, delayed maturation in 30%, and placental weight below the 10th percentile in 28%. Severity of placental pathology was negatively correlated with cortical gray matter, deep gray matter, brainstem, cerebellar, and total brain volumes (r=-0.25 to -0.31, all P<0.05). When correcting for postmenstrual age at magnetic resonance imaging in linear regression, this association remained significant for cortical gray matter, cerebellar, and total brain volume (adjusted R2=0.25-0.47, all P<0.05). Placental pathology occurs frequently in neonates with severe congenital heart disease and may contribute to impaired brain development, indicated by the association between placental pathology severity and reductions in postnatal cortical, cerebellar, and total brain volumes.

Universal Fetal Echocardiography for Pregestational Diabetes Mellitus: A Cost-Effectiveness Analysis.

To evaluate the cost effectiveness of universal fetal echocardiogram for patients with pregestational diabetes mellitus by first-trimester hemoglobin A1c (Hb A1c) level. We developed a cost-effectiveness model comparing two strategies of screening for critical fetal congenital heart disease among patients with diabetes: universal fetal echocardiogram and fetal echocardiogram only after abnormal findings on detailed anatomy ultrasonogram. We excluded ventricular septal defect, atrial septal defects, and bicuspid aortic valve from the definition of critical fetal congenital heart disease. Probabilities and costs were derived from the literature. We used individual models to evaluate different scenarios: first-trimester Hb A1c lower than 6.5%, Hb A1c 6.5-9.0%, and Hb A1c higher than 9.0%. Primary outcomes included fetal death, neonatal death, and false-positive and false-negative results. A cost-effectiveness threshold was set at $100,000 per quality-adjusted life-year. Univariable sensitivity analyses were performed to investigate the drivers of the model. Universal fetal echocardiogram is not cost effective except for when first-trimester Hb A1c level is higher than 9.0% (incremental cost-effectiveness ratio $638,100, $223,693, and $67,697 for Hb A1c lower than 6.5%, 6.5-9.0%, and higher than 9.0%, respectively). The models are sensitive to changes in the probability of congenital heart disease at a given Hb A1c level, as well as the cost of neonatal transfer to a higher level of care. Universal fetal echocardiogram became both cost saving and more effective when the probability of congenital heart disease reached 14.48% (15.4 times the baseline risk). In the Monte Carlo simulation, universal fetal echocardiogram is cost effective in 22.7%, 48.6%, and 62.3% of scenarios for each of the three models, respectively. For pregnant patients with first-trimester Hb A1c levels lower than 6.5%, universal fetal echocardiogram was not cost effective, whereas, for those with first-trimester Hb A1c levels higher than 9.0%, universal fetal echocardiogram was cost effective. For those with intermediate Hb A1c levels, universal fetal echocardiogram was cost effective in about 50% of cases; therefore, clinical judgment based on individual patient values, willingness to pay to detect congenital heart disease, and resource availability needs to be considered.

SPReCHD: Four-Chamber Semantic Parsing Network for Recognizing Fetal Congenital Heart Disease in Medical Metaverse.

Echocardiography is essential for evaluating cardiac anatomy and function during early recognition and screening for congenital heart disease (CHD), a widespread and complex congenital malformation. However, fetal CHD recognition still faces many difficulties due to instinctive fetal movements, artifacts in ultrasound images, and distinctive fetal cardiac structures. These factors hinder capturing robust and discriminative representations from ultrasound images, resulting in CHD's low prenatal detection rate. Hence, we propose a multi-scale gated axial-transformer network (MSGATNet) to capture fetal four-chamber semantic information. Then, we propose a SPReCHD: four-chamber semantic parsing network for recognizing fetal CHD in the clinical treatment of the medical metaverse, integrating MSGATNet to segment and locate four-chamber arbitrary contours, further capturing distinguished representations for the fetal heart. Comprehensive experiments indicate that our SPReCHD is sufficient in recognizing fetal CHD, achieving a precision of 95.92%, a recall of 94%, an accuracy of 95%, and a F1 score of 94.95% on the test set, dramatically improving the fetal CHD's prenatal detection rate.

884 Influence of growth restriction on perinatal outcomes in singleton pregnancies with fetal congenital heart disease

884 Influence of growth restriction on perinatal outcomes in singleton pregnancies with fetal congenital heart disease

Correlação de Imagem Espaço-Temporal: Imagens Tridimensionais para Triagem Cardíaca Fetal e Avaliação de Doenças Cardíacas Congênitas

Correlação de Imagem Espaço-Temporal: Imagens Tridimensionais para Triagem Cardíaca Fetal e Avaliação de Doenças Cardíacas Congênitas

Spatio-Temporal Image Correlation: Three-Dimensional Imaging for Fetal Cardiac Screening and Congenital Heart Disease Assessment.

Spatio-Temporal Image Correlation: Three-Dimensional Imaging for Fetal Cardiac Screening and Congenital Heart Disease Assessment.

SKGC: A General Semantic-level Knowledge Guided Classification Framework for Fetal Congenital Heart Disease.

Congenital heart disease (CHD) is the most common congenital disability affecting healthy development and growth, even resulting in pregnancy termination or fetal death. Recently, deep learning techniques have made remarkable progress to assist in diagnosing CHD. One very popular method is directly classifying fetal ultrasound images, recognized as abnormal and normal, which tends to focus more on global features and neglects semantic knowledge of anatomical structures. The other approach is segmentation-based diagnosis, which requires a large number of pixel-level annotation masks for training. However, the detailed pixel-level segmentation annotation is costly or even unavailable. Based on the above analysis, we propose SKGC, a universal framework to identify normal or abnormal four-chamber heart (4CH) images, guided by a few annotation masks, while improving accuracy remarkably. SKGC consists of a semantic-level knowledge extraction module (SKEM), a multi-knowledge fusion module (MFM), and a classification module (CM). SKEM is responsible for obtaining high-level semantic knowledge, serving as an abstract representation of the anatomical structures that obstetricians focus on. MFM is a lightweight but efficient module that fuses semantic-level knowledge with the original specific knowledge in ultrasound images. CM classifies the fused knowledge and can be replaced by any advanced classifier. Moreover, we design a new loss function that enhances the constraint between the foreground and background predictions, improving the quality of the semantic-level knowledge. Experimental results on the collected real-world NA-4CH and the publicly FEST datasets show that SKGC achieves impressive performance with the best accuracy of 99.68% and 95.40%, respectively. Notably, the accuracy improves from 74.68% to 88.14% using only 10 labeled masks.

Incidence of congenital heart disease in fetuses diagnosed with single isolated umbilical artery. Systematic review and meta-analysis.

To estimate the proportion of heart disease in fetuses with a prenatal diagnosis of a single isolated umbilical artery. We performed a search strategy in MEDLINE (OVID), EMBASE, and the Cochrane Central Register of Controlled Trials (CENTRAL) from inception to the present. We assessed the risk of bias and performed a meta-analysis. We completed the subgroup analysis according to the region. We found 1384 studies by the search strategy. After carefully reviewing the full-text, 15 studies were included. A total of 2008 fetuses with a single isolated umbilical artery were included, and 177 had cardiac malformations. There was an overall incidence of 9% 95%CI (0.05-0.14) I2 90%. The incidence by country of origin was between 5% and 19%. The most common heart disease reported was a ventricular septal defect. Seven studies were found describing 25 cases. We described other malformations, such as tetralogy of Fallot, coarctation of the aorta, and hypoplastic left ventricle, among others. The incidence of congenital heart disease in fetuses with a single isolated umbilical artery was high. In addition, half of these correspond to significant heart disease. Based on the above, we suggest that fetuses with a single isolated umbilical artery should have a complete anatomic evaluation emphasizing cardiac evaluation.

Association between abnormal uterine artery pulsatility index and the risk of fetal congenital heart defects: a hospital-based cohort study

To explore the associations between high uterine artery pulsatility index (UtA-PI) values and congenital heart disease (CHD) risk and whether they differed between singleton and multiple pregnancies. This hospital-based cohort study involving 52,047 pregnant women who underwent prenatal examinations from 2012 to 2016. Infants born to the included pregnant women were followed until 42 days after birth to identify those with CHDs. Generalized estimating equations were used to estimate the associations of high right UtA-PI (> 95th percentile) values with maternal preeclampsia and fetal CHDs. Logistic regression analyses were conducted using path analysis models to quantify the effect of high right UtA-PI values on fetal CHD risk. A total of 42,552 women and 43,470 infants (147 with CHDs) were included. Preeclampsia risk was associated with a high right UtA-PI in singleton-pregnant women (adjusted PR, 3.01; 95% CI 2.57–3.52). CHD risk was marginally associated with a high right UtA-PI in singleton-pregnant women (adjusted PR, 2.26, 95% CI 1.03–4.95). Considering only two factors, 96.0% of the fetal CHD risk was mediated by preeclampsia in singleton-pregnant women, while 93.8% of the risk was related to a high right UtA-PI in multiple-pregnant women. A high right UtA-PI was marginally associated with an increased fetal CHD risk in singleton-pregnant women and might play an important role in multiple-pregnant women. Further studies are warranted to confirm these findings given the high loss to follow-up rate.

Incidence, distribution, disease spectrum, and genetic deficits of congenital heart defects in China: implementation of prenatal ultrasound screening identified 18,171 affected fetuses from 2,452,249 pregnancies

BackgroundCongenital heart defects (CHDs) are the most common birth defects. Assessment of the incidence, distribution, disease spectrum, and genetic deficits of fetal CHDs in China is urgently needed.MethodsA national echocardiography screening program for fetal CHDs was implemented in 92 prenatal screening–diagnostic centers in China.FindingsA total of 18,171 fetal CHD cases were identified from 2,452,249 pregnancies, resulting in 7·4/1,000 as the national incidence rate of fetal CHD. The incidences of fetal CHD in the six geographical regions, the southern, central, eastern, southwestern, northern, and northwestern, were 7·647 (CI: 7·383–7·915), 7·839 (CI: 7·680–8·000), 7·647 (CI: 7·383–7·915), 7·562 (CI: 7·225–7·907), 5·618 (CI: 5·337–5·906), and 4·716 (CI: 4·341–5·108), respectively, per 1,000 pregnancies. Overall, ventricular septal defect was the most common fetal CHD, accounting for 17.04% of screened pregnancies nationwide, and tetralogy of Fallot, the most common anomaly in the major defect of fetal CHD, was the second most common, accounting for 9.72%. A total of 76.24% cases of fetal CHD were found to be an isolated intracardiac single defect. The remaining 23.76% of cases of fetal CHD had multiple heart defects. Among all extracardiac malformations, the central nervous system (CNS) was the most common tissue with extracardiac anomalies associated with CHD, accounting for 22.89% of fetal CHD cases. Chromosomal karyotyping identified trisomy 18 as the most common chromosomal abnormality in fetal CHD. We also documented that CHD-containing syndromes could be identified with a comprehensive approach integrating prenatal ultrasound, MRI, pathological autopsy, and cytogenetics and molecular genetics.ConclusionImplementation of prenatal echocardiography as a practically feasible platform to screen fetal CHD will reduce the financial and emotional burden of CHD, which may facilitate intrauterine and neonatal intervention of CHD.

The comprehensive study on the role of POSTN in fetal congenital heart disease and clinical applications

BackgroundCongenital heart defect (CHD) is the most common congenital abnormality, and it has long been a clinical and public health concern. Our previous findings have found Periostin (POSTN) and Pappalysin-1 (PAPPA) as potential biomarkers for fetal CHD. We aim to further elucidate POSTN's role in fetal heart development and explore the clinical applicability of POSTN and PAPPA as diagnostic marker for fetal CHD. This study is poised to establish a theoretical framework for mitigating the incidence of CHD and advance a novel approach for prenatal screening of fetal CHD.MethodsWe verified differential expression of POSTN and PAPPA in gravida serum and fetal amniotic fluid based on our previous research. We established the Postn knockout mouse by CRISPR/Cas9 to investigate whether Postn deletion leads to cardiac abnormalities in mice. Besides, we explored the mechanism of POSTN on heart development through Postn knockout mouse model and cell experiments. Finally, we established the logistic regression model and decision curve analysis to evaluate the clinical utility of POSTN and PAPPA in fetal CHD.ResultsWe observed a significant decrease in POSTN and increase in PAPPA in the CHD group. Atrial septal defects occurred in Postn−/− and Postn± C57BL/6 fetal heart, while ventricular septal defects with aortic saddle were observed in Postn± C57BL/6 fetal heart. Disruption of the extracellular matrix (ECM) in cardiomyocytes and multiple abnormalities in cellular sub-organelles were observed in Postn knockout mice. POSTN may positively regulate cell behaviors and unsettle ECM via the TGFβ-Smad2/3 signaling pathway. The combination of serum biomarkers POSTN and PAPPA with Echocardiogram can enhance the diagnostic accuracy of CHD. Furthermore, the comprehensive model including POSTN, PAPPA, and two clinical indicators (NT and age) exhibits significantly higher predictive ability than the diagnosis group without the use of serum biomarkers or clinical indicators.ConclusionsIt is the first evidence that Postn deletion leads to cardiac developmental abnormalities in fetal mice. This may involve the regulation of the TGFβ signaling pathway. Importantly, POSTN and PAPPA possess clinical utility as noninvasive prenatal promising screening indicators of CHD.

Exposure to volatile organic compounds induces cardiovascular toxicity that may involve DNA methylation

Volatile organic compounds (VOCs) are common air pollutants and water contaminants. We previously found maternal exposure to VOCs was associated with offspring congenital heart disease (CHD). However, little information is available about the effects of VOCs on cardiovascular development at embryonic stage and the underlying mechanism remains unclear. In this study, we aimed to investigate the effects of a mixture of six VOCs on cardiovascular development in zebrafish embryos. Embryos were exposed to different concentrations of VOCs mixture (32 mg/L, 64 mg/L and 128 mg/L) for 96 h, cardiovascular abnormalities including elongated heart shape, increased distance between sinus venosus and bulbus arteriosus, slowed circulation and altered heart rate were observed in a dose- and time-dependent manner. Meanwhile, VOCs exposure increased global DNA methylation levels in embryos. Analysis identified hundreds of differentially methylated sites and the enrichment of differentially methylated sites on cardiovascular development. Two differentially methylated-associated genes involved in MAPK pathway, hgfa and ntrk1, were identified to be the potential genes mediating the effects of VOCs. By enzyme-linked immunosorbent assay, altered human serum hgf and ntrk1 levels were detected in abnormal pregnancies exposed to higher VOCs levels with fetal CHD. For the first time, our study revealed exposure to VOCs induced severe cardiovascular abnormalities in zebrafish embryos. The toxicity might result from alterations in DNA methylation and corresponding expression levels of genes involved in MAPK pathway. Our study provides important information for the risk of VOCs exposure on embryonic cardiovascular development.