Parental non-hereditary teratogenic exposure factors on the occurrence of congenital heart disease in the offspring in the northeastern Sichuan, China

Maternal Exposure to Extreme Cold Events and Risk of Congenital Heart Defects: A Large Multicenter Study in China

Over the past decade, extreme temperature events have become more frequent and longer in duration. Previous studies on the association between extreme cold events (ECEs) and congenital heart defects (CHDs) are few and inconsistent. We conducted a national multicenter study in 1313 hospitals in 26 provinces in China and collected a total of 14 808 high CHD-risk participants from 2013 to 2021. We evaluated the ECEs experienced by each pregnant women during the embryonic period (3-8 weeks). The results indicated that ECEs experienced by pregnant women during the embryonic period were associated with the development of fetal CHD and were more strongly associated with some specific fetal CHD subtypes, such as pulmonary stenosis, pulmonary atresia, and tetralogy of Fallot. Of the CHD burden, 2.21% (95% CI: 1.43, 2.99%)-2.40% (95% CI: 1.26, 3.55%) of fetal CHD cases were attributable to ECEs during the embryonic period. Our findings emphasize the need to pay more attention to pregnant women whose embryonic period falls during the cold season to reduce cold spell detriments to newborns.

Maternal Serum tRNA-Derived Fragments (tRFs) as Potential Candidates for Diagnosis of Fetal Congenital Heart Disease

BACKGROUND

Congenital heart disease (CHD) is one of the most predominant birth defects that causes infant death worldwide. The timely and successful surgical treatment of CHD on newborns after delivery requires accurate detection and reliable diagnosis during pregnancy. However, there are no biomarkers that can serve as an early diagnostic factor for CHD patients. tRNA-derived fragments (tRFs) have been reported to play an important role in the occurrence and progression of numerous diseases, but their roles in CHD remains unknown.

METHODS

High-throughput sequencing was performed on the peripheral blood of pregnant women with an abnormal fetal heart and a normal fetal heart, and 728 differentially expressed tRFs/tiRNAs were identified, among which the top 18 tRFs/tiRNAs were selected as predictive biomarkers of CHD. Then, a quantitative reverse transcriptase polymerase chain reaction verified the expression of tRFs/tiRNAs in more clinical samples, and the correlation between tRFs/tiRNAs abnormalities and CHD was analyzed.

RESULTS

tRF-58:74-Gly-GCC-1 and tiRNA-1:35-Leu-CAG-1-M2 may be promising biomarkers. Through further bioinformatics analysis, we predicted that TRF-58:744-GLy-GCC-1 could induce CHD by influencing biological metabolic processes.

CONCLUSIONS

Our results provide a theoretical basis for the abnormally expressed tRF-58:74-Gly-GCC-1 in maternal peripheral blood as a new potential biomarker for the accurate diagnosis of CHD during pregnancy.

A predictive model of offspring congenital heart disease based on maternal risk factors during pregnancy: a hospital based case-control study in Nanchong City

Objective: Based on epidemiological field data, this study was to develop a prediction model which can be used as a preliminary screening tool to identify pregnant women who were at high risk of offspring congenital heart disease (CHD) in Nanchong City, and be beneficial in guiding prenatal management and prevention. Methods: A total of 367 children with CHD and 367 children without congenital malformations aged 0 to 14 years old were recruited from the Affiliated Hospital of North Sichuan Medical College and Nanchong Central Hospital between March 2016 and November 2018. Using the SPSS 22.0 case-control matching module, the controls were matched to the cases at a rate of 1:1, according to the same gestational age of child (premature delivery or full-term), the maternal age of pregnancy (less than 1 year). 327 matched case-control pairs were analyzed by SPSS 22. Univariate and multivariate analysis were performed to find the important maternal influencing factors of offspring CHD. A logistic regression disease prediction model was constructed as the final predictors, and Hosmer-Lemeshow goodness of fit test and receiver operating characteristic (ROC) curve were used to evaluate the model. Results: 654 subjects (327 cases and 327 controls) were matched. The 25 variables were analysed. The logistic regression model established in this study was as follows: Logit(P)= -2.871+(0.686×respiratory infections)+(1.176×water pollution)+(1.019×adverse emotions during pregnancy) - (0.617×nutrition supplementation). The Hosmer-Lemeshow chi-square value was 7.208 (df = 6), with a nonsignificant p value of 0.302, which indicates that the model was well-fitted. The calibration plot showed good agreement between the bias-corrected prediction and the ideal reference line. Area under the ROC curve was 0.72 (95% CI: 0.681~0.759), which means that the predictive power of the model set fitted the data. Conclusion: In Nanchong city, more attention should be paid to mother who had a history of respiratory infections, exposure to polluted water, adverse emotions during pregnancy and nutritional deficiency. The risk model might be an effective tool for predicting of the risk of CHD in offspring by maternal experience during pregnancy, which can be used for clinical practise in Nanchong area.