Accumulating evidence suggests that environmental pollutants may contribute to the occurrence of congenital heart defects (CHDs). However, no previous studies have evaluated the impact of perfluoroalkyl substances (PFAS), persistent environmental pollutants, on CHDs. This exploratory study aimed to generate testable hypotheses of the association between gestational PFAS and the risk of CHDs. A nested case-control study was conducted in a cohort of 11,578 newborns. Exposure odds ratios were compared between 158 CHD cases and 158 non-malformed controls delivered at the same hospital, individually matched by maternal age (±5 years) and parity. Concentrations of 27 PFAS, including linear and branched isomers, were determined in maternal peripheral blood and cord blood plasma collected before and during delivery using a ultra-performance liquid chromatography coupled to mass spectrometry. Conditional logistic regression was utilized to evaluate associations between individual PFAS and the risk of CHDs, adjusted for confounding variables. Maternal gestational exposure to the highly branched perfluorooctanesulfonate (PFOS) isomer potassium 6-trifluoromethyperfluoroheptanesulfonate [6 m-PFOS, adjusted odds ratio (aOR) (95% CI) = 2.47(1.05,5.83)] and perfluorodecanoic acid [PFDA, aOR (95% CI) = 2.33(1.00,5.45)] were associated with increased odds of septal defects with statistical significance, while linear PFOS [aOR (95% CI) = 3.65(1.09,12.16)] and perfluoro-n-dodecanoic acid [PFDoA, aOR (95% CI) = 6.82(1.75, 26.61)] were associated with conotruncal defects. Effect estimates also suggested associations for higher maternal 6 m-PFOS and PFDA concentrations with ventricular septal defect. However, we did not observe these associations in cord blood. These exploratory findings suggested that gestational exposure to most PFAS, especially linear PFOS, 6 m-PFOS, PFDA, and PFDoA, was associated with greater risks for septal and conotruncal defects. However, a larger, adequately powered study is needed to confirm our findings, and to more comprehensively investigate the potential teratogenic effects of other more recently introduced PFAS, and on associations with individual CHD subtypes.

Background: Maternal folic acid supplementation (FAS) reduces the risk of neural tube defects in offspring. However, its effect on congenital heart disease (CHDs), especially on the severe ones remains uncertain. This study aimed to assess the individual and joint effect of first‐trimester maternal FAS and multivitamin use on CHDs in offspring. Methods and Results: This is a case‐control study including 8379 confirmed CHD cases and 6918 controls from 40 healthcare centers of 21 cities in Guangdong Province, China. Adjusted odds ratios (aORs) of FAS and multivitamin use between CHD cases (overall and specific CHD phenotypes) and controls were calculated by controlling for parental confounders. The multiplicative interaction effect of FAS and multivitamin use on CHDs was estimated. A significantly protective association was detected between first‐trimester maternal FAS and CHDs among offspring (aOR, 0.69; 95% CI, 0.62–0.76), but not for multivitamin use alone (aOR, 1.42; 95% CI, 0.73–2.78). There was no interaction between FAS and multivitamin use on CHDs ( P =0.292). Most CHD phenotypes benefited from FAS (aORs ranged from 0.03–0.85), especially the most severe categories (ie, multiple critical CHDs [aOR, 0.16; 95% CI, 0.12–0.22]) and phenotypes (ie, single ventricle [aOR, 0.03; 95% CI, 0.004–0.21]). Conclusions: First‐trimester maternal FAS, but not multivitamin use, was substantially associated with lower risk of CHDs, and the association was strongest for the most severe CHD phenotypes. We recommend that women of childbearing age should supplement with folic acid as early as possible, ensuring coverage of the critical window for fetal heart development to prevent CHDs.

Objective: Congenital heart diseases (CHDs) are associated with an extremely heavy global disease burden as the most common category of birth defects. Genetic and environmental factors have been identified as risk factors of CHDs previously. However, high volume clinical indicators have never been considered when predicting CHDs. This study aimed to predict the occurrence of CHDs by considering thousands of variables from self-reported questionnaires and routinely collected clinical laboratory data using machine learning algorithms.Methods: We conducted a birth cohort study at one of the largest cardiac centers in China from 2011 to 2017. All fetuses were screened for CHDs using ultrasound and cases were confirmed by at least two pediatric cardiologists using echocardiogram. A total of 1,127 potential predictors were included to predict CHDs. We used the Explainable Boosting Machine (EBM) for prediction and evaluated the model performance using area under the Receive Operating Characteristics (ROC) curves (AUC). The top predictors were selected according to their contributions and predictive values. Thresholds were calculated for the most significant predictors.Results: Overall, 5,390 mother-child pairs were recruited. Our prediction model achieved an AUC of 76% (69-83%) from out-of-sample predictions. Among the top 35 predictors of CHDs we identified, 34 were from clinical laboratory tests and only one was from the questionnaire (abortion history). Total accuracy, sensitivity, and specificity were 0.65, 0.74, and 0.65, respectively. Maternal serum uric acid (UA), glucose, and coagulation levels were the most consistent and significant predictors of CHDs. According to the thresholds of the predictors identified in our study, which did not reach the current clinical diagnosis criteria, elevated UA (>4.38 mg/dl), shortened activated partial thromboplastin time (<33.33 s), and elevated glucose levels were the most important predictors and were associated with ranges of 1.17-1.54 relative risks of CHDs. We have developed an online predictive tool for CHDs based on our findings that may help screening and prevention of CHDs.Conclusions: Maternal UA, glucose, and coagulation levels were the most consistent and significant predictors of CHDs. Thresholds below the current clinical definition of “abnormal” for these predictors could be used to help develop CHD screening and prevention strategies.

Proximity to greenness has shown protective effects on coronary heart diseases by limiting exposure to environmental hazards, encouraging physical activity, and reducing mental stress. However, no studies have previously evaluated the impacts of greenness on congenital heart defects (CHDs). We examined the association between maternal residential greenness and the risks of CHDs. We conducted a case-control study (8042 children with major CHDs and 6887 controls without malformations) in 21 cities in Southern China, 2004 - 2016. CHDs cases were diagnosed and verified by obstetrician, pediatrician, or pediatric cardiologists, within one year. We estimated maternal residential greenness using satellite-derived normalized difference vegetation index (NDVI) in zones of 500 meters (m) and 1000 m surrounding participants' residences. Logistic regression models were used to assess NDVI-CHD relationships adjusting for confounders. Interquartile range NDVI increases within 500 m or 1000 m were associated with odds ratios (OR) of 0.95 (95% confidence interval (CI): 0.92, 0.98) and 0.94 (95%CI: 0.91, 0.97) for total CHDs respectively. Air pollutants mediated 52.1% of the association. We also identified a protective threshold at 0.21 NDVI on CHD. Similar protective effects from greenness were found in most CHDs subtypes. The protective associations were stronger for fall, urban or permanent residents, higher household income maternal age ≤35 years of age, and high maternal education (ORs: ranged from 0.85 to 0.96). Our findings suggest a beneficial effect of maternal residential greenness on CHDs. Further studies are needed to confirm our findings, which will help to refine preventive health and urban design strategies.