Pregestational diabetes mediates the association between maternal obesity and the risk of congenital heart defects

Risk factors for isolated congenital heart defects in infants from Western Mexico

Congenital heart defects (CHDs) are caused by a complex interaction between numerous genetic and environmental risk factors, some of which may differ between different populations. A case-control study was conducted among 1232 newborns, including 308 patients with isolated CHDs (cases) and 924 infants without birth defects (controls), born all during the period 2009-2023 at the Hospital Civil de Guadalajara "Dr. Juan I. Menchaca" (Guadalajara, Mexico). Potential parental risk factors for CHDs were compared using multivariate logistic regression analysis to evaluate the deviance explained by different variables of interest. Consanguinity [adjusted odds ratio (aOR) = 3.3; 95% confidence interval (CI) 1.3-8.5], relatives with CHD (aOR = 8.5; 95% CI 5.3-13.8), maternal first-trimester exposure to diabetes (aOR = 3.5; 95% CI 2.4-5.1), hypertension (aOR = 2.6; 95% CI 1.5-4.4), alcohol consumption (aOR = 1.5; 95% CI 1.0-2.1), and illicit drug use (aOR = 2.4; 95% CI 1.2-5.3), as well as for the paternal history of alcohol consumption (aOR = 1.4; 95% CI 1.0-1.8) and illicit drug use (aOR = 2.7; 95% CI 1.7-4.1), were associated with CHDs. Contrarily, aOR for maternal age ≤19 years (aOR = 0.6; 95% CI 0.4-0.8) and maternal first-trimester coffee consumption (aOR = 0.7; 95% CI 0.5-0.9) have protective odds. Our results suggest that genetic factors, maternal diseases, environmental exposures, and reproductive factors can increase the occurrence of isolated CHDs in our sample, and they are discussed as clues in its pathogenesis.

Systematic Review and Meta-analysis of Prenatal Risk Factors for Congenital Heart Disease: Part 1, Maternal Chronic Diseases and Parental Exposures

BACKGROUND

There is considerable heterogeneity in studies on prenatal risk factors for congenital heart diseases (CHDs). We performed a meta-analysis of all nongenetic factors of CHDs. This report presents results of factors related to maternal chronic diseases and parental exposures.

METHODS

A systematic search encompassing concepts of CHD and risk factors was used, using the following inclusion criteria: (1) original peer-reviewed articles, (2) quantifying the effects of risk factors for CHDs, (3) between 1989 and 2022. Pooled odds ratios (ORs) and 95% confidence interval (CI) were calculated using a random-effect model.

RESULTS

Inclusion criteria were met for 170 studies. There was an association between being overweight or obese and CHDs (OR, 1.26; 95% CI, 1.15-1.37), with a dose-effect relationship. Pregestational diabetes (PGDM) was associated with CHDs (OR, 3.51; 95% CI, 2.86-4.3), without difference between type 1 and type 2 PGDM. The effect size of gestational diabetes was less than that of PGDM (OR, 1.38; 95% CI, 1.18-1.61). There was an association between CHDs and pre-eclampsia (OR, 2.01; 95% CI, 1.32-3.05), paternal smoking (OR, 1.32; 95% CI, 1.03-1.70), and alcohol use (OR, 1.50; 95% CI, 1.08-2.08). A smaller association was found with maternal smoking and advanced maternal age.

CONCLUSIONS

There exists robust evidence for increased risk of CHD in the presence of obesity, maternal diabetes, maternal smoking, and increased maternal age. The effect sizes were relatively modest, except for PGDM. The robustness of the evidence decreased when CHDs were divided into subgroups or when the analyses were restricted to severe CHDs.

Maternal prepregnancy weight as an independent risk factor for congenital heart defect: systematic review and meta-analysis stratified by subtype and severity of defect

OBJECTIVE

To assess the association between increased maternal prepregnancy body mass index (BMI) and the risk of congenital heart defect (CHD) in offspring.

METHODS

This systematic review and meta-analysis searched PubMed/MEDLINE, Web of Science and Scopus from inception to 20 April 2023. Risk estimates were abstracted or calculated for increased BMI categories (overweight, obesity, moderate obesity and severe obesity) compared with normal weight (reference). Fixed-effects or random-effects models were used to combine individual study risk estimates based on the degree of heterogeneity. Sensitivity analyses were conducted to weight pooled estimates for relevant moderators, particularly diabetes before and during pregnancy. Subgroup analyses for specific CHD subtypes were conducted if there were at least two studies with available data. Findings were presented for groups of defects, categorized using severity and topographic-functional criteria, and for individual defects. The certainty of the evidence for each effect estimate was evaluated according to Grading of Recommendations, Assessment, Development and Evaluation (GRADE) guidelines.

RESULTS

Overall, 31 studies comprising 4 861 693 patients and 86 136 CHD cases were included. The risk of CHD increased progressively from moderate to severe obesity (pooled odds ratio (OR), 1.15 (95% CI, 1.11-1.20) and 1.39 (95% CI, 1.27-1.53), respectively). Sensitivity analysis indicated that this effect persisted independently of maternal diabetes status before or during pregnancy. In the subgroup analysis, obesity was associated with up to a 1.5-fold increase in the risk of severe CHD (pooled OR, 1.48 (95% CI, 1.03-2.13)). Severe obesity was associated with an even higher risk, with 1.8-times higher odds compared with the reference group for specific CHD subtypes, including tetralogy of Fallot (pooled OR, 1.72 (95% CI, 1.38-2.16)), pulmonary valve stenosis (pooled OR, 1.79 (95% CI, 1.39-2.30)) and atrial septal defect (pooled OR, 1.71 (95% CI, 1.48-1.97)).

CONCLUSIONS

Maternal weight is a crucial modifiable risk factor for CHD, particularly for severe forms of defect. Further research is needed to investigate whether weight management before pregnancy might serve as a preventive measure against CHD. In pregnant women with obesity, fetal echocardiography should be a routine diagnostic procedure. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Maternal Gestational Diabetes Mellitus and Congenital Heart Disease in Offspring: A Meta-Analysis

Maternal diabetes has been related to an increased risk of congenital heart disease (CHD) in offspring. However, inconsistent results were retrieved for studies evaluating the association between gestational diabetes mellitus (GDM) and CHD in offspring. We therefore performed a systematic review and meta-analysis for comprehensive investigation. Observational studies were identified by searching PubMed, Embase, and Web of Science according to the aim of the meta-analysis. A randomized-effects model was used to pool the data by incorporating the influence of potential heterogeneity. Twenty-three observational studies, involving 46953078 mother-child pairs, were available for the meta-analysis. Among them, 2131800 mothers were diagnosed as GDM and 214379 newborns had CHD. Overall, maternal GDM was associated with a higher incidence of CHD in offspring [odds ratio (OR): 1.32, 95% confidence interval (CI): 1.21 to 1.45, p<0.001; I2=62%]. Sensitivity analysis limited to studies with adjustment of maternal age and other potential confounding factors showed similar results (OR: 1.40, 95% CI: 1.30 to 1.51, p<0.001; I2=47%). Subgroup analysis suggested that the association between maternal GDM and CHD in offspring was not significantly affected by methods for diagnosis of GDM, methods for confirmation of CHD, or study quality scores (p for subgroup difference all>0.05). Subsequent analysis according to types of CHD showed that maternal GDM was associated with higher risks of atrial septal defect, ventricular septal defect, and Tetralogy of Fallot. Maternal GDM may be associated with a higher risk of CHD in offspring.

Maternal Pre-Existing Diabetes: A Non-Inherited Risk Factor for Congenital Cardiopathies

Congenital heart defects (CHDs) are the most common form of birth defects in humans. They occur in 9 out of 1000 live births and are defined as structural abnormalities of the heart. Understanding CHDs is difficult due to the heterogeneity of the disease and its multifactorial etiology. Advances in genomic sequencing have made it possible to identify the genetic factors involved in CHDs. However, genetic origins have only been found in a minority of CHD cases, suggesting the contribution of non-inherited (environmental) risk factors to the etiology of CHDs. Maternal pregestational diabetes is associated with a three- to five-fold increased risk of congenital cardiopathies, but the underlying molecular mechanisms are incompletely understood. According to current hypotheses, hyperglycemia is the main teratogenic agent in diabetic pregnancies. It is thought to induce cell damage, directly through genetic and epigenetic dysregulations and/or indirectly through production of reactive oxygen species (ROS). The purpose of this review is to summarize key findings on the molecular mechanisms altered in cardiac development during exposure to hyperglycemic conditions in utero. It also presents the various in vivo and in vitro techniques used to experimentally model pregestational diabetes. Finally, new approaches are suggested to broaden our understanding of the subject and develop new prevention strategies.

Prediction of congenital heart disease for newborns: comparative analysis of Holt-Winters exponential smoothing and autoregressive integrated moving average models

OBJECTIVE

To describe the temporal trend of the number of new congenital heart disease (CHD) cases among newborns in Jinhua from 2019 to 2020 and explored an appropriate model to fit and forecast the tendency of CHD.

METHODS

Data on CHD from 2019 to 2020 was collected from a health information system. We counted the number of newborns with CHD weekly and separately used the additive Holt-Winters ES method and ARIMA model to fit and predict the number of CHD for newborns in Jinhua. By comparing the mean square error, rooted mean square error and mean absolute percentage error of each approach, we evaluated the effects of different approaches for predicting the number of CHD in newborns.

RESULTS

A total of 1135 newborns, including 601 baby girls and 534 baby boys, were admitted for CHD from HIS in Jinhua during the 2-year study period. The prevalence of CHD among newborns in Jinhua in 2019 was 0.96%. Atrial septal defect was diagnosed the most frequently among all newborns with CHD. The number of CHD cases among newborns remained stable in 2019 and 2020. There were fewer cases in spring and summer, while cases peaked in November and December. The ARIMA(2,1,1) model relatively offered advantages over the additive Holt-winters ES method in predicting the number of newborns with CHD, while the accuracy of ARIMA(2,1,1) was not very ideal.

CONCLUSIONS

The diagnosis of CHD is related to many risk factors, therefore, when using temporal models to fit and predict the data, we must consider such factors' influence and try to incorporate them into the models.