Intersection of complex genetic traits affecting maternal metabolism, fetal metabolism, and neural tube defect risk: looking for needles in multiple haystacks

Association Between Maternal Factors and Risk of Congenital Heart Disease in Offspring: A Systematic Review and Meta-Analysis

INTRODUCTION

This study aimed to summarize the evidence describing the relationship between maternal factors during gestation and risk of congenital heart disease (CHD) in offspring.

METHODS

PubMed, EMBASE, and the Cochrane Library were searched for potentially relevant reports from inception to May 2021. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) calculated by the random-effects model were used to evaluate the association between maternal factors and CHD risk.

RESULTS

There was a significant association between CHD risk and obesity in pregnancy (OR 1.29, 95% CI 1.22-1.37; P < 0.001), smoking in pregnancy (OR 1.16, 95% CI 1.07-1.25; P < 0.001), maternal diabetes (OR 2.65, 95% CI 2.20-3.19; P < 0.001), and exposure of pregnant women to organic solvents (OR 1.82, 95% CI 1.23-2.70; P = 0.003). No correlations were revealed between CHD susceptibility and advanced maternal age (OR 1.04, 95% CI 0.96-1.12; P = 0.328), underweight (OR 1.02, 95% CI 0.96-1.08; P = 0.519), alcohol intake in pregnancy (OR 1.08, 95% CI 0.95-1.22; P = 0.251), coffee intake (OR 1.18, 95% CI 0.97-1.44; P = 0.105), and exposure to irradiation (OR 1.80, 95% CI 0.85-3.80; P = 0.125).

DISCUSSION

Maternal factors including maternal obesity, smoking in pregnancy, maternal diabetes and exposure to organic solvents might predispose the offspring to CHD risk.

Digenic variants of planar cell polarity genes in human neural tube defect patients

Neural tube defects (NTDs) are considered to be a complex genetic disorder, although the identity of the genetic factors remains largely unknown. Mouse model studies suggest a multifactorial oligogenic pattern of inheritance for NTDs, yet evidence from published human studies is surprisingly absent. In the present study, targeted next-generation sequencing was performed to screen for DNA variants in the entire coding regions and intron-exon boundaries of targeted genes using DNA samples from 510 NTD cases. These candidate genes were PCP genes, including VANGL1, VANGL2, CELSR1, SCRIB, DVL2, DVL3 and PTK7. Candidate variants were validated using Sanger sequencing. A total of 397 single nucleotide variants(SNVs) were identified with a mean depth of approximately 570×. Of these identified SNVs, 74 were predicted to affect protein function and had a minor allele frequency of <0.01 or unknown. Among these 74 missense SNVs, 10 were identified from six NTD cases that carried two mutated genes. Of the six NTD cases, three spina bifida cases and one anencephaly case carried digenic variants in the CELSR1 and SCRIB gene; one anencephaly case carried variants in the CELSR1 and DVL3 gene; and one spina bifida case carried variants in the PTK7 and SCRIB genes. Three cases that parental samples were available were confirmed to be compound heterozygous. None of the digenic variants were found in the 1000 genome database. The findings imply that genetic variation might interact in a digenic fashion to generate the visible NTD phenotypes and emphasize the importance of these genetic interactions in the development of NTDs in humans.

Original Findings and Updated Meta-Analysis for the Association Between Maternal Diabetes and Risk for Congenital Heart Disease Phenotypes

Maternal diabetes is associated with congenital heart defects (CHDs) as a group, but few studies have assessed risk for specific CHD phenotypes. We analyzed these relationships using data from the Texas Birth Defects Registry and statewide vital records for deliveries taking place in 1999-2009 (n = 48,249 cases). We used Poisson regression to calculate prevalence ratios for the associations between maternal diabetes (pregestational or gestational) and each CHD phenotype, adjusting for potential confounders. Analyses were repeated by type of diabetes. To address the potential for misclassification bias, we performed logistic regression, using malformed controls. We also conducted meta-analyses, combining our estimates of the association between pregestational diabetes and each CHD phenotype with previous estimates. The prevalence of every CHD phenotype was greater among women with pregestational diabetes than among nondiabetic women. Most of these differences were statistically significant (adjusted prevalence ratios = 2.47-13.20). Associations were slightly attenuated for many CHD phenotypes among women with gestational diabetes. The observed associations did not appear to be the result of misclassification bias. In our meta-analysis, pregestational diabetes was significantly associated with each CHD phenotype. These findings contribute to a better understanding of the teratogenic effects of maternal diabetes and improved counseling for risk of specific CHD phenotypes.