A Three-Way Interaction among Maternal and Fetal Variants Contributing to Congenital Heart Defects

A gene-based association test of interactions for maternal-fetal genotypes identifies genes associated with nonsyndromic congenital heart defects

The risk of congenital heart defects (CHDs) may be influenced by maternal genes, fetal genes, and their interactions. Existing methods commonly test the effects of maternal and fetal variants one-at-a-time and may have reduced statistical power to detect genetic variants with low minor allele frequencies. In this article, we propose a gene-based association test of interactions for maternal-fetal genotypes (GATI-MFG) using a case-mother and control-mother design. GATI-MFG can integrate the effects of multiple variants within a gene or genomic region and evaluate the joint effect of maternal and fetal genotypes while allowing for their interactions. In simulation studies, GATI-MFG had improved statistical power over alternative methods, such as the single-variant test and functional data analysis (FDA) under various disease scenarios. We further applied GATI-MFG to a two-phase genome-wide association study of CHDs for the testing of both common variants and rare variants using 947 CHD case mother-infant pairs and 1306 control mother-infant pairs from the National Birth Defects Prevention Study (NBDPS). After Bonferroni adjustment for 23,035 genes, two genes on chromosome 17, TMEM107 (p = 1.64e-06) and CTC1 (p = 2.0e-06), were identified for significant association with CHD in common variants analysis. Gene TMEM107 regulates ciliogenesis and ciliary protein composition and was found to be associated with heterotaxy. Gene CTC1 plays an essential role in protecting telomeres from degradation, which was suggested to be associated with cardiogenesis. Overall, GATI-MFG outperformed the single-variant test and FDA in the simulations, and the results of application to NBDPS samples are consistent with existing literature supporting the association of TMEM107 and CTC1 with CHDs.

AHR-mediated m6A RNA methylation contributes to PM2.5-induced cardiac malformations in zebrafish larvae

A growing body of evidence indicates that ambient fine particle matter (PM_2.5) exposure inhibits heart development, but the underlying mechanisms remain elusive. We hypothesized that m⁶A RNA methylation plays an important role in the cardiac developmental toxicity of PM_2.5. In this study, we demonstrated that extractable organic matter (EOM) from PM2.5 significantly decreased global m⁶A RNA methylation levels in the heart of zebrafish larvae, which were restored by the methyl donor, betaine. Betaine also attenuated EOM-induced ROS overgeneration, mitochondrial damage, apoptosis and heart defects. Furthermore, we found that the aryl hydrocarbon receptor (AHR), which was activated by EOM_, directly repressed the transcription of methyltransferases mettl14 and mettl3. EOM also induced genome-wide m⁶A RNA methylation changes, which led us to focus more on the aberrant m⁶A methylation changes that were subsequently alleviated by the AHR inhibitor, CH223191. In addition, we found that the expression levels of traf4a and bbc3, two apoptosis related genes, were upregulated by EOM but restored to control levels by the forced expression of mettl14. Moreover, knockdown of either traf4a or bbc3 attenuated EOM-induced ROS overproduction and apoptosis. In conclusion, our results indicate that PM_2.5 induces m⁶A RNA methylation changes via AHR-mediated mettl14 downregulation, which upregulates traf4a and bbc3, leading to apoptosis and cardiac malformations.

Epigenetics and Congenital Heart Diseases

Congenital heart disease (CHD) is a frequent occurrence, with a prevalence rate of almost 1% in the general population. However, the pathophysiology of the anomalous heart development is still unclear in most patients screened. A definitive genetic origin, be it single-point mutation or larger chromosomal disruptions, only explains about 35% of identified cases. The precisely choreographed embryology of the heart relies on timed activation of developmental molecular cascades, spatially and temporally regulated through epigenetic regulation: chromatin conformation, DNA priming through methylation patterns, and spatial accessibility to transcription factors. This multi-level regulatory network is eminently susceptible to outside disruption, resulting in faulty cardiac development. Similarly, the heart is unique in its dynamic development: growth is intrinsically related to mechanical stimulation, and disruption of the intrauterine environment will have a direct impact on fetal embryology. These two converging axes offer new areas of research to characterize the cardiac epigenetic regulation and identify points of fragility in order to counteract its teratogenic consequences.

Joint Analysis of SNP-SNP-Environment Interactions for Chronic Dialysis by an Improved Branch and Bound Algorithm

In previous studies, both single-nucleotide polymorphism (SNP)-SNP or gene-gene (G × G) interactions and SNP-environmental factor (G × E) interactions were reported to partially account for "missing" heritability. However, (G × G) × E interactions were less commonly addressed. The purpose of this study was to develop a novel strategy to evaluate possible (G × G) × E interactions in D-loop-based chronic dialysis association. Using values from our previously published data set (704 controls and 193 cases) of 77 D-loop SNPs and 7 environmental factors (coronary heart disease, hypertension, diabetes mellitus, triglyceride, cholesterol, blood thiol, and TBARS levels), we compared the performances of G, G × G, G × E, and (G × G) × E. We found that the interactions of four individual SNPs previously associated with a significantly high risk of chronic dialysis [odds ratio (OR) = 1.56-4.93] with environmental factors (G × E) increased the risk of chronic dialysis (maximum OR = 35.43). We then used an improved branch and bound algorithm to identify combinations of two to four SNPs that were most highly associated with chronic dialysis (OR = 9.27-34.39). When the interactions of the two- and three-SNP combinations with environmental factors were evaluated, we found that the (G × G) × E effects increased the risk of chronic dialysis (maximum OR = 8.32-57.54 and OR = 12.52-57.81, respectively; adjusted OR = 8.67-81.81 and OR = 12.29-81.95, respectively). Taken together, the (G × G) × E interactions identified chronic dialysis-associated SNPs that would not have been found using G × G or G × E interactions, suggesting that (G × G) × E interactions may be helpful to solve the problems of missing heritability in association studies.

A missense mutation in TCN2 is associated with decreased risk for congenital heart defects and may increase cellular uptake of vitamin B12 via Megalin

Deregulation of folate and vitamin B12 (VB12) metabolism contributes to the risk of congenital heart defects (CHDs). Transcobalamin (TCN2) is essential for transporting VB12 from blood to cells as TCN2-bound VB12 (holo-TC) is the only form for somatic cellular uptake. In this study, we performed an association study between common polymorphisms in 46 one carbon metabolism genes and CHD in 412 CHDs and 213 controls. Only two significant association signals in coding regions were identified: FTCD c.1470C>T & TCN2 c.230A>T. The only missense mutation, TCN2 c.230A>T, was further validated in 412 CHDs and 1177 controls. TCN2 c.230T is significantly associated with reduced CHD risk in North Chinese (odds ratio = 0.67, P = 4.62e-05), compared with the 230A allele. Interestingly, the mean level of plasma holo-TC in women with the TA genotype was 1.77-fold higher than that in women with the AA genotype. Further analysis suggested that c.230A>T enhanced the cellular uptake of holo-TC via the LRP2 receptor. Our results determined that a functional polymorphism in TCN2 contributes to the prevalence of CHDs. TCN2 c.230A>T is significantly associated with a reduced CHD risk, likely due to TCN2 c.230T improving the interaction between holo-TC and its LRP2 receptor.

Prenatal exposure to serotonin reuptake inhibitors and congenital heart anomalies: an exploratory pharmacogenetics study

AIM

To explore the role of pharmacogenetics in determining the risk of congenital heart anomalies (CHA) with prenatal use of serotonin reuptake inhibitors.

METHODS

We included 33 case-mother dyads and 2 mother-only (child deceased) cases of CHA in a case-only study. Ten genes important in determining fetal exposure to serotonin reuptake inhibitors were examined: CYP1A2, CYP2C9, CYP2C19, CYP2D6, ABCB1, SLC6A4, HTR1A, HTR1B, HTR2A and HTR3B.

RESULTS

Among the exposed cases, polymorphisms that tended to be associated with an increased risk of CHA were SLC6A4 5-HTTLPR and 5-HTTVNTR, HTR1A rs1364043, HTR1B rs6296 and rs6298 and HTR3B rs1176744, but none reached statistical significance due to our limited sample sizes.

CONCLUSION

We identified several polymorphisms that might potentially affect the risk of CHA among exposed fetuses, which warrants further investigation.

Human Birth Weight and Reproductive Immunology: Testing for Interactions between Maternal and Offspring KIR and HLA-C Genes

BACKGROUND/AIMS

Maternal and offspring cell contact at the site of placentation presents a plausible setting for maternal-fetal genotype (MFG) interactions affecting fetal growth. We test hypotheses regarding killer cell immunoglobulin-like receptor (KIR) and HLA-C MFG effects on human birth weight by extending the quantitative MFG (QMFG) test.

METHODS

Until recently, association testing for MFG interactions had limited applications. To improve the ability to test for these interactions, we developed the extended QMFG test, a linear mixed-effect model that can use multi-locus genotype data from families.

RESULTS

We demonstrate the extended QMFG test's statistical properties. We also show that if an offspring-only model is fit when MFG effects exist, associations can be missed or misattributed. Furthermore, imprecisely modeling the effects of both KIR and HLA-C could result in a failure to replicate if these loci's allele frequencies differ among populations. To further illustrate the extended QMFG test's advantages, we apply the extended QMFG test to a UK cohort study and the Norwegian Mother and Child Cohort (MoBa) study.

CONCLUSION

We find a significant KIR-HLA-C interaction effect on birth weight. More generally, the QMFG test can detect genetic associations that may be missed by standard genome-wide association studies for quantitative traits.