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Association of MTHFD1 gene polymorphisms and maternal smoking with risk of congenital heart disease: a hospital-based case-control study

BMC Pregnancy and Childbirth volume 22, Article number: 88 (2022) Cite this article

Abstract

Background

MTHFD1 gene may affect the embryonic development by elevated homocysteine levels, DNA synthesis and DNA methylation, but limited number of genetic variants of MTHFD1 gene was focused on the association with congenital heart disease (CHD). This study examined the role of MTHFD1 gene and maternal smoking on infant CHD risk, and investigated their interaction effects in Chinese populations.

Methods

A case-control study of 464 mothers of CHD infants and 504 mothers of health controls was performed. The exposures of interest were maternal tobacco exposure, single nucleotide polymorphisms (SNPs) of maternal MTHFD1 gene. The logistic regression model was used for accessing the strength of association.

Results

Mothers exposed to secondhand smoke during 3 months before pregnancy (adjusted odds ratio [aOR] = 1.56; 95% confidence interval [CI]: 1.13–2.15) and in the first trimester of pregnancy (aOR = 2.24; 95%CI: 1.57–3.20) were observed an increased risk of CHD. Our study also found that polymorphisms of maternal MTHFD1 gene at rs1950902 (AA vs. GG: aOR = 1.73, 95% CI: 1.01–2.97), rs2236222 (GG vs. AA: aOR = 2.38, 95% CI: 1.38–4.12), rs1256142 (GA vs.GG: aOR = 1.57, 95% CI: 1.01–2.45) and rs11849530 (GG vs. AA: aOR = 1.68, 95% CI: 1.02–2.77) were significantly associated with higher risk of CHD. However, we did not observe a significant association between maternal MTHFD1 rs2236225 and offspring CHD risk. Furthermore, we found the different degrees of interaction effects between polymorphisms of the MTHFD1 gene including rs1950902, rs2236222, rs1256142, rs11849530 and rs2236225, and maternal tobacco exposure.

Conclusions

Maternal polymorphisms of MTHFD1 gene, maternal tobacco exposure and their interactions are significantly associated with the risk of CHD in offspring in Han Chinese populations. However, more studies in different ethnic populations with a larger sample and prospective designs are required to confirm our findings.

Trial registration

Registration number: ChiCTR1800016635.

Peer Review reports

Background

Congenital heart defect (CHD) was often defined as a structural or functional abnormality of the heart and/or great vessels that were present at birth [1]. Among all recognized structural birth defects, CHD was the most common and severe, with 4 to 10 cases per 1000 live births, which imposed a huge economic burden on the society and family [2]. Although the past few decades have seen a rapidly growing interest in exploring the etiology of CHD, the pathogenesis of most CHD cases remains unknown [3, 4].

So far, folic acid supplementation was the most effective large-scale primary intervention for decreasing CHD in China [5,6,7,8,9]. The folate-cycle product homocysteine might affect fetal heart development by disruption of gene methylation, increasing oxidative stress and homocysteinylation of key proteins [7, 10], which indicated that the occurrence of CHD was highly responsive to changes in genes related to maternal folate-homocysteine metabolism. The methylenetetrahydrofolate dehydrogenase 1 (MTHFD1) gene, located on chromosome 14q24, encoded the trifunctional enzyme MTHFD1 (5,10-methylenetetrahydrofolate dehydrogenase [11], 5,10-methenyltetrahydrofolate cyclohydrolase, and 10-formyltetrahydrofolate synthetase). This enzyme catalyzed three sequential reactions in the interconversion of tetrahydrofolate (THF) to 5,10-methylenetettrahydrofolate (5,10-methylene THF), the crucial substrate for 5-methyltetrahydrofolate (5-methlyTHF), which was required for DNA synthesis, DNA repair and provided the methyl donor for regeneration of methionine from homocysteine for subsequent methylation reactions [12, 13]. The data published indicated plausible mechanisms of the MTHFD1 gene in CHD susceptibility might involve restricted DNA synthesis, high levels of homocysteine, and DNA methylation [7, 14,15,16,17]. The experimental studies had revealed that the MTHFD1 gene with mutant genotypes expressed less stable in vitro and low active in vivo MTHFD1 protein [14, 15], and consequently disturbed de novo purine synthesis and impacted DNA synthesis. Moreover, the epidemiologic studies suggested that polymorphisms of the MTHFD1 gene such as rs2236225 and rs1950902 were closely related to homocysteine levels [17,18,19,20] and DNA methylation [19]. MTHFD1 R653Q (rs2236225 G → A) and MTHFD1 R134K (rs1950902 G → A) as the two most well-studied polymorphisms [21], previous efforts involved in the associations of children’s genetic polymorphisms with CHD risk had yielded conflicting results [14, 22,23,24,25,26,27], and there were few studies on the associations of maternal genetic polymorphisms with CHD risk [14, 16]. Notably, previous studies focused mainly on a small number of functional nonsynonymous single-nucleotide polymorphisms (SNPs) of the MTHFD1 gene with known biochemical phenotypes such as rs1950902 and rs2236225; the other significant variants have been largely ignored; thus this study represents both the first report and replication efforts in Han Chinese populations.

It had been reported that 85% of CHD resulted from a complex interplay of genetic variants and environmental factors [28]. Maternal tobacco exposure in the periconceptional period, defined as 3 months before pregnancy through the first trimester of pregnancy, was one of the most common environmental factors affecting abnormal fetal development. Amounts of epidemiologic studies about the associations of maternal tobacco exposure in the periconceptional period involved in smoke exposure and CHD risk were showed heterogeneous results, indicating that people had different susceptibility to the effects of tobacco exposure [29,30,31,32,33]. Convincing evidence showed that it was clear that particular genotypes of metabolizing systems and DNA repair pathways might modulate the effect leading to varying susceptibility to the CHD of tobacco exposure [34]. The maternal tobacco exposure was observed associations with substantial reductions of folate levels in plasma [35, 36] as well as in cord blood [37], and red blood cells [38, 39], even after correcting for folate intake [40], which implied that the interactive association between maternal tobacco exposure and gene polymorphisms in the folate-homocysteine pathway was closely related to CHD susceptibility. Although no direct evidence were reported about the interaction between maternal MTHFD1 gene and smoking exposure on the CHD risk, some studies centered on 5,10-methylenetetrahydrofolate reductase (MTHFR) gene, an enzyme of great significance associated with folate metabolism, provided key clues. There were several studies in relation to the interaction of maternal MTHFR gene and smoke exposure on the risk of adverse pregnancy outcomes including low birth weight [41] and major birth defects such as neural tube defects, oral clefting [34] and CHD [42], and the mechanisms might be due to low folate status associated with genetic polymorphisms of MTHFR gene and smoke exposure [43]. MTHFD1 as a key enzyme catalyzed three sequential reactions in the interconversion of THF to 5,10-methylene THF, playing a significant role in the folate-homocysteine metabolism pathway, and thus we had reasons to believe MTHFD1 gene also had an impact on folate status associated with smoke exposure. In addition, a recent study suggested that maternal folate levels might partly modify the influence of maternal tobacco exposure during pregnancy on the DNA methylation of the newborn epigenome and therefore affected embryonic development [44]. Many meaningful clues above were collected to put forward such a reasonable assumption that there existed the interaction effects of maternal tobacco exposure and the MTHFD1 genetic variants, namely that the two factors jointly caused the CHD. In our study, a hospital-based case-control design based on the Han Chinese population was performed with the following objectives: (i) to assess the association of genetic variants of maternal MTHFD1 gene with risk of CHD in offspring; (ii) to examine whether maternal smoking including active and passive smoking was significantly associated with risk of CHD in offspring; and (iii) to analyze the interaction effects between maternal smoking and the MTHFD1 genetic variants for CHD.

Methods

Study design and recruitment of study participants

Recruitment was conducted by the Hunan Provincial Children’s Hospital (Changsha, Hunan Province, China). A total of 464 CHD patients and their mothers were consecutively enrolled from the Department of Cardiothoracic Surgery between November 2017 and December 2019. The non-CHD patients were from the Department of Child Healthcare in the same hospital during the same time period and were matched to the affected individuals by the age and sex of infants (frequency matching). The controls included 504 non-CHD patients who were without any congenital malformations after medical examination and their mothers. All CHD cases were diagnosed using echocardiography and confirmed by surgery. The CHD patients with structural malformations involving another organ system or known chromosomal abnormalities were excluded. Considering the homogenous ethnic background may reduce residual confounding factors from genetic and cultural differences, we only included the Han Chinese descent. We further excluded mothers who achieved pregnancy by assisted reproductive technology including in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) and reporting. Again, mothers who reported a history of depression or other psychiatric disorders or were diagnosed with depression or a psychiatric illness were also excluded. We classified the 464 CHD cases into 7 broad categories as described previously [45]. In particular, 28 (6.0%) had conotruncal defects, 360 (77.6%) had septation defects, 11 (2.4%) had left ventricular outflow tract obstruction, 17 (3.7%) had right ventricular outflow tract obstruction, 16 (3.4%) had anomalous pulmonary venous return, 20 (4.3%) had complex CHD, and 12 (2.6%) had other CHD defects (Table S1).

Our study was approved by the ethics committee of the Xiangya School of Public Health of Central South University, and written informed consent was obtained from all mothers. Besides, we have registered this study in the Chinese Clinical Trial Registry Center (registration number: ChiCTR1800016635).

Information collection

The main exposures included maternal active smoking in 3 months before pregnancy, active smoking in the first trimester of pregnancy, passive smoking in 3 months before pregnancy and passive smoking in the first trimester of pregnancy. We defined maternal active smoking in 3 months before pregnancy and in the first trimester of pregnancy were mothers who reported active smoke during any of the 3 months before pregnancy, and during any of the first 3 months of pregnancy, respectively. The definitions of maternal passive smoking in 3 months before pregnancy and in the first trimester of pregnancy were mothers who reported that someone smoked at home and/or near her at work/school during any of the 3 months before pregnancy, and any of the first 3 months of pregnancy, respectively. A self-designed questionnaire was used to collect the corresponding information by specially trained investigators. This questionnaire was developed by experts in the field of CHD research and administered to eligible mothers (test-retest reliability = 0.833; Cronbach’s alpha = 0.782). Based on the previous literature [46,47,48,49,50,51,52], we selected the potentially confounding factors of significance as follows: maternal age at pregnancy onset (< 35 or ≥ 35), residence location (rural or urban), maternal education level (≤9, 9–12, 12–16 or > 16 years), annual income in the past 1 year (≤50,000, 50,000–100,000, 100,000–150,000 or > 150000RMB), history of adverse pregnancy outcomes (yes or no), consanguineous marriage (yes or no), history of congenital malformations in family (yes or no), cold or fever (do you have a cold or fever experience in 3 months before pregnancy and/or during the first-trimester pregnancy, yes or no), drinking alcohol (do you have a drinking alcohol experience in 3 months before pregnancy and/or during the first-trimester pregnancy, yes or no), drinking tea (do you have a drinking tea experience in 3 months before pregnancy and/or during the first-trimester pregnancy, yes or no), living near environmental pollution source (yes or no), dyeing hair or perming (do you have a dyeing hair or perming experience in 3 months before pregnancy and/or during the first-trimester pregnancy, yes or no), decorating housing (are there any decorating housing at home or at work near you in 3 months before pregnancy and/or during the first-trimester pregnancy, yes or no) and folate use (do you use any folic acid in 3 months before pregnancy and/or during the first-trimester pregnancy, yes or no). We defined folate use as any use of folic acid in 3 months before pregnancy and/or during the first-trimester pregnancy. The above mentioned information was further confirmed by consulting their Maternal and Child Health Manual and medical records. In China, each pregnant woman will be provided with a Maternal and Child Health Manual, which will record their basic demographic characteristics, behavioral habits, illness, and the results of various medical examinations during pregnancy. We also examined the SNPs of the maternal MTHFD1 gene, which are described below.

Sequencing of MTHFD1 gene and genotyping

The MTHFD1 gene was the candidate gene for the present study. When mothers completed the questionnaires mentioned above, they were asked to provide 3 to 5 ml of peripheral venous blood for genotyping. Methods for DNA extraction and genotyping have been described previously [40]. The polymorphisms of MTHFD1 gene were tested using a matrix-assisted laser desorption and ionization time-of-flight mass spectrometry MassARRAY system (Agena iPLEX assay, San Diego, CA, USA). The laboratory technician, who performed the genotyping, retyped and double-checked each sample, and recorded the genotype data, was blinded to whether the samples were from cases or controls. SNP markers were selected using the SNPBrowser™ program (version 3.0) provided by AppliedBiosystems Inc. This program allowed the selection of SNP markers from the HapMap database. For each target gene, tagging SNPs were selected based on the pairwise r2 ≥ 0.8. However, we excluded these SNPs with minor allele frequencies less than 10% in Caucasians. We imposed a minimum SNP genotyping call rate at the level of 50%, which was applied to ensure data integrity of the individual’s genotypes that had been called. And successful rates for SNPlex assays were > 96% for 4 SNPs, from 90 to 96% for 1 SNPs. Finally, these genetic loci (rs1950902, rs2236225, rs2236222, rs11849530 and rs1256142) were selected as candidate loci for this study.

Statistical analysis

Statistical analysis was performed using R software, version 3.5.0 (R Foundation for Statistical Computing). All tests were performed significantly for a two-sided P value not exceeding 0.05, except where otherwise specified. Additionally, the false discovery rate (FDR) control was used in this study to correct for multiple testing. The statistically significant results were those with the false discovery rate P value (FDR_P) < 0.1. Qualitative data were described using frequencies and percentages, and quantitative data were described using means and standard deviations (SDs). Hardy-Weinberg equilibrium (HWE) was tested for the control group (significance level at P < 0.01). We used a two-phase analytical method based on genetic model selection (GMS) to test associations between SNPs and CHD, and the specific calculation process had been described previously [53]. The genetic models contained the dominant model (calculated for mutant type homozygote versus wild type homozygotes and heterozygote), the recessive model (calculated for heterozygotes and mutant type homozygotes versus wild type homozygotes), and the additive model (calculated for wild type homozygotes versus heterozygote versus mutant type homozygote). We classified the genetic model into the recessive model if ZHWDTT > c, the dominant model if ZHWDTT < −c, and in the additive model if otherwise, where we chose c = Φ− 1(0.95) = 1.645. The Pearson χ2 test was used to compare the differences of nominal variables across groups. And for ordinal categorical variables, Wilcoxon rank sum test was used.

Odds ratios (OR) and their 95% confidence intervals (CI) were used to show the level of association. Univariate logistic regression analysis was done among all these potentially confounding factors mentioned above, and the variables with p-value < 0.05 were entered into the multivariable logistic regression as explanatory variables. There were no missing data. In initial analyses, the two variates maternal age at pregnancy onset and decorating housing did not show the statistically significant differences between the case and control group, so we finally included the following covariates as confounders of the association between maternal smoke exposure and MTHFD1 gene on infant CHD risk in the multivariable model; residence location (rural or urban), maternal education level (≤9, 9–12, 12–16 or > 16 years), annual income in the past 1 year (≤50,000, 50,000–100,000, 100,000–150,000 or > 150000RMB), history of adverse pregnancy outcomes (yes or no), consanguineous marriage (yes or no), history of congenital malformations in family (yes or no), cold or fever (yes or no), drinking alcohol (yes or no), drinking tea (yes or no), living near environmental pollution source (yes or no), dyeing hair or perming (yes or no) and folate use (yes or no) were selected as confounding factors. The categorical explanatory variables with multiple categories were analyzed with indicator variables.

Gene-environment interactions were tested by introducing the multiplicative interaction term, all the covariates, and all the covariate-by-environment and the covariate-by-gene interaction terms into the same model, in order to properly control for potential confounders on the interaction term and assess its significance [54]. Of note, in the present study, we focused only on the risk of total CHD associated with maternal smoking and genetic variants of the MTHFD1 gene and did not assess the risk of specific CHD subtypes due to the limited number of sample sizes for these subtypes.

Results

Baseline characteristics of study population

After considering the inclusion criteria, we finally recruited 464 CHD cases and their parents into the case group and 504 health infants and their parents into the control group. Comparisons of baseline characteristics across groups were summarized in Table 1. Our study showed that there were statistically significant differences between two groups for the following characteristics: residence location, maternal education level (years), annual income in the past 1 year (RMB), history of adverse pregnancy outcomes, consanguineous marriage, history of congenital malformations in family, cold or fever in the periconceptional period, and personal lifestyle and habit in the periconceptional period including drinking alcohol, drinking tea, living near environmental pollution source, dyeing hair or perming and folate use (all P values < 0.05). Thus, these factors were adjusted when accessing the association of maternal tobacco exposure, the genetic variants of the maternal MTHFD1 gene, and their interactions with the risk of CHD in offspring.

Table 1 Baseline characteristics in case and control groupsa
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Maternal tobacco exposure and risk of CHD in offspring

Table 2 showed the association between maternal smoking and the risk of CHD in offspring. The prevalence rate of active smoking in 3 months before pregnancy in our controls (2.0%) was lower than the smoking rate among Chinese women in China Adult Tobacco Survey Report in 2015 (2.7%) [55]. None of the mothers in cases and controls reported active smoking in the first trimester of pregnancy. Mothers who reported active smoking in 3 months before pregnancy had an increased risk of CHD in offspring compared with the controls (P < 0.001), but this association was not independent of potential confounders (P = 0.052). After adjustment for baseline data, mothers exposed to secondhand smoke in 3 months before pregnancy were observed an increased risk of CHD in offspring (aOR = 1.56; 95% CI: 1.13–2.15). Additionally, the risk of CHD in offspring was significantly higher among mothers who were exposed to secondhand smoke in the first trimester of pregnancy (aOR = 2.24; 95% CI: 1.57–3.20).

Table 2 Maternal smoking and risk of congenital heart defects in offspringa
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Genotypes frequencies of SNPs and the results of HWE tests and GMS

The genotype frequencies for each SNP of the maternal MTHFD1 gene and the results of HWE tests were summarized in Table S2. The HWE tests showed that the genotype frequencies of the 5 SNPs of maternal MTHFD1 gene in the control group were all within HWE (all P values > 0.01). The results of the GMS of each SNP were presented in Table S3. The genetic models of SNPs including rs1950902, rs2236225, rs2236222 and rs11849530 were all classified into the additive model since ZHWDTT > − 1.645 and ZHWDTT < 1.645. The genetic model of rs1256142 was classified into the dominant model because of ZHWDTT < − 1.645. We initially ascertained the genetic models of overall SNPs of the maternal MTHFD1 gene, which was used for accessing the association between each SNP and risk of CHD in offspring based on the corresponding genetic model.

Genetic variants of maternal MTHFD1 gene and risk of CHD in offspring

The association between each maternal SNP of the MTHFD1 gene and the risk of CHD in the Han Chinese population was shown in Table 3. The univariate analyses suggested that there were statistically significant differences for the genetic variants at rs1950902 (AA vs. GG: P = 0.006; the additive model: P = 0.002), rs2236222 (GG vs. AA: P = 0.001; the additive model: P = 0.001) and rs1256142 (GA vs. GG: P = 0.035) between the case and control groups.

Table 3 MTHFD1 genes in mothers and risk of congenital heart disease in offspring
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After adjustment for the potential confounders, the polymorphisms including rs1950902 (AA vs. GG: aOR = 1.73, 95% CI: 1.01–2.97; the additive model: aOR =1.30, 95% CI: 1.02–1.65), rs2236222 (GG vs. AA: aOR = 2.38, 95% CI: 1.38–4.12; the additive model: aOR = 1.40, 95% CI: 1.14–1.73) and rs1256142 (GA vs.GG: aOR = 1.57, 95% CI: 1.01–2.45; the dominant model: aOR = 1.57, 95% CI: 1.03–2.40) were still observed an increased risk for CHD, respectively. In addition, rs11849530 (GG vs. AA: aOR = 1.68, 95% CI: 1.02–2.77; the additive model: aOR = 1.28, 95% CI: 1.02–1.62) was also observed a significant association with higher CHD risk.

Interactions between maternal smoke exposure and MTHFD1 gene for risk of CHD

The gene-environment interaction effects between maternal SNPs of MTHFD1 gene including rs1950902, rs2236222, rs1256142, rs11849530 and rs2236225 in the corresponding genetic model and maternal smoke exposure on CHD risk were summarized in Table 4. Due to the limited sample size of mothers who had an active smoke experience during the periconceptional period, the multivariable logistic regression models failed when adjusted for confounders, so we only explored the interactive effects of maternal passive smoke before pregnancy and in the first trimester, and MTHFD1 gene on infant CHD risk. Our results showed there were statistically significant interaction effects between maternal passive smoking in 3 months before pregnancy and genetic variants of MTHFD1 gene at rs2236225 (FDR_P = 0.003), rs2236222 (FDR_P < 0.001) and rs1256142 (FDR_P < 0.001). Additionally, maternal passive smoking in the first trimester was also observed statistically significant interaction effects with MTHFD1 gene at rs2236225 (FDR_P = 0.043), rs2236222 (FDR_P = 0.035) and rs1256142 (FDR_P = 0.035).

Table 4 Interactions between SNPs of MTHFD1 gene and maternal smoking detected by logistic regression
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Crossover analysis was conducted in order to further elaborate the gene-environment interaction effects of maternal passive smoking in 3 months before pregnancy (Table S4) and in the first trimester (Table S5), and maternal MTHFD1 gene on the risk of CHD. Mothers with the wild type genotype meanwhile without passive smoke exposure were considered to be the reference group. After the adjustment for confounders, it was suggested that mothers who had variant genotypes at rs2236225 (aOR = 1.96; 95% CI: 1.19 to 3.23; FDR_P = 0.034), rs11849530 (aOR = 2.01; 95% CI: 1.25 to 3.22; FDR_P = 0.020) and rs1256142 (aOR = 2.94; 95% CI: 1.54 to 5.62; FDR_P = 0.008), and meanwhile were exposed to second smoke before pregnancy were at a significantly higher risk of CHD in offspring compared with those in the reference group (Table S4). We also observed that mothers who exposed to second smoke in the first trimester, and meanwhile had variant genotypes at rs2236225 (aOR = 2.93; 95% CI: 1.64 to 5.24; FDR_P < 0.001), rs2236222 (aOR = 1.85; 95% CI: 1.05 to 3.27; FDR_P = 0.069), rs11849530 (aOR = 3.22; 95% CI: 1.91 to 5.45; FDR_P < 0.001) and rs1256142 (aOR = 3.36; 95% CI: 1.88 to 5.99; FDR_P < 0.001) were at a significantly higher risk of CHD in offspring compared with those in the reference group (Table S5).

Discussion

Convincing evidence implies that periconceptional intake of folic acid leads to a 40 to 60% reduction in the risk of a CHD-affected delivery, which makes investigating the association between genetic polymorphisms in genes related to folate metabolism and CHD risk an attractive pursuit [56]. The MTHFD1 gene plays a key role in the folate-homocysteine metabolism pathway, encoding a single protein with three catalytic properties crucial for DNA synthesis, DNA repair, and methylation reactions. The epidemiologic and experimental studies indicate the plausible association between genetic variants of the MTHFD1 gene and the risk of CHD [14,15,16,17,18], but previous efforts on the association have yielded controversial results, with the majority limited to a small number of functional nonsynonymous polymorphisms [14, 20, 22]. This is therefore the first study to explore the other variants of the MTHFD1 gene on CHD risk in Han Chinese populations. Furthermore, folate-homocysteine metabolism may partly modulate the effect leading to varying susceptibility to the CHD of tobacco exposure [34, 42,43,44]. Thus this study also seeks to examine the interactions of maternal tobacco exposure and polymorphisms of the MTHFD1 gene on CHD risk, which may help to provide new clues for future etiological research and intervention of CHD.

In the present study, four genetic variants of maternal MTHFD1 gene including rs1950902, rs2236222, rs1256142 and rs11849530 were revealed to have significant associations with an increased risk of CHD in case-control studies based on the Han Chinese population. The information from the public databases and the literature revealed unequivocally these SNPs were all within the coding region; one was functional nonsynonymous polymorphism with a known biochemical phenotype and the other were intronic ones [11, 14]. Notably, the well-studied polymorphism rs1950902 G → A (MTHFD1 G401A) leads to an arginine (G allele) to a lysine (A allele) substitution, lying within the dehydrogenase/cyclohydrolase domain of MTHFD1 protein. Although its role is unclear, it was speculated that the mutant genotypes of the MTHFD1 gene at rs1950902 may influence the stability of the enzyme and change the catalytic activity [20], causing disturbance of the folate-homocysteine metabolism pathway. It was reported that rs1950902 was significantly related to elevated plasma homocysteine and reduced folate levels [18, 19]. These observations suggested that MTHFD1 rs1950902 could affect embryonic development employing restricted DNA synthesis and a high level of homocysteine. Considering the results of the present study and the phenotypes related to rs1950902, we postulate that this polymorphism plays a role in fetal heart development. One previous study [24], however, found no evidence of a significant association between children’s MTHFD1 1,950,902 and Tetralogy of Fallot. Due to our limited sample size of each subtype of CHD cases, we didn’t analyze the association between specific CHD subtypes and genetic variants of maternal MTHFD1 gene. Besides, the present study modestly found the intronic polymorphisms including rs2236222, rs1256142 and rs11849530 were associated with increased CHD risk, and the plausible mechanism of these polymorphisms increasing CHD susceptibility was likely to affect codon usage and translational efficiency [57].

Particularly, it was worth mentioning that MTHFD1 rs2236225 (MTHFD1 R653Q), the most investigated genetic variant of the MTHFD1 gene, leads to an arginine (G allele) to glutamine (A allele) substitution in the MTHFD1 protein. Convincing evidence suggested that mutant type protein of MTHFD1 gene at rs2236225 caused significant DNA synthesis restriction [14] and increased homocysteine levels [17,18,19]. In addition, the specific CHD subtypes such as atrial septal defects [16], tetralogy of Fallot [58] and aortic stenosis [14] had been reported significant associations with children’ rs2236225, but previous efforts involved in their associations of children’ rs2236225 and CHD risk had yielded conflicting [14, 20, 22]. For the maternal MTHFD1 rs2236225, one previous study observed that maternal rs2236225 was associated with offspring CHD risk, and that rs2236225 was related to lower serum folic acid levels and higher homocysteine levels. However, neither Christensen KE’s nor our data revealed a significant association between maternal rs2236225 and offspring CHD risk. These inconclusive findings might result from the genetic differences between different populations of people, and might also partly be explained by the different susceptibility of folate-homocysteine imbalance to every subtype of CHD [7]. Evidence suggested that conotruncal defects and ventricular septal defects likely shared some etiologic and specifically genetic risk factors, and both were likely associated with disruption of the development of the cardiac neural crest, which was highly responsive to folate [7]. Overall, some of the polymorphisms involved in our study had not been confirmed before, and literature involved in the association between genetic variants of maternal MTHFD1 gene and CHD was still lack. It needs further and clearer evidence to figure out the mechanism.

We also examined the association between maternal smoking including active and passive smoking and the risk of CHD in offspring. Findings from the present study suggested that mothers who reported passive smoking at home or in the workplace 3 months before pregnancy and the first trimester of pregnancy were observed a 1.56-fold and 2.24-fold increased CHD risk, respectively, which was basically consistent with a recent meta-analysis [59]. Obviously, the maternal passive tobacco exposure in the first trimester of pregnancy was shown more harmful than in 3 months before pregnancy, which may be partly explained by the fact that the former was the sensitive period for fetal heart development. Additionally, a great number of previous epidemiologic studies supported that periconceptional active smoking was associated with risk of CHD in offspring [59]. However, we modestly did not observe that maternal active smoking in 3 months before pregnancy could increase CHD risk after adjusted potential confounders, and even none of our subjects reported active smoking during pregnancy. The causes for the insignificant association between maternal active smoking in 3 months before pregnancy and CHD risk may be due to our limited sample size and the subjective smoking records. There was a possibility that pregnant smokers underreported their smoking and such potential misclassification might lead to underestimation of the impact of maternal active smoking on CHD. The behavior was attributed to medical and societal pressures that made pregnant women reluctant to report their smoking activities [60].

Our results also showed the different degrees of interaction effects between polymorphisms of MTHFD1 gene including rs1950902, rs2236222, rs1256142, rs11849530 and rs2236225 and maternal passive smoking. However, studies concerning the interactions of SNPs in folate-related genes and maternal tobacco exposure were lack, Hobbs [42] indicated that the combined effect of elevations in maternal homocysteine, smoking, and the MTHFR CC genotype increased the risk of having a CHD-affected pregnancy (aOR = 11.8), compared with women who did not smoke, did not have an elevated homocysteine, and had the MTHFR 677 CC genotype served as the reference group. Possible mechanisms by which the MTHFD1 gene interacted with maternal tobacco exposure to increase CHD susceptibility include elevated serum homocysteine, increased DNA methylation, and DNA synthesis restriction. It was well-studied that the maternal tobacco exposure was observed associations with substantial reductions of folate levels [35,36,37, 40], elevated levels of homocysteine [61] in cord blood, and altered global genomic methylation. The polymorphisms of the MTHFD1 gene also showed a close relation to plasma homocysteine and DNA methylation. Hence, the mutant type of MTHFD1 protein and periconceptional tobacco exposure jointly caused the plasma homocysteine elevated, and high levels of homocysteine consequently affected fetal heart development by disruption of gene methylation, increasing oxidative stress and homocysteinylation of key proteins. Additionally, a recent study suggested that maternal folate-homocysteine metabolism may partly modify the influence of maternal tobacco exposure during pregnancy on the DNA methylation of newborn epigenome and therefore affected embryonic development [44], which provided indirect evidence to support our findings. Nevertheless, specific mechanisms were unclear and needed further research.

The limitations of the study need to be addressed. First, based on a case-control study, information on maternal tobacco exposure was collected through self-reported interviews, and therefore recall bias inevitably had to be taken into consideration. To reduce recall bias to some extent, the exposure information was further confirmed by consulting their Maternal and Child Health Manual and medical records. Second, despite adjusting many confounders, potential confounding factors cannot be entirely ruled out. Third, there are so many key enzyme genes in relation to folate metabolism pathway that are also involved in cardiovascular development, such as MTHFR, MTRR and MTR gene, but we only focused on the association between maternal MTHFD1 gene and offspring CHD risk. Fourth, even if the analyzed SNP is located in the MTHFD1 gene region, there may be SNPs in linkage disequilibrium in other gene regions, and the possibility that the SNPs are related to the function of the other gene cannot be denied. Fifth, considering population stratification bias in epidemiologic studies, we recruited the participants restricted to the Han Chinese ethnicity, and further work was needed to estimate the effect of the MTHFD1 gene and maternal tobacco exposure in CHD risk within other populations. Last, sample size limitations prevented us from examining specific CHD subtypes.

Conclusions

The current findings observed that maternal polymorphisms of the MTHFD1 gene at rs1950902, rs2236222, rs11849530, and rs1256142 were significantly associated with the risk of CHD in offspring. In addition, a positive association between maternal passive smoking in the periconceptional period and risk of CHD was found. Furthermore, our results showed the different degrees of interaction effects between polymorphisms of the MTHFD1 gene including rs1950902, rs2236222, rs1256142, rs11849530 and rs2236225, and maternal tobacco exposure. However, considering the complexity of the mechanism and the limitation of sample size, more studies in different ethnic populations with a larger sample and prospective designs were required to confirm our findings.

Availability of data and materials

The datasets supporting the conclusions of this article are included within the article and its additional files.

Abbreviations

CHD:

Congenital heart disease

aOR:

Adjusted odds ratio

CI:

Confidence interval

SNPs:

Single nucleotide polymorphisms

MTHFD1 :

Methylenetetrahydrofolate dehydrogenase 1

FDR_P :

False discovery rate P value

GMS:

Genetic model selection

HWE:

Hardy-Weinberg equilibrium

References

  1. Hoffman JIE, Kaplan S. The incidence of congenital heart disease. J Am Coll Cardiol. 2002;39(12):1890–900.

    Article  PubMed  Google Scholar 

  2. Botto LD, Correa A, Erickson JD. Racial and temporal variations in the prevalence of heart defects. Pediatrics. 2001;68(10):942–2.

    Google Scholar 

  3. Zhu H, Kartiko S, Finnell RH. Importance of gene-environment interactions in the etiology of selected birth defects. Clin Genet. 2009;75(5):409–23.

    Article  CAS  PubMed  Google Scholar 

  4. Bruneau BG. The developmental genetics of congenital heart disease. Nature. 2008;451(7181):943–8.

    Article  CAS  PubMed  Google Scholar 

  5. Jiang S, Wang J, Duan Y, Pang X, Bi Y, Zhang H, et al. Folic acid status and associated factors for pregnant Chinese women - China, 2015. China CDC weekly. 2021;3(11):226–31.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Li X, Li S, Mu D, Liu Z, Li Y, Lin Y, et al. The association between periconceptional folic acid supplementation and congenital heart defects: a case-control study in China. Prev Med. 2013;56(6):385–9.

    Article  PubMed  Google Scholar 

  7. Rosenquist TH. Folate, homocysteine and the cardiac neural crest. Dev Dyn. 2013;242(3):201–18.

    Article  CAS  PubMed  Google Scholar 

  8. Wang D, Jin L, Zhang J, Meng W, Ren A, Jin L. Maternal Periconceptional folic acid supplementation and risk for fetal congenital heart defects. J Pediatr. 2022;240:72–8.

    Article  PubMed  Google Scholar 

  9. Xu A, Cao X, Lu Y, Li H, Zhu Q, Chen X, et al. A Meta-analysis of the relationship between maternal folic acid supplementation and the risk of congenital heart defects. Int Heart J. 2016;57(6):725–8.

    Article  CAS  PubMed  Google Scholar 

  10. AC V-H, M V, NTC U: Maternal hyperhomocysteinaemia is a risk factor for congenital heart disease. BJOG 2006, 113(12):1412–1418.

  11. Hol FA, Put NMVD, Geurds MP, Heil SG, Trijbels FJ, Hamel BC, et al. Molecular genetic analysis of the gene encoding the trifunctional enzyme MTHFD (methylenetetrahydrofolate-dehydrogenase, methenyltetrahydrofolate-cyclohydrolase, formyltetrahydrofolate synthetase) in patients with neural tube defects. Clin Genet. 1998;53(2):119–25.

    Article  CAS  PubMed  Google Scholar 

  12. Blount BC, Mack MM, Wehr CM, MacGregor JT, Hiatt RA, Wang G, et al. Folate deficiency causes uracil misincorporation into human DNA and chromosome breakage: implications for cancer and neuronal damage. Proc Natl Acad Sci U S A. 1997;94(7):3290–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Castro R, Rivera I, Ravasco P, Camilo ME, Jakobs C, Blom HJ, de Almeida IT: 5,10-methylenetetrahydrofolate reductase (MTHFR) 677C-->T and 1298A-->C mutations are associated with DNA hypomethylation. J Med Genet 2004, 41(6):454–458.

  14. Christensen KE, Rohlicek CV, Andelfinger GU, Michaud J, Rozen R. The MTHFD1 p.Arg653Gln variant alters enzyme function and increases risk for congenital heart defects. Hum Mutat. 2009;30(2):212–20.

    Article  CAS  PubMed  Google Scholar 

  15. Christensen KE, Patel H, Kuzmanov U, Mejia NR, MacKenzie RE. Disruption of the mthfd1 gene reveals a monofunctional 10-formyltetrahydrofolate synthetase in mammalian mitochondria. J Biol Chem. 2005;280(9):7597–602.

    Article  CAS  PubMed  Google Scholar 

  16. Cheng J, Zhu WL, Dao JJ, Li SQ, Li Y. Relationship between polymorphism of methylenetetrahydrofolate dehydrogenase and congenital heart defect. Biomed Environ Sci. 2005;18(1):58–64.

    CAS  PubMed  Google Scholar 

  17. Li Y, Cheng J, Zhu WL, Dao JJ, Yan LY, Li MY, et al. Study of serum Hcy and polymorphisms of Hcy metabolic enzymes in 192 families affected by congenital heart disease. Beijing Da Xue Xue Bao. 2005;37(1):75–80.

    PubMed  Google Scholar 

  18. Wang L, Ke Q, Chen W, Wang J, Tan Y, Zhou Y, et al. Polymorphisms of MTHFD, plasma homocysteine levels, and risk of gastric cancer in a high-risk Chinese population. Clin Cancer Res. 2007;13(8):2526–32.

    Article  CAS  PubMed  Google Scholar 

  19. Wernimont SM, Clark AG, Stover PJ, Wells MT, Litonjua AA, Weiss ST, et al. Folate network genetic variation, plasma homocysteine, and global genomic methylation content: a genetic association study. BMC Med Genet. 2011;12:150.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Brody LC, Conley M, Cox C, Kirke PN, McKeever MP, Mills JL, et al. A polymorphism, R653Q, in the trifunctional enzyme methylenetetrahydrofolate dehydrogenase/methenyltetrahydrofolate cyclohydrolase/formyltetrahydrofolate synthetase is a maternal genetic risk factor for neural tube defects: report of the birth defects research group. Am J Hum Genet. 2002;71(5):1207–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Emilio ALG, Cresci M, Ait-Ali L, Foffa I, Grazia Andreassi M. Smoking and congenital heart disease: the epidemiological and biological link. Curr Pharm Des. 2010;16(23):2572–7.

    Article  Google Scholar 

  22. Shaw GM, Lu W, Zhu H, Yang W, Briggs FB, Carmichael SL, et al. 118 SNPs of folate-related genes and risks of spina bifida and conotruncal heart defects. BMC Med Genet. 2009;10:49.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Wang B, Liu M, Yan W, Mao J, Jiang D, Li H, et al. Association of SNPs in genes involved in folate metabolism with the risk of congenital heart disease. J Matern Fetal Neonatal Med. 2013;26(18):1768–77.

    Article  CAS  PubMed  Google Scholar 

  24. Xu J, Xu X, Xue L, Liu X, Gu H, Cao H, et al. MTHFR c.1793G>a polymorphism is associated with congenital cardiac disease in a Chinese population. Cardiol Young. 2010;20(3):318–26.

    Article  PubMed  Google Scholar 

  25. Gong D, Gu H, Zhang Y, Gong J, Nie Y, Wang J, et al. Methylenetetrahydrofolate reductase C677T and reduced folate carrier 80 G>a polymorphisms are associated with an increased risk of conotruncal heart defects. Clin Chem Lab Med. 2012;50(8):1455–61.

    Article  CAS  PubMed  Google Scholar 

  26. Khatami M, Ratki FM, Tajfar S, Akrami F. Relationship of the MTHFD1 (rs2236225), eNOS (rs1799983), CBS (rs2850144) and ACE (rs4343) gene polymorphisms in a population of Iranian pediatric patients with congenital heart defects. Kaohsiung J Med Sci. 2017;33(9):442–8.

    Article  PubMed  Google Scholar 

  27. Jiang YC, Kuang LL, Sun SN, Duan WY, Qiao B, Wang HY. Association of genetic polymorphisms of de novo nucleotide biosynthesis with increased CHD susceptibility in the northern Chinese population. Clin Genet. 2017;91(5):748–55.

    Article  CAS  PubMed  Google Scholar 

  28. van Mil NH, Oosterbaan AM, Steegers-Theunissen RP. Teratogenicity and underlying mechanisms of homocysteine in animal models: a review. Reprod Toxicol. 2010;30(4):520–31.

    Article  PubMed  Google Scholar 

  29. Deng K, Liu Z, Lin Y, Mu D, Chen X, Li J, et al. Periconceptional paternal smoking and the risk of congenital heart defects: a case-control study. Birth Defects Res A Clin Mol Teratol. 2013;97(4):210–6.

    Article  CAS  PubMed  Google Scholar 

  30. Malik S, Cleves MA, Honein MA, Romitti PA, Botto LD, Yang S, et al. Maternal smoking and congenital heart defects. Pediatrics. 2008;121(4):e810–6.

    Article  PubMed  Google Scholar 

  31. Patel SS, Burns TL, Botto LD, Riehle-Colarusso TJ, Lin AE, Shaw GM, Romitti PA: Analysis of selected maternal exposures and non-syndromic atrioventricular septal defects in the National Birth Defects Prevention Study, 1997–2005. Am J Med Genet A 2012, 158a(10):2447–2455.

  32. Alverson CJ, Strickland MJ, Gilboa SM, Correa A. Maternal smoking and congenital heart defects in the Baltimore-Washington infant study. Pediatrics. 2011;127(3):e647–53.

    Article  PubMed  Google Scholar 

  33. Karatza AA, Giannakopoulos I, Dassios TG, Belavgenis G, Mantagos SP, Varvarigou AA. Periconceptional tobacco smoking and isolated congenital heart defects in the neonatal period. Int J Cardiol. 2011;148(3):295–9.

    Article  PubMed  Google Scholar 

  34. Shi M, Wehby GL, Murray JC. Review on genetic variants and maternal smoking in the etiology of oral clefts and other birth defects. Birth defects research Part C, Embryo today : reviews. 2008;84(1):16–29.

    Article  CAS  Google Scholar 

  35. Gabriel HE, Crott JW, Ghandour H, Dallal GE, Choi SW, Keyes MK, et al. Chronic cigarette smoking is associated with diminished folate status, altered folate form distribution, and increased genetic damage in the buccal mucosa of healthy adults. Am J Clin Nutr. 2006;83(4):835–41.

    Article  CAS  PubMed  Google Scholar 

  36. Okumura K, Tsukamoto H. Folate in smokers. Clin Chim Acta. 2011;412(7–8):521–6.

    Article  CAS  PubMed  Google Scholar 

  37. Stark KD, Pawlosky RJ, Sokol RJ, Hannigan JH, Salem N Jr. Maternal smoking is associated with decreased 5-methyltetrahydrofolate in cord plasma. Am J Clin Nutr. 2007;85(3):796–802.

    Article  CAS  PubMed  Google Scholar 

  38. Piyathilake CJ, Hine RJ, Dasanayake AP, Richards EW, Freeberg LE, Vaughn WH, et al. Effect of smoking on folate levels in buccal mucosal cells. Int J Cancer. 1992;52(4):566–9.

    Article  CAS  PubMed  Google Scholar 

  39. Walmsley CM, Bates CJ, Prentice A, Cole TJ. Relationship between cigarette smoking and nutrient intakes and blood status indices of older people living in the UK: further analysis of data from the National Diet and nutrition survey of people aged 65 years and over, 1994/95. Public Health Nutr. 1999;2(2):199–208.

    Article  CAS  PubMed  Google Scholar 

  40. Piyathilake CJ, Macaluso M, Hine RJ, Vinter DW, Richards EW, Krumdieck CL. Cigarette smoking, intracellular vitamin deficiency, and occurrence of micronuclei in epithelial cells of the buccal mucosa. Cancer Epidemiol Biomark Prev. 1995;4(7):751–8.

    CAS  Google Scholar 

  41. Yila TA, Sasaki S, Miyashita C, Braimoh TS, Kashino I, Kobayashi S, et al. Effects of maternal 5,10-methylenetetrahydrofolate reductase C677T and A1298C polymorphisms and tobacco smoking on infant birth weight in a Japanese population. J Epidemiol. 2012;22(2):91–102.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Hobbs CA, James SJ, Jernigan S, Melnyk S, Lu YX, Malik S, et al. Congenital heart defects, maternal homocysteine, smoking, and the 677 C > T polymorphism in the methylenetetrahydroflate reductase gene: evaluating gene-environment interactions. Am J Obstet Gynecol. 2006;194(1):218–24.

    Article  CAS  PubMed  Google Scholar 

  43. McDonald SD, Perkins SL, Jodouin CA, Walker MC. Folate levels in pregnant women who smoke: an important gene/environment interaction. Am J Obstet Gynecol. 2002;187(3):620–5.

    Article  CAS  PubMed  Google Scholar 

  44. Zhang B, Hong X, Ji H, Tang W-Y, Kimmel M, Ji Y, et al. Maternal smoking during pregnancy and cord blood DNA methylation: new insight on sex differences and effect modification by maternal folate levels. Epigenetics. 2018;13(5):505–18.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Botto LD, Lin AE, Riehle-Colarusso T, Malik S, Correa A. Seeking causes: classifying and evaluating congenital heart defects in etiologic studies. Birth Defects Res A Clin Mol Teratol. 2007;79(10):714–27.

    Article  CAS  PubMed  Google Scholar 

  46. Batra M, Heike CL, Phillips RC, Weiss NS. Geographic and occupational risk factors for ventricular septal defects: Washington state, 1987-2003. Arch Pediatr Adolesc Med. 2007;161(1):89–95.

    Article  PubMed  Google Scholar 

  47. Li Y, Diao J, Li J, Luo L, Zhao L, Zhang S, et al. Association of maternal dietary intakes and CBS gene polymorphisms with congenital heart disease in offspring. Int J Cardiol. 2021;322:121–8.

    Article  PubMed  Google Scholar 

  48. Zhang S, Wang L, Yang T, Chen L, Zhao L, Wang T, et al. Parental alcohol consumption and the risk of congenital heart diseases in offspring: an updated systematic review and meta-analysis. Eur J Prev Cardiol. 2020;27(4):410–21.

    Article  PubMed  Google Scholar 

  49. Liu Z, Li X, Li N, Li S, Deng K, Lin Y, et al. Association between maternal exposure to housing renovation and offspring with congenital heart disease: a multi-hospital case-control study. Environ Health. 2013;12:25.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Gianicolo EA, Mangia C, Cervino M, Bruni A, Andreassi MG, Latini G: Congenital anomalies among live births in a high environmental risk area--a case-control study in Brindisi (southern Italy). Environ Res 2014, 128:9–14.

  51. Xiu XH, Yuan L, Wang XM, Chen YH, Wan AH, Fu P. Case-control study on influence factors of birth defects. Zhonghua Fu Chan Ke Za Zhi. 2011;46(7):481–6.

    PubMed  Google Scholar 

  52. Nie ZQ, Ou YQ, Chen JM, Liu XQ, Mai JZ, Gao XM, et al. Risk factors of congenital heart defects in fetal and infants born from 2004 to 2011 in Guangdong. Zhonghua xin xue guan bing za zhi. 2013;41(8):704–8.

    PubMed  Google Scholar 

  53. Zheng G, Ng HKT. Genetic model selection in two-phase analysis for case-control association studies. Biostatistics. 2008;9(3):391–9.

    Article  PubMed  Google Scholar 

  54. Keller MC. Gene × environment interaction studies have not properly controlled for potential confounders: the problem and the (simple) solution. Biol Psychiatry. 2014;75(1):18–24.

    Article  PubMed  Google Scholar 

  55. National Bureau of Statistics of China. http://www.stats.gov.cn/. Accessed 4 January 2013.

  56. Zhao JY, Yang XY, Gong XH, Gu ZY, Duan WY, Wang J, et al. Functional variant in methionine synthase reductase intron-1 significantly increases the risk of congenital heart disease in the Han Chinese population. Circulation. 2012;125(3):482–90.

    Article  CAS  PubMed  Google Scholar 

  57. Molloy AM, Brody LC, Mills JL, Scott JM, Kirke PN. The search for genetic polymorphisms in the homocysteine/folate pathway that contribute to the etiology of human neural tube defects. Birth Defects Res A Clin Mol Teratol. 2009;85(4):285–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Huang J, Mei J, Jiang L, Jiang Z, Liu H, Ding F. MTHFR rs1801133 C>T polymorphism is associated with an increased risk of tetralogy of Fallot. Biomedical reports. 2014;2(2):172–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Zhao L, Chen L, Yang T, Wang L, Wang T, Zhang S, et al. Parental smoking and the risk of congenital heart defects in offspring: an updated meta-analysis of observational studies. Eur J Prev Cardiol. 2019;27(12):1284–93.

    Article  PubMed  Google Scholar 

  60. Swamy GK. Reliance on self-reporting underestimates pregnancy smoking rates in Scotland, with more than 2400 pregnant smokers estimated to be missed annually. Evid Based Nurs. 2010;13(2):60–1.

    Article  PubMed  Google Scholar 

  61. Tuenter A, Nino PKB, Vitezova A, Pantavos A, Bramer WM, Franco OH, et al. Folate, vitamin B12, and homocysteine in smoking-exposed pregnant women: a systematic review. Maternal And Child Nutrition. 2019. https://doi.org/10.1111/mcn.12675.

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Acknowledgements

The authors would like to thank the editors and reviewers for their suggestions and all colleagues working in Maternal and Child Health Promotion and Birth Defect Prevention Group.

Funding

This study was supported by the Project Funded by National Natural Science Foundation Program of China [82073653 and 81803313], Hunan Provincial Key Research and Development Program [2018SK2063 and 2018SK2062], Hunan Provincial Science and Technology Talent Support Project [2020TJ-N07], Natural Science Foundation of Hunan Province [2018JJ2551], and Open Project from NHC Key Laboratory of Birth Defect for Research and Prevention [KF2020006].

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Authors and Affiliations

  1. Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, 110 Xiangya Road, Changsha, 410078, Hunan, China

    Xinli Song, Qiongxuan Li, Jingyi Diao, Jinqi Li, Yihuan Li, Senmao Zhang, Lijuan Zhao, Letao Chen, Jianhui Wei, Jing Shu, Yiping Liu, Mengting Sun & Jiabi Qin

  2. Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China

    Jiabi Qin

  3. NHC Key Laboratory of Birth Defect for Research and Prevention, Hunan Provincial Maternal and Child Health Care Hospital, 53 Xiangchun Road, Changsha, 410028, Hunan, China

    Tingting Wang & Jiabi Qin

  4. Hunan Provincial Key Laboratory of clinical epidemiology, Changsha, Hunan, China

    Jiabi Qin

  5. Department of Cardiothoracic Surgery, Hunan Children’s Hospital, Changsha, Hunan, China

    Peng Huang

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  1. Xinli Song
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Contributions

QXL, JYD, JQL and YHL performed the experiments. SMZ and LJZ analyzed the data and statistical analyses. JS, YPL and MTS contributed reagents/material/analysis tools. XLS, TTW and JBQ wrote the main manuscript text. PH, LTC, JHW and MTS collected reference and managed data. The author(s) read and approved the final manuscript.

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Correspondence to Tingting Wang or Jiabi Qin.

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This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Xiangya School of Public Health Central South University (No. XYGW-2018-36). Informed consent was obtained from all subjects involved in the study.

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Song, X., Li, Q., Diao, J. et al. Association of MTHFD1 gene polymorphisms and maternal smoking with risk of congenital heart disease: a hospital-based case-control study. BMC Pregnancy Childbirth 22, 88 (2022). https://doi.org/10.1186/s12884-022-04419-2

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BMC Pregnancy and Childbirth

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