Association between maternal MTHFR and MTRR gene polymorphisms and the risk of congenital heart disease in newborns

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This study aimed to investigate the association between maternal polymorphisms in MTHFR (rs1801133 and rs1801131) and MTRR (rs1801394) and the risk of neonatal CHD in the Chinese Han population from southern Fujian. Methods: We conducted a case–control study involving 155 mothers of neonates with CHD and 160 healthy controls. Three SNPs were genotyped using Sanger sequencing. Results: Our study showed that maternal polymorphisms of MTHFR at rs1801133 and MTRR at rs1801394 were significantly associated with risk of neonatal CHD in the homozygote comparisons (TT vs. CC at rs1801133: OR=2.346 [95% CI: 1.014–5.428]; GG vs. AA at 1801394: OR=3.127 [95% CI: 1.232–7.940]), as well as heterozygote comparison (CT vs. CC at rs1801133: OR=1.778 [95% CI: 1.107–2.856]) with mutant allele associated with a higher risk of CHDs (T vs. C at rs1801133: OR=1.665 [95% CI: 1.168-2.371]; G vs. A at 1801394: OR=1.588 [95% CI: 1.114-2.261]). Maternal polymorphisms were significantly associated with CHD subtypes: ASD risk was higher in TG vs. TT of MTHFR at rs1801131: OR=2.083 [95% CI: 1.185-3.662] and AG vs. AA of MTRR at rs1801394: OR=1.815 [95% CI: 1.043-3.156]; VSD risk was higher in GG vs. AA of MTRR at rs1801394 (OR = 3.837 [95% CI: 1.169–12.594])and CT vs. CC of MTHFR at 1801133: OR=2.094 [95% CI: 1.019-4.302]); PDA risk was higher in TT vs. CC of MTHFR at 1801133: OR=4.287 [95% CI: 1.426-12.893]. Mothers with the TT genotype at rs1801133 of the MTHFR gene had significantly higher serum Hcy levels than those with the CC or CT genotypes, and with the GG genotype at rs1801394 of MTRR higher than those with the AA genotype (all P < 0.05). Conclusion: Maternal polymorphisms in MTHFR rs1801133 and MTRR rs1801394 are significantly associated with elevated maternal serum Hcy levels and increased risk of neonatal CHD, including ASD, VSD, and PDA, in the Chinese Han population of southern Fujian. MTHFR rs1801131 polymorphism was significantly associated with neonatal ASD risk. Trial registration: Our study is an observational study. According to the International Committee of Medical Journal Editors (ICMJE), purely observational studies (in which the allocation of medical interventions is not under the investigator's discretion) do not require registration. Congenital heart disease MTHFR MTRR Polymorphisms homocysteine neonates Background Congenital heart disease (CHD) is the most prevalent human birth defect, with an incidence rate of approximately 0.8–1.2% of liveborn infants worldwide [ 1 ], and remains a leading cause of mortality in childhood. The prevalence of CHD is relatively high in Asian countries [ 2 ], making it a significant public health concern in the region. CHD is a heterogeneous condition resulting from the complex interplay between genetic and environmental factors [ 3 ]. Several maternal environmental factors, both extrinsic and intrinsic, including deficiencies in folic acid and other essential vitamins, are associated with the risk of CHD [ 4 ]. Numerous case–control studies and meta-analyses have reported associations between single nucleotide polymorphisms (SNPs) in parental genes, particularly those involved in folate/homocysteine (Hcy) metabolism, and an elevated risk of CHD in offspring [ 5 – 18 ], especially in Asian populations [ 5 ]. These findings suggest that maternal genotypes may serve as independent risk factors for CHD by influencing foetal development via altered folate/Hcy metabolism. However, not all studies have reported statistically significant associations [ 7 , 8 , 18 ], some studies have reported contradictory results [ 5 , 9 , 10 ]. Among the folate-related genes associated with CHD, 5,10-methylenetetrahydrofolate reductase (MTHFR) is one of the most widely studied. MTHFR encodes a key enzyme in the Hcy metabolic pathway [ 11 ], catalysing the conversion of MTHFR to 5-methyltetrahydrofolate (5-MTHF), which serves as the primary methyl donor for Hcy demethylation to produce methionine, and this conversion prevents Hcy accumulation, which is associated with developmental abnormalities [ 12 , 13 ]. The potential link between MTHFR gene polymorphisms and CHD risk was first proposed in 2001 [ 14 ], Subsequently, the effects of parental MTHFR gene polymorphisms on the risk of CHD in offspring have gained considerable attention. Consequently, MTHFR gene polymorphisms rs1801133 and/or rs1801131 were identified as high risk factors for CHD in offspring [ 5 , 10 , 15 – 17 , 19 , 20 ]. However, the findings remain inconsistent [ 5 , 10 ]. Some meta-analyses have reported a positive association between parental MTHFR variants rs1801133 [ 6 , 9 , 21 – 24 ] or rs1801131 [ 25 ], and CHD risk, while others have found no significant relationship between rs1801133 [ 8 ] or rs1801131 [ 9 ] and CHD risk. Methionine synthase reductase (MTRR) is another key regulatory enzyme involved in the metabolism of Hcy. MTRR functions as a cofactor for methionine synthase, maintaining its activity by reducing vitamin B12 to ensure the remethylation of Hcy to methionine. Methionine synthase catalyses the conversion of plasma Hcy to methionine and tetrahydrofolate, effectively reducing plasma Hcy levels. MTRR deficiency may result in hyperhomocysteinemia, which is a risk factor for congenital anomalies. The parental MTRR rs1801394 polymorphism has been linked to CHD, several studies have reported a possible association with an increased risk in offspring [ 15 , 17 , 26 ], however, conflicting results have been previously reported [ 7 , 10 , 18 , 19 ]. Given the inconsistent evidence in the literature, it remains unclear whether maternal MTHFR and MTRR polymorphisms contribute to the risk of CHD in offspring. These discrepancies may be due to variations in sample size, CHD subtypes, and the ethnic or regional backgrounds of the studied populations. Therefore, this study aimed to investigate the associations between maternal polymorphisms in MTHFR (rs1801133 and rs1801131) and MTRR (rs1801394) and the risk of neonatal acyanotic CHD and its subtypes in the Chinese Han population of Southern Fujian. Methods Study participants This hospital-based case–control study was conducted between January 2023 and December 2024, as previously described [27]. A total of 315 mothers were recruited from two hospitals: the Neonatology Department of Quanzhou First Hospital, affiliated with Fujian Medical University, and the Reproductive Medicine Center of the First Affiliated Hospital of Xiamen University. The study included 160 mothers of healthy neonates (control group) and 155 mothers of neonates diagnosed with acyanotic CHD (CHD group). CHD cases were further classified into three subtypes: atrial septal defect (ASD, n = 84), ventricular septal defect (VSD, n = 42), and patent ductus arteriosus (PDA, n = 34)). Some neonates were diagnosed with multiple CHD subtypes; therefore, the total number of CHD subtype cases exceeded 155. CHD diagnosis was confirmed using echocardiography and/or surgery. All eligible mothers were of Han Chinese descent, had singleton pregnancies, provided complete questionnaire data, and provided blood samples. The exclusion criteria included structural malformations involving other organ systems or known chromosomal abnormalities in neonates. Informed consent was obtained from all the participants. The study was approved by the Medical Ethics Committee of Quanzhou First Hospital, affiliated with Fujian Medical University [Approval Number: 2023K070]. Clinical parameters A questionnaire was developed for this study. Professionally trained investigators conducted face-to-face interviews to obtain maternal and neonatal clinical data. The collected maternal data included age, history of abnormal pregnancies (e.g. abortion, foetal death or stillbirth, and preterm birth), family history (e.g. consanguineous marriages and congenital malformations), lifestyle factors within 3 months before pregnancy (e.g. active/passive smoking and alcohol consumption), and medical history (e.g. folic acid supplementation and the use of macrolide antibiotics or antiviral drugs). Neonatal data included sex, gestational age at birth, birth height and weight, mode of delivery, and clinical CHD classification. Blood sample collection Peripheral venous blood samples were collected from each mother. The samples were processed using centrifugation (2–8 ℃, 1000 rpm, 15 min). Plasma and blood cells were separated, aliquoted into high-pressure sterilised EP tubes, labelled, and stored at -80 °C until further analysis. Tag SNP selection Candidate tag SNPs were selected based on a literature review and data obtained from the PubMed and Chinese HapMap (http://hapmap.ncbi.nlm.nih.gov/) databases. Tag SNPs were identified using Haploview 4.2, with selection thresholds of pairwise r 2 ≥ 0.8 and minor allele frequency ≥ 1%. Based on these selection criteria, three SNPs (MTHFR variants: rs1801133 and rs1801131 and MTRR variants: rs1801394) associated with the Hcy/folate pathway in the Han Chinese population were selected. DNA Extraction and Genotyping Genomic DNA was extracted from blood cells using a Sangon Biotech DNA Extraction Kit (Shanghai, China). Genotyping of the selected tag SNPs was performed using Sanger sequencing, as previously described [27]. PCR primer sequences and amplification parameters are listed in Table 1. Measurement of s erum H cy levels Serum Hcy levels in maternal samples were measured using a commercial enzymatic cycling assay kit (Human Homocysteine Detection Kit; LOT:AUZ3522; Beckman Coulter, Suzhou, China). All procedures were performed according to the manufacturer’s instructions. Statistical analysis All statistical analyses were performed using SPSS software (version 26.0; SPSS, Chicago, IL, USA). Hardy–Weinberg equilibrium was assessed for each SNP in the control group. Continuous variables were tested for normality and expressed as mean ± standard deviation (x ± s). Intergroup comparisons were performed using independent sample t-tests. Categorical variables are expressed as frequencies (%). Group comparisons were performed using the chi-square (χ 2 ) or Fisher’s exact tests. Binary logistic regression analysis was conducted to estimate the odds ratio (OR) and 95% confidence interval (CI) for the association between maternal genetic polymorphisms and the risk of overall CHD and its subtypes. P < 0.05 (two-tailed) was considered statistically significant. Results Maternal and Neonatal Baseline Characteristics No statistically significant differences were observed between the CHD and control groups regarding maternal characteristics, including age, history of abnormal pregnancy, family history of congenital conditions, personal lifestyle factors within 3 months before pregnancy, or medical history during pregnancy (P > 0.05) (Table 2). Similarly, neonatal baseline characteristics, including sex, gestational age at birth, birth height, birth weight, and mode of delivery, did not differ significantly between the two groups (P > 0.05) (Table 3). Hardy–Weinberg equilibrium The genotype distributions of maternal MTHFR and MTRR SNPs were consistent with Hardy–Weinberg genetic equilibrium in both the control and CHD groups, suggesting that the study population was genetically representative of the general population (P > 0.05) (Table 4). Association of maternal MTHFR and MTRR gene polymorphisms with neonatal CHD risk The maternal genotype and allele frequencies of MTHFR (rs1801133, rs1801131) and MTRR (rs1801394) polymorphisms are presented in Table 5. The genotypic and allelic frequencies of MTHFR (rs1801133, rs1801131) and MTRR (rs1801394) polymorphisms are presented in Table 5. For MTRR rs1801133, genotype frequencies for CT, TT, and CT+TT were 43.23%, 10.97%, and 54.19% in the CHD group, compared to 32.5%, 6.25%, and 38.75% in the control group, the OR of CT vs.CC was 1.778 (95% CI: 1.107–2.856) with P = 0.017, the OR of TT vs.CC was 2.346(95% CI: 1.014–5.428) with P = 0.046, and the OR of CT+TT vs. CC was 1.870 (95% CI: 1.194–2.928) with P = 0.006, the frequency of the T allele in the CHD group was higher than that in the control group, and the T allele was significantly associated with increased CHD risk (OR, 1.665; 95% CI: 1.168–2.371, P = 0.005) compared to the C allele. For MTHFR rs1801131, no significant differences in genotype or allele frequencies were observed between the groups ( P > 0.05). For MTRR rs1801394, GG and AG+GG genotypes were more frequent in the CHD group (10.97% and 52.90%, respectively) than in the control group (4.38% and 41.25%, respectively), the OR of GG vs. AA was 3.127 (95% CI: 1.232–7.940) with P = 0.016 and the OR of AG+GG vs. AA was 1.600 (95% CI: 1.025–2.498) with P = 0.039, the frequency of the G allele in the CHD group was higher than that in the control group, and the G allele was significantly associated with a higher CHD risk than the A allele (OR, 1.588; 95% CI, 1.114–2.261; P = 0.010). Associations of maternal MTHFR and MTRR genetic polymorphisms with CHD subtypes The logistic regression analysis for the association between maternal gene polymorphisms and specific CHD subtypes is summarised in Table 6. We observed that the maternal MTHFR gene polymorphism at rs1801133 was significantly associated with the risk of two neonatal CHD subtypes: VSD (OR of CT vs. CC = 2.094 [95% CI: 1.019–4.302], P = 0.044; OR of CT+TT vs. CC = 2.108 [95% CI: 1.058–4.197], P = 0.034; OR of T vs. C = 1.722 [95% CI: 1.020–2.909], P = 0.042 ) and PDA (OR of TT vs. CC = 4.287 [95% CI: 1.426–12.893], P = 0.010; OR of T vs. C = 2.003 [95% CI: 1.146–3.500], P = 0.015 ). The maternal MTHFR variant at rs1801131 was significantly associated only with the risk of neonatal ASD (OR of TG vs. TT was 2.083 [95% CI: 1.185–3.662], P = 0.011; OR of TG+GG vs. TT = 2.111 [95% CI: 1.217–3.662], P = 0.008; OR of G vs. T = 1.829 [95% CI: 1.147–2.918], P = 0.011). Additionally, the maternal MTRR variant at rs1801394 was significantly associated with the risk of two neonatal CHD subtypes: ASD (OR of AG vs. AA = 1.815 [95% CI: 1.043–3.156], P = 0.035; OR of AG+GG vs. AA = 1.899 [95% CI: 1.113–3.241], P = 0.019; OR of G vs. A = 1.647 [95% CI: 1.088–2.493], P = 0.018) and VSD (OR of GG vs. AA = 3.837 [95% CI: 1.169–12.594], P = 0.027). Serum Hcy levels and genotype associations Analysis of maternal serum Hcy levels revealed that mothers with the TT genotype at MTHFR rs1801133 had significantly higher serum Hcy levels than those with the CC or CT genotypes ( P < 0.05) (Table 7). Mothers with the GG genotype at MTRR rs1801394 had significantly higher serum Hcy levels than those with the AA genotype ( P < 0.05). Discussion The aetiology of CHD is multifactorial, involving complex interactions between genetic and environmental factors. Among these, maternal genetic effects, in which the maternal genotype affects the intrauterine environment, significantly impact foetal developmental disorders, acting as an environmental risk factor for CHD and other congenital disorders [ 28 , 29 ]. Understanding these maternal genetic contributions is essential for elucidating the pathogenesis of CHD. Folate plays a crucial role in embryonic development and is associated with a reduced risk of CHD in offspring, particularly in Asian populations [ 14 , 21 , 30 – 32 ]. Maternal periconceptional folic acid supplementation may lower the risk of CHD in offspring by up to 40% [ 33 – 36 ], with significant protective effects against septal defects, such as VSD and ASD [ 37 – 40 ]. Individualised folic acid supplementation strategies based on maternal genetic polymorphisms may be more effective than uniform approaches in preventing adverse pregnancy outcomes and neonatal CHD [ 30 ]. While the precise mechanisms linking maternal folate levels to foetal CHD risk remain unclear, they likely involve the maternal capacity to produce active folate metabolites. This capacity is influenced by maternal genetic variants in the folate/Hcy metabolism pathways [ 4 ]. Impaired maternal folate metabolism may disrupt the development of foetal cardiac neural crest cells (CNCs), which play a key role in cardiac outflow tract morphogenesis. The demand for active folate increases dramatically during early embryogenesis [ 4 , 21 ]. Additionally, altered folate metabolism may indirectly affect CNC development by modulating Hcy levels [ 4 ]. Previous studies have shown that maternal polymorphisms in key enzymes involved in folate metabolism may alter foetal susceptibility to CHD by affecting maternal folate/Hcy homeostasis; however, these findings have not been consistent [ 21 , 41 – 45 ]. Our study observed that mothers of children with CHD had significantly higher serum Hcy levels than controls, which is consistent with previous findings in Chinese Han populations [ 42 ]. Among the folate-related SNPs, the most extensively studied are MTHFR rs1801133 and rs1801131. Despite more than two decades of research, evidence regarding their association with CHD remains inconclusive [ 6 , 8 , 9 , 21 – 25 ]. The MTHFR gene, located at 1p36.22, spans 20,733 bases and encodes a 656-amino-acid enzyme. The rs1801133 polymorphism (C677T) leads to a missense mutation, replacing alanine with valine, and results in reduced enzyme activity, approximately 70% in TT homozygotes and 35% in CT heterozygotes [ 20 ]. Individuals with the TT genotype exhibit lower serum folate levels [ 21 , 43 – 45 ] and elevated Hcy levels [ 43 ]. In our study, the T allele as well as the CT, TT, and GT + TT genotypes of MTHFR at rs1801133 were significantly higher in mothers in the CHD group than in the controls. Maternal rs1801133 polymorphisms were significantly associated with an increased risk of total CHD and specific subtypes, including VSD and PDA. Compared with those with the CC or CT genotype, those with the TT genotype had significantly higher serum Hcy levels, supporting the hypothesis that this variant contributes to CHD susceptibility through impaired folate metabolism. These findings suggest that the T allele and CT/TT genotypes at rs1801133 may contribute to genetic susceptibility in offspring with CHD and could partially explain the elevated Hcy levels observed in mothers who give birth to offspring with CHD. These results are consistent with those of previous studies [ 15 – 17 , 19 , 26 ] and meta-analyses [ 6 , 9 , 21 – 24 ] demonstrated an association between maternal rs1801133 polymorphisms and CHD risk in offspring. However, contradictory findings have been reported [ 5 , 8 , 10 ]. The rs1801131 polymorphism (A1298C) results in a glutamate-to-alanine substitution and reduces MTHFR enzymatic activity by approximately 40% in homozygotes and 20% in heterozygotes [ 4 ]. However, a study in healthy Japanese women found no significant association between rs1801131 and serum folate or Hcy levels [ 46 ]. Case-control studies and meta-analyses exploring the association between maternal rs1801131 polymorphisms and offspring CHD have yielded conflicting results, some reported no association [ 6 , 9 , 15 , 17 ], while others suggested a significant link [ 5 , 10 , 25 , 26 ]. Our findings showed no overall association between the maternal rs1801131 polymorphism and total CHD risk or maternal Hcy levels; however, a significant association was observed between rs1801131 and the ASD subtype. The MTRR gene is located at 5p15.31 and spans 55,167 bases, encoding 698 amino acids. The MTRR rs1801394 polymorphism involves an A-to-G missense mutation, resulting in a methionine-to-isoleucine substitution. This variant may lead to impaired methylation processes, DNA hypomethylation, impaired formation of methylated tetrahydrofolate, reduced serum folate levels, and elevated serum Hcy concentrations [ 47 ]. Although one study in healthy Japanese women reported no association between rs1801394 and serum folate or Hcy levels [ 4 ]. Our findings indicate that the maternal rs1801394 polymorphism is significantly associated with an increased risk of total CHD, as well as ASD and VSD subtypes in the offspring. Homozygous variant carriers had higher serum Hcy levels than wild-type individuals, suggesting that rs1801394 may be a maternal genetic risk factor for CHD and may partially account for elevated maternal Hcy concentrations in the CHD group. These findings are consistent with previous studies linking maternal rs1801394 to CHD [ 15 , 26 ] and are further supported by subtype-specific studies [ 17 ], however, conflicting findings have been reported [ 7 , 10 , 18 , 19 ]. Discrepancies across studies, including those in our study, may be attributed to several factors. Population differences in ethnicity and geographic location may affect the genotype distribution. Additionally, CHD is a heterogeneous disease arising from interactions between multiple genes and environmental exposures, making it difficult to attribute causality to any single variant. Sample size limitations and differences in study design could have contributed to inconsistent findings. This study had several limitations. First, only three CHD subtypes were evaluated because of the limited sample size. Second, we did not stratify the participants based on the timing and dosage of maternal folic acid intake, which limited our ability to explore gene-environment interactions. Future studies should focus on larger multi-centre cohorts and incorporate analyses of both gene-gene and gene-environment interactions in relation to offspring CHD risk. Conclusions Our study demonstrated that maternal polymorphisms in MTHFR rs1801133 and MTRR rs1801394 were significantly associated with elevated maternal serum Hcy levels and an increased risk of total CHD and specific subtypes (ASD, VSD, and PDA) in the offspring of Han Chinese in southern Fujian. Additionally, the MTHFR rs1801131 polymorphism was significantly associated with ASD risk in offspring. These findings provide new insights into the maternal genetic contributions to CHD and highlight the need for further large-scale studies to validate these associations and explore potential gene-environment interactions. Abbreviations CHD congenital heart disease SNPs single nucleotide polymorphisms Hcy homocysteine MTHFR 5,10-methylenetetrahydrofolate reductase 5-MTHF 5-methyltetrahydrofolate MTRR Methionine synthase reductase ASD atrial septal defect VSD ventricular septal defect PDA patent ductus arteriosus OR odds ratio CI confidence interval CNCs cardiac neural crest cells Declarations Clinical trial number Not applicable. Ethics approval and consent to participate This study was reviewed and approved by the Medical Ethics Committee of Quanzhou First Hospital Affiliated to Fujian Medical University [Quanzhou First Hospital Affiliated to Fujian Medical University Ethics Censorship: 2023K070]. A written informed consent was obtained from all participants in the study. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported by grants from the Natural Science Foundation project of Fujian Province, China (2023J011781), Key Science and Technology Project of Quanzhou Medical College, China (XJK2204A), and Quanzhou City Science and Technology Program, China (2023NS083). Authors' contributions SML, ZSZ and YFC conceived and designed the trial. JLZ, HGZ and LL contributed to curate and analyze the data. SML, JLZ and HGZ wrote the manuscript. ZSZ and YFC reviewed and edited the manuscript. All authors had read and approved the fnal version of the manuscript, and agree with the order of presentation of the authors. 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Gene-nutrient and gene-gene interactions of controlled folate intake by Japanese women. Biochem Biophys Res Commun. 2004;316:1210–6. https://doi.org/10.1016/j.bbrc.2004.02.174. Li D, Zhao Q, Zhang C, Huang X, Godfrey O, Zhang W. Associations of MTRR A66G polymorphism and promoter methylation with ischemic stroke in patients with hyperhomocysteinemia. J Gene Med. 2020;22:e3170. https://doi.org/10.1002/jgm.3170. Tables Table 1. Primer sequence and amplification parameters of MTHFR and MTRR polymorphisms analysis. Target Primer sequence 5′-3′ Length (bp) Annealing temperature (℃) Product size (bp) MTHFR rs1801133 F: CCCTCACCTGGATGGGAAAG 20 60 279 R: CCAGTCCCTGTGGTCTCTTCAT 22 60 MTHFR rs1801131 F: CAGGGGATGAACCAGGGTC 19 60 284 R: GGGCATGTGGTGGCACTG 18 60 MTRR rs1801394 F: ATCTTTTTTCCCCCATTTTTCAGT 24 60 224 R: AATTCTTCAAAGCACAAAACGGT 23 60 MTHFR , methylene tetrahydrofolate reductase; MTRR , methionine synthase reductase; R, Reverse; F, Forward Table 2. Baseline data for the maternal healthy control and CHD groups. Variables Control(n=160) CHD(n=155) χ 2 /t value P value Maternal age (years) 30.84±4.56 30.48±4.47 0.719 0.473 <35 123(76.88%) 127(81.93%) ≥35 37(23.12%) 28(18.07%) 0.941 0.332 Abnormal pregnancy history before this pregnancy Abortion (yes) 47(29.38%) 44(28.39%) 0.005 0.945 Fetal death or stillbirth (yes) 4(2.50%) 8(5.16%) 0.882 0.348 Premature delivery (yes)* 1(0.63%) 4(2.58%) -- 0.209 Family history Consanguineous marriages (yes) 0(0.00%) 0(0.00%) -- -- Congenital malformations* (yes)* 4(2.50%) 1(0.65%) -- 0.371 Personal lifestyle in the 3 months before this pregnancy Active smoking (yes) 0(0.00%) 0(0.00%) -- -- Passive smoking (yes) 8(5.00%) 10(6.45%) 0.097 0.755 Drinking (yes) 0(0.00%) 0(0.00%) -- -- Medicine history in this pregnancy Folic acid use* (no) 3(1.88%) 6(3.87%) -- 0.330 Macrolide antibiotics (yes)* 1(0.63%) 1(0.65%) -- 1 Antiviral drugs (yes)* 4(2.50%) 3(1.94%) -- 1 HCY 11.29 ± 4.48 13.74±4.36 -4.912 <0.001* CHD: congenital heart diseas *Differences between cases and controls were tested by Fisher’s exact test Table 3. Baseline data for the neonatal healthy control and CHD groups. Index Groups Cases Gender (M/F) Gestational age (weeks) Birth height (cm) Birth weight (g) Delivery mode (Eutocia / Cesarean) Control 160 92/68 37.73 ± 2.73 48.16 ± 3.37 2896.81 ± 675.00 65/95 CHD 155 95/60 37.05 ± 3.72 47.31 ± 4.43 2783.12 ± 842.88 61/94 χ2 / t value 0.325 1.858 1.905 1.320 0.013 P value 0.569 0.064 0.058 0.188 0.908 CHD: congenital heart diseas Table 4. HWE test for MTHFR and MTRR genotype frequencies of the maternal groups. Target Logic Group Actual frequency Theoretical frequency Genotype frequency χ2 value P value MTHFR rs1801133 Control 98/52/10 96.1/55.8/8.1 61/33/6 0.742 0.389 (CC/CT/TT) CHD 71/67/17 70.4/68.1/16.5 70/68/16 0.039 0.842 MTHFR rs1801131 Control 115/42/3 115.6/40.8/3.6 72/26/2 0.138 0.710 (TT/TG/GG) CHD 96/54/5 97.6/50.8/6.6 62/35/3 0.620 0.431 MTRR rs1801394 Control 94/59/7 95.3/56.3/8.3 59/37/4 0.355 0.551 (AA/AG/GG) CHD 73/65/17 71.8/67.4/15.8 47/42/11 0.194 0.659 HWE, Hardy-Weinberg equilibrium; MTHFR, 5,10-methylenetetrahydrofolate reductase; MTRR, Methionine synthase reductase Table5. Genotypic distribution and allele frequencies of MTHFR/MTRR polymorphisms between maternal control and CHD groups. Gene /SNPs Genotype/ Allele Cases (%) B SE χ2 value OR value 95% CI P value Control group (n=160) CHD group (n=155) MTHFR /rs1801133 CC 98 (61.25%) 71 (45.81%) 1 CT 52 (32.50%) 67 (43.23%) 0.576 0.242 5.672 1.778 1.107-2.856 0.017* TT 10 (6.25%) 17 (10.97%) 0.853 0.428 3.973 2.346 1.014-5.428 0.046* CT+TT 62 (38.75%) 84 (54.19%) 0.626 0.229 7.489 1.870 1.194-2.928 0.006* C 248 (77.50%) 209 (67.42%) 1 T 72 (22.50%) 101 (32.58%) 0.510 0.181 7.963 1.665 1.168-2.371 0.005* MTHFR /rs1801131 TT 115 (71.88%) 96 (61.94%) 1 TG 42 (26.25%) 54 (34.83%) 0.432 0.248 3.036 1.540 0.948-2.504 0.081 GG 3 (1.88%) 5 (3.23%) 0.691 0.743 0.865 1.997 0.465-8.569 0.352 TG+GG 45 (28.13%) 59 (38.06%) 0.451 0.241 3.497 1.571 0.979-2.521 0.061 T 272 (85.00%) 246 (79.35%) 1 G 48 (15.55%) 64 (20.65%) 0.388 0.210 3.409 1.474 0.976-2.226 0.065 MTRR /rs1801394 AA 94 (58.75%) 73 (47.09%) 1 AG 59 (36.88%) 65 (41.94%) 0.350 0.238 2.158 1.419 0.890-2.262 0.142 GG 7 (4.38%) 17 (10.97%) 1.140 0.475 5.751 3.127 1.232-7.940 0.016* AG+GG 66 (41.25%) 82 (52.90%) 0.470 0.227 4.272 1.600 1.025-2.498 0.039* A 247 (77.19%) 211 (68.06%) 1 G 73 (22.81%) 99 (31.94%) 0.462 0.181 6.555 1.588 1.114-2.261 0.010* CHD, Congenital heart disease; MTHFR, 5,10-methylenetetrahydrofolate reductase; MTRR, Methionine synthase reductase Table 6. The relationship between maternal SNPs and neonatal CHD subtypes. Gene /SNPs Genotype/ Allele Group ASD VSD PDA Control ASD VSD PDA OR 95%CI P OR 95%CI P OR 95%CI P MTHFR /rs1801133 CC 98（61.3） 41（48.8） 18（42.9） 16（47.1） 1 1 1 CT 52（32.5） 37（44.1） 20（47.6） 11（32.4） 1.701 0.974-2.969 0.062 2.094 1.019-4.302 0.044* 1.296 0.560-2.996 0.545 TT 10（6.2） 6（7.1） 4（9.5） 7（20.5） 1.434 0.489-4.205 0.511 2.178 0.615-7.707 0.227 4.287 1.426-12.893 0.010* CT+TT 62（38.8） 43（51.2） 24（57.1） 14（41.2） 1.658 0.973-2.825 0.063 2.108 1.058-4.197 0.034* 0.723 0.330-1.585 0.418 C 248（77.5） 119（70.8） 56（66.7） 43（63.2） 1 1 1 T 72（22.5） 49（29.2） 28（33.3） 25（36.8） 1.418 0.928-2.167 0.106 1.722 1.020-2.909 0.042* 2.003 1.146-3.500 0.015* MTHFR /rs1801131 TT 115（71.9） 46（54.8） 26（61.9） 25（73.5） 1 1 1 TG 42（26.3） 35（41.7） 14（33.3） 8（23.5） 2.083 1.185-3.662 0.011* 1.474 0.704-3.089 0.304 0.876 0.367-2.094 0.766 GG 3（1.8） 3（3.5） 2（4.8） 1（3.0） 2.500 0.487-12.842 0.272 2.949 0.469-18.550 0.249 1.533 0.153-15.357 0.716 TG+GG 45（28.1） 38（45.2） 16（38.1） 9（26.5） 2.111 1.217-3.662 0.008* 1.573 0.772-3.204 0.212 0.920 0.399-2.123 0.845 T 272（85.0） 127（75.6） 66（78.6） 58（85.3） 1 1 1 G 48（15.0） 41（24.4） 18（21.4） 10（14.7） 1.829 1.147-2.918 0.011* 1.545 0.844-2.830 0.158 0.977 0.467-2.044 0.951 MTRR /rs1801394 AA 94（58.8） 36（42.9） 21（50.0） 20（58.8） 1 1 1 AG 59（36.9） 41（48.8） 15（35.7） 10（29.4） 1.815 1.043-3.156 0.035* 1.138 0.544-2.381 0.731 0.797 0.349-1.819 0.589 GG 7（4.3） 7（8.3） 6（14.3） 4（11.8） 2.611 0.855-7.970 0.092 3.837 1.169-12.594 0.027* 2.686 0.718-10.053 0.142 AG+GG 66（41.3） 48（57.1） 21（50.0） 14（41.2） 1.899 1.113-3.241 0.019* 1.424 0.720-2.816 0.309 0.997 0.470-2.115 0.994 A 247（77.2） 113（67.3） 57（67.9） 50（73.5） 1 1 1 G 73（22.8） 55（32.7） 27（32.1） 18（26.5） 1.647 1.088-2.493 0.018* 1.603 0.946-2.715 0.079 1.218 0.669-2.217 0.518 CHD, Congenital heart disease; MTHFR, 5,10-methylenetetrahydrofolate reductase; MTRR, Methionine synthase reductase; ASD, atrial septal defect; VSD,ventricular septal defect; PDA, patent ductus arteriosus Table 7. The relationship between maternal genotypes and serum Hcy levels. Gene/SNPs Genotype MTHFR rs1801133 MTHFR rs1801131 MTRR rs1801394 CC CT TT TT TG GG AA AG GG n value 169 119 27 211 96 8 167 124 24 Hcy(umol/L) 12.02±4.66 12.72±4.25 14.65±4.76 12.45± 4.88 12.52± 4.00 13.53 ± 2.93 12.01± 4.64 12.85 ± 4.47 14.10± 4.45 t value -1.308 -2.720 -0.132 -0.623 -1.547 -2.072 -2.084 -0.696 -1.256 P value 0.192 0.007* 0.895 0.534 0.123 0.040* 0.039 # 0.488 0.211 MTHFR, 5,10-methylenetetrahydrofolate reductase; MTRR, Methionine synthase reductase; Hcy, homocysteine *:Compared to the wild type; #:Compared to the heterozygote Additional Declarations No competing interests reported. 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13:12:24","extension":"html","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":194822,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7369575/v1/f8ce646101ed3a9ef77caa0f.html"},{"id":105754927,"identity":"6c4bbf21-3a03-44da-b6d3-c5940d1fc29d","added_by":"auto","created_at":"2026-03-30 16:23:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1149977,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7369575/v1/30523405-c29d-4aa8-a983-81e35d18688f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between maternal MTHFR and MTRR gene polymorphisms and the risk of congenital heart disease in newborns","fulltext":[{"header":"Background","content":"\u003cp\u003eCongenital heart disease (CHD) is the most prevalent human birth defect, with an incidence rate of approximately 0.8\u0026ndash;1.2% of liveborn infants worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], and remains a leading cause of mortality in childhood. The prevalence of CHD is relatively high in Asian countries [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], making it a significant public health concern in the region. CHD is a heterogeneous condition resulting from the complex interplay between genetic and environmental factors [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Several maternal environmental factors, both extrinsic and intrinsic, including deficiencies in folic acid and other essential vitamins, are associated with the risk of CHD [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Numerous case\u0026ndash;control studies and meta-analyses have reported associations between single nucleotide polymorphisms (SNPs) in parental genes, particularly those involved in folate/homocysteine (Hcy) metabolism, and an elevated risk of CHD in offspring [\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13 CR14 CR15 CR16 CR17\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], especially in Asian populations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. These findings suggest that maternal genotypes may serve as independent risk factors for CHD by influencing foetal development via altered folate/Hcy metabolism. However, not all studies have reported statistically significant associations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], some studies have reported contradictory results [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Among the folate-related genes associated with CHD, 5,10-methylenetetrahydrofolate reductase (MTHFR) is one of the most widely studied. MTHFR encodes a key enzyme in the Hcy metabolic pathway [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], catalysing the conversion of MTHFR to 5-methyltetrahydrofolate (5-MTHF), which serves as the primary methyl donor for Hcy demethylation to produce methionine, and this conversion prevents Hcy accumulation, which is associated with developmental abnormalities [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The potential link between MTHFR gene polymorphisms and CHD risk was first proposed in 2001 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], Subsequently, the effects of parental MTHFR gene polymorphisms on the risk of CHD in offspring have gained considerable attention. Consequently, MTHFR gene polymorphisms rs1801133 and/or rs1801131 were identified as high risk factors for CHD in offspring [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, the findings remain inconsistent [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Some meta-analyses have reported a positive association between parental MTHFR variants rs1801133 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] or rs1801131 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and CHD risk, while others have found no significant relationship between rs1801133 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] or rs1801131 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and CHD risk.\u003c/p\u003e\u003cp\u003eMethionine synthase reductase (MTRR) is another key regulatory enzyme involved in the metabolism of Hcy. MTRR functions as a cofactor for methionine synthase, maintaining its activity by reducing vitamin B12 to ensure the remethylation of Hcy to methionine. Methionine synthase catalyses the conversion of plasma Hcy to methionine and tetrahydrofolate, effectively reducing plasma Hcy levels. MTRR deficiency may result in hyperhomocysteinemia, which is a risk factor for congenital anomalies. The parental MTRR rs1801394 polymorphism has been linked to CHD, several studies have reported a possible association with an increased risk in offspring [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], however, conflicting results have been previously reported [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGiven the inconsistent evidence in the literature, it remains unclear whether maternal MTHFR and MTRR polymorphisms contribute to the risk of CHD in offspring. These discrepancies may be due to variations in sample size, CHD subtypes, and the ethnic or regional backgrounds of the studied populations. Therefore, this study aimed to investigate the associations between maternal polymorphisms in MTHFR (rs1801133 and rs1801131) and MTRR (rs1801394) and the risk of neonatal acyanotic CHD and its subtypes in the Chinese Han population of Southern Fujian.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy participants\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis hospital-based case\u0026ndash;control study was conducted between January 2023 and December 2024, as previously described [27]. A total of 315 mothers were recruited from two hospitals: the Neonatology Department of Quanzhou First Hospital, affiliated with Fujian Medical University, and the Reproductive Medicine Center of the First Affiliated Hospital of Xiamen University. The study included 160 mothers of healthy neonates (control group) and 155 mothers of neonates diagnosed with acyanotic CHD (CHD group). CHD cases were further classified into three subtypes: atrial septal defect (ASD, n = 84), ventricular septal defect (VSD, n = 42), and patent ductus arteriosus (PDA, n = 34)). Some neonates were diagnosed with multiple CHD subtypes; therefore, the total number of CHD subtype cases exceeded 155. CHD diagnosis was confirmed using echocardiography and/or surgery. All eligible mothers were of Han Chinese descent, had singleton pregnancies, provided complete questionnaire data, and provided blood samples. The exclusion criteria included structural malformations involving other organ systems or known chromosomal abnormalities in neonates.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all the participants. The study was approved by the Medical Ethics Committee of Quanzhou First Hospital, affiliated with Fujian Medical University [Approval Number: 2023K070].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA questionnaire was developed for this study. Professionally trained investigators conducted face-to-face interviews to obtain maternal and neonatal clinical data. The collected maternal data included age, history of abnormal pregnancies (e.g. abortion, foetal death or stillbirth, and preterm birth), family history (e.g. consanguineous marriages and congenital malformations), lifestyle factors within 3 months before pregnancy (e.g. active/passive smoking and alcohol consumption), and medical history (e.g. folic acid supplementation and the use of macrolide antibiotics or antiviral drugs). Neonatal data included sex, gestational age at birth, birth height and weight, mode of delivery, and clinical CHD classification. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBlood sample collection\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeripheral venous blood samples were collected from each mother. The samples were processed using centrifugation (2\u0026ndash;8 ℃, 1000 rpm, 15 min). Plasma and blood cells were separated, aliquoted into high-pressure sterilised EP tubes, labelled, and stored at -80 \u0026deg;C until further analysis.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTag SNP selection\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCandidate tag SNPs were selected based on a literature review and data obtained from the PubMed and Chinese HapMap (http://hapmap.ncbi.nlm.nih.gov/) databases. Tag SNPs were identified using Haploview 4.2, with selection thresholds of pairwise r\u003csup\u003e2\u003c/sup\u003e \u0026ge; 0.8 and minor allele frequency \u0026ge; 1%. Based on these selection criteria, three SNPs (MTHFR variants: rs1801133 and rs1801131 and MTRR variants: rs1801394) associated with the Hcy/folate pathway in the Han Chinese population were selected.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA Extraction and Genotyping\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenomic DNA was extracted from blood cells using a Sangon Biotech DNA Extraction Kit (Shanghai, China). Genotyping of the selected tag SNPs was performed using Sanger sequencing, as previously described [27]. PCR primer sequences and amplification parameters are listed in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurement of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003cstrong\u003eerum H\u003c/strong\u003e\u003cstrong\u003ecy\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;levels\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum Hcy levels in maternal samples were measured using a commercial enzymatic cycling assay kit (Human Homocysteine Detection Kit; LOT:AUZ3522; Beckman Coulter, Suzhou, China). All procedures were performed according to the manufacturer\u0026rsquo;s instructions.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using SPSS software (version 26.0; SPSS, Chicago, IL, USA).\u0026nbsp;Hardy\u0026ndash;Weinberg equilibrium was assessed for\u0026nbsp;each SNP in the control group. Continuous variables\u0026nbsp;were tested for normality and expressed as mean \u0026plusmn; standard deviation (x \u0026plusmn; s). Intergroup comparisons were performed using independent sample t-tests. Categorical variables are expressed as frequencies (%). Group comparisons were performed using the chi-square (\u0026chi;\u003csup\u003e2\u003c/sup\u003e) or Fisher\u0026rsquo;s exact tests. Binary logistic regression analysis was conducted to estimate the odds ratio (OR) and 95% confidence interval (CI) for the association between maternal genetic polymorphisms and the risk of overall CHD and its subtypes. P \u0026lt; 0.05 (two-tailed) was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eMaternal and Neonatal Baseline Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo statistically significant differences were observed between the CHD and control groups regarding maternal characteristics, including age, history of abnormal pregnancy, family history of congenital conditions, personal lifestyle factors within 3 months before pregnancy, or medical history during pregnancy (P \u0026gt; 0.05) (Table 2). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilarly, \u0026nbsp;neonatal baseline characteristics, including sex, gestational age at birth, birth height, birth weight, and mode of delivery, did not differ significantly between the two groups (P \u0026gt; 0.05) (Table 3). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHardy\u0026ndash;Weinberg equilibrium\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe genotype distributions of maternal MTHFR and MTRR SNPs were consistent with Hardy\u0026ndash;Weinberg genetic equilibrium in both the control and CHD groups, suggesting that the study population was genetically representative of the general population (P \u0026gt; 0.05) (Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation of maternal MTHFR and MTRR gene polymorphisms with neonatal\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCHD risk\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe maternal genotype and allele frequencies of MTHFR (rs1801133, rs1801131) and MTRR (rs1801394) polymorphisms are presented in Table 5.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe genotypic and allelic frequencies of MTHFR (rs1801133, rs1801131) and MTRR (rs1801394) polymorphisms are presented in Table 5. For MTRR rs1801133, genotype frequencies for CT, TT, and CT+TT were 43.23%, 10.97%, and 54.19% in the CHD group, compared to 32.5%, 6.25%, and 38.75% in the control group, the OR of CT vs.CC was 1.778 (95% CI: 1.107\u0026ndash;2.856) with \u003cem\u003eP\u003c/em\u003e = 0.017, the OR of TT vs.CC was 2.346(95% CI: 1.014\u0026ndash;5.428) with \u003cem\u003eP\u003c/em\u003e = 0.046, and the OR of CT+TT vs. CC was 1.870 (95% CI: 1.194\u0026ndash;2.928) with \u003cem\u003eP\u003c/em\u003e = 0.006, the frequency of the T allele in the CHD group was higher than that in the control group, and the T allele was significantly associated with increased CHD risk (OR, 1.665; 95% CI: 1.168\u0026ndash;2.371, \u003cem\u003eP\u003c/em\u003e = 0.005) compared to the C allele. For MTHFR rs1801131, no significant differences in genotype or allele frequencies were observed between the groups (\u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003eFor MTRR rs1801394, GG and AG+GG genotypes were more frequent in the CHD group (10.97% and 52.90%, respectively) than in the control group (4.38% and 41.25%, respectively), the OR of GG vs. AA was 3.127 (95% CI: 1.232\u0026ndash;7.940) with\u003cem\u003e\u0026nbsp;P\u003c/em\u003e = 0.016 and the OR of AG+GG vs. AA was 1.600 (95% CI: 1.025\u0026ndash;2.498) with \u003cem\u003eP\u003c/em\u003e = 0.039, the frequency of the G allele in the CHD group was higher than that in the control group, and the G allele was significantly associated with a higher CHD risk than the A allele (OR, 1.588; 95% CI, 1.114\u0026ndash;2.261; \u003cem\u003eP\u003c/em\u003e = 0.010). \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociations of maternal MTHFR and MTRR genetic polymorphisms with CHD subtypes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe logistic regression analysis for the association between maternal gene polymorphisms and specific CHD subtypes is summarised in Table 6. We observed that the maternal MTHFR gene polymorphism at rs1801133 was significantly associated with the risk of two neonatal CHD subtypes: VSD (OR of CT vs. CC = 2.094 [95% CI: 1.019\u0026ndash;4.302], \u003cem\u003eP\u003c/em\u003e = 0.044; OR of CT+TT vs. CC = 2.108 [95% CI: 1.058\u0026ndash;4.197], \u003cem\u003eP\u003c/em\u003e = 0.034; OR of T vs. C = 1.722 [95% CI: 1.020\u0026ndash;2.909], \u003cem\u003eP\u003c/em\u003e = 0.042 ) \u0026nbsp;and PDA (OR of TT vs. CC = 4.287 [95% CI: 1.426\u0026ndash;12.893], \u003cem\u003eP\u003c/em\u003e = 0.010; OR of T vs. C = 2.003 [95% CI: 1.146\u0026ndash;3.500], \u003cem\u003eP\u003c/em\u003e = 0.015 ). The maternal MTHFR variant at rs1801131 was significantly associated only with the risk of neonatal ASD (OR of TG vs. TT was 2.083 [95% CI: 1.185\u0026ndash;3.662], \u003cem\u003eP\u003c/em\u003e = 0.011; OR of TG+GG vs. TT = 2.111 [95% CI: 1.217\u0026ndash;3.662], \u003cem\u003eP\u003c/em\u003e = 0.008; OR of G vs. T = 1.829 [95% CI: 1.147\u0026ndash;2.918], P = 0.011). Additionally, the maternal MTRR variant at rs1801394 was significantly associated with the risk of two neonatal CHD subtypes: ASD (OR of AG vs. AA = 1.815 [95% CI: 1.043\u0026ndash;3.156], \u003cem\u003eP\u003c/em\u003e = 0.035; OR of AG+GG vs. AA = 1.899 [95% CI: 1.113\u0026ndash;3.241], \u003cem\u003eP\u003c/em\u003e = 0.019; OR of G vs. A = 1.647 [95% CI: 1.088\u0026ndash;2.493], \u003cem\u003eP\u003c/em\u003e = 0.018) and VSD (OR of GG vs. AA = 3.837 [95% CI: 1.169\u0026ndash;12.594], \u003cem\u003eP\u003c/em\u003e = 0.027).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSerum Hcy levels and genotype associations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of maternal serum Hcy levels revealed that mothers with the TT genotype at MTHFR rs1801133 had significantly higher serum Hcy levels than those with the CC or CT genotypes (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) (Table 7). Mothers with the GG genotype at MTRR rs1801394 had significantly higher serum Hcy levels than those with the AA genotype (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe aetiology of CHD is multifactorial, involving complex interactions between genetic and environmental factors. Among these, maternal genetic effects, in which the maternal genotype affects the intrauterine environment, significantly impact foetal developmental disorders, acting as an environmental risk factor for CHD and other congenital disorders [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Understanding these maternal genetic contributions is essential for elucidating the pathogenesis of CHD.\u003c/p\u003e\u003cp\u003eFolate plays a crucial role in embryonic development and is associated with a reduced risk of CHD in offspring, particularly in Asian populations [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Maternal periconceptional folic acid supplementation may lower the risk of CHD in offspring by up to 40% [\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], with significant protective effects against septal defects, such as VSD and ASD [\u003cspan additionalcitationids=\"CR38 CR39\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Individualised folic acid supplementation strategies based on maternal genetic polymorphisms may be more effective than uniform approaches in preventing adverse pregnancy outcomes and neonatal CHD [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile the precise mechanisms linking maternal folate levels to foetal CHD risk remain unclear, they likely involve the maternal capacity to produce active folate metabolites. This capacity is influenced by maternal genetic variants in the folate/Hcy metabolism pathways [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Impaired maternal folate metabolism may disrupt the development of foetal cardiac neural crest cells (CNCs), which play a key role in cardiac outflow tract morphogenesis. The demand for active folate increases dramatically during early embryogenesis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Additionally, altered folate metabolism may indirectly affect CNC development by modulating Hcy levels [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePrevious studies have shown that maternal polymorphisms in key enzymes involved in folate metabolism may alter foetal susceptibility to CHD by affecting maternal folate/Hcy homeostasis; however, these findings have not been consistent [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR42 CR43 CR44\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Our study observed that mothers of children with CHD had significantly higher serum Hcy levels than controls, which is consistent with previous findings in Chinese Han populations [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAmong the folate-related SNPs, the most extensively studied are MTHFR rs1801133 and rs1801131. Despite more than two decades of research, evidence regarding their association with CHD remains inconclusive [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The MTHFR gene, located at 1p36.22, spans 20,733 bases and encodes a 656-amino-acid enzyme. The rs1801133 polymorphism (C677T) leads to a missense mutation, replacing alanine with valine, and results in reduced enzyme activity, approximately 70% in TT homozygotes and 35% in CT heterozygotes [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Individuals with the TT genotype exhibit lower serum folate levels [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] and elevated Hcy levels [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In our study, the T allele as well as the CT, TT, and GT\u0026thinsp;+\u0026thinsp;TT genotypes of MTHFR at rs1801133 were significantly higher in mothers in the CHD group than in the controls. Maternal rs1801133 polymorphisms were significantly associated with an increased risk of total CHD and specific subtypes, including VSD and PDA. Compared with those with the CC or CT genotype, those with the TT genotype had significantly higher serum Hcy levels, supporting the hypothesis that this variant contributes to CHD susceptibility through impaired folate metabolism. These findings suggest that the T allele and CT/TT genotypes at rs1801133 may contribute to genetic susceptibility in offspring with CHD and could partially explain the elevated Hcy levels observed in mothers who give birth to offspring with CHD. These results are consistent with those of previous studies [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and meta-analyses [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] demonstrated an association between maternal rs1801133 polymorphisms and CHD risk in offspring. However, contradictory findings have been reported [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe rs1801131 polymorphism (A1298C) results in a glutamate-to-alanine substitution and reduces MTHFR enzymatic activity by approximately 40% in homozygotes and 20% in heterozygotes [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, a study in healthy Japanese women found no significant association between rs1801131 and serum folate or Hcy levels [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Case-control studies and meta-analyses exploring the association between maternal rs1801131 polymorphisms and offspring CHD have yielded conflicting results, some reported no association [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], while others suggested a significant link [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Our findings showed no overall association between the maternal rs1801131 polymorphism and total CHD risk or maternal Hcy levels; however, a significant association was observed between rs1801131 and the ASD subtype.\u003c/p\u003e\u003cp\u003eThe MTRR gene is located at 5p15.31 and spans 55,167 bases, encoding 698 amino acids. The MTRR rs1801394 polymorphism involves an A-to-G missense mutation, resulting in a methionine-to-isoleucine substitution. This variant may lead to impaired methylation processes, DNA hypomethylation, impaired formation of methylated tetrahydrofolate, reduced serum folate levels, and elevated serum Hcy concentrations [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Although one study in healthy Japanese women reported no association between rs1801394 and serum folate or Hcy levels [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Our findings indicate that the maternal rs1801394 polymorphism is significantly associated with an increased risk of total CHD, as well as ASD and VSD subtypes in the offspring. Homozygous variant carriers had higher serum Hcy levels than wild-type individuals, suggesting that rs1801394 may be a maternal genetic risk factor for CHD and may partially account for elevated maternal Hcy concentrations in the CHD group. These findings are consistent with previous studies linking maternal rs1801394 to CHD [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and are further supported by subtype-specific studies [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], however, conflicting findings have been reported [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDiscrepancies across studies, including those in our study, may be attributed to several factors. Population differences in ethnicity and geographic location may affect the genotype distribution. Additionally, CHD is a heterogeneous disease arising from interactions between multiple genes and environmental exposures, making it difficult to attribute causality to any single variant. Sample size limitations and differences in study design could have contributed to inconsistent findings.\u003c/p\u003e\u003cp\u003eThis study had several limitations. First, only three CHD subtypes were evaluated because of the limited sample size. Second, we did not stratify the participants based on the timing and dosage of maternal folic acid intake, which limited our ability to explore gene-environment interactions. Future studies should focus on larger multi-centre cohorts and incorporate analyses of both gene-gene and gene-environment interactions in relation to offspring CHD risk.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur study demonstrated that maternal polymorphisms in MTHFR rs1801133 and MTRR rs1801394 were significantly associated with elevated maternal serum Hcy levels and an increased risk of total CHD and specific subtypes (ASD, VSD, and PDA) in the offspring of Han Chinese in southern Fujian. Additionally, the MTHFR rs1801131 polymorphism was significantly associated with ASD risk in offspring. These findings provide new insights into the maternal genetic contributions to CHD and highlight the need for further large-scale studies to validate these associations and explore potential gene-environment interactions.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCHD congenital heart disease\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSNPs\u0026nbsp; \u0026nbsp;single nucleotide polymorphisms\u003c/p\u003e\n\u003cp\u003eHcy homocysteine\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMTHFR 5,10-methylenetetrahydrofolate reductase\u003c/p\u003e\n\u003cp\u003e5-MTHF 5-methyltetrahydrofolate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMTRR Methionine synthase reductase\u003c/p\u003e\n\u003cp\u003eASD atrial septal defect\u003c/p\u003e\n\u003cp\u003eVSD ventricular septal defect\u003c/p\u003e\n\u003cp\u003ePDA patent ductus arteriosus\u003c/p\u003e\n\u003cp\u003eOR odds ratio\u003c/p\u003e\n\u003cp\u003eCI confidence interval\u003c/p\u003e\n\u003cp\u003eCNCs cardiac neural crest cells\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the\u0026nbsp;Medical Ethics Committee of Quanzhou First Hospital Affiliated to Fujian Medical University [Quanzhou First Hospital Affiliated to Fujian Medical University Ethics Censorship: 2023K070].\u003c/p\u003e\n\u003cp\u003eA written informed consent was obtained from all participants in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ethe corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from the Natural Science Foundation project of Fujian Province, China (2023J011781), Key Science and Technology Project of Quanzhou Medical College, China (XJK2204A), and Quanzhou City Science and Technology Program, China (2023NS083).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSML, ZSZ and YFC conceived and designed the trial. JLZ, HGZ and LL contributed to curate and analyze the data. SML, JLZ and HGZ wrote the manuscript. ZSZ and YFC reviewed and edited the manuscript. All authors had read and approved the fnal version of the manuscript, and agree with the order of presentation of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the editors and reviewers for their suggestions and Editage (www.editage.cn) for English language editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSML:Master, Associate Chief Physician\u003c/p\u003e\n\u003cp\u003eJLZ: Bachelor, Associate Professor\u003c/p\u003e\n\u003cp\u003eHGZ: Master, Attending Doctor\u003c/p\u003e\n\u003cp\u003eLL:Bachelor, Professor\u003c/p\u003e\n\u003cp\u003eZSZ: Doctorate, Professor\u003c/p\u003e\n\u003cp\u003eYFC: Doctorate, Professor\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBoyd R, McMullen H, Beqaj H, Kalfa D. Environmental Exposures and Congenital Heart Disease. 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Nigerian Journal of Clinical Practice. 2021;24:1150\u0026ndash;8. https://doi.org/10.4103/njcp.njcp_381_20.\u003c/li\u003e\n\u003cli\u003eCzeizel A, Dud\u0026aacute;s I, Vereczkey A, B\u0026aacute;nhidy F. Folate Deficiency and Folic Acid Supplementation: The Prevention of Neural-Tube Defects and Congenital Heart Defects. Nutrients. 2013;5:4760\u0026ndash;75. https://doi.org/10.3390/nu5114760.\u003c/li\u003e\n\u003cli\u003eCzeizel AE. The primary prevention of birth defects: Multivitamins or folic acid? Int J Med Sci. 2004;:50\u0026ndash;61. https://doi.org/10.7150/ijms.1.50.\u003c/li\u003e\n\u003cli\u003eQu P, Li S, Liu D, Lei F, Zeng L, Wang D, et al. A propensity-matched study of the association between optimal folic acid supplementation and birth defects in Shaanxi province, Northwestern China. Sci Rep. 2019;9:5271. https://doi.org/10.1038/s41598-019-41584-5.\u003c/li\u003e\n\u003cli\u003eFeng Y, Wang S, Chen R, Tong X, Wu Z, Mo X. Maternal Folic Acid Supplementation and the Risk of Congenital Heart Defects in Offspring: A Meta-Analysis of Epidemiological Observational Studies. Sci Rep. 2015;5:8506. https://doi.org/10.1038/srep08506.\u003c/li\u003e\n\u003cli\u003eQu Y, Lin S, Zhuang J, Bloom MS, Smith M, Nie Z, et al. First‐Trimester Maternal Folic Acid Supplementation Reduced Risks of Severe and Most Congenital Heart Diseases in Offspring: A Large Case‐Control Study. JAHA. 2020;9:e015652. https://doi.org/10.1161/JAHA.119.015652.\u003c/li\u003e\n\u003cli\u003evan Beynum IM, Kapusta L, Bakker MK, den Heijer M, Blom HJ, de Walle HEK. Protective effect of periconceptional folic acid supplements on the risk of congenital heart defects: a registry-based case-control study in the northern Netherlands. Eur Heart J. 2010;31:464\u0026ndash;71. https://doi.org/10.1093/eurheartj/ehp479.\u003c/li\u003e\n\u003cli\u003eCzeizel AE. Periconceptional folic acid-containing multivitamin supplementation for the prevention of neural tube defects and cardiovascular malformations. Ann Nutr Metab. 2011;59:38\u0026ndash;40. https://doi.org/10.1159/000332125.\u003c/li\u003e\n\u003cli\u003eIonescu-Ittu R, Marelli AJ, Mackie AS, Pilote L. Prevalence of severe congenital heart disease after folic acid fortification of grain products: time trend analysis in Quebec, Canada. BMJ. 2009;338:b1673. https://doi.org/10.1136/bmj.b1673.\u003c/li\u003e\n\u003cli\u003eLiu S, Joseph KS, Luo W, Le\u0026oacute;n JA, Lisonkova S, Van den Hof M, et al. Effect of Folic Acid Food Fortification in Canada on Congenital Heart Disease Subtypes. Circulation. 2016;134:647\u0026ndash;55. https://doi.org/10.1161/CIRCULATIONAHA.116.022126.\u003c/li\u003e\n\u003cli\u003eCzeizel AE, Dud\u0026aacute;s I. Prevention of the first occurrence of neural-tube defects by periconceptional vitamin supplementation. N Engl J Med. 1992;327:1832\u0026ndash;5. https://doi.org/10.1056/NEJM199212243272602.\u003c/li\u003e\n\u003cli\u003eSahin-Uysal N, Gulumser C, Kocaman E, Varan B, Bayraktar N, Yanık F. Maternal and cord blood homocysteine, vitamin B12, folate, and B-type natriuretic peptide levels at term for predicting congenital heart disease of the neonate: A case-control study. The Journal of Maternal-Fetal \u0026amp; Neonatal Medicine. 2020;33:2649\u0026ndash;56. https://doi.org/10.1080/14767058.2019.1633300.\u003c/li\u003e\n\u003cli\u003eChang S, You F, Song C. Analysis on the correlation between MTHFR C677T polymorphisms, homocysteine level and fetal congenital heart disease. Chinese Journal of Women and Children Health. 2019;10:24\u0026ndash;9. https://doi.org/10.19757/j.cnki.issn1674-7763.2019.02.006.\u003c/li\u003e\n\u003cli\u003eHiraoka M, Kagawa Y. Genetic polymorphisms and folate status. Congenital Anomalies. 2017;57:142\u0026ndash;9. https://doi.org/10.1111/cga.12232.\u003c/li\u003e\n\u003cli\u003eTsang BL, Devine OJ, Cordero AM, Marchetta CM, Mulinare J, Mersereau P, et al. Assessing the association between the methylenetetrahydrofolate reductase (MTHFR) 677C\u0026gt;T polymorphism and blood folate concentrations: a systematic review and meta-analysis of trials and observational studies. The American Journal of Clinical Nutrition. 2015;101:1286\u0026ndash;94. https://doi.org/10.3945/ajcn.114.099994.\u003c/li\u003e\n\u003cli\u003eMolloy AM, Daly S, Mills JL, Kirke PN, Whitehead AS, Ramsbottom D, et al. Thermolabile variant of 5, 10-methylenetetrahydrofolate reductaseassociated with low red-cell folates: implications for folate intake recommendations. The Lancet. 1997;349:1591\u0026ndash;3. https://doi.org/10.1016/S0140-6736(96)12049-3.\u003c/li\u003e\n\u003cli\u003eHiraoka M, Kato K, Saito Y, Yasuda K, Kagawa Y. Gene-nutrient and gene-gene interactions of controlled folate intake by Japanese women. Biochem Biophys Res Commun. 2004;316:1210\u0026ndash;6. https://doi.org/10.1016/j.bbrc.2004.02.174.\u003c/li\u003e\n\u003cli\u003eLi D, Zhao Q, Zhang C, Huang X, Godfrey O, Zhang W. Associations of MTRR A66G polymorphism and promoter methylation with ischemic stroke in patients with hyperhomocysteinemia. J Gene Med. 2020;22:e3170. https://doi.org/10.1002/jgm.3170.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Primer sequence and amplification parameters of MTHFR and MTRR polymorphisms analysis.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eTarget\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003ePrimer sequence 5\u0026prime;-3\u0026prime;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eLength\u003cbr\u003e\u0026nbsp;(bp)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eAnnealing\u0026nbsp;\u003cbr\u003e\u0026nbsp;temperature (℃)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eProduct\u0026nbsp;\u003cbr\u003e\u0026nbsp;size (bp)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003eMTHFR\u003c/p\u003e\n \u003cp\u003ers1801133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eF: CCCTCACCTGGATGGGAAAG\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e279\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eR: CCAGTCCCTGTGGTCTCTTCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003eMTHFR\u003c/p\u003e\n \u003cp\u003ers1801131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eF: CAGGGGATGAACCAGGGTC\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e284\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eR: GGGCATGTGGTGGCACTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003eMTRR\u003c/p\u003e\n \u003cp\u003ers1801394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eF: ATCTTTTTTCCCCCATTTTTCAGT\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e224\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eR: AATTCTTCAAAGCACAAAACGGT\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eMTHFR\u003c/em\u003e, methylene tetrahydrofolate reductase; \u003cem\u003eMTRR\u003c/em\u003e, methionine synthase reductase;\u003c/p\u003e\n\u003cp\u003eR, Reverse; F, Forward\u003c/p\u003e\n\u003cp\u003eTable 2. Baseline data for the maternal healthy control and CHD groups.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003eControl(n=160)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eCHD(n=155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e/t\u003c/p\u003e\n \u003cp\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eMaternal age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e30.84\u0026plusmn;4.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e30.48\u0026plusmn;4.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.473\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026lt;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e123(76.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e127(81.93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026ge;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e37(23.12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e28(18.07%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eAbnormal pregnancy history before this pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eAbortion (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e47(29.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e44(28.39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.945\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eFetal death or stillbirth (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e4(2.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e8(5.16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.348\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003ePremature delivery (yes)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e1(0.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e4(2.58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eFamily history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eConsanguineous marriages (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0(0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0(0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eCongenital malformations* (yes)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e4(2.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e1(0.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.371\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003ePersonal lifestyle in the\u003c/p\u003e\n \u003cp\u003e3 months before this pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eActive smoking (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0(0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0(0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003ePassive smoking (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e8(5.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e10(6.45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.755\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eDrinking (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0(0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0(0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eMedicine history in this pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eFolic acid use* (no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e3(1.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e6(3.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.330\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eMacrolide antibiotics (yes)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e1(0.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e1(0.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eAntiviral drugs (yes)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e4(2.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e3(1.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eHCY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e11.29 \u0026plusmn; 4.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e13.74\u0026plusmn;4.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e-4.912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCHD: congenital heart diseas\u003c/p\u003e\n\u003cp\u003e*Differences between cases and controls were tested by Fisher\u0026rsquo;s exact test\u003c/p\u003e\n\u003cp\u003eTable 3. Baseline data for the neonatal healthy control and CHD groups.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"664\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp; Index\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eCases\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003cp\u003e(M/F)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eGestational age\u003c/p\u003e\n \u003cp\u003e(weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eBirth height\u003c/p\u003e\n \u003cp\u003e(cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eBirth weight\u003c/p\u003e\n \u003cp\u003e(g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eDelivery mode\u003c/p\u003e\n \u003cp\u003e(Eutocia / Cesarean)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e92/68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e37.73 \u0026plusmn; 2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e48.16 \u0026plusmn; 3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e2896.81 \u0026plusmn; 675.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e65/95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eCHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e95/60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e37.05 \u0026plusmn; 3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e47.31 \u0026plusmn; 4.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e2783.12 \u0026plusmn; 842.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e61/94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026chi;2 / \u003cem\u003et\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e1.858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.908\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eCHD: congenital heart diseas\u003c/p\u003e\n\u003cp\u003eTable 4. HWE test for MTHFR and MTRR genotype frequencies of the maternal groups.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"609\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eTarget Logic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eActual\u0026nbsp;\u003c/p\u003e\n \u003cp\u003efrequency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003eTheoretical frequency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eGenotype frequency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026chi;2\u003c/p\u003e\n \u003cp\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eMTHFR\u003c/p\u003e\n \u003cp\u003ers1801133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e98/52/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e96.1/55.8/8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e61/33/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.389\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e(CC/CT/TT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eCHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e71/67/17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e70.4/68.1/16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e70/68/16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.842\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eMTHFR\u003c/p\u003e\n \u003cp\u003ers1801131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e115/42/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e115.6/40.8/3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e72/26/2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.710\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e(TT/TG/GG)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eCHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e96/54/5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e97.6/50.8/6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e62/35/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.431\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eMTRR\u003c/p\u003e\n \u003cp\u003ers1801394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e94/59/7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e95.3/56.3/8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e59/37/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.551\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e(AA/AG/GG)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eCHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e73/65/17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e71.8/67.4/15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e47/42/11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.659\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eHWE, Hardy-Weinberg equilibrium; MTHFR, 5,10-methylenetetrahydrofolate reductase; MTRR, Methionine synthase reductase\u003c/p\u003e\n\u003cp\u003eTable5. Genotypic distribution and allele frequencies of \u003cem\u003eMTHFR/MTRR\u003c/em\u003e polymorphisms between maternal control and CHD groups.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"632\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 83px;\"\u003e\n \u003cp\u003eGene /SNPs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003eGenotype/\u003c/p\u003e\n \u003cp\u003eAllele\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003eCases (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 44px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 44px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026chi;2\u0026nbsp;\u003c/p\u003e\n \u003cp\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 44px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003cp\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 73px;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;P value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003eControl group\u003cbr\u003e\u0026nbsp;(n=160)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eCHD group\u003cbr\u003e\u0026nbsp;(n=155)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 83px;\"\u003e\n \u003cp\u003eMTHFR\u003c/p\u003e\n \u003cp\u003e/rs1801133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e98 (61.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e71 (45.81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e52 (32.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e67 (43.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e5.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1.778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e1.107-2.856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.017*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e10 (6.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e17 (10.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e3.973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e2.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e1.014-5.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.046*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eCT+TT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e62 (38.75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e84 (54.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e7.489\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1.870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e1.194-2.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.006*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e248 (77.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e209 (67.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e72 (22.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e101 (32.58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e7.963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1.665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e1.168-2.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 83px;\"\u003e\n \u003cp\u003eMTHFR\u003c/p\u003e\n \u003cp\u003e/rs1801131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e115 (71.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e96 (61.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e42 (26.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e54 (34.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e3.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.948-2.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e3 (1.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e5 (3.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.865\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.465-8.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.352\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eTG+GG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e45 (28.13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e59 (38.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e3.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.979-2.521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e272 (85.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e246 (79.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e48 (15.55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e64 (20.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e3.409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1.474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.976-2.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 83px;\"\u003e\n \u003cp\u003eMTRR\u003c/p\u003e\n \u003cp\u003e/rs1801394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e94 (58.75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e73 (47.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e59 (36.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e65 (41.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e2.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.890-2.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e7 (4.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e17 (10.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.475\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e5.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e3.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e1.232-7.940\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.016*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eAG+GG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e66 (41.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e82 (52.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e4.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e1.025-2.498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.039*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e247 (77.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e211 (68.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e73 (22.81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e99 (31.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e6.555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e1.588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e1.114-2.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.010*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eCHD, Congenital heart disease; MTHFR, 5,10-methylenetetrahydrofolate reductase; MTRR, Methionine synthase reductase\u003c/p\u003e\n\u003cp\u003eTable 6. The relationship between maternal SNPs and neonatal CHD subtypes.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"946\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003eGene /SNPs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003eGenotype/\u003c/p\u003e\n \u003cp\u003eAllele\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 291px;\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 164px;\"\u003e\n \u003cp\u003eASD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 167px;\"\u003e\n \u003cp\u003eVSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 152px;\"\u003e\n \u003cp\u003ePDA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eASD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eVSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003ePDA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 64px;\"\u003e\n \u003cp\u003eMTHFR\u003c/p\u003e\n \u003cp\u003e/rs1801133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e98（61.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e41（48.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e18（42.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e16（47.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e52（32.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e37（44.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e20（47.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e11（32.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1.701\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.974-2.969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e2.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e1.019-4.302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.044*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e1.296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.560-2.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.545\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e10（6.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e6（7.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e4（9.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e7（20.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.489-4.205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e2.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.615-7.707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e4.287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1.426-12.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.010*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eCT+TT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e62（38.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e43（51.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e24（57.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e14（41.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1.658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.973-2.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e2.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e1.058-4.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.034*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0.723\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.330-1.585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.418\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e248（77.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e119（70.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e56（66.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e43（63.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e72（22.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e49（29.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e28（33.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e25（36.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1.418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.928-2.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e1.020-2.909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.042*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e2.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1.146-3.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.015*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 64px;\"\u003e\n \u003cp\u003eMTHFR\u003c/p\u003e\n \u003cp\u003e/rs1801131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e115（71.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e46（54.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e26（61.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e25（73.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e42（26.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e35（41.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e14（33.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e8（23.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e2.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.185-3.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.011*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1.474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.704-3.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0.876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.367-2.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e3（1.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e3（3.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e2（4.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e1（3.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e2.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.487-12.842\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e2.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.469-18.550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e1.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.153-15.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.716\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eTG+GG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e45（28.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e38（45.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e16（38.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e9（26.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e2.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.217-3.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.008*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.772-3.204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.399-2.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e272（85.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e127（75.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e66（78.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e58（85.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e48（15.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e41（24.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e18（21.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e10（14.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.147-2.918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.011*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1.545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.844-2.830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.467-2.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.951\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 64px;\"\u003e\n \u003cp\u003eMTRR\u003c/p\u003e\n \u003cp\u003e/rs1801394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e94（58.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e36（42.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e21（50.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e20（58.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e59（36.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e41（48.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e15（35.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e10（29.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1.815\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.043-3.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.035*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.544-2.381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.349-1.819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.589\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e7（4.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e7（8.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e6（14.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e4（11.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e2.611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.855-7.970\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e3.837\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e1.169-12.594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.027*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e2.686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.718-10.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eAG+GG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e66（41.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e48（57.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e21（50.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e14（41.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1.899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.113-3.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.019*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.720-2.816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.470-2.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.994\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e247（77.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e113（67.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e57（67.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e50（73.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e73（22.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e55（32.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e27（32.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e18（26.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.088-2.493\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.018*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e1.603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.946-2.715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e1.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.669-2.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eCHD, Congenital heart disease; MTHFR, 5,10-methylenetetrahydrofolate reductase; MTRR, Methionine synthase reductase; ASD, atrial septal defect; VSD,ventricular septal defect; PDA, patent ductus arteriosus\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 7. The relationship between maternal genotypes and serum Hcy levels.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"854\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 11.3172%;\"\u003e\n \u003cp\u003eGene/SNPs\u003c/p\u003e\n \u003cp\u003eGenotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 29.4932%;\"\u003e\n \u003cp\u003eMTHFR rs1801133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 24.4634%;\"\u003e\n \u003cp\u003eMTHFR rs1801131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 18.519%;\"\u003e\n \u003cp\u003eMTRR rs1801394\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003eCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.2018%;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5159%;\"\u003e\n \u003cp\u003eTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8599%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003eAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.4016%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3172%;\"\u003e\n \u003cp\u003en value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.2018%;\"\u003e\n \u003cp\u003e211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5159%;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8599%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.4016%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3172%;\"\u003e\n \u003cp\u003eHcy(umol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e12.02\u0026plusmn;4.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e12.72\u0026plusmn;4.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e14.65\u0026plusmn;4.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.2018%;\"\u003e\n \u003cp\u003e12.45\u0026plusmn; 4.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5159%;\"\u003e\n \u003cp\u003e12.52\u0026plusmn; 4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8599%;\"\u003e\n \u003cp\u003e13.53 \u0026plusmn; 2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e12.01\u0026plusmn; 4.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e12.85 \u0026plusmn; 4.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.4016%;\"\u003e\n \u003cp\u003e14.10\u0026plusmn; 4.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3172%;\"\u003e\n \u003cp\u003et value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e-1.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e-2.720\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.2018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5159%;\"\u003e\n \u003cp\u003e-0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8599%;\"\u003e\n \u003cp\u003e-0.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e-1.547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.4016%;\"\u003e\n \u003cp\u003e-2.072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e-2.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.2018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5159%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8599%;\"\u003e\n \u003cp\u003e-0.696\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.4016%;\"\u003e\n \u003cp\u003e-1.256\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3172%;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e0.192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e0.007*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.2018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5159%;\"\u003e\n \u003cp\u003e0.895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8599%;\"\u003e\n \u003cp\u003e0.534\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.4016%;\"\u003e\n \u003cp\u003e0.040*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3172%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.8311%;\"\u003e\n \u003cp\u003e0.039\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.2018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.5159%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8599%;\"\u003e\n \u003cp\u003e0.488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.0587%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.4016%;\"\u003e\n \u003cp\u003e0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eMTHFR, 5,10-methylenetetrahydrofolate reductase; MTRR, Methionine synthase reductase; Hcy, homocysteine\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e*:Compared to the wild type; #:Compared to the heterozygote\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Congenital heart disease, MTHFR, MTRR, Polymorphisms, homocysteine, neonates","lastPublishedDoi":"10.21203/rs.3.rs-7369575/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7369575/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Although numerous studies have explored the maternal genetic contributions to congenital heart disease (CHD), their findings remain inconsistent. This study aimed to investigate the association between maternal polymorphisms in MTHFR (rs1801133 and rs1801131) and MTRR (rs1801394) and the risk of neonatal CHD in the Chinese Han population from southern Fujian.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We conducted a case–control study involving 155 mothers of neonates with CHD and 160 healthy controls. Three SNPs were genotyped using Sanger sequencing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003eOur study showed that maternal polymorphisms of MTHFR at rs1801133 and MTRR at rs1801394 were significantly associated with risk of neonatal CHD in the homozygote comparisons (TT vs. CC at rs1801133: OR=2.346 [95% CI: 1.014–5.428]; GG vs. AA at 1801394: OR=3.127 [95% CI: 1.232–7.940]), as well as heterozygote comparison (CT vs. CC at rs1801133: OR=1.778 [95% CI: 1.107–2.856]) with mutant allele associated with a higher risk of CHDs (T vs. C at rs1801133: OR=1.665 [95% CI: 1.168-2.371]; G vs. A at 1801394: OR=1.588 [95% CI: 1.114-2.261]). Maternal polymorphisms were significantly associated with CHD subtypes: ASD risk was higher in TG vs. TT of MTHFR at rs1801131: OR=2.083 [95% CI: 1.185-3.662] and AG vs. AA of MTRR at rs1801394: OR=1.815 [95% CI: 1.043-3.156]; VSD risk was higher in GG vs. AA of MTRR at rs1801394 (OR = 3.837 [95% CI: 1.169–12.594])and CT vs. CC of MTHFR at 1801133: OR=2.094 [95% CI: 1.019-4.302]); PDA risk was higher in TT vs. CC of MTHFR at 1801133: OR=4.287 [95% CI: 1.426-12.893]. Mothers with the TT genotype at rs1801133 of the MTHFR gene had significantly higher serum Hcy levels than those with the CC or CT genotypes, and with the GG genotype at rs1801394 of MTRR higher than those with the AA genotype (all \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003eMaternal polymorphisms in MTHFR rs1801133 and MTRR rs1801394 are significantly associated with elevated maternal serum Hcy levels and increased risk of neonatal CHD, including ASD, VSD, and PDA, in the Chinese Han population of southern Fujian. MTHFR rs1801131 polymorphism was significantly associated with neonatal ASD risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration:\u003c/strong\u003e Our study is an observational study. According to the International Committee of Medical Journal Editors (ICMJE), purely observational studies (in which the allocation of medical interventions is not under the investigator's discretion) do not require registration.\u003c/p\u003e","manuscriptTitle":"Association between maternal MTHFR and MTRR gene polymorphisms and the risk of congenital heart disease in newborns","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-22 13:12:19","doi":"10.21203/rs.3.rs-7369575/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-01T08:42:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-25T07:01:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-15T13:17:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"208492135188612478497744517675668390678","date":"2025-09-15T09:24:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136182343956252466331510197227157110600","date":"2025-09-13T03:53:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-12T19:57:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-24T18:47:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-23T08:15:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-23T08:14:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-08-14T04:06:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"39cfd24f-b394-4d95-8775-dc311a0abd80","owner":[],"postedDate":"September 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:17:02+00:00","versionOfRecord":{"articleIdentity":"rs-7369575","link":"https://doi.org/10.1186/s12887-026-06759-w","journal":{"identity":"bmc-pediatrics","isVorOnly":false,"title":"BMC Pediatrics"},"publishedOn":"2026-03-27 16:10:03","publishedOnDateReadable":"March 27th, 2026"},"versionCreatedAt":"2025-09-22 13:12:19","video":"","vorDoi":"10.1186/s12887-026-06759-w","vorDoiUrl":"https://doi.org/10.1186/s12887-026-06759-w","workflowStages":[]},"version":"v1","identity":"rs-7369575","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7369575","identity":"rs-7369575","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}