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A hospital-based case-control study was performed from November 2017 to January 2020 to assess the association between maternal drug use, CYP450 gene polymorphisms, and their interactions with the risk of CHDs in offspring. This study was approved by the Ethics Committee of the Xiangya School of Public Health of Central South University, and written informed consent was obtained from all mothers. This study was registered at the Chinese Clinical Trial Registry Center (registration number: ChiCTR1800016635). The research procedure and design have been described in our previous studies[16, 17]. The study participants were recruited from two Hunan Children’s Hospital clinics. The case group was recruited from the Department of Cardiothoracic Surgery, which provides diagnosis, treatment, surgery, and management for CHDs, and the control group was recruited from the Department of Child Healthcare after health counseling or a medical examination. The controls were selected from the same hospital during the same study period as the cases.
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The outcome of interest was CHDs. Children with CHD and their mothers were identified as the case group. Children without any congenital malformations after a medical examination and their mothers were identified as the control group. The CHD cases included the following subtypes: atrial septal defect (ASD), ventricular septal defect (VSD), atrioventricular septal defect (AVSD), patent ductus arteriosus (PDA), aortopulmonary septal defect (APSD), tetralogy of Fallot (TOF), and complete transposition of the great arteries (CTOGA). Non-syndromic CHD was of interest, but patients with other organ malformations or known abnormalities were excluded. All CHD patients were diagnosed by ultrasonography. Similarly, the control children were confirmed to have no malformations by ultrasonography. The exposures of interest were maternal drug use and genetic variants in the CYP450 genes. To minimize recall bias of exposure by mothers, all cases and controls were recruited when the children were < 1-year-old. Additionally, this study was aimed at mothers of Han Chinese descent with singleton pregnancies. Eligible mothers completed a questionnaire and provided informed consent and blood samples. We excluded mothers who achieved pregnancy by assisted reproductive technology, including in vitro fertilization or intracytoplasmic sperm injection.
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A standardized questionnaire was used to collect the corresponding maternal drug use information by specially trained investigators. As the critical stage of fetal heart development is the early stage of pregnancy, we investigated the maternal drug use information from 3 months before pregnancy to the first trimester of pregnancy. In our study, the drugs of interest were oral contraceptives, ovulatory drugs (e.g., clomiphene, luteinizing hormone-releasing hormone, and bromocriptine), macrolide antibiotics (e.g., erythromycin, azithromycin, clarithromycin, roxithromycin, dierythromycin, and fluoroerythromycin), antidepressants (e.g., clomipramine, citalopram, sympathomimetic decongestants, paroxetine, and phenylpropanolamine), traditional Chinese medicines, and antiabortifacients (e.g., progesterone preparations, chorionic gonadotropin, human blood immunoglobulin, and indomethacin). Additionally, we also collected data regarding the mothers’ sociodemographic characteristics (i.e., child-bearing age, education level, annual family income in the past year, residential area); obstetric history (i.e., adverse pregnancy outcomes and pregnancy-related complications); family history (i.e., consanguineous marriage and congenital malformations); personal medical history (i.e., congenital malformations, and cold or fever history in the 3 months before this pregnancy); personal lifestyle and habits (i.e., history of active and passive smoking in the 3 months before this pregnancy, and drinking history in the 3 months before this pregnancy); exposure history to environmentally hazardous substances (i.e., radioactive substances, house decorations, and harmful chemicals); and folate supplementation. After completing the questionnaire, we consulted the perinatal health care handbook (PHCH) and maternal medical records to further confirm the corresponding information. Notably, not all the information we needed was recorded by the PHCH. Therefore, we used face-to-face interviews and consulted the PHCH to ensure that the relevant information was accurately collected. When the information provided by these two methods was inconsistent, we relied on the information provided by the PHCH, considering that there may be recall bias during a face-to-face interview. These measures may have helped to reduce recall bias.
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After completing the questionnaire, all mothers were required to provide blood samples after consent. Three to five milliliters of peripheral venous blood were collected by a qualified phlebotomist from all participants using a 21-gage needle. Plasma and blood cells were separated by centrifugation and stored at −80 °C for later laboratory testing. The genomic DNA was extracted from blood cells using the QIAamp DNA Mini Kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s protocol and dissolved in sterile TBE buffer.
We chose four SNPs of the CYP450 genes (CYP1A1 at rs1048943 and rs4646903, CYP2D6 at rs1065852 and rs16947), which have been associated with adverse pregnancy outcomes and metabolism of drugs of interest[18,19], as candidate loci. Because the related primers were unavailable, we used rs4646421 instead of rs4646903 (r2 = 1.000), rs5751210 instead of rs1065852 (r2 = 0.900), and rs4147641 instead of rs16947 (r2 = 0.965) according to linkage disequilibrium analysis. All SNPs (rs1048943, rs4646421, rs5751210, and rs4147641) were genotyped using the matrix-assisted laser desorption and ionization time-of-flight mass spectrometry Mass Array system (Agena iPLEXassay, San Diego, CA, USA). Different cycling conditions were used to optimally amplify the target sequences. The details of polymerase chain reaction primers are described in Supplementary Table S1 (available in www.besjournal.com). The laboratory technician, who performed the genotyping, retyped and double-checked each sample, and recorded the genotype data, was blinded to the status of the control and case groups. The genotyping error rate was < 5%.
Table S1. Primer sequences for cytochrome P450 genetic polymorphisms
Genes SNPs Linkage r2 Primer sequences CYP1A1 rs1048943 − 1st-PCRP No ACGTTGGATGGGTGATTATCTTTGGCATGG 2nd-PCRP ACGTTGGATGGGTGATTATCTTTGGCATGG rs4646903 rs4646421 1.000 1st-PCRP ACGTTGGATGAGACTCCTTAGGGACACTTC 2nd-PCRP ACGTTGGATGCATTGATCTGACCACTCTTC CYP2D6 rs1065852 rs5751210 0.900 1st-PCRP ACGTTGGATGATGGACAGAGTTTTCCGGAC 2nd-PCRP ACGTTGGATGACAGCACTGGTCGGTGCGG rs16947 rs4147641 0.965 1st-PCRP ACGTTGGATGATGTCTGGACAATGAGGTGG 2nd-PCRP ACGTTGGATGGGTACCAGTTAACCACAGAG Note. SNPs, single nucleotide polymorphisms. -
Unordered categorical variables are described using percentages and compared between two groups using Pearson’s chi-square test or Fisher’s exact test, as appropriate. The Wilcoxon rank-sum test was used for ordinal categorical variables. Hardy-Weinberg equilibrium (HWE) was tested in the control group (significance level at P < 0.05). Odds ratios (ORs) and their 95% confidence intervals (CIs) were used to assess the level of the associations between maternal drug exposure and CYP450 genetic variants with the risk of CHDs in offspring. The crude ORs were calculated by univariate logistic regression. Adjusted ORs (aORs) were calculated by multivariate logistic regression. Moreover, all SNPs were estimated under the three genetic models (dominant, recessive, and additive).
Additionally, we used logistic regression analysis and controlled for other influencing factors to examine the effects of the environment-gene interaction of the maternal drug exposure and the CYP450 genes for the risk of CHDs in offspring. We determined the patterns and implications of the environment-gene interactions according to a method introduced by Wallace[20]. Interactions were determined using interaction coefficients (γ). The γ values were calculated using the regression coefficient (β) from logistic regression analysis (i.e., γ1 = βe*g/βe and γ2 = βe*g/βg for the gene-environment interaction). γ values > 1 indicated a positive interaction; and γ values < 1 indicated a negative interaction; when the γ value = 1, there was no interaction. To minimize type I error, the false discovery rate P-value (FDR_P), which was adjusted for multiple testing, was estimated to obtain a more precise P-value[16]. All tests were performed for a two-sided P-value not exceeding 0.05. All analyses were performed using SAS 9.1 software (SAS Institute, Cary, NC, USA).
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A total of 569 eligible mothers were included in the case group, and 652 were included in the control group from November 2017 to January 2020. Among the 569 CHD cases, 95 (16.7%) were diagnosed with ASD, 353 (62.0%) with VSD, 60 (10.5%) with AVSD, 170 (29.9%) with PDA, 8 (1.4%) with APSD, 32 (5.6%) with TOF, and 2 (0.4%) with CTOGA. Some cases were diagnosed with multiple CHD subtypes. Therefore, the sum of the various subtypes was not equal to 569. Maternal baseline characteristics in the case and control groups are summarized in Table 1. Significant differences in education level, annual family income, residential area, history of adverse pregnancy outcomes, pregnancy-related complications, consanguineous marriage, and congenital malformation history, drinking history before pregnancy, active or passive smoking history before pregnancy, cold and fever history before this pregnancy, and folate supplementation were observed between the two groups (all P < 0.05). These factors were adjusted when assessing the associations between maternal drug use, the CYP450 gene polymorphisms, and their interactions with the risk of CHDs in offspring.
Table 1. Maternal baseline characteristics in the case and control groups
Baseline characteristics Control group, n (%)
(n = 652)Case group, n (%)
(n = 569)P values Child-bearing age (years) (≥ 35) 92 (14.1) 75 (13.2%) 0.637 Education level Less than primary or primary 9 (1.4) 85 (14.9) < 0.001 Junior high school 127 (19.5) 231 (40.6) Senior middle school 210 (32.2) 162 (28.5) College or above 306 (46.9) 91 (16.0) Annual income in the past 1 year (RMB) < 50,000 187 (28.7) 463 (81.4) < 0.001 50,000–100,000 275 (42.2) 77 (13.5) 100,001–150,000 59 (9.0) 11 (1.9) > 150,000 131 (20.1) 18 (3.2) Residence areas (rural areas) 349 (53.5) 428 (75.2) < 0.001 History of adverse pregnancy outcomes (yes) 73 (11.2) 96 (16.9) 0.004 History of pregnancy related complications (yes) 37 (5.7) 95 (16.7) < 0.001 Family consanguineous marriages (yes) 2 (0.3) 24 (4.2) < 0.001 Family congenital malformations history (yes) 4 (0.6) 40 (7.0) < 0.001 Individual congenital malformations (yes) 2 (0.3) 5 (0.9) 0.261* Alcohol use before pregnancy (yes) 45 (6.9) 78 (13.7) < 0.001 Active smoking before pregnancy (yes) 12 (1.8) 46 (8.1) < 0.001 Passive smoking before pregnancy (yes) 249 (38.2) 293 (51.5) < 0.001 Exposure history of radioactive substance (yes) 12 (1.8) 19 (3.3) 0.097 History of house decoration (yes) 37 (5.7) 44 (7.7) 0.149 Exposure history to harmful chemicals (yes) 24 (3.7) 27 (4.7) 0.354 Cold history (yes) 76 (11.7) 122 (21.4) < 0.001 Fever history (yes) 13 (2.0) 47 (8.3) < 0.001 Folate supplementation (no) 44 (6.7) 95 (16.7) < 0.001 Note. *Fisher’s exact probability test. -
The associations between maternal drug use and the risk of CHDs in offspring are summarized in Table 2. After adjusting for other influencing factors, the results show that mothers who used ovulatory drugs (aOR = 2.12, 95% CI: 1.08–4.16), antidepressants (aOR = 2.56, 95% CI: 1.36–4.82), antiabortifacients (aOR = 1.55, 95% CI: 1.00–2.40), or traditional Chinese medicines (aOR = 1.97, 95% CI: 1.26–3.09) during this pregnancy were at a significantly higher risk of CHDs in offspring compared with the reference group. However, we did not observe a significant association between oral contraceptive or macrolide antibiotic use and the risk of CHDs.
Table 2. Maternal drug use and risk of congenital heart defect in offspring
Maternal drug use Control group,
n (%) (n = 652)Case group,
n (%) (n = 569)Crude OR Adjusted OR* OR (95% CI) P values OR (95% CI) P values Oral contraceptives (yes) 17 (2.6) 20 (3.5) 1.36 (0.71-2.62) 0.358 1.48 (0.70-3.16) 0.306 Ovulatory drugs (yes) 17 (2.6) 36 (6.3) 2.52 (1.40-4.54) 0.002 2.12 (1.08-4.16) 0.029 Macrolides antibiotics (yes) 31 (4.6) 57 (10.0) 2.23 (1.42-3.51) 0.001 1.45 (0.77-2.71) 0.251 Antidepressant drugs (yes) 21 (3.2) 45 (7.9) 2.58 (1.52-4.39) 0.000 2.56 (1.36-4.82) 0.004 Traditional Chinese drugs (yes) 75 (11.5) 103 (18.1) 1.70 (1.23-2.35) 0.001 1.97 (1.26-3.09) 0.003 Antiabortifacients (yes) 81 (12.4) 120 (21.1) 1.88 (1.39-2.56) 0.000 1.55 (1.00-2.40) 0.048 Note. *Adjusted for maternal education level, family annual income, residence areas, history of adverse pregnancy outcomes, history of pregnancy related complications, family consanguineous marriages, family history of congenital malformation, alcohol use before pregnancy, active or passive smoking before pregnancy, cold or fever history for this pregnancy, folate supplementation and the remaining drugs. OR: odds ratio; CI: confidence interval. -
The genotype frequencies for each SNP of the maternal CYP450 genes and P-values for the HWE test in the control group are summarized in Table 3. The genotype distributions in the control group were within HWE (all P > 0.05). The associations between maternal CYP450 genetic variants and the risk of CHDs in offspring based on logistic regression analyses are summarized in Table 4. After adjusting for influencing factors, the results suggested that maternal CYP450 genetic polymorphisms at rs1065852 and rs16947 were significantly associated with the risk of CHDs in offspring. Mothers with the A/T (aOR = 1.53, 95% CI: 1.10–2.14) and T/T (aOR = 1.57, 95% CI: 1.07–2.31) genotype for rs1065852 compared with those with the A/A genotype experienced a significantly increased risk of CHD in offspring. The dominant (aOR = 1.55, 95% CI: 1.13–2.12) and additive models (aOR = 1.25; 95% CI: 1.03–1.52) were significantly associated with an increased risk of CHDs in offspring.
Table 3. Maternal cytochrome P450 genotype frequencies and P values of HWE test
SNPs Major allele Minor allele MAF Group Genotype frequencies†,
n (%)
HWE test PAA AB BB rs1048943 T C 0.2514 Control 359 (55.1) 256 (39.3) 37 (5.7) 0.3244 Case 305 (53.6) 244 (42.9) 20 (3.5) rs4646903 G A 0.4423 Control 205 (31.4) 331 (50.8) 116 (17.8) 0.3768 Case 168 (29.5) 285 (50.1) 116 (20.4) rs1065852 A T 0.4906 Control 192 (29.4) 313 (48.0) 147 (22.5) 0.3676 Case 121 (21.3) 305 (53.6) 143 (25.1) rs16947 C G 0.1937 Control 462 (70.9) 166 (25.5) 24 (3.7) 0.0660 Case 353 (62.0) 173 (30.4) 43 (7.6) Note. †AA = homozygous wild-type; AB = heterozygous variant type; BB = homozygous variant type. SNPs, single nucleotide polymorphisms; HWE, Hardy-Weinberg equilibrium; MAF, minimum allele frequency. Table 4. Maternal cytochrome P450 genetic polymorphisms and risk of congenital heart defect in offspring
SNPs Crude OR Adjusted OR* OR (95% CI) P values OR (95% CI) P value FDR_P values CYP1A1 at rs1048943 T/T 1 1 T/C 1.12 (0.89−1.42) 0.332 1.03 (0.78−1.37) 0.802 0.802 C/C 0.64 (0.36−1.12) 0.117 0.88 (0.46−1.71) 0.716 0.818 Dominant 1.06 (0.85−1.33) 0.610 1.02 (0.78−1.34) 0.887 0.887 Recessive 0.61 (0.35−1.06) 0.077 0.87 (0.45−1.67) 0.677 0.677 Additive 0.98 (0.81−1.19) 0.835 1.00 (0.79−1.26) 0.978 0.978 CYP1A1 at rs4646903 G/G 1 1 G/A 1.05 (0.81−1.36) 0.708 1.18 (0.87−1.59) 0.287 0.383 A/A 1.22 (0.88−1.70) 0.235 1.43 (0.98−2.10) 0.067 0.134 Dominant 1.10 (0.86−1.40) 0.468 1.22 (0.91−1.64) 0.175 0.233 Recessive 1.18 (0.89−1.58) 0.249 1.40 (0.99−1.99) 0.057 0.114 Additive 1.10 (0.93−1.29) 0.258 1.19 (0.99−1.44) 0.067 0.089 CYP2D6 at rs1065852 A/A 1 A/T 1.55 (1.17−2.04) 0.002 1.53 (1.10−2.14) 0.011 0.044 T/T 1.54 (1.12−2.13) 0.009 1.57 (1.07−2.31) 0.023 0.061 Dominant 1.55 (1.19−2.01) 0.001 1.55 (1.13−2.12) 0.007 0.028 Recessive 1.15 (0.89−1.50) 0.290 1.17 (0.86−1.61) 0.316 0.421 Additive 1.25 (1.06−1.46) 0.008 1.25 (1.03−1.52) 0.022 0.044 CYP2D6 at rs16947 C/C 1 C/G 1.36 (1.06−1.76) 0.017 1.24 (0.91−1.68) 0.179 0.286 G/G 2.35 (1.40−3.94) 0.001 3.41 (1.82−6.39) < 0.001 < 0.001 Dominant 1.49 (1.17−1.89) 0.001 1.47 (1.10−1.95) 0.009 0.018 Recessive 2.14 (1.28−3.57) 0.004 3.23 (1.73−6.02) < 0.001 < 0.001 Additive 1.44 (1.19−1.75) < 0.001 1.51 (1.20−1.90) < 0.001 < 0.001 Note. *Adjusted for maternal education level, family annual income, residence areas, history of adverse pregnancy outcomes, history of pregnancy related complications, family consanguineous marriages, family history of congenital malformation, alcohol use before pregnancy, active or passive smoking before pregnancy, cold or fever history for this pregnancy, folate. OR, odds ratio; CI, confidence interval; SNPs, single nucleotide polymorphisms; FDR_P, false discovery rate P. supplementation and the remaining SNPs. Mothers with the G/G genotype for rs16947 were at a significantly higher risk of CHDs in offspring than those with the C/C genotype (aOR = 3.41, 95% CI: 1.82–6.39); and the dominant (aOR = 1.47, 95% CI: 1.10–1.95), recessive (aOR = 3.23, 95% CI: 1.73–6.02), and additive models (aOR = 1.51, 95% CI: 1.20–1.90) were significantly associated with an increased risk of CHDs in offspring.
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The gene-environment interactions between the maternal CYP450 genetic variants and drug use for the risk of CHDs in offspring are summarized in Table 5. In the interaction analyses, we only considered those drugs and SNPs that were significantly associated with the risk of CHDs in the above analyses. Significant interactive effects were observed between the maternal genetic variants at rs1065852 and drug use for the development of CHDs in offspring. Overall, when mothers had a risk genotype (A/T or T/T) at rs1065852, the risk of CHDs in offspring increased significantly if they used an antidepressant (aOR = 8.32, 95% CI: 3.56–19.45) or an antiabortifacient (aOR = 2.47, 95% CI: 1.48–4.10).
Table 5. Interactions between maternal cytochrome P450 gene and drug use for risk of congenital heart defect in offspring
Maternal drug use Maternal cytochrome P450 genotype Number
of controlNumber
of caseAdjusted OR (95% CI)* P Regression coefficient Interactive coefficient γ1 γ2 Ovulatory drugs rs1065852 No Wild genotype (A/A) 188 109 1 No Variant genotype (A/T or T/T) 447 424 1.68 (1.24−2.27) 0.001 0.519 (βg) Yes Wild genotype (A/A) 4 12 5.65 (1.59−20.11) 0.008 1.732 (βe) Yes Variant genotype (A/T or T/T) 13 24 3.84 (1.74−8.49) 0.001 1.345 (βg*e) 2.592 0.777 Antidepressant drugs rs1065852 No Wild genotype (A/A) 186 114 1 No Variant genotype (A/T or T/T) 445 410 1.59 (1.15−2.20) 0.005 0.462 (βg) Yes Wild genotype (A/A) 6 7 8.23 (2.22−30.44) 0.002 2.108 (βe) Yes Variant genotype (A/T or T/T) 15 38 8.32 (3.56−19.45) 0.000 2.118 (βg*e) 4.584 1.005 Traditional Chinese drugs rs1065852 No Wild genotype (A/A) 176 97 1 No Variant genotype (A/T or T/T) 401 369 1.83 (1.29−2.57) 0.001 0.602 (βg) Yes Wild genotype (A/A) 16 24 6.63 (2.80−15.71) 0.000 1.892 (βe) Yes Variant genotype (A/T or T/T) 59 79 3.25 (1.94−5.44) 0.000 1.179 (βg*e) 1.958 0.623 Antiabortifacients rs1065852 No Wild genotype (A/A) 171 96 1 No Variant genotype (A/T or T/T) 400 353 1.58 (1.12−2.22) 0.009 0.457 (βg) Yes Wild genotype (A/A) 21 25 1.66 (0.74−3.70) 0.216 0.507 (βe) Yes Variant genotype (A/T or T/T) 60 95 2.47 (1.48−4.10) 0.001 0.902 (βg*e) 1.974 1.779 Ovulatory drugs rs16947 No Wild genotype (C/C) 449 334 1 No Variant genotype (C/G or G/G) 186 199 1.52 (1.13−2.05) 0.006 0.420 (βg) Yes Wild genotype (C/C) 13 19 2.87 (1.13−7.28) 0.027 1.054 (βe) Yes Variant genotype (C/G or G/G) 4 17 6.49 (1.82−23.14) 0.004 1.871 (βg*e) 4.455 1.775 Antidepressant drugs rs16947 No Wild genotype (C/C) 441 329 1 No Variant genotype (C/G or G/G) 190 195 1.49 (1.10−2.01) 0.010 0.397 (βg) Yes Wild genotype (C/C) 21 24 3.81 (1.72−8.44) 0.001 1.338 (βe) Yes Variant genotype (C/G or G/G) 0 21 − 0.998 21.672 (βg*e) Traditional Chinese drugs rs16947 No Wild genotype (C/C) 405 283 1 No Variant genotype (C/G or G/G) 172 183 1.65 (1.20−2.26) 0.002 0.500 (βg) Yes Wild genotype (C/C) 57 70 2.59 (1.61−4.18) 0.000 0.952 (βe) Yes Variant genotype (C/G or G/G) 18 33 3.55 (1.72−7.29) 0.001 1.265 (βg*e) 2.530 1.329 Antiabortifacients rs16947 No Wild genotype (C/C) 408 270 1 No Variant genotype (C/G or G/G) 163 179 1.76 (1.28−2.41) 0.000 0.563 (βg) Yes Wild genotype (C/C) 54 83 2.05 (1.28−3.30) 0.003 0.720 (βe) Yes Variant genotype (C/G or G/G) 27 37 1.67 (0.87−3.21) 0.125 0.512 (βg*e) 0.909 0.711 Note. *Adjusted for maternal education level, family annual income, residence areas, history of adverse pregnancy outcomes, history of pregnancy related complications, family consanguineous marriages, family history of congenital malformation, alcohol use before pregnancy, active or passive smoking before pregnancy, cold or fever history for this pregnancy, and folate supplementation. OR: odds ratio; CI: confidence interval. There were also statistically significant interactive effects between maternal genetic variants at rs16947 and drug use for the development of CHDs in offspring. Overall, mothers with a risk genotype (C/G or G/G) at rs16947 had a significantly higher risk of CHDs in offspring if they used ovulatory drugs (aOR = 6.49, 95% CI: 1.82–23.14) or traditional Chinese medicines (aOR = 3.55, 95% CI: 1.72–7.29).
doi: 10.3967/bes2022.006
Association between Maternal Drug Use and Cytochrome P450 Genetic Polymorphisms and the Risk of Congenital Heart Defects in Offspring
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Abstract:
Objective This study aimed to assess the associations between maternal drug use, cytochrome P450 (CYP450) genetic polymorphisms, and their interactions with the risk of congenital heart defects (CHDs) in offspring. Methods A case-control study involving 569 mothers of CHD cases and 652 controls was conducted from November 2017 to January 2020. Results After adjusting for potential confounding factors, the results show that mothers who used ovulatory drugs (adjusted odds ratio [aOR] = 2.12; 95% confidence interval [CI]: 1.08–4.16), antidepressants (aOR = 2.56; 95% CI: 1.36–4.82), antiabortifacients (aOR = 1.55; 95% CI: 1.00–2.40), or traditional Chinese drugs (aOR = 1.97; 95% CI: 1.26–3.09) during pregnancy were at a significantly higher risk of CHDs in offspring. Maternal CYP450 genetic polymorphisms at rs1065852 (A/T vs. A/A: OR = 1.53, 95% CI: 1.10–2.14; T/T vs. A/A: OR = 1.57, 95% CI: 1.07–2.31) and rs16947 (G/G vs. C/C: OR = 3.41, 95% CI: 1.82–6.39) were also significantly associated with the risk of CHDs in offspring. Additionally, significant interactions were observed between the CYP450 genetic variants and drug use on the development of CHDs. Conclusions In those of Chinese descent, ovulatory drugs, antidepressants, antiabortifacients, and traditional Chinese medicines may be associated with the risk of CHDs in offspring. Maternal CYP450 genes may regulate the effects of maternal drug exposure on fetal heart development. -
Key words:
- Congenital heart defect /
- Maternal drug use /
- Cytochrome P450 genes /
- Case-control study
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S1. Primer sequences for cytochrome P450 genetic polymorphisms
Genes SNPs Linkage r2 Primer sequences CYP1A1 rs1048943 − 1st-PCRP No ACGTTGGATGGGTGATTATCTTTGGCATGG 2nd-PCRP ACGTTGGATGGGTGATTATCTTTGGCATGG rs4646903 rs4646421 1.000 1st-PCRP ACGTTGGATGAGACTCCTTAGGGACACTTC 2nd-PCRP ACGTTGGATGCATTGATCTGACCACTCTTC CYP2D6 rs1065852 rs5751210 0.900 1st-PCRP ACGTTGGATGATGGACAGAGTTTTCCGGAC 2nd-PCRP ACGTTGGATGACAGCACTGGTCGGTGCGG rs16947 rs4147641 0.965 1st-PCRP ACGTTGGATGATGTCTGGACAATGAGGTGG 2nd-PCRP ACGTTGGATGGGTACCAGTTAACCACAGAG Note. SNPs, single nucleotide polymorphisms. Table 1. Maternal baseline characteristics in the case and control groups
Baseline characteristics Control group, n (%)
(n = 652)Case group, n (%)
(n = 569)P values Child-bearing age (years) (≥ 35) 92 (14.1) 75 (13.2%) 0.637 Education level Less than primary or primary 9 (1.4) 85 (14.9) < 0.001 Junior high school 127 (19.5) 231 (40.6) Senior middle school 210 (32.2) 162 (28.5) College or above 306 (46.9) 91 (16.0) Annual income in the past 1 year (RMB) < 50,000 187 (28.7) 463 (81.4) < 0.001 50,000–100,000 275 (42.2) 77 (13.5) 100,001–150,000 59 (9.0) 11 (1.9) > 150,000 131 (20.1) 18 (3.2) Residence areas (rural areas) 349 (53.5) 428 (75.2) < 0.001 History of adverse pregnancy outcomes (yes) 73 (11.2) 96 (16.9) 0.004 History of pregnancy related complications (yes) 37 (5.7) 95 (16.7) < 0.001 Family consanguineous marriages (yes) 2 (0.3) 24 (4.2) < 0.001 Family congenital malformations history (yes) 4 (0.6) 40 (7.0) < 0.001 Individual congenital malformations (yes) 2 (0.3) 5 (0.9) 0.261* Alcohol use before pregnancy (yes) 45 (6.9) 78 (13.7) < 0.001 Active smoking before pregnancy (yes) 12 (1.8) 46 (8.1) < 0.001 Passive smoking before pregnancy (yes) 249 (38.2) 293 (51.5) < 0.001 Exposure history of radioactive substance (yes) 12 (1.8) 19 (3.3) 0.097 History of house decoration (yes) 37 (5.7) 44 (7.7) 0.149 Exposure history to harmful chemicals (yes) 24 (3.7) 27 (4.7) 0.354 Cold history (yes) 76 (11.7) 122 (21.4) < 0.001 Fever history (yes) 13 (2.0) 47 (8.3) < 0.001 Folate supplementation (no) 44 (6.7) 95 (16.7) < 0.001 Note. *Fisher’s exact probability test. Table 2. Maternal drug use and risk of congenital heart defect in offspring
Maternal drug use Control group,
n (%) (n = 652)Case group,
n (%) (n = 569)Crude OR Adjusted OR* OR (95% CI) P values OR (95% CI) P values Oral contraceptives (yes) 17 (2.6) 20 (3.5) 1.36 (0.71-2.62) 0.358 1.48 (0.70-3.16) 0.306 Ovulatory drugs (yes) 17 (2.6) 36 (6.3) 2.52 (1.40-4.54) 0.002 2.12 (1.08-4.16) 0.029 Macrolides antibiotics (yes) 31 (4.6) 57 (10.0) 2.23 (1.42-3.51) 0.001 1.45 (0.77-2.71) 0.251 Antidepressant drugs (yes) 21 (3.2) 45 (7.9) 2.58 (1.52-4.39) 0.000 2.56 (1.36-4.82) 0.004 Traditional Chinese drugs (yes) 75 (11.5) 103 (18.1) 1.70 (1.23-2.35) 0.001 1.97 (1.26-3.09) 0.003 Antiabortifacients (yes) 81 (12.4) 120 (21.1) 1.88 (1.39-2.56) 0.000 1.55 (1.00-2.40) 0.048 Note. *Adjusted for maternal education level, family annual income, residence areas, history of adverse pregnancy outcomes, history of pregnancy related complications, family consanguineous marriages, family history of congenital malformation, alcohol use before pregnancy, active or passive smoking before pregnancy, cold or fever history for this pregnancy, folate supplementation and the remaining drugs. OR: odds ratio; CI: confidence interval. Table 3. Maternal cytochrome P450 genotype frequencies and P values of HWE test
SNPs Major allele Minor allele MAF Group Genotype frequencies†,
n (%)
HWE test PAA AB BB rs1048943 T C 0.2514 Control 359 (55.1) 256 (39.3) 37 (5.7) 0.3244 Case 305 (53.6) 244 (42.9) 20 (3.5) rs4646903 G A 0.4423 Control 205 (31.4) 331 (50.8) 116 (17.8) 0.3768 Case 168 (29.5) 285 (50.1) 116 (20.4) rs1065852 A T 0.4906 Control 192 (29.4) 313 (48.0) 147 (22.5) 0.3676 Case 121 (21.3) 305 (53.6) 143 (25.1) rs16947 C G 0.1937 Control 462 (70.9) 166 (25.5) 24 (3.7) 0.0660 Case 353 (62.0) 173 (30.4) 43 (7.6) Note. †AA = homozygous wild-type; AB = heterozygous variant type; BB = homozygous variant type. SNPs, single nucleotide polymorphisms; HWE, Hardy-Weinberg equilibrium; MAF, minimum allele frequency. Table 4. Maternal cytochrome P450 genetic polymorphisms and risk of congenital heart defect in offspring
SNPs Crude OR Adjusted OR* OR (95% CI) P values OR (95% CI) P value FDR_P values CYP1A1 at rs1048943 T/T 1 1 T/C 1.12 (0.89−1.42) 0.332 1.03 (0.78−1.37) 0.802 0.802 C/C 0.64 (0.36−1.12) 0.117 0.88 (0.46−1.71) 0.716 0.818 Dominant 1.06 (0.85−1.33) 0.610 1.02 (0.78−1.34) 0.887 0.887 Recessive 0.61 (0.35−1.06) 0.077 0.87 (0.45−1.67) 0.677 0.677 Additive 0.98 (0.81−1.19) 0.835 1.00 (0.79−1.26) 0.978 0.978 CYP1A1 at rs4646903 G/G 1 1 G/A 1.05 (0.81−1.36) 0.708 1.18 (0.87−1.59) 0.287 0.383 A/A 1.22 (0.88−1.70) 0.235 1.43 (0.98−2.10) 0.067 0.134 Dominant 1.10 (0.86−1.40) 0.468 1.22 (0.91−1.64) 0.175 0.233 Recessive 1.18 (0.89−1.58) 0.249 1.40 (0.99−1.99) 0.057 0.114 Additive 1.10 (0.93−1.29) 0.258 1.19 (0.99−1.44) 0.067 0.089 CYP2D6 at rs1065852 A/A 1 A/T 1.55 (1.17−2.04) 0.002 1.53 (1.10−2.14) 0.011 0.044 T/T 1.54 (1.12−2.13) 0.009 1.57 (1.07−2.31) 0.023 0.061 Dominant 1.55 (1.19−2.01) 0.001 1.55 (1.13−2.12) 0.007 0.028 Recessive 1.15 (0.89−1.50) 0.290 1.17 (0.86−1.61) 0.316 0.421 Additive 1.25 (1.06−1.46) 0.008 1.25 (1.03−1.52) 0.022 0.044 CYP2D6 at rs16947 C/C 1 C/G 1.36 (1.06−1.76) 0.017 1.24 (0.91−1.68) 0.179 0.286 G/G 2.35 (1.40−3.94) 0.001 3.41 (1.82−6.39) < 0.001 < 0.001 Dominant 1.49 (1.17−1.89) 0.001 1.47 (1.10−1.95) 0.009 0.018 Recessive 2.14 (1.28−3.57) 0.004 3.23 (1.73−6.02) < 0.001 < 0.001 Additive 1.44 (1.19−1.75) < 0.001 1.51 (1.20−1.90) < 0.001 < 0.001 Note. *Adjusted for maternal education level, family annual income, residence areas, history of adverse pregnancy outcomes, history of pregnancy related complications, family consanguineous marriages, family history of congenital malformation, alcohol use before pregnancy, active or passive smoking before pregnancy, cold or fever history for this pregnancy, folate. OR, odds ratio; CI, confidence interval; SNPs, single nucleotide polymorphisms; FDR_P, false discovery rate P. supplementation and the remaining SNPs. Table 5. Interactions between maternal cytochrome P450 gene and drug use for risk of congenital heart defect in offspring
Maternal drug use Maternal cytochrome P450 genotype Number
of controlNumber
of caseAdjusted OR (95% CI)* P Regression coefficient Interactive coefficient γ1 γ2 Ovulatory drugs rs1065852 No Wild genotype (A/A) 188 109 1 No Variant genotype (A/T or T/T) 447 424 1.68 (1.24−2.27) 0.001 0.519 (βg) Yes Wild genotype (A/A) 4 12 5.65 (1.59−20.11) 0.008 1.732 (βe) Yes Variant genotype (A/T or T/T) 13 24 3.84 (1.74−8.49) 0.001 1.345 (βg*e) 2.592 0.777 Antidepressant drugs rs1065852 No Wild genotype (A/A) 186 114 1 No Variant genotype (A/T or T/T) 445 410 1.59 (1.15−2.20) 0.005 0.462 (βg) Yes Wild genotype (A/A) 6 7 8.23 (2.22−30.44) 0.002 2.108 (βe) Yes Variant genotype (A/T or T/T) 15 38 8.32 (3.56−19.45) 0.000 2.118 (βg*e) 4.584 1.005 Traditional Chinese drugs rs1065852 No Wild genotype (A/A) 176 97 1 No Variant genotype (A/T or T/T) 401 369 1.83 (1.29−2.57) 0.001 0.602 (βg) Yes Wild genotype (A/A) 16 24 6.63 (2.80−15.71) 0.000 1.892 (βe) Yes Variant genotype (A/T or T/T) 59 79 3.25 (1.94−5.44) 0.000 1.179 (βg*e) 1.958 0.623 Antiabortifacients rs1065852 No Wild genotype (A/A) 171 96 1 No Variant genotype (A/T or T/T) 400 353 1.58 (1.12−2.22) 0.009 0.457 (βg) Yes Wild genotype (A/A) 21 25 1.66 (0.74−3.70) 0.216 0.507 (βe) Yes Variant genotype (A/T or T/T) 60 95 2.47 (1.48−4.10) 0.001 0.902 (βg*e) 1.974 1.779 Ovulatory drugs rs16947 No Wild genotype (C/C) 449 334 1 No Variant genotype (C/G or G/G) 186 199 1.52 (1.13−2.05) 0.006 0.420 (βg) Yes Wild genotype (C/C) 13 19 2.87 (1.13−7.28) 0.027 1.054 (βe) Yes Variant genotype (C/G or G/G) 4 17 6.49 (1.82−23.14) 0.004 1.871 (βg*e) 4.455 1.775 Antidepressant drugs rs16947 No Wild genotype (C/C) 441 329 1 No Variant genotype (C/G or G/G) 190 195 1.49 (1.10−2.01) 0.010 0.397 (βg) Yes Wild genotype (C/C) 21 24 3.81 (1.72−8.44) 0.001 1.338 (βe) Yes Variant genotype (C/G or G/G) 0 21 − 0.998 21.672 (βg*e) Traditional Chinese drugs rs16947 No Wild genotype (C/C) 405 283 1 No Variant genotype (C/G or G/G) 172 183 1.65 (1.20−2.26) 0.002 0.500 (βg) Yes Wild genotype (C/C) 57 70 2.59 (1.61−4.18) 0.000 0.952 (βe) Yes Variant genotype (C/G or G/G) 18 33 3.55 (1.72−7.29) 0.001 1.265 (βg*e) 2.530 1.329 Antiabortifacients rs16947 No Wild genotype (C/C) 408 270 1 No Variant genotype (C/G or G/G) 163 179 1.76 (1.28−2.41) 0.000 0.563 (βg) Yes Wild genotype (C/C) 54 83 2.05 (1.28−3.30) 0.003 0.720 (βe) Yes Variant genotype (C/G or G/G) 27 37 1.67 (0.87−3.21) 0.125 0.512 (βg*e) 0.909 0.711 Note. *Adjusted for maternal education level, family annual income, residence areas, history of adverse pregnancy outcomes, history of pregnancy related complications, family consanguineous marriages, family history of congenital malformation, alcohol use before pregnancy, active or passive smoking before pregnancy, cold or fever history for this pregnancy, and folate supplementation. OR: odds ratio; CI: confidence interval. -
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