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European Heart Journal Advance Access originally published online on April 25, 2008
European Heart Journal 2008 29(11):1424-1431; doi:10.1093/eurheartj/ehn170
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Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2008. For permissions please email: journals.permissions@oxfordjournals.org

Eight-fold increased risk for congenital heart defects in children carrying the nicotinamide N-methyltransferase polymorphism and exposed to medicines and low nicotinamide

Lydi M.J.W. van Driel1,2, Huberdina P.M. Smedts1, Willem A. Helbing2, Aaron Isaacs3, Jan Lindemans4, André G. Uitterlinden4,5,6, Cornelia M. van Duijn6, Jeanne H.M. de Vries7, Eric A.P. Steegers1 and Regine P.M. Steegers-Theunissen1,2,3,6,*

1 Division of Obstetrics and Prenatal Medicine, Department of Obstetrics and Gynaecology, Erasmus University Medical Centre, s-Gravendijkwal 230, 3015 CE Rotterdam, The Netherlands
2 Division of Paediatric Cardiology, Department of Paediatrics, Erasmus University Medical Centre, Rotterdam, The Netherlands
3 Department of Clinical Genetics, Erasmus University Medical Centre, Rotterdam, The Netherlands
4 Department of Clinical Chemistry, Erasmus University Medical Centre, Rotterdam, The Netherlands
5 Department of Internal Medicine, Erasmus University Medical Centre, Rotterdam, The Netherlands
6 Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, The Netherlands
7 Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands

Received 29 October 2007; revised 22 February 2008; accepted 4 April 2008; online publish-ahead-of-print 25 April 2008.

* Corresponding author. Tel: +31 10 4636886, Fax: +31 10 4636815, Email: r.steegers{at}erasmusmc.nl


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
Aims: Congenital heart defects (CHDs) have a multifactorial origin, in which subtle genetic factors and peri-conception exposures interact. We hypothesize that derangements in the homocysteine and detoxification pathways, due to a polymorphism in the nicotinamide N-methyltransferase (NNMT) gene, low maternal dietary nicotinamide intake, and medicine use in the peri-conception period, affect CHD risk.

Methods and results: In 292 case and 316 control families, maternal peri-conception medicine use and low dietary intake of nicotinamide (≤13.8 mg/day) were independently associated with CHD risk [odds ratio (95% confidence interval) 1.6 (1.1–2.3) and 1.5 (1.03–2.3), respectively]. No significant association was found for the NNMT AG/AA genotype in mothers [0.9 (0.7–1.3)], fathers [1.1 (0.8–1.6)], or children [1.1 (0.8–1.6)]. However, the combination of peri-conception medicine use, low dietary nicotinamide intake, and the NNMT AG/AA genotype in mothers or children showed risk of 2.7 (1.02–8.1) and 8.8 (2.4–32.5), respectively.

Conclusion: Children carrying the NNMT A allele face additional CHD risk in combination with peri-conception exposure to medicines and/or a low dietary nicotinamide intake. These findings provide a first set of data against which future studies with larger sample sizes can be compared with.

Key Words: Cardiovascular anomalies • Aetiology • NNMT • Nutrition • Medicine • B-vitamin


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
Congenital heart defects (CHDs) are among the most common congenital malformations and are a leading cause of peri-natal mortality. Over 85% of CHDs have a multifactorial origin, involving genetic factors, maternal nutrition, and lifestyle factors during embryogenesis.1

One important risk factor for CHDs is maternal hyperhomocysteinaemia, which can be caused by subtle variations in genes, such as methylene tetrahydrofolate reductase (MTHFR)2 and a low dietary folate intake.3,4 It is very likely that other nutrients involved in this pathway are implicated as well.5,6 Furthermore, it is increasingly apparent that medicines in general exert side effects sometimes due to interference with the nutrient status. Interestingly, medicines and nutrients can be metabolized by the same detoxification pathways.7

Against this background, it is interesting to note that a new candidate gene for hyperhomocysteinaemia was identified in a genome-wide study.8 Linkage was shown in chromosomal region 11q23, where the nicotinamide N-methyltransferase (NNMT, E.C. 2.1.1.1) gene is located; it was explained by one single-nucleotide polymorphism (SNP) in this gene (dbSNP rs694539, minor allele frequency 16.7% in European population). The NNMT enzyme catalyses the N-methylation of nicotinamide and other pyridines. The methyl group used in this reaction is generated during the conversion of S-adenosylmethionine (SAM) to S-adenosylhomocysteine (SAH); SAM and SAH are both important intermediates in the homocysteine pathway. This NNMT enzyme is important for energy supply, but also for detoxification processes of medicines that undergo methylation via methyltransferases, such as tricyclic antidepressants.9 Nicotinamide (vitamin B3) is a water-soluble B-vitamin, essential for energy supply and the substrate for NNMT.

As a mother is the environment of the developing foetus, we hypothesized that the NNMT polymorphism in a mother or child and a low maternal dietary intake of nicotinamide and medicine use in the peri-conception period may be risk factors for CHDs. This hypothesis was tested in a case–control family study in an ethnically homogeneous population in the western part of the Netherlands.


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 Funding
 Acknowledgements
 References
 
Study population
This study is part of the HAVEN study, whose name is a Dutch acronym for the ongoing investigation of genetic and environmental factors in the aetiology and prevention of CHDs. From June 2003, this study has included cases from four University Medical Centres and controls in collaboration with the child health centres of ‘Thuiszorg Nieuwe Waterweg Noord’ in the Rotterdam area. The domain population comprised case children and control children living in the western part of the Netherlands. The materials and methods for this study have been described previously and are summarized in what follows.10

In the analyses, we included case children and control children with their parents from whom DNA was available. All children were aged between 11 and 18 months, of European origin, and no familial relationship existed between cases and controls.11 Successful DNA analysis was performed in 283 case children, 291 case mothers, and 292 case fathers. The CHD phenotypes included were tetralogy of Fallot (n = 30), transposition of the great arteries (n = 51), atrioventricular septal defect (n = 30), peri-membranous ventricular septal defect (n = 81), coarctation of the aorta (n = 28), aortic valve stenosis (n = 6), pulmonary valve stenosis (n = 50), and hypoplastic left heart syndrome (n = 16). The selection of the included CHD phenotypes was based on experimental and epidemiological studies that showed that hyperhomocysteinaemia and related gene–environment interactions are involved in their aetiology.12–14 Two paediatric cardiologists diagnosed the CHDs using echocardiography and/or cardiac catheterization and/or surgery data.

DNA was available from 316 control children, 313 control mothers, and 314 control fathers. These children had no major congenital malformations or chromosomal abnormalities according to the medical record and regular health checks by physicians of the child health centres. A smaller group was used for the combined analyses, because we excluded mothers who were pregnant or lactating, and those who reported that their diet at the time of the study moment was different from that during the peri-conception period.

The study protocol was approved by the Central Committee on Research involving Human Subjects and the Institutional Review Boards (Medical Ethics Committees) of all participating hospitals. In addition, written informed consent was obtained from every participant.

Measurements
All parents filled out a general questionnaire about 16 months after the birth of the index child. At this fixed study moment, mothers also filled out a standardized and validated food-frequency questionnaire (FFQ) on their food intake over the previous 4 weeks.15 At the same time, blood or buccal swabs were obtained to extract DNA from all children and their parents. The questionnaires were filled out at home and checked for completeness and consistency by the researcher during the hospital visit.

The general questionnaire referred to two different time periods. The first period was the peri-conception period, which was defined as 4 weeks prior to conception until 8 weeks after conception. The second period was defined as 4 weeks before the study moment, i.e. ~16 months after the index pregnancy. We collected sociodemographic characteristics such as age, ethnicity, and educational level, and also obtained information on lifestyle factors, such as the use of medicine, alcohol, tobacco, and B-vitamin supplements in both time periods. Medicine use was defined as any prescribed use of medicine. Overall, the different medicines reported were mainly antibiotics, anticonvulsants, anti-inflammatory medicines, hormones, and antimycotics. Women were defined as ‘tobacco users’ if they reported having used at least 1–10 cigarettes and/or cigars per day. Alcohol use was defined as any use of alcohol. The use of B-vitamin supplements in the peri-conception period was defined as the daily use during the complete period. Inconsistent users or mothers who used B-vitamin supplements only during a part of the peri-conception period were classified as non-users.

The FFQ filled out by the mothers covered their daily dietary intake over 4 weeks prior to the study moment, i.e. ~16 months after the index pregnancy. The dietary intake collected at this moment is comparable with that in the peri-conception period. This is supported by others.16,17 From the FFQ, we extracted total energy, dietary nicotinamide, and folate intake for analysis. At the hospital visit, maternal weight (weighing scale, SECA, Hamburg, Germany) and height (anthropometric rod, SECA) were measured.

Laboratory determinations
DNA from mothers, fathers, and children was obtained from either a blood sample or a buccal swab. Genomic DNA was isolated from 0.2 mL ethylenediamine tetra-acetate whole blood with the Total Nucleic Acid Extraction kit on a MagNA Pure LC (Roche Molecular Biochemicals, Mannheim, Germany). Of four case children, one case father and one control father DNA was isolated from buccal swabs instead of blood samples because of logistical problems or failure in blood sampling. The DNA isolation was carried out using the QuickExtract DNA Extraction Solution 1.0 according to the manufacturers’ instructions (Epicentre, Madison, WI, USA). NNMT genotyping was performed using an Assays-on-Demand (SNP ID rs694539, Applied Biosystems, Foster City, CA, USA) allelic discrimination assay on a Taqman 7000 analyser (Applied Biosystems) according to manufacturers’ instructions (http://www.appliedbiosystems.com). Polymerase chain reaction was performed using 384-well plates. Each genotype plate contained no DNA template (water) controls and a total of 75 randomly chosen duplicate samples. The reproducibility was 100%.

Data analysis
Sociodemographic and lifestyle characteristics both at the study moment and in the peri-conception period were compared between cases and controls using the {chi}2 test for categorical variables and the Mann–Whitney U test for continuous variables. All continuous variables are presented as medians with interquartile range, because some of them were positively skewed even after transformation.

Genotype data were checked for Mendelian segregation errors. Inconsistent triads (nine case triads and six control triads) were excluded from analysis. Deviation from Hardy–Weinberg equilibrium was tested with the {chi}2 test. Univariate logistic regression was used to compute odds ratios (ORs) and 95% confidence intervals (CIs) for the association between case–control status and the dichotomous variables NNMT polymorphism, medicine use, and nicotinamide intake. We used the dominant model by which the NNMT AG/AA genotype group was considered the risk group. Moreover, a subgroup analysis was performed on risk of NNMT polymorphism for each CHD phenotype separately.

Linkage and/or association between the NNMT polymorphism and CHD risk was tested using the family-based association test (FBAT), which looks for distortions in the transmission frequencies of a given allele, compared with the assumed transmission frequencies of random transmission.18 FBAT is attractive because it is robust against population admixture or stratification.

Logistic regression analyses were performed to assess the additive effects of the NNMT polymorphism, medicine use, and nicotinamide intake on the risk of CHDs. First, we coded separate categories for the risk of the genotype of mother or child in combination with peri-conception medicine use. NNMT GG carriers without peri-conception medicine use were expected to have the lowest risk and therefore considered as the reference category. The highest risk group comprised NNMT AG/AA carriers and peri-conception exposure to medicine. Secondly, different categories were created of the combined risk of the genotype with maternal dietary nicotinamide intake. Therefore, nicotinamide intake was divided into low and high intake by using the lowest tertile of the control mothers as a cut-off point (≤13.8 mg/day). The different subgroups thus ranged from the combination of the NNMT-GG polymorphism with high maternal dietary nicotinamide intake (reference group) to the NNMT AG/AA polymorphism with low maternal dietary nicotinamide intake. We computed adjusted ORs with 95% CIs in a multivariable logistic regression model. These ORs were adjusted for family history of CHD, maternal age, dietary folate intake, and peri-conception use of alcohol, tobacco, and B-vitamin supplements, because they were considered potential confounders.

We also tested multiplicative interaction between NNMT genotype (coded as GG = 0 and AG/AA = 1 of mothers or children), dietary intake of nicotinamide (both as a continuous variable and as a dichotomized variable), and peri-conception medicine use. This was done using multivariable logistic regression models in which we included the interaction terms ‘medicine use x NNMT genotype’, ‘nicotinamide intake x NNMT genotype’, and ‘medicine use x nicotinamide intake x NNMT genotype’ and calculated P-values for interaction. The additive effects and the interaction analyses were adjusted for multiple testing by the method of Bonferroni. Probability values of P < 0.05 were considered statistically significant and all tests were two-sided.

Analyses were performed with SPSS for Windows software (version 15.0; SPSS Inc., Chicago, IL, USA) or FBAT 3.2.


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 Funding
 Acknowledgements
 References
 
Figure 1 depicts the study population flowchart. The sociodemographic and lifestyle characteristics of mothers, fathers, and children are presented in Table 1. Maternal age was slightly, although significantly, different between cases and controls and was included as a putative confounder in the further analysis. Case mothers used more medicines in the peri-conception period; this led to an adjusted OR (95% CI) of 1.5 (1.0–2.3) with a crude P-value of 0.027 and an adjusted P-value of 0.032. After dietary nicotinamide intake has been categorized into low or high intake, mothers on a diet low in nicotinamide showed a 1.6-fold higher CHD risk (95% CI 1.0–2.5); crude P-value = 0.042, adjusted P-value = 0.039. The adjusted OR (95% CI) for nicotinamide intake as a continuous variable was 0.94 (0.87–1.00); crude P-value = 0.210, adjusted P-value = 0.056. The adjusted ORs and P-values were adjusted for maternal age, peri-conception use of tobacco, alcohol, and B-vitamins, family history of CHD, total dietary energy, and folate intake. There were no significant differences in sociodemographic and lifestyle characteristics between case and control children and fathers.


Figure 1
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  		Figure 1 Study population flowchart. The numbers are the absolute numbers of case mothers/control mothers.

 

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  		Table 1 Sociodemographic and lifestyle characteristics

 
Table 2 presents the distribution of the genotype frequencies and the risk estimates of the NNMT polymorphisms of mothers, fathers, and children. All genotype distributions were in Hardy–Weinberg equilibrium. NNMT frequencies were not different between cases and controls. FBAT did not reveal any statistically significant association between the NNMT genotype and CHD risk (data not shown).


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  		Table 2 Distribution of the nicotinamide N-methyltransferase genotypes in families

 
Table 3 presents the distribution of the genotype frequencies and the risk estimates of the NNMT polymorphisms of mothers, fathers, and children for each CHD phenotype separately. There are no significant effects; though of interest are the borderline-significant increased risk estimates for transposition of the great arteries, which are consistent for mothers, fathers, and children.


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  		Table 3 Subgroup analysis of the association between the nicotinamide N-methyltransferase AG/AA polymorphism and each congenital heart defect phenotype

 
Interaction analysis
Figure 2 presents the risk estimates in mothers and children carrying the NNMT genotypes, peri-conception exposure to medicines (left panels), and low or high nicotinamide intake (right panels). Children who carry the NNMT GG genotype and have been peri-conceptionally exposed to medicines have an almost two-fold significantly increased risk of having a CHD than non-exposed children with the same genotype (adjusted P-value = 0.018, Bonferroni adjusted P-value = 0.036). Moreover, mothers who carry the NNMT GG genotype and have a low dietary nicotinamide intake show a two-fold significantly higher risk than mothers with the same genotype who have a high nicotinamide intake (adjusted P-value = 0.012, Bonferroni adjusted P-value = 0.036). Figure 3 shows the results of medicine and nicotinamide intake and the NNMT genotypes in mothers and children. The combination of the mother’s NNMT AG/AA genotype with low maternal dietary intake of nicotinamide and use of medicines showed the highest relative risk [OR (95% CI) 3.2 (1.02–10.2), adjusted P-value = 0.048, Bonferroni adjusted P-value = 0.144]. Moreover, the CHD risk was almost nine times higher in children carrying the NNMT AG/AA genotype who were peri-conceptionally exposed to medicines and low maternal intake of nicotinamide (95% CI = 2.3–33.0, adjusted P-value = 0.002, Bonferroni adjusted P-value = 0.006).


Figure 2
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  		Figure 2 Peri-conception medicine use or dietary nicotinamide intake combined with the nicotinamide N-methyltransferase genotypes of the mother or the child and congenital heart defect risk. The first group in each panel represents the reference group. In the left two panels, the odds ratios with 95% confidence intervals are shown of the different subgroups with combinations of maternal medicine use in the peri-conception period and nicotinamide N-methyltransferase genotype of the mother (first panel) or the child (second panel). In the right two panels, the odds ratios with 95% confidence intervals are shown of the combinations of maternal dietary nicotinamide intake with nicotinamide N-methyltransferase genotype of the mother (first panel) or the child (second panel).

 

Figure 3
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  		Figure 3 Peri-conception medicine use, dietary nicotinamide intake, and the nicotinamide N-methyltransferase genotype. The first category in each panel is the reference category. These consist of mothers who did not use any medicines in the peri-conception period, who had a high dietary intake of nicotinamide based on the 30th percentile of the control group, and who carried the nicotinamide N-methyltransferase GG-variant (left panel); the nicotinamide N-methyltransferase GG-variant in children (right panel).

 
We did not detect any significant multiplicative interactions between the NNMT genotype and either of the environmental factors (data not shown).


   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
Funding
 Acknowledgements
 References
 
This is the first study to investigate associations between the NNMT polymorphism and the combined peri-conception exposure to medicine and/or a diet low in nicotinamide on CHD risk. The NNMT AG/AA genotypes did not affect CHD risk. The association with the subgroup of transposition of the great arteries, although not significant, is interesting. However, the results of the separate CHD phenotypes should be further investigated in much larger data sets. Peri-conception medicine and low dietary nicotinamide intake independently almost two-fold increased the risk of CHD. This is supported by the additive effect between the NNMT AG/AA genotypes of both mothers and children and peri-conception medicine or low nicotinamide intake, of which the environmental factors seem to have the largest contribution. An almost nine-fold increased CHD risk was found for children carrying the NNMT AG/AA genotype who were exposed to both peri-conception medicines and low nicotinamide intake.

So far, no epidemiological studies reported on associations between the NNMT polymorphism and CHD or other congenital malformations. However, up to now, three papers have been published on the effects of the NNMT polymorphism on plasma homocysteine levels. Souto et al.8 found strong evidence that the NNMT gene is a major determinant of plasma homocysteine in a Spanish population. Evidence on the functionality of the NNMT polymorphism is still conflicting. Zhang et al.19 found that Japanese men (≥40 years) with low plasma folate between 1.5 and 4.8 nmol/L, who carried the NNMT GG genotype, had mildly elevated plasma homocysteine concentrations. In a Danish population, no significant effect of the NNMT polymorphism on homocysteine levels was shown.20 In that study, it is suggested that the MTHFR gene is responsible for almost all variations in the homocysteine level attributable to genetic factors. The exact function of NNMT in the homocysteine pathway is not completely understood. NNMT is a SAM-dependent methyltransferase and predominantly metabolizes nicotinamide to N-methyl nicotinamide. NNMT binds the methyl group generated from the conversion of SAM into SAH, which are both precursors of homocysteine. Therefore, alterations in the activity of NNMT may affect the SAH and homocysteine level. The maternal homocysteine levels were also available in this study, which enabled us to perform an additional analysis to test whether homocysteine is an effect modifier of CHD risk. In the interaction analysis, the interaction term NNMT x homocysteine level was included. The P-value of 0.681 indicates that homocysteine is not an effect modifier of CHD risk. Although we cannot show effect modification by homocysteine, it is an interesting issue that should be further investigated.

We demonstrated that peri-conception medicine use significantly increased CHD risk. Others reported associations between anticonvulsants and unspecified CHD phenotypes, and non-steroidal anti-inflammatory medicines and transposition of the great arteries and ventricular septal defects.21,22 We hypothesize that children are in particular at increased risk for CHD when their detoxification pathway is also compromised due to polymorphisms in methylated genes, such as NNMT,23 because NNMT plays a role in the detoxification of medicines that undergo methylation.24 Therefore, if the NNMT polymorphism leads to a decreased enzyme activity resulting in an altered detoxification of methylated medicines, it may enhance CHD risk. This is supported by the additive effect shown especially in the children (Figure 2). Unfortunately, we were not able to make a distinction between the different types of medicines because of the small numbers. Further research with larger sample sizes is needed to explore these specific associations.

We also demonstrated that a maternal dietary intake of nicotinamide <13.8 mg/day almost two-fold increased the risk of CHD. In epidemiological and experimental studies, levels of nicotinamide intake comparable with our study have been shown to be a risk factor for oral facial clefts and spina bifida.25–27 Nicotinamide is important for cellular maintenance, antioxidant activity, DNA repair mechanisms, and methylation processes, which are important biological processes in embryonic cardiac development. The Dutch Recommended Daily Allowance (RDA) of nicotinamide is 13 mg nicotinic amide equivalents per day for women >18 years.28 The cut-off value that we used (≤13.8 mg/day) was based on the lowest tertile of the control group and is just slightly above the RDA. In our population, 23% of the control mothers and 27% of the case mothers had a nicotinamide intake below the Dutch RDA. This is a high proportion of which underreporting is not a likely explanation, because the FFQ has been validated twice, and after energy adjustment, the results remained the same. It is possible that the association is due to potential confounders, such as folate, because nicotinamide and folate are present in liver, fruits, and vegetables. Folate intake was not significantly different between case mothers and control mothers (Table 1). Therefore, it is very unlikely that an accompanying low folate intake explains the risks associated with nicotinamide intake.

Epigenetics is a mechanism in which nutritional factors regulate gene expression, whereby methylation is best understood. NNMT and nicotinamide play a role in the transfer of methyl groups to genes and as such are involved in the epigenetics of mother and child. Therefore, we suggest that the demonstrated additive risks of the NNMT AG/AA genotype and nicotinamide intake may affect the control of specific embryonic cardiac genes. This needs, however, detailed experimental studies.

Strengths and weaknesses of our study have to be considered as well. Recall bias is one of the pitfalls of case–control designs. However, this is not frequently present in case–control studies on congenital malformations.29,30 Our sample size of 283 case families might have been too small to detect a 1.5-fold increased CHD risk in children carrying the NNMT AG/AA genotype (risk allele frequency of 20%, type 1 error of 0.05, CHD population risk of 0.008 resulted in a power of 65%). Moreover, the fixed study moment, as strength of our study, minimizes recall bias. Finally, we show an effect of medicine only in carriers of the A allele. As mothers and children are not aware of their genotypes, this association cannot be explained by recall bias. Other strengths of our study are the inclusion of CHD phenotypes associated with hyperhomocysteinaemia and the ethnic homogeneity of the families. The latter is particularly important when studying genetic factors and culture-determined lifestyle factors, such as diet.

In conclusion, we identified new risk factors for complex CHD and gained new insights in its multifactorial aetiology. Our results provide a first set of data against which future studies with larger sample sizes can be compared with.


   Funding
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Funding
Acknowledgements
 References
 
This research was supported by The Netherlands Heart Foundation (grant 2002.B027) and the Corporate Development International (grant 2005).


   Acknowledgements
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
References
 
We thank all participating families and acknowledge the coordinating of the recruitment by Professor Dr J. Ottenkamp and Dr F.M.H. Siebel of the Department of Paediatric Cardiology of Leiden University Medical Centre, Academic Medical Centre, and VU University Medical Centre in Amsterdam, and the child health centres of ‘Thuiszorg Nieuwe Waterweg Noord’. We also thank Dr A.C. Verkleij-Hagoort, Miss M. Verlinde, and Miss S.A. Borst for data entry and recruitment. We thank Mr B. van Zelst for laboratory assistance and Mrs S. Meyboom for data extraction from the FFQs.

Conflict of interest: none declared.


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 

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