Article

Interaction between maternal caffeine intake during pregnancy and CYP1A2 C164A polymorphism affects infant birth size in the Hokkaido study

Abstract

Background

Caffeine, 1,3,7-trimethylxanthine, is widely consumed by women of reproductive age. Although caffeine has been proposed to inhibit fetal growth, previous studies on the effects of caffeine on infant birth size have yielded inconsistent findings. This inconsistency may result from failure to account for individual differences in caffeine metabolism related to polymorphisms in the gene for CYP1A2, the major caffeine-metabolizing enzyme.

Methods

Five hundred fourteen Japanese women participated in a prospective cohort study in Sapporo, Japan, from 2002 to 2005, and 476 mother–child pairs were included for final analysis.

Results

Caffeine intake was not significantly associated with mean infant birth size. When caffeine intake and CYP1A2 C164A genotype were considered together, women with the AA genotype and caffeine intake of ≥300 mg per day had a mean reduction in infant birth head circumference of 0.8 cm relative to the reference group after adjusting for confounding factors. In a subgroup analysis, only nonsmokers with the AA genotype and caffeine intake of ≥300 mg per day had infants with decreased birth weight (mean reduction, 277 g) and birth head circumference (mean reduction, 1.0 cm).

Conclusion

Nonsmokers who rapidly metabolize caffeine may be at increased risk for having infants with decreased birth size when consuming ≥300 mg of caffeine per day.

Main

Caffeine, 1,3,7-trimethylxanthine, is widely consumed in the form of coffee, tea, and cocoa. Cytochrome P450 1A2 (CYP1A2) is the main enzyme involved in the metabolism of caffeine, accounting for 95% of caffeine clearance. Its primary metabolites are paraxanthine (1,7-dimethylxanthine), theobromine (3,7-dimethylxanthine), and theophylline (1,3-dimethylxanthine), which account for 82%, 11%, and 5% of caffeine metabolites, respectively (1, 2).

Although the UK Standards Agency has recommended that women of reproductive age maintain their caffeine intake below 200 mg per day (3), many women consume caffeine during pregnancy. In Japan, mean caffeine intake among women aged 30–39 years was 213 mg per day, and 7% of women were found to consume >400 mg per day (4). In the United Kingdom, 18% of women of childbearing age consumed caffeine in excess of 300 mg per day (5). Maternal caffeine intake can directly affect the fetus because caffeine and its metabolites readily cross the placental barrier and the fetoplacental unit to rely on maternal metabolism for caffeine clearance (6, 7).

Maternal caffeine intake may increase the risk for fetal growth restriction. Significant associations have been found between high caffeine intake during pregnancy and decreased birth weight or increased risk of small-for-gestational-age infants (8, 9, 10). Several studies, however, failed to replicate these associations (11, 12). One study found that pregnant women who consume >200 mg of caffeine per day have an increased risk for spontaneous abortion (SA) independent of pregnancy-related symptoms such as nausea (13). A similar result was found in a population-based case–control study of pregnant women, among whom the risk for SA increased in the exposure group consuming >300 mg of caffeine per day, but in this case the association did not exist after adjusting for nausea (14). Klonoff-Cohen et al. (15) reported a higher risk for preterm birth with increasing caffeine intake during pregnancy; however, most studies did not find an association between caffeine intake and length of gestation (8, 12). Recent dose–response meta-analyses examining the association between prenatal caffeine exposure and risk for adverse pregnancy outcomes indicate that greater caffeine intake during pregnancy may be associated with an increased risk for SA, low birth weight, and small-for-gestational-age infants, but not with preterm birth (16, 17).

The inconsistency among these results may be due to different methods for estimation of caffeine intake, retrospective assessment of caffeine intake, or variations in maternal caffeine metabolism. Previous studies have demonstrated the importance of metabolic differences in maternal caffeine intake for fetal development. Of the several known CYP1A2 polymorphisms with associated in vivo functional changes, the C164A polymorphism is of particular interest, as it leads to a slow caffeine metabolizer phenotype (CC/CA) and a fast phenotype (AA) with higher ratios of caffeine metabolites. Maternal caffeine intake of ≥100 mg per day is associated with an increased risk for SA as compared with an intake of ≤99 mg per day among women with the AA genotype (18). A significantly increased risk for recurrent pregnancy loss has been found in women with the AA genotype who consume ≥300 mg of caffeine per day, as compared with those who consume ≤99 mg of caffeine per day (19). This genotype is also associated with an increased risk for neural tube defects (20). These results suggest that the risk of maternal caffeine intake during pregnancy having an impact on fetal development is higher among women with fast caffeine metabolism than among those with slow caffeine metabolism. However, the issue of whether this genotype is a modifying factor in the association between caffeine intake during pregnancy and infant birth size has not yet been investigated. To clarify the effects of caffeine on fetal growth, data from a prospective cohort study were analyzed to ascertain whether increased caffeine intake was associated with decreased infant birth size when considering the CYP1A2 C164A polymorphism and controlling for confounding factors such as smoking status.

Results

As shown in Table 1, the mean maternal age was 30.7 years, with 266 (55.9%) women having more than a high-school education. One hundred and two (21.4%) women were classified as smokers during pregnancy and 148 (31.1%) women drank alcohol during pregnancy.

Table 1 Characteristics of mother–infant pairs in relation to maternal caffeine intake levels during pregnancy (n=476)

Maternal and infant characteristics of the study population were then reviewed in relation to the three categories of caffeine intake. Maternal pre-pregnancy body mass index, annual household income, education level, parity, infant gender, infant birth size, and gestational age did not differ significantly between the <100, 100–299, and ≥300 mg per day caffeine intake groups. The frequency of CYP1A2 genotypes was also similar for the <100, 100–299, and ≥300 mg per day caffeine intake groups, and distributions were in Hardy–Weinberg equilibrium (P=0.863, 0.647, and 0.572, respectively). Genotype frequencies were similar to those published previously for a Japanese population (21).

There was a tendency for smokers to have a high caffeine intake, with 35.5% of smokers consuming ≥300 mg of caffeine per day, compared with 11.1% consuming <100 mg of caffeine per day. Women who were classified as smokers during pregnancy had significantly lighter babies than did nonsmokers (2,997 vs. 3,086 g; P=0.032, data not shown) and had infants with birth weights similar to those of mothers consuming ≥300 mg of caffeine per day (2,962 g). When considering alcohol intake, a larger proportion of alcohol drinkers (36.2%) consumed 100–299 mg of caffeine per day compared with those with <100 mg per day caffeine intake (24.4%). However, when alcohol intake was considered a continuous variable among women who drank during pregnancy, the median intake was similar for women in all three caffeine intake groups (Table 1).

The individual effects of caffeine intake and CYP1A2 genotype on mean infant birth size were then investigated using linear regression models with adjustment for confounding factors. The individual effect of maternal smoking status during pregnancy on infant birth size was also analyzed. When the effect of caffeine intake alone was analyzed using <100 mg per day consumption as the reference group, there was a nonsignificant decrease in birth weight for caffeine intake of ≥300 mg per day. The maternal CYP1A2 genotype alone was not significantly associated with mean infant birth weight. When considering maternal smoking status during pregnancy, infants of smokers had a mean reduction in birth weight of 85 g (95% confidence interval (CI): −157, −12) as compared with infants born to nonsmokers after adjustment for confounding factors (Table 2A). Mean birth length and head circumference, however, were not affected by maternal smoking status during pregnancy (Table 2B,C).

Table 2 Individual associations of maternal caffeine intake during pregnancy, maternal smoking status, and maternal CYP1A2 genotype with infant birth size (n=476)

The mothers were then categorized into six subgroups by CYP1A2 genotype and caffeine intake. Linear regression analysis was performed, using women with the CC/CA genotype and <100 mg per day caffeine intake as the reference category. Table 3 shows the results from the main model on infant birth weight. When compared to the reference group, mothers with the AA genotype and caffeine intake of ≥300 mg per day had a mean reduction in infant birth weight of 316 g (P=0.004) in the crude model; however, the mean reduction in infant birth weight was not significant in the adjusted model (P=0.116). After stratification by smoking status during pregnancy, only nonsmokers with the AA genotype and caffeine intake of ≥300 mg per day had infants with decreased infant birth weight (mean decrease, 277 g; P=0.024). The interaction between the AA genotype and caffeine intake of ≥300 mg per day was also significant (P=0.019). For infant birth length, we found the largest decrease in infant birth length (0.7 cm) for women with the AA genotype and caffeine intake of ≥300 mg per day in the nonsmoker group, although it was not significant (Table 4).

Table 3 Combined association of maternal caffeine intake during pregnancy and maternal CYP1A2 genotype with infant birth weight by maternal smoking status
Table 4 Combined association of maternal caffeine intake during pregnancy and maternal CYP1A2 genotype with infant birth length by maternal smoking status

The results from the main model on infant birth head circumference are presented in Table 5. Women with genotype AA and caffeine intake ≥300 mg per day had a mean reduction in infant birth head circumference of 1.2 cm (P=0.002) compared to the reference group in the crude model, and a mean reduction in infant birth head circumference of 0.8 cm (P=0.024) after adjusting for confounding factors. In the nonsmoker group, infants born to women with the AA genotype and caffeine intake of ≥300 mg per day showed a decrease in infant birth head circumferences of 1.0 cm in the adjusted model stratified by smoking status during pregnancy (P=0.027), whereas no CYP1A2 caffeine subgroups showed significant changes in infant birth head circumference in the smoking group.

Table 5 Combined association of maternal caffeine intake during pregnancy and maternal CYP1A2 genotype with infant birth head circumference by maternal smoking status

Discussion

To our knowledge, this is the first study to consider the effects of maternal caffeine intake during pregnancy and the CYP1A2 C164A polymorphism on infant birth size. The results show that when caffeine intake is considered independently of genetic factors, its consumption during pregnancy does not have a significant effect on mean infant birth size after adjustment for confounding factors. However, when both caffeine intake and the CYP1A2 genotype are considered, there appeared to be a significant effect on infant birth head circumference (P=0.024). The reductions in infant birth weight and birth length associated with caffeine and the CYP1A2 genotype, however, were eliminated after controlling for smoking and other factors. Previous studies have reported that small head circumference at birth influenced brain development and that low birth length was associated with behavioral problems during childhood (22, 23). Small birth size might adversely affect neurodevelopmental and cognitive outcomes. In a subset of nonsmokers with the CYP1A2 AA genotype and caffeine consumption of >300 mg per day, there was evidence of decreased infant birth weight and birth head circumference (P=0.024 and 0.027, respectively), as compared with women with the CC/CA genotype who consumed <100 mg of caffeine per day.

Individuals carrying the CYP1A2 AA genotype are fast metabolizers of caffeine and have higher levels of paraxanthine than do those carrying the CC and CA genotypes. Women with the high inducible genotype for CYP1A2 have an increased risk for harmful reproductive outcomes. Signorello et al. (18) evaluated the rate of caffeine metabolism as a risk factor for SA. Their results indicated that women with high CYP1A2 activity have an increased risk for SA (odds ratio (OR): 2.42, 95% CI: 1.01, 5.80 for 100–299 mg of caffeine per day; OR: 3.17, 95% CI: 1.22, 8.22 for ≥300 mg per day), but no increase in SA risk was observed in women with low CYP1A2 activity (OR: 0.46, 95% CI: 0.12, 1.73 for ≥300 mg per day) (18). Sata et al. (19) investigated how the association between maternal consumption of high levels of caffeine and the risk for recurrent pregnancy loss is modified by CYP1A2 activity in a case–control study. Recurrent pregnancy loss risk significantly increased among women with the CYP1A2 AA genotype (OR: 1.94, 95% CI: 0.57, 6.66 for 100–299 mg per day; OR: 5.23, 95% CI: 11.05, 25.9 for >300 mg per day; P=0.03). However, no associations were observed between recurrent pregnancy loss and the CYP1A2 AC/CC genotypes (19). These findings suggest that there may be adverse effects of the caffeine metabolite paraxanthine, rather than of caffeine itself.

A previous study found that paraxanthine concentrations are higher in women who have SAs than in the controls, and that the highest levels of paraxanthine had an increased risk for SA (OR: 1.9, 95% CI: 1.2, 2.8); however, the study reported no associations between SA and caffeine concentrations (24). For fetal growth, high concentrations of paraxanthine are associated with increased risk of IUGR (OR: 3.29, 95% CI: 1.17, 9.22), and the ratio of paraxanthine to caffeine, which is a marker of CYP1A2 enzymatic activity, is also associated with an increased risk of IUGR (OR: 1.21, 95% CI: 1.07, 1.37), whereas higher levels of caffeine are associated with a decreased risk of IUGR (25).

Recent experimental studies in animal models have indicated that prenatal caffeine exposure is associated with developmental toxicities (26). Prenatal caffeine ingestion increases maternal glucocorticoid (GC) levels and inhibits the expression of placental 11β-hydroxysteroid dehydrogenase-2, an enzyme that prevents fetal exposure to excessive maternal GC. Upon exposure to high levels of maternal GC, the expression of 11β-HSD-1 and GC receptor in the fetal hippocampus is enhanced, and then the functional development of the fetal hypothalamic–pituitary–adrenal (HPA) axis is inhibited through negative feedback regulation. The hippocampus is the primary negative feedback regulatory center of the HPA axis (27). In addition, caffeine can enter the fetus and directly inhibit 11β-HSD2 expression in the hippocampus. The reduced 11β-hydroxysteroid dehydrogenase-2 expression can promote the expression of 11β-HSD-1 and the GC receptor in the fetal hippocampus, which also inhibit the activity of the fetal HPA axis as a crucial switch for development in many organs, including the pituitary and the brain (28). It has been suggested that these changes are linked to impaired placental and fetal growth, such as decreased fetal body and brain weight (29). Paraxanthine also decreases placental 11β-hydroxysteroid dehydrogenase-2 expression and activity in cultured human trophoblast cells (30). It is possible that paraxanthine may have a greater impact than caffeine on growth and development in fetuses.

The question why adverse effects are more pronounced in nonsmokers with the AA genotype is of particular interest. Rodenburg et al. (31) examined the modifying effects of gender, age, smoking status, and CYP1A2 genotype on caffeine intake and showed that smoking status and gender were responsible for the largest differences in caffeine intake: men who smoked metabolized caffeine more rapidly, and the genetic effect explained only a portion of this effect. A previous study in a Turkish population also found that smoking status and gender explained most of the variation in the metabolite ratio of caffeine after coffee intake (24 and 10%, respectively), whereas genotype explained <1% (32). Thus, the lack of a significant association between caffeine intake, genotype, and birth measures among smokers in our study may be due to the stronger influence of smoking than of the CYP1A2 genotype on caffeine metabolism.

Two strengths of the present study are that possible recall bias due to retrospective data collection has been eliminated and that caffeine intake was assessed using a format fitted to the dietary habits of the study population. First, because women in this study assessed their average caffeine intake prospectively at enrollment, before birth outcomes were known, there was no possibility for women with reduced birth size infants to overestimate their caffeine consumption, or for women with heavier or healthier babies to underestimate intake. Second, a questionnaire based on a survey by Nagata et al. (33) was used to accurately assess caffeine consumption. However, although subjects chose from nine possible responses for frequency of caffeine intake, information on exact portion size and preparation method was not obtained. To ensure more accurate caffeine estimations, several classifications for canned coffee, instant coffee, and several subcategories for tea, as well as standard size notations for each category, were added for this study.

It has been suggested that the CYP1A2 activity may differ between ethnicities. Denden et al. (34) conducted a meta-analysis to assess an association between the CYP1A2 rs762551 polymorphism and caffeine consumption. Although Asians showed a significantly increased coffee intake compared to Caucasians, significant relationship between the AA genotype and coffee intake was found only in Caucasian ethnicity, not in Asians. Schliep et al. (35) investigated whether caffeine intake was associated with reproductive hormone levels and its effect was modified by race. They reported that caffeine intake ≥200 mg per day was associated with reduced free estradiol (E2) levels among Caucasian women and elevated E2 levels among Asian women; however, these differences by race may be due to limited numbers of Asians with high exposure. Although a significant effect of caffeine on birth size modified by maternal gene polymorphisms was found, further study with a larger population may help support the results of this study, as our study sample consisted of a relatively small number of women who consumed high levels of caffeine and who smoked during pregnancy. Moreover, interpretation of our results is limited by the following points: the average maternal age of 1,796 candidate women was 29.7±4.9 years and it was lower than that of 476 women. It is possible that women who took an interest in our study would have participated more frequently and this may limit generalizability of the enrolled study population, as the possibility of selection bias exists; levels of caffeine in urine or serum were not measured in this study. However, a recent study determined that reported caffeine intake estimates were strongly correlated with urinary and cord blood biomarkers throughout pregnancy, suggesting that self-reported caffeine intake is a satisfactory estimate of actual caffeine intake (36); the analyses may have been affected by possible uncontrolled or inadequately controlled confounding variables. Other limitations of this study are that nausea, thought to affect caffeine-seeking behavior and indicate overall health of the pregnancy (37), was not controlled for in the model. In addition, separate measures of caffeine intake during all three trimesters of pregnancy would serve to clarify both changes in caffeine-seeking behavior, as well as determine a critical window for adverse effects. Further research is needed to determine the adverse effects of paraxanthine on reproductive outcomes in both experimental and epidemiological studies.

In conclusion, after consideration of the CYP1A2 C164A genotype, nonsmokers who are fast metabolizers of caffeine and who consume ≥300 mg of caffeine per day have an increased risk of having infants with decreased birth weight and birth head circumference. The absence of these associations among smokers may be due to the stronger influence of smoking compared to CYP1A2 phenotypic effects on caffeine metabolism.

Methods

Study Participants

From July 2002 to October 2005, women who were residents of Sapporo and surrounding areas were asked to participate in a prospective cohort study (the Hokkaido Study on Environment and Children’s Health), which aimed to investigate whether environmental factors combined with genetic predisposition contribute to numerous adverse developments and health effects during childhood, as described previously (38) and this work was a part of the study. Participants were native Japanese women who enrolled at 23–35 weeks of gestation during a routine obstetric visit and delivered at Sapporo Toho Hospital.

A total of 1,796 pregnant women were invited to take part in the study. Of these women, 22% were excluded because they had decided to enroll in the Japanese cord blood bank and 3% were excluded because they delivered their baby at another hospital. Finally, 514 women agreed to participate (participation rate of 28.6%). Among these 514 women, 10 dropped out due to stillbirth, relocation, or voluntary withdrawal from the study before follow-up. Another 7 women with multiple pregnancies were excluded from analysis, 13 women were excluded due to pregnancy complications or illness (11 for pregnancy-induced hypertension, 1 for diabetes, and 1 for fetal heart failure), and blood samples could not be collected for 8 women; thus, there were finally 476 mother–child pairs for final analysis.

Data Collection

A self-administered questionnaire was used to collect relevant information at enrollment (weeks 23–35 of pregnancy). Information relating to smoking status, alcohol consumption, caffeine intake during pregnancy, annual household income, and education was included in the questionnaire. Information drawn from maternal and infant medical records included details of pregnancy complications, maternal age, maternal pre-pregnancy body mass index, parity, infant gender, gestational age, and infant birth size. A 40-ml blood sample was drawn from the peripheral vein of the mother. All samples were stored at −80 °C until analysis.

Caffeine intake during pregnancy was estimated using a modified version of the self-administered questionnaire used by Nagata et al. (33) and described in detail by Washino et al. (39). Average daily caffeine intake during pregnancy was estimated in milligrams of caffeine per day. The questionnaire included categories on beverages popular in Japan, including instant coffee (60 mg of caffeine per cup); regular coffee (50 mg per cup); decaffeinated coffee (0 mg per cup); canned coffee (50 mg per cup); black tea (60 mg per cup); oolong tea (30 mg per cup); powdered green tea (200 mg per cup); gyokuro (high-quality green tea, 100 mg per cup); other tea varieties including natural leaf teas, coarse green tea, brown rice tea, and roasted green tea (30 mg per cup); cocoa (5 mg per cup); cola (60 mg per glass); and caffeinated energy drinks (50 mg per bottle). The frequency of intake was divided into five categories: rarely/never, once or twice per month, once or twice per week, three to four times per week, or every day. The amount consumed per occasion was divided into four categories by cups (or glasses or bottles): one cup or less, two cups, three cups, or four or more cups. Average caffeine intake per day during pregnancy was calculated as the caffeine content per beverage multiplied by the amount consumed per occasion multiplied by the frequency of intake per day. In this study, caffeine exposure was categorized as <100, 100–299, and ≥300 mg per day (19, 40).

In this study, nonsmokers were defined as women who never smoked during pregnancy or those who quit during the first trimester, and smokers were defined as those who smoked throughout pregnancy or quit after the first trimester, based on self-reporting. Smoking status was classified in this manner because the mean birth weight of infants born to women who quit smoking during the first trimester was 3,123 g, similar to the mean birth weight of infants born to women who never smoked (3,060 g). Because infant mean birth weight decreased to 2,922 and 2,911 g when women quit smoking during the second and third trimester, respectively, these women were grouped with women who smoked throughout pregnancy. This agrees with previous findings that quitting smoking early in pregnancy does not greatly affect infant birth size (41).

Genotyping Analyses

CYP1A2 (C164A, rs762551) polymorphisms were determined by real-time PCR, using minor groove binder probes. DNA amplification was carried out in batches in a 96-well MicroAmp reaction plate on a Gene Amp 9700 thermal cycler (Applied Biosystems, Foster City, CA). The validated TaqMan probes were prepared and each of the reporters was quenched by excess minor groove binder. PCR was performed, and fluorescence of the products was measured using a 7300/7500 Real-Time PCR system (Applied Biosystems) (42, 43). This resulted in the clear identification of the CC, CA, and AA genotypes of CYP1A2. A CYP1A2 genotype of CC or CA indicated a slow metabolizer phenotype, and AA indicated a high inducible phenotype. These two phenotypes were used for statistical analyses.

Statistical Analyses

Maternal and infant characteristics were analyzed in relation to categories of maternal caffeine intake using the χ2-test for categorical variables and analysis of variance or the Kruskal–Wallis test for continuous variables. The individual effect of maternal caffeine intake on infant birth size and that of the CYP1A2 genotype (CC/CA vs. AA) on infant birth size were considered in separate regression models, with adjustment for maternal age, maternal pre-pregnancy body mass index (kg/m2), maternal education level (≤12 vs. ≥13 years), maternal smoking status during pregnancy (smoker vs. nonsmoker), maternal alcohol intake during pregnancy (g per day), parity (0, defined as though the woman had no previous viable pregnancies vs. ≥1), mode of delivery (vaginal vs. cesarean section), infant gender, and gestational age (weeks). Because none of the women reported caffeine intake of 0 mg per day, the <100 mg per day intake group was used as the reference group for analysis. In addition, the individual effect of smoking on birth size was analyzed because of its known impact on fetal growth (41, 44). The main linear regression model included mean infant birth size as the dependent variable, caffeine intake as a categorical variable, the CYP1A2 genotype (CC/CA vs. AA), and the CYP1A2 and caffeine gene–environment interaction variable (the product term of maternal caffeine intake and CYP1A2 genotype) adjusted by the confounders listed above. To further assess the confounding effects of smoking, the regression analysis was stratified by maternal smoking status. Pregnant women at 23–35 weeks of gestation were asked to participate in our prospective cohort study and most women completed a self-administered questionnaire in the third trimester. They were asked about their daily alcohol and caffeine intake throughout pregnancy, and their answers might be an average consumption of all three trimesters of pregnancy. Smoking status was asked about in each trimester and smokers were defined as women who smoked throughout pregnancy or quit after the first trimester as described above. So the timing of smoking exposure was after the second trimester. Intermediate variable is a consequence of exposure and it lies on the causal pathway between exposure and outcome. The onset of exposure leads to changes in the intermediate variable that occur prior to the onset of outcome (45). In our study, exposure and outcome were caffeine intake and birth size, respectively. As alcohol and tobacco smoke exposure might occur prior to caffeine exposure, and they were associated with both exposure and outcome, both alcohol intake and smoking status were used as confounders in our study. Hardy–Weinberg equilibrium analyses were performed to compare observed and expected genotype frequencies using the χ2-test. All P values were two-sided, and statistical significance was defined as P<0.05. All statistical analyses were performed using SPSS for Windows, version 20.0J (SPSS, Chicago, IL).

Ethical Approval

This study was approved by the Institutional Ethics Board for Human Gene and Genome Studies of the Hokkaido University Graduate School of Medicine and the Hokkaido University Center for Environmental and Health Sciences. Informed consent was obtained from all participants.

References

  1. 1

    Gu L, Gonzalez FJ, Kalow W, Tang BK . Biotransformation of caffeine, paraxanthine, theobromine and theophylline by cDNA-expressed human CYP1A2 and CYP2E1. Pharmacogenetics 1992;2:73–7.

    CAS  Article  PubMed  Google Scholar 

  2. 2

    Benowitz NL, Jacob P 3rd, Mayan H, Denaro C . Sympathomimetic effects of paraxanthine and caffeine in humans. Clin Pharmacol Ther 1995;58:684–91.

    CAS  Article  PubMed  Google Scholar 

  3. 3

    Food Standards Agency 2008 Food Standards Agency publishes new caffeine advice for pregnant women. Available at http://www.food.gov.uk/news/pressreleases/2008/nov/caffeineadvice (accessed December 2016).

  4. 4

    Yamada M, Sasaki S, Murakami K et al, Estimation of caffeine intake in Japanese adults using 16 d weighed diet records based on a food composition database newly developed for Japanese populations. Public Health Nutr 2010;13:663–72.

    Article  PubMed  Google Scholar 

  5. 5

    Derbyshire E, Abdula S . Habitual caffeine intake in women of childbearing age. J Hum Nutr Diet 2008;21:159–64.

    CAS  Article  PubMed  Google Scholar 

  6. 6

    Kalow W, Tang BK . Use of caffeine metabolite ratios to explore CYP1A2 and xanthine oxidase activities. Clin Pharmacol Ther 1991;50:508–19.

    CAS  Article  PubMed  Google Scholar 

  7. 7

    Syme MR, Paxton JW, Keelan JA . Drug transfer and metabolism by the human placenta. Clin Pharmacokinet 2004;43:487–514.

    CAS  Article  PubMed  Google Scholar 

  8. 8

    Bracken MB, Triche EW, Belanger K, Hellenbrand K, Leaderer BP . Association of maternal caffeine consumption with decrements in fetal growth. Am J Epidemiol 2003;57:456–66.

    Article  Google Scholar 

  9. 9

    Bakker R, Steegers EA, Obradov A, Raat H, Hofman A, Jaddoe VW . Maternal caffeine intake from coffee and tea, fetal growth, and the risks of adverse birth outcomes: the Generation R Study. Am J Clin Nutr 2010;91:1691–98.

    CAS  Article  PubMed  Google Scholar 

  10. 10

    CARE Study Group. Maternal caffeine intake during pregnancy and risk of fetal growth restriction: a large prospective observational study. BMJ 2010;340:c2331.

    Article  Google Scholar 

  11. 11

    Grosso LM, Rosenberg KD, Belanger K, Saftlas AF, Leaderer B, Bracken MB . Maternal caffeine intake and intrauterine growth retardation. Epidemiology 2001;2:447–55.

    Article  Google Scholar 

  12. 12

    Clausson B, Granath F, Ekbom A et al, Effect of caffeine exposure during pregnancy on birth weight and gestational age. Am J Epidemiol 2002;155:429–36.

    Article  PubMed  Google Scholar 

  13. 13

    Weng X, Odouli R, Li DK . Maternal caffeine consumption during pregnancy and the risk of miscarriage: a prospective cohort study. Am J Obstet Gynecol 2008;198:279.e1–8.

    Article  Google Scholar 

  14. 14

    Maconochie N, Doyle P, Prior S, Simmons R . Risk factors for first trimester miscarriage—results from a UK-population-based case-control study. BJOG 2007;114:170–86.

    CAS  Article  PubMed  Google Scholar 

  15. 15

    Klonoff-Cohen H, Bleha J, Lam-Kruglick P . A prospective study of the effects of female and male caffeine consumption on the reproductive endpoints of IVF and gamete intra-Fallopian transfer. Hum Reprod 2002;17:1746–54.

    CAS  Article  PubMed  Google Scholar 

  16. 16

    Greenwood DC, Thatcher NJ, Ye J et al, Caffeine intake during pregnancy and adverse birth outcomes: a systematic review and dose-response meta-analysis. Eur J Epidemiol 2014;29:725–34.

    CAS  Article  PubMed  Google Scholar 

  17. 17

    Chen LW, Wu Y, Neelakantan N, Chong MF, Pan A, van Dam RM . Maternal caffeine intake during pregnancy is associated with risk of low birth weight: a systematic review and dose-response meta-analysis. BMC Med 2014;12:174.

    Article  PubMed  PubMed Central  Google Scholar 

  18. 18

    Signorello LB, Nordmark A, Granath F et al, Caffeine metabolism and the risk of spontaneous abortion of normal karyotype fetuses. Obstet Gynecol 2001;98:1059–66.

    CAS  PubMed  Google Scholar 

  19. 19

    Sata F, Yamada H, Suzuki K et al, Caffeine intake, CYP1A2 polymorphism and the risk of recurrent pregnancy loss. Mol Hum Reprod 2005;11:357–60.

    CAS  Article  PubMed  Google Scholar 

  20. 20

    Schmidt RJ, Romitti PA, Burns TL et al, National Birth Defects Prevention Study Caffeine, selected metabolic gene variants, and risk for neural tube defects. Birth Defects Res A Clin Mol Teratol 2010;88:560–69.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  21. 21

    Chida M, Yokoi T, Fukui T, Kinoshita M, Yokota J, Kamataki T . Detection of three genetic polymorphisms in the 5'-flanking region and intron 1 of human CYP1A2 in the Japanese population. Jpn J Cancer Res 1999;90:899–902.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  22. 22

    Broekman BF, Chan YH, Chong YS et al, The influence of birth size on intelligence in healthy children. Pediatrics 2009;123:e1011–e1016.

    Article  PubMed  Google Scholar 

  23. 23

    Wiles NJ, Peters TJ, Heron J et al, Fetal growth and childhood behavioral problems: results from the ALSPAC cohort. Am J Epidemiol 2006;163:829–37.

    Article  PubMed  Google Scholar 

  24. 24

    Klebanoff MA, Levine RJ, DerSimonian R, Clemens JD, Wilkins DG . Maternal serum paraxanthine, a caffeine metabolite, and the risk of spontaneous abortion. N Engl J Med 1999;341:1639–44.

    CAS  Article  PubMed  Google Scholar 

  25. 25

    Grosso LM, Triche EW, Belanger K, Benowitz NL, Holford TR, Bracken MB . Caffeine metabolites in umbilical cord blood, cytochrome P-450 1A2 activity, and intrauterine growth restriction. Am J Epidemiol 2006;163:1035–41.

    Article  PubMed  Google Scholar 

  26. 26

    Huang J, Zhou S, Ping J et al, Role of p53- dependent placental apoptosis in the reproductive and developmentaltoxicities of caffeine in rodents. Clin Exp Pharmacol Physiol 2012;39:357–63.

    Article  PubMed  Google Scholar 

  27. 27

    Xu D, Zhang B, Liang G et al, Caffeine-induced activated glucocorticoid metabolism in the hippocampus causes hypothalamic-pituitary-adrenal axis inhibition in fetal rats. PLoS ONE 2012;7:e44497.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  28. 28

    Moisiadis VG, Matthews SG . Glucocorticoids and fetal programming part 1: outcomes. Nat Rev Endocrinol 2014;10:391–402.

    CAS  Article  PubMed  Google Scholar 

  29. 29

    Xu D, Wu Y, Liu F et al, A hypothalamic-pituitary-adrenal axis-associated neuroendocrine metabolic programmed alteration in offspring rats of IUGR induced by prenatal caffeine ingestion. Toxicol Appl Pharmacol 2012;264:395–403.

    CAS  Article  PubMed  Google Scholar 

  30. 30

    Sharmin S, Guan H, Williams AS, Yang K . Caffeine reduces 11β-hydroxysteroid dehydrogenase type 2 expression in human trophoblast cells through the adenosine A(2B) receptor. PLoS ONE 2012;7:e38082.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  31. 31

    Rodenburg EM, Eijgelsheim M, Geleijnse JM et al, CYP1A2 and coffee intake and the modifying effect of sex, age, and smoking. Am J Clin Nutr 2012;96:182–87.

    CAS  Article  PubMed  Google Scholar 

  32. 32

    Gunes A, Ozbey G, Vural EH et al, Influence of genetic polymorphisms, smoking, gender and age on CYP1A2 activity in a Turkish population. Pharmacogenomics 2009;10:769–78.

    CAS  Article  PubMed  Google Scholar 

  33. 33

    Nagata C, Kabuto M, Shimizu H . Association of coffee, green tea, and caffeine intakes with serum concentrations of estradiol and sex hormone-binding globulin in premenopausal Japanese women. Nutr Cancer 1998;30:21–4.

    CAS  Article  PubMed  Google Scholar 

  34. 34

    Denden S, Bouden B, Haj Khelil A, Ben Chibani J, Hamdaoui MH . Gender and ethnicity modify the association between the CYP1A2 rs762551 polymorphism and habitual coffee intake: evidence from a meta-analysis. Genet Mol Res 2016;15:gmr.15027487.

  35. 35

    Schliep KC, Schisterman EF, Mumford SL et al, Caffeinated beverage intake and reproductive hormones among premenopausal women in the BioCycle Study. Am J Clin Nutr 2012;95:488–97.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  36. 36

    Grosso LM, Triche E, Benowitz NL, Bracken MB . Prenatal caffeine assessment: fetal and maternal biomarkers or self-reported intake? Ann Epidemiol 2008;18:172–78.

    Article  PubMed  PubMed Central  Google Scholar 

  37. 37

    Signorello LB, McLaughlin J . Maternal caffeine consumption and spontaneous abortion. A review of epidemiologic evidence. Epidemiology 2004;15:229–39.

    Article  PubMed  Google Scholar 

  38. 38

    Kishi R, Kobayashi S, Ikeno T et al, Ten years of progress in the Hokkaido birth cohort study on environment and children's health: cohort profile–updated 2013. Environ Health Prev Med 2013;18:429–50.

    Article  PubMed  PubMed Central  Google Scholar 

  39. 39

    Washino N, Saijo Y, Sasaki S et al, Correlations between prenatal exposure to perfluorinated chemicals and reduced fetal growth. Environ Health Perspect 2009;117:660–67.

    CAS  Article  PubMed  Google Scholar 

  40. 40

    Santos IS, Victora CG, Huttly S, Carvalhal JB . Caffeine intake and low birth weight: a population-based case-control study. Am J Epidemiol 1998;147:620–27.

    CAS  Article  PubMed  Google Scholar 

  41. 41

    Ohmi H, Hirooka K, Mochizuki Y . Fetal growth and the timing of exposure to maternal smoking. Pediatr Int 2002;44:55–9.

    Article  PubMed  Google Scholar 

  42. 42

    Ranade K, Chang MS, Ting CT et al, High-throughput genotyping with single nucleotide polymorphisms. Genome Res 2001;11:1262–68.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43

    Kobayashi S, Sata F, Sasaki S et al, Genetic association of aromatic hydrocarbon receptor (AHR) and cytochromeP450, family 1, subfamily A, polypeptide 1 (CYP1A1) polymorphisms with dioxin blood concentrations among pregnant Japanese women. Toxicol Lett 2013;219:269–78.

    CAS  Article  PubMed  Google Scholar 

  44. 44

    England LJ, Kendrick JS, Wilson HG et al, Effects of smoking reduction during pregnancy on the birth weight of term infants. Am J Epidemiol 2001;154:694–701.

    CAS  Article  PubMed  Google Scholar 

  45. 45

    Chaiton M, Cohen JE, Rehm J, Abdulle M, O'Loughlin J . Confounders or intermediate variables? Testing mechanisms for the relationship between depression and smoking in a longitudinal cohort study. Addict Behav 2015;42:154–61.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by Grants-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (JSPS; grant numbers JP13307015, 16209022, and 19209024). We acknowledge all of the participants in this study and the staff at Sapporo Toho Hospital.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Reiko Kishi.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Sasaki, S., Limpar, M., Sata, F. et al. Interaction between maternal caffeine intake during pregnancy and CYP1A2 C164A polymorphism affects infant birth size in the Hokkaido study. Pediatr Res 82, 19–28 (2017). https://doi.org/10.1038/pr.2017.70

Download citation

Further reading

Search

Quick links