Abstract
Maternal alcohol use during the perinatal period is a major public health issue, the higher ends of which are associated with foetal alcohol spectrum disorder and a range of adverse health outcomes in the progeny. The underlying molecular mechanisms remain largely unknown but may include the epigenetic disruption of gene activity during development. Alcohol directly activates the neurotransmitter dopamine, which plays an essential role in neurodevelopment. To investigate whether antenatal and early postnatal alcohol consumption were associated with differential dopamine receptor DRD4 promoter methylation in infants (n = 844). Data were drawn from the large population based Triple B pregnancy cohort study, with detailed information on maternal alcohol consumption in each trimester of pregnancy and early postpartum. DNA was extracted from infant buccal swabs collected at 8-weeks. DRD4 promoter DNA methylation was analysed by Sequenom MassARRAY.
No strong evidence was found for an association between alcohol consumption during pregnancy and infant DRD4 methylation at 8-weeks postpartum. However, maternal alcohol consumption assessed contemporaneously at 8-weeks postpartum was associated with increased methylation at 13 of 19 CpG units examined (largest Δ + 3.20%, 95%Confidence Interval:1.66,4.75%, P = 0.0001 at CpG.6). This association was strongest in women who breastfeed, suggesting the possibility of a direct effect of alcohol exposure via breast milk. The findings of this study could influence public health guidelines around alcohol consumption for breastfeeding mothers; however, further research is required to confirm these novel findings.
Keywords: alcohol, pregnancy, perinatal, postpartum, dopamine receptor (DRD4), foetal programming, DNA methylation, epigenetics, breastfeeding
Introduction
Australian prevalence data suggest that alcohol use during pregnancy is common [1]. A recent National Drug Strategy Household survey indicated that over 50% of women drank alcohol prior to pregnancy awareness, and one in four continued to drink throughout pregnancy [2]. High maternal alcohol use during pregnancy is associated with a range of detrimental short- and long-term effects on the developing foetus, such as increased risk of birth defects, delayed development and poor child behaviour [3, 4]. This may occur through foetal programming, where the foetus adapts to its intrauterine environment to maximize its growth and development in utero, impacting later health [5]. Alcohol is a known teratogen, and the foetus is directly exposed to maternal alcohol consumed during pregnancy via diffusion across the feto-placental barrier [6]. This can directly influence foetal development [7]. Accumulating evidence suggests that epigenetic mechanisms, including DNA methylation, may play a mediating role in foetal programming. Epigenetics refers to mitotically heritable alterations to cellular phenotype or gene expression that do not change the underlying DNA sequence [8]. Numerous maternal exposures in pregnancy, such as stress, smoking and folate intake, have now been associated with differential DNA methylation in more than one study [9–11].
Few studies have investigated the influence of in utero alcohol exposure on infant DNA methylation. One epigenome-wide association study (EWAS) using buccal swab DNA of children with foetal alcohol spectrum disorder (n = 6), identified a number of genes that were differentially methylated between cases and controls, particularly genes involved in neurodevelopment [12]. In terms of more moderate levels of alcohol consumption, such as a few standard drinks a week which is commonly observed in the general population, only a few candidate gene studies have been undertaken. Prenatal alcohol consumption has been associated with an increase in methylation (3.3%) of the long interspersed nuclear Element-1 (LINE1) in placenta (n = 380), compared with non-drinkers [13]; however, the sample size of women reporting prenatal drinking (n = 3) was severely limited. Another study showed that pleiomorphic adenoma gene-like 1 gene (PLAGL1) in cord blood was differentially methylated in association with prenatal alcohol use in Trimester 3 (n = 254) [14], although effect sizes were not reported. In a study of 164 cord blood samples, maternal binge drinking during pregnancy was associated with an ∼20% increase in methylation at dopamine associated transporter (DAT1) promoter compared with non-binge drinkers (all other alcohol groups combined including heavy drinkers) [15]. No data on the timing of alcohol consumption were available though, and there was no difference in DAT1 methylation between non-drinkers and drinkers overall. Genes involved in dopaminergic signalling, however, do represent good candidates for disruption in response to alcohol exposure.
Motivation to consume alcohol is, in part, thought to be mediated by reward pathways within the meso-cortico-limbic system of the mid brain. Dopamine is the primary neurotransmitter within this system and alcohol directly activates dopaminergic signalling [16, 17]. Dopaminergic signalling also plays an important role in mood regulation and neurodevelopment [18,19]. Disruptions in dopaminergic signalling can result in a broad range of neuropsychiatric and development conditions, including depression and schizophrenia [20]. The dopamine receptor D4 (DRD4) was chosen as a strong candidate gene for investigation in this study given that it is a key component of dopamine signalling, responsible for inhibiting adenylate cyclase during signal transduction [21]. Furthermore, higher peripheral DRD4 methylation levels have been observed in in adults with alcohol dependence [22] but no study has yet investigated whether perinatal alcohol exposure can influence DRD4 methylation in the offspring.
The aim of this study was to examine the association between maternal alcohol intake during pregnancy and early postpartum, and infant buccal DRD4 promoter methylation shortly after birth, taking into account the timing of alcohol exposure and a range of possible confounding perinatal factors.
Methods
Triple B Cohort
Triple B is a longitudinal pregnancy cohort study that recruited 1634 families though public antenatal services associated with major hospitals in New South Wales and Western Australia, including specialist drug and alcohol antenatal services. Mothers and or pregnancies with major medical complications were excluded. Ethics approval for the study was granted by the relevant Human Research Ethics Committees, and all participants provided written informed consent. Participants responded to questionnaires to gather data on socio-demographic, health and lifestyle factors across pregnancy and postpartum. Women self-reported alcohol consumption in each trimester of pregnancy and during the first 8-weeks postpartum, by completing detailed questionnaires. To address a potential bias in the self-reporting of substance use, a random selection of participants (n = 85) underwent a urine analysis during the third trimester. Between self-reporting and urine analysis, the data were 97% in agreement, which indicated the strong reliability of the reporting.
DRD4 Promoter Region
The 396 bp assay designed using epidesigner.com, covered a region of the promoter CpG island (chr11:635 510–636 905, University of California, Santa Cruz (UCSC) genome build hg38), previously shown to be differentially methylated [23, 24] (forward primer 5′-GGACCCCCTGCCC AGGGTCAGAGG-3′; reverse 5′-TGCCAGATACCAGGT GGACTAGG GTG-3′). Data were obtainable for 19 analytical CpG units encompassing 32 CpG sites. DNA was extracted from 8-week infant buccal samples and 400 ng of genomic DNA was used for bisulphite conversion [EZ-96 DNA Methylation-Lightning MagPrep kit (Irvine, USA)]. All samples were amplified and assayed in triplicate. DNA methylation data were obtained using the Sequenom MassARRAY EpiTYPER. Technical replicates passed quality control if they were within 10% of the median sample, and the average methylation was calculated. CpG units or participants where <85% of methylation data were obtained after quality control, as well as outliers (>10% outside 1.5 times the Interquartile Range) were excluded (Supplementary Table S1).
Statistical Analysis
From 903 extracted infant buccal samples, 844 passed quality control (technical triplicates within 10% of sample median at each CpG, and >85% data retained for all CpGs per sample). For each individual CpG unit, sample number ranged from 743 to 844 (Supplementary Table S1), with 552 samples having complete data for all 19 CpG units. These participants were representative of the whole sample, as they did not differ significantly on the socio-demographic, health and lifestyle characteristics shown in Table 1.
Table 1.
Maternal and infant population characteristics
| Population characteristics | ||
|---|---|---|
| Maternal characteristics | n | Mean ± SD |
| Maternal age at child’s birth (years) | 821 | 32.6 ± 5.0 |
| Country of birth | 844 | n(%) |
| Australia | 464 (55.0) | |
| Other | 380 (45.0) | |
| Currently living with partner | 821 | 762 (92.8) |
| Education level | 821 | |
| Year 12 or under | 153 (18.6) | |
| Completed Tafe/tech school | 116 (14.1) | |
| Completed university/college | 552 (67.3) | |
| Employment | 821 | |
| Full-time/self-employed | 377 (45.9) | |
| Part time/casual | 154 (18.8) | |
| Home/student/unemployed | 290 (35.3) | |
| Maternal alcohol consumption | ||
| At any time during pregnancy | 816 | 561 (68.8) |
| Trimester 1 | 816 | 507 (62.1) |
| Trimester 2 | 821 | 254 (30.9) |
| Trimester 3 | 811 | 254 (31.3) |
| 8-weeks postpartum | 814 | 502 (61.7) |
| Maternal tobacco use | ||
| Any time during pregnancy | 812 | 139 (17.1) |
| 8-weeks postpartum | 814 | 77 (9.5) |
| Infant characteristics | ||
| Sex: male | 816 | 422 (51.7) |
| Female | 394 (48.3) | |
| Mean ± SD | ||
| Gestation age at birth (weeks) | 816 | 39.3 ± 1.7 |
| Birthweight (kg) | 812 | 3.5 ± 0.5 |
Univariate analysis was used to investigate the association between alcohol exposure during pregnancy and mean DRD4 methylation. The association between maternal alcohol consumption at 8-weeks postpartum and mean infant DRD4 methylation at this same time-point was also examined, as were associations between alcohol exposure and methylation levels at individual CpG units. When significant associations were found, multivariate linear regression models were generated including potential confounding factors, associated with both alcohol consumption and DRD4 methylation. Batch effects from different Sequenom Chips were controlled for.
Results
Study Population
The maternal and infant characteristics of the study population are shown in Table 1. The majority of women consumed alcohol during pregnancy, predominantly in Trimester 1 prior to pregnancy awareness. There was a similar frequency of drinkers at 8-weeks postpartum (61.7%).
Maternal Alcohol Consumption during Pregnancy and Infant DRD4 Methylation
We first examined whether maternal alcohol use during pregnancy and early postpartum was associated with differential DRD4 methylation in infants at 8-weeks (Table 2). Mothers who reported drinking alcohol during Trimester 3 (64.6% of whom also drank in both Trimesters 1 and 2) had infants with significantly higher DRD4 methylation levels, both mean levels across the region (Table 2) and at individual 5 of 19 CpG units (Supplementary Table S2). Postpartum alcohol was also significantly associated with increased mean DRD4 methylation and at 13 of 19 units, (Table 3 and Supplementary Fig. S1). In the latter case, 5 of these associations would remain significant even after Bonferroni correction taking into account the 19 CpG units examined (P < 0.0026). The largest effect size observed was at CpG.6 (chr11:636 593) (Δ + 1.87, 95%CI:0.21,3.52%, P = 0.027 Trimester 3; Δ + 3.20, 95%CI:1.66,4.75%, P = 0.0001 8-week postpartum, Fig. 1).
Table 2.
association between maternal alcohol consumption and infant mean DRD4 promoter methylation
| Alcohol consumption |
DRD4 methylation |
||||
|---|---|---|---|---|---|
| n | Mean methylation (95%CI) | Δ | P | ||
| At any stage during pregnancy | No | 161 | 36.98 (36.74,37.56) | +0.13 | 0.704 |
| Yes | 375 | 37.11 (36.75,37.48) | |||
| During Trimester 1a | No | 195 | 37.09 (36.55,37.62) | +0.05 | 0.88 |
| Yes | 339 | 37.03 (36.66,37.41) | |||
| During Trimester 2a | No | 367 | 36.96 (36.59,37.33) | +0.37 | 0.28 |
| Yes | 172 | 37.32 (36.77,37.88) | |||
| During Trimester 3a | No | 373 | 36.83 (36.46,37.20) | +0.89 | 0.0090 |
| Yes | 161 | 37.72 (37.17,38.26) | |||
| During the first 8-weeks postpartuma | No | 202 | 36.51 (36.02,37.00) | +0.91 | 0.0049 |
| Yes | 334 | 37.41 (37.02,37.80) | |||
Women’s reporting of consumption at that period but not exclusively (i.e. 62% of women consuming alcohol in Trimester 3, also reported consumption in Trimesters 1 and 2).
Table 3.
infant DRD4 methylation according to maternal alcohol consumption at 8-weeks postpartum
| CpG unit | Alcohol | n | Mean methylation (95%CI) | Difference (%) | P |
|---|---|---|---|---|---|
| 1 | No | 304 | 80.4 (79.8,81.0) | +0.49 | 0.20 |
| Yes | 494 | 80.9 (80.4,81.3) | |||
| 2_3 | No | 303 | 81.4 (80.8,81.2) | +0.79 | 0.029 |
| Yes | 496 | 82.2 (81.8,82.6) | |||
| 4_5 | No | 311 | 38.7 (38.3,39.1) | +1.11 | <0.0001 |
| Yes | 502 | 39.8 (39.5,40.5) | |||
| 6 | No | 279 | 60.5 (59.3,61.7) | +3.20 | 0.0001 |
| Yes | 441 | 63.7 (62.7,64.6) | |||
| 7 | No | 293 | 69.6 (68.6,70.6) | +2.00 | 0.0033 |
| Yes | 477 | 71.6 (70.8,72.5) | |||
| 8 | No | 285 | 71.8 (70.9,72.8) | +1.76 | 0.0037 |
| Yes | 475 | 73.6 (72.8,74.3) | |||
| 9 | No | 294 | 65.6 (64.5,66.7) | +1.39 | 0.037 |
| Yes | 484 | 67.0 (66.2,67.7) | |||
| 12_13_14 | No | 312 | 28.2 (27.7,28.8) | +0.98 | 0.0050 |
| Yes | 500 | 29.2 (28.8,29.6) | |||
| 15_16_17 | No | 296 | 22.0 (21.5,22.5) | +0.61 | 0.073 |
| Yes | 465 | 22.6 (22.2,23.1) | |||
| 21_22_23 | No | 331 | 18.1 (17.7,18.6) | +0.69 | 0.028 |
| Yes | 498 | 18.8 (18.4,19.2) | |||
| 24_25_26 | No | 312 | 31.5 (31.1,32.0) | +1.00 | 0.0011 |
| Yes | 501 | 32.5 (32.2,32.9) | |||
| 27 | No | 310 | 33.4 (33.0,33.8) | +0.77 | 0.0010 |
| Yes | 501 | 34.2 (33.9,34.5) | |||
| 28_29 | No | 311 | 18.5 (17.9,19.0) | +1.27 | 0.0003 |
| Yes | 498 | 19.7 (19.3,20.5) | |||
| 30 | No | 301 | 24.2 (23.3,25.1) | +1.04 | 0.0530 |
| Yes | 481 | 25.3 (24.6,25.9) | |||
| 32 | No | 299 | 1.9 (1.6,2.1) | −0.07 | 0.67 |
| Yes | 486 | 1.8 (1.6,2.0) | |||
| 34_35 | No | 312 | 24.0 (23.6,24.4) | +0.52 | 0.041 |
| Yes | 502 | 24.5 (24.2,24.8) | |||
| 36 | No | 306 | 13.1 (12.6,13.7) | +0.78 | 0.0300 |
| Yes | 496 | 13.9 (13.5,14.4) | |||
| 37_38 | No | 311 | 8.3 (8.0,8.6) | +0.06 | 0.76 |
| Yes | 501 | 8.4 (8.1,8.6) | |||
| 39 | No | 312 | 3.6 (3.4,3.7) | +0.21 | 0.070 |
| Yes | 502 | 3.8 (3.6,3.9) | |||
| Mean | No | 202 | 36.5 (36.0,37.0) | +0.91 | 0.0049 |
| Yes | 334 | 37.4 (37.0,37.8) |
Figure 1.
DRD4 promoter methylation in infants according to maternal alcohol consumption in the first 8-weeks postpartum. (A) Mean promoter methylation (mean effect 0.91 95%CI:0.28,1.54, P = 0.0049). (B) CpG.6 methylation (mean effect 3.20, 95%CI:1.66,4.75%, P = 0.0001). Whiskers indicate 1.5*IQR, above and below the 75th and 25th percentile, respectively
Given that significant associations were identified with both maternal alcohol consumption during Trimester 3 and early postpartum, we sought to disentangle these effects developmentally. It was not possible to isolate the effects of drinking at Trimester 3, because with the exception of 1 participant, all mothers who drank in Trimester 3 also drank at 8-weeks postpartum. Furthermore, only 6% of women drinking in Trimester 3, abstained from drinking at other stages of pregnancy. However, we could investigate the subpopulation of women who abstained from drinking alcohol during Trimester 3 but drank early postpartum (n = 161). Indeed, when excluding Trimester 3 drinkers from the analysis, the strength of association between early postpartum alcohol consumption and DRD4 methylation increased in effect size Supplementary Table S3, CpG.6: 4.87%, P = 0.0007.
Multivariate Analysis
As shown in Table 4, women who reported alcohol consumption postpartum were older, more likely to be Australian born, more highly educated and employed full-time. Infants exposed to alcohol 8-weeks postpartum were more likely to have had a longer gestation age and a heavier birthweight. Maternal age (P = 0.11) and education level (P = 0.10) also showed moderate associations with DRD4 methylation, as did tobacco use during pregnancy (P = 0.11). DRD4 promotor methylation also higher in male infants compared with females (P = 0.005). There was no significant association between breastfeeding and alcohol consumption early postpartum (P = 0.66). We therefore adjusted for maternal age, education level, plate number (to account for possible batch effects) and in multivariate models, while also ensuring that the inclusion of other covariates such as offspring sex, did not modify the findings. Smoking was included in the adjusted models given the strong published evidence that it can influence DNA methylation in the offspring [25]. However, inclusion of these covariates had no influence on the findings (i.e. 8-week alcohol consumption, (mean β:+0.80, SE:0.32, P = 0.014; CpG.6 β + 2.88, SE 0.79, P < 0.001)).
Table 4.
population characteristics of mothers and infants, according to alcohol use 8-weeks postpartum
| Population characteristics | Alcohol consumption 8-weeks postpartum |
||
|---|---|---|---|
| No (n= 312) | Yes (n= 502) | P | |
| Maternal characteristics | Mean ± SD | ||
| Maternal age at birth (years) | 31.9 ± 5.1 | 33.0 ± 4.9 | <0.0029 |
| n(%) | |||
| Country of birth: | |||
| Australia | 152 (51.3) | 309 (61.6) | <0.001 |
| Other | 160 (48.7) | 193 (38.4) | |
| Currently living with partner | 285 (91.4) | 472 (94.0) | 0.146 |
| Education level | |||
| Year 12 or under | 70 (22.4) | 81 (16.1) | 0.015 |
| Completed Tafe/tech school | 51 (16.4) | 65 (13.0) | |
| Completed university/college | 191 (61.2) | 356 (70.9) | |
| Employment | |||
| Full-time/self-employed | 120 (38.5) | 254 (50.6) | 0.48 |
| Part time/casual | 60 (19.2) | 93 (18.5) | |
| Home/student/unemployed | 132 (42.3) | 155 (30.9) | |
| Maternal tobacco use | |||
| During pregnancy | 52 (16.8) | 86 (17.2) | 0.88 |
| 8-weeks postpartum | 25 (8.0) | 52 (10.4) | 0.27 |
| Infant characteristics | |||
| Mean ± SD | |||
| Gestation age at birth (weeks) | 39.1 ± 1.9 | 39.5 ± 1.5 | 0.0039 |
| Birthweight (kg) | 3.4 ± 0.6 | 3.5 ± 0.5 | 0.040 |
The Potential Role of Breastfeeding in Alcohol Transmission
To further investigate our principal finding, that of an association between alcohol exposure during the first 8-weeks postpartum and an increase in infant DRD4 methylation assessed contemporaneously, we considered the possible role of breastfeeding. As all participant data were not available at the time of this study, we focused on the subpopulation of women who reported breastfeeding for the first 8-weeks postpartum (n ranged from 386–441 for individual CpG units). The maternal and infant characteristics within this subpopulation were representative of the whole population (data not shown). The association between postpartum alcohol consumption and DRD4 methylation was found to be even stronger in the breastfeeding subpopulation (i.e. CpG.6:Δ4.01, 95%CI:1.91,6.11%, P = 0.0002; Supplementary Table S4).
Discussion
The strongest and most consistent finding from our study was an association between postpartum alcohol consumption and increased infant DRD4 methylation (at 13 of 19 CpG units) assessed contemporaneously. Furthermore, postpartum alcohol consumption remained significantly associated with increased methylation, even after excluding women drinking during pregnancy, as well as controlling for other potential confounding factors. Our results also showed that this association was strongest among women who reported breastfeeding for the first 8-weeks postpartum, suggesting that transmission of alcohol through the breast milk may help account for this finding.
Dopaminergic Gene Methylation in Other Studies
DRD4 is enriched in the brain, primarily in the pituitary, amygdala, cerebral cortex and hypothalamus [26]. DRD4 is a key component of dopamine signalling and was chosen for this candidate gene study due to the way alcohol effects dopamine signalling. It is a D2-like receptor that acts in postsynaptic signal transduction facilitating the inhibition of adenylate cyclase [21]. Alcohol does not directly interact with dopamine receptors such as DRD4; however, when alcohol is consumed, it causes dopamine release in the brain [27]. This in turn indirectly modulates dopaminergic signal transduction, activating reward pathways which can also lead to alcohol dependence [17]. Further, genetic variants in DRD4 have been associated with attention deficit hyperactive disorder, alterations in inhibitory behaviour and other childhood behavioural problems [28].
No previous study has investigated the association between DRD4 methylation and perinatal alcohol exposure, although other phenotypes have been explored. DRD4 methylation in peripheral blood has been positively associated with the risk of schizophrenia in adult males (n = 45) but not females [29]. Findings of a study of monozygotic and dizygotic twins (n = 182), suggest that environmental, rather than genetic factors play a more important role in influencing DNA methylation of this gene in buccal cells [23]. Another study found increased blood DRD4 promoter methylation in alcohol dependent adults versus controls of European American ethnicity (Δ + 0.9% ± 0.1 SEM, P = 0.0003, n = 249) [22]. This is a similar effect size for mean methylation observed in our study with postpartum alcohol use and infant DNA methylation. Of note, the greatest effect size observed in our study was with CpG.6, and this lies close to a specific Protein-1 transcription factor binding site, which is 9 bp upstream [30]. This transcription binding factor is known to bind to CpG-rich genetic motifs within gene promoter regions, such as the one investigated within this study. Increased CpG.6 methylation in this region could block the binding of this transcription factor and thus suppress gene transcription [31], highlighting a potential functional role of differential methylation at this site. Although the observed effect sizes are relatively small, as is the case for most studies in this area, many small changes in DNA methylation across a network of genes, such as those within the dopaminergic pathway, may accumulate and result in potential significant detrimental effects [32].
DNA methylation levels of another gene involved in dopaminergic signalling, DAT1, has also been investigated in association with alcohol exposure. DAT1 is a dopamine transporter that regulates dopamine concentration and the duration of dopamine neurotransmission within neural synapses by actively transporting it from the synaptic terminal back into the cell [33]. Although DAT1 is transcribed from a different genomic region (chr5), the transporter interacts with DRD4 by making dopamine available across neuronal synapses for signal transduction. Only one study has investigated an association between prenatal alcohol use and infant DNA methylation within the DAT1 promoter in cord blood (n = 164) [15]. This study found that in infants whose mothers binge-drank during pregnancy, there was an approximate 20% increase in DAT1 promoter methylation when compared with mothers who were drinkers. However, no significant results were found when comparing promoter methylation between drinkers or binge-drinkers and non-drinkers. A few other studies of DAT1 methylation investigated a direct association with alcohol exposure in adults. A study of 29 alcohol dependent Caucasian adult males found that relapsed patients (n = 17) had an average 3% higher DAT1 methylation levels in blood compared with the abstinent group (n = 12) [34] but this did not reach significance (P = 0.095). In contrast, a larger study of 171 alcohol dependant adult Caucasian men found no significant difference in mean DAT1 methylation levels in leucocytes, compared with 160 matched healthy controls [35]. However, at one of 23 CpG sites analysed, increased methylation was observed in the control group (P = 0.029, effect size not stated). Due to its integral part in dopaminergic signalling pathways and these initial findings, DAT1 would be a candidate gene for further studies in maternal alcohol use and differential infant methylation.
Alcohol and B reastfeeding
Our primary finding of an association between maternal alcohol consumption early postpartum and infant DRD4 methylation in buccal cells was unexpected and could be explained, at least in part, by the transmission of alcohol via breast milk. Ethanol, found in alcoholic drinks, is water soluble and passively diffuses into breast milk from the blood stream. Within an hour, alcohol levels in breast milk can reach the same as blood alcohol levels [36]. The vast majority of studies that have investigated maternal alcohol use and infant outcomes focus solely on the prenatal period; however, there is prior evidence to suggest that breast milk can modify DNA methylation and gene expression patterns. This could help explain the infant health benefits from breastfeeding (including lower risk of infections, obesity and related disorders). For example, lactoferrin in breast milk may reduce the inflammatory response by inhibiting NF-kappaB gene expression [37] and binding of lactoferrin to unmethylated CpGs in bacterial DNA in turn inhibits the immunostimulatory, hence inflammatory effects on human B cells [38, 39]. The high cholesterol content of breast milk may reduce endogenous cholesterol synthesis through downregulation of gene expression, which could explain the reduced cholesterol levels of adults who were breastfeed in infancy [37].
Our findings highlight the need to consider breastfeeding in cohort studies of infant DNA methylation patterns generally, as well as the amount of alcohol neonates are exposed to though breast milk consumption. This is especially important given that 62% of women have reported the consummation of alcohol in the early postnatal period, an important period of brain development [40].
Further R esearch
Although this initial analysis has investigated the associations between alcohol use at different stages of pregnancy and in the early postpartum, and infant DRD4 methylation, it is possible that the dose of exposure during pregnancy is also important, and this is an avenue for future research in Triple B. Compared with heavy alcohol use, less is known about low or moderate maternal drinking pre or post birth. The majority of research concerns foetal alcohol spectrum disorder with its major phenotypic alterations as the primary focus. However, direct effects of low to moderate drinking may be too subtle to detect. A meta-analysis (n = 11 900) of children aged 9 months to 5 years showed that moderate drinking during pregnancy was associated with poor child behaviour [41]. However, this meta-analysis only included 3 studies. Another study (n = 4496) found that low–moderate alcohol during pregnancy (≤1 standard drink/week) was not associated with intrauterine growth restriction, preterm delivery or low birthweight, all reported outcomes of heavy pregnancy drinking [42]. Further research into DNA methylation effects from drinking, especially at low to moderate amounts of alcohol, and coupled with breastfeeding, is needed. Further, an important next step within this cohort will be to determine whether differential DRD4 methylation is associated with developmental health outcomes in infants.
Strengths and Limitations
The major strength of this study is the large sample size combined with extensive data on the mother–infant dyads. This included detailed alcohol exposure data and a range of potential confounding factors. Thus, this study makes an important contribution to the field. Potential limitations to the current analysis relate to the DRD4 methylation data obtained. Methylation is known to be dynamic, differing between tissues and cell types [43], thus the findings presented here are unique to buccal samples collected from infants at 8-weeks and cannot be generalized to other tissues or time-points. Even though neuronal genes were of specific interest in this study, buccal cells were used and preferred as a biological sample for their non-invasive collection method and possible usefulness as a biomarker. They are also a very pure cell population derived from embryonic ectoderm, from which neural tissue also arises [44]. Further, recent data have highlighted the utility of buccal-derived DNA for studies of central nervous system related phenotypes [23].
As buccal cells would be in direct contact with breast milk, results may be influenced by maternal DNA contamination from the milk, resulting in erroneous results. A further limitation to this study is in that DRD4 variable number tandem repeats were not accounted for, which have been shown to be associated with alcohol seeking behaviour [45] and could possibly influence differences in methylation values [46]. Dose response should be investigated in future studies, as well as other longitudinal time-points, to observe if these effects remain stable. Another limitation to consider is the small effect sizes observed, although this is within the range commonly observed in studies of early-life exposure [32, 47]. Although we do not yet know how these could translate into biological differences, it is possible that the accumulation of many small epigenetic changes during development could be sufficient to result in detrimental health outcomes [48]. Further EWASs will enable us to determine whether groups of genes linked to common signalling pathways are disrupted. Although we considered a range of covariates in our analysis, it remains possible that other confounders, not considered here, have influenced the associations. Finally, the fact that no buccal samples were collected at birth made it impossible to fully explore postnatal exposure in isolation, therefore where possible, these should be collected in future birth cohort studies.
Conclusion
The Australian Breastfeeding Association suggest that it is safe to have up to two standard drinks a day after the child is 1 month old, as long as the feed is before the alcohol consumption [49]. This study has found that alcohol exposure postpartum is associated with increased infant methylation. If further research shows that effects translate into infant health risks, redefinition of standards may be required, such as altering the alcohol free postnatal period and the suggested amount of alcohol which is consumed. Further studies are needed to replicate our findings, preferably ones that incorporate measurements of genetic variation into modelling of associations, as well as the timing and dose of exposure pre and postnatally. Only with robustly replicated findings, can the true reliability of these associations be ascertained, such as those consistently replicated studies that found smoking associated changes in methylation [47, 50 ]. Future studies could focus on the biological relevance of this methylation difference and how it is achieved, whether it equates to changes in gene expression, whether it remains stable over time and whether these differences are associated with infant health and development. The potential for epigenetic variation to mediate the relationship between maternal exposures and childhood outcomes is an important area of investigation, with great potential to influence the health of future generations through the development of novel interventions.
Supplementary Material
Acknowledgements
The authors gratefully acknowledge the NDARC research staff and students who assisted with collection of the Triple B cohort data, the hospitals and antenatal clinics for their assistance with recruitment and the study participants and their families. They acknowledge Rosa Alati, Brandi Baylock, Lauren Bell, Elissa Bowey Annie Bleeker, Apo Demirkol, Genevive Eckstein, David Fergusson, Thea Gumbert, Helen Gunn, Jeannie Minnis, Colleen O’Leary, Vaughan Palmer, Jemma Pope, Jarrod Proudfoot, Candice Rainsford, Joanne Ross, Fiona Shand, Lisa Sin, Matthew Sunderland, Wendy Swift, Scarlet Wilcock and Jesse Young. They also acknowledge the Longitudinal Cohorts Research Consortium for their role in Triple B (LCRC; Formerly the Cannabis Cohorts Research Consortium; NHMRC Project Grants: AAP1009381, AAP1064893), the Biobank at the Murdoch Childrens Research Institute and Dr Benjamin Ong for assistance with the Sequenom MassARRAY platform.
The Triple B Research Consortium: including the primary investigators already listed and: Joanne Cassar, Aurora Popescu, Gabrielle Campbell, Lee Taylor, Maria Gomez, Emma Black, Danya Braunstein, Laura Dewberry, Erin Kelly, Alex Aiken, Sarah Brann, Sara Clews, Sharon Dawe, Adrienne Gordon, Paul Haber, Dale Hamilton, Andrew Lewis, Nyanda McBride, Elizabeth Moore, Raewyn Mutch, Julee Oei, George Patton, Ronald Rapee, Tim Slade, Marian Shanahan, Christine Stephens, Meredith Ward and George J Youssef.
Funding
This study is funded by a grant from the Financial Markets Foundation for Children (Australia) to C.A.O., D.H. and J.R. (2015-252). The Triple B study was funded by an Australian National Health and Medical Research Council (NHMRC) Project Grant #GNT630517 for $2 196 179 to R.P.M., D.H., S.A., J.N., E.E., Lucy Burns, Sue Jacobs, C.A.O. and Anne Bartu and was financially supported by the National Drug and Alcohol Research Centre (NDARC), University of New South Wales. NDARC and the National Drug Research Institute (NDRI), Curtin University are funded by the Australian Government under the Substance Misuse Prevention and Service Improvements Grants Fund. D.H. is supported by an Australian Unity Industry Partner Senior Research Fellowship, and C.A.O. is supported by an Australian Research Council Senior Research Fellowship (DORA: DP 130101459). R.P.M. is supported by an NHMRC Principal Research Fellowship Award, E.E. by an NHMRC Practitioner Fellowship (APP1021480) and R.S. by an NHMRC Senior Research Fellowships (APP1045161).
Supplementary data
Supplementary data is available at EnvEpig online.
References
- 1. Hutchinson D, Moore EA, Breen C, Burns L, Mattick RP. Alcohol use in pregnancy: prevalence and predictors in the Longitudinal Study of Australian Children. Drug Alcohol Rev 2013;32:475–82 [DOI] [PubMed] [Google Scholar]
- 2. Australian Institute of Health and Welfare. National drug strategy household survey detailed report 2013. Australian Institute of Health and Welfare, 2014, Drug statistics series no. 28. Cat. no. PHE 183. Canberra: AIHW. [Google Scholar]
- 3. Jones KL, Smith DW. Recognition of the fetal alcohol syndrome in early infancy. Lancet 1973;302:999–1001 [DOI] [PubMed] [Google Scholar]
- 4. D’Onofrio BM, Van Hulle CA, Waldman ID, Rodgers J, Rathouz PJ, Lahey BB. Causal inferences regarding prenatal alcohol exposure and childhood externalizing problems. Arch Gen Psychiatry 2007;64:1296–304 [DOI] [PubMed] [Google Scholar]
- 5. Vaiserman AM. Long-term health consequences of early-life exposure to substance abuse: an epigenetic perspective. J Dev Orig Health Dis 2013;4:269–79 [DOI] [PubMed] [Google Scholar]
- 6. Burd L, Blair J, Dropps K. Prenatal alcohol exposure, blood alcohol concentrations and alcohol elimination rates for the mother, fetus and newborn. J Perinatol 2012;32:652–9 [DOI] [PubMed] [Google Scholar]
- 7. Lan N, Chiu MP, Ellis L, Weinberg J. Prenatal alcohol exposure and prenatal stress differentially alter glucocorticoid signaling in the placenta and fetal brain. Neuroscience 2015; doi:10.1016/j.neuroscience.2015.08.058. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Kabesch M, Adcock IM. Epigenetics in asthma and COPD. Biochimie 2012;94:2231–41 [DOI] [PubMed] [Google Scholar]
- 9. Joubert BR, Felix JF, Yousefi P, Bakulski KM, Just AC, Breton C, Reese SE, Markunas CA, Richmond RC, Xu CJ. et al. DNA methylation in newborns and maternal smoking in pregnancy: genome-wide consortium meta-analysis. Am J Hum Genet 2016;98:680–96 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Mansell T, Vuillermin P, Ponsonby AL, Collier F, Saffery R, Ryan J. Maternal mental well-being during pregnancy and glucocorticoid receptor gene promoter methylation in the neonate. Dev Psychopathol 2016 Apr 4:1–10. [DOI] [PubMed] [Google Scholar]
- 11. Joubert BR, den Dekker HT, Felix JF, Bohlin J, Ligthart S, Beckett E, Tiemeier H, van Meurs JB, Uitterlinden AG, Hofman A. et al. Maternal plasma folate impacts differential DNA methylation in an epigenome-wide meta-analysis of newborns. Nat Commun 2016;7:10577–85. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Laufer BI, Kapalanga J, Castellani CA, Diehl EJ, Yan L, Singh SM. Associative DNA methylation changes in children with prenatal alcohol exposure. Epigenomics 2015;7:1259–74 [DOI] [PubMed] [Google Scholar]
- 13. Wilhelm-Benartzi CS, Houseman EA, Maccani MA, Poage GM, Koestler DC, Langevin SM, Gagne LA, Banister CE, Padbury JF, Marsit CJ. In utero exposures, infant growth, and DNA methylation of repetitive elements and developmentally related genes in human placenta. Environ Health Perspect 2012;120:296–302 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Azzi S, Sas TC, Koudou Y, Le Bouc Y, Souberbielle JC, Dargent-Molina P, Netchine I, Charles MA. Degree of methylation of ZAC1 (PLAGL1) is associated with prenatal and post-natal growth in healthy infants of the EDEN mother child cohort. Epigenetics 2014;9:338–45 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Lee BY, Park SY, Ryu HM, Shin CY, Ko KN, Han JY, Koren G, Cho YH. Changes in the methylation status of DAT, SERT, and MeCP2 gene promoters in the blood cell in families exposed to alcohol during the periconceptional period. Alcohol Clin Exp Res 2015;39:239–50 [DOI] [PubMed] [Google Scholar]
- 16. Ikemoto S, Yang C, Tan A. Basal ganglia circuit loops, dopamine and motivation: a review and enquiry. Behav Brain Res 2015;290:17–31 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Nutt D, Lingford-Hughes A, Erritzoe D, Stokes PR. The dopamine theory of addiction: 40 years of highs and lows. Nat Rev Neurosci 2015;16:305–12 [DOI] [PubMed] [Google Scholar]
- 18. Spencer GE, Klumperman J, Syed NI. Neurotransmitters and neurodevelopment. Role of dopamine in neurite outgrowth, target selection and specific synapse formation. Perspect Dev Neurobiol 1998;5:451–67 [PubMed] [Google Scholar]
- 19. Money KM, Stanwood GD. Developmental origins of brain disorders: roles for dopamine. Front Cell Neurosci 2013;7 Article 260:1–14 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Shorter KR, Miller BH. Epigenetic mechanisms in schizophrenia. Progress in Biophys Mol Biol 2015;118:1–7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Herman AI, DeVito EE, Jensen KP, Sofuoglu M. Pharmacogenetics of nicotine addiction: role of dopamine. Pharmacogenomics 2014;15:221–34 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Zhang H, Herman AI, Kranzler HR, Anton RF, Zhao H, Zheng W, Gelernter J. Array-based profiling of DNA methylation changes associated with alcohol dependence. Alcohol Clin Exp Res 2013;37: E108–15 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Wong CC, Caspi A, Williams B, Craig IW, Houts R, Ambler A, Moffitt TE, Mill J. A longitudinal study of epigenetic variation in twins. Epigenetics 2010;5:516–26 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. van Mil NH, Steegers-Theunissen RPM, Bouwland-Both MI, Verbiest MMPJ, Rijlaarsdam J, Hofman A, Steegers EAP, Heijmans BT, Jaddoe VWV, Verhulst FC. et al. DNA methylation profiles at birth and child ADHD symptoms. J Psychiatr Res 2014;49:51–9 [DOI] [PubMed] [Google Scholar]
- 25. Kupers LK, Xu X, Jankipersadsing SA, Vaez A, la Bastide-van Gemert S, Scholtens S, Nolte IM, Richmond RC, Relton CL, Felix JF. et al. DNA methylation mediates the effect of maternal smoking during pregnancy on birthweight of the offspring. Int J Epidemiol 2015;44:1224–37 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Di Ciano P, Pushparaj A, Kim A, Hatch J, Masood T, Ramzi A, Khaled MA, Boileau I, Winstanley CA, Le Foll B. The impact of selective dopamine D2, D3 and D4 ligands on the rat gambling task. PLoS One 2015;10:e0136267. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Urban NB, Kegeles LS, Slifstein M, Xu X, Martinez D, Sakr E, Castillo F, Moadel T, O’Malley SS, Krystal JH. et al. Sex differences in striatal dopamine release in young adults after oral alcohol challenge: a positron emission tomography imaging study with [(1)(1)C]raclopride. Biol Psychiatry 2010;68:689–96. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Faraone SV, Bonvicini C, Scassellati C. Biomarkers in the diagnosis of ADHD–promising directions. Curr Psychiatry Rep 2014;16:497. [DOI] [PubMed] [Google Scholar]
- 29. Cheng J, Wang Y, Zhou K, Wang L, Li J, Zhuang Q, Xu X, Xu L, Zhang K, Dai D. et al. Male-specific association between dopamine receptor D4 gene methylation and schizophrenia. PLoS One 2014;9:e89128. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. QIAGEN. EpiTect ChIP qPCR Primers, 2016. http://www.sabiosciences.com/chipqpcrsearch.php?gene=DRD4&species_id=0&factor=Sp1&ninfo=n&ngene=n&nfactor=n (28 June 2016, date last accessed).
- 31. Heyward FD, Sweatt JD. DNA methylation in memory formation: emerging insights. Neuroscientist 2015;21(5):475–89. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Mansell T, Novakovic B, Meyer B, Rzehak P, Vuillermin P, Ponsonby AL, Collier F, Burgner D, Saffery R, Ryan J. The effects of maternal anxiety during pregnancy on IGF2/H19 methylation in cord blood. Transl Psychiatry 2016;6:e765. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Fernandez-Jaen A, Lopez-Martin S, Albert J, Fernandez-Mayoralas DM, Fernandez-Perrone AL, de La Pena MJ, Calleja-Perez B, Rodriguez MR, Lopez-Arribas S, Munoz-Jareno N. Cortical thickness differences in the prefrontal cortex in children and adolescents with ADHD in relation to dopamine transporter (DAT1) genotype. Psychiatry Res 2015;233:409–17 [DOI] [PubMed] [Google Scholar]
- 34. Wiers CE, Shumay E, Volkow ND, Frieling H, Kotsiari A, Lindenmeyer J, Walter H, Bermpohl F. Effects of depressive symptoms and peripheral DAT methylation on neural reactivity to alcohol cues in alcoholism. Transl Psychiatry 2015;5:e648. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Jasiewicz A, Rubis B, Samochowiec J, Malecka I, Suchanecka A, Jablonski M, Grzywacz A. DAT1 methylation changes in alcohol-dependent individuals vs. controls. J Psychiatr Res 2015;64:130–3 [DOI] [PubMed] [Google Scholar]
- 36. Giglia R, Binns C. Alcohol and lactation: a systematic review. Nutr Diet 2006;63:103–16 [Google Scholar]
- 37. Verduci E, Banderali G, Barberi S, Radaelli G, Lops A, Betti F, Riva E, Giovannini M. Epigenetic effects of human breast milk. Nutrients 2014;6:1711–24 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Britigan BE, Lewis TS, Waldschmidt M, McCormick ML, Krieg AM. Lactoferrin binds CpG-containing oligonucleotides and inhibits their immunostimulatory effects on human B cells. J Immunol 2001;167:2921–8 [DOI] [PubMed] [Google Scholar]
- 39. Mulligan P, White NR, Monteleone G, Wang P, Wilson JW, Ohtsuka Y, Sanderson IR. Breast milk lactoferrin regulates gene expression by binding bacterial DNA CpG motifs but not genomic DNA promoters in model intestinal cells. Pediatr Res 2006;59:656–61 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Clark-Gambelunghe MB, Clark DA. Sensory development. Pediatr Clin North Am 2015;62:367–84 [DOI] [PubMed] [Google Scholar]
- 41. Flak AL, Su S, Bertrand J, Denny CH, Kesmodel US, Cogswell ME. The association of mild, moderate, and binge prenatal alcohol exposure and child neuropsychological outcomes: a meta-analysis. Alcohol Clin Exp Res 2014;38:214–26 [DOI] [PubMed] [Google Scholar]
- 42. Lundsberg LS, Illuzzi JL, Belanger K, Triche EW, Bracken MB. Low-to-moderate prenatal alcohol consumption and the risk of selected birth outcomes: a prospective cohort study. Ann Epidemiol 2015;25:46–54.e3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43. Stelzer Y, Jaenisch R. Monitoring dynamics of DNA methylation at single-cell resolution during development and disease. Cold Spring Harb Symp Quant Biol 2015;80:199–206. [DOI] [PubMed] [Google Scholar]
- 44. Alberts B, Wilson J, Hunt T. Molecular Biology of the Cell. New York: Garland Science, 2008 [Google Scholar]
- 45. Filbey FM, Ray L, Smolen A, Claus ED, Audette A, Hutchison KE. Differential neural response to alcohol priming and alcohol taste cues is associated with DRD4 VNTR and OPRM1 genotypes. Alcohol Clin Exp Res 2008;32:1113–23 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Tobi EW, Slagboom PE, van Dongen J, Kremer D, Stein AD, Putter H, Heijmans BT, Lumey LH. Prenatal famine and genetic variation are independently and additively associated with DNA methylation at regulatory loci within IGF2/H19. PLoS One 2012;7:e37933. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47. Markunas CA, Xu Z, Harlid S, Wade PA, Lie RT, Taylor JA, Wilcox AJ. Identification of DNA methylation changes in newborns related to maternal smoking during pregnancy. Environ Health Perspect 2014;122:1147–53 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48. Saffery R. Epigenetic change as the major mediator of fetal programming in humans: are we there yet?. Ann Nutr Metab 2014;64:203–7 [DOI] [PubMed] [Google Scholar]
- 49. Australian Breastfeeding Association. Alcohol and Breastfeeding: Austalian Breastfeeding Association, 2014. https://www.breastfeeding.asn.au/bf-info/safe-when-breastfeeding/alcohol-and-breastfeeding. (May 2016, date last accessed).
- 50. Novakovic B, Ryan J, Pereira N, Boughton B, Craig JM, Saffery R. Postnatal stability, tissue, and time specific effects of AHRR methylation change in response to maternal smoking in pregnancy. Epigenetics 2014;9:377–86 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.

