In Ark if a Baby Is Damaged Does It Lower Imprinting
FASEB J. 2017 Dec; 31(12): 5149–5158.
Impact of folic acid intake during pregnancy on genomic imprinting of IGF2/H19 and 1-carbon metabolism
Aggeliki Tserga
*Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany;
Alexandra M. Binder
†Obstetrics and Gynecology Epidemiology Center, Department of Obstetrics, Gynecology, and Reproductive Biology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; and
‡Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
Karin B. Michels
*Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany;
†Obstetrics and Gynecology Epidemiology Center, Department of Obstetrics, Gynecology, and Reproductive Biology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; and
‡Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
Received 2016 Dec 1; Accepted 2017 Jul 17.
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Supplemental Data
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Abstract
Folic acid is an essential component of 1-carbon metabolism, which generates methyl groups for DNA methylation. Disruption of genomic imprinting leads to biallelic expression which may affect disease susceptibility possibly reflected in high levels of S-adenosyl-homocysteine (SAH) and low levels of S-adenosyl-methionine (SAM). We investigated the association between folic acid supplementation during pregnancy and loss of imprinting (LOI) of IGF2 and H19 genes in placentas and cord blood of 90 mother–child dyads in association with the methylenetetrahydrofolate reductase (MTHFR) genotype. Pyrosequencing was used to evaluate deviation from monoallelic expression among 47 placentas heterozygous for H19 and 37 placentas and cord blood tissues heterozygous for IGF2 and H19 methylation levels of 48 placentas. We detected relaxation of imprinting (ROI) and LOI of H19 in placentas not associated with differences in methylation levels of the H19ICR. Placentas retained monoallelic allele-specific gene expression of IGF2, but 32.4% of cord blood samples displayed LOI of IGF2 and 10.8% showed ROI. High SAH levels were significantly associated with low H19 methylation. An interesting positive association between SAM/SAH ratio and high H19 methylation levels was detected among infants with low B12 levels. Our data suggest profound differences in regulation of imprinting in placenta and cord blood; a lack of correlation of the methylome, transcriptome, and proteome; and a complex regulatory feedback network between free methyl groups and genomic imprinting at birth.—Tserga, A., Binder, A. M., Michels, K. B. Impact of folic acid intake during pregnancy on genomic imprinting of IGF2/H19 and 1-carbon metabolism.
Keywords: folate, epigenetics, DNA methylation, MTHFR, placenta
Folic acid supplementation before and during pregnancy is recommended, even in fortified populations to prevent neural tube defects (1–4). In addition, maternal folate levels may impact the risk of pregnancy complications and influence infant phenotypes. The reported associations between maternal folate levels and infant birthweight are inconsistent, whereas one study in the United States showed a slight decreased risk for low birth weight after folic acid fortification (5), no relation between folate and growth-retarded fetuses was found in a population of low-socioeconomic status South Asian women (6). These variations could be related to differences in the populations studied or the methods used. Low socioeconomic status is associated with both low folate levels and intrauterine growth restriction and may thus confound this association (7, 8). Elevated levels of homocysteine, a biomarker of folate status, have been associated with miscarriage (9), preeclampsia (10), Down syndrome (11) and placenta abruptions (12). Moreover, periconceptional folic acid supplementation has been associated with an increased incidence of asthma in the offspring (13, 14).
These associations between maternal folate levels and in utero development may be mediated by epigenetic marks, which are established prenatally. One of the most studied epigenetic marks is DNA methylation, which describes the enzymatic addition of a methyl group to the carbon 5′ position of cytosines (15, 16). Micronutrients, such as folate and vitamin B12, affect the process of 1-carbon metabolism, which provides the methyl groups for DNA methylation (2). Folate transfers its methyl group to homocysteine, to form methionine, with vitamin B12 as cofactor. Methionine is then converted to the methyl donor S-adenosyl-methionine (SAM), which is subsequently catalyzed by DNA methyltransferases to produce 5-methylcytosine and S-adenosyl-homocysteine (SAH). SAH is reversibly hydrolyzed to adenosine and homocysteine. Homocysteine can either be remethylated back to methionine or removed from the methylation cycle by cystathionine β-synthase in the transsulfuration pathway and used for the production of glutathione, the key molecule of the oxidative cycle (17, 18). One key enzyme of 1-carbon metabolism is methylenetetrahydrofolate reductase (MTHFR), which regulates 5-methyltetrahydrofolate synthesis and homocysteine remethylation (19). The best studied MTHFR single-nucleotide polymorphism (SNP) is MTHFR C677T (rs1801133), which results in a thermolabile variant of MTHFR (20). Individuals homozygous for the MTHFR 677TT displays lower folate and increased homocysteine levels, impaired SAM production, and lower methyl group availability (21, 22).
DNA methylation is an important regulator of genomic imprinting that plays a key role in fetal development. Genomic imprinting is the monoallelic gene expression of certain genes, dependent on the parent of origin (23, 24). Disruption of genomic imprinting [loss of imprinting (LOI)] leads to reactivation the silent allele, resulting in biallelic expression. LOI is associated with several childhood disorders, such as Angelman syndrome (25), Prader-Willi syndrome (26), Beckwith-Wiedemann syndrome (27), Rett syndrome (28), and Wilms' tumor (29) and has also been a primary determinant of adult cancers (30). Two well-studied reciprocally imprinted genes associated with fetal growth are IGF2 and H19. The maternal allele of the IGF2DMR0 is silenced via DNA methylation and is paternally expressed (31). The maternally expressed H19 is located downstream of IGF2 encoding a noncoding RNA which also regulates cellular growth (31). Epigenetic control of these genes may be influenced by maternal plasma folate, which is actively delivered to the fetus through placental folate receptors (32). Specifically, preconceptional folate levels may be relevant, because DNA methylation of imprinted genes is established in gametes and escapes the second demethylation and remethylation cycle after fertilization (24).
In this study, we investigated the influence of maternal folate intake on IGF2 and H19 imprinting regulation in the offspring and whether this association is modified by C677T genotype. We assessed folate levels in fetal cord blood, which reflects the sum of maternal folate intake and folate metabolism of mother and child in the Harvard Epigenetic Birth Cohort. We examined the associations between folate level and other elements of 1-carbon metabolism with methylation and allele-specific expression of the imprinted genes IGF2 and H19 in cord blood and placenta tissue. To the best of our knowledge, this is the first study to investigate the effect of folate on LOI in pregnancy.
MATERIALS AND METHODS
Study population
Data and biospecimens were collected between June 2007 and June 2009 on the labor and delivery floor of the Department of Obstetrics, Gynecology, and Reproductive Biology [Brigham and Women's Hospital (BWH), Boston, MA, USA], as part of the Harvard Epigenetic Birth Cohort, which comprises 1941 mother–child dyads. The study protocol was approved by the BWH Institutional Review Board, and has been described by Michels et al. (33). We selected 90 non-Hispanic Caucasian mother–child dyads with a gestational age ≥37 wk, who were homozygous for either the C or the T allele of the MTHFR C677T polymorphism in both mother and child. Pregnancies with gestational diabetes and preeclampsia were excluded. Information on supplement use before and during pregnancy was self-reported by participants at the time of delivery. Women were classified as having taken folic acid supplements before pregnancy if they reported having taken multivitamins, folic acid supplements, or prenatal vitamins before confirmation of pregnancy. Supplement use during pregnancy was coded similarly. If intake during pregnancy was not reported, we used information abstracted from medical charts to determine supplement use.
Sample preparation
Placental tissue was sampled by a 2-cm incision in the amnion. For this study, we analyzed samples (1 cm3) taken from the fetal side near the umbilical cord (near upper). Genomic DNA and RNA were extracted from fresh-frozen placenta tissue by using the QiaAmp DNA Mini Kit and RNeasy Mini Kit, respectively, following the manufacturer's instructions (Qiagen, Valencia, CA, USA). RNA was also extracted from whole cord blood using the mirVana miRNA Isolation Kit, according to the manufacturer's instructions (Thermo Fisher Scientific, Waltham, MA, USA). cDNA and reverse transcriptase (RT)–negative controls were synthesized in duplicate according to the High Capacity cDNA Reverse Transcription Kit manufacturer's protocol (Thermo Fisher Scientific). DNA- and DNAse-treated RNA concentrations were determined with the NanoDrop ND-1000 Spectrophotometer. DNA isolated from placenta specimens was treated with sodium bisulfite with the EZ DNA Gold Methylation kit, according to the manufacturer's alternative protocol 2 (Zymo Research, Irvine, CA, USA). Every sample was bisulfite treated in duplicate.
RBC folate assessment
Red blood cell (RBC) folate was assessed in cord blood. Cord blood samples were collected into EDTA-Vacutainer tubes (BD Biosciences, San Jose, CA, USA) and immediately chilled on ice before centrifuging at 4000 g for 10 min at 4°C. Plasma, buffy coat, and RBCs were separated into 3 phases and stored separately in liquid nitrogen or at −80°C, respectively, until further processing. RBC folate was assessed in the laboratory of Nader Rifai (Children's Hospital, Boston, MA, USA). RBC folate was measured with an autoimmunoanalyzer (2010 Elecsys; Roche Diagnostics, Indianapolis, IN, USA) by a competitive test principle that involves a natural folate-binding protein specific for folate. RBCs were first lysed with ascorbic acid, and folate was measured on the hemolysate. Hemoglobin was also measured on this hemolysate, so the final RBC folate result was expressed as folate per gram of hemoglobin. The sample was treated with monothioglycerol and sodium hydroxide to release the folate from endogenous binding proteins. Then, the sample was incubated with a ruthenium-labeled folate-binding protein, forming a folate complex. Biotinylated folate and streptavidin-coated magnetic microparticles were then added to the reaction mixture. The entire ruthenium labeled folate binding protein–folate biotin complexes become bound to the magnetic microparticles, where they were magnetically entrapped on the electrode and the unbound reagents and sample were washed away. A chemiluminescent reaction was electrically stimulated to generate light, the intensity being indirectly proportional to the amount of folate present in the sample. This assay has been approved by the U.S. Food and Drug Administration for clinical use. The lowest detection limit of the assay is 0.6 ng/ml, and the day-to-day imprecision values at concentrations of 7.6, 14.3, and 19.2 ng/ml are 3.9, 3.1, and 2.0%, respectively. Normal range is 3.1 to 17.5 ng/ml.
SAM/SAH, adenosine measurements
Cord blood samples were collected into EDTA-Vacutainer tubes and immediately chilled on ice before centrifuging at 4000 g for 10 min at 4°C. Plasma aliquots were transferred into cryostat tubes and stored in liquid nitrogen until extraction and HPLC quantification. SAM and SAH measurements were performed in the laboratory of Jill James (Autism Metabolic Genomics Laboratory, Arkansas Children's Hospital Research Institute, Little Rock, AR, USA). To assay SAM and SAH, 100 ml of 10% metaphosphoric acid was added to 200 ml plasma to precipitate protein; the solution was mixed well and incubated on ice for 30 min. After centrifugation for 15 min at 18,000 g at 4°C, supernatants were passed through a 0.2-mm nylon membrane filter, and 20 ml was injected into the high-performance liquid chromotography (HPLC) system. The separation of metabolites was performed by HPLC with a Shimadzu (Tokyo, Japan) solvent delivery system (ESA model 580), and a reverse phase C18 column (5 mm; 4.6 × 150 mm; MCM) obtained from ESA Biosciences (Chelmsford, MA, USA). A 20-ml aliquot of plasma extract was directly injected onto the column by using Autosampler (model 507E; Beckman Coulter, Brea, CA, USA). All plasma metabolites were quantified on a model 5200A Coulochem II and CoulArray electrochemical detection systems (ESA Biosciences) equipped with a dual analytical cell (model 5010), a 4-channel analytical cell (model 6210), and a guard cell (model 5020). The concentrations of plasma metabolites were calculated from peak areas and standard calibration curves with HPLC software.
Vitamin B12 measurements
Vitamin B12 assessments in cord blood were performed in the laboratory of Nader Rifai (Children's Hospital, Boston, MA, USA). Vitamin B12 was measured by a quantitative sandwich enzyme immunoassay technique on the E Modular system (Roche Diagnostics). In short, a biotinylated monoclonal vitamin B12-specific antibody and ruthenium-labeled monoclonal vitamin B12-specific antibody were mixed with the serum sample to capture sample vitamin B12 in a sandwich complex. Streptavidin-coated magnetic microparticles were then added to the reaction mixture to bind the biotinylated antibody. The immune complexes were magnetically entrapped on the electrode and the unbound reagents and sample were washed away. Voltage was applied to the electrode, stimulating a chemiluminescent reaction to generate light, the intensity being directly proportional to the amount of vitamin B12 present in the sample. The lowest detection limit of this assay is 30 pg/ml and the day-to-day imprecision values at concentrations of 203, 481, and 1499 pg/ml are 7.6, 4.4, and 3.2%, respectively.
H19, IGF2, and MTHFR genotyping
Isolated DNA (25 ng) was genotyped for the H19 SNPs rs3741219 and rs2839698, IGF2 SNP rs2585 (34), and MTHFR SNP rs1801133 SNP (primers available upon request), by PCR and pyrosequencing with the PyroMark Q24 pyrosequencer (Qiagen).
Quantification of allele-specific expression
The quantification of allele-specific expression was performed on heterozygous cDNA (informative) for IGF2 and H19 SNPs (the H19 SNPs rs3741219 and rs2839698, IGF2 rs2585) on the Pyromark Q24 Pyrosequencer (Qiagen). Allele-specific expression assays were designed with the PyroMark Assay Design 2.0 software (http://www.qiagen.com), with the same sequence regions that were used for the SNP genotyping assays for H19 and IGF2. The reverse primer was biotinylated for H19 rs3741219 and the forward primer for H19 rs2839698 and IGF2 rs2585, with the sequencing primer located next to the SNP for all assays (34). Primer sequence and PCR conditions for pyroassays have been described by Rancourt et al. (34). Allele-specific pyrosequencing values are reported as a percentage of expression from each allele ranging from 0 to 100%. Each imprinted gene is expected to show 100% expression from one of the parental alleles and 0% from the other. RT-negative control samples revealed no amplification, ensuring that the presence of both alleles was strictly from the RNA. The parent of origin of the SNP could not be determined, as we did not assess the genotype of the parents.
Bisulfite pyrosequencing to assess DNA methylation
Pyrosequencing was performed on bisulfite-treated DNA with the Pyromark Q24 Pyrosequencer. Bisulfite treatment and pyrosequencing were performed in duplicate. Percentage methylation was analyzed across 8 cytosine-phosphate-guanine (CpG) sites located within H19ICR. The number of CpG sites was dependent on the neighboring sequence and was determined by the PyroMark Assay Design 2.0 software. Bisulfite-converted DNA was mixed with 0.2 μM of each primer and amplified with the 2MMG Megamix-Gold master mix (Microzone, Haywards Heath, United Kingdom). H19 primers have been described (35). We did not measure methylation changes at IGF2DMR2 or IGF2DMR0.
IGF2 protein measurements
IGF2 protein levels in cord blood were assessed in the laboratory of Nader Rifai, PhD, at Children's Hospital. IGF2 protein levels were measured by an ELISA assay from Alpco Diagnostics (Salem, NH, USA). The assay employs the quantitative sandwich enzyme immunoassay technique. First the sample was diluted with an acidic buffer to release the IGF2 from its binding protein. Monoclonal antibodies specific for IGF2 were precoated onto a microtiter plate. After incubation with treated samples, standards, and controls, the microtiter plate was washed to remove unbound compounds. A peroxidase conjugated antibody was then added to attach to the IGF2 bound to the microtiter plate, forming a sandwich of the immobilized antibody, the IGF2 and the enzyme-linked antibody specific to IGF2. After a wash to remove unbound substances, an enzyme substrate was added and color was generated that was proportional to the amount of IGF2 present in the sample. The day-to-day variability of the assay at various concentrations IGF2 is <10%.
Ethics statement
The participation of human subjects occurred after informed consent was obtained. The study protocols were approved by the Institutional Review Board of Brigham and Women's Hospital.
Statistical analysis
To investigate the network of linear dependencies among the measured 1-carbon metabolism biomarkers, we estimated the pairwise Pearson correlations between all biomarkers. Conditional dependence was assessed by estimating the partial correlations (36), evaluating the correlations between 2 biomarkers adjusting for all other compounds. Significant partial correlations are a stronger indicator of a direct association. For these correlations, missing values were mean imputed, assuming random missingness.
Imprinting variation was assessed by the deviation from allele-specific expression, which ranged from 0 to 50%, with 0% indicating allele-specific expression and 50% representing total loss of imprinting (equal expression of both alleles). Variation in imprinting has previously been investigated in an independent subset of this cohort by Rancourt et al. (34). Using cutoffs published in this prior publication, we divided imprinting status into 3 categories that included maintenance of imprinting: deviation from allele-specific expression ≤10%; relaxation of imprinting (ROI): deviation from allele specific expression 11–25%, and loss of imprinting (LOI): deviation from allele-specific expression >25%. One-carbon metabolism biomarkers with a distribution significantly different from normal (Shapiro-Wilk test; P < 0.05) were log transformed to reduce right skew. Spearman and Pearson correlations were used to identify shared variation between maternal and infant characteristics and 1-carbon metabolism, as well associations with H19 and IGF2 imprinting and imprinting control. Parametric models were used to identify possible effect modification by MTHFR genotype or B12 level, using robust standard errors to account for possible heteroscedasticity. The H19 and IGF2 measures were modeled as a linear function of each of 1-carbon metabolism biomarkers separately, with effect modification by MTHFR genotype assessed by adding an interaction with the biomarker and using a Wald test to evaluate significance of this term. Similarly, we tested for effect modification by B12 level, dichotomized as high or low, relative to the median (696 pg/ml) in the population, on these associations. Among models for which these interactions were significant, correlations were stratified by the effect modifier. Significance was determined by an α-level of 0.05. All statistical analysis was performed with R, version 3.2.1.
RESULTS
Our study population was restricted to non-Hispanic Caucasian mothers who had a spontaneous conception and term delivery. To assess possible effect modification by MTHFR C677T genotype, we selected 45 dyads for which both the mother and infant were homozygous for the C allele, and 45 that were both homozygous for the T allele. Most of the mothers were over 30 yr old and had a normal body mass index (18 < BMI < 25 kg/m2) ( Table 1 ). Approximately 78% of the mothers self-reported taking folic acid supplements, multivitamins, or prenatal vitamins before conception. Correspondingly, 82% of the women reported that their pregnancy was planned. Of the 20 women who did not take any of these supplements before pregnancy, 90% initiated taking supplements after pregnancy confirmation. Among the mothers who took supplements during pregnancy, the impact of supplement use before pregnancy on RBC folate was modified by the MTHFR genotype (P = 0.04, Fig. 1 ). However, there was no significant association between RBC folate and self-reported intake before pregnancy, after stratifying by MTHFR genotype. The lack of association between preconceptional supplement use and RBC folate at birth in this cohort may be explained by the generally adequate folate supply in this fortified population. Furthermore, supplement use during pregnancy may have obfuscated any influence of preconception folic acid on RBC folate at birth. Other 1-carbon-metabolism biomarkers were measured in the plasma of all cord blood samples obtained at delivery. The analysis of H19 allele-specific expression was assessed in 48 placenta samples heterozygous (informative) for either the rs2839698 or rs3741219 SNPs in H19, located in the first and last exon, respectively. For IGF2 allele-specific expression, associations with biomarkers were restricted to the 37 placenta and cord blood samples heterozygous for the IGF2 SNP rs2585.
TABLE 1.
Maternal and infant characteristics in the full samples and the dyads informative for H19 and IGF2 allele-specific expression
Characteristic | Full sample, n = 90 | Samples for H19 ASE, n = 48 | Samples for IGF2 ASE, n = 37 |
---|---|---|---|
Maternal age (yr) | 32 (18–43) | 33 (18–43) | 32 (19–41) |
Prepregnancy BMI (kg/m2) | 23 (17.49–44.09) | 22.99 (18.66–44.09) | 21.95 (17.72–44.09) |
Gestational age (wk) | 39.39 (47.14–41.57) | 39.36 (37.57–41.29) | 39.36 (38.57–41.57) |
Birth weight (kg) | 3.49 (2.41–4.22) | 3.43 (2.41–4.22) | 3.54 (2.86–4.20) |
Birth weight for GA [n (%)] | |||
SGA | 1 (1.11) | 1 (2.08) | 0 (0) |
AGA | 84 (93.33) | 43 (89.58) | 34 (91.89) |
LGA | 5 (5.56) | 4 (8.33) | 3 (8.11) |
Birth length (cm) | 49.53 (45.72–53.34) | 49.53 (45.72–53.34) | 50.80 (45.72–53.34) |
Infant sex [n (%)] | |||
Female | 54 (60) | 30 (62.5) | 22 (59.46) |
Male | 46 (40) | 18 (37.5) | 15 (40.54) |
Folic acid supplementation [n (%)] | |||
Preconception | |||
No | 2 (2.22) | 2 (4.17) | 0 (0) |
No | 18 (20.00) | 10 (20.83) | 8 (21.62) |
Yes | 70 (77.78) | 36 (75.00) | 29 (78.38) |
Postconception | |||
No | 2 (2.22) | 2 (4.17) | 0 (0) |
Yes | 18 (20.00) | 10 (20.83) | 8 (21.62) |
Yes | 70 (77.78) | 36 (75.00) | 29 (78.38) |
RBC folate levels in cord blood of infants whose mothers reported taking folic acid supplements before pregnancy (yes) and those who did not (no), stratified by MTHFR genotype. Restricted to mothers who reported taking folic acid during pregnancy.
Correlations between the biomarkers of 1-carbon metabolism
To appraise the concordance between our data and the expected correlations based on the 1-carbon metabolism pathway, we assessed both the pairwise and partial correlations between our measured biomarkers of 1-carbon metabolism. After correcting for multiple testing (Bonferroni), we detected only 2 significant correlations ( Fig. 2 and Supplemental Table 1). Adenosine correlated strongly (R = 0.67) with its precursor SAH. SAM also strongly correlated (R = 0.67) with its precursor methionine. These correlations were consistent when we considered the partial correlation between biomarkers, and possible effect modification by B12 levels. MTHFR genotype was not associated with measured levels of any of the biomarkers such as SAH, SAM, and adenosine (Supplemental Fig. 1). Our results suggest that, although some direct influences can be identified in our data, the biomarkers of the 1-carbon metabolism represent a complex network that should be considered in its entirety.
Pairwise Pearson (A) and partial (B) correlations between each biomarker, and among individuals with high (C) and low (D) B12 (dichotomized at median 696 pg/ml). Width of line corresponds to the strength of the correlation (wider, stronger correlation); blue, positive correlation; red, negative correlation; solid line, significant correlation adjusting for multiple testing (Bonferroni); dotted line, not significant, after adjusting for multiple testing. Estimated correlations significant at P < 0.05 included in Supplemental Table 1.
Imprinting control in the placenta and cord blood
In placental samples, we analyzed H19 allele-specific expression and DNA methylation within the H19 imprinted control region (ICR). Pyrosequencing revealed ROI of H19 in 2 placentas, with LOI in 1. To examine the influence of DNA methylation on the observed variation in H19 placental imprinting, we pyrosequenced 8 CpG loci within the H19ICR of 48 placentas informative for allele-specific expression. Total biallelic percentage of DNA methylation across this region was averaged and ranged from 30.6 to 46.1%. The 2 individuals with H19 ROI showed an average biallelic methylation level of 36.1 and 30.6%, respectively, and the placenta with H19 LOI had an average methylation level of 42.5%. Thus, methylation levels averaged across 8 CpG loci within the H19ICR did not correlate with the allele-specific expression of H19 (ρ = 0.118; P = 0.423). Similarly, average methylation of the H19ICR did not significantly vary between categories of imprinting (e.g., maintenance of imprinting, ROI, and LOI) for H19 (Kruskal-Wallis, P = 0.110). We did not investigate imprinting status of H19 in cord blood after the observation of Rancourt et al. (34), who did not identify differences between H19 allele-specific gene expression in cord blood.
In contrast, we analyzed allele-specific expression of IGF2 in both placenta tissue and cord blood, as well as the associated variation in cord blood plasma IGF2 protein levels. IGF2 protein levels can be considered as a proxy for the potential biologic impact of loss of imprinted gene expression. We did not directly assay cord blood IGF2DMR2 or IGF2DMR0 methylation. DNA methylation is one of the determinants of protein levels; other modifiers include histone modifications and noncoding RNAs. All placentas displayed monoallelic gene expression of IGF2, confirming the previous results of Rancourt et al. (34). Correspondingly, methylation of the H19ICR did not correlate with IGF2 allele-specific expression in the placenta (ρ = −0.193, P = 0.400). In accordance with these prior findings, allele-specific gene expression was substantially less maintained in cord blood, with 32.4% (n = 12) of infants displaying an LOI of IGF2 and ROI in an additional 10.8% (n = 4). Allele-specific expression of IGF2 cord blood did not correlate with an increase in IGF2 protein levels measured in cord plasma (ρ = −0.010; P = 0.95). Given the high prevalence of imprinting maintenance (allele-specific gene expression) in placenta IGF2, we focused further analyses on associations with IGF2 allele-specific expression in cord blood.
Association between self-reported folic acid supplements, folate blood levels, and the regulation of H19 and IGF2 imprinting status
The focus of our study was to evaluate the influence of folate on imprinting status in cord blood and placenta tissue. First we considered self-reported folic acid intake. Given that only two individuals did not take supplements (multivitamins or folic acid) during pregnancy, they were excluded from the statistical analyses and we focused our attention on the impact of supplement use before pregnancy compared to women who reported taking folic acid only during pregnancy. MTHFR677 genotype modified the association between self-reported supplement use and IGF2 allele-specific expression in cord blood (P = 0.01). However, these interactions were driven by two MTHFR677TT individuals who did not take supplements and should be interpreted with caution (Fig. 1). RBC folate in cord blood was not associated with the imprinting control of either H19 in placenta tissue or IGF2 in cord blood ( Fig. 3 ). We did not detect any significant associations between self-reported supplement use before pregnancy and imprinting control of either H19 in placental tissue or IGF2 in cord blood ( Fig. 4A ).
Spearman (ρ) and Pearson (R) correlations between 1-carbon metabolism biomarkers and H19 (A) and IGF2 (B) imprinting status. *P < 0.05.
A) DNA methylation and imprinting status of H19 in placental tissue of mothers who took folic acid supplements before pregnancy (yes) and those who did not (no), stratified by MTHFR genotype. Restricted to mothers who took folic acid during pregnancy. B) Imprinting status of IGF2 and IGF2 protein level in cord blood of infants whose mothers took folic acid supplements before pregnancy (yes) and those who did not (no), stratified by MTHFR genotype. Restricted to mothers who took folic acid during pregnancy.
Association between direct and indirect methyl group donors and the regulation of H19 and IGF2 imprinting in placenta and cord blood
Next, we considered the association between correlates of folic acid intake or free methyl group availability or both on H19 imprinting maintenance in the placenta. H19 allele-specific expression did not correlate with any of the one-carbon metabolism biomarkers (e.g., SAM, SAH, SAM/SAH, B12, and methionine) (Fig. 3). SAH is an inhibitor of most SAM-dependent methyltransferases, and thus an increase in SAH may be associated with global hypomethylation. Correspondingly, log(SAH) had a significant moderate inverse correlation (R = −0.40) with the methylation level of the H19ICR. We found a significant interaction between B12 level, dichotomized as high or low relative to the median (696 pg/ml), and the SAM:SAH ratio on H19ICR methylation in placenta (P = 0.01 for interaction). An increase in the SAM:SAH ratio, indicative of greater methyl-group donor availability, was associated with higher methylation levels only among individuals with low B12 levels (ρ = 0.60; Supplemental Fig. 2). An increase in SAM/SAH also correlated with higher H19 methylation levels among all placenta samples (R = 0.38; Fig. 3). MTHFR677 genotype did not modify any of these associations.
IGF2 allele-specific expression in cord blood was independent of the measured markers of 1-carbon metabolism, but correlated inversely with B12 plasma levels (Fig. 3; ρ = −0.35). In parametric models, we found that MTHFR genotype modified this association (P = 0.02 for interaction). Among mothers and infants with the homozygous MTHFR 677TT genotype, deviation from IGF2 allele-specific expression decreased as B12 levels increased (ρ = −0.72; Supplemental Fig. 3). Despite these impacts on allele-specific expression, none of these biomarkers was associated with IFG2 protein levels (Fig. 3).
Correlations with maternal–infant traits
Variation in H19 or IGF2 imprinting did not correlate with any maternal or fetal traits (Supplemental Fig. 4). Little of the observed variation in 1-carbon metabolism biomarkers was associated with maternal or infant traits; the few significant correlations found were relatively weak (Supplemental Fig. 5). Higher maternal age and greater birth length correlated weakly with higher methionine levels. Maternal age also correlated inversely with SAH levels. An increase in birth weight was associated with a decrease in B12 levels (R = −0.23).
DISCUSSION
The periconceptional period is characterized by the erasure and resetting of epigenetic markers, specifically those that regulate imprinting. This reprogramming step may be influenced by the availability of free methyl groups and thus by maternal folate status. Since 1998, staple foods such as refined flour and white rice have been fortified with folic acid in the United States to prevent neural tube defects in unplanned pregnancies (38). In addition, it is recommended that pregnant women and women who plan a pregnancy take a 400 μg/d folic acid supplement (39, 40). Folic acid food fortification has increased RBC folate and lowered total homocysteine levels in the U.S. population (41, 42), but there is no consensus regarding the optimal maternal and fetal folate levels (43). In this study, we investigated the influence of maternal folate intake on IGF2 and H19 imprinting regulation in cord blood and the placenta. Compared to prior investigations, our study was uniquely powered to investigate possible effect modification of the association between folate levels and IGF2/H19 imprinting by MTHFR genotype and the first to analyze changes in the placental imprinting of these genes. In addition, this was the first study to investigate possible associations between imprinting control and other 1-carbon metabolism biomarkers.
IGF2 and H19 are involved in the development of embryonic and extraembryonic tissues and fetal growth, and 2 of the most studied imprinted genes. Most prior studies investigating the impact of maternal folic acid supplementation or RBC folate on the imprinting status of these genes have focused on associations with DNA methylation within the ICRs (44). In the Newborn Epigenetics Study (NEST), Hoyo et al. (45) studied the association between estimated folate intake based on self-reported questionnaires and DNA methylation in the IGF2 and H19 ICRs in umbilical cord blood. The authors concluded that folic acid supplementation, periconceptionally and during pregnancy, is associated with lower DNA methylation of IGF2DMRs in infants. In another recent study, Haggarty et al. (46) assayed the methylation level of a handful of CpGs in IGF2, rPEG3, SNRPN, and LINE1 in cord blood in relation to folate intake before and during pregnancy. The authors genotyped mothers and infants according to common SNPs in MTHFR, MTR, MTRR, and TCN2 and measured maternal and cord blood RBC folate status. No correlation between RBC folate levels and DNA methylation status of any gene and SNP genotype was found. However, the authors observed that self-reported folic acid intake after 12 wk of gestation was associated with higher DNA methylation of IGF2 and lower DNA methylation of PEG3 and LINE1 in the offsprings. In our study, self-reported folic acid supplementation did not correlate significantly with RBC folate levels measured in cord blood. Beyond possible errors in self-reports, an explanation for this lack of association may be a difference in the gestational period covered by the self-reported folic acid intake compared to RBC folate, which is an integrative long-term biomarker. In addition, food fortification many obscure the impact of additional supplements on folate levels. Despite this lack of correlation, neither self-reported folic acid intake nor RBC folate was associated with H19 DNA methylation in our population, in contrast to these prior reports. Furthermore, we found no association between either folic acid supplementation or RBC folate and allele-specific expression of H19 in the placenta or IGF2 in placenta or cord blood.
In the present study, increased SAH levels correlated significantly with decreased H19ICR methylation; SAH has higher affinity binding to SAM-dependent methyltransferases than SAM, acting as an inhibitor of DNA methylation (47, 48). Our results are in accordance with previous studies in human lymphocytes (49) and animal studies (50) in which high SAH levels were associated with lymphocyte DNA hypomethylation or global DNA hypomethylation in mice. We found an unexpected positive association between the SAM:SAH ratio and high H19ICR methylation levels among individuals with low B12 levels. We have no obvious explanation for this finding. It is possible that, at low B12 levels, the concentrations of SAM and SAH become more important determinants of methylation. We found low B12 levels to be associated with aberrant allele-specific expression of IGF2, especially among infants with the MTHFR TT/TT genotype. MTHFR converts 5,10-methylene tetrahydrofolate to 5-methyl tetrahydrofolate, which is the methyl donor in homocysteine remethylation to methionine (43, 51). The reduced enzymatic activity of MTHFR 677TT genotype may therefore represent a possible explanation of the increased deviation of IGF2 allele-specific expression in the cord blood of TT/TT infants.
We did not observe any correlation between imprinting and imprinting control in either the placenta or in cord blood. Variation in H19 DNA methylation was not associated with allele-specific expression of H19 in our population. These findings are in contrast to textbooks of epigenetics (15) and observations made in animal studies, but are in agreement with previous studies (34, 52, 53), which detected no significant differences in ICR methylation levels of biallelically expressed imprinted genes in human cord blood, placenta, and adult blood. Normal methylation levels of H19ICR, even in the presence of allele-specific expression may be related to a somatic imprinting aberration. Because we could measure IGF2 protein levels, we did not assay IGF2DMR2 or IGF2DMR0 methylation in cord blood. Protein levels reflect the exact expression status of a gene, which is partially modulated by CpG methylation an intermediate process that leads to alterations on allele-specific gene expression. Allele-specific expression of IGF2 in cord blood was not associated with changes in IGF2 protein levels measured in cord blood plasma. Several other studies have also reported a lack of association between allele-specific expression of IGF2 and overall IGF2 expression levels (34, 54, 55). Ru-Fei et al. (54) detected no significant differences in overall IGF2 expression levels in the blood of healthy Chinese women and IGF2 ROI or LOI. In Wilms' tumors, Wang et al. (55) detected no association between the increased overall expression of IGF2 and LOI. Our results, along with these studies, suggest that the imprinting status of IGF2 may not substantially affect IGF2 protein levels. Absence of variation in the protein levels of the cases with LOI could result from abnormal expression of the normally silent allele and repression of the normally active allele. Cellular degradation of the excess IGF2 protein or involvement of other repressive epigenetic mechanisms such as noncoding RNAs, histone modifications, and chromatin structure may explain IGF2 stable protein levels.
Deviations from allele-specific expression of H19 and IGF2 in placenta and of IGF2 in cord blood, and the mean methylation of H19ICR in placentas were not associated with any maternal or infant characteristics. LOI and ROI are prevalent at birth (34) and in adulthood (56, 57) among phenotypically normal individuals. Conversely, whether LOI at birth may affect future disease susceptibility remains to be established (58). It is noteworthy that there was 100% maintenance of the placental monoallelic IGF2 expression among the 90 mother–infant dyads, which may be in line with the healthy phenotypes at birth. (This study population included no intrauterine growth restriction, preeclampsia, or other pregnancy complications.)
In conclusion, we detected aberrant H19 methylation in placenta and deviation from monoallelic gene expression of IGF2 in cord blood of infants that was independent of self-reported maternal folic acid supplementation during pregnancy. RBC folate levels in cord blood also were not associated with imprinting control of H19 or IGF2. Infants with LOI or aberrant DNA methylation had normal phenotype at birth; however, little information is available on how these alterations may affect health throughout the life course. The lack of association between IFG2 LOI and protein levels suggests a more complex regulatory process of protein synthesis or a potential threshold effect. Future large studies and follow-up studies of the infants in the current study are needed to examine the possible effects of folic acid fortification on development and its potential link to disease later in life.
Supplementary Material
ACKNOWLEDGMENTS
The Harvard Epigenetic Birth Cohort was funded by U.S. National Institutes of Health (NIH), National Cancer Institute Research Grant R21CA128382 (to K.B.M.). A.M.B. was supported by NIH National Institute of Child Health and Human Development Training Grant T32HD060454 in Reproductive, Perinatal and Pediatric Epidemiology. The authors declare no conflicts of interest.
Glossary
CpG | cytosine-phosphate-guanine |
HPLC | high-performance liquid chomatography |
ICR | imprinted control region |
LOI | loss of imprinting |
MTHFR | methylenetetrahydrofolate reductase |
RBC | red blood cell |
ROI | relaxation of imprinting |
SAH | S-adenosyl-homocysteine |
SAM | S-adenosyl-methionine |
SNP | single-nucleotide polymorphism |
Footnotes
AUTHOR CONTRIBUTIONS
A. Tserga and K. B. Michels designed and conducted the research; A. Tserga performed the experiments; A. M. Binder performed the statistical analyses; and all authors wrote the draft, and read and approved the final manuscript.
REFERENCES
1. Vanhees K., Vonhögen I. G., van Schooten F. J., Godschalk R. W. (2014) You are what you eat, and so are your children: the impact of micronutrients on the epigenetic programming of offspring. Cell. Mol. Life Sci. 71, 271–285 [PubMed] [Google Scholar]
2. Laanpere M., Altmäe S., Stavreus-Evers A., Nilsson T. K., Yngve A., Salumets A. (2010) Folate-mediated one-carbon metabolism and its effect on female fertility and pregnancy viability. Nutr. Rev. 68, 99–113 [PubMed] [Google Scholar]
3. Bailey L. B., Stover P. J., McNulty H., Fenech M. F., Gregory J. F. III, Mills J. L., Pfeiffer C. M., Fazili Z., Zhang M., Ueland P. M., Molloy A. M., Caudill M. A., Shane B., Berry R. J., Bailey R. L., Hausman D. B., Raghavan R., Raiten D. J. (2015) Biomarkers of nutrition for development-folate review. J. Nutr. 145, 1636S–1680S [PMC free article] [PubMed] [Google Scholar]
4. Czeizel A. E., Dudás I. (1992) Prevention of the first occurrence of neural-tube defects by periconceptional vitamin supplementation. N. Engl. J. Med. 327, 1832–1835 [PubMed] [Google Scholar]
5. Shaw G. M., Carmichael S. L., Nelson V., Selvin S., Schaffer D. M. (2004) Occurrence of low birthweight and preterm delivery among California infants before and after compulsory food fortification with folic acid. Public Health Rep. 119, 170–173 [PMC free article] [PubMed] [Google Scholar]
6. Lindblad B., Zaman S., Malik A., Martin H., Ekström A. M., Amu S., Holmgren A., Norman M. (2005) Folate, vitamin B12, and homocysteine levels in South Asian women with growth-retarded fetuses. Acta Obstet. Gynecol. Scand. 84, 1055–1061 [PubMed] [Google Scholar]
7. Rondo P. H., Tomkins A. M. (2000) Folate and intrauterine growth retardation. Ann. Trop. Paediatr. 20, 253–258 [PubMed] [Google Scholar]
8. Mason J. B., Saldanha L. S., Ramakrishnan U., Lowe A., Noznesky E. A., Girard A. W., McFarland D. A., Martorell R. (2012) Opportunities for improving maternal nutrition and birth outcomes: synthesis of country experiences. Food Nutr. Bull. 33(2 Suppl)S104–S137 [PubMed] [Google Scholar]
9. Wouters M. G., Boers G. H., Blom H. J., Trijbels F. J., Thomas C. M., Borm G. F., Steegers-Theunissen R. P., Eskes T. K. (1993) Hyperhomocysteinemia: a risk factor in women with unexplained recurrent early pregnancy loss. Fertil. Steril. 60, 820–825 [PubMed] [Google Scholar]
10. Dekker G. A., de Vries J. I., Doelitzsch P. M., Huijgens P. C., von Blomberg B. M., Jakobs C., van Geijn H. P. (1995) Underlying disorders associated with severe early-onset preeclampsia. Am. J. Obstet. Gynecol. 173, 1042–1048 [PubMed] [Google Scholar]
11. Martínez-Frías M. L., Pérez B., Desviat L. R., Castro M., Leal F., Rodríguez L., Mansilla E., Martínez-Fernández M. L., Bermejo E., Rodríguez-Pinilla E., Prieto D., Ugarte M.; ECEMC Working Group (2006) Maternal polymorphisms 677C-T and 1298A-C of MTHFR, and 66A-G MTRR genes: is there any relationship between polymorphisms of the folate pathway, maternal homocysteine levels, and the risk for having a child with down syndrome? Am. J. Med. Genet. A. 140, 987–997 [PubMed] [Google Scholar]
12. Hibbard B. M., Hibbard E. D., Hwa T. S., Tan P. (1969) Abruptio placentae and defective folate metabolism in Singapore women. J. Obstet. Gynaecol. Br. Commonw. 76, 1003–1007 [PubMed] [Google Scholar]
13. Håberg S. E., London S. J., Stigum H., Nafstad P., Nystad W. (2009) Folic acid supplements in pregnancy and early childhood respiratory health. Arch. Dis. Child. 94, 180–184 [PMC free article] [PubMed] [Google Scholar]
14. Whitrow M. J., Moore V. M., Rumbold A. R., Davies M. J. (2009) Effect of supplemental folic acid in pregnancy on childhood asthma: a prospective birth cohort study. Am. J. Epidemiol. 170, 1486–1493 [PubMed] [Google Scholar]
15. Allis C. D., Jenuwein T., Reinberg D. (2008) Epigenetics, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, USA [Google Scholar]
16. Ferguson-Smith A. C., Greally J. M., Martienssen R. A., eds. (2009) Epigenomics, Springer, New York: [Google Scholar]
17. James S. J., Cutler P., Melnyk S., Jernigan S., Janak L., Gaylor D. W., Neubrander J. A. (2004) Metabolic biomarkers of increased oxidative stress and impaired methylation capacity in children with autism. Am. J. Clin. Nutr. 80, 1611–1617 [PubMed] [Google Scholar]
18. Forman H. J., Zhang H., Rinna A. (2009) Glutathione: overview of its protective roles, measurement, and biosynthesis. Mol. Aspects Med. 30, 1–12 [PMC free article] [PubMed] [Google Scholar]
19. Bailey L. B., Gregory J. F. III (1999) Polymorphisms of methylenetetrahydrofolate reductase and other enzymes: metabolic significance, risks and impact on folate requirement. J. Nutr. 129, 919–922 [PubMed] [Google Scholar]
20. Yamada K., Chen Z., Rozen R., Matthews R. G. (2001) Effects of common polymorphisms on the properties of recombinant human methylenetetrahydrofolate reductase. Proc. Natl. Acad. Sci. USA 98, 14853–14858 [PMC free article] [PubMed] [Google Scholar]
21. Friso S., Choi S. W., Girelli D., Mason J. B., Dolnikowski G. G., Bagley P. J., Olivieri O., Jacques P. F., Rosenberg I. H., Corrocher R., Selhub J. (2002) A common mutation in the 5,10-methylenetetrahydrofolate reductase gene affects genomic DNA methylation through an interaction with folate status. Proc. Natl. Acad. Sci. USA 99, 5606–5611 [PMC free article] [PubMed] [Google Scholar]
22. Stern L. L., Mason J. B., Selhub J., Choi S. W. (2000) Genomic DNA hypomethylation, a characteristic of most cancers, is present in peripheral leukocytes of individuals who are homozygous for the C677T polymorphism in the methylenetetrahydrofolate reductase gene. Cancer Epidemiol. Biomarkers Prev. 9, 849–853 [PubMed] [Google Scholar]
23. Reik W., Dean W., Walter J. (2001) Epigenetic reprogramming in mammalian development. Science 293, 1089–1093 [PubMed] [Google Scholar]
24. Morgan H. D., Santos F., Green K., Dean W., Reik W. (2005) Epigenetic reprogramming in mammals. Hum. Mol. Genet. 14, R47–R58 [PubMed] [Google Scholar]
25. Mabb A. M., Judson M. C., Zylka M. J., Philpot B. D. (2011) Angelman syndrome: insights into genomic imprinting and neurodevelopmental phenotypes. Trends Neurosci. 34, 293–303 [PMC free article] [PubMed] [Google Scholar]
26. Cassidy S. B., Schwartz S., Miller J. L., Driscoll D. J. (2012) Prader-Willi syndrome. Genet. Med. 14, 10–26 [PubMed] [Google Scholar]
27. Azzi S., Abi Habib W., Netchine I. (2014) Beckwith-Wiedemann and Russell-Silver syndromes: from new molecular insights to the comprehension of imprinting regulation. Curr. Opin. Endocrinol. Diabetes Obes. 21, 30–38 [PubMed] [Google Scholar]
28. Badcock C., Crespi B. (2006) Imbalanced genomic imprinting in brain development: an evolutionary basis for the aetiology of autism. J. Evol. Biol. 19, 1007–1032 [PubMed] [Google Scholar]
29. Sullivan M. J., Taniguchi T., Jhee A., Kerr N., Reeve A. E. (1999) Relaxation of IGF2 imprinting in Wilms tumours associated with specific changes in IGF2 methylation. Oncogene 18, 7527–7534 [PubMed] [Google Scholar]
30. Ito Y., Koessler T., Ibrahim A. E., Rai S., Vowler S. L., Abu-Amero S., Silva A. L., Maia A. T., Huddleston J. E., Uribe-Lewis S., Woodfine K., Jagodic M., Nativio R., Dunning A., Moore G., Klenova E., Bingham S., Pharoah P. D., Brenton J. D., Beck S., Sandhu M. S., Murrell A. (2008) Somatically acquired hypomethylation of IGF2 in breast and colorectal cancer. Hum. Mol. Genet. 17, 2633–2643 [PMC free article] [PubMed] [Google Scholar]
31. Kalish J. M., Jiang C., Bartolomei M. S. (2014) Epigenetics and imprinting in human disease. Int. J. Dev. Biol. 58, 291–298 [PubMed] [Google Scholar]
32. Dominguez-Salas P., Cox S. E., Prentice A. M., Hennig B. J., Moore S. E. (2012) Maternal nutritional status, C(1) metabolism and offspring DNA methylation: a review of current evidence in human subjects. Proc. Nutr. Soc. 71, 154–165 [PMC free article] [PubMed] [Google Scholar]
33. Michels K. B., Harris H. R., Barault L. (2011) Birthweight, maternal weight trajectories and global DNA methylation of LINE-1 repetitive elements. PLoS One 6, e25254 [PMC free article] [PubMed] [Google Scholar]
34. Rancourt R. C., Harris H. R., Barault L., Michels K. B. (2013) The prevalence of loss of imprinting of H19 and IGF2 at birth. FASEB J. 27, 3335–3343 [PMC free article] [PubMed] [Google Scholar]
35. Guo L., Choufani S., Ferreira J., Smith A., Chitayat D., Shuman C., Uxa R., Keating S., Kingdom J., Weksberg R. (2008) Altered gene expression and methylation of the human chromosome 11 imprinted region in small for gestational age (SGA) placentae. Dev. Biol. 320, 79–91 [PubMed] [Google Scholar]
36. Krumsiek J., Suhre K., Illig T., Adamski J., Theis F. J. (2011) Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data. BMC Syst. Biol. 5, 21 [PMC free article] [PubMed] [Google Scholar]
37. Olsen I. E., Groveman S. A., Lawson M. L., Clark R. H., Zemel B. S. (2010) New intrauterine growth curves based on United States data. Pediatrics 125, e214–e224 [PubMed] [Google Scholar]
38. US Food and Drug Administration (1996) Food standards: amendment of standards of identity for enriched grain products to require addition of folic acid. Final rule. 21 CFR parts 136, 137, and 139. Fed. Regist. 61, 8781–8797 [Google Scholar]
39. CDC (Centers for Disease Control and Prevention) (1992) Recommendations for the use of folic acid to reduce the number of cases of spina bifida and other neural tube defects. MMWR Morb. Mortal. Wkly. Rep. 41(RR-14), 001 [PubMed] [Google Scholar]
40. Eichholzer M., Tönz O., Zimmermann R. (2006) Folic acid: a public-health challenge. Lancet 367, 1352–1361 [PubMed] [Google Scholar]
41. Jacques P. F., Selhub J., Bostom A. G., Wilson P. W., Rosenberg I. H. (1999) The effect of folic acid fortification on plasma folate and total homocysteine concentrations. N. Engl. J. Med. 340, 1449–1454 [PubMed] [Google Scholar]
42. Pfeiffer C. M., Caudill S. P., Gunter E. W., Osterloh J., Sampson E. J. (2005) Biochemical indicators of B vitamin status in the US population after folic acid fortification: results from the National Health and Nutrition Examination Survey 1999-2000. Am. J. Clin. Nutr. 82, 442–450 [PubMed] [Google Scholar]
43. Crider K. S., Yang T. P., Berry R. J., Bailey L. B. (2012) Folate and DNA methylation: a review of molecular mechanisms and the evidence for folate's role. Adv. Nutr. 3, 21–38 [PMC free article] [PubMed] [Google Scholar]
44. Parle-McDermott A., Ozaki M. (2011) The impact of nutrition on differential methylated regions of the genome. Adv. Nutr. 2, 463–471 [PMC free article] [PubMed] [Google Scholar]
45. Hoyo C., Murtha A. P., Schildkraut J. M., Jirtle R. L., Demark-Wahnefried W., Forman M. R., Iversen E. S., Kurtzberg J., Overcash F., Huang Z., Murphy S. K. (2011) Methylation variation at IGF2 differentially methylated regions and maternal folic acid use before and during pregnancy. Epigenetics 6, 928–936 [PMC free article] [PubMed] [Google Scholar]
46. Haggarty P., Hoad G., Campbell D. M., Horgan G. W., Piyathilake C., McNeill G. (2013) Folate in pregnancy and imprinted gene and repeat element methylation in the offspring. Am. J. Clin. Nutr. 97, 94–99 [PubMed] [Google Scholar]
47. Hoffman D. R., Marion D. W., Cornatzer W. E., Duerre J. A. (1980) S-Adenosylmethionine and S-adenosylhomocystein metabolism in isolated rat liver: effects of l-methionine, l-homocystein, and adenosine. J. Biol. Chem. 255, 10822–10827 [PubMed] [Google Scholar]
48. James S. J., Melnyk S., Pogribna M., Pogribny I. P., Caudill M. A. (2002) Elevation in S-adenosylhomocysteine and DNA hypomethylation: potential epigenetic mechanism for homocysteine-related pathology. J. Nutr. 132(8 Suppl)2361S–2366S [PubMed] [Google Scholar]
49. Yi P., Melnyk S., Pogribna M., Pogribny I. P., Hine R. J., James S. J. (2000) Increase in plasma homocysteine associated with parallel increases in plasma S-adenosylhomocysteine and lymphocyte DNA hypomethylation. J. Biol. Chem. 275, 29318–29323 [PubMed] [Google Scholar]
50. Caudill M. A., Wang J. C., Melnyk S., Pogribny I. P., Jernigan S., Collins M. D., Santos-Guzman J., Swendseid M. E., Cogger E. A., James S. J. (2001) Intracellular S-adenosylhomocysteine concentrations predict global DNA hypomethylation in tissues of methyl-deficient cystathionine beta-synthase heterozygous mice. J. Nutr. 131, 2811–2818 [PubMed] [Google Scholar]
51. Blom H. J., Shaw G. M., den Heijer M., Finnell R. H. (2006) Neural tube defects and folate: case far from closed. Nat. Rev. Neurosci. 7, 724–731 [PMC free article] [PubMed] [Google Scholar]
52. Frost J. M., Monk D., Stojilkovic-Mikic T., Woodfine K., Chitty L. S., Murrell A., Stanier P., Moore G. E. (2010) Evaluation of allelic expression of imprinted genes in adult human blood. PLoS One 5, e13556 [PMC free article] [PubMed] [Google Scholar]
53. Monk D., Arnaud P., Apostolidou S., Hills F. A., Kelsey G., Stanier P., Feil R., Moore G. E. (2006) Limited evolutionary conservation of imprinting in the human placenta. Proc. Natl. Acad. Sci. USA 103, 6623–6628 [PMC free article] [PubMed] [Google Scholar]
54. Ru-Fei G., Xue-Qing L., Ying-Xiong W., Xue-Mei C., Yu-Bin D., Jun-Lin H. (2012) IGF2 expression in blood is not associated with its imprinting status in healthy pregnant Chinese women. Biol. Res. 45, 351–356 [PubMed] [Google Scholar]
55. Wang W. H., Duan J. X., Vu T. H., Hoffman A. R. (1996) Increased expression of the insulin-like growth factor-II gene in Wilms' tumor is not dependent on loss of genomic imprinting or loss of heterozygosity. J. Biol. Chem. 271, 27863–27870 [PubMed] [Google Scholar]
56. Cui H., Horon I. L., Ohlsson R., Hamilton S. R., Feinberg A. P. (1998) Loss of imprinting in normal tissue of colorectal cancer patients with microsatellite instability. Nat. Med. 4, 1276–1280 [PubMed] [Google Scholar]
57. Cui H., Cruz-Correa M., Giardiello F. M., Hutcheon D. F., Kafonek D. R., Brandenburg S., Wu Y., He X., Powe N. R., Feinberg A. P. (2003) Loss of IGF2 imprinting: a potential marker of colorectal cancer risk. Science 299, 1753–1755 [PubMed] [Google Scholar]
58. Michels K. B., Xue F. (2006) Role of birthweight in the etiology of breast cancer. Int. J. Cancer 119, 2007–2025 [PubMed] [Google Scholar]
In Ark if a Baby Is Damaged Does It Lower Imprinting
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