The effects of long-term daily folic acid and vitamin B12 supplementation on genome-wide DNA methylation in elderly subjects
© Kok et al. 2015
Received: 22 July 2015
Accepted: 4 November 2015
Published: 14 November 2015
Folate and its synthetic form folic acid function as donor of one-carbon units and have been, together with other B-vitamins, implicated in programming of epigenetic processes such as DNA methylation during early development. To what extent regulation of DNA methylation can be altered via B-vitamins later in life, and how this relates to health and disease, is not exactly known. The aim of this study was to identify effects of long-term supplementation with folic acid and vitamin B12 on genome-wide DNA methylation in elderly subjects.
This project was part of a randomized, placebo-controlled trial on effects of supplemental intake of folic acid and vitamin B12 on bone fracture incidence (B-vitamins for the PRevention Of Osteoporotic Fractures (B-PROOF) study). Participants with mildly elevated homocysteine levels, aged 65–75 years, were randomly assigned to take 400 μg folic acid and 500 μg vitamin B12 per day or a placebo during an intervention period of 2 years. DNA was isolated from buffy coats, collected before and after intervention, and genome-wide DNA methylation was determined in 87 participants (n = 44 folic acid/vitamin B12, n = 43 placebo) using the Infinium HumanMethylation450 BeadChip.
After intervention with folic acid and vitamin B12, 162 (versus 14 in the placebo group) of the 431,312 positions were differentially methylated as compared to baseline. Comparisons of the DNA methylation changes in the participants receiving folic acid and vitamin B12 versus placebo revealed one single differentially methylated position (cg19380919) with a borderline statistical significance. However, based on the analyses of differentially methylated regions (DMRs) consisting of multiple positions, we identified 6 regions that differed statistically significantly between the intervention and placebo group. Pronounced changes were found for regions in the DIRAS3, ARMC8, and NODAL genes, implicated in carcinogenesis and early embryonic development.
Furthermore, serum levels of folate and vitamin B12 or plasma homocysteine were related to DNA methylation of 173, 425, and 11 regions, respectively. Interestingly, for several members of the developmental HOX genes, DNA methylation was related to serum levels of folate.
Long-term supplementation with folic acid and vitamin B12 in elderly subjects resulted in effects on DNA methylation of several genes, among which genes implicated in developmental processes.
KeywordsDNA methylation Folic acid Vitamin B12 B-vitamins One-carbon metabolism Intervention trial Infinium 450k BeadChip Elderly Cancer Development Epigenetics
During early development, DNA methylation is one of the epigenetic phenomena responsible for programming of gene expression profiles . It has been shown that the plasticity of epigenetic regulation can be determined by environmental factors, such as parental diet and lifestyle, during the critical windows in early development [1–3]. B-vitamins play an essential role in one-carbon metabolism and have, as such, also been implicated in the regulation of DNA methylation and DNA synthesis [1, 4–6].
Recently, neonatal folate-sensitive regions of differential methylation were identified based on the maternal folate status during the last trimester of pregnancy . Maternal use of folic acid before and during pregnancy has been previously associated with specific DNA methylation patterns in the infants [8–10]. Also, maternal vitamin B12 levels have been shown to influence global DNA methylation in cord blood, whereas infants’ levels of vitamin B12 were associated with distinct gene-specific DNA methylation patterns . These findings illustrate and confirm the potential role of B-vitamins on DNA methylation during early development [12, 13].
The “developmental origins of health and disease” hypothesis states that adult diseases often originate from aberrant epigenetic programming during early development [14, 15]. To what extent environmental exposures later in life can induce changes in DNA methylation and how this relates to development of adult diseases is an emerging field of research. Although some studies demonstrate plasticity of DNA methylation in adults [16, 17], it is still largely unknown to what extent B-vitamins involved in one-carbon metabolism can affect DNA methylation throughout the life cycle. Although not consistently, suboptimal levels of B-vitamins and homocysteine, a major key player in one-carbon metabolism, in adult life have been implicated in several clinical phenotypes , such as an increased risk of osteoporosis [19, 20], vascular diseases [21, 22], cognitive impairment , and cancer [24–26]. There is a growing body of evidence that the association between B-vitamins and disease risk implies a narrow range of an optimal B-vitamin status, and depends, in case of cancer, on the presence of preclinical neoplastic lesions [27–30]. Detailed insight into the effects of B-vitamins on DNA methylation is therefore urgently required in order to elucidate the mechanisms underlying the suggested effects of these B-vitamins on health and disease in adult life.
The aim of the current study was to determine the effects of a long-term daily supplementation with folic acid and vitamin B12 on genome-wide DNA methylation in leukocytes of elderly subjects.
Characteristics of the participants at baseline and after 2 years of intervention with either folic acid and vitamin B12 or placebo
Folic acid and vitamin B12 (n = 44)
Placebo (n = 43)
Age at baseline (years)
70.8 ± 2.9
71.1 ± 3.0
25 (57 %)
22 (51 %)
Body mass index (kg/m2)
25 (57 %)
31 (72 %)
19 (43 %)
12 (28 %)
MTHFR C677T genotype (%)b
22 (50 %)
20 (47 %)
22 (50 %)
23 (54 %)
Serum folate levels (nmol/L)
Serum vitamin B12 levels (pmol/L)
Plasma homocysteine levels (μmol/L)
−5.3 (−6.7 to −3.4)
In order to assess whether the mean leukocyte composition changed as a result of the intervention or duration of the study, leukocyte proportions were estimated based on DNA methylation data. The composition of the leukocyte fraction was similar for participants receiving folic acid and vitamin B12 or placebo and for both time points (Additional file 1: Figure S1). The Pearson correlation coefficient for estimated versus measured cell proportions in all follow-up samples (n = 85, 2 missing samples) was 0.66 for monocytes, 0.45 for lymphocytes (CD4+ and CD8+ T-lymphocytes, natural killer cells, and B-lymphocytes), and 0.46 for granulocytes (eosinophils, basophils, and neutrophils). No significant differences in measured or estimated cell proportions between the placebo and intervention group were measured at follow-up.
Differentially methylated positions
Differentially methylated positions that differ between groups
The top-20 of differentially methylated positions representing changes in DNA methylation that differ between participants receiving folic acid and vitamin B12 or placebo
Mean change in methylation (%)
Adjusted p value
Folic acid and vitamin B12
Differentially methylated regions that differ between groups
Differentially methylated regions with DNA methylation changes that differ between participants receiving folic acid and vitamin B12 or placebo
Minimal p value
Mean p value
Maximal difference in methylation change (%)a
Relation with serum or plasma levels of B-vitamins and homocysteine
The current study shows that long-term supplementation with folic acid and vitamin B12 resulted in DNA methylation changes in leukocytes of older persons. We identified several differentially methylated positions as well as regions for which the change in DNA methylation differed between the participants receiving folic acid and vitamin B12 versus placebo. Furthermore, the DNA methylation levels of several genomic loci were found to correlate to serum levels of either folate, vitamin B12, or plasma homocysteine. Most prominent DNA methylation patterns associated with supplemental intake or status of these B-vitamins seemed to be related to developmental processes as well as carcinogenesis.
Based on comparisons between the two groups (folic acid and vitamin B12 versus placebo), DIRAS3 was identified as a gene of interest with a DMR consisting of 11 consecutive positions. DIRAS3, also known as ARHI, is a maternally imprinted member of the ras superfamily and is considered to be a tumor suppressor gene . Downregulation of DIRAS3 expression has been described for several forms of cancer and has been specifically associated with progression and invasive behavior of neoplastic cells [33–35]. To what extent transcriptional downregulation of DIRAS3 occurs via epigenetic mechanisms is not exactly known, although previous work indicated that regulation by miRNAs, chromatin remodeling as well as promoter hypermethylation may be responsible for this effect [35–37].
Another gene identified based on its DMR responsive to the intervention with folic acid and vitamin B12 is the nodal growth differentiation factor (NODAL), a member of the transforming growth factor-β (TGF-beta) superfamily. Like DIRAS3, NODAL has been recognized for its role in cancer progression, with abundant expression of NODAL associated with cellular migration, invasion, and metastatic behavior [38–41].
Noteworthy, NODAL is not only known for its role in cancer progression as it has been originally identified as a morphogen and regulator of mesoderm formation and organization of axial structures during early-stage embryogenesis [42, 43]. Upregulation of NODAL expression as a consequence of tobacco or nicotine exposure in differentiating human embryonic stem cells (hESCs) suggests that the NODAL signaling routes are vulnerable to environmental exposures or stimuli during embryonic development . Interestingly, it has been recently demonstrated that expression of NODAL is regulated via an epigenetic regulatory element for which dynamic changes in DNA methylation were described throughout embryonic development . Although this epigenetic regulatory element was found upstream of the NODAL gene, whereas our small DMR was located in the 3′UTR, these results support our findings that NODAL may be sensitive to endogenous or environmental exposures.
Besides NODAL, also positions or regions within other developmental genes have been identified as potentially responsive to the intervention with folic acid and vitamin B12 or were related to serum folate levels in our study. The homeobox B7 (HOXB7) gene was identified for its relation with serum folate levels of the participants in the current study. HOXB7 is a member of the homeobox family  and occurs in a cluster with other homeobox B genes. For HOXA4, a DMR was related to serum folate levels. The highly conserved HOX genes are considered important transcriptional regulators during embryonic development, where they are mainly responsible for vertebral axial patterning [47, 48].
Epigenetic control of HOX genes in developmental processes related to health and disease has been described previously [47, 49]. Hypomethylation of HOXB7 has been recently recognized as a risk factor for neural tube defects in a case-control study . It is firmly established that periconceptional folic acid supplementation decreases the risk of neural tube defects in the offspring [50, 51]. To what extent HOX or other developmental genes are key targets for the prevention of neural tube defects through folic acid supplementation has not been described extensively so far . The clinical relevance of our findings with respect to mechanisms underlying prevention of neural tube defects, however, is questionable since we found modest increases (~2–5 %) in DNA methylation of the NODAL or HOX genes after supplementation in our elderly population. Case-control studies have previously shown that DNA methylation of several HOX genes differed up to 29 % between children with myelomeningocele (a form of spina bidifa) and healthy controls . To what extent epigenetic control of developmental genes during fetal development  can be translated into an aging population, and vice versa, is not clear. Thus, our careful and explorative hypotheses about the effects of folic acid and vitamin B12 on epigenetic processes in relation to programming of (early) developmental genes warrant further investigation and confirmation in future research with a specific focus on the suggested interaction between genetic, biological, and nutritional factors .
As stated before, aberrant DNA methylation or expression of several HOX genes, NODAL and DIRAS3 have been implicated in the etiology of cancer [54, 55]. Members of the homeobox family as well as NODAL are specifically associated with cancer progression and metastatic behavior [56–59]. Reactivation of embryonic pathways in cancer cells may contribute to uncontrolled differentiation, proliferation, invasion, and metastatic behavior. To what extent the suggested increases in DNA methylation of tumor-related genes such as DIRAS3, NODAL, HOXB7, HOXA4, and other HOX genes may contribute to the pathogenesis of cancer cannot be concluded from the current study. Theoretically, our findings, however, support the hypothesis that folic acid and possibly other B-vitamins specifically increase cancer risk if preclinical neoplastic lesions already exist, pointing toward an effect on progression rather than development of cancer [27, 29]. Our findings may also explain the explorative results of the entire B-vitamins for the PRevention Of Osteoporotic Fractures (B-PROOF) study, where a slightly increased cancer risk was reported after intervention with folic acid and vitamin B12 as compared to the placebo group (hazard ration 1.56; 95 % confidence interval 1.04-2.30) . Taken altogether, our data suggest that supplementation with folic acid and vitamin B12, and consequential changes in serum levels of the corresponding B-vitamins or plasma homocysteine, in older subjects is associated with changes in DNA methylation of several genes implicated in normal developmental processes, which may be reactivated or deregulated during carcinogenesis. It should be noted that the observed effects on DNA methylation were marginal and that biological and functional consequences with respect to gene expression cannot be validated with the current study. On the other hand, previous studies from our groups and others have already shown that nutritional or environmental exposures often result in small, but biologically meaningful, effects on DNA methylation in comparison to the tremendously deviating methylation patterns observed in complex diseases such as cancer [61–63].
Potential limitations of our study include the relatively heterogeneous study population with respect to characteristics that may have occurred or changed during the intervention period, such as changes in dietary habits, use of drugs, and presentation of diseases. It should be noted, however, that these characteristics represent and reflect the general elderly population, which is therefore an advantage with respect to the generalizability of our findings. For disease-related findings, it is questionable whether our results observed in leukocytes also reflect the situation in the tissue of interest, since DNA methylation patterns are highly tissue specific [64–66]. Finally, all participants in our study received 15 μg of vitamin D3 per day in order to ensure a normal vitamin D status. Therefore, we cannot exclude the possibility that some DNA methylation changes may be predominantly attributable to vitamin D rather than folic acid and vitamin B12 . However, since all participants, both from the intervention group and the placebo group, received vitamin D in their study tablets (also containing the placebo or folic acid/vitamin B12), this did not hinder our main analyses dedicated to comparisons between these two groups. Although, the results from our study were fairly consistent with other studies and current insights, strict replication of our findings was not feasible so far given the unique design of our long-term intervention study with folic acid as well as vitamin B12 among elderly subjects.
Strengths of our study include the analyses of genome-wide DNA methylation both before and after long-term supplementation, which allow comparisons within individuals over time. Furthermore, our population consisted of older subjects with mildly elevated homocysteine levels. Elevated homocysteine levels, which are common among elderly subjects in The Netherlands , may point toward inadequate levels or deficiencies of folate and vitamin B12 . Therefore, especially, this population may have benefited from the prolonged supplementation with these B-vitamins and thus enabled detection of changes in DNA methylation patterns.
Long-term supplementation with folic acid and vitamin B12 in elderly subjects with mildly elevated homocysteine levels resulted in changes in DNA methylation of several genes implicated in normal developmental processes and carcinogenesis. These findings may provide unique leads for further research unraveling the mechanisms underlying the effects of B-vitamins on health and disease during the life cycle.
Design and recruitment
The current study was part of a double-blind, randomized, and placebo-controlled trial on the effects of supplemental intake of folic acid and vitamin B12 on fracture incidence (B-PROOF) in The Netherlands [60, 70]. Design of the B-PROOF study and recruitment of the participants have been described in detail previously . Briefly, men and women, aged 65 years and older, with an elevated homocysteine level (12–50 μmol/L) were eligible to participate in this study. Between September 2008 and March 2011, over 69,000 subjects were screened and 2919 participants were finally enrolled in the B-PROOF study (Fig. 1). All participants provided written informed consent and the study protocol was approved by the institutional Medical Ethics Committee. Participants were randomly assigned to take 400 μg folic acid and 500 μg vitamin B12 (Orthica, Almere, The Netherlands) per day or a placebo (Orthica, Almere, The Netherlands) during an intervention period of 2 years. Moreover, all participants received a daily dose of 15 μg vitamin D3, in the same tablet as the placebo or B-vitamins, to ensure a normal vitamin D status.
For the current study, a subgroup of participants was selected from the B-PROOF study cohort. From the 331 participants, who were among the first who completed the intervention period of 2 years, 92 participants were selected for DNA methylation analyses. In order to obtain a relatively homogenous study population, our predefined selection criteria included: age between 65 and 75 years and no reported changes in use of dietary supplements containing folic acid or vitamin B12 during the study. Levels of the C-reactive protein (CRP) at baseline should be ≤10 mg/L, because elevated levels of CRP as a consequence of inflammation may indicate aberrant leukocyte counts. Furthermore, participants who were current smokers, or excessive alcohol users (at least once a week ≥6 glasses of alcohol or 5–7 days/week ≥4 glasses of alcohol)  at baseline were not selected for the current study. All participants had elevated homocysteine levels, which is in line with inclusion criteria of the B-PROOF study. Given the essential role of MTHFR in folate-mediated one-carbon metabolism, the functional C677T single nucleotide polymorphism (SNP) of the MTHFR gene was considered as well for the selection procedure. Participants with the MTHFR (C677T) CC (n = 46) and TT (n = 46) genotypes were equally and exclusively represented in the current study. The MTHFR SNP was determined using the Illumina Omni-express array (Illumina Inc., San Diego, CA, USA).
Sample collection and biochemical analyses
At baseline and after 2 years of intervention, blood samples were collected from all 92 participants. Serum levels of folate and vitamin B12 were determined using electrochemiluminescence immunoassays (Elecsys 2010, Roche, Almere, The Netherlands). Depending on the study center, plasma levels of homocysteine were measured using the Architect i2000 RS analyzer (VU University Medical Center, Amsterdam), HPLC (Wageningen University, Wageningen), or LC-MS/MS method (Erasmus MC, Rotterdam). According to a cross-calibration, outcomes of the three centers did not differ significantly .
Genome-wide DNA methylation analysis
DNA was isolated from buffy coats and 500 ng genomic DNA was bisulfite converted using the EZ DNA Methylation Kit according to the manufacturer instructions (Zymo Research, Freiburg, Germany). Bisulfite converted DNA was used for the genome-wide DNA methylation analyses. Genome-wide DNA methylation was determined in a total of 184 samples from 92 participants using the Infinium HumanMethylation450 BeadChip (Illumina). All samples were processed and analyzed at the Genetic laboratory of Internal Medicine of the Erasmus MC, Rotterdam, The Netherlands. Initial quality control of the samples revealed that one participant had to be excluded because bisulfite conversion for the baseline sample failed. Furthermore, two participants were excluded since their baseline samples showed (1) an average intensity signal in the methylated or unmethylated channel below our predefined threshold of 1966 and (2) a percentage of probes with a call rate <97.5 %. Clustering based on the 65 known SNP probes on the BeadChip as well as multidimensional scaling stratified for gender, revealed two potential sample mix-ups. The corresponding participants of these samples were excluded resulting in samples from 87 participants available for final analysis (Fig. 1).
Raw idat.files were subsequently used for analysis in the R statistical environment (R 3.1.2) through the minfi package (version 1.12.0) available from Bioconductor . Preprocessing of the data included filtering of 65 control probes containing known SNPs and probes annotated to the X and Y chromosome. Probes with a detection p value of >0.01 in at least one sample were filtered, as these probes did not surpass the background signal. Finally, probes containing an SNP (based on the dbSNP version 137)  at the CpG interrogation and/or the single nucleotide extension were excluded, resulting in 431,312 probes included in the analyses (Fig. 1).
Filtered data were normalized using the SWAN normalization procedure  available through the minfi package . The datasets were annotated based on the ilmn12.hg19 annotation . The M-values, which are the log2 ratios of the methylated versus the unmethylated probe intensities, were used for statistical testing as recommended by Du et al. . For visualization purposes, methylation status of the individual probes was expressed as a β-value. These β-values range from 0 or 0 % (fully unmethylated) to 1 or 100 % (fully methylated). Phenotypic data and idat-files from the genome-wide DNA methylation analysis are available through the NCBI’s Gene Expression Omnibus (GEO) repository  with accession number GSE74548.
Differentially methylated positions
Initially, differentially methylated positions, representing changes in DNA methylation over time, were identified in both the placebo as well as the intervention group using a multi-level linear regression analysis within the limma package [78, 79]. For these analyses, subjects were treated as random effects using the “duplicateCorrelation” function in order to conduct the comparisons in a pairwise manner [78, 80].
Differences in changes in DNA methylation between the placebo and intervention group were identified using this multi-level linear regression analysis as well [78, 80]. The contrast ((Placebo_followup-Placebo_baseline)-(Intervention_followup-Intervention_baseline)) allowed the comparison between DNA methylation changes in the two groups.
Besides the comparisons between the two groups, differentially methylated positions were identified as a function of serum folate, vitamin B12, or plasma homocysteine levels using the dmpFinder function for continuous phenotypes (available from the minfi package ). For these analyses, log10-transformed serum levels of folate, vitamin B12 levels, or plasma homocysteine at baseline and after intervention were considered as continuous variables in the linear regression analyses (n = 174).
Differentially methylated regions
Identification of differentially methylated regions (DMRs) was conducted using the DMRcate package available through Bioconductor . DMRs were defined as regions with a maximal distance of 1000 nucleotides between consecutive probes . Identified DMRs consisting of a single probe were excluded for further analyses. Unless otherwise stated, we have taken into account the issue of multiple testing for all analyses by considering p values which are adjusted for the false discovery rate (FDR) by using the Benjamini-Hochberg (BH) procedure .
Samples with a heterogeneous cell population are a major issue for epigenomic analyses, since DNA methylation shows a pronounced cell-type specific pattern . In order to determine whether the leukocyte fractions differed between the groups or baseline and follow-up samples, we predicted the leukocyte composition using the Houseman method [83, 84] implemented in minfi . For a subgroup of participants (n = 85, follow-up samples only), automated cell counts (lymphocytes, monocytes and basophil, eosinophil and neutrophil granulocytes) were available. Pearson correlation coefficients were calculated for the predicted and measured counts of these specific leukocyte fractions. The statistical analyses were adjusted for the different cell fractions by inclusion of predicted percentages of CD4+ and CD8+ T-lymphocytes, B-lymphocytes, natural killer cells, monocytes, and granulocytes as covariates in the linear regression models. Also, the plates used for the bisulfite conversion (four in total) were included as covariates in the models.
Since numerous demographic and biochemical variables were not normally distributed, these data were summarized as median and interquartile ranges (IQR) or numbers and percentages. The Mann-Whitney U test was used to compare characteristics and changes in serum levels of folate, vitamin B12, or plasma homocysteine between the intervention group and the placebo group. The Statistical package for Social Sciences (SPSS version 22) was, unless otherwise stated, used for all the statistical analyses regarding the descriptive and biochemical parameters.
3′ untranslated region
5′ untranslated region
B-vitamins for the prevention of osteoporotic fractures
differentially methylated region
folic acid and vitamin B12
false discovery rate
human embryonic stem cell
high-performance liquid chromatography
liquid chromatography-tandem mass spectrometry
single nucleotide polymorphism
subset-quantile within array normalization
transcription start site
We gratefully acknowledge all participants and research teams of the B-PROOF study. Furthermore, Philip de Groot and Tim Peters are acknowledged for their help and advices with regard to the bioinformatics and statistical analyses. The current project is funded by a grant from the World Cancer Research Fund (WCRF) NL and WCRF International (WCRF 2009/68). The B-PROOF study is supported and funded by The Netherlands Organization for Health Research and Development (ZonMw, Grant 6130.0031), the Hague; unrestricted grant from NZO (Dutch Dairy Association), Zoetermeer; NCHA (Netherlands Consortium Healthy Ageing) Leiden/ Rotterdam; Ministry of Economic Affairs, Agriculture and Innovation (project KB-15-004-003), the Hague; Wageningen University, Wageningen; VU University Medical Center, Amsterdam; Erasmus MC, Rotterdam all in the Netherlands. DK was supported by a research grant (2011-5234) from the Alpe d’Huzes/Dutch Cancer Society. The funding bodies did not have any role in the design or implementation of the study, data collection, data management, data analysis, data interpretation, or in the preparation, review, or submission of this manuscript.
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- Xu J, Sinclair KD. One-carbon metabolism and epigenetic regulation of embryo development. Reproduction, Fertility and Development. 2015. doi:10.1071/RD14377.Google Scholar
- Hanson MA, Gluckman PD. Early developmental conditioning of later health and disease: physiology or pathophysiology? Physiol Rev. 2014;94(4):1027–76. doi:10.1152/physrev.00029.2013.PubMed CentralView ArticlePubMedGoogle Scholar
- Steegers-Theunissen RPM, Twigt J, Pestinger V, Sinclair KD. The periconceptional period, reproduction and long-term health of offspring: the importance of one-carbon metabolism. Hum Reprod Update. 2013;19(6):640–55. doi:10.1093/humupd/dmt041.View ArticlePubMedGoogle Scholar
- Jung A, Kampman E. Nutrition, epigenetics, and cancer: an epidemiological perspective. Nutrition in Epigenetics. Oxford, UK: Wiley-Blackwell; 2011. p. 329–43.
- Liu JJ, Ward RL. Folate and one-carbon metabolism and its impact on aberrant DNA methylation in cancer. Adv Genet. 2010;71:79–121. doi:10.1016/B978-0-12-380864-6.00004-3.View ArticlePubMedGoogle Scholar
- Mandaviya PR, Stolk L, Heil SG. Homocysteine and DNA methylation: a review of animal and human literature. Mol Genet Metab. 2014;113(4):243–52. doi:10.1016/j.ymgme.2014.10.006.View ArticlePubMedGoogle Scholar
- Amarasekera M, Martino D, Ashley S, Harb H, Kesper D, Strickland D et al. Genome-wide DNA methylation profiling identifies a folate-sensitive region of differential methylation upstream of ZFP57-imprinting regulator in humans. FASEB journal:official publication of the Federation of American Societies for Experimental Biology. 2014. doi:10.1096/fj.13-249029.
- Steegers-Theunissen RP, Obermann-Borst SA, Kremer D, Lindemans J, Siebel C, Steegers EA, et al. Periconceptional maternal folic acid use of 400 microg per day is related to increased methylation of the IGF2 gene in the very young child. PLoS One. 2009;4(11):e7845. doi:10.1371/journal.pone.0007845.PubMed CentralView ArticlePubMedGoogle Scholar
- Hoyo C, Murtha AP, Schildkraut JM, Jirtle RL, Demark-Wahnefried W, Forman MR, et al. Methylation variation at IGF2 differentially methylated regions and maternal folic acid use before and during pregnancy. Epigenetics. 2011;6(7):928–36.PubMed CentralView ArticlePubMedGoogle Scholar
- Haggarty P, Hoad G, Campbell DM, Horgan GW, Piyathilake C, McNeill G. Folate in pregnancy and imprinted gene and repeat element methylation in the offspring. Am J Clin Nutr. 2013;97(1):94–9. doi:10.3945/ajcn.112.042572.View ArticlePubMedGoogle Scholar
- McKay JA, Groom A, Potter C, Coneyworth LJ, Ford D, Mathers JC, et al. Genetic and non-genetic influences during pregnancy on infant global and site specific DNA methylation: role for folate gene variants and vitamin B12. PLoS One. 2012;7(3):e33290. doi:10.1371/journal.pone.0033290.PubMed CentralView ArticlePubMedGoogle Scholar
- McKay JA, Mathers JC. Diet induced epigenetic changes and their implications for health. Acta Physiologica. 2011;202(2):103–18. doi:10.1111/j.1748-1716.2011.02278.x.View ArticlePubMedGoogle Scholar
- Vickers MH. Early life nutrition, epigenetics and programming of later life disease. Nutrients. 2014;6(6):2165–78. doi:10.3390/nu6062165.PubMed CentralView ArticlePubMedGoogle Scholar
- Barker DJP. Fetal and infant origins of adult disease. London: British Medical Journal; 1992.Google Scholar
- Barker DJP. Maternal nutrition, fetal nutrition, and disease in later life. Nutrition. 1997;13(9):807–13. doi:10.1016/S0899-9007(97)00193-7.View ArticlePubMedGoogle Scholar
- Jacob RA, Gretz DM, Taylor PC, James SJ, Pogribny IP, Miller BJ, et al. Moderate folate depletion increases plasma homocysteine and decreases lymphocyte DNA methylation in postmenopausal women. J Nutr. 1998;128(7):1204–12.PubMedGoogle Scholar
- Rampersaud GC, Kauwell GP, Hutson AD, Cerda JJ, Bailey LB. Genomic DNA methylation decreases in response to moderate folate depletion in elderly women. Am J Clin Nutr. 2000;72(4):998–1003.PubMedGoogle Scholar
- Lucock M, Yates Z. Folic acid fortification: a double-edged sword. Curr Opin Clin Nutr Metab Care. 2009;12(6):555–64. doi:10.1097/MCO.0b013e32833192bc.View ArticlePubMedGoogle Scholar
- van Wijngaarden JP, Doets EL, Szczecińska A, Souverein OW, Duffy ME, Dullemeijer C, et al. Vitamin B(12), folate, homocysteine, and bone health in adults and elderly people: a systematic review with meta-analyses. J Nutri Metabol. 2013;2013:486186. doi:10.1155/2013/486186.Google Scholar
- McLean RR, Hannan MT. B vitamins, homocysteine, and bone disease: epidemiology and pathophysiology. Curr Osteoporos Rep. 2007;5(3):112–9.View ArticlePubMedGoogle Scholar
- Huo Y, Li J, Qin X, Huang Y, Wang X, Gottesman RF, et al. Efficacy of folic acid therapy in primary prevention of stroke among adults with hypertension in China: the CSPPT randomized clinical trial. JAMA. 2015;313(13):1325–35. doi:10.1001/jama.2015.2274.View ArticlePubMedGoogle Scholar
- Wang X, Qin X, Demirtas H, Li J, Mao G, Huo Y, et al. Efficacy of folic acid supplementation in stroke prevention: a meta-analysis. Lancet. 2007;369(9576):1876–82. doi:10.1016/S0140-6736(07)60854-X.View ArticlePubMedGoogle Scholar
- Durga J, van Boxtel MPJ, Schouten EG, Kok FJ, Jolles J, Katan MB, et al. Effect of 3-year folic acid supplementation on cognitive function in older adults in the FACIT trial: a randomised, double blind, controlled trial. Lancet. 2007;369(9557):208–16. doi:10.1016/S0140-6736(07)60109-3.View ArticlePubMedGoogle Scholar
- Bassett JK, Severi G, Hodge AM, Baglietto L, Hopper JL, English DR, et al. Dietary intake of B vitamins and methionine and colorectal cancer risk. Nutr Cancer. 2013;65(5):659–67. doi:10.1080/01635581.2013.789114.View ArticlePubMedGoogle Scholar
- Kim D-H, Smith-Warner S, Spiegelman D, Yaun S-S, Colditz G, Freudenheim J, et al. Pooled analyses of 13 prospective cohort studies on folate intake and colon cancer. Cancer Causes Control. 2010;21(11):1919–30. doi:10.1007/s10552-010-9620-8.PubMed CentralView ArticlePubMedGoogle Scholar
- Gibson TM, Weinstein SJ, Pfeiffer RM, Hollenbeck AR, Subar AF, Schatzkin A, et al. Pre- and postfortification intake of folate and risk of colorectal cancer in a large prospective cohort study in the United States. Am J Clin Nutr. 2011;94(4):1053–62. doi:10.3945/ajcn.110.002659.PubMed CentralView ArticlePubMedGoogle Scholar
- Ulrich CM, Potter JD. Folate supplementation: too much of a good thing? Cancer Epidemiol Biomarkers Prev. 2006;15(2):189–93. doi:10.1158/1055-9965.epi-06-0054.View ArticlePubMedGoogle Scholar
- Kim YI. Folic acid fortification and supplementation—good for some but not so good for others. Nutr Rev. 2007;65(11):504–11.View ArticlePubMedGoogle Scholar
- van den Donk M, Pellis L, Crott JW, van Engeland M, Friederich P, Nagengast FM, et al. Folic acid and vitamin B-12 supplementation does not favorably influence uracil incorporation and promoter methylation in rectal mucosa DNA of subjects with previous colorectal adenomas. J Nutr. 2007;137(9):2114–20.PubMedGoogle Scholar
- Cole BF, Baron JA, Sandler RS, Haile RW, Ahnen DJ, Bresalier RS, et al. Folic acid for the prevention of colorectal adenomas: a randomized clinical trial. JAMA. 2007;297(21):2351–9. doi:10.1001/jama.297.21.2351.View ArticlePubMedGoogle Scholar
- Rochtus A, Izzi B, Vangeel E, Louwette S, Wittevrongel C, Lambrechts D et al. DNA methylation analysis of homeobox genes implicates HOXB7 hypomethylation as risk factor for neural tube defects. Epigenetics : official journal of the DNA Methylation Society. 2015:1–10. doi:10.1080/15592294.2014.998531.
- Yu Y, Xu F, Peng H, Fang X, Zhao S, Li Y, et al. NOEY2 (ARHI), an imprinted putative tumor suppressor gene in ovarian and breast carcinomas. Proc Natl Acad Sci. 1999;96(1):214–9. doi:10.1073/pnas.96.1.214.PubMed CentralView ArticlePubMedGoogle Scholar
- Wang L, Hoque A, Luo RZ, Yuan J, Lu Z, Nishimoto A, et al. Loss of the expression of the tumor suppressor gene ARHI is associated with progression of breast cancer. Clin Cancer Res. 2003;9(10 Pt 1):3660–6.PubMedGoogle Scholar
- Chen J, Shi S, Yang W, Chen C. Over-expression of ARHI decreases tumor growth, migration, and invasion in human glioma. 2014;31(3):1–10. doi:10.1007/s12032-014-0846-2.
- Li Y, Liu M, Zhang Y, Han C, You J, Yang J et al. Effects of ARHI on breast cancer cell biological behavior regulated by microRNA-221. 2013;34(6):3545–54. doi:10.1007/s13277-013-0933-6.
- Yuan J, Luo RZ, Fujii S, Wang L, Hu W, Andreeff M, et al. Aberrant methylation and silencing of ARHI, an imprinted tumor suppressor gene in which the function is lost in breast cancers. Cancer Res. 2003;63(14):4174–80.PubMedGoogle Scholar
- Yu Y, Fujii S, Yuan J, Luo RZ, Wang LIN, Bao J, et al. Epigenetic regulation of ARHI in breast and ovarian cancer cells. Ann N Y Acad Sci. 2003;983(1):268–77. doi:10.1111/j.1749-6632.2003.tb05981.x.View ArticlePubMedGoogle Scholar
- Quail DF, Zhang G, Walsh LA, Siegers GM, Dieters-Castator DZ, Findlay SD, et al. Embryonic morphogen nodal promotes breast cancer growth and progression. PLoS One. 2012;7(11):e48237. doi:10.1371/journal.pone.0048237.PubMed CentralView ArticlePubMedGoogle Scholar
- Strizzi L, Hardy KM, Margaryan NV, Hillman DW, Seftor EA, Chen B, et al. Potential for the embryonic morphogen nodal as a prognostic and predictive biomarker in breast cancer. Breast Cancer Res. 2012;14(3):R75. doi:10.1186/bcr3185.PubMed CentralView ArticlePubMedGoogle Scholar
- Chen J, Liu WB, Jia WD, Xu GL, Ma JL, Ren Y, et al. Embryonic morphogen nodal is associated with progression and poor prognosis of hepatocellular carcinoma. PLoS One. 2014;9(1):e85840. doi:10.1371/journal.pone.0085840.PubMed CentralView ArticlePubMedGoogle Scholar
- Lee CC, Jan HJ, Lai JH, Ma HI, Hueng DY, Lee YC, et al. Nodal promotes growth and invasion in human gliomas. Oncogene. 2010;29(21):3110–23. doi:10.1038/onc.2010.55.View ArticlePubMedGoogle Scholar
- Schier AF, Shen MM. Nodal signalling in vertebrate development. Nature. 2000;403(6768):385–9.View ArticlePubMedGoogle Scholar
- Schier AF. Nodal morphogens. Cold Spring Harb Perspect Biol. 2009;1(5):a003459. doi:10.1101/cshperspect.a003459.PubMed CentralView ArticlePubMedGoogle Scholar
- Liszewski W, Ritner C, Aurigui J, Wong SSY, Hussain N, Krueger W, et al. Developmental effects of tobacco smoke exposure during human embryonic stem cell differentiation are mediated through the transforming growth factor-β superfamily member, nodal. Differentiation. 2012;83(4):169–78. doi:10.1016/j.diff.2011.12.005.PubMed CentralView ArticlePubMedGoogle Scholar
- Arai D, Hayakawa K, Ohgane J, Hirosawa M, Nakao Y, Tanaka S, et al. An epigenetic regulatory element of the nodal gene in the mouse and human genomes. Mech Dev. 2015;136(0):143–54. doi:10.1016/j.mod.2014.12.003.View ArticlePubMedGoogle Scholar
- Holland PWH, Booth HAF, Bruford EA. Classification and nomenclature of all human homeobox genes. BMC Biol. 2007;5:47. doi:10.1186/1741-7007-5-47.PubMed CentralView ArticlePubMedGoogle Scholar
- Barber BA, Rastegar M. Epigenetic control of Hox genes during neurogenesis, development, and disease. Ann Anat. 2010;192(5):261–74. doi:10.1016/j.aanat.2010.07.009.View ArticlePubMedGoogle Scholar
- Wellik DM. Hox genes and vertebrate axial pattern. Curr Top Dev Biol. 2009;88:257-78. doi: 10.1016/S0070-2153(09)88009-5.View ArticlePubMedGoogle Scholar
- Soshnikova N, Duboule D. Epigenetic temporal control of mouse Hox genes in vivo. Science. 2009;324(5932):1320–3. doi:10.1126/science.1171468.View ArticlePubMedGoogle Scholar
- Czeizel AE, Dudas I, Metneki J. Pregnancy outcomes in a randomised controlled trial of periconceptional multivitamin supplementation. Final report. Arch Gynecol Obstet. 1994;255(3):131–9.View ArticlePubMedGoogle Scholar
- Wolff T, Witkop CT, Miller T, Syed SB. Folic acid supplementation for the prevention of neural tube defects: an update of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med. 2009;150(9):632–9.View ArticlePubMedGoogle Scholar
- Kappen C, Mello MA, Finnell RH, Salbaum JM. Folate modulates Hox gene controlled skeletal phenotypes. Genesis. 2004;39(3):155–66. doi:10.1002/gene.20036.PubMed CentralView ArticlePubMedGoogle Scholar
- Imbard A, Benoist J-F, Blom HJ. Neural tube defects, folic acid and methylation. Int J Environ Res Public Health. 2013;10(9):4352–89. doi:10.3390/ijerph10094352.PubMed CentralView ArticlePubMedGoogle Scholar
- Shah N, Sukumar S. The Hox genes and their roles in oncogenesis. Nat Rev Cancer. 2010;10(5):361–71. doi:10.1038/nrc2826.View ArticlePubMedGoogle Scholar
- Abate-Shen C. Deregulated homeobox gene expression in cancer: cause or consequence?. Nat Rev Cancer. 2002;2(10):777–85.View ArticlePubMedGoogle Scholar
- Liu S, Jin K, Hui Y, Fu J, Jie C, Feng S et al. HOXB7 Promotes malignant progression by activating the TGFβ signaling pathway. Cancer research. 2014. doi:10.1158/0008-5472.can-14-3100.
- Wu X, Chen H, Parker B, Rubin E, Zhu T, Lee JS, et al. HOXB7, a homeodomain protein, is overexpressed in breast cancer and confers epithelial-mesenchymal transition. Cancer Res. 2006;66(19):9527–34. doi:10.1158/0008-5472.can-05-4470.View ArticlePubMedGoogle Scholar
- Kovochich AN, Arensman M, Lay AR, Rao NP, Donahue T, Li X et al. HOXB7 promotes invasion and predicts survival in pancreatic adenocarcinoma. Cancer. 2013;119(3):10.1002/cncr.27725. doi:10.1002/cncr.27725.
- Yuan H, Kajiyama H, Ito S, Yoshikawa N, Hyodo T, Asano E, et al. ALX1 induces snail expression to promote epithelial-to-mesenchymal transition and invasion of ovarian cancer cells. Cancer Res. 2013;73(5):1581–90. doi:10.1158/0008-5472.can-12-2377.View ArticlePubMedGoogle Scholar
- van Wijngaarden JP, Swart KM, Enneman AW, Dhonukshe-Rutten RA, van Dijk SC, Ham AC, et al. Effect of daily vitamin B-12 and folic acid supplementation on fracture incidence in elderly individuals with an elevated plasma homocysteine concentration: B-PROOF, a randomized controlled trial. Am J Clin Nutr. 2014;100(6):1578–86. doi:10.3945/ajcn.114.090043.View ArticlePubMedGoogle Scholar
- Ronn T, Volkov P, Davegardh C, Dayeh T, Hall E, Olsson AH, et al. A six months exercise intervention influences the genome-wide DNA methylation pattern in human adipose tissue. PLoS Genet. 2013;9(6):e1003572. doi:10.1371/journal.pgen.1003572.PubMed CentralView ArticlePubMedGoogle Scholar
- Jacobsen SC, Brøns C, Bork-Jensen J, Ribel-Madsen R, Yang B, Lara E, et al. Effects of short-term high-fat overfeeding on genome-wide DNA methylation in the skeletal muscle of healthy young men. Diabetologia. 2012;55(12):3341–9. doi:10.1007/s00125-012-2717-8.View ArticlePubMedGoogle Scholar
- Kupers LK, Xu X, Jankipersadsing SA, Vaez A, la Bastide-van Gemert S, Scholtens S et al. DNA methylation mediates the effect of maternal smoking during pregnancy on birthweight of the offspring. International journal of epidemiology. 2015. doi:10.1093/ije/dyv048.
- Slieker RC, Bos SD, Goeman JJ, Bovée JVMG, Talens RP, van der Breggen R, et al. Identification and systematic annotation of tissue-specific differentially methylated regions using the Illumina 450k array. Epigenetics Chromatin. 2013;6:26. doi:10.1186/1756-8935-6-26.PubMed CentralView ArticlePubMedGoogle Scholar
- Jaffe AE, Irizarry RA. Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biol. 2014;15(2):R31-R. doi:10.1186/gb-2014-15-2-r31.View ArticleGoogle Scholar
- Montano C, Irizarry R, Kaufmann W, Talbot K, Gur R, Feinberg A, et al. Measuring cell-type specific differential methylation in human brain tissue. Genome Biol. 2013;14(8):R94.PubMed CentralView ArticlePubMedGoogle Scholar
- Fetahu IS, Höbaus J, Kállay E. Vitamin D and the epigenome. Front Physiol. 2014;5:164. doi:10.3389/fphys.2014.00164.PubMed CentralView ArticlePubMedGoogle Scholar
- de Bree A, van der Put NMJ, Mennen LI, Verschuren WMM, Blom HJ, Galan P et al. Prevalences of hyperhomocysteinemia, unfavorable cholesterol profile and hypertension in European populations. Eur J Clin Nutr. 2005;59(4):480–8.View ArticlePubMedGoogle Scholar
- Refsum H, Smith AD, Ueland PM, Nexo E, Clarke R, McPartlin J, et al. Facts and recommendations about total homocysteine determinations: an expert opinion. Clin Chem. 2004;50(1):3–32. doi:10.1373/clinchem.2003.021634.View ArticlePubMedGoogle Scholar
- van Wijngaarden JP, Dhonukshe-Rutten RA, van Schoor NM, van der Velde N, Swart KM, Enneman AW, et al. Rationale and design of the B-PROOF study, a randomized controlled trial on the effect of supplemental intake of vitamin B12 and folic acid on fracture incidence. BMC Geriatr. 2011;11:80. doi:10.1186/1471-2318-11-80.PubMed CentralView ArticlePubMedGoogle Scholar
- Garretsen HFL. Probleemdrinken: Prevalentiebepaling, beinvloedende factoren en preventiemogelijkheden: Theoretische overwegingen en onderzoek in Rotterdam (thesis in Dutch, with summary in English). 1983.Google Scholar
- Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, et al. Minfi: a flexible and comprehensive bioconductor package for the analysis of infinium DNA methylation microarrays. Bioinformatics. 2014;30(10):1363–9. doi:10.1093/bioinformatics/btu049.PubMed CentralView ArticlePubMedGoogle Scholar
- Sherry ST, Ward M-H, Kholodov M, Baker J, Phan L, Smigielski EM, et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001;29(1):308–11. doi:10.1093/nar/29.1.308.PubMed CentralView ArticlePubMedGoogle Scholar
- Maksimovic J, Gordon L, Oshlack A. SWAN: subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips. Genome Biol. 2012;13(6):R44. doi:10.1186/gb-2012-13-6-r44.PubMed CentralView ArticlePubMedGoogle Scholar
- Hansen KD. IlluminaHumanMethylation450kanno.ilmn12.hg19: annotation for illumina’s 450k methylation arrays. R package version 0.2.1.
- Du P, Zhang X, Huang CC, Jafari N, Kibbe WA, Hou L, et al. Comparison of beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinform. 2010;11:587. doi:10.1186/1471-2105-11-587.View ArticleGoogle Scholar
- Edgar R, Domrachev M, Lash AE. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002;30(1):207–10. doi:10.1093/nar/30.1.207.PubMed CentralView ArticlePubMedGoogle Scholar
- Smyth GK. Limma: linear models for microarray data. In: Gentleman R, Carey V, Dudoit S, Irizarry R, Huber W, editors. Bioinformatics and computational biology solutions using R and bioconductor. New York: Springer; 2005. p. 397–420.View ArticleGoogle Scholar
- Smyth GK. Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. 2004. Statistical Applications in Genetics and Molecular Biology, Vol. 3, No. 1, Article 3.Google Scholar
- Smyth GK, Michaud J, Scott HS. Use of within-array replicate spots for assessing differential expression in microarray experiments. Bioinformatics. 2005;21(9):2067–75. doi:10.1093/bioinformatics/bti270.View ArticlePubMedGoogle Scholar
- Peters T, Buckley M, Statham A, Pidsley R, Samaras K, Lord R, et al. De novo identification of differentially methylated regions in the human genome. Epigenetics Chromatin. 2015;8(1):6.PubMed CentralPubMedGoogle Scholar
- Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Royal Stat Soc Series B. 1995;57(1):289–300. doi:10.2307/2346101.Google Scholar
- Houseman E, Accomando W, Koestler D, Christensen B, Marsit C, Nelson H, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinform. 2012;13(1):86.View ArticleGoogle Scholar
- Koestler DC, Christensen BC, Karagas MR, Marsit CJ, Langevin SM, Kelsey KT, et al. Blood-based profiles of DNA methylation predict the underlying distribution of cell types. Epigenetics. 2013;8(8):816–26. doi:10.4161/epi.25430.PubMed CentralView ArticlePubMedGoogle Scholar