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Effects of dietary interventions on DNA methylation in adult humans: systematic review and meta-analysis

Published online by Cambridge University Press:  24 October 2018

Khalil ElGendy*
Affiliation:
Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne NE2 4HH, UK Surgery Department, Northumbria NHS Foundation Trust, Cramlington NE23 6NZ, UK
Fiona C. Malcomson
Affiliation:
Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
Jose G. Lara
Affiliation:
Applied Sciences Department, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
David Michael Bradburn
Affiliation:
Surgery Department, Northumbria NHS Foundation Trust, Cramlington NE23 6NZ, UK
John C. Mathers
Affiliation:
Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
*
*Corresponding author: K. ElGendy, email Khalil.elgendy@ncl.ac.uk
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Abstract

DNA methylation is a key component of the epigenetic machinery that is responsible for regulating gene expression and, therefore, cell function. Patterns of DNA methylation change during development and ageing, differ between cell types, are altered in multiple diseases and can be modulated by dietary factors. However, evidence about the effects of dietary factors on DNA methylation patterns in humans is fragmentary. This study was initiated to collate evidence for causal links between dietary factors and changes in DNA methylation patterns. We carried out a systematic review of dietary intervention studies in adult humans using Medline, EMBASE and Scopus. Out of 22 149 screened titles, sixty intervention studies were included, of which 65% were randomised (n 39). Most studies (53%) reported data from blood analyses, whereas 27% studied DNA methylation in colorectal mucosal biopsies. Folic acid was the most common intervention agent (33%). There was great heterogeneity in the methods used for assessing DNA methylation and in the genomic loci investigated. Meta-analysis of the effect of folic acid on global DNA methylation revealed strong evidence that supplementation caused hypermethylation in colorectal mucosa (P=0·009). Meta-regression analysis showed that the dose of supplementary folic acid was the only identified factor (P<0·001) showing a positive relationship. In summary, there is limited evidence from intervention studies of effects of dietary factors, other than folic acid, on DNA methylation patterns in humans. In addition, the application of multiple different assays and investigations of different genomic loci makes it difficult to compare, or to combine, data across studies.

Type
Review-Systematic with Meta-Analysis
Copyright
© The Authors 2018 

In humans, DNA is methylated by the addition of a methyl group to the 5′ position on cytosine (C) residues where the C is followed by a guanine (G) residue – that is, a CpG dinucleotide. This methylation is catalysed by DNA methyl transferase using S-adenosyl methionine (SAM) as the methyl donor. DNA methylation is a component of a suite of epigenetic marks and molecules, which also includes post-translational modification of histones and small non-coding RNA. These epigenetic mechanisms are functionally important because they are key players in the regulation of gene expression( Reference Mathers, Strathdee and Relton 1 ).

Patterns of DNA methylation change during development and ageing, differ between cell types and are altered in multiple diseases including cardiovascular and neoplastic diseases and neurological disorders( Reference Kandi and Vadakedath 2 ). Altered DNA methylation is an early and consistent event in the development of cancer, including colorectal cancer (CRC)( Reference Sakai, Nakajima and Kaneda 3 ), where it plays a causal role through silencing of tumour suppressor genes and activation of oncogenes. Aberrant DNA methylation patterns result in reduced DNA integrity and stability, development of mutations, changes in gene expression and chromosomal modifications( Reference Kim, Golub and Park 4 ). DNA methylation, measured in target or surrogate tissues, has been developed as a diagnostic, prognostic or predictive biomarker for several diseases( Reference Chen, Gaudino and Pass 5 Reference Levenson 7 ). However, DNA methylation patterns differ between cell and tissue types and may respond differently to interventions( Reference McKay, Xie and Harris 8 ) so that DNA methylation assayed in a surrogate tissue may not be reflective of the target tissue.

Patterns of DNA methylation respond to many environmental exposures and lifestyle factors including diet( Reference Mathers, Strathdee and Relton 1 , Reference Patai, Molnár and Kalmár 9 ). Nutritional factors can affect DNA methylation by modifying the activity of enzymes involved in DNA methylation such as DNA methyltransferase or by changing the availability of methyl donors for SAM synthesis( Reference McKay and Mathers 10 ). Experimental studies using tissue culture and animal models have demonstrated effects of multiple dietary factors including polyphenols, flavonoids and phyto-oestrogens on DNA methylation( Reference Vanden Berghe 11 ), some of which have also been reported in observational studies in humans. However, folic acid supplementation remains the most widely studied nutritional factor affecting DNA methylation( Reference Lim and Song 12 , Reference Lamprecht and Lipkin 13 ). Most of the evidence of effects of dietary factors on DNA methylation in humans comes from cross-sectional observational studies and there appear to be few relevant intervention studies( Reference Lim and Song 12 ).

The aim of this study was to undertake a systematic review of intervention studies in adult humans that involved diet or dietary factors and which reported DNA methylation as an outcome to (i) synthesise the evidence for causal links between specific dietary factors and corresponding changes in DNA methylation and (ii) ascertain the utility of easier-to-collect surrogate samples for investigating effects of dietary factors on DNA methylation in target tissues. To our knowledge, no prior systematic review has addressed these questions.

Methods

The systematic review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist and flow chart( Reference Moher, Liberati and Tetzlaff 14 ) and was registered with the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42017072315).

Search strategy and screening

A total of three databases were searched (Embase, Scopus and Medline) from inception until April 2017 by using the following search terms: ((methylation [Mesh] OR dna methylation [Mesh] OR methylat*) AND ((Supplement OR supplement* OR dietary supplements [Mesh]) OR (trial* OR clinical trial [Mesh]) OR (Intervention OR intervention*))).

Articles were screened against the following pre-specified inclusion criteria – (1) study design: any intervention study, randomised or non-randomised; (2) participants: adult human beings (≥16 years old); (3) intervention: dietary interventions (single, multiple or combined with other modalities – e.g. physical activity) and (4) outcome: DNA methylation measured using any methodology as an outcome (primary or secondary) assessed before and after the intervention. Where DNA methylation was assessed after the intervention only, randomised controlled trials (RCT) only were included in the review. Where DNA methylation was assessed before intervention only, studies were excluded.

Studies that recruited patients undergoing active treatment of cancer including chemotherapy or/and radiotherapy were excluded because of the likelihood that such therapies would confound the dietary effects. In studies involving pregnant women, the study was included if the outcome was assessed in tissue samples from the pregnant woman, but not if the measurements were made in the offspring or products of conception – for example, cord blood or placenta.

Titles and abstracts were screened independently by two independent investigators (K. E. and F. C. M.). This was followed by accessing full texts to ensure meeting inclusion and exclusion criteria. Any discrepancy regarding the decision to include a study was resolved by a third reviewer (J. C. M.).

Data extraction and quality assessment

The following data were collected using a pre-tested standard form: year of publication, study design, health or disease status of participants, number of participants, nature of dietary intervention, intervention duration, sample site, DNA methylation assessment method (including genomic loci, where appropriate), DNA methylation levels of participants before and after intervention with measures of variance and level of significance. These data were uploaded into Microsoft® Excel 2013 and used to compile a narrative synthesis of the results that is reported below using descriptive statistics (e.g. percentages) and summary tables.

Meta-analysis and meta-regression

Eligible studies were included in a meta-analysis conducted using the Review Manager software (version 5.3, the Cochrane Collaboration, 2014) and intervention effects were quantified using a random-effects model (owing to heterogeneity) and standardised mean difference (owing to different methods used to quantify DNA methylation). In addition, risk of bias was assessed using the Cochrane Collaboration’s Risk of Bias tool. Heterogeneity between studies was assessed using χ 2 statistic (expressed as P value) and I 2 statistics (expressed as percentage) using Review Manager version 5.3.

Results of meta-analysis of different techniques for quantification of global DNA methylation (direct v. indirect measurement and different direction of effects) were examined using comprehensive meta-analysis (CMA) software (version 2; Biostat) using a random-effects model (owing to heterogeneity) and standardised mean difference. The CMA software was also used to carry out meta-regression analysis using a mixed-effect model, and publication bias was examined via funnel plots and Egger’s regression test (expressed as P value).

Results

The PRISMA flow chart (online Supplementary Fig. S1) summarises the outcomes of the search strategy. Out of 22 149 titles, sixty intervention studies were included, of which thirty-nine studies (65%) were RCT and seven (12%) were cross-over RCT. The number of participants recruited per study ranged from 7 to 388, with a median value of 34.

Across sixty trials, twenty-two different dietary interventions were applied. The most common intervention agent was folic acid, which was tested in one-third of the studies (n 20, 33%) followed by a low-energy diet (n 5, 8%) and multi-vitamin supplements (n 5, 8%) (online Supplementary Fig. S2). One-third of the studies (twenty trials) recruited healthy individuals, whereas participants with sixteen disease conditions or risk factors were studied in the remaining forty papers. Studies on patients with colorectal disease (n 13) represented 22% of the total, whereas seven studies (11%) recruited obese and/or overweight patients (online Supplementary Fig. S3).

A wide range of DNA methylation assessment methods (thirty in total; see online Supplementary Table S2) were used, and only ten studies (17%) reported outcomes from a combination of types of DNA methylation assessment (online Supplementary Table S1). Global DNA methylation was investigated in more than half of the trials (n 31, 52%) and was the sole DNA methylation measurement in twenty-six studies (43%). The most common techniques were the [3H]-methyl acceptance assay (n 9, 15%) for estimation of global DNA methylation and Sequenom’s MassARRAY EpiTyper (n 7, 12%) for methylation at specific genomic loci. Bisulphite sequencing, using ten different techniques, was applied in more than one-third of the trials (n 21, 35%) (online Supplementary Table S3).

Methylation in DNA extracted from six different tissues was studied (online Supplementary Fig. S4). Blood samples were used in more than half of the trials (n 32, 53%), with leucocytes being the most common cell fraction studied (n 12, 20%). Methylation in DNA from colorectal mucosal biopsies was reported in sixteen studies (27%). Other tissues included adipose tissue, muscle, semen and mammary tissue. In the text below, the results of the intervention studies have been categorised according to the tissue/sample site and dietary intervention.

Effects of dietary intervention on DNA methylation in blood

Of the thirty-two trials that reported data from blood samples, seventeen were RCT with one cross-over RCT. In all, eight studies used folic acid as the intervention agent (Table 1)( Reference Jacob, Gretz and Taylor 15 Reference Martín-Núñez, Cabrera-Mulero and Rubio-Martín 22 ), whereas seven trials involved weight-loss interventions (Table 2)( Reference Milagro, Campión and Cordero 23 Reference Duggan, Xiao and Terry 29 ). Other studies are summarised in Table 3 ( Reference Kok, Dhonukshe-Rutten and Lute 30 Reference Pusceddu, Herrmann and Kirsch 46 ).

Table 1 Effects of folic acid supplementation on DNA methylation in different blood samples

RCT, randomised controlled trial; ↓, decrease; PBMC, peripheral blood mononuclear cells; ↑, increase; MTHFR, methylenetetrahydrofolate reductase.

Table 2 Effects of weight-loss nutritional interventions on DNA methylation in different blood products*

RCT, randomised controlled trial; NA, not available; PBMC, peripheral blood mononuclear cells; ↑, increase; CpG, cytosine-phosphate-guanosine; ↓, decrease; RESMENA, MEtabolic Syndrome REduction in Navarra; LUMA, luminometric methylation assay.

* For full names of each of the genes listed in this table by their ID, please see Supplementary Table S4.

Table 3 Effects of different dietary interventions (other than folic acid and weight-loss interventions) on DNA methylation in different blood products*

RCT, randomised controlled trial; ↑, increase; TDS, ter die sumendum (three times per d); ↓, decrease; MTHFR, methylenetetrahydrofolate reductase; HTN, hypertension; F/V, fruits/vegetables; MedDiet, Mediterranean diet; EVOO, extra-virgin olive oil; PBC, peripheral blood cells; PBMC, peripheral blood mononuclear cells; LCPUFA, long-chain PUFA; DM, diabetes mellitus; IFG, impaired fasting glucose; NA, not available.

* For full names of each of the genes listed in this table by their ID, please see Supplementary Table S4.

Folic acid supplementation

Jacob et al. ( Reference Jacob, Gretz and Taylor 15 ) and Rampersaud et al. ( Reference Rampersaud, Kauwell and Hutson 16 ) quantified global DNA methylation in postmenopausal females, and reported decreased methylation in response to folate depletion. Following folic acid supplementation, that change was revered in the study by Jacob et al. ( Reference Jacob, Gretz and Taylor 15 ), but not in the study by Rampersaud et al. ( Reference Rampersaud, Kauwell and Hutson 16 ), who found no significant change after repletion in a study with greater power.

In male patients with hyperhomocysteinaemia, Ingrosso et al. ( Reference Ingrosso, Cimmino and Perna 17 ) conducted a non-randomised folic acid supplementation study and observed significantly increased global DNA methylation, whereas Pizzolo et al. ( Reference Pizzolo, Blom and Choi 18 ) reported no significant change after folic acid supplements in a non-RCT. Similarly, in an RCT involving 216 patients with hyperhomocysteinaemia, Jung et al. ( Reference Jung, Smulders and Verhoef 22 ) found no effect of folic acid supplementation over 3 years on global DNA methylation in leucocytes. This lack of effect of folic acid supplementation on global DNA methylation was also observed in RCT involving healthy volunteers( Reference Basten, Duthie and Pirie 20 ) and women of reproductive age( Reference Crider, Yang and Berry 21 ).

The combination of folic acid with other nutrients involved in one-carbon metabolism including methionine( Reference van der Kooi, de Greef and Wohlgemuth 31 ), choline and betaine( Reference Abratte, Wang and Li 39 ) and vitamin B12 ( Reference Stopper, Treutlein and Bahner 44 ) did not modify methylation at specific genomic loci (Table 3). An exception was Kok et al. ( Reference Kok, Dhonukshe-Rutten and Lute 30 ) who investigated effects of folic acid (0·4 mg/d) and vitamin B12 (0·5 mg/d) and demonstrated significant changes in DNA methylation at many CpG sites in or close to DIRAS3, ARMC8 and NODAL genes. (For full names of each of the genes listed in this paper by their ID, please see Supplementary Table S4.)

Weight-loss nutritional intervention

Nicoletti et al. ( Reference Nicoletti, Cortes-Oliveira and Pinhel 25 ) compared the effects of reduced dietary energy intake and bariatric surgery on DNA methylation in buffy coat samples from obese patients in a non-randomised study. Compared with baseline, methylation of IL-6 increased in those exposed to dietary energy restriction and decreased in the bariatric surgery group. However, there was no effect of either intervention on global DNA methylation (assessed as methylation of the repeated element LINE1). Duggan et al. ( Reference Duggan, Xiao and Terry 29 ) did not detect any significant changes in LINE1 methylation in leucocytes from 298 postmenopausal obese females after 1 year of exposure to an energy-restricted diet, exercise or both. Delgado-Cruzata et al. ( Reference Delgado-Cruzata, Zhang and McDonald 28 ) reported that LINE1 methylation increased after 6 months of a weight-loss programme involving both diet and exercise in twenty-four breast cancer survivors, whereas, in contrast, Martín-Núñez et al.( Reference Martín-Núñez, Cabrera-Mulero and Rubio-Martín 26 ) found significantly lower LINE1 methylation in 310 participants after 9 months of intervention with a combination of Mediterranean diet, physical activity and education aiming at weight loss.

Effects of dietary intervention on DNA methylation in the colorectal mucosa

Methylation of DNA extracted from colorectal mucosal biopsies was investigated in sixteen studies, most of which (n 14) were RCT. The large majority (n 11) involved patients with colorectal adenomas, whereas only three studies recruited healthy participants. Other disease conditions included familial adenomatous polyposis and ulcerative colitis (one trial each). Folic acid was the intervention agent in ten trials (Table 4), whereas other intervention studies investigated effects of black raspberries, vegetables, non-digestible carbohydrates, Bifidobacterium lactis, high-amylose maize starch and combined folic acid and vitamin B12 (Table 5).

Table 4 Effects of folic acid supplementation on DNA methylation in colorectal mucosa*

RCT, randomised controlled trial; FA, folic acid; ↑, increase; UC, ulcerative colitis; ERa, oestrogen receptor α.

* For full names of each of the genes listed in this table by their ID, please see Supplementary Table S4.

Table 5 Effects of different dietary supplementation (other than folic acid) on DNA methylation in colorectal mucosa*

RCT, randomised controlled trial; MTHFR, methylenetetrahydrofolate reductase; ↑, increase; NA, not available; UVI, UV imager; CRC, colorectal cancer; ↓, decrease; FAP, familial adenomatous polyposis; MDBC-seq, methyl-CpG binding domain-based capture and sequencing; RS, resistant starch.

* For full names of each of the genes listed in this table by their ID, please see Supplementary Table S4.

Effects of folic acid on DNA methylation status in colorectal biopsies differed between studies. In all, eight trials studied effects on global methylation. Figueiredo et al. ( Reference Figueiredo, Grau and Wallace 52 ) randomised 388 patients with adenoma to a folic acid supplement or a placebo and reported no effect on global DNA methylation. That finding was supported by results from another RCT( Reference Cravo, Glória and Salazar de Sousa 48 ) and from a non-RCT( Reference Protiva, Mason and Liu 53 ). However, five RCT found increased global DNA methylation in adenoma patients following folic acid supplementation. Wallace et al. ( Reference Wallace, Grau and Levine 54 ) and Al-Ghnaniem Abbadi et al. ( Reference Al-Ghnaniem Abbadi, Emery and Pufulete 55 ) found no effect of folic acid on DNA methylation of SFRP1, ESR1 or MLH1 in patients with adenoma. Findings from meta-analysis and meta-regression of the available evidence for the effects of folic acid supplementation on global DNA methylation are presented later in this article.

Wang et al. ( Reference Wang, Arnold and Huang 60 ) found a significant lower methylation of SFRP2 and SFRP5 after consumption of black raspberries by patients at high risk of CRC, but there were no effects of this food on LINE1, WIF1 or SPRP2 methylation( Reference Wang, Burke and Hasson 61 ). van den Donk et al. ( Reference van den Donk, Pellis and Crott 57 ) reported significantly higher global DNA methylation and increased methylation of specific genes (O6-MGMT, hMLH1, p14ARF, p16INK4A and RASSF1A) but decreased APC methylation after use of folic acid and vitamin B12 supplements. Increased consumption of vegetables( Reference van Breda, van Delft and Engels 58 ), non-digestible carbohydrates( Reference Malcomson, Willis and McCallum 62 ) or maize starch/B. lactis ( Reference Worthley, Le Leu and Whitehall 59 ) did not affect methylation of the specific genes studied in each of those trials (Table 5).

Effects of dietary interventions on DNA methylation in adipose tissue

Adipose tissue samples were obtained from subcutaneous tissues of the abdomen in four out of five intervention studies that investigated the effects of dietary interventions on DNA methylation (Table 6) (Cordero et al. ( Reference Cordero, Campion and Milagro 64 ) did not report the site of biopsy). In all, two non-RCT investigated the effect of energy restriction in obese women. Bouchard et al. ( Reference Bouchard, Rabasa-Lhoret and Faraj 63 ) reported that energy restriction for 6 months altered methylation at three specific loci (1p36, 4q21 and 5q13), whereas 8 weeks of restricted energy intake had no effect on methylation of LEP and TNFα in females of reproductive age( Reference Cordero, Campion and Milagro 64 ).

Table 6 Effects of dietary interventions on DNA methylation in adipose cells*

RCT, randomised controlled trial; CpG, cytosine-phosphate-guanosine; LBW, low birth weight; NBW, normal birth weight; ↑, increase; LEP, leptin; ADIPOQ, adiponectin, C1Q and collagen domain containing; CHO, carbohydrates.

* For full names of each of the genes listed in this table by their ID, please see Supplementary Table S4.

Hjort et al. ( Reference Hjort, Jørgensen and Gillberg 66 ) found that 36 h fasting after 2 d of a standard diet increased methylation of LEP and ADIPOQ significantly in normal-birth-weight (NBW) adults but not in those with low birth weight (LBW). In contrast, Gillberg et al. ( Reference Gillberg, Jacobsen and Rönn 65 ) reported that overfeeding with fat increased methylation of PPARGC1A in adults with LBW but not those of NBW. Overfeeding with a diet rich in saturated and unsaturated fatty acids increased mean genome-wide methylation (assayed using a BeadChip Array; Illumina) in healthy adults( Reference Perfilyev, Dahlman and Gillberg 68 ).

Effects of dietary interventions DNA methylation in other tissues

Table 7 summarises findings from studies that reported effects of dietary interventions on DNA methylation in muscle biopsies, mammary cells and semen. In all, three cross-over RCT studied effects of high-fat overfeeding on DNA methylation on muscle cells of vastus lateralis in healthy adults, and one study( Reference Brøns, Jacobsen and Nilsson 69 ) reported that this intervention increased PPARGC1A methylation in NBW adults.

Table 7 Effects of dietary interventions on DNA methylation in specialised tissues (mammary tissue, muscle cells and semen)*

RCT, randomised controlled trial; NBW, normal birth weight; LBW, low-birth-weight; ↑, increase; ER, oestrogen receptor; NA, not available; ↓, decrease; RRBS, reduced representation bisulfite sequencing; MTHFR, methylenetetrahydrofolate reductase; RLGS, restriction landmark genomic scanning; MCIp, methyl-CpG immunoprecipitation.

* For full names of each of the genes listed in this table by their ID, please see Supplementary Table S4.

DNA methylation in mammary cells was investigated in two RCT( Reference Zhu, Qin and Zhang 67 , Reference Qin, Zhu and Shi 72 ), with no significant change observed after interventions with soya isoflavones or with trans-resveratrol. However, Zhu et al. ( Reference Zhu, Qin and Zhang 67 ) found a significant inverse correlation between methylation of RASSF1A and serum trans-resveratrol concentration in healthy women at increased risk of breast cancer.

Methylation of DNA in semen after folic acid supplementations was assessed in two intervention studies( Reference Aarabi, San Gabriel and Chan 73 , Reference Chan, McGraw and Klein 74 ). Folic acid supplements resulted in reduced global DNA methylation in men with idiopathic infertility( Reference Aarabi, San Gabriel and Chan 73 ) but had no effect on global DNA methylation in healthy fertile men( Reference Chan, McGraw and Klein 74 ).

Meta-analysis and meta-regression of effects of folic acid supplementation on global DNA methylation

A total of five RCT used the [3H]-methyl acceptance assay for quantification of global DNA methylation in colorectal mucosal samples. In all, one study( Reference Cravo, Glória and Salazar de Sousa 48 ) was excluded as the study reported the significance of results only following folic acid supplementation but did not provide numerical data on DNA methylation. For the remaining four studies, meta-analysis showed that folic acid supplementation increased global DNA methylation significantly (P<0·0001) but there was significant heterogeneity between the included trials (I 2: 91%, P<0·001). Overall, there was low or unclear risk of bias owing to failure of reporting of randomisation and blinding (Fig. 1).

Fig. 1 Forest plot and risk of bias assessment of randomised controlled trial studying the effects of folic acid supplements on global DNA methylation in colorectal mucosal samples using [3H]-methyl acceptance assay using Review Manager (version 5.3).

Meta-regression was used to investigate the effects of dose and duration of folic acid supplementation. This revealed that the dose of folic acid had a highly significant (P=0·0046) and positive effect on global DNA methylation (online Supplementary Fig. S5), whereas there was no detectable effect of the duration of intervention (P=0·41).

Considering different techniques of quantification of DNA methylation, eight RCT were included for meta-analysis with two subgroups: colorectal (n 6) and blood samples (n 3, as Pufulete et al. ( Reference Pufulete, Al-Ghnaniem and Khushal 51 ) reported data for both colorectal and blood samples). Folic acid increased DNA methylation overall (P=0·048) and in colorectal mucosal samples specifically (P=0·002) (Fig. 2). However, there was no significant effect of folic acid on DNA methylation in blood samples (P=0·468). There was significant heterogeneity in the data for the colorectal subgroup (I 2=91%, P≤0·001), blood subgroup (I 2=84%, P=0·002) and overall (I 2=89%, P<0·001). The test for subgroup differences was also significant (P=0·04, I 2=75·6%) (online Supplementary Fig. S6). No high risk of bias was identified, but information to assess risk of bias was limited owing to incomplete reporting of randomisation, allocation concealment and blinding (online Supplementary Fig. S6).

Fig. 2 Forest plot of randomised controlled trial studying effects of folic acid supplements on global DNA methylation in colorectal and blood samples using different techniques of quantification of DNA methylation using CMA software (version 2).

Meta-regression analysis showed that, when investigated across both tissues and all analytical methods, the dose of folic acid used for supplementation had a highly significant and positive effect on global DNA methylation (P=0·0003, Fig. 3). However, it should be noted that this effect is driven by changes in the colorectal mucosa as there was no evidence for an effect on DNA methylation in blood (online Supplementary Fig. S7). Duration of folic acid supplementation (P=0·35) and post-intervention concentration of folate in serum (0·69) had no significant effect.

Fig. 3 Meta-regression of standardised mean difference in relation to the dose of folic acid supplements in the eight randomised controlled trial that were included in meta-analysis involving different techniques of quantification of DNA methylation.

Assessment of publication bias

Investigation of potential publication bias was performed by producing a forest plot (Fig. 4) and statistical analysis using Egger’s test (P=0·03), and this revealed a risk of publication bias for Cravo et al. ( Reference Cravo, Fidalgo and Pereira 47 ). This study recruited patients with a history of either adenoma or carcinoma, whereas other studies recruited participants with a history of adenoma only. As a sensitivity analysis, meta-analysis was performed with inclusion of results of global DNA methylation in colorectal mucosal samples from the adenoma group only( Reference Cravo, Fidalgo and Pereira 47 ). There was no change in risk of publication bias or significance of results (colorectal subgroup: P=0·02, overall effect: P=0·04, and Egger’s test for publication bias: P=0·0025, online Supplementary Fig. S7). Re-analysis of the data after exclusion of Cravo et al. ( Reference Cravo, Fidalgo and Pereira 47 ) (online Supplementary Fig. S8) revealed a positive trend towards global DNA hypermethylation with folic acid supplementation in both the colorectal subgroup (P=0·08) and overall (P=0·22).

Fig. 4 Funnel plot of standard error by standard differences in means of the eight randomised controlled trial included in the meta-analysis.

Stratification according to methylenetetrahydrofolate reductase genotype

A total of eight intervention studies stratified patients according to a polymorphism in the gene coding methylenetetrahydrofolate reductase (MTHFR; 677C→T variant). When stratification according to MTHFR genotype was applied, a significant change in DNA methylation was reported in four studies. Crider et al. ( Reference Crider, Yang and Berry 21 ) reported a significant increase in global DNA methylation of leucocytes in those participants with the TT variant only following folic acid supplementation, whereas depletion of folic acid caused a significant decrease in global DNA methylation in carriers of the CC variant only. On the other hand, Aarabi et al. ( Reference Aarabi, San Gabriel and Chan 73 ) reported that folic acid supplementation decreased DNA methylation in semen in participants with the TT variant. Global DNA methylation in leucocytes decreased following supplementation with choline in carriers of the CC variant( Reference Shin, Yan and Abratte 32 ) and following cocoa supplementation in those with the TT variant( Reference Crescenti, Solà and Valls 35 ).

Discussion

Principal findings

We identified, and analysed data from, sixty dietary intervention studies in adult human participants that reported effects on DNA methylation. Most studies (53%) reported data from blood analyses, whereas 27% studied DNA methylation in colorectal mucosal biopsies. Some studies investigated effects on global DNA methylation, which were assessed using both direct and indirect methods. The methyl acceptance assay was the assay used most frequently for this purpose, but several studies also assessed methylation of the repeat element LINE1, which makes up 17–18% of the human genome and which has been shown to be an acceptable surrogate for global DNA methylation in many cases( Reference Lisanti, Omar and Tomaszewski 75 ). Other studies interrogated specific genomic loci using either targeted – for example, Sequenom’s MassARRAY EpiTyper – or genome-wide – for example, Illumina Bead array – approaches. Folic acid was the most common intervention agent (33%) followed by low-energy diet (8%) and multivitamins (8%). Meta-analysis revealed that folic acid supplementation increased global DNA methylation significantly in colorectal mucosal samples, whereas meta-regression analysis showed that the dose of supplementary folic acid was the only significant factor (P<0·001) causing this positive relationship.

In all, four out of eight intervention studies reported significant changes in DNA methylation following folic acid supplementation when participants were stratified according to MTHFR 677C→T genotype. Carriage of the T variant at position 677 in the of MTHFR gene is associated with lower folate status, higher circulating homocysteine concentration, reduced global DNA methylation and with increased risk of many disorders( Reference Christensen, Arbour and Tran 76 , Reference Den Heijer, Lewington and Clarke 77 ), including greater cancer risk( Reference Lu, Xie and Wang 78 , Reference Wang, Sasco and Fu 79 ). This finding highlights the importance of considering subgroup classification according to MTHFR polymorphism in future research in effects of folic acid supplementation.

In all, two( Reference Jacob, Gretz and Taylor 15 , Reference Rampersaud, Kauwell and Hutson 16 ) out of three non-RCT reported a significant effect of folate depletion in decreasing global DNA methylation in blood products, but this effect was not observed in colorectal samples( Reference Protiva, Mason and Liu 53 ). While Jacob et al. ( Reference Jacob, Gretz and Taylor 15 ) observed that folic acid repletion reversed the DNA hypomethylation, no such effect was apparent in the study by Rampersaud et al. ( Reference Rampersaud, Kauwell and Hutson 16 ). The participants in the latter study were older (>63 years) than those studied by Jacob et al. ( Reference Jacob, Gretz and Taylor 15 ) (49–63 years), and it is possible that age blunted the speed of response to nutritional repletion. In this systematic review, there was no detectable effect of folic acid supplementation on DNA methylation in blood, but there was a significant effect on methylation of DNA from colorectal mucosal samples.

Possible mechanisms responsible for these findings

The mechanism responsible for such tissue differences in response to folic acid supplementation is not known. In human intervention studies, folic acid supplementation raises folate concentrations in both blood and the colorectal mucosa( Reference Powers, Hill and Welfare 80 ) so that it seems unlikely that there would be differential availability of methyl groups for synthesis of SAM for DNA methylation within blood cells and colonocytes. However, studies in mice have shown that folate depletion leads to tissue-specific effects on DNA methylation at selected genomic loci( Reference McKay, Xie and Harris 8 ). In addition, reduced circulating concentration of folate in blood was associated with DNA hypomethylation in human diabetic liver( Reference Nilsson, Matte and Perfilyev 81 ). Such observations are consistent with cell-type-specific differences in cellular distribution of available methyl groups and/or differences in policing of the DNA methylome.

Strengths and limitations

Poor diet and diet-related factors are major contributors to the burden of ill health, especially cancer and cardiometabolic diseases( Reference Murray, Richards and Newton 82 ). This review summarises the available evidence for the impact of dietary factors on DNA methylation in both health and disease. Our systematic review shows that, in humans, little is known about the effects of dietary interventions on DNA methylation in tissues other blood and colorectal mucosa; only one-fifth of the included intervention studies in this review investigated other tissues. In addition, none of the included RCT correlated DNA methylation levels between target tissues and other surrogate tissues. The availability of validated assays for DNA methylation biomarkers in reliable and accessible surrogate tissues, such as blood, would avoid the need for invasive sample collection procedures, such as colorectal biopsies, which would facilitate larger population-based studies( Reference Rockett, Burczynski and Fornace 83 ).

This systematic review faced many challenges in data summary and synthesising the evidence. The effects of dietary interventions on DNA methylation are gene and site specific, dependent on cell type and target tissue, and dose and duration of the interventions( Reference Kim, Golub and Park 4 ). There was great heterogeneity in the methods used for assessing DNA methylation and in the genomic loci investigated. Samples were collected from both healthy individuals and from people with specific diseases, which contributed to the heterogeneity in the available data. Statistical heterogeneity was observed in the meta-analysis of eight trials, which had all tested effects of the same nutrient (folic acid). Most of the included RCT failed to report randomisation methods, allocation concealment or blinding that could lead to selective bias owing to poor choice of methods( Reference Kahan, Rehal and Cro 84 ) and could affect outcome assessment( Reference Feys, Bekkering and Singh 85 ). Failure to report such important methodological aspect results in the inability to assess the risk of bias, which could compromise the overall strength of evidence.

Conclusion

Folic acid supplementation increases global DNA methylation in the colorectal mucosa in a dose-dependent manner. This observation may provide the basis for future research in prevention of bowel cancer as DNA hypomethylation is a consistent event in colonic carcinogenesis( Reference Sakai, Nakajima and Kaneda 3 ). However, little is known about the effects of other dietary factors on DNA methylation patterns in any human tissue. In addition, multiple assays and different genomic loci have been used in investigations of effect of dietary interventions on DNA methylation, which makes it difficult to compare or combine data across studies. Standardisation of outcome measurements would facilitate future research.

Acknowledgements

This research received no specific grant from any funding agency or from commercial or not-for-profit sectors.

K. E. contributed to formulating the research question, designing the study, carrying the study out, analysing the data and writing the manuscript. F. C. M. contributed as the second independent screener of the titles, and reviewed the manuscript. J. G. L. assisted in designing the study and reviewed the manuscript. D. M. B. was involved in critical review of the manuscript and final approval. J. C. M. was involved in formulating the research question, designing the study, writing up and critical review of the manuscript, as well as in final approval.

The authors declare that there are no conflicts of interest.

Supplementary materials

For supplementary material/s referred to in this article, please visit https://doi.org/10.1017/S000711451800243X

References

1. Mathers, JC, Strathdee, G & Relton, CL (2010) Induction of epigenetic alterations by dietary and other environmental factors. Adv Genet 71, 339.Google Scholar
2. Kandi, V & Vadakedath, S (2015) Effect of DNA methylation in various diseases and the probable protective role of nutrition: a mini-review. Cureus 7, e309.Google Scholar
3. Sakai, E, Nakajima, A & Kaneda, A (2014) Accumulation of aberrant DNA methylation during colorectal cancer development. World J Gastroenterol 20, 978987.Google Scholar
4. Kim, H, Golub, GH & Park, H (2005) Missing value estimation for DNA microarray gene expression data: local least squares imputation. Bioinformatics 21, 187198.Google Scholar
5. Chen, Z, Gaudino, G, Pass, HI, et al. (2017) Diagnostic and prognostic biomarkers for malignant mesothelioma: an update. Transl Lung Cancer Res 6, 259269.Google Scholar
6. Mikeska, T & Craig, JM (2014) DNA methylation biomarkers: cancer and beyond. Genes 5, 821864.Google Scholar
7. Levenson, VV (2010) DNA methylation as a universal biomarker. Expert Rev Mol Diagn 10, 481488.Google Scholar
8. McKay, JA, Xie, L, Harris, S, et al. (2011) Blood as a surrogate marker for tissue-specific DNA methylation and changes due to folate depletion in post-partum female mice. Mol Nutr Food Res 55, 10261035.Google Scholar
9. Patai, AV, Molnár, B, Kalmár, A, et al. (2012) Role of DNA methylation in colorectal carcinogenesis. Dig Dis 30, 310315.Google Scholar
10. McKay, JA & Mathers, JC (2011) Diet induced epigenetic changes and their implications for health. Acta Physiol (Oxf) 202, 103118.Google Scholar
11. Vanden Berghe, W (2012) Epigenetic impact of dietary polyphenols in cancer chemoprevention: lifelong remodeling of our epigenomes. Pharmacol Res 65, 565576.Google Scholar
12. Lim, U & Song, MA (2012) Dietary and lifestyle factors of DNA methylation. Methods Mol Biol 863, 359376.Google Scholar
13. Lamprecht, SA & Lipkin, M (2003) Chemoprevention of colon cancer by calcium, vitamin D and folate: molecular mechanisms. Nat Rev Cancer 3, 601614.Google Scholar
14. Moher, D, Liberati, A, Tetzlaff, J, et al. (2010) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg 8, 336341.Google Scholar
15. Jacob, RA, Gretz, DM, Taylor, PC, et al. (1998) Moderate folate depletion increases plasma homocysteine and decreases lymphocyte DNA methylation in postmenopausal women. J Nutr 128, 12041212.Google Scholar
16. Rampersaud, GC, Kauwell, GP, Hutson, AD, et al. (2000) Genomic DNA methylation decreases in response to moderate folate depletion in elderly women. Am J Clin Nutr 72, 9981003.Google Scholar
17. Ingrosso, D, Cimmino, A, Perna, AF, et al. (2003) Folate treatment and unbalanced methylation and changes of allelic expression induced by hyperhomocysteinaemia in patients with uraemia. Lancet 361, 16931699.Google Scholar
18. Pizzolo, F, Blom, HJ, Choi, SW, et al. (2011) Folic acid effects on S-adenosylmethionine, S-adenosylhomocysteine, and DNA methylation in patients with intermediate hyperhomocysteinemia. J Am Coll Nutr 30, 1118.Google Scholar
19. Ellingrod, VL, Grove, TB, Burghardt, KJ, et al. (2015) The effect of folate supplementation and genotype on cardiovascular and epigenetic measures in schizophrenia subjects. NPJ Schizophr 1, 15046.Google Scholar
20. Basten, GP, Duthie, SJ, Pirie, L, et al. (2006) Sensitivity of markers of DNA stability and DNA repair activity to folate supplementation in healthy volunteers. Br J Cancer 94, 19421947.Google Scholar
21. Crider, KS, Yang, TP, Berry, RJ, et al. (2012) Folate and DNA methylation: a review of molecular mechanisms and the evidence for folate’s role. Adv Nutr 3, 2138.Google Scholar
22. Jung, AY, Smulders, Y & Verhoef, P (2011) No effect of folic acid supplementation on global DNA methylation in men and women with moderately elevated homocysteine. PLoS ONE 6, e24976.Google Scholar
23. Milagro, FI, Campión, J, Cordero, P, et al. (2011) A dual epigenomic approach for the search of obesity biomarkers: DNA methylation in relation to diet-induced weight loss. FASEB J 25, 13781389.Google Scholar
24. Abete, I, Gómez-Úriz, AM, Mansego, ML, et al. (2015) Epigenetic changes in the methylation patterns of KCNQ1 and WT1 after a weight loss intervention program in obese stroke patients. Curr Neurovasc Res 12, 321333.Google Scholar
25. Nicoletti, CF, Cortes-Oliveira, C, Pinhel, MAS, et al. (2017) Bariatric surgery and precision nutrition. Nutrients 9, 974.Google Scholar
26. Martín-Núñez, GM, Cabrera-Mulero, R, Rubio-Martín, E, et al. (2014) Methylation levels of the SCD1 gene promoter and LINE-1 repeat region are associated with weight change: an intervention study. Mol Nutr Food Res 58, 15281536.Google Scholar
27. Samblas, M, Milagro, FI, Gómez-Abellán, P, et al. (2016) Methylation on the circadian gene BMAL1 is associated with the effects of a weight loss intervention on serum lipid levels. J Biol Rhythms 31, 308317.Google Scholar
28. Delgado-Cruzata, L, Zhang, W, McDonald, JA, et al. (2015) Dietary modifications, weight loss, and changes in metabolic markers affect global DNA methylation in Hispanic, African American, and Afro-Caribbean breast cancer survivors. J Nutr 145, 783790.Google Scholar
29. Duggan, C, Xiao, L, Terry, MB, et al. (2014) No effect of weight loss on LINE-1 methylation levels in peripheral blood leukocytes from postmenopausal overweight women. Obesity (Silver Spring) 22, 20912096.Google Scholar
30. Kok, DE, Dhonukshe-Rutten, RA, Lute, C, et al. (2015) The effects of long-term daily folic acid and vitamin B12 supplementation on genome-wide DNA methylation in elderly subjects. Clin Epigenetics 7, 121.Google Scholar
31. van der Kooi, EL, de Greef, JC, Wohlgemuth, M, et al. (2011) No effect of folic acid and methionine supplementation on D4Z4 methylation in patients with facioscapulohumeral muscular dystrophy. Neuromuscul Disord 16, 766769.Google Scholar
32. Shin, W, Yan, J, Abratte, CM, et al. (2010) Choline intake exceeding current dietary recommendations preserves markers of cellular methylation in a genetic subgroup of folate-compromised men. J Nutr 140, 975980.Google Scholar
33. Milenkovic, D, Vanden Berghe, W, Boby, C, et al. (2014) Dietary flavanols modulate the transcription of genes associated with cardiovascular pathology without changes in their DNA methylation state. PLOS ONE 9, e95527.Google Scholar
34. Scoccianti, C, Ricceri, F, Ferrari, P, et al. (2011) Methylation patterns in sentinel genes in peripheral blood cells of heavy smokers: influence of cruciferous vegetables in an intervention study. Epigenetics 6, 11141119.Google Scholar
35. Crescenti, A, Solà, R & Valls, RM (2013) Cocoa consumption alters the global DNA methylation of peripheral leukocytes in humans with cardiovascular disease risk factors: a randomized controlled trial. PLOS ONE 8, e65744.Google Scholar
36. Greenlee, H, Gaffney, AO, Aycinena, AC, et al. (2016) Long-term diet and biomarker changes after a short-term intervention among Hispanic breast cancer survivors: the ¡Cocinar Para Su Salud! randomized controlled trial. Cancer Epidemiol Biomarkers Prev 25, 14911502.Google Scholar
37. Zhu, H, Bhagatwala, J, Huang, Y, et al. (2016) Race/ethnicity-specific association of vitamin D and global DNA methylation: cross-sectional and interventional findings. PLOS ONE 11, e0152849.Google Scholar
38. Arpón, A, Riezu-Boj, JI, Milagro, FI, et al. (2016) Adherence to Mediterranean diet is associated with methylation changes in inflammation-related genes in peripheral blood cells. J Physiol Biochem 73, 445455.Google Scholar
39. Abratte, CM, Wang, W, Li, R, et al. (2009) Choline status is not a reliable indicator of moderate changes in dietary choline consumption in premenopausal women. J Nutr Biochem 20, 6269.Google Scholar
40. Do Amaral, CL, Milagro, FI, Curi, R, et al. (2014) DNA methylation pattern in overweight women under an energy-restricted diet supplemented with fish oil. BioMed Res Int 2014, 675021.Google Scholar
41. Hoile, SP, Clarke-Harris, R, Huang, R-C, et al. (2014) Supplementation with n-3 long-chain polyunsaturated fatty acids or olive oil in men and women with renal disease induces differential changes in the DNA methylation of FADS2 and ELOVL5 in peripheral blood mononuclear cells. PLOS ONE 9, e109896.Google Scholar
42. Switzeny, OJ, Müllner, E, Wagner, K-H, et al. (2012) Vitamin and antioxidant rich diet increases MLH1 promoter DNA methylation in DMT2 subjects. Clin Epigenetics 4, 19.Google Scholar
43. Hübner, U, Geisel, J, Kirsch, SH, et al. (2013) Effect of 1 year B and D vitamin supplementation on LINE-1 repetitive element methylation in older subjects. Clin Chem Lab Med 51, 649655.Google Scholar
44. Stopper, H, Treutlein, AT, Bahner, U, et al. (2008) Reduction of the genomic damage level in haemodialysis patients by folic acid and vitamin B12 supplementation. Nephrol Dial Transplant 23, 32723279.Google Scholar
45. Hariri, M, Salehi, R, Feizi, A, et al. (2015) A randomized, double-blind, placebo-controlled, clinical trial on probiotic soy milk and soy milk: effects on epigenetics and oxidative stress in patients with type II diabetes. Genes Nutr 10, 52.Google Scholar
46. Pusceddu, I, Herrmann, M, Kirsch, SH, et al. (2016) Prospective study of telomere length and LINE-1 methylation in peripheral blood cells: the role of B vitamins supplementation. Eur J Nutr 55, 18631873.Google Scholar
47. Cravo, M, Fidalgo, P, Pereira, AD, et al. (1994) DNA methylation as an intermediate biomarker in colorectal cancer: modulation by folic acid supplementation. Eur J Cancer Prev 3, 473479.Google Scholar
48. Cravo, M, Glória, L, Salazar de Sousa, L, et al. (1995) Folate status, DNA methylation and colon cancer risk in inflammatory bowel disease. Clin Nutr 14, 5053Google Scholar
49. Cravo, ML, Pinto, AG, Chaves, P, et al. (1998) Effect of folate supplementation on DNA methylation of rectal mucosa in patients with colonic adenomas: correlation with nutrient intake. Clin Nutr 17, 4549.Google Scholar
50. Kim, YI, Baik, HW, Fawaz, K, et al. (2001) Effects of folate supplementation on two provisional molecular markers of colon cancer: a prospective, randomized trial. Am J Gastroenterol 96, 184195.Google Scholar
51. Pufulete, M, Al-Ghnaniem, R, Khushal, A, et al. (2005) Effect of folic acid supplementation on genomic DNA methylation in patients with colorectal adenoma. Gut 54, 648653.Google Scholar
52. Figueiredo, JC1, Grau, MV, Wallace, K, et al. (2009) Global DNA hypomethylation (LINE-1) in the normal colon and lifestyle characteristics and dietary and genetic factors. Cancer Epidemiol Biomarkers Prev 18, 10411049.Google Scholar
53. Protiva, P, Mason, JB, Liu, Z, et al. (2011) Altered folate availability modifies the molecular environment of the human colon: implications for colorectal carcinogenesis. Cancer Prev Res (Phila) 4, 530543.Google Scholar
54. Wallace, K, Grau, MV, Levine, JA, et al. (2010) Association between folate levels and CpG island hypermethylation in normal colorectal mucosa. Cancer Prev Res (Phila) 3, 15521564.Google Scholar
55. Al-Ghnaniem Abbadi, R, Emery, P & Pufulete, M (2012) Short-term folate supplementation in physiological doses has no effect on ESR1 and MLH1 methylation in colonic mucosa of individuals with adenoma. J Nutrigenet Nutrigenomics 5, 327338.Google Scholar
56. O’Reilly, SL, McGlynn, AP, McNulty, H, et al. (2016) Folic acid supplementation in postpolypectomy patients in a randomized controlled trial increases tissue folate concentrations and reduces aberrant DNA biomarkers in colonic tissues adjacent to the former polyp site. J Nutr 146, 933939.Google Scholar
57. van den Donk, M, Pellis, L, Crott, JW, et al. (2007) 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 137, 21142120.Google Scholar
58. van Breda, SG, van Delft, JH, Engels, LG, et al. (2009) Methylation status of CpG islands in the promoter region of genes differentially expressed in colonic mucosa from adenoma patients and controls in response to altered vegetable intake. Br J Nutr 101, 12951299.Google Scholar
59. Worthley, DL, Le Leu, RK, Whitehall, VL, et al. (2009) A human, double-blind, placebo-controlled, crossover trial of prebiotic, probiotic, and synbiotic supplementation: effects on luminal, inflammatory, epigenetic, and epithelial biomarkers of colorectal cancer. Am J Clin Nutr 90, 578586.Google Scholar
60. Wang, L-S, Arnold, M, Huang, Y-W, et al. (2011) Modulation of genetic and epigenetic biomarkers of colorectal cancer in humans by black raspberries: a phase I pilot study. Clin Cancer Res 17, 598610.Google Scholar
61. Wang, LS, Burke, CA & Hasson, H (2014) A phase Ib study of the effects of black raspberries on rectal polyps in patients with familial adenomatous polyposis. Cancer Prev Res (Phila) 7, 666674.Google Scholar
62. Malcomson, FC, Willis, ND, McCallum, I, et al.. (2017) Effects of supplementation with nondigestible carbohydrates on fecal calprotectin and on epigenetic regulation of SFRP1 expression in the large-bowel mucosa of healthy individuals. Am J Clin Nutr 105, 400410.Google Scholar
63. Bouchard, L, Rabasa-Lhoret, R, Faraj, M, et al. (2010) Differential epigenomic and transcriptomic responses in subcutaneous adipose tissue between low and high responders to caloric restriction. Am J Clin Nutr 91, 309320.Google Scholar
64. Cordero, P, Campion, J, Milagro, FI, et al. (2011) Leptin and TNF-alpha promoter methylation levels measured by MSP could predict the response to a low-calorie diet. J Physiol Biochem 67, 463470.Google Scholar
65. Gillberg, L, Jacobsen, SC, Rönn, T, et al. (2013) PPARGC1A DNA methylation in subcutaneous adipose tissue in low birth weight subjects--impact of 5 days of high-fat overfeeding. Metabolism 63, 263271.Google Scholar
66. Hjort, L, Jørgensen, SW, Gillberg, L, et al. (2017) 36 h fasting of young men influences adipose tissue DNA methylation of LEP and ADIPOQ in a birth weight-dependent manner. Clin Epigenetics 9, 40.Google Scholar
67. Zhu, W, Qin, W, Zhang, K, et al. (2012) trans-Resveratrol alters mammary promoter hypermethylation in women at increased risk for breast cancer. Nutr Cancer 64, 393400.Google Scholar
68. Perfilyev, A, Dahlman, I, Gillberg, L, et al. (2017) Impact of polyunsaturated and saturated fat overfeeding on the DNA-methylation pattern in human adipose tissue: a randomized controlled trial. Am J Clin Nutr 105, 9911000.Google Scholar
69. Brøns, C, Jacobsen, S, Nilsson, E, et al. (2010) Deoxyribonucleic acid methylation and gene expression of PPARGC1A in human muscle is influenced by high-fat overfeeding in a birth-weight-dependent manner. J Clin Endocrinol Metab 95, 30483056.Google Scholar
70. Jacobsen, SC, Brøns, C, Bork-Jensen, J, et al. (2012) Effects of short-term high-fat overfeeding on genome-wide DNA methylation in the skeletal muscle of healthy young men. Diabetologia 55, 33413349.Google Scholar
71. Jacobsen, SC, Gillberg, L, Bork-Jensen, J, et al. (2014) Young men with low birthweight exhibit decreased plasticity of genome-wide muscle DNA methylation by high-fat overfeeding. Diabetologia 57, 11541158.Google Scholar
72. Qin, W, Zhu, W, Shi, H, et al. (2009) Soy isoflavones have an antiestrogenic effect and alter mammary promoter hypermethylation in healthy premenopausal women. Nutr Cancer 61, 238244.Google Scholar
73. Aarabi, M, San Gabriel, MC, Chan, D, et al. (2015) High-dose folic acid supplementation alters the human sperm methylome and is influenced by the MTHFR C677T polymorphism. Hum Mol Genet 24, 63016313.Google Scholar
74. Chan, D, McGraw, S, Klein, K, et al. (2017) Stability of the human sperm DNA methylome to folic acid fortification and short-term supplementation. Hum Reprod 32, 272283.Google Scholar
75. Lisanti, S, Omar, WAW, Tomaszewski, B, et al. (2013) Comparison of methods for quantification of global DNA methylation in human cells and tissues. PLOS ONE 8, e79044.Google Scholar
76. Christensen, B, Arbour, L, Tran, P, et al. (1999) Genetic polymorphisms in methylenetetrahydrofolate reductase and methionine synthase, folate levels in red blood cells, and risk of neural tube defects. Am J Med Genet 84, 151157.Google Scholar
77. Den Heijer, M, Lewington, S & Clarke, R (2005) Homocysteine, MTHFR and risk of venous thrombosis: a meta-analysis of published epidemiological studies. J Thromb Haemost 3, 292299.Google Scholar
78. Lu, C, Xie, H, Wang, F, et al. (2011) Diet folate, DNA methylation and genetic polymorphisms of MTHFR C677T in association with the prognosis of esophageal squamous cell carcinoma. BMC Cancer 11, 91.Google Scholar
79. Wang, J, Sasco, AJ, Fu, C, et al. (2008) Aberrant DNA methylation of P16, MGMT, and hMLH1 genes in combination with MTHFR C677T genetic polymorphism in esophageal squamous cell carcinoma. Cancer Epidemiol Biomarkers Prev 17, 118125.Google Scholar
80. Powers, HJ, Hill, MH, Welfare, M, et al. (2007) Responses of biomarkers of folate and riboflavin status to folate and riboflavin supplementation in healthy and colorectal polyp patients (the FAB2 study). Cancer Epidemiol Biomarkers Prev 16, 21282135.Google Scholar
81. Nilsson, E, Matte, A, Perfilyev, A, et al. (2015) Epigenetic alterations in human liver from subjects with type 2 diabetes in parallel with reduced folate levels. J Clin Endocrinol Metab 100, E1491E1501.Google Scholar
82. Murray, CJL, Richards, MA, Newton, JN, et al. (2013) UK health performance: findings of the Global Burden of Disease Study 2010. Lancet 381, 9971020.Google Scholar
83. Rockett, JC, Burczynski, ME, Fornace, AJ, et al. (2004) Surrogate tissue analysis: monitoring toxicant exposure and health status of inaccessible tissues through the analysis of accessible tissues and cells. Toxicol Appl Pharmacol 194, 189199.Google Scholar
84. Kahan, BC, Rehal, S & Cro, S (2015) Risk of selection bias in randomised trials. Trials 16, 405.Google Scholar
85. Feys, F, Bekkering, GE, Singh, K, et al. (2014) Do randomized clinical trials with inadequate blinding report enhanced placebo effects for intervention groups and nocebo effects for placebo groups? Syst Rev 3, 14.Google Scholar
Figure 0

Table 1 Effects of folic acid supplementation on DNA methylation in different blood samples

Figure 1

Table 2 Effects of weight-loss nutritional interventions on DNA methylation in different blood products*

Figure 2

Table 3 Effects of different dietary interventions (other than folic acid and weight-loss interventions) on DNA methylation in different blood products*

Figure 3

Table 4 Effects of folic acid supplementation on DNA methylation in colorectal mucosa*

Figure 4

Table 5 Effects of different dietary supplementation (other than folic acid) on DNA methylation in colorectal mucosa*

Figure 5

Table 6 Effects of dietary interventions on DNA methylation in adipose cells*

Figure 6

Table 7 Effects of dietary interventions on DNA methylation in specialised tissues (mammary tissue, muscle cells and semen)*

Figure 7

Fig. 1 Forest plot and risk of bias assessment of randomised controlled trial studying the effects of folic acid supplements on global DNA methylation in colorectal mucosal samples using [3H]-methyl acceptance assay using Review Manager (version 5.3).

Figure 8

Fig. 2 Forest plot of randomised controlled trial studying effects of folic acid supplements on global DNA methylation in colorectal and blood samples using different techniques of quantification of DNA methylation using CMA software (version 2).

Figure 9

Fig. 3 Meta-regression of standardised mean difference in relation to the dose of folic acid supplements in the eight randomised controlled trial that were included in meta-analysis involving different techniques of quantification of DNA methylation.

Figure 10

Fig. 4 Funnel plot of standard error by standard differences in means of the eight randomised controlled trial included in the meta-analysis.

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