Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Oct 1;112(4):1099-1113.
doi: 10.1093/ajcn/nqaa193.

Effect of maternal preconceptional and pregnancy micronutrient interventions on children's DNA methylation: Findings from the EMPHASIS study

Collaborators, Affiliations

Effect of maternal preconceptional and pregnancy micronutrient interventions on children's DNA methylation: Findings from the EMPHASIS study

Ayden Saffari et al. Am J Clin Nutr. .

Abstract

Background: Maternal nutrition in pregnancy has been linked to offspring health in early and later life, with changes to DNA methylation (DNAm) proposed as a mediating mechanism.

Objective: We investigated intervention-associated DNAm changes in children whose mothers participated in 2 randomized controlled trials of micronutrient supplementation before and during pregnancy, as part of the EMPHASIS (Epigenetic Mechanisms linking Preconceptional nutrition and Health Assessed in India and sub-Saharan Africa) study (ISRCTN14266771).

Design: We conducted epigenome-wide association studies with blood samples from Indian (n = 698) and Gambian (n = 293) children using the Illumina EPIC array and a targeted study of selected loci not on the array. The Indian micronutrient intervention was food based, whereas the Gambian intervention was a micronutrient tablet.

Results: We identified 6 differentially methylated CpGs in Gambians [2.5-5.0% reduction in intervention group, all false discovery rate (FDR) <5%], the majority mapping to ESM1, which also represented a strong signal in regional analysis. One CpG passed FDR <5% in the Indian cohort, but overall effect sizes were small (<1%) and did not have the characteristics of a robust signature. We also found strong evidence for enrichment of metastable epialleles among subthreshold signals in the Gambian analysis. This supports the notion that multiple methylation loci are influenced by micronutrient supplementation in the early embryo.

Conclusions: Maternal preconceptional and pregnancy micronutrient supplementation may alter DNAm in children measured at 7-9 y. Multiple factors, including differences between the nature of the intervention, participants, and settings, are likely to have contributed to the lack of replication in the Indian cohort. Potential links to phenotypic outcomes will be explored in the next stage of the EMPHASIS study.

Keywords: DNA methylation; RCT; epigenetics; epigenome-wide association study; micronutrient intervention.

PubMed Disclaimer

Figures

FIGURE 1
FIGURE 1
Volcano plots for each cohort of statistical significance against difference in methylation Beta values between intervention and control groups for all CpGs tested. Multiple linear regression models were used for an epigenome-wide association study in both Gambian (A: n = 289) and Indian (B: n = 686) cohorts. The dashed vertical and horizontal lines indicate thresholds for delta Beta 2% and nominal P = 0.05, respectively. Orange circles show differentially methylated positions—significant CpGs with false discovery rate (FDR) <5%; an orange triangle indicates a point falling outside the plot area.
FIGURE 2
FIGURE 2
Boxplots showing the distributions of methylation values for the CpGs within the (A) ESM1 and (B) LZTS1 DMRs identified in the Gambian epigenome-wide association study regional analysis (n = 289). DMRs were identified using DMRcate and comb-p methods. In ESM1, 4 CpGs are also significant differentially methylated positions (DMPs) [false discovery rate (FDR) < 5%]. LZTS1 contains no significant DMPs. In both regions, the intervention is consistently associated with reduced methylation concentrations. Blank and filled boxes represent control and intervention arms, respectively. CpG site-wise false discovery rates: *FDR < 0.1; **FDR < 1×10-2; ***FDR < 1×10-3. DMR, differentially methylated regions; ns, not significant.
FIGURE 3
FIGURE 3
The ESM1 differentially methylated region (DMR) shown within its genomic context and annotated with regulatory features (data tracks from the University of California, Santa Cruz genome browser). The identified DMR overlaps the transcription start site (TSS), 5′ untranslated region, and first exon of the gene and is in an area of active transcription. The tracks show (in order): the chromosomal location; the CpGs making up the region with differentially methylated positions (false discovery rate <5%) in yellow; the ESM1 DMR; Ensembl gene predictions (red); predicted promoter location (blue—Eukaryotic Promoter Database v006); histone tail marks H3K4Me1, H3K4Me3, and H3K27Ac indicating active regions of transcription (on 7 cell lines from ENCODE); DNAse hypersensitivity clusters showing open chromatin (125 cell types from ENCODE version 3); and transcription factor ChIP-seq clusters (ENCODE v3).
FIGURE 4
FIGURE 4
The LZTS1 differentially methylated region (DMR) within its genomic context and annotated with regulatory features (data tracks from the University of California, Santa Cruz genome browser). The identified DMR is intronic and downstream of a CpG island (green). The tracks show (in order): the chromosomal location; the CpGs making up the region; the LZTS1 DMR; Ensembl gene prediction (red); predicted promoter location (blue—Eukaryotic Promoter Database v006); histone tail marks H3K4Me1, H3K4Me3, and H3K27Ac indicating active regions of transcription (on 7 cell lines from ENCODE); DNAse hypersensitivity clusters showing open chromatin (125 cell types from ENCODE version 3); and transcription factor ChIP-seq clusters (ENCODE v3).

References

    1. Fleming TP, Watkins AJ, Velazquez MA, Mathers JC, Prentice AM, Stephenson J, Barker M, Saffery R, Yajnik CS, Eckert JJ et al. . Origins of lifetime health around the time of conception: causes and consequences. Lancet. 2018;391:1842–52. - PMC - PubMed
    1. Stephenson J, Heslehurst N, Hall J, Schoenaker DAJM, Hutchinson J, Cade JE, Poston L, Barrett G, Crozier SR, Barker M et al. . Before the beginning: nutrition and lifestyle in the preconception period and its importance for future health. Lancet. 2018;391:1830–41. - PMC - PubMed
    1. Bortolus R, Blom F, Filippini F, van Poppel MNM, Leoncini E, de Smit DJ, Benetollo PP, Cornel MC, de Walle HEK, Mastroiacovo P. Prevention of congenital malformations and other adverse pregnancy outcomes with 4.0 mg of folic acid: community-based randomized clinical trial in Italy and the Netherlands. BMC Pregnancy Childbirth. 2014;14:166. - PMC - PubMed
    1. Branca F, Ferrari M. Impact of micronutrient deficiencies on growth: the stunting syndrome. Ann Nutr Metab. 2002;46:8–17. - PubMed
    1. Murrin C, Shrivastava A, Kelleher CC. Maternal macronutrient intake during pregnancy and 5 years postpartum and associations with child weight status aged five. Eur J Clin Nutr. 2013;67:670–9. - PubMed

Publication types