Environmentally sensitive hotspots in the methylome of the early human embryo

  1. Matt J Silver  Is a corresponding author
  2. Ayden Saffari
  3. Noah J Kessler
  4. Gririraj R Chandak
  5. Caroline HD Fall
  6. Prachand Issarapu
  7. Akshay Dedaniya
  8. Modupeh Betts
  9. Sophie E Moore
  10. Michael N Routledge
  11. Zdenko Herceg
  12. Cyrille Cuenin
  13. Maria Derakhshan
  14. Philip T James
  15. David Monk
  16. Andrew M Prentice
  1. MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, United Kingdom
  2. University of Cambridge, United Kingdom
  3. CSIR-Centre for Cellular and Molecular Biology, India
  4. University of Southampton, United Kingdom
  5. MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Gambia
  6. King's College London, United Kingdom
  7. University of Leeds, United Kingdom
  8. International Agency For Research On Cancer, France
  9. University of East Anglia, United Kingdom

Abstract

In humans, DNA methylation marks inherited from gametes are largely erased following fertilisation, prior to construction of the embryonic methylome. Exploiting a natural experiment of seasonal variation including changes in diet and nutritional status in rural Gambia, we analysed three datasets covering two independent child cohorts and identified 259 CpGs showing consistent associations between season of conception (SoC) and DNA methylation. SoC effects were most apparent in early infancy, with evidence of attenuation by mid-childhood. SoC-associated CpGs were enriched for metastable epialleles, parent-of-origin specific methylation and germline DMRs, supporting a periconceptional environmental influence. Many SoC-associated CpGs overlapped enhancers or sites of active transcription in H1 ESCs and fetal tissues. Half were influenced but not determined by measured genetic variants that were independent of SoC. Environmental ‘hotspots’ providing a record of environmental influence at periconception constitute a valuable resource for investigating epigenetic mechanisms linking early exposures to lifelong health and disease.

Data availability

Illumina 450k methylation array data generated from Gambian 2 year olds from the ENID trial is deposited in GEO (GSE99863). Requests to access and analyse the other Gambian methylation datasets (ENID 5-7yr and EMPHASIS 7-9yr) should be submitted to the corresponding author in the first instance. An application would then need to be made to MRC Unit The Gambia's Scientific Coordinating Committee and the Joint MRC/Gambia Government Ethics Committee.Sources and locations of other publicly available data used in this analysis are described in Methods. Bespoke code used in the analysis is available at https://zenodo.org/record/5801480.

The following previously published data sets were used

Article and author information

Author details

  1. Matt J Silver

    Faculty of Epidemiology and Public Health, MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, London, United Kingdom
    For correspondence
    matt.silver@lshtm.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3852-9677
  2. Ayden Saffari

    Faculty of Epidemiology and Public Health, MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Noah J Kessler

    Department of Genetics, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Gririraj R Chandak

    Genomic Research on Complex Diseases, CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
    Competing interests
    The authors declare that no competing interests exist.
  5. Caroline HD Fall

    MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Prachand Issarapu

    Genomic Research on Complex Diseases, CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
    Competing interests
    The authors declare that no competing interests exist.
  7. Akshay Dedaniya

    Genomic Research on Complex Diseases, CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
    Competing interests
    The authors declare that no competing interests exist.
  8. Modupeh Betts

    Faculty of Epidemiology and Public Health, MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Fajara, Gambia
    Competing interests
    The authors declare that no competing interests exist.
  9. Sophie E Moore

    Department of Women and Children's Health, King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  10. Michael N Routledge

    School of Medicine, University of Leeds, Leeds, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  11. Zdenko Herceg

    Epigenomics and Mechanisms Branch, International Agency For Research On Cancer, Lyon, France
    Competing interests
    The authors declare that no competing interests exist.
  12. Cyrille Cuenin

    Epigenomics and Mechanisms Branch, International Agency For Research On Cancer, Lyon, France
    Competing interests
    The authors declare that no competing interests exist.
  13. Maria Derakhshan

    Faculty of Epidemiology and Public Health, MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  14. Philip T James

    Faculty of Epidemiology and Public Health, MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  15. David Monk

    Biomedical Research Centre, University of East Anglia, Norwich, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  16. Andrew M Prentice

    Faculty of Epidemiology and Public Health, MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Fajara, Gambia
    Competing interests
    The authors declare that no competing interests exist.

Funding

Medical Research Council (MC-A760-5QX00)

  • Matt J Silver
  • Andrew M Prentice

Bill and Melinda Gates Foundation (OPP1 066947)

  • Sophie E Moore
  • Michael N Routledge
  • Zdenko Herceg

Medical Research Council (MR/N006208/1)

  • Matt J Silver
  • Caroline HD Fall
  • Andrew M Prentice

Department of Biotechnology, Ministry of Science and Technology, India (BT/IN/DBT-MRC/DFID/24/GRC/2015-16)

  • Gririraj R Chandak

Medical Research Council (MR/M01424X/1)

  • Matt J Silver
  • Ayden Saffari
  • Noah J Kessler
  • Andrew M Prentice

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: Ethics approval for the Gambian ENID and EMPHASIS trials was obtained from the joint Gambia Government/MRC Unit The Gambia's Ethics Committee (ENID: SCC1126v2; EMPHASIS: SCC1441). The ENID study is registered as ISRCTN49285450. The EMPHASIS study is registered as ISRCTN14266771. Signed informed consent for both studies was obtained from parents, and verbal assent was additionally obtained from the older children who participated in the EMPHASIS study.

Copyright

© 2022, Silver et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,599
    views
  • 249
    downloads
  • 19
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Matt J Silver
  2. Ayden Saffari
  3. Noah J Kessler
  4. Gririraj R Chandak
  5. Caroline HD Fall
  6. Prachand Issarapu
  7. Akshay Dedaniya
  8. Modupeh Betts
  9. Sophie E Moore
  10. Michael N Routledge
  11. Zdenko Herceg
  12. Cyrille Cuenin
  13. Maria Derakhshan
  14. Philip T James
  15. David Monk
  16. Andrew M Prentice
(2022)
Environmentally sensitive hotspots in the methylome of the early human embryo
eLife 11:e72031.
https://doi.org/10.7554/eLife.72031

Share this article

https://doi.org/10.7554/eLife.72031

Further reading

    1. Epidemiology and Global Health
    2. Microbiology and Infectious Disease
    Bo Zheng, Bronner P Gonçalves ... Caoyi Xue
    Research Article

    Background:

    In many settings, a large fraction of the population has both been vaccinated against and infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, quantifying the protection provided by post-infection vaccination has become critical for policy. We aimed to estimate the protective effect against SARS-CoV-2 reinfection of an additional vaccine dose after an initial Omicron variant infection.

    Methods:

    We report a retrospective, population-based cohort study performed in Shanghai, China, using electronic databases with information on SARS-CoV-2 infections and vaccination history. We compared reinfection incidence by post-infection vaccination status in individuals initially infected during the April–May 2022 Omicron variant surge in Shanghai and who had been vaccinated before that period. Cox models were fit to estimate adjusted hazard ratios (aHRs).

    Results:

    275,896 individuals were diagnosed with real-time polymerase chain reaction-confirmed SARS-CoV-2 infection in April–May 2022; 199,312/275,896 were included in analyses on the effect of a post-infection vaccine dose. Post-infection vaccination provided protection against reinfection (aHR 0.82; 95% confidence interval 0.79–0.85). For patients who had received one, two, or three vaccine doses before their first infection, hazard ratios for the post-infection vaccination effect were 0.84 (0.76–0.93), 0.87 (0.83–0.90), and 0.96 (0.74–1.23), respectively. Post-infection vaccination within 30 and 90 days before the second Omicron wave provided different degrees of protection (in aHR): 0.51 (0.44–0.58) and 0.67 (0.61–0.74), respectively. Moreover, for all vaccine types, but to different extents, a post-infection dose given to individuals who were fully vaccinated before first infection was protective.

    Conclusions:

    In previously vaccinated and infected individuals, an additional vaccine dose provided protection against Omicron variant reinfection. These observations will inform future policy decisions on COVID-19 vaccination in China and other countries.

    Funding:

    This study was funded the Key Discipline Program of Pudong New Area Health System (PWZxk2022-25), the Development and Application of Intelligent Epidemic Surveillance and AI Analysis System (21002411400), the Shanghai Public Health System Construction (GWVI-11.2-XD08), the Shanghai Health Commission Key Disciplines (GWVI-11.1-02), the Shanghai Health Commission Clinical Research Program (20214Y0020), the Shanghai Natural Science Foundation (22ZR1414600), and the Shanghai Young Health Talents Program (2022YQ076).

    1. Epidemiology and Global Health
    Marina Padilha, Victor Nahuel Keller ... Gilberto Kac
    Research Article Updated

    Background:

    The role of circulating metabolites on child development is understudied. We investigated associations between children’s serum metabolome and early childhood development (ECD).

    Methods:

    Untargeted metabolomics was performed on serum samples of 5004 children aged 6–59 months, a subset of participants from the Brazilian National Survey on Child Nutrition (ENANI-2019). ECD was assessed using the Survey of Well-being of Young Children’s milestones questionnaire. The graded response model was used to estimate developmental age. Developmental quotient (DQ) was calculated as the developmental age divided by chronological age. Partial least square regression selected metabolites with a variable importance projection ≥1. The interaction between significant metabolites and the child’s age was tested.

    Results:

    Twenty-eight top-ranked metabolites were included in linear regression models adjusted for the child’s nutritional status, diet quality, and infant age. Cresol sulfate (β=–0.07; adjusted-p <0.001), hippuric acid (β=–0.06; adjusted-p <0.001), phenylacetylglutamine (β=–0.06; adjusted-p <0.001), and trimethylamine-N-oxide (β=–0.05; adjusted-p=0.002) showed inverse associations with DQ. We observed opposite directions in the association of DQ for creatinine (for children aged –1 SD: β=–0.05; pP=0.01;+1 SD: β=0.05; p=0.02) and methylhistidine (–1 SD: β = - 0.04; p=0.04;+1 SD: β=0.04; p=0.03).

    Conclusions:

    Serum biomarkers, including dietary and microbial-derived metabolites involved in the gut-brain axis, may potentially be used to track children at risk for developmental delays.

    Funding:

    Supported by the Brazilian Ministry of Health and the Brazilian National Research Council.