Evidence map›Paper›PMID 33048947›Full record

ArticlePLoS genetics2020

The DNA methylome of human sperm is distinct from blood with little evidence for tissue-consistent obesity associations.

Fredrika Åsenius, Tyler J Gorrie-Stone, Ama Brew, Yasmin Panchbhaya, Elizabeth Williamson, Leonard C Schalkwyk, Vardhman K Rakyan, Michelle L Holland, Sarah J Marzi, David J Williams

Open access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Epigenetics of Male Infertility: The Role of DNA Methylation.Frontiers in cell and developmental biology · 2021
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 7 institutions in 1 country.

Fredrika ÅseniusUCL EGA Institute for Women's Health, University College London, London, United Kingdom.ORCID 0000-0002-0393-0962
Tyler J Gorrie-StoneSchool of Biological Sciences, University of Essex, Colchester, United Kingdom.ORCID 0000-0002-1817-1495
Ama BrewThe Blizard Institute, Queen Mary University of London, London, United Kingdom.
Yasmin PanchbhayaUCL Genomics, Great Ormond Street Institute of Child Health, London, United Kingdom.
Elizabeth WilliamsonFertility & reproductive medicine laboratory, University College Hospital, London, United Kingdom.
Leonard C SchalkwykSchool of Biological Sciences, University of Essex, Colchester, United Kingdom.
Vardhman K RakyanThe Blizard Institute, Queen Mary University of London, London, United Kingdom.
Michelle L HollandDepartment of Medical and Molecular Genetics, School of Basic and Medical Biosciences, King's College London, London, United Kingdom.ORCID 0000-0003-0775-2902
Sarah J MarziUK Dementia Research Institute, Imperial College London, London, United Kingdom.ORCID 0000-0002-3924-2053
David J WilliamsUCL EGA Institute for Women's Health, University College London, London, United Kingdom.
Queen Mary University of London · GBUniversity College London · GBUniversity of Essex · GBGreat Ormond Street Hospital · GBKing's College London · GBUK Dementia Research Institute · GBUniversity College Hospital · GB

Funding

Department of HealthMedical Research Council MR/P011799/1
6 · The paper itself

Abstract

Epidemiological research suggests that paternal obesity may increase the risk of fathering small for gestational age offspring. Studies in non-human mammals indicate that such associations could be mediated by DNA methylation changes in spermatozoa that influence offspring development in utero. Human obesity is associated with differential DNA methylation in peripheral blood. It is unclear, however, whether this differential DNA methylation is reflected in spermatozoa. We profiled genome-wide DNA methylation using the Illumina MethylationEPIC array in a cross-sectional study of matched human blood and sperm from lean (discovery n = 47; replication n = 21) and obese (n = 22) males to analyse tissue covariation of DNA methylation, and identify obesity-associated methylomic signatures. We found that DNA methylation signatures of human blood and spermatozoa are highly discordant, and methylation levels are correlated at only a minority of CpG sites (~1%). At the majority of these sites, DNA methylation appears to be influenced by genetic variation. Obesity-associated DNA methylation in blood was not generally reflected in spermatozoa, and obesity was not associated with altered covariation patterns or accelerated epigenetic ageing in the two tissues. However, one cross-tissue obesity-specific hypermethylated site (cg19357369; chr4:2429884; P = 8.95 × 10-8; 2% DNA methylation difference) was identified, warranting replication and further investigation. When compared to a wide range of human somatic tissue samples (n = 5,917), spermatozoa displayed differential DNA methylation across pathways enriched in transcriptional regulation. Overall, human sperm displays a unique DNA methylation profile that is highly discordant to, and practically uncorrelated with, that of matched peripheral blood. We observed that obesity was only nominally associated with differential DNA methylation in sperm, and therefore suggest that spermatozoal DNA methylation is an unlikely mediator of intergenerational effects of metabolic traits.

Indexed as

AdolescentAdultBody Mass IndexChildChild, PreschoolCpG IslandsDNA MethylationDNA ReplicationEpigenesis, GeneticEpigenomeGene Expression ProfilingGene Expression RegulationGenome, HumanGestational AgeHumansInfant

Identifiers

PMID33048947
PMCPMC7584170
OpenAlexW3092304831

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.