Evidence map›Paper›PMID 31246962›Full record

ArticlePloS one2019

Male obesity effects on sperm and next-generation cord blood DNA methylation.

Ramya Potabattula, Marcus Dittrich, Martin Schorsch, Thomas Hahn, Thomas Haaf, Nady El Hajj

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 5% 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

33 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. A Review of the Effects of Maternal and Paternal Obesity on Neurodevelopmental Disorders and Related Neurobiology in Rodent and Human Offspring.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026
    Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Male aging in germ cells: What are we inheriting?Genetics and molecular biology · 2025
    Article
  11. Review
  12. Article
  13. Food science & nutrition · 2024
    Article
  14. Article
  15. Childhood obesity from the genes to the epigenome.Frontiers in endocrinology · 2024
    Review
  16. Article
  17. Review
  18. Article
  19. Review
  20. Article
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

6 authors at 2 institutions in 3 countries.

Ramya PotabattulaInstitute of Human Genetics, Julius Maximilians University, Würzburg, Germany.
Marcus DittrichInstitute of Human Genetics, Julius Maximilians University, Würzburg, Germany.
Martin SchorschFertility Center; Wiesbaden, Germany.
Thomas HahnFertility Center; Wiesbaden, Germany.
Thomas HaafInstitute of Human Genetics, Julius Maximilians University, Würzburg, Germany.
Nady El HajjInstitute of Human Genetics, Julius Maximilians University, Würzburg, Germany.ORCID 0000-0003-3420-8531
New Hope Fertility Center · USHamad bin Khalifa University · QA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prevalence of metabolic disorders, in particular obesity has dramatically increased worldwide. Genetic variants explain only a minor part of the obesity epidemic induced by physical inactivity and over-nutrition. Epidemiological studies in humans and animal models indicate that epigenetic changes associated with adverse parental and/or intrauterine factors may contribute to the missing heritability of metabolic disorders. Possible adverse paternal effects are likely transmitted by sperm to the next-generation. To investigate this hypothesis, we have systematically analyzed the effects of male body mass index (BMI) on sperm epigenome and its association with next-generation fetal cord blood (FCB) DNA methylation. Methylation levels of maternally imprinted (PEG1, PEG4, PEG5, and PEG10), paternally imprinted (H19-IG DMR, IGF2-DMR0, and MEG3-IG DMR) regions, and obesity-related non-imprinted HIF3A gene were quantified by bisulphite pyrosequencing in sperm samples of 294 human donors undergoing in vitro fertilization or intracytoplasmic sperm injection, and in 113 FCBs of the resulting offspring. Multivariable regression analyses revealed that MEG3 intergenic differentially methylated region (IG DMR) showed positive correlation between sperm methylation and donor's BMI. A gender-specific correlation between paternal BMI and FCB methylation was observed for MEG3-IG DMR, HIF3A, and IGF2-DMR0. The former two genes displayed same directional nominal association (as sperm) between paternal BMI and FCB methylation in male offspring. Hypomethylation of IGF2-DMR0 with increased paternal BMI was observed in FCBs from female offsprings. Our results suggest that male obesity is nominally associated with modification of sperm DNA methylome in humans, which may affect the epigenome of the next-generation. Nevertheless, it is important to note that none of the associated p-values survived multiple testing adjustments. Future work should test the effect of associated methylation aberrations in the offspring as DNA methylation was shown to control expression and/or imprint establishment across the studied genes.

Indexed as

DNA MethylationAnimalsApoptosis Regulatory ProteinsBody Mass IndexEpigenesis, GeneticFemaleFetal BloodGenomic ImprintingHigh-Throughput Nucleotide SequencingHumansInsulin-Like Growth Factor IIMaleObesityRepressor ProteinsRNA, Long NoncodingSpermatozoaApoptosis Regulatory ProteinsHIF3A protein, humanIGF2 protein, humanInsulin-Like Growth Factor IIMEG3 non-coding RNA, humanRepressor ProteinsRNA, Long Noncoding

Identifiers

PMID31246962
PMCPMC6597061
OpenAlexW2955321591

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.