Evidence map›Paper›PMID 22498030›Full record

ArticleBMC medical genomics2012

DNA methylation differences at growth related genes correlate with birth weight: a molecular signature linked to developmental origins of adult disease?

Nahid Turan, Mohamed F Ghalwash, Sunita Katari, Christos Coutifaris, Zoran Obradovic, Carmen Sapienza

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 3 pooled it
15.3field-weighted citation impact, top 1% 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

53 citing papers in PubMed, 3 syntheses or guidelines pooled it, 105 citations in OpenAlex.

  1. Pooled it
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  11. A single-nucleotide-polymorphism in the 5'-flanking region ofTherapeutic advances in medical oncology · 2022
    Article
  12. Extensive Placental Methylation Profiling in Normal Pregnancies.International journal of molecular sciences · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. Creation of a Prognostic Risk Prediction Model for Lung Adenocarcinoma Based on Gene Expression, Methylation, and Clinical Characteristics.Medical science monitor : international medical journal of experimental and clinical research · 2020
    Article
  17. Article
  18. Article
  19. Genetics and Epigenetics of Infertility and Treatments on Outcomes.The Journal of clinical endocrinology and metabolism · 2019
    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 1 country.

Nahid TuranFels Institute for Cancer Research and Molecular Biology, Temple University School of Medicine, Philadelphia, PA 19140, USA.
Mohamed F Ghalwash
Sunita Katari
Christos Coutifaris
Zoran Obradovic
Carmen Sapienza
Temple University · USUniversity of Pennsylvania · US

Funding

Research Project 4: Epigenetic Regulation of Retrotransposon Silencing and Male Fertility in the MouseP50HD068157 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI Suneeta Senapati · 2014 to 2026
$16.3M
Stability of epigenetic structures in ART childrenR01HD048730 · NICHD · TEMPLE UNIV OF THE COMMONWEALTH · PI SAPIENZA, CARMEN · 2006 to 2010
$2.5M
NICHD NIH HHS 3 R01 HD048730-04S1NICHD NIH HHS P50 HD068157NICHD NIH HHS R01 HD048730
6 · The paper itself

Abstract

backgroundInfant birth weight is a complex quantitative trait associated with both neonatal and long-term health outcomes. Numerous studies have been published in which candidate genes (IGF1, IGF2, IGF2R, IGF binding proteins, PHLDA2 and PLAGL1) have been associated with birth weight, but these studies are difficult to reproduce in man and large cohort studies are needed due to the large inter individual variance in transcription levels. Also, very little of the trait variance is explained. We decided to identify additional candidates without regard for what is known about the genes. We hypothesize that DNA methylation differences between individuals can serve as markers of gene "expression potential" at growth related genes throughout development and that these differences may correlate with birth weight better than single time point measures of gene expression.

methodsWe performed DNA methylation and transcript profiling on cord blood and placenta from newborns. We then used novel computational approaches to identify genes correlated with birth weight.

resultsWe identified 23 genes whose methylation levels explain 70-87% of the variance in birth weight. Six of these (ANGPT4, APOE, CDK2, GRB10, OSBPL5 and REG1B) are associated with growth phenotypes in human or mouse models. Gene expression profiling explained a much smaller fraction of variance in birth weight than did DNA methylation. We further show that two genes, the transcriptional repressor MSX1 and the growth factor receptor adaptor protein GRB10, are correlated with transcriptional control of at least seven genes reported to be involved in fetal or placental growth, suggesting that we have identified important networks in growth control. GRB10 methylation is also correlated with genes involved in reactive oxygen species signaling, stress signaling and oxygen sensing and more recent data implicate GRB10 in insulin signaling.

conclusionsSingle time point measurements of gene expression may reflect many factors unrelated to birth weight, while inter-individual differences in DNA methylation may represent a "molecular fossil record" of differences in birth weight-related gene expression. Finding these "unexpected" pathways may tell us something about the long-term association between low birth weight and adult disease, as well as which genes may be susceptible to environmental effects. These findings increase our understanding of the molecular mechanisms involved in human development and disease progression.

Indexed as

DNA MethylationAdultAnimalsBirth WeightComputational BiologyFemaleFetal BloodGene Expression ProfilingGRB10 Adaptor ProteinHumansInfant, NewbornMiceMSX1 Transcription FactorPhenotypePlacentaPregnancyGRB10 Adaptor ProteinGRB10 protein, humanMSX1 protein, humanMSX1 Transcription Factor

Identifiers

PMID22498030
PMCPMC3359247
OpenAlexW2103957974

What OpenQuestion holds

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LicenceCC BY
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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.