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Logo of bmcmedgenoBioMed Centralsearchsubmit a manuscriptregisterthis articleBMC Medical Genomics
 
BMC Med Genomics. 2012; 5: 10.
Published online Apr 12, 2012. doi:  10.1186/1755-8794-5-10
PMCID: PMC3359247
DNA methylation differences at growth related genes correlate with birth weight: a molecular signature linked to developmental origins of adult disease?
Nahid Turan,#1 Mohamed F Ghalwash,#2 Sunita Katari,1 Christos Coutifaris,3 Zoran Obradovic,2 and Carmen Sapienzacorresponding author1,4
1Fels Institute for Cancer Research and Molecular Biology, Temple University School of Medicine, Philadelphia, PA 19140, USA
2Center for Information Science and Technology, Temple University, Philadelphia, PA 19122, USA
3Department of Obstetrics & Gynecology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
4Department of Pathology and Laboratory Medicine, Temple University School of Medicine, Philadelphia, PA 19140, USA
corresponding authorCorresponding author.
#Contributed equally.
Nahid Turan: nturan/at/temple.edu; Mohamed F Ghalwash: mohamed.ghalwash/at/temple.edu; Sunita Katari: dandusunita/at/gmail.com; Christos Coutifaris: CCoutifaris/at/obgyn.upenn.edu; Zoran Obradovic: zoran.obradovic/at/temple.edu; Carmen Sapienza: sapienza/at/temple.edu
Received December 8, 2011; Accepted April 12, 2012.
Abstract
Background
Infant 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.
Methods
We 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.
Results
We 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.
Conclusions
Single 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.
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