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Sexual dimorphism in epigenomic responses of stem cells to extreme fetal growth.

Delahaye F, Wijetunga NA, Heo HJ, Tozour JN, Zhao YM, Greally JM, Einstein FH - Nat Commun (2014)

Bottom Line: We tested whether heritable epigenetic processes in long-lived CD34(+) haematopoietic stem/progenitor cells showed evidence for re-programming associated with the extremes of fetal growth.Here we show that both fetal growth restriction and over-growth are associated with global shifts towards DNA hypermethylation, targeting cis-regulatory elements in proximity to genes involved in glucose homeostasis and stem cell function.We find a sexually dimorphic response; intrauterine growth restriction is associated with substantially greater epigenetic dysregulation in males, whereas large for gestational age growth predominantly affects females.

View Article: PubMed Central - PubMed

Affiliation: Department of Obstetrics &Gynecology and Women's Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Block Building, Room 631, Bronx, New York 10461, USA.

ABSTRACT
Extreme fetal growth is associated with increased susceptibility to a range of adult diseases through an unknown mechanism of cellular memory. We tested whether heritable epigenetic processes in long-lived CD34(+) haematopoietic stem/progenitor cells showed evidence for re-programming associated with the extremes of fetal growth. Here we show that both fetal growth restriction and over-growth are associated with global shifts towards DNA hypermethylation, targeting cis-regulatory elements in proximity to genes involved in glucose homeostasis and stem cell function. We find a sexually dimorphic response; intrauterine growth restriction is associated with substantially greater epigenetic dysregulation in males, whereas large for gestational age growth predominantly affects females. The findings are consistent with extreme fetal growth interacting with variable fetal susceptibility to influence cellular ageing and metabolic characteristics through epigenetic mechanisms, potentially generating biomarkers that could identify infants at higher risk for chronic disease later in life.

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Network AnalysisA network representation of KEGG pathways for (a) Maturity onset diabetes of the young and (b) Hedgehog (HH) signaling. Nodes are color- and size-coded based on the association of genes represented by each node with LGA or IUGR, or with both LGA and IUGR. Edges (solid lines) represent known physical interaction between genes.
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Figure 4: Network AnalysisA network representation of KEGG pathways for (a) Maturity onset diabetes of the young and (b) Hedgehog (HH) signaling. Nodes are color- and size-coded based on the association of genes represented by each node with LGA or IUGR, or with both LGA and IUGR. Edges (solid lines) represent known physical interaction between genes.

Mentions: We test whether the subset of loci affected by DNA methylation changes are enriched at a specific subset of genes characterized by concordance of function of their protein products. A candidate differentially methylated locus is linked to a specific gene if the site is (a) located in proximity to the transcription start site of the RefSeq gene and (b) overlapping candidate regulatory loci (features 4 or 6). We select only those candidate promoters (feature 6) within ±2 kb and candidate enhancers (feature 4) within ±5 kb of RefSeq transcription start sites. While enhancers can act over substantially longer distances than 5 kb31, we are deliberately conservative in restricting the distance so that we would be more likely to associate an enhancer with the gene upon which it exerts its effects. The resulting list of genes is used to perform a gene set enrichment analysis (GSEA). Traditional GSEA does not take into account the physical characteristics of the gene and has been shown to be biased by factors such as the numbers of CG dinucleotide sites associated with different classes of gene and gene promoters32. To address this, the Bioconductor package GoSeq33 was developed to control for variability of length of genes. We adapted GoSeq to normalize our data to control for the number of CG dinucleotides linked to each gene by the above criteria. Detailed information describing the results of the normalized GSEA is shown in Supplementary Tables 1–2. Among the different significant pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes), two pathways of interest emerge as significant regardless of group comparison: the KEGG pathways for Maturity onset diabetes of the young, relevant to glucose homeostasis and Hedgehog (HH) signaling. Both of these pathways contain genes involved in proliferation, differentiation and self-renewal capabilities of stem cells. Permutation analysis was performed to confirm the significance of these results. Based on the criteria for assigning HpaII sites to RefSeq genes described above, the HELP-tagging assay represents 97.6% of RefSeq genes, so we randomly select from within this group of genes the same number of genes used to define our pathways, and perform the GSEA analysis 1,000 and 3,000 times to test how frequently the same pathways are identified as, defining the significance of our detection of these pathways as p<10−3. The same pathways are targeted by IUGR and LGA even when the loci involved are not identical (Fig. 4). A similar effect is seen for the loci affected differentially between males and females (Supplementary Fig. 3). These findings combine to show convergence of dysregulation of the same pathways by IUGR and LGA and in male and female subjects respectively, even though the loci targeted for DNA methylation changes are not necessarily the same in each group.


Sexual dimorphism in epigenomic responses of stem cells to extreme fetal growth.

Delahaye F, Wijetunga NA, Heo HJ, Tozour JN, Zhao YM, Greally JM, Einstein FH - Nat Commun (2014)

Network AnalysisA network representation of KEGG pathways for (a) Maturity onset diabetes of the young and (b) Hedgehog (HH) signaling. Nodes are color- and size-coded based on the association of genes represented by each node with LGA or IUGR, or with both LGA and IUGR. Edges (solid lines) represent known physical interaction between genes.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4197137&req=5

Figure 4: Network AnalysisA network representation of KEGG pathways for (a) Maturity onset diabetes of the young and (b) Hedgehog (HH) signaling. Nodes are color- and size-coded based on the association of genes represented by each node with LGA or IUGR, or with both LGA and IUGR. Edges (solid lines) represent known physical interaction between genes.
Mentions: We test whether the subset of loci affected by DNA methylation changes are enriched at a specific subset of genes characterized by concordance of function of their protein products. A candidate differentially methylated locus is linked to a specific gene if the site is (a) located in proximity to the transcription start site of the RefSeq gene and (b) overlapping candidate regulatory loci (features 4 or 6). We select only those candidate promoters (feature 6) within ±2 kb and candidate enhancers (feature 4) within ±5 kb of RefSeq transcription start sites. While enhancers can act over substantially longer distances than 5 kb31, we are deliberately conservative in restricting the distance so that we would be more likely to associate an enhancer with the gene upon which it exerts its effects. The resulting list of genes is used to perform a gene set enrichment analysis (GSEA). Traditional GSEA does not take into account the physical characteristics of the gene and has been shown to be biased by factors such as the numbers of CG dinucleotide sites associated with different classes of gene and gene promoters32. To address this, the Bioconductor package GoSeq33 was developed to control for variability of length of genes. We adapted GoSeq to normalize our data to control for the number of CG dinucleotides linked to each gene by the above criteria. Detailed information describing the results of the normalized GSEA is shown in Supplementary Tables 1–2. Among the different significant pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes), two pathways of interest emerge as significant regardless of group comparison: the KEGG pathways for Maturity onset diabetes of the young, relevant to glucose homeostasis and Hedgehog (HH) signaling. Both of these pathways contain genes involved in proliferation, differentiation and self-renewal capabilities of stem cells. Permutation analysis was performed to confirm the significance of these results. Based on the criteria for assigning HpaII sites to RefSeq genes described above, the HELP-tagging assay represents 97.6% of RefSeq genes, so we randomly select from within this group of genes the same number of genes used to define our pathways, and perform the GSEA analysis 1,000 and 3,000 times to test how frequently the same pathways are identified as, defining the significance of our detection of these pathways as p<10−3. The same pathways are targeted by IUGR and LGA even when the loci involved are not identical (Fig. 4). A similar effect is seen for the loci affected differentially between males and females (Supplementary Fig. 3). These findings combine to show convergence of dysregulation of the same pathways by IUGR and LGA and in male and female subjects respectively, even though the loci targeted for DNA methylation changes are not necessarily the same in each group.

Bottom Line: We tested whether heritable epigenetic processes in long-lived CD34(+) haematopoietic stem/progenitor cells showed evidence for re-programming associated with the extremes of fetal growth.Here we show that both fetal growth restriction and over-growth are associated with global shifts towards DNA hypermethylation, targeting cis-regulatory elements in proximity to genes involved in glucose homeostasis and stem cell function.We find a sexually dimorphic response; intrauterine growth restriction is associated with substantially greater epigenetic dysregulation in males, whereas large for gestational age growth predominantly affects females.

View Article: PubMed Central - PubMed

Affiliation: Department of Obstetrics &Gynecology and Women's Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Block Building, Room 631, Bronx, New York 10461, USA.

ABSTRACT
Extreme fetal growth is associated with increased susceptibility to a range of adult diseases through an unknown mechanism of cellular memory. We tested whether heritable epigenetic processes in long-lived CD34(+) haematopoietic stem/progenitor cells showed evidence for re-programming associated with the extremes of fetal growth. Here we show that both fetal growth restriction and over-growth are associated with global shifts towards DNA hypermethylation, targeting cis-regulatory elements in proximity to genes involved in glucose homeostasis and stem cell function. We find a sexually dimorphic response; intrauterine growth restriction is associated with substantially greater epigenetic dysregulation in males, whereas large for gestational age growth predominantly affects females. The findings are consistent with extreme fetal growth interacting with variable fetal susceptibility to influence cellular ageing and metabolic characteristics through epigenetic mechanisms, potentially generating biomarkers that could identify infants at higher risk for chronic disease later in life.

Show MeSH
Related in: MedlinePlus