Extreme fetal growth, either restricted (IUGR) or large (LGA), is associated with epigenetic changes in hematopoietic stem/progenitor cells that may increase risk of adult diseases. The study found global shifts towards DNA hypermethylation in these cells from infants with IUGR or LGA compared to controls. There was a sexually dimorphic response, with IUGR associated with greater epigenetic dysregulation in males and LGA predominantly affecting females. The differentially methylated loci were enriched near genes involved in glucose homeostasis and stem cell function.

1. ARTICLE
Received 7 Jan 2014 | Accepted 8 Sep 2014 | Published 10 Oct 2014
Sexual dimorphism in epigenomic responses
of stem cells to extreme fetal growth
Fabien Delahaye1, N. Ari Wijetunga2, Hye J. Heo1, Jessica N. Tozour1, Yong Mei Zhao1, John M. Greally2
& Francine H. Einstein1
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 CD34þ 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.
DOI: 10.1038/ncomms6187
#epiroadmap-20 スライド① @n0rr
Density
0
7 7
50
100
150
200
0
100
200
300
400
Female
Male
IUGR/control LGA/control
NATURE COMMUNICATIONS | DOI: 1

2. 新生児の体重
IUGRとLGA
比較区の設定
今回調べた細胞
細胞の取り方
HELP-tagging assay
GSE53177の内訳
大きい/小さい児はメチル化されてた
性的２型
機能について
Cohort 2 で検証
まとめ
#epiroadmap-20 スライド② @n0rr

3. 06） 日本小児科学会雑誌 第114巻
新生児の体重
#epiroadmap-20 スライド③ @n0rr
日本小児科学会雑誌 114巻 8 号 1271 1293(2010年)

4. 06） 日本小児科学会雑誌 第114巻
IUGRとLGA
IUGR
LGA
在胎不当過大
子宮内胎児発育遅延
IUGR 小さい
LGA 大きい
#epiroadmap-20 スライド④ @n0rr
日本小児科学会雑誌 114巻 8 号 1271 1293(2010年)

5. associated epigenetic changes, the choice of cell type generally
represents a compromise between accessibility, purity, quantity
and mechanistic relevance. Unpurified peripheral blood
leukocytes have previously been studied in individuals whose
mothers were exposed prenatally to famine. Altered DNA
methylation of multiple sites within the differentially
methylated region of the imprinted Insulin-like growth factor 2
(IGF2) gene was found in subjects decades later13. Cord blood
leukocytes have also been used to demonstrate associations of
DNA methylation with in utero conditions and birth weight15,16.
Another commonly studied tissue type is the placenta, which
score of 0 indicating full methylation and 100 indicating complete
lack of methylation, based on a normalized ratio between tag
counts generated by the methylation-sensitive enzyme HpaII and
its methylation-insensitive isoschizomer MspI28. Based on quality
control measures (Methods and Supplementary Fig. 1), 993,514
loci are selected for further analyses. Of these, 10,043 loci
are defined as candidate differentially methylated loci using
batch-adjusted significance and degree of methylation difference
thresholds in comparisons of IUGR and LGA infants with the
normal birth weight controls. We observe a global relative
shift towards DNA hypermethylation in CD34þ HSPCs in both
Table 1 | Clinical cohort characteristics.
Cohort 1 Cohort 2
Control (n ¼ 20) IUGR (n ¼ 20) LGA (n ¼ 20) Control (n ¼ 8) IUGR (n ¼ 8) LGA (n ¼ 8)
Gestational age, weeks 39.3±0.3 38.7±0.4 39.2±0.2 39.1±0.5 38.7±0.4 39.8±0.3
Birth weight, g 3,150±64 2,515±69* 3,996 ±81* 3,150±161 2,498±78w 4,053±67*
Ponderal index, g cmÀ 3 2.8±0.03 2.3±0.04* 3.2±0.03* 2.8±0.07 2.3±0.04* 3.4±0.07*
% Male 50 50 50 50 50 50
Maternal age, years 24.6±0.9 26.5±1.3 31.1±1.1* 33.1±1.7 27.7±2.6w 31.5±1.6
Pre-pregnancy BMI, kg mÀ 2 26.6±1.3 25.5±0.9 29.0±1.3 27.0±2.1 26.5±2.8 28.5±1.4
Weight gain, pounds 29.4±2.7 23.0±2.7 29.9±2.1 27.0±5.1 12.7±5.1 24.8±2.9
BMI, body mass index; IUGR, intrauterine growth restriction; LGA, large for gestational age.
Showing mean±standard deviation values.
*Po0.001 compared with Control.
wPo0.05 compared with Control.
2 NATURE COMMUNICATIONS | 5:5187 | DOI: 10.1038/ncomms6187 | www.nature.com/naturecommunications
& 2014 Macmillan Publishers Limited. All rights reserved.
比較区の設定
Cohort 1
ゲノムワイドな解析に使う
HELP-tagging assay
IUGR 小さい児
LGA 大きい児
Cohort 2
Cohort 1 の検証に使う
MassArray
バイサルファイト-seq
IUGR 小さい
LGA 大きい
#epiroadmap-20 スライド⑤ @n0rr

6. 今回調べた細胞
臍帯血由来の造血幹細胞
#epiroadmap-20 スライド⑥ @n0rr
wikipedia より

7. 0
2
4
6
8
10
12
14
16
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
(×108) (×10 )
AutoMACS HP より
StemXVivo HPより
細胞の取り方
2x10^6 くらいしか取れない
#epiroadmap-20 スライド⑦ @n0rr
第38回造血幹細胞移植委員会(H25.3.15)資料3
HELP ta 1回 500ng = 8x10^5 必要
次世代シークエンス解析スタンダード p.176

8. 新生児の体重
IUGRとLGA
比較区の設定
今回調べた細胞
細胞の取り方
HELP-tagging assay
GSE53177の内訳
大きい/小さい児はメチル化されてた
性的２型
機能について
Cohort 2 で検証
まとめ
#epiroadmap-20 スライド⑧ @n0rr

9. HELP-tagging assay
HpaⅡ メチル化感受性
MspⅠ メチル化無視
#epiroadmap-20 スライド⑨ @n0rr

10. GSE53177の内訳
#epiroadmap-20 スライド⑩ @n0rr

11. 47.1 1.7 36.1
42.9 1.6 37.3
54.1 2.1 38.8
54.6 2.1 38.5
42.7 1.7 39.8
60.0 2.6 43.3
156.2 7.0 44.8
82.6 3.7 44.8
49.8 2.2 44.2
12.8 0.5 38.9
55.9 2.2 39.4
56.0 2.2 39.3
57.0 2.2 38.6
8.7 0.3 39.1
36.8 1.4 38.0
28.4 1.1 38.7
56.0 2.4 42.9
46.0 1.8 39.1
52.6 2.1 39.9
139.1 6.3 45.3
77.3 3.5 45.3
59.7 2.6 43.6
9.0 0.3 38.8
112.1 5.0 44.6
80.6 3.6 44.7
57.4 2.2 38.3
59.5 2.3 38.7
59.9 2.6 43.4
16.6 0.6 39.0
63.6 2.9 45.6
40.1 1.5 37.4
56.1 2.2 39.2
49.8 1.9 38.2
155.9 7.0 44.9
51.2 1.8 35.2
28.6 1.1 38.5
47.6 1.9 39.9
75.4 2.8 37.1
49.2 1.8 36.6
15.2 0.6 38.9
11.2 0.4 36.9
9.1 0.3 36.9
7.0 0.3 36.9
8.7 0.3 36.8
32.2 1.2 37.3
23.4 0.9 38.9
56.6 2.4 42.4
64.1 2.9 45.2
143.3 6.4 44.7
28.3 1.1 38.9
152.8 6.9 45.2
154.3 6.9 44.7
163.0 7.3 44.8
26.4 1.0 37.9
20.5 0.8 38.9
50.5 1.8 35.6
151.5 6.8 44.9
51.3 2.3 44.8
130.1 5.9 45.3
154.4 6.9 44.7
LGA(大) IUGR(小) ctrl
スポット数（M reads) データ量（G bases) 推定リード長（bp）
GSE53177の内訳
IUGR 小さい
LGA 大きい
#epiroadmap-20 スライド⑪ @n0rr

12. 新生児の体重
IUGRとLGA
比較区の設定
今回調べた細胞
細胞の取り方
HELP-tagging assay
GSE53177の内訳
大きい/小さい児はメチル化されてた
性的２型
機能について
Cohort 2 で検証
まとめ
#epiroadmap-20 スライド⑫ @n0rr

13. methylated loci compared with males (Fig. 2b). These findings
indicate a sexual dimorphism in the epigenetic responses of
HSPCs to the extremes of growth conditions in utero.
Targeting of DNA methylation changes to specific genomic
contexts. Although the consequences of DNA methylation
changes at recognized promoter sequences are generally pre-
dictable, a genome-wide study of this type can generate a majority
of findings in un-annotated genomic locations. To predict the
derived methylation scores for cases (IUGR and LGA
combined) are compared with controls to demonstrate the
magnitude of the change at this locus (Fig. 3b).
Targeting of DNA methylation changes to genes with specific
properties. 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
0
0.02
0.04
Density
0
0.02
0.04Density
0
0.02
0.04
Density
0 50 100
Methylation score
ControlIUGRLGA
1
3
5
7
Hypermethylation Hypomethylation
a b
c
IUGR/control LGA/control IUGR/LGA
4,645 223
–50 500
Methylation score
difference
5,560 588 1,051 1,571
–50 500
Methylation score
difference
–50 500
Methylation score
difference
–Log10(Pvalue)
d
IUGR/control
IUGR/LGA
LGA/control 980
1,189815
4,353
2,699
618
Control
IUGR
LGA
Figure 1 | Genome-wide DNA methylation profiles. (a) Density plots of methylation scores for IUGR or LGA compared with controls. The distributions of
DNA methylation scores are shown in red. (b) A self-organizing heatmap of candidate differentially methylated loci showing clustering by sample.
(c) Volcano plots of DNA methylation score differences for IUGR compared with control, LGA compared with control and IUGR compared with LGA, based
on 993,514 loci throughout the genome. Differentially methylated loci with P value o0.05 and methylation difference 4|20| are shown in black.
(d) Differentially methylated loci meeting threshold criteria are quantified in a proportional Venn diagram for each comparison.
NATURE COMMUNICATIONS | 5:5187 | DOI: 10.1038/ncomms6187 | www.nature.com/naturecommunications 3
大きい/小さい児はメチル化されてた
IUGR 小さい
LGA 大きい
#epiroadmap-20 スライド⑬ @n0rr

14. Methylation score difference Methylation score difference
–Log10(Pvalue)
Density
0
7
6
5
4
3
2
1
0
7
6
5
4
3
2
1
0
–60 –40 –20 0 20 40 60 –60 –40 –20 0 20 40 60
50
100
150
200
0
100
200
300
400
Female
Male
IUGR/control LGA/control
Figure 2 | Sexual dimorphism in IUGR males and LGA females for differentially methylated loci. The lower panels show volcano plots of DNA
methylation score differences, the upper panels quantify the densities of differentially methylated loci (P valueo0.05 using analysis of variance with
pairwise two-tailed Tukey-tests, methylation difference 4|20|). (a) IUGR compared with controls, (b) LGA compared with controls.
Repressive
Transcribed
0
1
2
137,215,000 137,220,000 137,225,000 137,230,000 137,235,000 137,240,000chr9
thylation
rence
control)
50
ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms6187
性的２型
IUGR 小さい
LGA 大きい
#epiroadmap-20 スライド⑭ @n0rr

15. 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 Po10À 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,
pathway and MAFA from the Maturity onset diabetes of the young
pathway (Supplementary Fig. 6). We find the direction of DNA
methylation changes to be concordant between genome-wide and
targeted assays for all three loci, with statistically significant dif-
ferences demonstrable for TBS data from WNT6 (P ¼ 0.023) and
PTCH1 (P ¼ 0.014; Supplementary Table 4). We also show the
PTCH1 and WNT6 genes to have increased DNA methylation by
TBS at local cis-regulatory elements in cases (IUGR and LGA)
compared with controls (Supplementary Table 4, Po0.05). Finally,
we interrogate loci associated with genes that are differentially
methylated on average between cases (IUGR plus LGA) and
KEGG: HH (Hedgehog) signaling pathway
Gene associated with IUGR
Gene associated with IUGR and LGA
Gene associated with LGA
PTCH1
KEGG: maturity onset diabetes of the young
PDX1
MAFA
WNT family
HH
homologues
Figure 4 | Network analysis. A network representation of KEGG pathways for (a) Maturity onset diabetes of the young and (b) Hedgehog (HH) signalling.
Nodes are colour- 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.
NATURE COMMUNICATIONS | 5:5187 | DOI: 10.1038/ncomms6187 | www.nature.com/naturecommunications 5
& 2014 Macmillan Publishers Limited. All rights reserved.
機能について
IUGR 小さい
LGA 大きい
#epiroadmap-20 スライド⑮ @n0rr

16. Supplementary Figure 4 Correlations between HELP-tagging and MassArray results
Correlation between HELP-tagging and bisulphite MassArray (Sequenom) is high for the control
loci shown. Standard error values for each type of assay at each locus are shown.
Primer
Methylation
Score
MassArray
Methylation
Score HELP-
Tagging
DL5.1 chr1 32704998 32704999 0.923±0.005 0±0.000
DL4.3 chr7 2661007 2661008 0.926±0.01 12.649±2.769
DL1.5 chr2 28830072 28830073 0.31±0.003 52.054±4.234
DL1.4 chr1 42204926 42204927 0.02±0.003 12.649±3.677
Locus
R²#=#0.97685#
0#
0.2#
0.4#
0.6#
0.8#
1#
0# 10# 20# 30# 40# 50# 60# 70# 80# 90#
MassArray'Methyla,on'Level'
HELP4tagging'Methyla, on'score'
R2=0.98
Supplementary Figure 5. Correlations between HELP-tagging and targeted bisulphite
sequencing (TBS) results
Cohort 2で検証
#epiroadmap-20 スライド⑯ @n0rr

17. まとめ
胎児期の環境が細胞に記憶されるのか調べた
新生児20人x3 の臍帯血からCD34+細胞もらった
HELP-tagging assay で993,514 loci みた
極端な胎児期を過ごした細胞は多くメチル化されていた
男児-小、女児-大のときメチル化されていた
#epiroadmap-20 スライド⑰ @n0rr