Abstract
The DNA methylation of human offspring can change due to the use of
assisted reproductive technology (ART). In order to find the
differentially methylated regions (DMRs) in ART newborns, cord blood
maternal cell contamination and parent DNA methylation background,
which will add noise to the real difference, must be removed. We
analyzed newborns’ heel blood from six families to identify the DMRs
between ART and natural pregnancy newborns, and the genetic model of
methylation was explored, meanwhile we analyzed 32 samples of umbilical
cord blood of infants born with ART and those of normal pregnancy to
confirm which differences are consistent with cord blood data. The DNA
methylation level was lower in ART-assisted offspring at the whole
genome-wide level. Differentially methylated sites, DMRs, and cord
blood differentially expressed genes were enriched in the important
pathways of the immune system and nervous system, the genetic patterns
of DNA methylation could be changed in the ART group. A total of three
imprinted genes and 28 housekeeping genes which were involved in the
nervous and immune systems were significant different between the two
groups, six of them were detected both in heel blood and cord blood. We
concluded that there is an ART-specific DNA methylation pattern
involved in neuro- and immune-system pathways of human ART neonates,
providing an epigenetic basis for the potential long-term health risks
in ART-conceived neonates.
Keywords: human offspring, differentially methylated regions,
housekeeping gene, assisted reproductive technology, DNA methylation
pattern, imprinted gene
Introduction
Assisted reproductive technology (ART) involves fertilizing a human egg
in vitro and the transplantation of the resulting embryo into the
uterus for conception ([39]Van Voorhis, 2007; [40]Belva et al., 2016;
[41]Boulet et al., 2016; [42]De Geyter et al., 2018). Decades after the
first successful application of ART in humans, over 8 million infants
have been born with ART assistance worldwide ([43]Wade et al., 2015;
[44]Rao et al., 2018; [45]Fauser, 2019; [46]Leaver and Wells, 2019).
ART has become well-accepted and popular in recent years ([47]Liu et
al., 2015; [48]Simopoulou et al., 2018; [49]Gleicher et al., 2019).
Epidemiological and animal experiments show that the early stage of
fetal development is particularly sensitive to changes in the
environment and that the environmental abnormalities suffered during
this period may lead to problems later in life ([50]Faulk and Dolinoy,
2011; [51]Hanson and Gluckman, 2014; [52]Grandjean et al., 2015;
[53]Heindel et al., 2017; [54]Li T. et al., 2019). During this
sensitive period, adverse environmental stimulation may affect cell
proliferation and lineage differentiation by affecting normal
epigenetic reprogramming processes, leading to abnormal epigenetic
modification levels and permanent changes in gene expression patterns
([55]Yamazaki et al., 2003; [56]Hanson and Gluckman, 2014; [57]Nelissen
et al., 2014; [58]Koot et al., 2016). ART treatments, such as exposure
to culture medium and gamete or embryo freezing, may affect DNA
methylation reprogramming and embryonic development ([59]de Waal et
al., 2015; [60]Canovas et al., 2017b; [61]Mani and Mainigi, 2018;
[62]Argyraki et al., 2019). Zoological and embryological studies have
revealed that ART can affect the DNA methylation pattern and the
expression of imprinted genes in mouse, pig, and bovine embryos
([63]Wright et al., 2011; [64]de Waal et al., 2014; [65]Anckaert and
Fair, 2015; [66]Salilew-Wondim et al., 2015; [67]Canovas et al., 2017a;
[68]Hattori et al., 2019). Additionally, epidemiological studies have
reported the abnormal development of the immune system ([69]Tan et al.,
2016; [70]Kollmann et al., 2017; [71]Pathare et al., 2017), increased
risk of neurological diseases, the presence of metabolic abnormalities,
and the presence of congenital anomalies in ART-assisted human
offspring, including autism spectrum disorders, intellectual
disability, specific congenital heart defects, cardiovascular disease,
and metabolic disorder ([72]Sandin et al., 2013; [73]Tararbit et al.,
2013; [74]Guo et al., 2017; [75]Liu et al., 2017).
More and more observations of rising health risks in ART-conceived
neonates have linked ART technology to potential epigenetic abnormities
([76]Tararbit et al., 2013; [77]Guo et al., 2017). Previous works only
focused on the epigenetic influence of ART on a limited numbers of
genes. Recent works reported the impact of ART on genome-wide DNA
methylation. Nevertheless, the DNA methylation of ART processes has not
been fully elucidated, and parental background has not been considered.
Several studies showed that ART was associated with diverse DNA
methylation changes in human offspring ([78]Melamed et al., 2015;
[79]Castillo-Fernandez et al., 2017; [80]DeAngelis et al., 2018;
[81]Menezo et al., 2019). However, these observations were primary and
these studies analyzed DNA methylation from cord blood data, which
contained maternal cell contamination ([82]Lo et al., 1996, [83]2000)
affecting the results of the methylation data analyses ([84]Houseman et
al., 2012; [85]Bakulski et al., 2016; [86]Jones et al., 2017; [87]Lin
et al., 2018). Therefore, a mixture of cord blood samples may result in
high background and unclear data of DNA methylation.
Herein, as shown in [88]Figure 1A, by using the heel blood of the
ART-conceived newborns and removing the background DNA methylation
level of parents, we are able to perform a more accurate and reliable
analysis of DNA methylation with low background noise. Heel prick blood
sampling enables us to identify ART-specific DNA methylation pattern
changes precisely, objectively, and accurately.
FIGURE 1.
[89]FIGURE 1
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Genome-wide DNA hypomethylation pattern in assisted reproductive
technology (ART)-conceived infants. (A) Graphical overview of the study
design. (B) The distribution of DNA methylation showed that the two
groups had a similar pattern at the genome level. Mean (C) and median
(D) DNA methylation levels. DNA methylation ratio distribution of the
control (E) and ART group (F).
Materials and Methods
Editorial Policies and Ethical Considerations
All samples were obtained in the Center for Reproductive Medicine,
Peking University Third Hospital. All blood samples were obtained after
written informed patient consent and were fully anonymized. The studies
involving human participants were reviewed and approved by The
Reproductive Study Ethics Committee of Peking University Third Hospital
(approved protocol no. 201752-044). The participants’ parents and legal
guardians provided written informed consent to participate in this
study.
Participants and Study Design
We collected information on three families who had assisted
reproductive pregnancies and three families who normal pregnancies. All
families had twins by cesarean birth. The heel blood of neonates was
collected 3 days after birth. The peripheral blood of parents was
stored in an EDTA blood collection vessel. The Illumina Methylation
450K array was performed on all samples. Meanwhile, we analyzed the
RNA-seq data we recently uploaded to the GEO database which we
collected from umbilical cord blood of 32 newborns who underwent
IVF-ET, IVF-FET, ICSI-ET, ICSI-FET, and normal pregnancy.
Characteristics of the ART and Control Groups
The gestational age of the newborns at birth was 34–38 weeks. All the
newborns in the three ART families and three control families were
delivered by cesarean section. Neither parent had a history of familial
hereditary diseases, these details are shown in [91]Table 1.
TABLE 1.
Detailed information on Control and assisted reproductive technology
(ART) samples.
Control 1 Control 2 Control 3 Control 4 Control 5 Control 6 ART1 ART2
ART3 ART4 ART5 ART6
Family ID Control Family 1 Control Family 1 Control Family 2 Control
Family 2 Control Family 3 Control Family 3 ART Family 1 ART Family 1
ART Family 2 ART Family 2 ART Family 3 ART Family 3
Cesarean birth Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Gestational age 36 36 37 37 34 34 37 37 38 38 34 34
Infant body length 47 cm 47 cm 48 cm 48 cm 43 cm 41 cm 47 cm 45 cm 49
cm 48 cm 44 cm 44 cm
Infant weight 2560 g 2600 g 2600 g 2810 g 2250 g 1810 g 2740 g 2220 g
2940 g 2830 g 1980 g 2010 g
Sex Female Female Male Male Male Male Female Female Female Female Male
Male
Father’s age – – – – 26 26 40 40 33 33 – –
Mother’s age 28 28 30 30 25 25 38 38 32 32 27 27
Mother’s weight 82 kg 82 kg 66.5 kg 66.5 kg 82 kg 82 kg 68 kg 68 kg
74.5 kg 74.5 kg 77 kg 77 kg
Mother’s height 161 cm 161 cm 163 cm 163 cm 172 cm 172 cm 167 cm 167 cm
169 cm 169 cm 162 cm 162 cm
Weight gain during pregnancy 18.5 kg 18.5 kg 18.5 kg 18.5 kg 20 kg 20
kg 7.5 kg 7.5 kg 15 kg 15 kg 18 kg 18 kg
Hereditary diseases None None None None None None None None None None
None None
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DNA Extraction
Genomic DNA was extracted using the QIAamp DNA Mini Kit (QIAGEN 51304,
Germany) according to the manufacturer’s instructions.
Methylation Microarray Analysis
Genomic DNA (1 μg) was bisulfite-converted using the EZ DNA
Methylation-Gold Kit (ZYMO RESEARCH, D5005, FosterCity, California,
United States). Then DNA was whole-genome-amplified, enzymatically
fragmented, purified, and applied to the Illumina Infinium Methylation
450K array according to the Illumina methylation protocol.
Analysis of the Methylation Microarray Data
DNA methylation files were processed and normalized by R software
packages using the “Illumina Methylation Analyzer (IMA)” package. For
each of the samples, CpG sites with a detection p-value less than 0.05
were excluded from the analysis. In addition, probes with SNPs or their
single base extension, X chromosome and Y chromosome at the CpG site
were excluded. Differences in global DNA methylation levels between the
ART and control groups were analyzed by the Wilcoxon test. The standard
DMSs between the ART and control groups were δ beta| > 0.2 and p < 0.05
(Wilcoxon test). DMRs analysis used QDMR Tutorial software ([93]Zhang
et al., 2011).
Chromosome distribution differences were analyzed by the Wilcoxon test.
Cluster analysis and visualization were performed using pheatmap (R
package). Heel blood DNA methylation pathway enrichment analysis was
performed by IPA. Information on imprinted genes was obtained from the
gene imprint website.^[94]1 Information on housekeeping genes was
obtained from [95]Eisenberg and Levanon (2013).
Analysis of RNA-Seq Data
Downloaded raw fastq data were firstly processed using Trimmomatic
(version 0.36) to remove the library adapter, low-quality bases, and
reads smaller than 50 bases. The retained reads were mapped to the Homo
sapiens reference genome (human GRCh38/hg38) using STAR (version
2.5.3a) with the default parameters, and read counting was performed
using featureCounts (version 1.6.3). Finally, DEseq2 (version 1.26.0)
was used to obtain the normalized count matrix for all samples. GO
enrichment analysis was carried out using the R/Bioconductor package
ChIPseeker ([96]Houseman et al., 2012; version 1.10.3).
Results
The Whole Genome-Wide Methylation Differences in ART-Conceived and Naturally
Conceived Neonates
In order to compare the differences of global methylation level between
ART and naturally conceived newborns, we first analyzed the genome-wide
methylation patterns. The overall DNA methylation beta value showed
similar distribution patterns among all samples ([97]Figure 1B and
[98]Supplementary Figure 1). However, the global DNA methylation level
was lower in the ART group (
[MATH: β¯ :MATH]
ART = 0.504 ± 0.003 versus
[MATH: β¯ :MATH]
ctrl = 0.508 ± 0.003). Further analysis of the mean ([99]Figure 1C) and
median ([100]Figure 1D) DNA methylation beta values of individuals
confirmed this observation.
After the methylation beta level (0–1) was divided into approximately
20 intervals, the results revealed that such hypomethylation in the ART
group was mainly caused by the decreased ratio in CpG sites with high
DNA methylation levels (methylation beta level > 0.85), with 29.61% in
the ART group and 30.52% in the control group, and the increased ratio
in the CpG site with low and medium DNA methylation levels (methylation
beta level < 0.85), with 70.39% in the ART group and 69.48% in the
control group ([101]Figures 1E,F).
Differential Methylation Sites Were Enriched in Important Pathways of the
Immune and Nervous Systems
As shown in [102]Figure 2A, a total of 301 differential methylation
sites (DMSs) were screened as described in the “Materials and Methods”
part. The number of hypomethylated DMSs counted for 178, and the number
of hypermethylated DMSs was 123 (59 versus 41%; [103]Figure 2B), which
was consistent with the analysis of demethylation at the genome-wide
level mentioned. The beta value analysis of the DMSs for each sample
showed this tendency more clearly. The mean beta values of differential
hypomethylation sites in the ART group were 0.418 ± 0.032 and 0.730 ±
0.007 in the control group ([104]Figure 2C). The mean beta values of
differential hypermethylation sites in the ART group were 0.702 ± 0.018
and 0.372 ± 0.0124 in the control group ([105]Figure 2D). Through t-SNE
analysis, the DMSs can significantly divide the ART and control infants
into two groups ([106]Figure 2E).
FIGURE 2.
[107]FIGURE 2
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Differential methylation analysis showed that the number of
hypomethylation sites in ART-conceived infants was significantly higher
than the number of hypermethylation sites. (A) Distribution of
differences in DNA methylation levels between the two groups of
infants. (B) The ratio of sites with hypomethylation differences and
hypermethylation differences was 59:41. Distribution of methylation
levels at different sites of hypomethylation (C) and hypermethylation
(D). (E) tSNE analysis of differentially methylated sites (DMSs).
DMSs were significantly enriched in the S shelf and open sea based on
their relationship with CpG islands ([109]Figures 3A,B) and gene bodies
and intergenic regions based on the nearest genes ([110]Figures 3C,D).
Specifically, they were represented in the CpG islands, TSS1500,
TSS200, 5′UTR, and 1st exon. These findings further indicated that the
ART-assisted and control groups shared similar methylation patterns
with specific differences.
FIGURE 3.
[111]FIGURE 3
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Non-randomized effects of ART on DNA methylation patterns were
associated with early infant development. The distribution of
hypomethylated (A) and hypermethylated DMSs (B) affected by ART in
relation to the nearest CpG island. The distribution of hypomethylated
(C) and hypermethylated DMSs (D) affected by ART in relation to the
nearest genes. (E) Heatmap derived from supervised cluster analysis of
DMSs. The red color in the heatmap indicates hypermethylation values,
and blue indicates hypomethylation values.
Furthermore, the DMSs we identified could be used to classify the ART
group and control group by supervised cluster analysis. Six ART infants
were clustered together, and six control infants were grouped together
at the top of the cluster tree ([113]Figure 3E). Further, we discovered
several consistent patterns when DMSs were clustered into six subgroups
(C1–C6) based on supervised clusters. The methylation levels of DMSs in
the C1, C4, and C5 subgroups were relatively conservative in all six
control infants (C1: hypomethylation in nearly all sites, C4 and C5:
hypermethylation in nearly all sites) but with high randomness and
diversity in the six ART infants (different samples had different
methylation levels at the same site). In contrast, the methylation
levels of DMSs in the C2, C3, and C6 subgroups were greatly
heterogeneous among the six control infants (different samples had
different methylation levels at the same site) but with high
consistency in the six ART infants (C2 and C3: hypermethylation in
nearly all sites, C6: hypomethylation in nearly all sites).
Additionally, all loci were statistically analyzed for the degree of
dispersion to confirm our results. In parts C1, C4, and C5, the
scattering degree (SD) value of the ART group was larger, while that of
the control group was more conservative. In parts C2, C3, and C6, the
SD value of the ART group was smaller, while that of the control group
was larger ([114]Supplementary Table 1). Furthermore, ingenuity pathway
analysis (IPA) showed that DMSs were enriched in key pathways, e.g.,
(1) the “Ceramide Degradation” and “Catecholamine Biosynthesis”
pathways were well associated with nervous system development and nerve
signals transfer; (2) the “Antigen Presentation Pathway,” “Th1
Pathway,” and “Th2 Pathway” were important pathways related to immune
system establishment; (3) “NAD Biosynthesis III,” “NAD Salvage Pathway
III,” and “NAD Biosynthesis” played key roles in metabolic development.
Importantly, the pathway analysis results were consistent with clinical
manifestations, such as with a cognitive development problem and a
higher risk of autism in ART-conceived infants ([115]Fountain et al.,
2015; [116]Rumbold et al., 2017; [117]Berntsen et al., 2019).
Immune- and Nervous-System Pathways Were Identified by Differential
Methylation Regions Analysis and Cord Blood RNA-Seq
DNA methylation usually functioned in a region, we identified
differentially methylated regions (DMRs) to find their functional
association. Interestingly, DMRs analysis showed similar results with
DMSs. The obtained DMRs were highly enriched in the regulation of
neuron differentiation processes, antigen presentation, and other
important developmental pathways ([118]Supplementary Figure 2).
Moreover, 10 of the 301 DMSs with the most remarkable differences in
methylation beta values could be used to divide the two groups in the
principal component analysis (PCA) ([119]Supplementary Figure 3). These
10 most susceptible sites included 7 genes, namely, ZNF137, TAP2,
RBM28, NUDT1, NMNAT3, EIF3E, and AFAP1 ([120]Supplementary Table 2).
Among the above genes, four genes were involved in neurological and
immune-related functions: (1) TAP2 was related to the expression of
major histocompatibility complex (MHC) class I molecules and the
development of insulin-dependent diabetes mellitus ([121]Qu et al.,
2007; [122]Qiu et al., 2015; [123]Praest et al., 2018); (2) RBM28 was
related to progressive neurological defects and endocrinopathy
([124]Nousbeck et al., 2008); (3) NUDT1 was related to
neurodegeneration ([125]Pudelko et al., 2017; [126]Haruyama et al.,
2019); (4) NMNAT3 encoded a member of the nicotinamide/nicotinic acid
mononucleotide adenylyltransferase family and played a neuroprotective
role as a molecular chaperone ([127]Galindo et al., 2017).
Collectively, these results suggested that DNA methylation in ART
offspring could be changed and that these changes were enriched in
development-related pathways, particularly in the nervous, immune, and
metabolic systems.
The Opposite Genetic Pattern of DNA Methylation Between ART and Normal
Pregnancy Infants
We have confirmed that the DNA methylation pattern of ART infants was
different from that of normal pregnant infants through DMSs, DMRs, and
DEGs analyses, further, we want to confirm whether these epigenetic
differences are influenced by parental heredity. As shown in
[128]Figure 4, we analyzed C1–C6 separately and combined them with
their parents, then we found that the difference of DNA methylation
pattern between ART and natural pregnancy infants also existed in their
parents (heatmap, C1–C6), however, the genetic pattern of ART infants
was opposite compared to normal pregnancy infants (boxplot, C1–C6 and
histogram C1–C6). When we removed the background DNA methylation level
of parents, we found that in C1–C3 ([129]Figure 4A) the methylation
level of normal pregnancy infants tended toward hypomethylation
compared with their parents, however, there was a trend of
hypermethylation in ART infants compared with their parents. In C4–C6
([130]Figure 4B), the methylation level of normal pregnancy infants
tended toward hypermethylation compared with their parents, however,
there was a trend of hypomethylation in ART infants compared with their
parents. All the opposite genetic patterns had significant statistical
difference (p < 0.001).
FIGURE 4.
[131]FIGURE 4
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The opposite genetic pattern of DNA methylation between ART and normal
pregnancy infants. (A) In C1–C3, the methylation level of normal
pregnancy infants tended toward hypomethylation compared with their
parents, however, there was a trend of hypermethylation in ART infants
compared with their parents. (B) In C4–C6, the methylation level of
normal pregnancy infants tended toward hypermethylation compared with
their parents, however, there was a trend of hypomethylation in ART
infants compared with their parents. All the opposite genetic patterns
had significant statistical difference (p < 0.001).
The Discovery of Imprinted Genes and Housekeeping Genes Changes Can Be Found
in RNA-Seq of Cord Blood
As described above, ART could specifically affect the conservativeness
of the DNA methylation pattern. Imprinted genes and housekeeping genes
were conserved in genetic processes and played important roles in
development. In a comparison involving the imprinted and housekeeping
gene database, we identified 3 DMSs located in 2 imprinted genes
([133]Table 2) and 28 DMSs located in 26 housekeeping genes ([134]Table
3). The two imprinted genes included: (1) NTM, which encoded a protein
of the IgLON family with specific expression in the brain that promotes
neurite outgrowth and adhesion via a homophilic mechanism ([135]Li et
al., 2015; [136]Maruani et al., 2015); (2) BRUNOL4, which was related
to variable splicing of precursor RNA and its editing and normal
function of the nervous system ([137]Wang et al., 2016; [138]An et al.,
2019). Among the housekeeping genes, CASP7, RBM28, and FEZ2 were
associated with the maintenance of nerve function ([139]Nousbeck et
al., 2008; [140]Choudhury et al., 2015; [141]Hapairai et al., 2017).
CMPK1 and INPP5A were related to metabolic function ([142]Zhu et al.,
2018; [143]Li G. et al., 2019). GALNS and TAPBP were involved in the
innate immune system and MHC class I-mediated antigen processing and
presentation ([144]Williams et al., 2000, [145]2002; [146]Park et al.,
2004; [147]Tamarozzi et al., 2014).
TABLE 2.
Analysis of imprinted genes affected in ART.
Target ID CHR MAPINFO Gene name Diff (ART-N) P-value
cg09663736 11 131554122 NTM −0.20 0.026
cg13077366 18 34908626 BRUNOL4 −0.22 0.004
cg20094343 18 34917603 – −0.27 0.015
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TABLE 3.
Analysis of housekeeping genes affected in ART.
Target ID CHR MAPINFO Gene name Diff (ART-N) P-value
cg12501287 10 134411480 INPP5A 0.20 0.015
cg16645815 10 134556992 INPP5A –0.25 0.004
cg16542356 7 1121190 C7orf50 –0.20 0.026
cg23496178 7 1142861 C7orf50 –0.26 0.041
cg00023507 6 33276465 TAPBP –0.33 0.002
cg00999163 1 47799638 CMPK1 0.26 0.041
cg01128042 10 115465924 CASP7 –0.47 0.041
cg02379549 6 36887307 C6orf89 0.31 0.026
cg03119308 7 127950724 RBM28 0.68 0.002
cg05385718 2 242693323 D2HGDH 0.28 0.015
cg05398700 14 102677141 WDR20 –0.23 0.015
cg06314883 6 5404958 FARS2 0.21 0.041
cg08136432 16 88902276 GALNS 0.38 0.026
cg08603678 8 109235928 EIF3E 0.69 0.002
cg08912652 11 130779479 SNX19 0.31 0.041
cg12604331 1 156906485 ARHGEF11 0.29 0.002
cg13143872 2 200778865 C2orf69 –0.31 0.002
cg14060113 19 18054643 CCDC124 –0.34 0.041
cg14497649 4 528497 PIGG –0.30 0.002
cg14609104 10 111989324 MXI1 0.41 0.009
cg1542132 5 153372524 FAM114A2 –0.53 0.002
cg16241932 6 157876915 ZDHHC14 0.35 0.026
cg17004290 4 108853384 CYP2U1 –0.45 0.015
cg24976563 14 24587638 DCAF11 0.36 0.041
cg25282454 1 1158325 SDF4 0.31 0.002
cg25465065 1 156198365 PMF1 –0.36 0.026
cg26303777 1 230311676 GALNT2 –0.24 0.026
cg06634576 2 36782386 FEZ2 –0.32 0.015
[149]Open in a new tab
To further verify the above imprinted and housekeeping gene, we used
our recently published RNA-sequencing data ([150]GSE136849) to analyze
the gene expression. The ART-conceived pregnancy families were further
divided into four subgroups based on the type of ART applied, including
the in vitro fertilization-embryo transfer (IVF-ET), in vitro
fertilization and frozen-thawed embryo transfer (IVF-FET),
intracytoplasmic sperm injection-embryo transfer (ICSI-ET), and
intracytoplasmic sperm injection and frozen-thawed embryo transfer
(ICSI-FET) subgroups. Each ART subgroup had its technical details, but
they all intervened on embryonic cells in vitro. As shown in
[151]Figure 5 and [152]Supplementary Figure 4, the gene expression
pattern of the above four ART subgroups was different from that of the
control group. Among them, six genes were significantly different from
the control group in all ART subgroups, namely GALNT2, GALNS, EIF3E,
C2ORF69, CYP2U1, and CASP7, respectively. Among the above genes, GALNT2
was involved in glucose and lipid metabolism; EIF3E was highly
associated with the survival of human glioblastoma cells; CYP2U1
transcripts were most abundant in the thymus and the brain, indicating
a specific physiological role for CYP2U1 in these tissues. Next, we did
hierarchical cluster analysis on the transcriptome ([153]Figure 6A),
PCA results showed that that the expression profiles of the control
group and ART newborns could be significantly divided into two groups
([154]Figure 6B), the number of DEGs between the IVF frozen and natural
pregnancy groups was relatively large ([155]Figure 6C). They were
highly enriched in pathways involving autophagy and sialic acid
secretion ([156]Figure 6D). At the same time, we found that the immune
and nervous system-related pathways also had significant statistical
differences, which justifies the results of our heel blood methylation
pathway analysis ([157]Supplementary Figure 5).
FIGURE 5.
[158]FIGURE 5
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The housekeeping genes and imprinting genes in DMSs was confirmed by
RNA-seq. The expression profiles of imprinted genes and housekeeping
genes in the four ART subgroups: IVF-ET, IVF-FET, ICSI-ET, and
ICSI-FET, six genes had significant differences in all ART subgroups.
FIGURE 6.
[160]FIGURE 6
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Analysis of RNA-seq in umbilical cord blood of different types of ART
and natural pregnancy infants. (A) Hierarchical clustering analysis of
RNA seq data. (B) Principal component analysis (PCA) analysis of ART
and natural pregnancy infants. (C) Differentially expressed genes
(DEGs) analysis of IVF-fresh and IVF-frozen. (D) KEGG pathway analysis
of IVF-frozen and ICSI-frozen.
Discussion
ART treatment can affect the epigenomes of offspring, such as aberrant
DNA methylation ([162]Tan et al., 2016; [163]Castillo-Fernandez et al.,
2017; [164]El Hajj et al., 2017; [165]Ghosh et al., 2017), most of the
studies addressing these changes use the cord blood, which has an
unwanted maternal background. Moreover, most of these studies are not
whole genome-wide. To demonstrate the specific effect caused by ART, we
used heel blood to compare the DNA methylation patterns of ART and
naturally conceived newborns.
Our main findings were as follows: (1) ART can affect the conservation
of DNA methylation in specific genomic regions, and the DMSs are mainly
enriched in the function of the nervous system and immune system; (2)
our discovery of DMSs can be confirmed by the difference of DMRs, RNA
expression level of imprinted genes, and housekeeping genes in ART
babies.
Our study reveals that ART infants show a similar global DNA
methylation pattern with naturally conceived infants, which is
consistent with the results of NirMelamed’s study ([166]Melamed et al.,
2015). However, by using cord blood, which adds background noise from
the maternal cells, the above work fails to show the specific
methylation difference in ART-assisted babies. We screened 301 DMSs in
the heel blood of ART-assisted samples. Although the number of loci
screened out was relatively small, it actually reflects the real
difference in methylation levels between the ART and control groups. It
can be explained by the fact that our sample contains only the
methylation information of newborns with no environmental influence,
and we set up a strict standard for screening. Previous works do not
reveal the genes annotated from all 301 DMSs ([167]Supplementary Figure
6; [168]Melamed et al., 2015; [169]Castillo-Fernandez et al., 2017;
[170]El Hajj et al., 2017). The differential genes we found were
consistent with the gene found by Juan et al., and there have been very
few common discoveries among previous works. Furthermore, our data
demonstrate that ART shows a specific effect on the reprogramming of
DNA methylation patterns in human offspring.
The pathway analysis of DMSs and DMRs shows that the altered DNA
methylation patterns are mainly enriched in key pathways in early-stage
developmental pathways, such as neurotransmitter secretion, immune
system establishment, and NAD metabolism. Quite a few previous works of
clinical studies suggest an increased risk of autism spectrum
disorders, intellectual disability, specific congenital heart defects,
cardiovascular disease, and metabolic disorder in late-stage
ART-assisted infants ([171]Sandin et al., 2013; [172]Guo et al., 2017;
[173]Liu et al., 2017). It is reasonable to hypothesize that abnormal
DNA methylation in ART-assisted offspring is rooted in the effect of
DNA methylation reprogramming in the early developmental stage, as
suggested by the Developmental Origins of Health and Disease (DOHaD)
theory ([174]Berntsen et al., 2019).
Although we used the blood sample analysis differences of DNA
methylation between ART infants and natural pregnancy infants, it is
reasonable that ART may have an impact on the development of nervous
and immune systems. Heel blood contains a large number of white blood
cells, it is easier to understand why the results of heel blood would
be enriched in the immune system. Meanwhile, analysis pathway in blood
and predating the dysregulation of brain tissue is comprehensively used
in many different fields. The results of W Esther show that blood can
serve as a surrogate marker for the brain. There is a large correlation
between blood DNA methylation and brain diseases, a proportion that,
although small, was significantly greater than prediction by chance. A
subset of peripheral data may represent the methylation status of brain
tissue. The results of [175]Chuang et al. (2017) also showed that DNA
methylation levels in human blood and saliva is associated with
Parkinson’s disease ([176]Walton et al., 2016; [177]Edgar et al., 2017;
[178]Zhang et al., 2017). Although we are not yet able to know the
mental and nervous system development of these children in the future,
our pathway research shows that it is consistent with current known
clinical research phenomena.
We also identify three significant DMSs-located imprinted genes and 28
significant DMSs-located housekeeping genes, and these are key genes
related to the development and echo the results of pathway enrichment
analysis. These results collectively suggest that the ART process
potentially influenced the development of the nervous system in
progenies, not only by the co-effect of multiple genes of the nerve
gene signaling pathway but also by influencing the methylation status
of imprinted genes and housekeeping genes. These six genes, GALNT2,
GALNS, EIF3E, C2ORF69, CYP2U1, and CASP7, may be the key genes affected
by ART technology, the significant differences can be seen in heel
blood and umbilical cord blood at the same time in all kinds of ART
technology (IVF-ET, IVF-FET, ICSI-ET, and ICSI-FET), meanwhile, they
are related to the nervous system and immune system.
Our findings are highly consistent with previous clinical epidemiology
data and highlight the epigenetic impact of ART on the nervous system
and the immune system during development. Since the first DNA
methylation reprogramming starts from the two-cell stage, it may be
influenced by the in vitro environment. Further investigation to
compare the multi-cell stage embryo may help to uncover the underlying
mechanism. Due to the great heterogeneity among populations (such as
living habits, genetic background, reproductive age, and health status
of the parents), a larger cohort is needed to systematically assess and
confirm the above-mentioned epigenetic risk in ART-assisted children.
At the same time, our research also has some areas that can be further
optimized. For example, we can further control the homozygote and
heterozygote of the sampling to ensure that our data are more accurate
and reliable and expand our sample size to provide better evidence for
our conclusion. Also, since the heel blood was harvested 3 days
post-natal, there could be some differential methylation marks added to
the baby epigenetic marks. At the same time, we can ensure the quality
of blood collection as much as possible, so that we can carry out
multi-omics analysis of DNA methylation and transcriptome of the same
infant to verify the conclusion of our heel blood data and explore the
effect of ART technology on DNA methylation and the genetic pattern of
newborns more accurately.
Conclusion
In summary, we found DMRs between ART-assisted and naturally conceived
human offspring at the whole genome-wide level. These DNA methylation
variations were enriched in important pathways of the immune system and
nervous system.
Data Availability Statement
The datasets presented in this study can be found in online
repositories. The names of the repository/repositories and accession
number(s) can be found below: [179]https://www.ncbi.nlm.nih.gov/,
[180]GSE142554
[181]https://www.ncbi.nlm.nih.gov/, [182]GSE136849.
Author Contributions
ZL participated in sample collection, data analysis, and manuscript
writing. WC participated in sample collection and manuscript writing.
YW participated in sample collection. ZZ, LH, and Y-KY participated in
data analysis. JW, JQ, and YS designed the experiment and revised the
article. All authors read and approved the final manuscript.
Conflict of Interest
ZZ was employed by the company Tianjin Novogene Bioinformatic
Technology Co., Ltd., China. The remaining authors declare that the
research was conducted in the absence of any commercial or financial
relationships that could be construed as a potential conflict of
interest.
Publisher’s Note
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and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or claim
that may be made by its manufacturer, is not guaranteed or endorsed by
the publisher.
Acknowledgments