REVIEW
Epigenomics, gestational programming and risk of metabolic
syndrome
M Desai1,2
, JK Jellyman1,2
and MG Ross1,2
Epigenetic mechanisms are emerging as mediators linking early environmental exposures during pregnancy with programmed
changes in gene expression that alter offspring growth and development. There is irrefutable evidence from human and animal
studies that nutrient and environmental agent exposures (for example, endocrine disruptors) during pregnancy may affect
fetal/newborn development resulting in offspring obesity and obesity-associated metabolic abnormalities (metabolic syndrome).
This concept of ‘gestational programming’ is associated with alterations to the epigenome (nongenomic) rather than changes
in the DNA sequence (genomic). Epigenetic alterations induced by suboptimal maternal nutrition/endocrine factors include DNA
methylation, histone modifications, chromatin remodeling and/or regulatory feedback by microRNAs, all of which have the ability
to modulate gene expression and promote the metabolic syndrome phenotype. Recent studies have shown tissue-specific
transcriptome patterns and phenotypes not only in the exposed individual, but also in subsequent progeny. Notably, the
transmission of gestational programming effects to subsequent generations occurs in the absence of continued adverse
environmental exposures, thus propagating the cycle of obesity and metabolic syndrome. This phenomenon may be attributed
to an extrinsic process resulting from the maternal phenotype and the associated nutrient alterations occurring within each
pregnancy. In addition, epigenetic inheritance may occur through somatic cells or through the germ line involving both maternal
and paternal lineages. Since epigenetic gene modifications may be reversible, understanding how epigenetic mechanisms
contribute to transgenerational transmission of obesity and metabolic dysfunction is crucial for the development of novel early
detection and prevention strategies for programmed metabolic syndrome. In this review we discuss the evidence in human and
animal studies for the role of epigenomic mechanisms in the transgenerational transmission of programmed obesity and metabolic
syndrome.
International Journal of Obesity (2015) 39, 633–641; doi:10.1038/ijo.2015.13
OBESITY AND METABOLIC SYNDROME EPIDEMIC
Obesity is a public health crisis, contributing to morbidity and
mortality throughout the world.1
Obesity is central to the
development of metabolic syndrome, which includes a constellation
of metabolic abnormalities comprised of insulin resistance,
elevated triglycerides, hypertension and atherosclerosis.2
Among
US adults, 69% are overweight (body mass index (BMI) 425
kg m− 2
), 35% are obese (BMI ⩾ 30 kg m− 2
) and 24% have at least
three features of metabolic syndrome.3–5
Importantly, 17% of
children are obese and thus at increased risk of adult obesity.6
Among childbearing women, the prevalence of obesity is ~ 30%.
In conjunction with increased maternal obesity, we have
witnessed an increase in obesity-associated pregnancy complications
and a 25% increase in the incidence of high birth weight
babies,7
which itself represents a risk factor for childhood
obesity.8,9
The world-wide shift towards an obese phenotype has occurred
in a relatively short period of one or two generations (from
15–35.7%).3,10
This suggests that environmental or epigenetic
factors rather than genetic mechanisms play a role in the obesity
epidemic. While there is little doubt that Western style, high-fat
diets combined with decreased activity levels are strong
contributors to the prevalence of obesity, data from our laboratory
and others, support the concept that obesity may have its origins
in utero.11–15
More importantly, obesity and its associated
metabolic abnormalities persist in offspring that are developmentally
programmed by suboptimal nutrition in utero, despite normal
postnatal nutrition, and may be evident in multiple generations.
Such transgenerational transmission of obesity may occur as a
result of changes to the epigenome. Since epigenetic modifications
alter the phenotype rather than the genotype, there is
potential for intervention and reversibility. This review focuses on
the emerging evidence for the role of epigenetics in the
developmental origins of metabolic syndrome and heritable
changes in gene expression.
PROGRAMMED OBESITY AND METABOLIC SYNDROME
Epidemiological studies have convincingly demonstrated associations
between the early nutritional environment, patterns of
postnatal growth and metabolic syndrome in adults.16,17
The
Dutch famine in 1944/45 provided an opportunity to determine
the effects of perinatal malnutrition on babies that would later be
exposed to a surfeit of calories. Offspring of mothers exposed to
the famine during the first two trimesters of pregnancy had lower
1
Department of Obstetrics and Gynecology, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Perinatal Research Laboratories, Torrance, CA, USA and
2
Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA. Correspondence: Professor M Desai, Department of
Obstetrics and Gynecology, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Perinatal Research Laboratories, 1124 West Carson Street Box 446,
Torrance 90502, CA, USA.
E-mail: mdesai@obgyn.humc.edu
Received 23 September 2014; revised 8 January 2015; accepted 18 January 2015; accepted article preview online 2 February 2015; advance online publication, 24 February 2015
International Journal of Obesity (2015) 39, 633–641
© 2015 Macmillan Publishers Limited All rights reserved 0307-0565/15
www.nature.com/ijo
birth weights, though paradoxically a higher incidence of obesity
than the general population.17
In particular, low birth weight infants
with rapid catch-up growth in the first several years of life had the
highest risk of adult obesity and metabolic syndrome.18,19
While low
birth weight infants develop in a state of relative ‘undernutrition’,
fetal ‘overnutrition’ also has adverse implications for offspring
health. Recent interest has focused on the effect of maternal
overnutrition on fetal programming. Specifically, maternal prepregnancy
obesity and/or increased weight gain during pregnancy
are associated with higher birth weight newborns20,21
and an
increased risk of obesity and diabetes in later life.22
Thus, there is a
U-shaped curve for the relationship between birth weight and adult
metabolic disease, such that those born small or large have an
increased risk of obesity later in life.23,24
Together, these processes
likely contribute, in part, to the population shift toward obesity and
to the intergeneration aggregation of obesity (Figure 1).
Animal models of low birth weight, induced using a variety of
methods such as maternal nutrient restriction, placental uterine
ligation or glucocorticoid exposure, have confirmed an increased
risk of offspring adiposity,25–27
particularly among those who
exhibit rapid catch-up growth.12,28,29
More recent animal models
of maternal overnutrition, including maternal obesity and
Western, high-fat diets similarly replicate the human experience,
in that offspring are predisposed to adult obesity.13,30,31
These
data raise important questions about divergent maternal nutritional
exposures that result in differential fetal growth. First, how
do both under and overnutrition produce a metabolic syndrome
phenotype in the offspring? And second, how does the memory of
the short period of insult persist across generations?
EPIGENETIC MECHANISMS OF PROGRAMMED OBESITY AND
METABOLIC SYNDROME
During the developmental period, rapidly growing fetuses and
neonates are vulnerable to perturbations of the maternal
nutritional and non-nutritional milieu, resulting in programmed
changes in organ structure, cellular responses and gene expression
that impact metabolism and physiology of the offspring.
Developmental programming may have immediate effects, for
example, impaired organ growth at a critical stage, whereas other
programming effects are deferred and altered organ function
occurs at a later age. This again raises the question as to how the
memory of early events is stored and later expressed, despite
continuous cellular replication and replacement. Among the
different mechanisms causing obesity, epigenetics has emerged
as an important determinant that can influence phenotypic
outcomes, even in the absence of genetic or environmental
heterogeneity.
Epigenome
Epigenetic phenomena are an essential feature of mammalian
development that cause heritable and persistent changes in gene
expression without altering the DNA sequence.32
The three major
molecular substrates that are involved in this process are the DNA,
proteins that form the core around which the DNA wraps
(histones) and a specific form of RNA molecules (noncoding
RNA). Epigenetic changes include DNA methylation, chromatin
folding and binding, packaging of DNA around nucleosomes and
covalent modifications of the histone proteins (Figure 2).33
The
epigenome varies across different cell types and undergoes
precise, coordinated changes during a lifetime.34,35
Epigenetic regulation of gene transcription occurs, in part, by
DNA methylation.36
DNA methylation is highly dynamic during
embryogenesis. Prior to implantation DNA is hypomethylated and
following implantation there is a progressive increase in DNA
methylation that leads to differentiation and organogenesis.37,38
During postnatal and adult life, DNA methylation is susceptible to
intrinsic and extrinsic factors,39,40
and with aging there is global
loss of DNA methylation.41
Increased methylation mediated by
DNA methyltransferase enzymes (DNMTs) is associated with
transcriptional silencing. Abnormal DNA methylation is associated
with inappropriate gene silencing, and such changes in epigenetic
marks are associated with several human diseases (for example,
cancers, neurological disorders and inflammation). As methylation
involves the supply and enzymatic transfer of methyl groups, it is
Figure 1. The role of gestational programming in population shifts towards obesity and metabolic syndrome. Normal weight mothers usually
give birth to normal-weight infants with normal adiposity. These offspring develop into normal adults with normal body fat content and a
normal metabolic profile. The increased incidence of prematurity and intrauterine growth restriction (IUGR) resulting from undernutrition,
among other factors, combined with improved neonatal survival, formula feeding and exposure to a Western postnatal diet has resulted in
increased offspring obesity and metabolic syndrome. A small portion of obese mothers give birth to newborns with increased body fat, as a
result of overnutrition (consumption of a high-fat diet). These processes may contribute to the population shift towards an obese phenotype,
with second generation obese women at increased risk for giving birth to newborns with increased body fat content, and who in turn, are at
risk of developing obesity and metabolic syndrome.
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M Desai et al
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International Journal of Obesity (2015) 633 – 641 © 2015 Macmillan Publishers Limited
plausible that in utero nutritional (for example, methyl donors),
hormonal or other metabolic cues alter the timing and direction of
methylation patterns during fetal development.42,43
An additional essential mechanism of regulating gene expression
and silencing is the packaging of chromatin into open
(euchromatic) or closed (heterochromatic) states, respectively.
Chromatin consists of DNA packaged around histones. Posttranslational
modifications of histone tails commonly involve
methylation/demethylation and acetylation/deacetylation mediated
by histone modifying enzymes. Histone methylation can either
repress or activate transcription depending on which lysine is
methylated. For example, trimethylation of histone H3 at lysine
4 (H3K4me3) is associated with active gene transcription, whereas
dimethylation of histone H3 at lysine 9 (H3K9me2) is associated
with transcriptional silencing. Unlike methylation, acetylation
potentiates and deacetylation suppresses gene expression.44,45
Non-coding RNAs (ncRNAs) also participate in the epigenetic
regulation of gene transcription. In general ncRNAs are transcribed
from DNA, but are not translated into proteins, and function to
regulate gene expression at the transcriptional and posttranscriptional
level. Those ncRNAs that are involved in epigenetic
regulation comprise the short ncRNAs (o30 nts) and the long
ncRNAs (4200 nts). The three major short ncRNAs associated with
gene silencing are microRNAs (miRNAs), short inhibitory RNAs and
piwi-interacting RNAs.46,47
Long ncRNAs play a regulatory role
during development,48
exhibit cell type-specific expression49,50
and are associated with adipogenesis.51,52
While these noncoding
RNAs are usually associated with regulation of gene expression at
the translational level, recent work suggests they may be involved
in DNA methylation and histone modifications as well, thereby
further regulating the transcription of their target genes.53,54
It is now recognized that the epigenome is dynamic, changing
in response to nutrient availability, physical exercise, weight loss
and aging, among other exposures.55–58
In utero nutrition,
environmental exposures and other factors (for example, maternal
or fetal stress) may permanently alter offspring gene expression
via epigenetic mechanisms, and hence alter the structure and
function of cells and organs leading to metabolic abnormalities.
Nutrition, the epigenome and obesity
Evidence implicating epigenetic mechanisms as potential mediators
of obesity is largely from animal and limited human studies.
Notably, nutritional and environmental factors can interact with
the genotype by modulating epigenetic markings in the somatic
cells and thus impacting the phenotype. This is well-demonstrated
in monozygous twins, in which the offspring exhibit divergent
DNA methylation and histone acetylation patterns,57
and in the
agouti mouse, in which the diet affects methylation status and the
animal's coat color.59,60
To address the phenotypic discordance
(that is, anthropomorphic features and susceptibility to disease) in
monozygous twins, lymphocyte and muscle biopsy samples were
obtained from 3–74-years-old Spanish monozygotic twins (monochorionic
and dichorionic). These biopsy samples were analyzed
for global and locus-specific DNA methylation and histone
acetylation. Older, but not younger, twins showed differences in
their epigenetic markings and their gene-expression profile,
suggesting an environmental influence on the regulation of gene
expression, despite a similar genotype. In agouti mice, the agouti
gene is normally methylated and, as a result, the mice are thin and
have a brown coat color. However, when the agouti gene is
completely unmethylated, the coat color is yellow and the mice
are obese and diabetic. Although, the ‘fat yellow mice’ and ‘skinny
brown mice’ have a similar genotype, the phenotype is different as
a result of epigenetic changes. Notably, these methylation
patterns can be transmitted across generations.59,61
More
remarkably, ‘fat yellow mice’ fed a methyl-rich diet during
pregnancy produced pups with brown coat without obesity.62
These results reinforce the interaction between nutrition and the
epigenome, and offer opportunities for potential intervention.
While epigenetic modulation of imprinted genes is well-
recognized,63,64
including their impact on body weight (for
example, IGF2),65,66
epigenetic changes also occur in key nonimprinted
genes that are involved in energy metabolism. Genes
that regulate adipogenesis, glucose homeostasis, inflammation
and/or insulin signaling are regulated by epigenetic mechanisms,
including genes encoding hormones (for example, leptin), nuclear
receptors (adipogenic and lipogenic transcription factors PPARγ
and PPARα, respectively) gluconeogenic enzymes (for example,
phosphoenolpyruvate carboxykinase (PEPCK)) and transmembrane
proteins (for example, uncoupling protein 1).67–75
Plasma
levels of leptin, a satiety hormone produced by adipocytes, can be
modulated by diet via epigenetic mechanisms. Consumption of a
high-fat diet in rats increased methylation of leptin gene promoter
in retroperitoneal adipocytes and this was associated with lower
circulating leptin levels, suggesting leptin methylation affects
leptin gene expression.67
Similarly, adipogenesis is driven by
adipocyte differentiation and induction of adipogenic transcription
factors (PPARγ, C/EBPα) via epigenetic mechanisms.
Both histone lysine methylation (H3K4) and acetylation (AcH3)
regulate adipocyte differentiation. During terminal differentiation,
significant increases in histone trimethylation (H3K4me3) and
acetylation (AcH3K9/K14) coincide with upregulation of PPARγ
and C/EBPα. Early induction of adipogenic genes as a result of
increased H3K4me3 and AcH3K9/K14 contributes to early adipocyte
differentiation and obesity.76–78
Hepatic PEPCK is the rate-limiting
enzyme in the metabolic pathway of gluconeogenesis and
consumption of a high-calorie diet caused hypomethylation of
the PEPCK gene in rats. This was associated with increased PEPCK
mRNA levels indicative of increased liver gluconeogenesis.43
Indeed, these methylation changes were associated with changes
in target gene expression and glucose and lipid metabolism.
In humans, global DNA methylation, specific histone methylation
(H3K4 and H3K9) and certain miRNAs are positively associated
with BMI.79–81
For example, genome wide methylation analysis
showed that human obesity was associated with methylation
changes in blood leukocyte DNA.79
Another study of specific
Figure 2. Epigenetic regulation. There are three distinct, interrelated
mechanisms of epigenetic regulation: (i) DNA methylation: methyl
groups attached to CpG islands regulate gene activity. Methylation
renders the DNA inaccessible and thereby suppresses gene
expression; (ii) Histone modifications: methylation (Me) or acetylation
(Ac) of histones determines the activity of the DNA wrapped
around them, and; (iii) microRNA (miRNA): noncoding RNA
molecules that affect RNA silencing and post-transcriptional
regulation of gene expression.
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© 2015 Macmillan Publishers Limited International Journal of Obesity (2015) 633 – 641
histone methylation (K4 and K9) in primary human adipocytes
from overweight subjects with and without type 2 diabetes
revealed 40% lower levels of K4 dimethylation in overweight, nondiabetic
individuals. In contrast, trimethylation at K4 was 40%
higher in adipocytes from overweight diabetic subjects as
compared with normal-weight and overweight non-diabetic
subjects. Obese and lean individuals show varying DNA methylation
levels in specific genes and cultured preadipocytes and
mature adipocytes show differentially expression of miRNAs.80
Similarly, genome wide miRNA profiling of human subcutaneous
adipose tissue biopsies showed differential and dysregulated
expression of miRNA in obese versus lean individuals. Moreover,
the expression pattern of miRNAs in human adipose tissue was
associated with obesity and parameters of glucose metabolism.81
Animal studies provide further evidence implicating epigenetic
mechanisms in the regulation of adipogenesis and appetite in the
development of obesity, though this pertains more specifically
to histone modifications and miRNA rather than DNA
methylation.73,82–85
For instance, histone modifications (methylation
and acetylation) and miRNA have been linked to the
regulation of the principal adipogenic transcription factor (PPAR)
and its target genes, resulting in obesity, hyperphagia and
hyperlipidemia.82,86–88
Specifically, maternal obesity/high-fat diet
in mice increases the expression of a key transcription factor
responsible for adipogenic lineage commitment (Zfp423) during
fetal development. Consistent with this, the repressive histone
methylation (H3K27me3) was lower in the Zfp423 promoter of
fetal tissues from maternal obese mice.89
Together with increased
mRNA expression, alterations in DNA methylation of CpG sites and
CGI shores of pro-adipogenic factors (Zfp423 and C/EBP-β) have
also been demonstrated in rat offspring (3 week old) from obese
pregnancies.90
In contrast, mice with genetically increased or
decreased levels of DNA methyltransferases (DNMT1 and
DNMT3b) do not gain weight or have increased adiposity.91
Although de novo DNMT3a was more than doubled in white
adipose tissue of obese mice, in that study, a transgenic mouse
that had threefold elevated DNMT3a mRNA levels in adipose
tissue did not exhibit increased body weight or adiposity.91
These
findings argue against DNA methyltransferase-driven obesity.
Unlike ubiquitous DNA methyltransferases, perhaps it is histone
deacetylases that serve specialized functions and have tissuespecific
expression that are major contributors. Indeed, specific
histone methyltransferases are important for adipogenesis; mice
with mutations in the histone H3, lysine 4 methyltransferase MLL3
exhibit reduced adipogenesis and are protected from high-fat
diet-induced obesity.92
In contrast, mice with loss of function of
the H3K9-specific demethylase JmjC domain-containing histone
demethylase 2A are obese and hyperlipidemic.82,83
Therefore,
there is evidence that mutations in epigenetic-modifiers may
contribute to obesity.
Epigenome and programmed obesity
There is also evidence that environmental exposures during early
life can induce persistent alterations in the offspring epigenome,
which may lead to an increased risk of obesity and metabolic
syndrome later in life.
In humans, programmed obesity occurs principally via alterations
in DNA methylation, but the involvement of histone
modifications and changes in chromatin structure has not yet
been demonstrated. Remarkably, exposure to either maternal
famine or obesity reduced DNA methylation of the imprinted IGF2
gene in the offspring. In the Dutch Famine (1944–1945) cohort,
60-year-old adults who were prenatally exposed to famine
showed hypomethylation of whole blood IGF2 gene, and
hypermethylation of two obesity-related non-imprinted genes
(TNF, leptin) as compared with their unexposed, same-sex siblings.
This association was specific for periconceptional exposure,
reinforcing that the early developmental period is crucial for
establishing and maintaining epigenetic marks.93,94
More recently,
parental obesity and specifically paternal obesity was associated
with IGF2 hypomethylation in umbilical cord blood leukocytes of
newborns.95,96
Specific maternal characteristics, including gestational
weight gain and gestational diabetes, have also been
associated with signature DNA methylation in cord blood and
increased placental leptin gene methylation, respectively.55,97
Furthermore, maternal carbohydrate intake in early pregnancy
was associated with the umbilical cord methylation levels of the
nuclear receptor gene, retinoid X receptor-α, which heterodimers
with the adipogenic transcription factor PPARγ, as well as with
adiposity in later childhood.98
Human newborn studies are
generally limited to determination of umbilical blood leukocytes
or placental tissue epigenetic assessments, which may not parallel
organ-specific cellular changes.
Animal studies demonstrate that both DNA methylation
and histone modification changes are associated with the
developmental programming of obesity in rodent models of
maternal under or overnutrition (for example, high-fat diet,
maternal obesity), and newborn-specific nutritional modifications
(for example, litter size manipulation). This has been extensively
reviewed recently.99–103
For example, epigenetic
changes have been detected at genes that regulate growth
factors,104
adipogenesis,67,105
brain appetite and satiety/reward
pathways98,106–109
and glucose homeostasis.110
Similar to humans,
there is some indication that both maternal under and overnutrition
may impact similar genes,90,111
though whether this
occurs via similar epigenomic changes remains to be established.
The subtle differences between human and animal findings,
including genetically modified mice may partly be attributed to
certain factors, such as sampling tissue (umbilical blood versus
specific tissue/cells), period and duration of exposure (periconceptual,
fetal or neonatal) and in the case of humans, lifestyle.
Nonetheless, both human and animal studies provide evidence of
programmed metabolic syndrome resulting from early nutritional
exposures and suggest that epigenetic modification of nonimprinted
genes may be a major contributing factor.
TRANSGENERATIONAL EPIGENETIC INHERITANCE OF OBESITY
AND METABOLIC SYNDROME
It is crucial to understand how epigenetic marks become heritable.
DNA methylation is highly dynamic during early embryogenesis,
but contrary to popular belief, is not completely erased during
very early development or gametogenesis.112–114
As such, some
methylated sites survive and are replicated every time a cell
divides and the DNA is passed along with associated histones.
These markings can then be copied every time the cell divides,
influencing gene expression throughout life (Figure 3).115
Thus,
epigenetic modifications provide a mechanism by which early
nutritional and environmental exposures affect the offspring
phenotype via germline modifications.116
More importantly,
epigenetic changes can be inherited mitotically in somatic cells
with long-term effects on gene expression.117,118
As described by
Skinner,117
an intrinsic transgenerational process requires only one
exposure to the environmental factor resulting in germline
involvement and, whereas extrinsic transgenerational epigenetic
processes involve an epigenetic alteration in a somatic tissue with
required (repeat) exposures at each generation. Intergeneration
aggregation of obesity (that is, BMI) has been consistently
demonstrated with evidence of both familial and geographic
clustering. Increased BMI occurs disproportionally among offspring
of heavier parents and there is greater familial influence on
offspring obesity from mothers than fathers.119,120
A vicious cycle
develops as females born to obese women have an increased risk
of obesity121
and give birth to a subsequent generations with the
same risks. In support of this concept, maternal weight loss via
Epigenomics, gestational programming and metabolic syndrome
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International Journal of Obesity (2015) 633 – 641 © 2015 Macmillan Publishers Limited
bariatric surgery reduces obesity in the F1 generation. Children of
obese women who underwent bariatric surgery compared with
those in children born before maternal surgery, had lower birth
weight, reduced prevalence of macrosomia and a threefold lower
prevalence of severe obesity at follow-up (2.5–26 years).122
Epidemiologic studies have largely attributed this phenomenon
to an extrinsic process resulting from the maternal phenotype and
the associated nutrient alterations occurring within each pregnancy,
rather than to germline alterations, which persist through
generations.
True transgenerational inheritance must extend from the F0 to
the F3 generation, as the developing fetal germ cells, which will
produce the F2 generation, are exposed to the F0 environment.123
Therefore, expression through the F3 generation may occur
via germline transmission. Notably, nutritional and nonnutritional
factors (for example, endocrine disruptors) are
independently59,124,125
and synergistically126
capable of causing
methylation changes in the male germ line. For example,
bisphenol A an endocrine disruptor, causes site specific
hypomethylation in the agouti mouse in conjunction with the
development of offspring obesity,126
which suggests the potential
for transgenerational transmission of obesity. Bisphenol A also
impairs male fertility for three generations, inducing transgenerational,
tissue-specific changes in the transcriptome,127,128
suggesting
that epigenetic modifications in the germ line may impact
secondary epigenetic mechanisms, which regulate somatic cell
gene expression.129
Importantly, maternal nutritional supplements
negated the effects of bisphenol A on the offspring phenotype,126
raising the potential for preventative and therapeutic strategies.
Epigenetic changes in the germ line may affect somatic cell
gene expression by changes in inflammatory signaling pathways.
Maternal nutrition affects the methylation of offspring genes
central to immune responses, adipogenesis and lipogenesis.8,130
Sub-optimal maternal nutrition also inhibits adiponectin and
stimulates the release of inflammatory adipokines, including IL-6
and TNFα from human offspring adipose tissue.131
Notably,
inflammatory mediators can modify DNA methylation, as mastitis
silences bovine casein gene expression.132
Thus, offspring
epigenetic modifications induced by suboptimal nutrition may
be mediated by inflammation-associated mechanisms. In addition,
transcription factors (for example, nuclear receptors), which are
susceptible to nutritional modulation, can cause epigenetic
changes. Nuclear receptors associate with both positive and
negative chromatin modifying complexes to activate or repress
gene transcription.133–135
Similarly, nutritionally mediated changes
in hormones (for example, estrogen and androgen) can influence
miRNA expression.136,137
In addition to maternal nutrition,
an inappropriate metabolic environment in utero may also
perpetuate the transgenerational cycle. For example, maternal
gestational diabetes and the resultant intrauterine hyperglycemia
can transmit the diabetogenic phenotype to the next
generation.138,139
Indeed animal studies in mice have demonstrated
that intrauterine hyperglycemia alters imprinted gene
expression of the sperm.140
In summary, evidence supports that
adverse nutritional exposure results in F1/F2 obesity and
potentially F3 transgenerational obesity.141
Transgenerational effects in humans
To date, most of the evidence for transgenerational inheritance
pertains to effects on offspring growth, particularly on body
weight. However, human and animal studies have shown that
increased adiposity can occur despite normal body weight.13,142
Nonetheless, the human studies described below provide
important evidence of transgenerational effects. The earliest study
showing transgenerational birth weight effects examined Swedish
women and their offspring. Women who were themselves born
small for gestational age had an increased risk of giving birth to
either intrauterine growth restricted or preterm infants, emphasizing
the importance of both maternal factors and the intrauterine
milieu in determining the offspring phenotype.143
Retrospective cohort studies, the Dutch Hunger Winter Families
Study in the western Netherlands, Chinese famine and the
Overkalix cohort in Sweden also indicate non-genomic transmission
of phenotypic traits and metabolic abnormalities. The Dutch
Hunger Winter famine occurred at the end of World War II, from
October 1944 to May 1945. The birth cohort that was in utero
during this time, when nutritional intake plummeted to o500
kcal per day has been extensively studied. The vast majority of
studies of developmental programming (F0 to F1) by the Dutch
Hunger Winter have demonstrated effects of altered in utero and
newborn nutrition, with the offspring phenotype often dependent
on the developmental stage of exposure. However, reports on
transgenerational (F0 to F2, F3) effects are conflicting. An early
study reported that offspring born during the famine were smaller
than average and that the risk of having smaller babies could last
two generations (F1 and F2).144
Further, the maternal diet during
Figure 3. Environmental exposures and transgenerational epigenetic inheritance. Transgenerational inheritance must extend from the F0 to
the F3 generation, as the developing fetal germ cells (which will produce the F2 generation) are exposed to the F0 environmental factors. The
expression through the F3 generation may occur due to germline transmission.
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the F0 pregnancy affected the F2 birth weight, independent of the
F1 birth weight.145,146
However, a subsequent study failed to
replicate these findings.147
Similarly, F1 women who experienced
the famine as fetuses had F2 babies with increased neonatal
adiposity and poorer adult health,148
though a more recent study
found no evidence of transgenerational effects if the grandmother
had been undernourished.149
Instead, there was evidence of
increased adiposity in the offspring of prenatally undernourished
fathers.149
These conflicting results have been attributed to the
differing methods of obtaining data. Early studies were based on
record retrieval and relied on parents' recall of their offspring's size
at birth and later health, whereas in later studies, the offspring
were directly contacted to assess their body composition and
health.
Relative to the Dutch famine, the Chinese famine was longer
(1959–1961), less precisely defined and superimposed on a
background of widespread chronic undernutrition. However,
studies of the Chinese famine also suggest transgenerational
effects of the famine on offspring growth. The offspring of
mothers exposed to famine in utero and during the first few years
gave birth to newborns with larger birth size as compared with
those offspring that were not exposed to the famine.150
Data from both famines suggest that transgenerational effects
of nutrition on offspring phenotype occur via the maternal
lineage. However, a historical study of three generations in
Overkalix, Sweden revealed that fathers’ diets may also play a
crucial role. In the early 20th century, this region suffered marked
food shortages due to failed harvests, interspersed with periods of
great plenty, during which many people would gorge. The fathers
who ate a surfeit of food during the pre-adolescence period had
sons and grandsons with an increased risk of diabetic mortality.
The paternal grandmother’s food supply was also linked to the
mortality risk ratio of the granddaughters, suggesting sex-specific
transmission operating exclusively through the paternal line.151,152
Recent animal studies further support the finding that maternal
high-fat diet-induced obesity extends to the F3 female offspring
via the paternal lineage.153
Although limited, human data suggest
that both maternal and paternal nutrition may exert transgenerational
effects on the metabolic phenotype of their offspring.
Transgenerational effects in animals
There is evidence of both somatic and germline transmission of
metabolic phenotypes via epigenetic alterations. Early rat studies
demonstrated that protein restriction for 12 generations has a
cumulative effect on fetal growth, causing progressively greater
reductions in fetal body and organ weights.154
As noted above,
maternal undernutrition or a high-fat maternal diet predisposes
the first-generation (F1) offspring to obesity and metabolic
syndrome.12,13,30,155
Importantly, the F1 generation can transmit
similar phenotypes to the second (F2),141,156–158
and third (F3)
generations,159
despite normal nutrition during pregnancy in the
F1 generation. Consumption of a protein-restricted diet during rat
pregnancy in the F0 generation resulted in obesity, elevated blood
pressure and insulin resistance in the F1 and F2 offspring.160,161
Notably, transgenerational transmission of the birth weight
phenotype occurred via the paternal lineage, transmission of
obesity occurred via the maternal lineage and transmission of
abnormal glucose homeostasis occurred via both maternal and
paternal lineages.141
The role of epigenetic regulation of gene
expression was demonstrated in the male progeny of F1 females
that were exposed to the protein-restricted diet. The F2 males
showed hypomethylation of the hepatic PPARα promoter to levels
comparable to F1 males,162
suggesting that transmission of a
phenotype induced in the F1 generation to the F2 generation
preserves levels of DNA methylation of specific genes in somatic
cells.163
A similar effect is seen with in utero dexamethasone
exposure, where F1 and F2 generation show comparable
reduction in birth weight and blood glucose levels.164
Although
these studies emphasize the primary mechanism of transmission
between generations via somatic cells, other studies demonstrate
transmission through the germ line. Maternal high-fat diet during
pregnancy and lactation increased mouse offspring body size in
the F1 and F2 generations, with transmission via both the
maternal and the paternal lineages. However, subsequent
transmission to F3 of the higher body size and weight phenotype
was restricted only to females, and was transmitted through the
paternal lineage only.153
Similarly, overfeeding of male mice via
culling of litter size, resulted in altered insulin and glucose
metabolism of two subsequent generations only in male
offspring.156
These studies highlight the importance of examining
both gender-specific programming effects, the expression of
which may change with each generation, and gender-specific
(maternal versus paternal) lineage effects influencing the phenotype
expression. When studying transgenerational models (F0 to
F3), the interplay of exposures, lineages and gender may result in
a daunting number of subjects. Nevertheless, further mechanistic
studies of parental nutrition and transgenerational epigenetic
inheritance are required to establish the specificity of germline
versus somatic cell transmission of metabolic phenotypes.
Although human and animal studies indicate that transgenerationals
effects can be transmitted via both the maternal and the
paternal lineages, studies of bariatric surgery in women strongly
support the maternal environment as a key factor driving the
obesity cycle. Bariatric surgery improves patient metabolic
profiles.165–168
Further, children born after maternal bariatric
surgery exhibited lower prevalence of severe obesity, greater
insulin sensitivity and improved lipid profile in comparison to
siblings born before maternal surgery.122,169
Several studies have
identified changes in genes associated with insulin action after
bariatric operations170,171
and demonstrated that this may be
mediated through differential methylation of genes involved in
immune and inflammatory pathways.172,173
CONCLUSION
Although still preliminary, there is compelling evidence from
human and animal studies that altered epigenetic states may
contribute, in part, to the obesity epidemic. Nonetheless, many
questions remain: (1) is there a causal link between epigenetic
modifications and metabolic disease phenotypes?; (2) does
analysis of one tissue reflect the epigenetic profile of other
tissues?; and (3) are epigenetic changes reversible? Improved
understanding of epigenetic pathways, including the potential
for reversing epigenetic gene modifications, raises the hope of
developing preventive and therapeutic approaches to address
transgenerational aggregation of obesity.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
REFERENCES
1 James PT, Leach R, Kalamara E, Shayeghi M. The worldwide obesity epidemic.
Obes Res 2001; 9: 228S–233S.
2 Reilly MP, Rader DJ. The metabolic syndrome: more than the sum of its parts?
Circulation 2003; 108: 1546–1551.
3 Ogden CL, Fryar CD, Carroll MD, Flegal KM. Mean body weight, height, and body
mass index, United States 1960-2002. Adv Data 2004; 347: 1–17.
4 Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the
distribution of body mass index among US adults, 1999-2010. JAMA 2012; 307:
491–497.
5 Beltrán-Sánchez H, Harhay MO, Harhay MM, McElligott S. Prevalence and trends
of metabolic syndrome in the adult U.S. population, 1999-2010. J Am Coll Cardiol
2013; 62: 697–703.
Epigenomics, gestational programming and metabolic syndrome
M Desai et al
638
International Journal of Obesity (2015) 633 – 641 © 2015 Macmillan Publishers Limited
6 Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult
obesity in the United States, 2011-2012. JAMA 2014; 311: 806–814.
7 Surkan PJ, Hsieh CC, Johansson AL, Dickman PW, Cnattingius S. Reasons for
increasing trends in large for gestational age births. Obstet Gynecol 2004; 104:
720–726.
8 Ross MG, Desai M. Developmental programming of offspring obesity,
adipogenesis, and appetite. Clin Obstet Gynecol 2013; 56: 529–536.
9 Laitinen J, Jääskeläinen A, Hartikainen AL, Sovio U, Vääräsmäki M, Pouta A et al.
Maternal weight gain during the first half of pregnancy and offspring obesity at
16 years: a prospective cohort study. BJOG 2012; 119: 716–723.
10 Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in
body mass index among US children and adolescents, 1999-2010. JAMA 2012;
307: 483–490.
11 de Rooij SR, Painter RC, Holleman F, Bossuyt PM, Roseboom TJ. The metabolic
syndrome in adults prenatally exposed to the Dutch famine. Am J Clin Nutr 2007;
86: 1219–1224.
12 Desai M, Gayle D, Babu J, Ross MG. Programmed obesity in intrauterine growthrestricted
newborns: modulation by newborn nutrition. Am J Physiol Regul Integr
Comp Physiol 2005; 288: R91–R96.
13 Desai M, Jellyman JK, Han G, Beall M, Lane RH, Ross MG. Maternal obesity and
high-fat diet program offspring metabolic syndrome. Am J Obstet Gynecol 2014;
211: 237.e1–237.e13.
14 Vickers MH, Krechowec SO, Breier BH. Is later obesity programmed in utero?
Curr Drug Targets 2007; 8: 923–934.
15 Remacle C, Bieswal F, Reusens B. Programming of obesity and cardiovascular
disease. Int J Obes Relat Metab Disord 2004; 28: S46–S53.
16 Barker DJ, Osmond C, Kajantie E, Eriksson JG. Growth and chronic disease:
findings in the Helsinki Birth Cohort. Ann Hum Biol 2009; 36: 445–458.
17 Barker DJ. The developmental origins of adult disease. Eur J Epidemiol 2003; 18:
733–736.
18 Euser AM, Finken MJ, Keijzer-Veen MG, Hille ET, Wit JM, Dekker FWDutch POPS-19
Collaborative Study Group. Associations between prenatal and infancy weight gain
and BMI, fat mass, and fat distribution in young adulthood: a prospective cohort
study in males and females born very preterm. Am J Clin Nutr 2005; 81: 480–487.
19 Monteiro PO, Victora CG. Rapid growth in infancy and childhood and obesity in
later life--a systematic review. Obes Rev 2005; 6: 143–154.
20 Boney CM, Verma A, Tucker R, Vohr BR. Metabolic syndrome in childhood:
association with birth weight, maternal obesity, and gestational diabetes
mellitus. Pediatrics 2005; 115: e290–e296.
21 Oken E, Rifas-Shiman SL, Field AE, Frazier AL, Gillman MW. Maternal gestational
weight gain and offspring weight in adolescence. Obstet Gynecol 2008; 112:
999–1006.
22 Armitage JA, Poston L, Taylor PD. Developmental origins of obesity and the
metabolic syndrome: the role of maternal obesity. Front Horm Res 2008; 36: 73–84.
23 Pettitt DJ, Jovanovic L. Birth weight as a predictor of type 2 diabetes mellitus: the
U-shaped curve. Curr Diab Rep 2001; 1: 78–81.
24 Ong KK. Size at birth, postnatal growth and risk of obesity. Horm Res 2006; 65:
65–69.
25 McMillen IC, Robinson JS. Developmental origins of the metabolic syndrome:
prediction, plasticity, and programming. Physiol Rev 2005; 85: 571–633.
26 Desai M, Hales CN. Role of fetal and infant growth in programming metabolism
in later life. Biol Rev Camb Philos Soc 1997; 72: 329–348.
27 Seckl JR, Meaney MJ. Glucocorticoid programming. Ann NY Acad Sci 2004; 1032:
63–84.
28 Bol VV, Delattre AI, Reusens B, Raes M, Remacle C. Forced catch-up growth after fetal
protein restriction alters the adipose tissue gene expression program leading to
obesity in adult mice. Am J Physiol Regul Integr Comp Physiol 2009; 297: R291–R299.
29 Jones AP, Simson EL, Friedman MI. Gestational undernutrition and the development
of obesity in rats. J Nutr 1984; 114: 1484–1492.
30 White CL, Purpera MN, Morrison CD. Maternal obesity is necessary for programming
effect of high-fat diet on offspring. Am J Physiol Regul Integr Comp
Physiol 2009; 296: R1464–R1472.
31 Howie GJ, Sloboda DM, Kamal T, Vickers MH. Maternal nutritional history predicts
obesity in adult offspring independent of postnatal diet. J Physiol 2009; 587:
905–915.
32 Bird A. Perceptions of epigenetics. Nature 2007; 447: 396–398.
33 Dolinoy DC, Jirtle RL. Environmental epigenomics in human health and disease.
Environ Mol Mutagen 2008; 49: 4–8.
34 Feil R, Fraga MF. Epigenetics and the environment: emerging patterns and
implications. Nat Rev Genet 2012; 13: 97–109.
35 Lister R, Pelizzola M, Dowen RH, Hawkins RD, Hon G, Tonti-Filippini J et al.
Human DNA methylomes at base resolution show widespread epigenomic
differences. Nature 2009; 462: 315–322.
36 Robertson KD, Wolffe AP. DNA methylation in health and disease. Nat Rev Genet
2000; 1: 11–19.
37 Clarke HJ. Nuclear and chromatin composition of mammalian gametes and early
embryos. Biochem Cell Biol 1992; 70: 856–866.
38 Weaver JR, Susiarjo M, Bartolomei MS. Imprinting and epigenetic changes in the
early embryo. Mamm Genome 2009; 20: 532–543.
39 Caldji C, Hellstrom IC, Zhang TY, Diorio J, Meaney MJ. Environmental regulation
of the neural epigenome. FEBS Lett 2011; 585: 2049–2058.
40 Guo JU, Ma DK, Mo H, Ball MP, Jang MH, Bonaguidi MA et al. Neuronal activity
modifies the DNA methylation landscape in the adult brain. Nat Neurosci 2011;
14: 1345–1351.
41 Horvath S. DNA methylation age of human tissues and cell types. Genome Biol
2013; 14: R115.
42 Fang M, Chen D, Yang CS. Dietary polyphenols may affect DNA methylation.
J Nutr 2007; 137: 223S–228S.
43 Burdge GC, Hoile SP, Uller T, Thomas NA, Gluckman PD, Hanson MA et al.
Progressive, transgenerational changes in offspring phenotype and epigenotype
following nutritional transition. PLoS One 2011; 6: e28282.
44 Jenuwein T, Allis CD. Translating the histone code. Science 2001; 293: 1074–1080.
45 Cosgrove MS. Histone proteomics and the epigenetic regulation of nucleosome
mobility. Expert Rev Proteomics 2007; 4: 465–478.
46 Higgs PG, Lehman N. The RNA World: molecular cooperation at the origins
of life. Nat Rev Genet 2015; 16: 7–17.
47 Taft RJ, Pang KC, Mercer TR, Dinger M, Mattick JS. Non-coding RNAs: regulators
of disease. J Pathol 2010; 220: 126–139.
48 Rinn JL, Kertesz M, Wang JK, Squazzo SL, Xu X, Brugmann SA et al. Functional
demarcation of active and silent chromatin domains in human HOX loci by
noncoding RNAs. Cell 2007; 129: 1311–1323.
49 Mercer TR, Dinger ME, Sunkin SM, Mehler MF, Mattick JS. Specific expression of long
noncoding RNAs in the mouse brain. Proc Natl Acad Sci USA 2008; 105: 716–721.
50 Clemson CM, Hutchinson JN, Sara SA, Ensminger AW, Fox AH, Chess A et al. An
architectural role for a nuclear noncoding RNA: NEAT1 RNA is essential for the
structure of paraspeckles. Mol Cell 2009; 33: 717–726.
51 Sun L, Goff LA, Trapnell C, Alexander R, Lo KA, Hacisuleyman E et al. Long noncoding
RNAs regulate adipogenesis. Proc Natl Acad Sci USA 2013; 110: 3387–3392.
52 Zhao XY, Li S, Wang GX, Yu Q, Lin JD. A long noncoding RNA transcriptional
regulatory circuit drives thermogenic adipocyte differentiation. Mol Cell 2014; 55:
372–382.
53 Chen K, Rajewsky N. The evolution of gene regulation by transcription factors
and microRNAs. Nat Rev Genet 2007; 8: 93–103.
54 Ding XC, Weiler J, Grosshans H. Regulating the regulators: mechanisms
controlling the maturation of microRNAs. Trends Biotechnol 2009; 27: 27–36.
55 Bouchard L, Rabasa-Lhoret R, Faraj M, Lavoie ME, Mill J, Pérusse L et al. Differential
epigenomic and transcriptomic responses in subcutaneous adipose tissue between
low and high responders to caloric restriction. Am J Clin Nutr 2010; 91: 309–320.
56 McGee SL, Hargreaves M. Exercise and skeletal muscle glucose transporter 4
expression: molecular mechanisms. Clin Exp Pharmacol Physiol 2006; 33: 395–399.
57 Fraga MF, Ballestar E, Paz MF, Ropero S, Setien F, Ballestar ML et al. Epigenetic
differences arise during the lifetime of monozygotic twins. Proc Natl Acad Sci USA
2005; 102: 10604–10609.
58 Moleres A, Campión J, Milagro FI, Marcos A, Campoy C, Garagorri JM et al.
Differential DNA methylation patterns between high and low responders
to a weight loss intervention in overweight or obese adolescents: the
EVASYON study. FASEB J 2013; 27: 2504–2512.
59 Morgan HD, Sutherland HG, Martin DI, Whitelaw E. Epigenetic inheritance at the
agouti locus in the mouse. Nat Genet 1999; 23: 314–318.
60 Waterland RA, Jirtle RL. Transposable elements: targets for early nutritional
effects on epigenetic gene regulation. Mol Cell Biol 2003; 23: 5293–5300.
61 Cropley JE, Suter CM, Beckman KB, Martin DI. Germ-line epigenetic modification
of the murine A vy allele by nutritional supplementation. Proc Natl Acad Sci USA
2006; 103: 17308–17312.
62 Waterland RA, Travisano M, Tahiliani KG. Diet-induced hypermethylation at
agouti viable yellow is not inherited transgenerationally through the female.
FASEB J 2007; 21: 3380–3385.
63 Luedi PP, Hartemink AJ, Jirtle RL. Genome-wide prediction of imprinted
murine genes. Genome Res 2005; 15: 875–884.
64 Waterland RA, Lin JR, Smith CA, Jirtle RL. Post-weaning diet affects genomic
imprinting at the insulin-like growth factor 2 (Igf2) locus. Hum Mol Genet 2006;
15: 705–716.
65 Aasheim ET, Hofsø D, Hjelmesaeth J, Birkeland KI, Bøhmer T. Vitamin status in
morbidly obese patients: a cross-sectional study. Am J Clin Nutr 2008; 87:
362–369.
66 Weinstein LS, Xie T, Qasem A, Wang J, Chen M. The role of GNAS and other
imprinted genes in the development of obesity. Int J Obes (Lond) 2010; 34: 6–17.
67 Milagro FI, Campión J, García-Díaz DF, Goyenechea E, Paternain L, Martínez JA.
High fat diet-induced obesity modifies the methylation pattern of leptin
promoter in rats. J Physiol Biochem 2009; 65: 1–9.
Epigenomics, gestational programming and metabolic syndrome
M Desai et al
639
© 2015 Macmillan Publishers Limited International Journal of Obesity (2015) 633 – 641
68 Yang BT, Dayeh TA, Kirkpatrick CL, Taneera J, Kumar R, Groop L et al. Insulin
promoter DNA methylation correlates negatively with insulin gene expression
and positively with HbA(1c) levels in human pancreatic islets. Diabetologia 2011;
54: 360–367.
69 Noer A, Boquest AC, Collas P. Dynamics of adipogenic promoter DNA methylation
during clonal culture of human adipose stem cells to senescence. BMC Cell
Biol 2007; 8: 18.
70 Stepanow S, Reichwald K, Huse K, Gausmann U, Nebel A, Rosenstiel P et al.
Allele-specific, age-dependent and BMI-associated DNA methylation of
human MCHR1. PLoS One 2011; 6: e17711.
71 Yokomori N, Tawata M, Onaya T. DNA demethylation during the differentiation
of 3T3-L1 cells affects the expression of the mouse GLUT4 gene. Diabetes 1999;
48: 685–690.
72 Fujiki K, Kano F, Shiota K, Murata M. Expression of the peroxisome proliferator
activated receptor gamma gene is repressed by DNA methylation in visceral
adipose tissue of mouse models of diabetes. BMC Biol 2009; 7: 38.
73 Musri MM, Corominola H, Casamitjana R, Gomis R, Párrizas M. Histone H3 lysine 4
dimethylation signals the transcriptional competence of the adiponectin promoter
in preadipocytes. J Biol Chem 2006; 281: 17180–17188.
74 Sullivan KE, Reddy AB, Dietzmann K, Suriano AR, Kocieda VP, Stewart M et al.
Epigenetic regulation of tumor necrosis factor alpha. Mol Cell Biol 2007; 27:
5147–5160.
75 Kilpeläinen TO, Zillikens MC, Stančákova A, Finucane FM, Ried JS, Langenberg C
et al. Genetic variation near IRS1 associates with reduced adiposity and an
impaired metabolic profile. Nat Genet 2011; 43: 753–760.
76 Musri MM, Párrizas M. Epigenetic regulation of adipogenesis. Curr Opin Clin Nutr
Metab Care 2012; 15: 342–349.
77 Ge K. Epigenetic regulation of adipogenesis by histone methylation. Biochim
Biophys Acta 2012; 1819: 727–732.
78 Li HX, Xiao L, Wang C, Gao JL, Zhai YG. Review: Epigenetic regulation of adipocyte
differentiation and adipogenesis. J Zhejiang Univ Sci B 2010; 11: 784–791.
79 Wang X, Zhu H, Snieder H, Su S, Munn D, Harshfield G et al. Obesity related
methylation changes in DNA of peripheral blood leukocytes. BMC Med 2010; 8: 87.
80 Jufvas A, Sjödin S, Lundqvist K, Amin R, Vener AV, Strålfors P. Global differences
in specific histone H3 methylation are associated with overweight and type 2
diabetes. Clin Epigenetics 2013; 5: 15.
81 Ortega FJ, Moreno-Navarrete JM, Pardo G, Sabater M, Hummel M, Ferrer A et al.
MiRNA expression profile of human subcutaneous adipose and during adipocyte
differentiation. PLoS One 2010; 5: e9022.
82 Tateishi K, Okada Y, Kallin EM, Zhang Y. Role of Jhdm2a in regulating metabolic
gene expression and obesity resistance. Nature 2009; 458: 757–761.
83 Inagaki T, Tachibana M, Magoori K, Kudo H, Tanaka T, Okamura M et al. Obesity
and metabolic syndrome in histone demethylase JHDM2a-deficient mice. Genes
Cells 2009; 14: 991–1001.
84 Lu YL, Jing W, Feng LS, Zhang L, Xu JF, You TJ et al. Effects of hypoxic exercise
training on microRNA expression and lipid metabolism in obese rat livers.
J Zhejiang Univ Sci B 2014; 15: 820–829.
85 Son YH, Ka S, Kim AY, Kim JB. Regulation of Adipocyte Differentiation via
MicroRNAs. Endocrinol Metab (Seoul) 2014; 29: 122–135.
86 Vinnikov IA, Hajdukiewicz K, Reymann J, Beneke J, Czajkowski R, Roth LC et al.
Hypothalamic miR-103 protects from hyperphagic obesity in mice. J Neurosci
2014; 34: 10659–10674.
87 Funato H, Oda S, Yokofujita J, Igarashi H, Kuroda M. Fasting and high-fat
diet alter histone deacetylase expression in the medial hypothalamus. PLoS One
2011; 6: e18950.
88 McGregor RA, Choi MS. microRNAs in the regulation of adipogenesis and obesity.
Curr Mol Med 2011; 11: 304–316.
89 Yang QY, Liang JF, Rogers CJ, Zhao JX, Zhu MJ, Du M. Maternal obesity induces
epigenetic modifications to facilitate Zfp423 expression and enhance adipogenic
differentiation in fetal mice. Diabetes 2013; 62: 3727–3735.
90 Borengasser SJ, Zhong Y, Kang P, Lindsey F, Ronis MJ, Badger TM et al. Maternal
obesity enhances white adipose tissue differentiation and alters genome-scale
DNA methylation in male rat offspring. Endocrinology 2013; 154: 4113–4125.
91 Kamei Y, Suganami T, Ehara T, Kanai S, Hayashi K, Yamamoto Y et al. Increased
expression of DNA methyltransferase 3a in obese adipose tissue: studies with
transgenic mice. Obesity (Silver Spring) 2010; 18: 314–321.
92 Lee J, Saha PK, Yang QH, Lee S, Park JY, Suh Y et al. Targeted inactivation of MLL3
histone H3-Lys-4 methyltransferase activity in the mouse reveals vital roles for
MLL3 in adipogenesis. Proc Natl Acad Sci USA 2008; 105: 19229–19234.
93 Heijmans BT, Tobi EW, Stein AD, Putter H, Blauw GJ, Susser ES et al. Persistent
epigenetic differences associated with prenatal exposure to famine in humans.
Proc Natl Acad Sci USA 2008; 105: 17046–17049.
94 Tobi EW, Lumey LH, Talens RP, Kremer D, Putter H, Stein AD et al. DNA
methylation differences after exposure to prenatal famine are common and
timing- and sex-specific. Hum Mol Genet 2009; 18: 4046–4053.
95 Soubry A, Murphy SK, Wang F, Huang Z, Vidal AC, Fuemmeler BF et al. Newborns
of obese parents have altered DNA methylation patterns at imprinted genes.
Int J Obes (Lond) 2013; e-pub ahead of print 25 October 2013; doi:10.1038/
ijo.2013.193.
96 Soubry A, Schildkraut JM, Murtha A, Wang F, Huang Z, Bernal A et al. Paternal
obesity is associated with IGF2 hypomethylation in newborns: results from a
Newborn Epigenetics Study (NEST) cohort. BMC Med 2013; 11: 29.
97 Morales E, Groom A, Lawlor DA, Relton CL. DNA methylation signatures in cord
blood associated with maternal gestational weight gain: results from the
ALSPAC cohort. BMC Res Notes 2014; 7: 278.
98 Godfrey KM, Sheppard A, Gluckman PD, Lillycrop KA, Burdge GC, McLean C et al.
Epigenetic gene promoter methylation at birth is associated with child's later
adiposity. Diabetes 2011; 60: 1528–1534.
99 Campión J, Milagro F, Martínez JA. Epigenetics and obesity. Prog Mol Biol Transl
Sci 2010; 94: 291–347.
100 Lavebratt C, Almgren M, Ekström TJ. Epigenetic regulation in obesity. Int J Obes
(Lond) 2012; 36: 757–765.
101 Lillycrop KA, Burdge GC. Epigenetic changes in early life and future risk of
obesity. Int J Obes (Lond) 2011; 35: 72–83.
102 Wang J, Wu Z, Li D, Li N, Dindot SV, Satterfield MC et al. Nutrition, epigenetics,
and metabolic syndrome. Antioxid Redox Signal 2012; 17: 282–301.
103 Ganu RS, Harris RA, Collins K, Aagaard KM. Maternal diet: a modulator for
epigenomic regulation during development in nonhuman primates
and humans. Int J Obes Suppl 2012; 2: S14–S18.
104 Tosh DN, Fu Q, Callaway CW, McKnight RA, McMillen IC, Ross MG et al.
Epigenetics of programmed obesity: alteration in IUGR rat hepatic IGF1 mRNA
expression and histone structure in rapid vs delayed postnatal catch-up growth.
Am J Physiol Gastrointest Liver Physiol 2010; 299: G1023–G1029.
105 Desai M, Jellyman JK, Han G, Beall MH, Ross MG. Mechanism of programmed
obesity in intrauterine growth restricted newborns: epigenetic mediated early
induction of adipocyte differentiation contributes to enhanced adipogenesis.
J Dev Orig Health Dis 2013: 4(Suppl 2): S138.
106 Cho CE, Sánchez-Hernández D, Reza-López SA, Huot PS, Kim YI, Anderson GH. High
folate gestational and post-weaning diets alter hypothalamic feeding pathways by
DNA methylation in Wistar rat offspring. Epigenetics 2013; 8: 710–719.
107 Vucetic Z, Kimmel J, Totoki K, Hollenbeck E, Reyes TM. Maternal high-fat
diet alters methylation and gene expression of dopamine and opioidrelated
genes. Endocrinology 2010; 151: 4756–4764.
108 Stevens A, Begum G, Cook A, Connor K, Rumball C, Oliver M et al. Epigenetic
changes in the hypothalamic proopiomelanocortin and glucocorticoid receptor
genes in the ovine fetus after periconceptional undernutrition. Endocrinology
2010; 151: 3652–3664.
109 Plagemann A, Harder T, Brunn M, Harder A, Roepke K, Wittrock-Staar M et al.
Hypothalamic proopiomelanocortin promoter methylation becomes altered by
early overfeeding: an epigenetic model of obesity and the metabolic syndrome.
J Physiol 2009; 587: 4963–4976.
110 Raychaudhuri N, Raychaudhuri S, Thamotharan M, Devaskar SU. Histone code
modifications repress glucose transporter 4 expression in the intrauterine
growth-restricted offspring. J Biol Chem 2008; 283: 13611–13626.
111 Desai M, Ross MG. Fetal programming of adipose tissue: effects of intrauterine
growth restriction and maternal obesity/high-fat diet. Semin Reprod Med 2011;
29: 237–245.
112 Fan S, Zhang X. CpG island methylation pattern in different human tissues and its
correlation with gene expression. Biochem Biophys Res Commun 2009; 383: 421–425.
113 Flanagan JM, Popendikyte V, Pozdniakovaite N, Sobolev M, Assadzadeh A,
Schumacher A et al. Intra- and interindividual epigenetic variation in human
germ cells. Am J Hum Genet 2006; 79: 67–84.
114 Trasler JM. Epigenetics in spermatogenesis. Mol Cell Endocrinol 2009; 306: 33–36.
115 Guibert S, Forné T, Weber M. Global profiling of DNA methylation erasure in
mouse primordial germ cells. Genome Res 2012; 22: 633–641.
116 Barres R, Zierath JR. DNA methylation in metabolic disorders. Am J Clin Nutr
2011; 93: 897S–900S.
117 Skinner MK. Environmental epigenetic transgenerational inheritance and
somatic epigenetic mitotic stability. Epigenetics 2011; 6: 838–842.
118 Lange UC, Schneider R. What an epigenome remembers. Bioessays 2010; 32:
659–668.
119 Johnson PC, Logue J, McConnachie A, Abu-Rmeileh NM, Hart C, Upton MN et al.
Intergenerational change and familial aggregation of body mass index.
Eur J Epidemiol 2012; 27: 53–61.
120 Jodkowska M, Oblacińska A, Tabak I, Mikiel-Kostyra K. [Overweight and obesity
among parents and their 13-old children in Poland]. Przegl Epidemiol 2011; 65:
497–502.
121 Cnattingius S, Villamor E, Lagerros YT, Wikström AK, Granath F. High birth weight
and obesity—a vicious circle across generations. Int J Obes (Lond) 2012; 36:
1320–1324.
Epigenomics, gestational programming and metabolic syndrome
M Desai et al
640
International Journal of Obesity (2015) 633 – 641 © 2015 Macmillan Publishers Limited
122 Smith J, Cianflone K, Biron S, Hould FS, Lebel S, Marceau S et al. Effects of
maternal surgical weight loss in mothers on intergenerational transmission of
obesity. J Clin Endocrinol Metab 2009; 94: 4275–4283.
123 Skinner MK. What is an epigenetic transgenerational phenotype? F3 or F2.
Reprod Toxicol 2008; 25: 2–6.
124 Paoloni-Giacobino A. Epigenetic effects of methoxychlor and vinclozolin on male
gametes. Vitam Horm 2014; 94: 211–227.
125 Radford EJ, Ito M, Shi H, Corish JA, Yamazawa K, Isganaitis E et al. In utero effects.
In utero undernourishment perturbs the adult sperm methylome and
intergenerational metabolism. Science 2014; 345: 1255903.
126 Dolinoy DC, Huang D, Jirtle RL. Maternal nutrient supplementation counteracts
bisphenol A-induced DNA hypomethylation in early development. Proc Natl
Acad Sci USA 2007; 104: 13056–13061.
127 Prins GS, Tang WY, Belmonte J, Ho SM. Developmental exposure to bisphenol A
increases prostate cancer susceptibility in adult rats: epigenetic mode of action
is implicated. Fertil Steril 2008; 89: e41.
128 Skinner MK, Anway MD, Savenkova MI, Gore AC, Crews D. Transgenerational
epigenetic programming of the brain transcriptome and anxiety behavior. PLoS
One 2008; 3: e3745.
129 Salian S, Doshi T, Vanage G. Perinatal exposure of rats to Bisphenol A affects
fertility of male offspring--an overview. Reprod Toxicol 2011; 31: 359–362.
130 Bäckdahl L, Bushell A, Beck S. Inflammatory signalling as mediator of epigenetic
modulation in tissue-specific chronic inflammation. Int J Biochem Cell Biol 2009;
41: 176–184.
131 Desai M, Beall M, Ross MG. Developmental origins of obesity: programmed
adipogenesis. Curr Diab Rep 2013; 13: 27–33.
132 Singh K, Molenaar AJ, Swanson KM, Gudex B, Arias JA, Erdman RA et al. Epigenetics:
a possible role in acute and transgenerational regulation of dairy cow
milk production. Animal 2012; 6: 375–381.
133 Kinyamu HK, Jefferson WN, Archer TK. Intersection of nuclear receptors and the
proteasome on the epigenetic landscape. Environ Mol Mutagen 2008; 49: 83–95.
134 Green CD, Han JD. Epigenetic regulation by nuclear receptors. Epigenomics 2011;
3: 59–72.
135 Kato S, Yokoyama A, Fujiki R. Nuclear receptor coregulators merge transcriptional
coregulation with epigenetic regulation. Trends Biochem Sci 2011; 36:
272–281.
136 Klinge CM. Estrogen regulation of microRNA expression. Curr Genomics 2009; 10:
169–183.
137 Shi XB, Tepper CG, deVere White RW. Cancerous miRNAs and their regulation.
Cell Cycle 2008; 7: 1529–1538.
138 Aerts L, Van Assche FA. Intra-uterine transmission of disease. Placenta 2003; 24:
905–911.
139 Aerts L, Van Assche FA. Animal evidence for the transgenerational development
of diabetes mellitus. Int J Biochem Cell Biol 2006; 38: 894–903.
140 Ding GL, Huang HF. Paternal transgenerational glucose intolerance with epigenetic
alterations in second generation offspring of GDM. Asian J Androl 2013; 15: 451–452.
141 Jimenez-Chillaron JC, Isganaitis E, Charalambous M, Gesta S, Pentinat-Pelegrin T,
Faucette RR et al. Intergenerational transmission of glucose intolerance and
obesity by in utero undernutrition in mice. Diabetes 2009; 58: 460–468.
142 Yajnik CS. The lifecycle effects of nutrition and body size on adult adiposity,
diabetes and cardiovascular disease. Obes Rev 2002; 3: 217–224.
143 Klebanoff MA, Meirik O, Berendes HW. Second-generation consequences of
small-for-dates birth. Pediatrics 1989; 84: 343–347.
144 Emanuel I, Filakti H, Alberman E, Evans SJ. Intergenerational studies of human
birthweight from the 1958 birth cohort. 1. Evidence for a multigenerational effect.
Br J Obstet Gynaecol 1992; 99: 67–74.
145 Lumey LH. Decreased birthweights in infants after maternal in utero exposure to
the Dutch famine of 1944-1945. Paediatr Perinat Epidemiol 1992; 6: 240–253.
146 Lumey LH, Stein AD, Ravelli AC. Timing of prenatal starvation in women and
birth weight in their first and second born offspring: the Dutch Famine Birth
Cohort study. Eur J Obstet Gynecol Reprod Biol 1995; 61: 23–30.
147 Stein AD, Lumey LH. The relationship between maternal and offspring birth
weights after maternal prenatal famine exposure: the Dutch Famine Birth
Cohort Study. Hum Biol 2000; 72: 641–654.
148 Painter RC, Osmond C, Gluckman P, Hanson M, Phillips DI, Roseboom TJ.
Transgenerational effects of prenatal exposure to the Dutch famine on neonatal
adiposity and health in later life. BJOG 2008; 115: 1243–1249.
149 Veenendaal MV, Painter RC, de Rooij SR, Bossuyt PM, van der Post JA, Gluckman
PD et al. Transgenerational effects of prenatal exposure to the 1944-45
Dutch famine. BJOG 2013; 120: 548–553.
150 Huang C, Li Z, Narayan KM, Williamson DF, Martorell R. Bigger babies born to
women survivors of the 1959-1961 Chinese famine: a puzzle due to survival
selection? J Dev Orig Health Dis 2010; 1: 412–418.
151 Pembrey ME, Bygren LO, Kaati G, Edvinsson S, Northstone K, Sjöström M et al.
Sex-specific, male-line transgenerational responses in humans. Eur J Hum Genet
2006; 14: 159–166.
152 Kaati G, Bygren LO, Edvinsson S. Cardiovascular and diabetes mortality
determined by nutrition during parents' and grandparents' slow growth period.
Eur J Hum Genet 2002; 10: 682–688.
153 Dunn GA, Bale TL. Maternal high-fat diet effects on third-generation female body
size via the paternal lineage. Endocrinology 2011; 152: 2228–2236.
154 Stewart RJ, Preece RF, Sheppard HG. Twelve generations of marginal protein
deficiency. Br J Nutr 1975; 33: 233–253.
155 Vickers MH, Breier BH, Cutfield WS, Hofman PL, Gluckman PD. Fetal
origins of hyperphagia, obesity, and hypertension and postnatal amplification
by hypercaloric nutrition. Am J Physiol Endocrinol Metab 2000; 279:
E83–E87.
156 Pentinat T, Ramon-Krauel M, Cebria J, Diaz R, Jimenez-Chillaron JC. Transgenerational
inheritance of glucose intolerance in a mouse model of neonatal
overnutrition. Endocrinology 2010; 151: 5617–5623.
157 Pinheiro AR, Salvucci ID, Aguila MB, Mandarim-de-Lacerda CA. Protein restriction
during gestation and/or lactation causes adverse transgenerational effects on
biometry and glucose metabolism in F1 and F2 progenies of rats. Clin Sci (Lond)
2008; 114: 381–392.
158 Thamotharan M, Garg M, Oak S, Rogers LM, Pan G, Sangiorgi F et al. Transgenerational
inheritance of the insulin-resistant phenotype in embryo-transferred
intrauterine growth-restricted adult female rat offspring. Am J Physiol Endocrinol
Metab 2007; 292: E1270–E1279.
159 Benyshek DC, Johnston CS, Martin JF. Glucose metabolism is altered in the
adequately-nourished grand-offspring (F3 generation) of rats malnourished
during gestation and perinatal life. Diabetologia 2006; 49: 1117–1119.
160 Martin JF, Johnston CS, Han CT, Benyshek DC. Nutritional origins of insulin
resistance: a rat model for diabetes-prone human populations. J Nutr 2000; 130:
741–744.
161 Zambrano E, Martínez-Samayoa PM, Bautista CJ, Deás M, Guillén L,
Rodríguez-González GL et al. Sex differences in transgenerational alterations
of growth and metabolism in progeny (F2) of female offspring (F1) of rats
fed a low protein diet during pregnancy and lactation. J Physiol 2005; 566:
225–236.
162 Burdge GC, Slater-Jefferies J, Torrens C, Phillips ES, Hanson MA, Lillycrop KA.
Dietary protein restriction of pregnant rats in the F0 generation induces altered
methylation of hepatic gene promoters in the adult male offspring in the F1 and
F2 generations. Br J Nutr 2007; 97: 435–439.
163 Lane N, Dean W, Erhardt S, Hajkova P, Surani A, Walter J et al. Resistance of IAPs
to methylation reprogramming may provide a mechanism for epigenetic
inheritance in the mouse. Genesis 2003; 35: 88–93.
164 Drake AJ, Walker BR, Seckl JR. Intergenerational consequences of fetal programming
by in utero exposure to glucocorticoids in rats. Am J Physiol Regul
Integr Comp Physiol 2005; 288: R34–R38.
165 Sjöström L, Lindroos AK, Peltonen M, Torgerson J, Bouchard C, Carlsson B et al.
Lifestyle, diabetes, and cardiovascular risk factors 10 years after bariatric surgery.
N Engl J Med 2004; 351: 2683–2693.
166 Rao SR. Inflammatory markers and bariatric surgery: a meta-analysis. Inflamm Res
2012; 61: 789–807.
167 Buchwald H, Avidor Y, Braunwald E, Jensen MD, Pories W, Fahrbach K et al.
Bariatric surgery: a systematic review and meta-analysis. JAMA 2004; 292:
1724–1737.
168 Scopinaro N, Marinari GM, Camerini GB, Papadia FS, Adami GF. Specific effects of
biliopancreatic diversion on the major components of metabolic syndrome: a
long-term follow-up study. Diabetes Care 2005; 28: 2406–2411.
169 Kral JG, Biron S, Simard S, Hould FS, Lebel S, Marceau S et al. Large maternal
weight loss from obesity surgery prevents transmission of obesity to children
who were followed for 2 to 18 years. Pediatrics 2006; 118: e1644–e1649.
170 Berisha SZ, Serre D, Schauer P, Kashyap SR, Smith JD. Changes in whole blood
gene expression in obese subjects with type 2 diabetes following bariatric
surgery: a pilot study. PLoS One 2011; 6: e16729.
171 Park JJ, Berggren JR, Hulver MW, Houmard JA, Hoffman EP. GRB14, GPD1,
and GDF8 as potential network collaborators in weight loss-induced
improvements in insulin action in human skeletal muscle. Physiol Genomics
2006; 27: 114–121.
172 Guénard F, Tchernof A, Deshaies Y, Cianflone K, Kral JG, Marceau P et al.
Methylation and expression of immune and inflammatory genes in the offspring
of bariatric bypass surgery patients. J Obes 2013; 2013: 492170.
173 Guénard F, Deshaies Y, Cianflone K, Kral JG, Marceau P, Vohl MC. Differential
methylation in glucoregulatory genes of offspring born before vs after maternal
gastrointestinal bypass surgery. Proc Natl Acad Sci USA 2013; 110: 11439–11444.
Epigenomics, gestational programming and metabolic syndrome
M Desai et al
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