Palomar College Intergenerational Transmission of The Effects of Maternal Exposure to Childhood Maltreatment on Offspring Obesity Risk Summary

Please use the number | lettering scheme used in the prompt to label your response

A fetal programming perspective.

Read and Summarize [using APA format] the posted Journal Article ‘Intergenerational transmission of the effects of maternal exposure to childhood maltreatment on offspring obesity risk: A fetal programming perspective’ located immediately below the link to this assignment

Comment

In lecture we discussed the epigenetics and how it has been shown that mothers who are morbidly obese during pregnancy risk genetically predisposing their offspring to obesity. The article proposes that ‘maternal conditions and states experienced prior to conception, such as stress, obesity and metabolic dysfunction, may program offspring obesity risk’If you had to guess, what could be the possible long-term impact of this ‘perspective’ onWomen’s ‘fear’ of having childrenSociety’s perception of the seriousness of child maltreatmentThe perception of mother’s whose children are obese Psychoneuroendocrinology 116 (2020) 104659
Contents lists available at ScienceDirect
Psychoneuroendocrinology
journal homepage: www.elsevier.com/locate/psyneuen
Intergenerational transmission of the eﬀects of maternal exposure to
childhood maltreatment on oﬀspring obesity risk: A fetal programming
perspective
T
Karen L. Lindsaya,e, Sonja Entringera,e,f, Claudia Bussa,e,f, Pathik D. Wadhwaa,b,c,d,e,*
a
Department of Pediatrics, University of California, Irvine, School of Medicine, CA 92697, USA
Department of Psychiatry and Human Behavior, University of California, Irvine, School of Medicine, CA 92697, USA
c
Department of Obstetrics and Gynecology, University of California, Irvine, School of Medicine, CA 92697, USA
d
Department of Epidemiology, University of California, Irvine, School of Medicine, CA 92697, USA
e
UCI Development, Health and Disease Research Program, University of California, Irvine, School of Medicine, CA 92697, USA
f
Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health (BIH), Institute of Medical Psychology, Germany
b
A R T I C LE I N FO
A B S T R A C T
Keywords:
Childhood obesity
Childhood maltreatment
Intergenerational transmission
Fetal programming
Pregnancy
Gestational biology
Childhood obesity constitutes a major global public health challenge. A substantial body of evidence suggests
that conditions and states experienced by the embryo/fetus in utero can result in structural and functional
changes in cells, tissues, organ systems and homeostatic set points related to obesity. Furthermore, growing
evidence suggests that maternal conditions and states experienced prior to conception, such as stress, obesity and
metabolic dysfunction, may spill over into pregnancy and inﬂuence those key aspects of gestational biology that
program oﬀspring obesity risk. In this narrative review, we advance a novel hypothesis and life-span framework
to propose that maternal exposure to childhood maltreatment may constitute an important and as-yet-underappreciated risk factor implicated in developmental programming of oﬀspring obesity risk via the long-term
psychological, biological and behavioral sequelae of childhood maltreatment exposure. In this context, our
framework considers the key role of maternal-placental-fetal endocrine, immune and metabolic pathways and
also other processes including epigenetics, oocyte mitochondrial biology, and the maternal and infant microbiomes. Finally, our paper discusses future research directions required to elucidate the nature and mechanisms
of the intergenerational transmission of the eﬀects of maternal childhood maltreatment on oﬀspring obesity risk.
1. Introduction
Childhood obesity represents a major, global public health challenge. Its etiology is multi-factorial, and currently identiﬁed risk factors
account for only a moderate proportion of its prevalence (Robinson
et al., 2017; van der Klaauw and Farooqi, 2015; Willyard, 2014). Furthermore, once established, obesity is extremely diﬃcult to reverse
(Schwartz et al., 2017), underscoring the critical importance of primary
prevention (Ghoorah et al., 2014). Thus, the elucidation of additional
risk factors remains a key priority. In this perspectives paper, we advance the concept that an additional determinant of an individual’s risk
for childhood obesity may arise from her or his mother’s physiological
and emotional states prior to conception. Speciﬁcally, we hypothesize
that maternal exposure to maltreatment during the period of her own
childhood may constitute an important and novel risk factor for
increased susceptibility in her oﬀspring for the development of obesity
and metabolic dysfunction.
The extent of an individual’s exposure to obesogenic factors clearly
is an important determinant of her or his likelihood of developing
obesity. However, it also is evident that individuals vary widely in
terms of the eﬀects of obesogenic exposures on obesity risk (i.e., exhibit
considerable variation in their susceptibility) (Albuquerque et al.,
2017). Thus, primary prevention of obesity necessitates not only addressing the obesogenic exposure part of the equation, but also and
critically importantly a better understanding of the determinants of
individual diﬀerences in susceptibility to the eﬀects of obesogenic factors
(Bluher, 2019).
In this regard, growing evidence suggests developmental processes
during intrauterine life play a key role in determining susceptibility to
childhood obesity (i.e., the concept of fetal programming) (Entringer
⁎
Corresponding author at: UC Irvine Development, Health and Disease Research Program, University of California, Irvine, School of Medicine, 3117 Gillespie,
Neuroscience Research Facility (GNRF), 837 Health Sciences Road, Irvine, CA 92697, USA.
E-mail address: pwadhwa@uci.edu (P.D. Wadhwa).
https://doi.org/10.1016/j.psyneuen.2020.104659
Received 14 October 2019; Received in revised form 12 March 2020; Accepted 19 March 2020
0306-4530/ © 2020 Elsevier Ltd. All rights reserved.
Psychoneuroendocrinology 116 (2020) 104659
K.L. Lindsay, et al.
obesogenic factors.
What, then, determines individual diﬀerences in susceptibility? The
conventional paradigm proposes that an individual’s genetic makeup
(reﬂected in DNA sequence variation) is the primary determinant of her
or his susceptibility. However, based on ﬁndings from genome wide
association and other studies, it is increasingly apparent that genetic
makeup alone (i.e., independently) accounts for only a modest proportion of the observed variance in obesity risk (Robinson et al., 2017;
Sluyter et al., 2013; van der Klaauw and Farooqi, 2015; Willyard,
2014). Even among carriers of genetic loci most strongly associated
with obesity risk (e.g., polymorphisms of the FTO gene (Albuquerque
et al., 2013; Deliard et al., 2013; Leon-Mimila et al., 2013)), it appears
that factors such as early developmental processes may moderate this
susceptibility. For example, among carriers of the FTO risk alleles, infants with a lower body mass index (BMI) are at increased risk of developing childhood obesity (Sovio et al., 2011). Thus, it is the phenotypic speciﬁcation of the initial settings or set-points of central and
peripheral systems implicated in energy balance homeostasis that appears
to play a major role in determining susceptibility for future obesity
(adiposity) risk (Schwartz et al., 2017). We note that the U.S. Endocrine
Society recently published a scientiﬁc position statement arguing that
based on the convergence of evidence, obesity should now be conceptualized as a disorder of the energy homeostasis system, rather than
simply arising from the accumulation of excess weight. Moreover, they
emphasized the need to elucidate underlying mechanisms, with a major
focus on developmental inﬂuences (Schwartz et al., 2017).
et al., 2015; Friedman, 2018). Furthermore, over and beyond eﬀects of
events during pregnancy, the importance of maternal preconceptional
conditions is becoming increasingly evident (Haire-Joshu and Tabak,
2016), as some of their long-term eﬀects carry forward and spill over
into pregnancy to impact key gestational biology-related endocrine,
immune and metabolic processes implicated in fetal programming of
childhood obesity risk. In light of these considerations, we submit that
maternal exposure to childhood maltreatment (CM) may constitute a
novel, important, and as-yet-underappreciated and understudied condition of interest. We have previously published a perspective paper
that describes our conceptual formulation by which maternal CM exposure may contribute to fetal programming of oﬀspring brain development (Buss et al., 2017). While the current paper shares many
commonalities and arguments within the context of the broader framework of CT exposure and fetal programming, we focus here on the
diﬀerent and equally important outcome of oﬀspring obesity risk.
This perspectives paper begins with an overview of the problem of
childhood obesity and the evidence for preconception and prenatal
exposures and conditions that may inﬂuence susceptibility to development of obesity via the process of fetal programming of health and
disease risk. Next, we address the issue of childhood maltreatment, with
a brief overview of its prevalence and long-term health consequences.
We then summarize ﬁndings that suggest the long-term eﬀects of CM
may not be restricted to the life span of the exposed individual alone,
but also may be transmitted across generations to inﬂuence the development and health of their oﬀspring, including oﬀspring obesity risk.
We then present our conceptual framework to describe the three key
elements which may plausibly explain an intergenerational transmission of the eﬀects of maternal CM on childhood obesity risk; i) spillover
of the adverse behavioral, psychological and physiological sequelae of
maternal CM from the preconceptional to prenatal life stage; ii) the
impact of these sequelae on various gestational biological pathways
that may program the developing fetus for an increased susceptibility
towards obesity in childhood; iii) the potential interaction of prenatal
and postnatal states and conditions related to maternal CM exposure,
which could further explain the risk for obesity development in the
child. We also present recommendations for future directions to advance this ﬁeld of research and lastly, highlight the public health signiﬁcance of this framework.
2.2. Role of developmental processes
A growing and converging body of epidemiological, clinical and
experimental evidence in humans and animals now supports the concept that phenotypic speciﬁcation of complex traits (such as the initial
setting of the energy balance homeostasis system) is an emergent property of developmental processes in early life, particularly during the
intrauterine period (i.e., the process of fetal programming of health and
disease risk) (Langley-Evans, 2006; Padmanabhan et al., 2016). In this
regard, it also is evident, ﬁrstly, that the proximate mechanism by which
gestational conditions impact phenotypic speciﬁcation is ultimately
biological in nature (Catalano and Shankar, 2017); secondly, that stressrelated maternal-placental-fetal endocrine, immune/ inﬂammatory,
oxidative and metabolic pathways may play a particularly prominent
role in this process (Entringer et al., 2015); and thirdly, that a constellation of upstream maternal biophysical, behavioral, psychological
and clinical states exert a major inﬂuence on gestational biology
(Keenan et al., 2018; Stephenson et al., 2018). Thus, primary prevention (of the establishment of increased susceptibility for obesity) implies not only the identiﬁcation of relevant modiﬁable risk factors, but
also and importantly, the critical time period(s) for intervention.
With the exception of new and controversial germline gene-editing
approaches (Ormond et al., 2017), the prenatal period may represent
one of the earliest possible windows for deploying primary prevention
strategies to target potentially modiﬁable risk factors that inﬂuence
gestational biology, in order to inﬂuence the individual’s susceptibility
for developing obesity. Furthermore, developmental trajectory models
suggest that complex phenotypes emerge through a series of interactions or conditional probabilities. That is, the likelihood of acquiring
any given phenotype is shaped by events and environments at earlier,
critical stages of development (Barker, 2002). For example, the eﬀects
of genes on fetal growth and birth outcomes are conditioned by the
intrauterine and fetal environment; the eﬀects of birth outcomes on
infant growth and health status are conditioned by events and environments during the early infancy period, and so forth.
2. The problem of childhood obesity
Obesity represents one of the most urgent national and global health
challenges because of its high prevalence and adverse health, economic
and societal consequences (Kelly et al., 2013; McPherson, 2014;
Schwartz et al., 2017). Childhood obesity is a particularly grave concern because children with obesity are substantially more likely to be
aﬀected by obesity in adulthood (Serdula et al., 1993; Whitaker et al.,
1997) and to develop obesity-related disorders at younger ages
(Dabelea and Harrod, 2013; Freedman et al., 2001) and of greater severity (Dietz, 1998; Fagot-Campagna et al., 2001; Freedman et al.,
2007). The ramiﬁcations are alarming: Owing to the increase in obesity,
life expectancy in developed countries is projected to decrease for the
ﬁrst time in recent history (Olshansky et al., 2005).
2.1. Susceptibility
The extent of any given individual’s exposure to obesogenic factors
clearly is an important determinant of her or his likelihood of developing obesity. However, it also is evident that individuals vary widely
in terms of the magnitude of eﬀects of obesogenic exposures on obesity
risk. In other words, they exhibit diﬀerences in their susceptibility for
developing obesity (Albuquerque et al., 2017). Thus, primary prevention of obesity may necessitate not only addressing the obesogenic
exposure part of the equation, but also and critically importantly, the
determinants of individual diﬀerences in susceptibility to the eﬀects of
2.3. Role of maternal preconceptional state
It is clear that maternal exposures and experiences during
2
Psychoneuroendocrinology 116 (2020) 104659
K.L. Lindsay, et al.
spectrum disorder (Collishaw et al., 2007; Plant et al., 2013; Roberts
et al., 2013), and obesity (Leonard et al., 2017; Roberts et al., 2014).
The time windows, mechanisms and pathways are not well understood,
and their elucidation is an area of considerable scientiﬁc and public
health interest and importance.
In this context, the prevailing paradigm posits that the child’s brain
represents the primary outcome of interest (Buss et al., 2017; Everaerd
et al., 2015; McLaughlin et al., 2014). However, we submit that another
child outcome of at least equal importance and public health signiﬁcance may also be implicated – that of childhood obesity risk. Direct
evidence comes from two recent large cohort studies. In a study of
16,774 mother-child dyads, Roberts et al. reported an approximately 50
% increased incidence of obesity among children (aged 9–14 yrs) of
CM-exposed mothers, with the most pronounced eﬀect in children
whose mothers were most severely abused (Roberts et al., 2014). Also,
in another study of 6718 mother-child dyads, Leonard et al. reported a
21 % increased risk of obesity among children (aged 2–5 yrs) whose
mothers were physically abused in childhood (Leonard et al., 2017).
Indirect evidence comes from the convergence of a large body of epidemiological, clinical and experimental ﬁndings in humans and animals
that suggest all the above-described maternal states that, on one hand,
constitute the adverse sequelae of CM exposure, also are, on the other
hand, associated with increased risk of obesity in their oﬀspring (Midei
et al., 2010, 2013; Rikknen et al., 2002; Tamayo et al., 2010).
pregnancy can potentially impact embryonic/fetal development, in
part, via their eﬀects on gestational biology. But what of exposures and
experiences that may have occurred earlier, prior to conception? Could
some of these, when a woman becomes pregnant, also impact gestational biology (which in turn may aﬀect oﬀspring phenotypes such as
energy balance homeostasis set points and risk for obesity and metabolic dysfunction)? Growing evidence suggests that certain maternal
pre-conceptional states and conditions do exert a substantial inﬂuence
on gestational biology (Lewis et al., 2015; Moussa et al., 2016) and fetal
development. Indeed, there is increasing recognition that the time
window for potential intervention on the process of fetal programming
of obesity risk and associated comorbidities should be extended to the
maternal pre-conception period (Haire-Joshu and Tabak, 2016;
Mumford et al., 2014).
With respect to maternal pre-conceptional factors that may promote
fetal programming of obesity risk, high maternal BMI and associated
comorbid states (e.g. diabetes, metabolic syndrome) and unhealthy
lifestyle behaviors (e.g. poor diet and sedentariness) have received
considerable attention to date (Drake and Reynolds, 2010; Lane et al.,
2015). However, other exposures over a woman’s life course, and
particularly exposure to adversity during the early life period, may also
exert long term eﬀects on physiology and health. Upon becoming
pregnant, these long-term eﬀects may spill-over into the gestational
period to inﬂuence aspects of maternal-placental-fetal biology that are
implicated in the process of fetal programming of obesity risk.
4. Conceptual framework: intergenerational transmission of the
eﬀects of maternal exposure to CM on oﬀspring obesity risk
3. The problem of childhood maltreatment exposure
3.1. Prevalence and long-term health consequences of CM exposure
We articulate here a trans-disciplinary, lifespan framework for the
intergenerational, mother-to-child transmission of the eﬀects of maternal exposure to CM on oﬀspring obesity risk. This framework is
based on principles from evolutionary and developmental biology, and
it integrates the concepts of biological embedding of life experiences and
fetal origins of health and disease risk (see Fig. 1). Its major elements are
as follow: 1) When women who had been exposed to maltreatment in
their childhood become pregnant, many or all of the long-term biological, biophysical, behavioral and psychological sequelae of CM exposure (e.g., endocrine, immune and metabolic dysfunction, obesity,
unhealthy diet (over- or under nutrition), substance abuse, depression,
stress hyper-responsiveness) may carry forward and spill over into their
gestational state (Barrios et al., 2015; Hollingsworth et al., 2012; Moog
et al., 2012; Nagl et al., 2015; Slopen et al., 2015). 2) Next, through the
process of fetal programming, the CM experience of one generation
(mother) may inﬂuence the health of the subsequent generation (child),
thereby creating an intergenerational cycle. Intergenerational transmission in utero is largely determined by the degree to which the developing placental-fetal unit receives and transduces biological signals
indicative of maternal state (in this case, of maternal CM-related alterations in her systemic physiology), and by the extent to which such
signals participate in oﬀspring phenotypic speciﬁcation. Additional
pathways of inter-generational transmission of maternal CM’s sequelae
may include eﬀects of CM exposure on germ line epigenetic characteristics, oocyte cytoplasm/follicular ﬂuid biology, and infant microbiome acquisition. 3) Our model recognizes that the prenatal and
postnatal eﬀects of maternal CM sequelae on childhood obesity risk
may not be mutually exclusive, and thus, also considers the mediating
or moderating eﬀects of CM-related postnatal factors such as breast
feeding and the quality of mother-child attachment. However, we
submit it is important to ascertain whether such intergenerational effects start in utero, as elucidation of the earliest transmission windows
and mechanisms is necessary to develop eﬃcacious strategies for primary prevention. The plausibility of each component of our model is
supported by empirical evidence in not only the general population
(Entringer et al., 2012a; Godfrey and Barker, 2001; Wadhwa, 2005;
Wadhwa et al., 2011), but also more speciﬁcally by ﬁndings among
oﬀspring of CM exposed women (Leonard et al., 2017; Roberts et al.,
The detrimental eﬀects of stress exposure on health and disease risk
are well established. They are particularly pronounced when stress
occurs during critical developmental periods (Heim and Binder, 2012).
Although stress is a ubiquitous feature of modern life, certain stressors
stand out in terms of their salience and consequences. Childhood maltreatment – physical, sexual or emotional abuse, or physical or emotional
neglect – likely represents one of the most pervasive and pernicious stressors
in society in terms of its widespread prevalence and devastating long-term
consequences. Estimates from the Centers for Disease Control and Prevention and others suggest a majority of children are exposed to one or
more traumatic events in their lifetimes (CDC, 2010; Hussey et al.,
2006), and that 30–40 % of adult women have experienced at least one,
and 15–25 % more than one type of CM (Scher et al., 2004). CM produces a suite of adverse and long-lasting biological, biophysical, behavioral and psychological sequelae including depression, post-traumatic stress disorder, substance abuse, unhealthy dietary practices,
risky sexual behavior, obesity, premature menarche, and dysregulated
neural, endocrine, immune and metabolic function that may result in
chronic inﬂammation and elevated cardiometabolic disease risk factors
(Aﬁﬁ et al., 2009; Anda et al., 2006; Dong et al., 2004; Felitti et al.,
1998; Heim et al., 2010; Jakubowski et al., 2018; Min et al., 2013;
Rasmussen et al., 2019). In the context of pregnancy and fetal development, it is apparent that many of these adverse sequelae of CM,
singly and collectively, represent the very same constellation of maternal risk factors that have been implicated in the process of fetal
programming of obesity risk.
3.2. Intergenerational transmission of the adverse sequelae of CM exposure
Emerging evidence now suggests that among women, the long
shadow cast by childhood maltreatment may not be restricted to their
lifespan, but also may be transmitted to their children. Indeed, children
of CM-exposed mothers, in the absence of CM exposure to themselves,
exhibit alterations in stress physiology systems (Bierer et al., 2014;
Brand et al., 2010; Jovanovic et al., 2011), behavioral disorders (conduct problems, internalizing and externalizing behavior), autism
3
Psychoneuroendocrinology 116 (2020) 104659
K.L. Lindsay, et al.
Fig. 1. Intergenerational transmission during gestation of the eﬀects of maternal exposure to childhood maltreatment: a conceptual framework.
genetic variants account for less than 5% of variation in BMI (Locke
et al., 2015; Speliotes et al., 2010). Growing evidence supports the
concept that the origins of obesity can be traced to the intrauterine period of
life (Entringer et al., 2012b; Oken and Gillman, 2003), at which time
the developing fetus responds to suboptimal conditions by producing
structural and functional changes in cells, tissues and organ systems
(Barker, 2002; Gluckman and Hanson, 2004b). Many of these changes,
such as altered set points in hypothalamic circuits that regulate appetite
and satiety (Cripps et al., 2005), reduced pancreatic β-cell mass (Portha
et al., 2011), impaired adipocyte (PPAR-ɣ) function (Desai and Ross,
2011), and reduced insulin sensitivity (Catalano et al., 2009) have
important long-term consequences for the propensity for developing
obesity and associated disorders through one or both of two processes:
they may inﬂuence magnitude and choice of dietary intake, and they
may inﬂuence the biological fate of energy intake. It is important to
note that these intrauterine eﬀects set the stage, but by no means negate
the importance of postnatal inﬂuences such as infant nutrition and
feeding practices. In fact, the eﬀects of fetal programming may interact
additively or multiplicatively with such postnatal eﬀects. Thus, we
suggest that incorporation of the life course perspective to the fetal
programming paradigm provides the optimal framework for elucidating
key pathways underlying the intergenerational transmission during
gestation of maternal CM experience on newborn and infant adiposity.
2014).
We also note here that the concept of intergenerational transmission
of the adverse sequelae of maternal CM exposure is not new. Indeed,
previous research has established the existence of such eﬀects, but with
a primary focus on child neurodevelopmental/ behavioral phenotypes
as the principal outcome of interest; on the child’s postnatal period of
life as the primary transmission window; and on the quality of maternal
parenting behavior as the primary transmission pathway. What is novel
about our hypothesis is the formulation that childhood obesity risk may
represent an additional and at least equally important outcome of interest and public health signiﬁcance; that the process of intergenerational transmission may start as early as during the child’s intrauterine
period of life; and that stress-related maternal-placental-fetal gestational biology may represent a key transmission pathway. We also note
that while maternal obesity (which is one of the long-term consequences of CM exposure (Hollingsworth et al., 2012; Midei et al.,
2010)) represents an example of a condition that may mediate the link
between maternal CM and oﬀspring obesity risk, the intergenerational
eﬀects of maternal CM likely include but may not be restricted to this
pathway alone. In this paper we discuss several other equally plausible
candidate pathways.
5. Relevance of the fetal programming approach
Development is a plastic process, wherein a range of diﬀerent
phenotypes can be expressed from a given genotype. The concept of
fetal programming describes the journey across the multi-contoured
landscape from genotype to phenotype, whereby the embryo/fetus
seeks, receives, and responds to the intrauterine environment during
sensitive periods of proliferation, diﬀerentiation and maturation, resulting in structural and functional changes in cells, tissues, organ
systems and homeostatic set points. These changes, independently or
through interactions with subsequent processes and environments, may
confer critical long-term consequences for future health and disease
susceptibility (Entringer et al., 2012a; Gluckman and Hanson, 2004a;
Hanson et al., 2011).
5.2. From the perspective of intergenerational eﬀects of maternal CM
exposure
To date, the literature on the intergenerational eﬀects of maternal
CM exposure has focused on the child’s early postnatal period of life as
the primary transmission window. However, the application of the fetal
programming paradigm may shed new light on the potential for
transmission to begin at an earlier time period (during the highly sensitive period of gestation and in utero development). The concept that a
woman’s pre-conceptional state may have important implications for
her child’s intrauterine development is supported by the key tenets of
evolutionary and life history theory (Kermack et al., 1934). CM experience represents a critical cue of extrinsic morbidity and unpredictability that may change life history strategies and alter morphological, physiological and behavioral traits (Braendle et al., 2011)
that, in turn, impact the state in which a woman enters pregnancy. The
plausibility of our hypothesis that the adverse eﬀects of maternal CM on
child obesity risk may start during the intrauterine period comes from
a) studies we have recently published demonstrating the ﬁrst direct
links between maternal CM exposure and i) placental-fetal stress biology
via production and trajectory of placental corticotrophin-releasing
5.1. From the perspective of childhood obesity risk
As discussed earlier, the magnitude of cumulative exposure to
obesogenic conditions only partially accounts for obesity risk (Sluyter
et al., 2013; Willyard, 2014). There are large individual diﬀerences in
susceptibility for weight gain and fat mass accretion upon exposure to
an identical degree of excess energy intake (Brehm et al., 2005;
Warwick and Schiﬀman, 1992). Furthermore, currently-identiﬁed
4
Psychoneuroendocrinology 116 (2020) 104659
K.L. Lindsay, et al.
2015), HPA axis hypersensitivity (Moog et al., 2012), and obesity
(Hollingsworth et al., 2012; Nagl et al., 2015). Moreover, the pre-preconception and/or prenatal presence of several of the same states and
conditions that happen to be CM sequelae has been shown to impact
gestational biology. These include psychological (depression, PTSD),
dysregulated HPA-axis activity (Christian, 2014; Christian et al., 2010),
metabolic (chronic inﬂammation, elevated lipids, insulin resistance)
(Heerwagen et al., 2013; Winzer et al., 2004), biophysical (obesity,
elevated fat mass) (Friedman, 2015; Stirrat et al., 2016), and behavioral
(smoking, drug abuse) (Collier et al., 2015; Somm et al., 2008; Xia
et al., 2014) factors. In many instances, the biological eﬀects of maternal exposure to CM or adult preconceptional abuse have also been
documented in fetal (cord) blood (Moog et al., 2012; Sternthal et al.,
2009).
hormone (CRH) (Moog et al., 2016), a key regulator of fetal growth,
parturition, and childhood obesity risk (Gillman et al., 2006; Wadhwa
et al., 2004); ii) increased susceptibility for maternal hypothyroidism
during pregnancy (Moog et al., 2017a); iii) altered fetal brain development during gestation, characterized by a lower cortical gray matter
volume in the newborn (Moog et al., 2017b); and b) observations that
the above-described CM sequelae are associated with biological alterations during pregnancy that, in turn, may directly or indirectly be
linked to childhood obesity risk (Donahue et al., 2011; Donnelly et al.,
2015; Gademan et al., 2014; Gillman et al., 2006; Hellmuth et al., 2016;
Josefson et al., 2014; Moon et al., 2013; Much et al., 2013; SchaeferGraf et al., 2011; Stirrat et al., 2014; Teague et al., 2015).
6. Mechanisms for the intergenerational transmission of the
eﬀects of maternal CM on oﬀspring obesity
6.1.2. Role as transducers between the maternal and fetal compartments of
the sequelae of maternal CM
Current evidence links the above-mentioned biological pathways
and speciﬁc biomarkers across the maternal and fetal compartments,
supporting the plausibility that information about the existence of unfavorable external environmental conditions, which have been “sensed”
by maternal biology, also utilize these same biological systems as a
pathway for the mother-to-fetus transmission of this information. For
example, prenatal stress induction in animals elevates maternal and
fetal cortisol, with a high correlation between their respective concentrations (Rakers et al., 2015). Levels of the pro-inﬂammatory cytokine Interleukin (IL)-6 are similarly correlated in maternal and cord
blood among pregnancies delivered by elective Cesarean section (i.e., in
the context of absence of the acute physiological stress of labor) (VegaSanchez et al., 2010). Maternal metabolic dysregulation such as poor
glycemic control is reﬂected in elevated cord blood C-Peptide, a biomarker of fetal insulin secretion (Josefson et al., 2014; Scholtens et al.,
2014; Walsh et al., 2014). Maternal and fetal leptin also are highly
correlated (Josefson et al., 2014; Luo et al., 2013; Walsh et al., 2014),
while plasma free fatty acids are correlated between maternal and fetal
compartments in normoglycemic as well as pregnancies aﬀected by
gestational diabetes mellitus (Schaefer-Graf et al., 2008, 2011).
The biological pathway by which maternal states impact intrauterine development is a longitudinal process, beginning before
conception and extending into the postnatal period, and which may
involve several mechanisms including; i) transduction and reception of
biological signals across the placental-fetal unit that participate in fetal
development and phenotypic speciﬁcation (including, but not limited to
the establishment of de novo epigenetic alterations in the embryo/fetus/
child), ii) preconceptional eﬀects on (maternal) oocytes and follicular
ﬂuid composition, iii) the composition and activity of the maternal
microbiome prior to and during gestation, and iv) postnatal processes
including feeding practices, mother-child attachment, and infant microbiome acquisition.
6.1. Maternal and fetal gestational biology
A crucial component of our formulation is the question of whether
maternal CM sequelae can inﬂuence those speciﬁc aspects of gestational
biology that participate in fetal programming of child obesity risk. In
this regard, we propose that maternal and fetal endocrine, immune/
inﬂammatory, metabolic and lipid biology collectively constitute an
attractive candidate mechanism. Firstly, these systems are responsive to
all classes of intrauterine perturbations linked to maternal CM sequelae
(sensors); secondly, they extensively mediate communication between
maternal and fetal compartments (transducers); and thirdly, they play
an essential, obligatory role in orchestrating and producing variation in
key events underlying cellular growth, replication and diﬀerentiation in
the brain (regions and circuitry underlying energy balance homeostasis) and peripheral tissues (adipocytes, pancreas, liver, muscle) related to obesity and metabolic dysfunction-related phenotypes (eﬀectors) (Fowden et al., 2006; Matthews, 2000; Thompson and Al-Hasan,
2012).
6.1.3. Role as eﬀectors of fetal programming of newborn and childhood
obesity risk
Substantial human and animal literature suggests that dysregulation
of the gestational biological systems mentioned above is associated
with increased childhood adiposity and obesity risk, thereby suggesting
that these same biological ligands act on targets within the fetal compartment to causally produce phenotypic eﬀects that underlie the outcomes of interest (in this case, oﬀspring obesity/adiposity). For example, cortisol and corticotrophin releasing hormone (CRH) in
gestation predict macrosomia (Stirrat et al., 2014) and early childhood
central adiposity (Gillman et al., 2006). IL-6 has been identiﬁed as
among the strongest prenatal predictors of child adiposity (Radaelli
et al., 2006), while other inﬂammatory markers have also been implicated (Mestan et al., 2010). Biomarkers of maternal and fetal metabolic dysregulation such as poor maternal glycemic control and insulin
resistance (Schaefer-Graf et al., 2011; Scholtens et al., 2014), elevated
cord blood C-peptide (Hou et al., 2014; Regnault et al., 2011), and
elevated maternal/fetal leptin (Donnelly et al., 2015; Josefson et al.,
2014; Walsh et al., 2014), all have been linked to child adiposity. Triglycerides in maternal and cord blood also are strongly associated with
adiposity at birth (Nayak et al., 2013; Schaefer-Graf et al., 2008;
Scholtens et al., 2014) and in childhood (Gademan et al., 2014). Prenatal fatty acid proﬁles are emerging as predictors of childhood obesity
risk (Schaefer-Graf et al., 2008; Scholtens et al., 2014) and are reported
to exert an even larger eﬀect than triglycerides and lipoproteins on
oﬀspring BMI, body fat percentage, and waist-to-height ratio (Gademan
et al., 2014). Maternal omega-6 fatty acid status is associated with birth
weight (Much et al., 2013) and percent body fat at 4 years of age (Moon
6.1.1. Role as sensors of the adverse sequelae of maternal CM exposure
Substantial evidence in non-pregnant women demonstrates the
persistent, life-long impact of CM on endocrine, metabolic, and inﬂammatory pathways, suggesting that in the context of pregnancy and
fetal development these biological systems may act as sensors of a
constellation of unfavorable external environmental conditions related
to maternal CM exposure. For instance, CM induces endocrine dysregulation via dysregulated cortisol response and hypothalamic-pituitaryadrenal (HPA)-axis reactivity (Carpenter et al., 2009; Klaassens et al.,
2009), promotes chronic inﬂammation via elevated pro-inﬂammatory
cytokines (Friedman et al., 2015; Matthews et al., 2014), and is associated with adverse metabolic and lipid proﬁles via increased risk of
type 2 diabetes mellitus (Rich-Edwards et al., 2010; Thomas et al.,
2008) and the metabolic syndrome (Midei et al., 2013). Previous research and our own published and preliminary studies suggest there is a
continuity and spill-over eﬀect from the pre-conceptional to the gestational state of many of the conditions that are CM sequelae, such as
maternal depression (Barrios et al., 2015), inﬂammation (Slopen et al.,
5
Psychoneuroendocrinology 116 (2020) 104659
K.L. Lindsay, et al.
altered by preconception states and conditions during the process of
oocyte growth and maturation. For example, maternal obesity prior to
conception, a common sequelae of CM exposure, is associated with
altered oocyte endoplasmic reticulum (ER) stress signaling (Latham,
2015), resulting in reduced mitochondrial membrane potential and
increased autophagy (Wu et al., 2015). As such, oocyte mitochondrial
dysfunction may contribute to the intergenerational transmission of
obesity (Turner and Robker, 2015). Studies of women undergoing in
vitro fertilization also indicate that psychosocial stress (An et al., 2013;
Turner et al., 2013) and heightened physiological reactivity to stress
(Facchinetti et al., 1997) is associated with reduced oocyte competence
and failure to conceive. Although alterations in oocyte cytoplasm have
not yet been studied in relation to maternal CM exposure, it is plausible
that the adverse lifelong sequelae of CM (i.e., stress in this context)
could aﬀect oocyte quality and mitochondrial function across all stages
of oocyte development and maturation, thereby inﬂuencing aspects of
fetal development that are associated with increased susceptibility for
excess adiposity via inherited cellular metabolic dysfunctions. While
this mechanism has not yet been studied in humans, there is supporting
evidence from animal studies (Turner and Robker, 2015). Luzzo et al.
demonstrated that blastocysts from female mice with obesity, after
transfer to females without obesity for gestation, resulted in low birth
weight phenotype oﬀspring at risk of subsequent increased adiposity
and glucose intolerance (Luzzo et al., 2012).
et al., 2013), while a raised omega-6/omega-3 ratio in cord blood demonstrated a strong positive association with child adiposity at age 3
years (Donahue et al., 2011).
6.2. Epigenetic characteristics
Several epigenetic states/characteristics are prospectively associated
with adiposity and metabolic dysfunction (Godfrey et al., 2011; Lin
et al., 2017), and growing evidence supports a role for certain environmental exposures/conditions in the production of some of these
epigenetic characteristics (Bays & Scinta, 2015; Godfrey et al., 2011).
From the developmental perspective, epigenetic inter-generational
transmission of obesity risk may occur via one or both of two possible
routes; i) inheritance of maternally-derived epigenetic alterations in the
germ line (oocytes), and ii) de novo production of epigenetic marks in
the oﬀspring via exposure to maternal conditions during intrauterine
life. There is currently very limited evidence (and only among animal
studies) to suggest that some epigenetic marks can survive the erasure
and re-establishment of epigenetic characteristics that occurs shortly
after fertilization. Animal models of early life stress have demonstrated
that some epigenetic inheritance may be possible through the paternal
germ line (Gapp et al., 2014; Soubry et al., 2014), as environmental
conditions can inﬂuence the miRNA composition of sperm. In this way,
it is plausible that paternal CM exposure also may contribute to the
intergenerational transmission of CM eﬀects on oﬀspring health, but
thus far this concept has only been studied in the context of paternal
stress and oﬀspring brain development (Yeshurun and Hannan, 2019).
Furthermore, epigenetic inheritance has not yet been demonstrated
through the maternal germ line, which would be required to support
the inter- and trans-generational transmission of eﬀects of early life
exposures, including that of CM (Daxinger and Whitelaw, 2012).
However, it is plausible that de novo production of epigenetic alterations in the developing fetus, via the sequelae of maternal CM exposure
(Palma-Gudiel et al., 2015), may contribute to the developmental
programming of childhood obesity (Heerwagen et al., 2010; Laker
et al., 2013). For example, several animal studies have demonstrated
that maternal obesity and in utero exposure to excess maternal lipids
can impact gene pathways of metabolic importance for the developing
fetus, including those for lipid oxidation (Bruce et al., 2009), insulin
resistance (Yan et al., 2010), cellular diﬀerentiation (Kirchner et al.,
2010; Zhu et al., 2008), adipogenesis (Muhlhausler et al., 2007), and
brain circuitry aﬀecting appetite regulation and feeding behavior
(Chang et al., 2008). In a longitudinal human cohort study, unbalanced
maternal diet in pregnancy was associated with alterations in DNA
methylation in the adult oﬀspring within genes for 11-betahydroxysteroid dehydrogenase type 2 (cortisol regulation), glucocorticoid receptor, and insulin-like growth factor-2, which were positively associated with increased adiposity and blood pressure (Drake et al., 2012).
However, maternal obesity and poor diet are only two sequelae associated with exposure to CM. The potential eﬀects of maternal stress and
other behavioral, psychological and physiological sequelae of CM on
epigenetic alterations during fetal development require signiﬁcantly
more research in longitudinal human studies.
6.4. Maternal and infant microbiome
A rapidly growing and convergent body of literature has linked
characteristics of the infant gut microbiome with the subsequent development of oﬀspring disorders, including obesity (Luoto et al., 2013).
The composition of the infant microbiome is determined by not only
perinatal and early postnatal exposures (such as mode of delivery, infant feeding practices, antibiotic use) but also directly and indirectly by
the composition and activity of the maternal microbiome during
pregnancy (Soderborg et al., 2016). Recent evidence indicates the
presence of microbial DNA in the placenta, amniotic ﬂuid, meconium
and umbilical cord blood from healthy pregnancies without intrauterine infection (Funkhouser and Bordenstein, 2013), suggesting
some mechanism(s) for direct microbial transfer between the maternal
and fetal compartments in utero, which may subsequently shape the
composition of the infant microbiome. While research in this area is
currently in its infancy, one hypothesized mechanism is that maternal
microbes reach the placenta via the bloodstream after translocation
across the gut epithelium (Jenmalm, 2017; Soderborg et al., 2016).
Maternal gut and cervicovaginal microbes may indirectly inﬂuence
obesity risk in the child via alterations to systemic maternal biology
(e.g., enhanced inﬂammation, increased availability of metabolic fuels)
(Basu et al., 2011), facilitating fetal programming of brain and peripheral tissues with predisposition for greater adiposity during in utero
development and early childhood. Furthermore, the maternal microbiome composition and activity may inﬂuence the development of the
fetal immune system (Jenmalm, 2017), which then would be expected
to play a role in the establishment of the newborn and infant microbiome.
Thus, an increasing body of empirical and experimental evidence
suggests that the determinants of the maternal microbiome composition
before and during pregnancy may contribute to the intergenerational
transfer of obesity risk. Maternal overweight, obesity and unhealthy
periconceptional diet are currently the primary exposures under study
in this regard, and have each been associated with an altered microbiome during pregnancy (Collado et al., 2008; Gohir et al., 2015a;
Santacruz et al., 2010), which in turn aﬀects the infant microbiota
acquisition, composition and activity (Collado et al., 2010; Gohir et al.,
2015b). Additional factors which are also known sequelae of CM exposure, such as psychological stress (Gur and Bailey, 2016), depression
(Daniels et al., 2017), substance abuse (Engen et al., 2015; Volpe et al.,
6.3. Oocyte cytoplasm and mitochondrial function
The cytoplasm of the oocyte and follicular ﬂuid constitutes the very
ﬁrst environmental exposure for a fertilized egg (in humans it takes
about 24−36 hrs post fertilization for the newly-conceived individual’s
full DNA complement to be assembled from maternal and paternal
chromosomes). The quality of the oocyte cytoplasm is known to impact
many outcomes including early embryonic survival, establishment and
maintenance of pregnancy, fetal development, and even adult disease
risk (Krisher, 2004). The structure and function of mitochondria, cellular proteins, and RNA molecules contained in the oocyte cytoplasm
are central to these processes (Van Blerkom, 2011), and these may be
6
Psychoneuroendocrinology 116 (2020) 104659
K.L. Lindsay, et al.
highlighted as a critical window of intervention (Lakshman et al., 2012;
Nader et al., 2012; Wojcicki and Heyman, 2010). Indeed, prenatal interventions have targeted gestational weight gain, diet, and exercise in
pregnancy, however, these measures have demonstrated limited success
in inﬂuencing birth weight and oﬀspring adiposity (Dodd et al., 2014;
Poston et al., 2015; Walsh et al., 2012). We suggest that a greater
emphasis on improving preconception health may be required to
ameliorate the intergenerational transmission of obesity (Haire-Joshu
and Tabak, 2016; Mumford et al., 2014). Thus, adopting a fetal programming approach to investigate the intergenerational transmission of
the eﬀects of maternal CM on oﬀspring obesity risk oﬀers the potential
and new opportunity to identify a vulnerable target population, and
speciﬁc behavioral, biological and/or psychological pathways amenable to intervention that may help tackle the growing burden of
childhood obesity.
The multitude of adverse health sequelae experienced by individuals exposed to CM highlights their increased healthcare requirements across their lifespan (Arnow, 2004; Hulme, 2000). Moreover, the
American College of Obstetricians and Gynecologists report that female
survivors of sexual abuse may be less likely to seek appropriate prenatal
care services compared to non-exposed women (American College of
Obstetricians and Gynecologists, 2011), thus increasing the likelihood
for adverse pregnancy and neonatal outcomes. Therefore, our perspective highlights the urgency for public health policies and practices
to identify, engage with and treat women with CM exposure, in order to
address their own health requirements and possibly reduce the risk of
adverse health consequences for their unborn children.
Another important factor to consider in identifying vulnerable population groups is maternal socioeconomic status (SES). A bidirectional
relationship may exist between SES and CM, such that the incidence of
CM is higher among families of lower SES (Lefebvre et al., 2017; Walsh
et al., 2019), and exposure to CM is subsequently associated with lower
SES in adulthood, even after adjusting for childhood SES (Zielinski,
2009). Furthermore, lower SES is associated with a higher likelihood of
developing obesity in childhood and across the life-course (Andrea
et al., 2017; Newton et al., 2017). Thus, SES may lie on the causal
pathway between maternal CM exposure and intergenerational transmission of its eﬀects on oﬀspring obesity risk, highlighting the need to
develop eﬃcacious public health strategies to improve the health and
wellbeing of socially disadvantaged women, with potential impact on
health outcomes for subsequent generations.
2014) and socioeconomic disadvantage (Miller et al., 2016), have also
been associated with alterations in microbiome composition in nonpregnancy studies. Empirical evidence suggests that early life trauma
may impact the process of microbial colonization, or may have diﬀerential eﬀects based on how the microbiota inﬂuence the HPA axis in
early life development (Daniels et al., 2017).
6.5. Postnatal factors
Our model recognizes that maternal CM exposure may exert independent postnatal eﬀects on child obesity risk, and furthermore, that
prenatal and postnatal eﬀects may interact in programming susceptibility for obesity. An important and potentially modiﬁable early
postnatal factor contributing to childhood obesity is infant diet/feeding
practices, particularly breastfeeding and its duration (Hunsberger et al.,
2013; Oddy et al., 2014), which may also mitigate the impact of earlier
adverse prenatal exposures (Gibbs and Forste, 2014). A study from a
large Norwegian cohort (N = 53,934) reported that women with CMexposure had a 41 % increased risk of ceasing breastfeeding before 4
months postnatal (Sorbo et al., 2015), and similar ﬁndings have been
reported in a smaller Canadian cohort (Boston, 2012). Moreover, it is
evident that many sequelae of CM, including depression (AhlqvistBjorkroth et al., 2016), anxiety (Arifunhera et al., 2015), abuse exposure in adulthood (Silverman et al., 2006), and obesity (Wojcicki,
2011), are associated with reduced breastfeeding initiation and/or
duration.
Another early-life factor that is signiﬁcantly associated with oﬀspring obesity risk is poor quality maternal-child attachment (Anderson
and Whitaker, 2011), which may also be aﬀected by maternal CM exposure and psychological state (Mogi et al., 2011). While the mechanism underlying this link is uncertain, poor quality maternal-child
attachment may aﬀect the development of children’s emotion regulation and stress response systems, with subsequent eﬀects on appetite,
sleep and activity (Anderson et al., 2012). Furthermore, maternal psychosocial states in pregnancy such as anxiety and depression, which are
also CM sequelae, have been associated with ‘fussy’ child temperament
(Austin et al., 2005), a characteristic linked to shorter breastfeeding
duration (Niegel et al., 2008), early introduction of solid foods (Wasser
et al., 2011), and altered parental sensitivity/attachment (Planalp and
Braungart-Rieker, 2013). Thus, there is evidence for interaction eﬀects
between CM sequelae and postnatal factors that are strongly implicated
in the development of childhood adiposity.
As discussed in the previous section, the infant microbiome is another postnatal factor believed to play an important role in the development of childhood obesity. While we have outlined how the eﬀects of
maternal CM exposure and its sequelae may inﬂuence the infant microbiome acquisition, composition and activity via the maternal microbiome, we hypothesize that these eﬀects are likely to persist
throughout the postnatal period (e.g. altered microbial and immune
composition of breastmilk, suboptimal feeding practices), potentially
augmenting the adverse eﬀects of prenatal programming mechanisms.
However, we are not currently aware of any studies describing the association of maternal CM exposure with infant microbiome composition, neither from the perspective of fetal programming or postnatal
acquisition.
8. Research directions
It is evident from the review of literature presented in this paper
that there is a strong scientiﬁc premise underlying each component of
the proposed model for intergenerational transmission of the eﬀects of
maternal CM on oﬀspring obesity risk. However, longitudinal studies
across intrauterine life and extending into the postnatal period are required to verify our hypotheses, and to investigate the proposed fetal
programming mechanisms. While animal studies have provided an initial platform to investigate the gestational biological eﬀects of preconception or prenatal stress and subsequent inﬂuence on oﬀspring
obesity, there are no appropriate animal models for CM exposure. Thus,
human studies are warranted that systematically characterize the gestational environment in which oﬀspring of mothers with CM-exposure
develop.
While observational, longitudinal studies of this nature may provide
important insight to the intergenerational eﬀects of CM exposure on
oﬀspring obesity, we acknowledge that this study design suﬀers several
limitations, particularly with respect to causal inference. Knowledge
gleaned from observational studies regarding the most vulnerable population groups and mechanisms of transmission of CM eﬀects should,
therefore, be targeted in future intervention studies. Given the multitude of adverse eﬀects of CM exposure on the mother, future interventions should consider integrating behavioral, psychological and
7. Identifying vulnerable population groups and informing public
health measures
The long-term burden of the development of obesity-related comorbidities in childhood and adult life cannot be ignored, and ongoing,
eﬀective early-life intervention strategies for obesity prevention are
required (Institute of Medicine, 2011; Lakshman et al., 2012). While the
majority of national public health policies currently target school-aged
children and adolescents, the growing body of evidence for prenatal
programming of susceptibility to childhood obesity has been repeatedly
7
Psychoneuroendocrinology 116 (2020) 104659
K.L. Lindsay, et al.
pharmacological modalities in an attempt to mitigate the eﬀects of the
sequelae of maternal CM on fetal programming pathways related to
susceptibility to oﬀspring obesity. Ideally, such interventions should
target the preconception period in an eﬀort to improve the embryonic/
fetal environment from the time of conception.
New approaches to identify and interpret information from placental and fetal exosomes in the maternal compartment may advance
our understanding of which biological factors in the fetal compartment
play key roles in obesity-related phenotypic speciﬁcation in the oﬀspring. There is also much scope for further animal and human studies
to investigate the impact of maternal CM exposure on de novo epigenetic alterations, oocyte biology, the composition and activity of the
maternal microbiome and acquisition and establishment of the infant
microbiome. For example, longitudinal case-control studies among
women undergoing in vitro fertilization could reveal whether maternal
CM exposure is associated with alterations in oocyte cytoplasm or mitochondrial function, and whether such alterations predict downstream
adiposity and cardiometabolic outcomes in the oﬀspring. Similarly,
comparing the microbiome composition and activity of CM and non-CM
exposed women before and during pregnancy, and follow-up with the
infant microbiome, growth and adiposity, could provide insight as to
whether microbial composition and colonization plays a role in transmitting the eﬀects of maternal CM on oﬀspring obesity risk.
Furthermore, future studies examining the transmission of the eﬀects of
CM exposure must carefully consider the moderating eﬀects of prenatal
conditions and exposures on postnatal factors in the intergenerational
transfer of obesity risk among this vulnerable population.
Albuquerque, D., Nobrega, C., Manco, L., 2013. Association of FTO polymorphisms with
obesity and obesity-related outcomes in Portuguese children. PLoS One 8 (1),
e54370. https://doi.org/10.1371/journal.pone.0054370.
Albuquerque, D., Nobrega, C., Manco, L., Padez, C., 2017. The contribution of genetics
and environment to obesity. Br. Med. Bull. 123 (1), 159–173. https://doi.org/10.
1093/bmb/ldx022.
American College of Obstetricians and Gynecologists, 2011. Committee opinion no. 498:
adult manifestations of childhood sexual abuse. Obstet. Gynecol. 118 (2, Part 1),
392–395. https://doi.org/10.1097/AOG.0b013e31822c994d.
An, Y., Sun, Z., Li, L., Zhang, Y., Ji, H., 2013. Relationship between psychological stress
and reproductive outcome in women undergoing in vitro fertilization treatment:
psychological and neurohormonal assessment. J. Assist. Reprod. Genet. 30 (1),
35–41. https://doi.org/10.1007/s10815-012-9904-x.
Anda, R.F., Felitti, V.J., Bremner, J.D., Walker, J.D., Whitﬁeld, C., Perry, B.D., et al.,
2006. The enduring eﬀects of abuse and related adverse experiences in childhood. A
convergence of evidence from neurobiology and epidemiology. Eur. Arch. Psychiatry
Clin. Neurosci. 256 (3), 174–186. https://doi.org/10.1007/s00406-005-0624-4.
Anderson, S.E., Whitaker, R.C., 2011. Attachment security and obesity in US preschoolaged children. Arch. Pediatr. Adolesc. Med. 165 (3), 235–242. https://doi.org/10.
1001/archpediatrics.2010.292.
Anderson, S.E., Gooze, R.A., Lemeshow, S., Whitaker, R.C., 2012. Quality of early maternal-child relationship and risk of adolescent obesity. Pediatrics 129 (1), 132–140.
https://doi.org/10.1542/peds.2011-0972.
Andrea, S.B., Hooker, E.R., Messer, L.C., Tandy, T., Boone-Heinonen, J., 2017. Does the
association between early life growth and later obesity diﬀer by race/ethnicity or
socioeconomic status? A systematic review. Ann. Epidemiol. 27 (9), 583–592.
https://doi.org/10.1016/j.annepidem.2017.08.019. e585.
Arifunhera, J.H., Srinivasaraghavan, R., Sarkar, S., Kattimani, S., Adhisivam, B., Vishnu
Bhat, B., 2015. Is maternal anxiety a barrier to exclusive breastfeeding? J. Matern.
Fetal. Neonatal. Med. 1–4. https://doi.org/10.3109/14767058.2015.1104662.
Arnow, B.A., 2004. Relationships between childhood maltreatment, adult health and
psychiatric outcomes, and medical utilization. J. Clin. Psychiatry 65, 10–15.
Austin, M.-P., Hadzi-Pavlovic, D., Leader, L., Saint, K., Parker, G., 2005. Maternal trait
anxiety, depression and life event stress in pregnancy: relationships with infant
temperament. Early Hum. Dev. 81 (2), 183–190. https://doi.org/10.1016/j.
earlhumdev.2004.07.001.
Barker, D.J., 2002. Fetal programming of coronary heart disease. Trends Endocrinol.
Metab. 13 (9), 364–368.
Barrios, Y.V., Gelaye, B., Zhong, Q., Nicolaidis, C., Rondon, M.B., Garcia, P.J., et al., 2015.
Association of childhood physical and sexual abuse with intimate partner violence,
poor general health and depressive symptoms among pregnant women. PLoS One 10
(1), e0116609. https://doi.org/10.1371/journal.pone.0116609.
Basu, S., Haghiac, M., Surace, P., Challier, J.C., Guerre-Millo, M., Singh, K., et al., 2011.
Pregravid obesity associates with increased maternal endotoxemia and metabolic
inﬂammation. Obesity (Silver Spring) 19 (3), 476–482. https://doi.org/10.1038/oby.
2010.215.
Bays, H., Scinta, W., 2015. Adiposopathy and epigenetics: an introduction to obesity as a
transgenerational disease. Curr. Med. Res. Opin. 31 (11), 2059–2069. https://doi.
org/10.1185/03007995.2015.1087983.
Bierer, L.M., Bader, H.N., Daskalakis, N.P., Lehrner, A.L., Makotkine, I., Seckl, J.R., et al.,
2014. Elevation of 11β-hydroxysteroid dehydrogenase type 2 activity in Holocaust
survivor oﬀspring: evidence for an intergenerational eﬀect of maternal trauma exposure. Psychoneuroendocrinology 48, 1–10. https://doi.org/10.1016/j.psyneuen.
2014.06.001.
Bluher, M., 2019. Obesity: global epidemiology and pathogenesis. Nat. Rev. Endocrinol.
15 (5), 288–298. https://doi.org/10.1038/s41574-019-0176-8.
Boston, N., 2012. The Association between Childhood Trauma and Breastfeeding for a
Sample of Women From Hamilton, Ontario, Canada (MSc). Emory University.
Braendle, C., Heyland, F., Flatt, T., 2011. Integrating mechanistic and evolutionary
analysis on life history variation. In: Flatt, T., Heyland, F. (Eds.), Mechanisms of Life
History Evolution. The Genetics and Physiology of Life History Traits and Trade-Oﬀs.
Oxford University Press, pp. 3–10.
Brand, S.R., Brennan, P.A., Newport, D.J., Smith, A.K., Weiss, T., Stowe, Z.N., 2010. The
impact of maternal childhood abuse on maternal and infant HPA axis function in the
postpartum period. Psychoneuroendocrinology 35 (5), 686–693. https://doi.org/10.
1016/j.psyneuen.2009.10.009.
Brehm, B.J., Spang, S.E., Lattin, B.L., Seeley, R.J., Daniels, S.R., D’Alessio, D.A., 2005. The
role of energy expenditure in the diﬀerential weight loss in obese women on low-fat
and low-carbohydrate diets. J. Clin. Endocrinol. Metab. 90 (3), 1475–1482.
Bruce, K.D., Cagampang, F.R., Argenton, M., Zhang, J., Ethirajan, P.L., Burdge, G.C.,
et al., 2009. Maternal high-fat feeding primes steatohepatitis in adult mice oﬀspring,
involving mitochondrial dysfunction and altered lipogenesis gene expression.
Hepatology 50 (6), 1796–1808. https://doi.org/10.1002/hep.23205.
Buss, C., Entringer, S., Moog, N.K., Toepfer, P., Fair, D.A., Simhan, H.N., et al., 2017.
Intergenerational transmission of maternal childhood maltreatment exposure: implications for fetal brain development. J. Am. Acad. Child Adolesc. Psychiatry 56 (5),
373–382. https://doi.org/10.1016/j.jaac.2017.03.001.
Carpenter, L.L., Tyrka, A.R., Ross, N.S., Khoury, L., Anderson, G.M., Price, L.H., 2009.
Eﬀect of childhood emotional abuse and age on cortisol responsivity in adulthood.
Biol. Psychiatry 66 (1), 69–75. https://doi.org/10.1016/j.biopsych.2009.02.030.
Catalano, P.M., Shankar, K., 2017. Obesity and pregnancy: mechanisms of short term and
long term adverse consequences for mother and child. Bmj 356https://doi.org/10.
1136/bmj.j1. j1-j1.
Catalano, P.M., Presley, L., Minium, J., Hauguel-de Mouzon, S., 2009. Fetuses of obese
mothers develop insulin resistance in utero. Diabetes Care 32 (6), 1076–1080
doi:dc08-2077 [pii]10.2337/dc08-2077.
9. Conclusions
In summary, childhood abuse and neglect represent one of the most
pervasive, persistent and pernicious stressors in our society. Emerging
evidence now suggests the adverse consequences of CM may not be
restricted to the exposed women alone, but may also be transmitted to
their children. The perspective outlined in this article proposes that the
intergenerational transmission of the adverse eﬀects of maternal CM
may start as early as the child’s intrauterine period of life, via a culmination of gestational biological pathways, in order to increase the
propensity for obesity in the oﬀspring. Longitudinal prospective studies
are required to test this hypothesis, and to elucidate intrauterine biological processes that may be amenable to intervention. Ultimately, the
aim would be to break the vicious cycle of the enduring consequences
of early life stress passed down from a vulnerable population of abused
women, to the even more vulnerable population of their unborn children.
Declaration of Competing Interest
None.
Funding
This work was supported by the National Institutes of Health, grant
numbers K99 HD-096109, R01 MH-105538, R01 MD-01078, R01 AG050455 and UG3 OD-023349. These funding sources had no role in the
preparation and writing of the manuscript, or the decision to submit the
paper for publication.
References
Aﬁﬁ, T.O., Boman, J., Fleisher, W., Sareen, J., 2009. The relationship between child
abuse, parental divorce, and lifetime mental disorders and suicidality in a nationally
representative adult sample. Child Abuse Negl. 33 (3), 139–147.
Ahlqvist-Bjorkroth, S., Vaarno, J., Junttila, N., Pajulo, M., Raiha, H., Niinikoski, H., et al.,
2016. Initiation and exclusivity of breastfeeding: association with mothers’ and fathers’ prenatal and postnatal depression and marital distress. Acta Obstet. Gynecol.
Scand. https://doi.org/10.1111/aogs.12857.
8
Psychoneuroendocrinology 116 (2020) 104659
K.L. Lindsay, et al.
CDC, 2010. Adverse childhood experiences reported by adults — ﬁve states, 2009.
MMWR Morb. Mortal. Wkly. Rep. 59 (49), 1609–1613.
Chang, G.Q., Gaysinskaya, V., Karatayev, O., Leibowitz, S.F., 2008. Maternal high-fat diet
and fetal programming: increased proliferation of hypothalamic peptide-producing
neurons that increase risk for overeating and obesity. J. Neurosci. 28 (46),
12107–12119. https://doi.org/10.1523/jneurosci.2642-08.2008.
Christian, L.M., 2014. Eﬀects of stress and depression on inﬂammatory immune parameters in pregnancy. Am. J. Obstet. Gynecol. 211 (3), 275–277. https://doi.org/10.
1016/j.ajog.2014.06.042.
Christian, L.M., Franco, A., Iams, J.D., Sheridan, J., Glaser, R., 2010. Depressive symptoms predict exaggerated inﬂammatory responses to an in vivo immune challenge
among pregnant women. Brain Behav. Immun. 24 (1), 49–53. https://doi.org/10.
1016/j.bbi.2009.05.055.
Collado, M.C., Isolauri, E., Laitinen, K., Salminen, S., 2008. Distinct composition of gut
microbiota during pregnancy in overweight and normal-weight women. Am. J. Clin.
Nutr. 88 (4), 894–899.
Collado, M.C., Isolauri, E., Laitinen, K., Salminen, S., 2010. Eﬀect of mother’s weight on
infant’s microbiota acquisition, composition, and activity during early infancy: a
prospective follow-up study initiated in early pregnancy. Am. J. Clin. Nutr. 92 (5),
1023–1030. https://doi.org/10.3945/ajcn.2010.29877.
Collier, A.C., Sato, B.L., Milam, K.A., Wright, T.E., 2015. Methamphetamine, smoking,
and gestational hypertension aﬀect norepinephrine levels in umbilical cord tissues.
Clin. Exp. Obstet. Gynecol. 42 (5), 580–585.
Collishaw, S., Dunn, J., O’Connor, T.G., Golding, J., 2007. Maternal childhood abuse and
oﬀspring adjustment over time. Dev. Psychopathol. 19 (2), 367–383. https://doi.org/
10.1017/S0954579407070186.
Cripps, R.L., Martin-Gronert, M.S., Ozanne, S.E., 2005. Fetal and perinatal programming
of appetite. Clin. Sci. 109 (1), 1–11.
Dabelea, D., Harrod, C.S., 2013. Role of developmental overnutrition in pediatric obesity
and type 2 diabetes. Nutr. Rev. 71 (S1), S62–S67.
Daniels, J.K., Koopman, M., Aidy, S.E., 2017. Depressed gut? The microbiota-diet-inﬂammation trialogue in depression. Curr. Opin. Psychiatry. https://doi.org/10.1097/
yco.0000000000000350.
Daxinger, L., Whitelaw, E., 2012. Understanding transgenerational epigenetic inheritance
via the gametes in mammals. Nat. Rev. Genet. 13 (3), 153–162. https://doi.org/10.
1038/nrg3188.
Deliard, S., Panossian, S., Mentch, F.D., Kim, C.E., Hou, C., Frackelton, E.C., et al., 2013.
The missense variation landscape of FTO, MC4R, and TMEM18 in obese children of
African ancestry. Obesity 21 (1), 159–163. https://doi.org/10.1002/oby.20147.
Desai, M., Ross, M.G., 2011. Fetal programming of adipose tissue: eﬀects of intrauterine
growth restriction and maternal obesity/high-fat diet. Paper Presented at the
Seminars in Reproductive Medicine.
Dietz, W.H., 1998. Health consequences of obesity in youth: childhood predictors of adult
disease. Pediatrics 101 (3 Pt 2), 518–525.
Dodd, J.M., Turnbull, D., McPhee, A.J., Deussen, A.R., Grivell, R.M., Yelland, L.N., et al.,
2014. Antenatal lifestyle advice for women who are overweight or obese: LIMIT
randomised trial. Bmj 348, g1285. https://doi.org/10.1136/bmj.g1285.
Donahue, S.M., Rifas-Shiman, S.L., Gold, D.R., Jouni, Z.E., Gillman, M.W., Oken, E., 2011.
Prenatal fatty acid status and child adiposity at age 3 y: results from a US pregnancy
cohort. Am. J. Clin. Nutr. 93 (4), 780–788. https://doi.org/10.3945/ajcn.110.
005801.
Dong, M., Giles, W.H., Felitti, V.J., Dube, S.R., Williams, J.E., Chapman, D.P., et al., 2004.
Insights into causal pathways for ischemic heart disease: adverse childhood experiences study. Circulation 110 (13), 1761–1766. https://doi.org/10.1161/01.CIR.
0000143074.54995.7F.
Donnelly, J.M., Lindsay, K.L., Walsh, J.M., Horan, M., Molloy, E.J., McAuliﬀe, F.M., 2015.
Fetal metabolic inﬂuences of neonatal anthropometry and adiposity. BMC Pediatr.
15, 175. https://doi.org/10.1186/s12887-015-0499-0.
Drake, A.J., Reynolds, R.M., 2010. Impact of maternal obesity on oﬀspring obesity and
cardiometabolic disease risk. Reproduction 140 (3), 387–398. https://doi.org/10.
1530/rep-10-0077.
Drake, A.J., McPherson, R.C., Godfrey, K.M., Cooper, C., Lillycrop, K.A., Hanson, M.A.,
et al., 2012. An unbalanced maternal diet in pregnancy associates with oﬀspring
epigenetic changes in genes controlling glucocorticoid action and foetal growth. Clin
Endocrinol (Oxf) 77 (6), 808–815. https://doi.org/10.1111/j.1365-2265.2012.
04453.x.
Engen, P.A., Green, S.J., Voigt, R.M., Forsyth, C.B., Keshavarzian, A., 2015. The gastrointestinal microbiome: alcohol eﬀects on the composition of intestinal microbiota.
Alcohol Res. 37 (2), 223–236.
Entringer, S., Buss, C., Swanson, J.M., Cooper, D.M., Wing, D.A., Waﬀarn, F., et al.,
2012a. Fetal programming of body composition, obesity, and metabolic function: the
role of intrauterine stress and stress biology. J. Nutr. Metab. 2012, 632548 632516
pages.
Entringer, S., Buss, C., Swanson, J.M., Cooper, D.M., Wing, D.A., Waﬀarn, F., et al.,
2012b. Fetal programming of body composition, obesity, and metabolic function: the
role of intrauterine stress and stress biology. J. Nutr. Metab. 2012, 632548. https://
doi.org/10.1155/2012/632548.
Entringer, S., Buss, C., Wadhwa, P.D., 2015. Prenatal stress, development, health and
disease risk: a psychobiological perspective – 2015 Curt Richter Award Winner.
Psychoneuroendocrinology 62, 366–375. https://doi.org/10.1016/j.psyneuen.2015.
08.019.
Everaerd, D., Klumpers, F., Zwiers, M., Guadalupe, T., Franke, B., van Oostrom, I., et al.,
2015. Childhood abuse and deprivation are associated with distinct sex-dependent
diﬀerences in brain morphology. Neuropsychopharmacology. https://doi.org/10.
1038/npp.2015.344.
Facchinetti, F., Volpe, A., Matteo, M.L., Genazzani, A.R., Artini, G.P., 1997. An increased
vulnerability to stress is associated with a poor outcome of in vitro fertilizationembryo transfer treatment. Fertil. Steril. 67 (2), 309–314. https://doi.org/10.1016/
S0015-0282(97)81916-4.
Fagot-Campagna, A., Narayan, K.M., Imperatore, G., 2001. Type 2 diabetes in children.
BMJ 322 (7283), 377–378.
Felitti, V.J., Anda, R.F., Nordenberg, D., Williamson, D.F., Spitz, A.M., Edwards, V., et al.,
1998. Relationship of childhood abuse and household dysfunction to many of the
leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study.
Am. J. Prev. Med. 14 (4), 245–258.
Fowden, A.L., Giussani, D.A., Forhead, A.J., 2006. Intrauterine programming of physiological systems: causes and consequences. Physiology 21 (1), 29–37. https://doi.org/
10.1152/physiol.00050.2005.
Freedman, D.S., Khan, L.K., Dietz, W.H., Srinivasan, S.R., Berenson, G.S., 2001.
Relationship of childhood obesity to coronary heart disease risk factors in adulthood:
the Bogalusa Heart Study. Pediatrics 108 (3), 712–718.
Freedman, D.S., Mei, Z., Srinivasan, S.R., Berenson, G.S., Dietz, W.H., 2007.
Cardiovascular risk factors and excess adiposity among overweight children and
adolescents: the Bogalusa Heart Study. J. Pediatr. 150 (1), 12–17 e12.
Friedman, J.E., 2015. Obesity and gestational diabetes mellitus pathways for programming in mouse, monkey, and man-where do we go next? The 2014 Norbert Freinkel
award lecture. Diabetes Care 38 (8), 1402–1411. https://doi.org/10.2337/dc150628.
Friedman, J.E., 2018. Developmental programming of obesity and diabetes in mouse,
monkey, and man in 2018: where are we headed? Diabetes 67 (11), 2137–2151.
https://doi.org/10.2337/dbi17-0011.
Friedman, E.M., Karlamangla, A.S., Gruenewald, T.L., Koretz, B., Seeman, T.E., 2015.
Early life adversity and adult biological risk proﬁles. Psychosom. Med. 77 (2),
176–185. https://doi.org/10.1097/psy.0000000000000147.
Funkhouser, L.J., Bordenstein, S.R., 2013. Mom knows best: the universality of maternal
microbial transmission. PLoS Biol. 11 (8), e1001631. https://doi.org/10.1371/
journal.pbio.1001631.
Gademan, M.G., Vermeulen, M., Oostvogels, A.J., Roseboom, T.J., Visscher, T.L., van
Eijsden, M., et al., 2014. Maternal prepregancy BMI and lipid proﬁle during early
pregnancy are independently associated with oﬀspring’s body composition at age 5-6
years: the ABCD study. PLoS One 9 (4), e94594. https://doi.org/10.1371/journal.
pone.0094594.
Gapp, K., Jawaid, A., Sarkies, P., Bohacek, J., Pelczar, P., Prados, J., et al., 2014.
Implication of sperm RNAs in transgenerational inheritance of the eﬀects of early
trauma in mice. Nat. Neurosci. 17 (5), 667–669. https://doi.org/10.1038/nn.3695.
Ghoorah, K., Campbell, P., Kent, A., Maznyczka, A., Kunadian, V., 2014. Obesity and
cardiovascular outcomes: a review. Eur. Heart J. Acute Cardiovasc. Care (Epub ahead
of print), doi: 2048872614523349.
Gibbs, B.G., Forste, R., 2014. Socioeconomic status, infant feeding practices and early
childhood obesity. Pediatr. Obes. 9 (2), 135–146. https://doi.org/10.1111/j.20476310.2013.00155.x.
Gillman, M.W., Rich-Edwards, J.W., Huh, S., Majzoub, J.A., Oken, E., Taveras, E.M.,
et al., 2006. Maternal corticotropin-releasing hormone levels during pregnancy and
oﬀspring adiposity. Obesity (Silver Spring) 14 (9), 1647–1653. https://doi.org/10.
1038/oby.2006.189.
Gluckman, P.D., Hanson, M.A., 2004a. Living with the past: evolution, development, and
patterns of disease. Science 305 (5691), 1733–1736.
Gluckman, P.D., Hanson, M.A., 2004b. Living with the past: evolution, development, and
patterns of disease. Science 305 (5691), 1733–1736.
Godfrey, K.M., Barker, D.J., 2001. Fetal programming and adult health. Public Health
Nutr. 4 (2B; SPI), 611–624.
Godfrey, K.M., Sheppard, A., Gluckman, P.D., Lillycrop, K.A., Burdge, G.C., McLean, C.,
et al., 2011. Epigenetic gene promoter methylation at birth is associated with child’s
later adiposity. Diabetes 60 (5), 1528–1534. https://doi.org/10.2337/db10-0979.
Gohir, W., Whelan, F.J., Surette, M.G., Moore, C., Schertzer, J.D., Sloboda, D.M., 2015a.
Pregnancy-related changes in the maternal gut microbiota are dependent upon the
mother’s periconceptional diet. Gut Microbes 6 (5), 310–320. https://doi.org/10.
1080/19490976.2015.1086056.
Gohir, W., Ratcliﬀe, E.M., Sloboda, D.M., 2015b. Of the bugs that shape us: maternal
obesity, the gut microbiome, and long-term disease risk. Pediatr. Res. 77 (1-2),
196–204. https://doi.org/10.1038/pr.2014.169.
Gur, T.L., Bailey, M.T., 2016. Eﬀects of stress on commensal microbes and immune system
activity. Adv. Exp. Med. Biol. 874, 289–300. https://doi.org/10.1007/978-3-31920215-0_14.
Haire-Joshu, D., Tabak, R., 2016. Preventing obesity across generations: evidence for
early life intervention. Annu. Rev. Public Health 37 (1), 253–271 doi:doi:10.1146/
annurev-publhealth-032315-021859.
Hanson, M., Godfrey, K.M., Lillycrop, K.A., Burdge, G.C., Gluckman, P.D., 2011.
Developmental plasticity and developmental origins of non-communicable disease:
theoretical considerations and epigenetic mechanisms. Prog. Biophys. Mol. Biol. 106
(1), 272–280.
Heerwagen, M.J.R., Miller, M.R., Barbour, L.A., Friedman, J.E., 2010. Maternal obesity
and fetal metabolic programming: a fertile epigenetic soil. American Journal of
Physiology – Regulatory, Integrative and Comparative Physiology 299 (3),
R711–R722. https://doi.org/10.1152/ajpregu.00310.2010.
Heerwagen, M.J., Stewart, M.S., de la Houssaye, B.A., Janssen, R.C., Friedman, J.E., 2013.
Transgenic increase in N-3/n-6 Fatty Acid ratio reduces maternal obesity-associated
inﬂammation and limits adverse developmental programming in mice. PLoS One 8
(6), e67791. https://doi.org/10.1371/journal.pone.0067791.
Heim, C., Binder, E.B., 2012. Current research trends in early life stress and depression:
review of human studies on sensitive periods, gene-environment interactions, and
epigenetics. Exp. Neurol. 233 (1), 102–111. https://doi.org/10.1016/j.expneurol.
9
Psychoneuroendocrinology 116 (2020) 104659
K.L. Lindsay, et al.
Lewis, A., Austin, E., Knapp, R., Vaiano, T., Galbally, M., 2015. Perinatal maternal mental
health, fetal programming and child development. Healthcare 3 (4), 1212.
Lin, X., Lim, I.Y., Wu, Y., Teh, A.L., Chen, L., Aris, I.M., et al., 2017. Developmental
pathways to adiposity begin before birth and are inﬂuenced by genotype, prenatal
environment and epigenome. BMC Med. 15 (1), 50. https://doi.org/10.1186/s12916017-0800-1.
Locke, A.E., Kahali, B., Berndt, S.I., Justice, A.E., Pers, T.H., Day, F.R., et al., 2015.
Genetic studies of body mass index yield new insights for obesity biology. Nature 518
(7538), 197–206. https://doi.org/10.1038/nature14177.
Luo, Z.C., Nuyt, A.M., Delvin, E., Fraser, W.D., Julien, P., Audibert, F., et al., 2013.
Maternal and fetal leptin, adiponectin levels and associations with fetal insulin sensitivity. Obesity (Silver Spring) 21 (1), 210–216. https://doi.org/10.1002/oby.
20250.
Luoto, R., Collado, M.C., Salminen, S., Isolauri, E., 2013. Reshaping the gut microbiota at
an early age: functional impact on obesity risk? Ann. Nutr. Metab. 63 (Suppl 2),
17–26. https://doi.org/10.1159/000354896.
Luzzo, K.M., Wang, Q., Purcell, S.H., Chi, M., Jimenez, P.T., Grindler, N., et al., 2012.
High fat diet induced developmental defects in the mouse: oocyte meiotic aneuploidy
and fetal growth retardation/brain defects. PLoS One 7 (11), e49217. https://doi.
org/10.1371/journal.pone.0049217.
Matthews, S.G., 2000. Antenatal glucocorticoids and programming of the developing
CNS. Pediatr. Res. 47 (3), 291–300.
Matthews, K.A., Chang, Y.F., Thurston, R.C., Bromberger, J.T., 2014. Child abuse is related to inﬂammation in mid-life women: role of obesity. Brain Behav. Immun. 36,
29–34. https://doi.org/10.1016/j.bbi.2013.09.013.
McLaughlin, K.A., Sheridan, M.A., Lambert, H.K., 2014. Childhood adversity and neural
development: deprivation and threat as distinct dimensions of early experience.
Neurosci. Biobehav. Rev. 47, 578–591. https://doi.org/10.1016/j.neubiorev.2014.
10.012.
McPherson, K., 2014. Reducing the global prevalence of overweight and obesity. Lancet
384 (9945), 728–730. https://doi.org/10.1016/S0140-6736(14)60767-4.
Mestan, K., Ouyang, F., Matoba, N., Pearson, C., Ortiz, K., Wang, X., 2010. Maternal
obesity, diabetes mellitus and cord blood biomarkers in large-for-gestational age
infants. J. Pediatr. Biochem. 1 (3), 217–224.
Midei, A.J., Matthews, K.A., Bromberger, J.T., 2010. Childhood abuse is associated with
adiposity in midlife women: possible pathways through trait anger and reproductive
hormones. Psychosom. Med. 72 (2), 215–223. https://doi.org/10.1097/PSY.
0b013e3181cb5c24.
Midei, A.J., Matthews, K.A., Chang, Y.F., Bromberger, J.T., 2013. Childhood physical
abuse is associated with incident metabolic syndrome in mid-life women. Health
Psychol. 32 (2), 121–127. https://doi.org/10.1037/a0027891.
Miller, G.E., Engen, P.A., Gillevet, P.M., Shaikh, M., Sikaroodi, M., Forsyth, C.B., et al.,
2016. Lower neighborhood socioeconomic status associated with reduced diversity of
the colonic microbiota in healthy adults. PLoS One 11 (2), e0148952. https://doi.
org/10.1371/journal.pone.0148952.
Min, M.O., Minnes, S., Kim, H., Singer, L.T., 2013. Pathways linking childhood maltreatment and adult physical health. Child Abuse Negl. 37 (6), 361–373. https://doi.
org/10.1016/j.chiabu.2012.09.008.
Mogi, K., Nagasawa, M., Kikusui, T., 2011. Developmental consequences and biological
signiﬁcance of mother-infant bonding. Prog. Neuropsychopharmacol. Biol. Psychiatry
35 (5), 1232–1241. https://doi.org/10.1016/j.pnpbp.2010.08.024.
Moog, N., Buss, C., Entringer, S., Sandman, C.A., Wadhwa, P.D., 2012. Exposure to
childhood trauma among pregnant women is associated with increased placental
CRH production over gestation. Eur. J. Psychotraumatol. 3 (Supp 1) 19554 – https://
doi.org/19510.13402/ejpt.v19553i19550.19554.
Moog, N.K., Buss, C., Entringer, S., Shahbaba, B., Gillen, D.L., Hobel, C.J., et al., 2016.
Maternal exposure to childhood trauma is associated during pregnancy with placental-fetal stress physiology. Biol. Psychiatry 79 (10), 831–839. https://doi.org/10.
1016/j.biopsych.2015.08.032.
Moog, N.K., Heim, C.M., Entringer, S., Kathmann, N., Wadhwa, P.D., Buss, C., 2017a.
Childhood maltreatment is associated with increased risk of subclinical hypothyroidism in pregnancy. Psychoneuroendocrinology 84, 190–196. https://doi.org/10.
1016/j.psyneuen.2017.07.482.
Moog, N.K., Entringer, S., Heim, C., Wadhwa, P.D., Kathmann, N., Buss, C., 2017b.
Inﬂuence of maternal thyroid hormones during gestation on fetal brain development.
Neuroscience 342, 68–100. https://doi.org/10.1016/j.neuroscience.2015.09.070.
Moon, R.J., Harvey, N.C., Robinson, S.M., Ntani, G., Davies, J.H., Inskip, H.M., et al.,
2013. Maternal plasma polyunsaturated fatty acid status in late pregnancy is associated with oﬀspring body composition in childhood. J. Clin. Endocrinol. Metab. 98
(1), 299–307. https://doi.org/10.1210/jc.2012-2482.
Moussa, H.N., Alrais, M.A., Leon, M.G., Abbas, E.L., Sibai, B.M., 2016. Obesity epidemic:
impact from preconception to postpartum. Future Sci. OA 2 (3), FSO137. https://doi.
org/10.4155/fsoa-2016-0035.
Much, D., Brunner, S., Vollhardt, C., Schmid, D., Sedlmeier, E.M., Bruderl, M., et al.,
2013. Eﬀect of dietary intervention to reduce the n-6/n-3 fatty acid ratio on maternal
and fetal fatty acid proﬁle and its relation to oﬀspring growth and body composition
at 1 year of age. Eur. J. Clin. Nutr. 67 (3), 282–288. https://doi.org/10.1038/ejcn.
2013.2.
Muhlhausler, B.S., Duﬃeld, J.A., McMillen, I.C., 2007. Increased maternal nutrition stimulates peroxisome proliferator activated receptor-gamma, adiponectin, and leptin
messenger ribonucleic acid expression in adipose tissue before birth. Endocrinology
148 (2), 878–885. https://doi.org/10.1210/en.2006-1115.
Mumford, S.L., Michels, K.A., Salaria, N., Valanzasca, P., Belizán, J.M., 2014.
Preconception care: it’s never too early. Reprod. Health 11 (1), 1–3. https://doi.org/
10.1186/1742-4755-11-73.
Nader, P.R., Huang, T.T., Gahagan, S., Kumanyika, S., Hammond, R.A., Christoﬀel, K.K.,
2011.10.032.
Heim, C., Shugart, M., Craighead, W.E., Nemeroﬀ, C.B., 2010. Neurobiological and psychiatric consequences of child abuse and neglect. Dev. Psychobiol. 52 (7), 671–690.
https://doi.org/10.1002/dev.20494.
Hellmuth, C., Lindsay, K.L., Uhl, O., Buss, C., Wadhwa, P.D., Koletzko, B., et al., 2016.
Association of maternal prepregnancy BMI with metabolomic proﬁle across gestation.
Int. J. Obes. https://doi.org/10.1038/ijo.2016.153.
Hollingsworth, K., Callaway, L., Duhig, M., Matheson, S., Scott, J., 2012. The association
between maltreatment in childhood and pre-pregnancy obesity in women attending
an antenatal clinic in Australia. PLoS One 7 (12), e51868. https://doi.org/10.1371/
journal.pone.0051868.
Hou, R.L., Jin, W.Y., Chen, X.Y., Jin, Y., Wang, X.M., Shao, J., et al., 2014. Cord blood Cpeptide, insulin, HbA1c, and lipids levels in small- and large-for-gestational-age
newborns. Med. Sci. Monit. 20, 2097–2105. https://doi.org/10.12659/msm.890929.
Hulme, P.A., 2000. Symptomatology and health care utilization of women primary care
patients who experienced childhood sexual abuse1. Child Abuse Negl. 24 (11),
1471–1484. https://doi.org/10.1016/S0145-2134(00)00200-3.
Hunsberger, M., Lanfer, A., Reeske, A., Veidebaum, T., Russo, P., Hadjigeorgiou, C., et al.,
2013. Infant feeding practices and prevalence of obesity in eight European countries the IDEFICS study. Public Health Nutr. 16 (2), 219–227. https://doi.org/10.1017/
s1368980012003850.
Hussey, J.M., Chang, J.J., Kotch, J.B., 2006. Child maltreatment in the United States:
prevalence, risk factors, and adolescent health consequences. Pediatrics 118 (3),
933–942. https://doi.org/10.1542/peds.2005-2452.
Institute of Medicine, 2011. Early Childhood Obesity Prevention Policies. The National
Academies Press, Washington, DC. https://doi.org/10.17226/13124.
Jakubowski, K.P., Cundiﬀ, J.M., Matthews, K.A., 2018. Cumulative childhood adversity
and adult cardiometabolic disease: a meta-analysis. Health Psychol. 37 (8), 701–715.
https://doi.org/10.1037/hea0000637.
Jenmalm, M.C., 2017. The mother–oﬀspring dyad: microbial transmission, immune interactions and allergy development. J. Intern. Med. https://doi.org/10.1111/joim.
12652.
Josefson, J.L., Zeiss, D.M., Rademaker, A.W., Metzger, B.E., 2014. Maternal leptin predicts adiposity of the neonate. Horm. Res. Paediatr. 81 (1), 13–19. https://doi.org/
10.1159/000355387.
Jovanovic, T., Smith, A., Kamkwalala, A., Poole, J., Samples, T., Norrholm, S.D., et al.,
2011. Physiological markers of anxiety are increased in children of abused mothers.
J. Child Psychol. Psychiatry 52 (8), 844–852. https://doi.org/10.1111/j.1469-7610.
2011.02410.x.
Keenan, K., Hipwell, A.E., Class, Q.A., Mbayiwa, K., 2018. Extending the developmental
origins of disease model: impact of preconception stress exposure on oﬀspring neurodevelopment. Dev. Psychobiol. 60 (7), 753–764. https://doi.org/10.1002/dev.
21773.
Kelly, A.S., Barlow, S.E., Rao, G., Inge, T.H., Hayman, L.L., Steinberger, J., et al., 2013.
Severe obesity in children and adolescents: identiﬁcation, associated health risks, and
treatment approaches a scientiﬁc statement from the American Heart Association.
Circulation 128 (15), 1689–1712.
Kermack, W.O., McKendrick, A.G., McKinlay, P.L., 1934. Death-rates in Great Britain and
Sweden: expression of speciﬁc mortality rates as products of two factors, and some
consequences thereof. J Hyg (Lond) 34 (4), 433–457.
Kirchner, S., Kieu, T., Chow, C., Casey, S., Blumberg, B., 2010. Prenatal exposure to the
environmental obesogen tributyltin predisposes multipotent stem cells to become
adipocytes. Mol. Endocrinol. 24 (3), 526–539. https://doi.org/10.1210/me.20090261.
Klaassens, E.R., van Noorden, M.S., Giltay, E.J., van Pelt, J., van Veen, T., Zitman, F.G.,
2009. Eﬀects of childhood trauma on HPA-axis reactivity in women free of lifetime
psychopathology. Prog. Neuropsychopharmacol. Biol. Psychiatry 33 (5), 889–894.
https://doi.org/10.1016/j.pnpbp.2009.04.011.
Krisher, R.L., 2004. The eﬀect of oocyte quality on development. J. Anim. Sci. 82 (ESuppl), E14–23.
Laker, R.C., Wlodek, M.E., Connelly, J.J., Yan, Z., 2013. Epigenetic origins of metabolic
disease: the impact of the maternal condition to the oﬀspring epigenome and later
health consequences. Food Sci. Hum. Wellness 2 (1), 1–11. https://doi.org/10.1016/
j.fshw.2013.03.002.
Lakshman, R., Elks, C.E., Ong, K.K., 2012. Childhood obesity. Circulation 126 (14),
1770–1779. https://doi.org/10.1161/circulationaha.111.047738.
Lane, M., Zander-Fox, D.L., Robker, R.L., McPherson, N.O., 2015. Peri-conception parental obesity, reproductive health, and transgenerational impacts. Trends Endocrinol.
Metab. 26 (2), 84–90. https://doi.org/10.1016/j.tem.2014.11.005.
Langley-Evans, S.C., 2006. Fetal Programming and Adult Disease. Programming of
Chronic Disease through Fetal Exposure to Undernutrition. CABI Publishing.,
Wallingford.
Latham, K.E., 2015. Endoplasmic reticulum stress signaling in mammalian oocytes and
embryos: life in balance. Int. Rev. Cell Mol. Biol. 316, 227–265. https://doi.org/10.
1016/bs.ircmb.2015.01.005.
Lefebvre, R., Fallon, B., Van Wert, M., Filippelli, J., 2017. Examining the relationship
between economic hardship and child maltreatment using data from the ontario incidence study of reported child abuse and neglect-2013 (OIS-2013). Behav. Sci.
(Basel, Switzerland) 7 (1), 6. https://doi.org/10.3390/bs7010006.
Leonard, S.A., Petito, L.C., Rehkopf, D.H., Ritchie, L.D., Abrams, B., 2017. Maternal
history of child abuse and obesity risk in oﬀspring: mediation by weight in pregnancy. Child. Obes. 13 (4), 259–266. https://doi.org/10.1089/chi.2017.0019.
Leon-Mimila, P., Villamil-Ramirez, H., Villalobos-Comparan, M., Villarreal-Molina, T.,
Romero-Hidalgo, S., Lopez-Contreras, B., et al., 2013. Contribution of common genetic variants to obesity and obesity-related traits in Mexican children and adults.
PLoS One 8 (8), e70640. https://doi.org/10.1371/journal.pone.0070640.
10
Psychoneuroendocrinology 116 (2020) 104659
K.L. Lindsay, et al.
pregnancies with gestational diabetes mellitus. Diabetes Care 31 (9), 1858–1863.
https://doi.org/10.2337/dc08-0039.
Schaefer-Graf, U.M., Meitzner, K., Ortega-Senovilla, H., Graf, K., Vetter, K., Abou-Dakn,
M., et al., 2011. Diﬀerences in the implications of maternal lipids on fetal metabolism
and growth between gestational diabetes mellitus and control pregnancies. Diabet.
Med. 28 (9), 1053–1059. https://doi.org/10.1111/j.1464-5491.2011.03346.x.
Scher, C.D., Forde, D.R., McQuaid, J.R., Stein, M.B., 2004. Prevalence and demographic
correlates of childhood maltreatment in an adult community sample. Child Abuse
Negl. 28 (2), 167–180. https://doi.org/10.1016/j.chiabu.2003.09.012.
Scholtens, D.M., Muehlbauer, M.J., Daya, N.R., Stevens, R.D., Dyer, A.R., Lowe, L.P.,
et al., 2014. Metabolomics reveals broad-scale metabolic perturbations in hyperglycemic mothers during pregnancy. Diabetes Care 37 (1), 158–166. https://doi.org/10.
2337/dc13-0989.
Schwartz, M.W.S.R.J., Zeltser, L.M., Drewnowski, A., Ravussin, E., Redman, L.M., Leibel,
R.L., 2017. Obesity pathogenesis: an endocrine society scientiﬁc statement. Endocr.
Rev. https://doi.org/10.1210/er.2017-00111. er.2017-00111. doi:doi:.
Serdula, M.K., Ivery, D., Coates, R.J., Freedman, D.S., Williamson, D.F., Byers, T., 1993.
Do obese children become obese adults? A review of the literature. Prev. Med. 22 (2),
167–177.
Silverman, J.G., Decker, M.R., Reed, E., Raj, A., 2006. Intimate partner violence around
the time of pregnancy: association with breastfeeding behavior. J Womens Health
(Larchmt) 15 (8), 934–940. https://doi.org/10.1089/jwh.2006.15.934.
Slopen, N., Loucks, E.B., Appleton, A.A., Kawachi, I., Kubzansky, L.D., Non, A.L., et al.,
2015. Early origins of inﬂammation: An examination of prenatal and childhood social
adversity in a prospective cohort study. Psychoneuroendocrinology 51, 403–413.
https://doi.org/10.1016/j.psyneuen.2014.10.016.
Sluyter, J.D., Scragg, R.K., Plank, L.D., Waqa, G.D., Fotu, K.F., Swinburn, B.A., 2013.
Sizing the association between lifestyle behaviours and fatness in a large, heterogeneous sample of youth of multiple ethnicities from 4 countries. Int. J. Behav. Nutr.
Phys. Act. 10, 115. https://doi.org/10.1186/1479-5868-10-115.
Soderborg, T.K., Borengasser, S.J., Barbour, L.A., Friedman, J.E., 2016. Microbial transmission from mothers with obesity or diabetes to infants: an innovative opportunity
to interrupt a vicious cycle. Diabetologia 59 (5), 895–906. https://doi.org/10.1007/
s00125-016-3880-0.
Somm, E., Schwitzgebel, V.M., Vauthay, D.M., Camm, E.J., Chen, C.Y., Giacobino, J.P.,
et al., 2008. Prenatal nicotine exposure alters early pancreatic islet and adipose tissue
development with consequences on the control of body weight and glucose metabolism later in life. Endocrinology 149 (12), 6289–6299. https://doi.org/10.1210/
en.2008-0361.
Sorbo, M.F., Lukasse, M., Brantsaeter, A.L., Grimstad, H., 2015. Past and recent abuse is
associated with early cessation of breast feeding: results from a large prospective
cohort in Norway. BMJ Open 5 (12), e009240. https://doi.org/10.1136/bmjopen2015-009240.
Soubry, A., Hoyo, C., Jirtle, R.L., Murphy, S.K., 2014. A paternal environmental legacy:
evidence for epigenetic inheritance through the male germ line. Bioessays 36 (4),
359–371. https://doi.org/10.1002/bies.201300113.
Sovio, U., Mook-Kanamori, D.O., Warrington, N.M., Lawrence, R., Briollais, L., Palmer,
C.N., et al., 2011. Association between common variation at the FTO locus and
changes in body mass index from infancy to late childhood: the complex nature of
genetic association through growth and development. PLoS Genet. 7 (2), e1001307.
https://doi.org/10.1371/journal.pgen.1001307.
Speliotes, E.K., Willer, C.J., Berndt, S.I., Monda, K.L., Thorleifsson, G., Jackson, A.U.,
et al., 2010. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42 (11), 937–948. https://doi.org/10.1038/
ng.686.
Stephenson, J., Heslehurst, N., Hall, J., Schoenaker, D.A.J.M., Hutchinson, J., Cade, J.E.,
et al., 2018. Before the beginning: nutrition and lifestyle in the preconception period
and its importance for future health. Lancet (London, England) 391 (10132),
1830–1841. https://doi.org/10.1016/S0140-6736(18)30311-8.
Sternthal, M.J., Enlow, M.B., Cohen, S., Canner, M.J., Staudenmayer, J., Tsang, K., et al.,
2009. Maternal interpersonal trauma and cord blood IgE levels in an inner-city cohort: a life-course perspective. J. Allergy Clin. Immunol. 124 (5), 954–960. https://
doi.org/10.1016/j.jaci.2009.07.030.
Stirrat, L.I., O’Reilly, J.R., Riley, S.C., Howie, A.F., Beckett, G.J., Smith, R., et al., 2014.
Altered maternal hypothalamic-pituitary-adrenal axis activity in obese pregnancy is
associated with macrosomia and prolonged pregnancy. Pregnancy Hypertens. 4 (3),
238. https://doi.org/10.1016/j.preghy.2014.03.028.
Stirrat, L.I., O’Reilly, J.R., Barr, S.M., Andrew, R., Riley, S.C., Howie, A.F., et al., 2016.
Decreased maternal hypothalamic-pituitary-adrenal axis activity in very severely
obese pregnancy: associations with birthweight and gestation at delivery.
Psychoneuroendocrinology 63, 135–143. https://doi.org/10.1016/j.psyneuen.2015.
09.019.
Tamayo, T., Christian, H., Rathmann, W., 2010. Impact of early psychosocial factors
(childhood socioeconomic factors and adversities) on future risk of type 2 diabetes,
metabolic disturbances and obesity: a systematic review. BMC Public Health 10, 525.
https://doi.org/10.1186/1471-2458-10-525.
Teague, A.M., Fields, D.A., Aston, C.E., Short, K.R., Lyons, T.J., Chernausek, S.D., 2015.
Cord blood adipokines, neonatal anthropometrics and postnatal growth in oﬀspring
of Hispanic and Native American women with diabetes mellitus. Reprod. Biol.
Endocrinol. 13, 68. https://doi.org/10.1186/s12958-015-0061-9.
Thomas, C., Hypponen, E., Power, C., 2008. Obesity and type 2 diabetes risk in midadult
life: the role of childhood adversity. Pediatrics 121 (5), e1240–1249. https://doi.org/
10.1542/peds.2007-2403.
Thompson, L.P., Al-Hasan, Y., 2012. Impact of oxidative stress in fetal programming. J.
Pregnancy 2012, 8. https://doi.org/10.1155/2012/582748.
Turner, N., Robker, R.L., 2015. Developmental programming of obesity and insulin
2012. Next steps in obesity prevention: altering early life systems to support healthy
parents, infants, and toddlers. Child. Obes. 8 (3), 195–204. https://doi.org/10.1089/
chi.2012.0004.
Nagl, M., Steinig, J., Klinitzke, G., Stepan, H., Kersting, A., 2015. Childhood maltreatment
and pre-pregnancy obesity: a comparison of obese, overweight, and normal weight
pregnant women. Arch. Womens Ment. Health. https://doi.org/10.1007/s00737015-0573-5.
Nayak, C.D., Agarwal, V., Nayak, D.M., 2013. Correlation of cord blood lipid heterogeneity in neonates with their anthropometry at birth. Indian J. Clin. Biochem. 28
(2), 152–157. https://doi.org/10.1007/s12291-012-0252-5.
Newton, S., Braithwaite, D., Akinyemiju, T.F., 2017. Socio-economic status over the life
course and obesity: systematic review and meta-analysis. PLoS One 12 (5), e0177151.
https://doi.org/10.1371/journal.pone.0177151.
Niegel, S., Ystrom, E., Hagtvet, K.A., Vollrath, M.E., 2008. Diﬃcult Temperament,
Breastfeeding, and Their Mutual Prospective Eﬀects: The Norwegian Mother and
Child Cohort Study. J. Dev. Behav. Pediatr. 29 (6), 458–462. https://doi.org/10.
1097/DBP.0b013e3181877a88.
Oddy, W.H., Mori, T.A., Huang, R.C., Marsh, J.A., Pennell, C.E., Chivers, P.T., et al., 2014.
Early infant feeding and adiposity risk: from infancy to adulthood. Ann. Nutr. Metab.
64 (3-4), 262–270. https://doi.org/10.1159/000365031.
Oken, E., Gillman, M.W., 2003. Fetal origins of obesity. Obes. Res. 11 (4), 496–506.
Olshansky, S.J., Passaro, D.J., Hershow, R.C., Layden, J., Carnes, B.A., Brody, J., et al.,
2005. A potential decline in life expectancy in the United States in the 21st century.
N. Engl. J. Med. 352 (11), 1138–1145.
Ormond, K.E., Mortlock, D.P., Scholes, D.T., Bombard, Y., Brody, L.C., Faucett, W.A.,
et al., 2017. Human germline genome editing. Am. J. Hum. Genet. 101 (2), 167–176.
https://doi.org/10.1016/j.ajhg.2017.06.012.
Padmanabhan, V., Cardoso, R.C., Puttabyatappa, M., 2016. Developmental programming,
a pathway to disease. Endocrinology 157 (4), 1328–1340. https://doi.org/10.1210/
en.2016-1003.
Palma-Gudiel, H., Córdova-Palomera, A., Eixarch, E., Deuschle, M., Fananas, L., 2015.
Maternal psychosocial stress during pregnancy alters the epigenetic signature of the
glucocorticoid receptor gene promoter in their oﬀspring: a meta-analysis. Epigenetics
10 (10), 893–902.
Planalp, E.M., Braungart-Rieker, J.M., 2013. Temperamental precursors of infant attachment with mothers and fathers. Infant Behav. Dev. 36 (4), 796–808. https://doi.
org/10.1016/j.infbeh.2013.09.004.
Plant, D.T., Barker, E.D., Waters, C.S., Pawlby, S., Pariante, C.M., 2013. Intergenerational
transmission of maltreatment and psychopathology: the role of antenatal depression.
Psychol. Med. 43 (3), 519–528. https://doi.org/10.1017/S0033291712001298.
Portha, B., Chavey, A., Movassat, J., 2011. Early-life origins of type 2 diabetes: fetal
programming of the beta-cell mass. Exp. Diabetes Res. 2011https://doi.org/10.1155/
2011/105076). 16 pages.
Poston, L., Bell, R., Croker, H., Flynn, A.C., Godfrey, K.M., Goﬀ, L., et al., 2015. Eﬀect of a
behavioural intervention in obese pregnant women (the UPBEAT study): a multicentre, randomised controlled trial. Lancet Diabetes Endocrinol. 3 (10), 767–777.
https://doi.org/10.1016/S2213-8587(15)00227-2.
Radaelli, T., Uvena-Celebrezze, J., Minium, J., Huston-Presley, L., Catalano, P., Hauguelde Mouzon, S., 2006. Maternal interleukin-6: marker of fetal growth and adiposity. J.
Soc. Gynecol. Investig. 13 (1), 53–57. https://doi.org/10.1016/j.jsgi.2005.10.003.
Rakers, F., Bischoﬀ, S., Schiﬀner, R., Haase, M., Rupprecht, S., Kiehntopf, M., et al., 2015.
Role of catecholamines in maternal-fetal stress transfer in sheep. Am. J. Obstet.
Gynecol. 213 (5), 684. https://doi.org/10.1016/j.ajog.2015.07.020. e681-689.
Rasmussen, L.J.H., Moﬃtt, T.E., Arseneault, L., Danese, A., Eugen-Olsen, J., Fisher, H.L.,
et al., 2019. Association of adverse experiences and exposure to violence in childhood
and adolescence with inﬂammatory burden in young people. JAMA Pediatr. 174 (1),
1–11. https://doi.org/10.1001/jamapediatrics.2019.3875.
Regnault, N., Botton, J., Heude, B., Forhan, A., Hankard, R., Foliguet, B., et al., 2011.
Higher cord C-peptide concentrations are associated with slower growth rate in the
1st year of life in girls but not in boys. Diabetes 60 (8), 2152–2159. https://doi.org/
10.2337/db10-1189.
Rich-Edwards, J.W., Spiegelman, D., Lividoti Hibert, E.N., Jun, H.J., Todd, T.J., Kawachi,
I., et al., 2010. Abuse in childhood and adolescence as a predictor of type 2 diabetes
in adult women. Am. J. Prev. Med. 39 (6), 529–536. https://doi.org/10.1016/j.
amepre.2010.09.007.
Rikknen, K., Matthews, K.A., Kuller, L.H., 2002. The relationship between psychological
risk attributes and the metabolic syndrome in healthy women: Antecedent or consequence? Metabolism 51 (12), 1573–1577. https://doi.org/10.1053/meta.2002.
36301.
Roberts, A.L., Lyall, K., Rich-Edwards, J.W., Ascherio, A., Weisskopf, M.G., 2013.
Association of maternal exposure to childhood abuse with elevated risk for autism in
oﬀspring. JAMA Psychiatry 70 (5), 508–515. https://doi.org/10.1001/
jamapsychiatry.2013.447.
Roberts, A.L., Galea, S., Austin, S.B., Corliss, H.L., Williams, M.A., Koenen, K.C., 2014.
Women’s experience of abuse in childhood and their children’s smoking and overweight. Am. J. Prev. Med. 46 (3), 249–258. https://doi.org/10.1016/j.amepre.2013.
11.012.
Robinson, M.R., English, G., Moser, G., Lloyd-Jones, L.R., Triplett, M.A., Zhu, Z., et al.,
2017. Genotype-…

Hire a Writer

Client Reviews

4.9

Sitejabber

4.6

Trustpilot

4.8

Our Guarantees

100% Confidentiality

Information about customers is confidential and never disclosed to third parties.

Original Writing

We complete all papers from scratch. You can get a plagiarism report.

Timely Delivery

No missed deadlines – 97% of assignments are completed in time.

Money Back

If you're confident that a writer didn't follow your order details, ask for a refund.

New to Artemis 2000? Sign up & Save

Calculate the price of your order

Type of paper needed:

Pages:

You will get a personal manager and a discount.

Academic level:

We'll send you the first draft for approval by at

Total price:

$0.00

Power up Your Academic Success with the
Team of Professionals. We’ve Got Your Back.

Power up Your Study Success with Experts We’ve Got Your Back.

Order Now Order Now