Content uploaded by Elizabeth D Handley
Author content
All content in this area was uploaded by Elizabeth D Handley on May 16, 2019
Content may be subject to copyright.
Genome-wide DNA methylation in 1-year-old infants of mothers
with major depressive disorder
DANTE CICCHETTI,
a,b
SUSAN HETZEL,
a
FRED A. ROGOSCH,
b
ELIZABETH D. HANDLEY,
b
AND
SHEREE L. TOTH
b
aUniversity of Minnesota Institute of Child Development; and bUniversity of Rochester Mt. Hope Family Center
Abstract
A genome-wide methylation study was conducted among a sample of 114 infants (Mage ¼13.2 months, SD ¼1.08) of low-income urban women with
(n¼73) and without (n¼41) major depressive disorder. The Illumina HumanMethylation450 BeadChip array with a GenomeStudio Methylation Module
and Illumina Custom model were used to conduct differential methylation analyses. Using the 5.010–7 pvalue, 2,119 loci were found to be significantly
different between infants of depressed and nondepressed mothers. Infants of depressed mothers had greater methylation at low methylation sites (0%–29%)
compared to infants of nondepressed mothers. At high levels of methylation (70%–100%), the infants of depressed mothers were predominantly
hypomethylated. The mean difference in methylation between the infants of depressed and infants of nondepressed mothers was 5.23%. Disease by biomarker
analyses were also conducted using GeneGo MetaCore Software. The results indicated significant cancer-related differences in biomarker networks such as
prostatic neoplasms, ovarian and breast neoplasms, and colonic neoplasms. The results of a process networks analysis indicated significant differences in
process networks associated with neuronal development and central nervous system functioning, as well as cardiac development between infants of depressed
and nondepressed mothers. These findings indicate that early in development, infants of mothers with major depressive disorder evince epigenetic differences
relative to infants of well mothers that suggest risk for later adverse health outcomes.
As has been widely documented in the scientific literature,
children of mothers with depression are at risk for a range of
negative developmental sequelae over the course of develop-
ment (Cicchetti & Schneider-Rosen, 1986;Cicchetti&Toth,
1998; Goodman & Gotlib, 1999). Infants of mothers with de-
pression also exhibit problems with developmental attainments
(Cicchetti & Aber, 1986; Field & Diego, 2008). Included among
these negative effects of maternal depression on infant out-
come are homeostatic and physiological dysregulation, affect
differentiation and emotional responsivity, emotion dysregula-
tion, insecure and disorganized attachment, hemispheric acti-
vation asymmetries, and self–other differentiation (Cicchetti
&Toth,1995,1998; Cicchetti, Rogosch, Toth, & Spagnola,
1997; Cole, Luby, & Sullivan, 2008; Davidson & Fox, 1982;
Radke-Yarrow, Cummings, Kuczynski, & Chapman, 1985).
The developmental cascade of negative developmental
outcomes is attributed to interactive, experiential aspects of
the mother–child relationship (e.g., maternal insensitivity, in-
appropriate responsivity, and greater blunted, depressed, and
angry affect; Cole et al., 2008; Cummings & Cicchetti, 1990).
Thus, it is thought that infants of depressed mothers go
through atypical, “not good enough,” rearing experiences
and do not receive the appropriate level of relational “nutri-
ents” to foster adaptive development.
The same scenario holds for infants who are maltreated.
Stress mechanisms have been invoked as the “cause” of
epigenetic modification in these children. Moreover, the in-
fant of a depressed mother also may experience “stress,”
but of a rather different kind. In addition to stress, there
may be other aspects of the infant of a depressed mother’s
relational experience that may be related to epigenetic mod-
ification, relative to infants with “good enough” rearing ex-
periences.
We hypothesize that epigenetic modifications occur that
are a consequence of rearing by a depressed mother. If
there is no appreciable modification, then developmental
differences in offspring may be more experientially based
and not influenced by epigenetics. However, if there are
differences, then consideration of the role of epigenetics
in the developmental process and trajectories of these in-
fants may be an important area of inquiry. A first step,
then, is to determine if there is evidence for epigenetic dif-
ferences.
This is the first study, or at least one of the very first stud-
ies, conducted with infants from low-socioeconomic status
backgrounds who are the offspring of mothers with, or with-
out, major depressive disorder (MDD). Thus, this investiga-
tion contains both the risks associated with poverty and those
associated with having a mother with MDD.
Address correspondence and reprint requests to: Dante Cicchetti, Institute
of Child Development, University of Minnesota, 51 East River Road, Min-
neapolis, MN 55455; E-mail: cicchett@umn.edu.
This research was supported by grants from the Jacobs Foundation (to D.C.)
and the National Institute of Mental Health (R01 MH67792 to D.C. and
S.L.T.).
Development and Psychopathology, 2016, page 1 of 7
#Cambridge University Press 2016
doi:10.1017/S0954579416000912
1
http://dx.doi.org/10.1017/S0954579416000912
Downloaded from http:/www.cambridge.org/core. University of Rochester, on 11 Oct 2016 at 19:55:30, subject to the Cambridge Core terms of use, available at http:/www.cambridge.org/core/terms.
1. We hypothesize that infant offspring of mothers with
MDD will evince methylation differences relative to in-
fants of well mothers.
2. Compared to infants of well mothers, infants with MDD
will demonstrate greater adverse physical and mental
health risk based on patterns of differential methylation as-
sociated with disorder outcomes.
Method
Participants
Participants included 114 infants (Mage ¼13.2 months, SD
¼1.08) of low-income urban women. The sample was drawn
from a larger randomized control trial investigation evaluat-
ing preventive interventions for mothers with MDD (Toth,
Rogosch, Manly, & Cicchetti, 2006) and was composed of in-
fants of mothers with MDD (n¼73) and a comparison group
of infants of mothers without depression (n¼41). More
mothers and children were recruited for the depressed group
for random assignment to intervention arms. Data from the
current investigation were drawn from baseline assessments
prior to randomization. Mothers provided informed consent
for participation prior to the initiation of data collection,
and the research was conducted in accord with Institutional
Review Board approval.
Recruitment. All mothers in the depressed group met criteria
for MDD. We recruited a community sample of non–treat-
ment-seeking women from primary care clinics serving
low-income women and from Women, Infant and Children
(WIC) clinics. To be eligible, women needed to reside at or
below the federal poverty level. Seventy-eight percent of
the sample was below the US Department of Health and Hu-
man Services definition of poverty level, and 96% met WIC
criteria (185% of the poverty level). A project recruitment co-
ordinator initially screened women with the Center for Epide-
miologic Studies Depression Scale (CES-D; Radloff, 1977),
and those scoring above 16 were targeted for further assess-
ments to determine eligibility for inclusion. Women who sub-
sequently scored 19 or higher on the Beck Depression Inven-
tory—II (BDI-II; Beck, Steer, & Brown, 1996), and who met
MDD diagnostic criteria based on the operational criteria on
the Diagnostic Interview Schedule (DIS-IV; Robins, Cottler,
Bucholz, & Compton, 1995) were eligible to participate. For
all but 6.3% of the women, the onset of their first major de-
pressive episode had been over 1 year ago, thus preceding
the infant’s birth. Accordingly, the current sample was not
composed of women with depression restricted to the post-
partum period, but rather was of longer standing duration.
At baseline, consistent with inclusion criteria, all mothers
in the depressed group had BDI-II scores above 19 and also
met criteria for a current MDD diagnosis. Women meeting di-
agnostic criteria for lifetime bipolar disorder or for any life-
time psychotic spectrum disorder were excluded. Women
with mood disorder due to a general medical condition and
substance-induced mood disorder also were excluded, as
were women with any current alcohol or substance abuse dis-
order, as defined by DSM-IV criteria. Women with other co-
morbid disorders were not excluded.
Demographically comparable low-income mothers of in-
fants in the nondepressed group also were recruited by the
project recruitment coordinator at primary care clinics and
WIC offices. These mothers also were screened for depres-
sive symptoms with the CES-D, and those scoring below
the clinical cutoff were invited for further screening. Baseline
assessments with the BDI-II and DIS-IV were used to exclude
mothers with BDI-II scores greater than 12 or with histories
of MDD or other DSM-IV diagnoses.
Sample characteristics. Infants in the depressed and nonde-
pressed mother groups were comparable on a range of demo-
graphic variables (see Table 1). No significant differences
were observed between groups for child age, t(112) ¼
0.25, p¼.80, child gender, x2(1) ¼0.20, p¼.66, child
race, x2(1) ¼0.05, p¼.83, or child ethnicity, x2(1) ¼
0.63, p¼.43. Similarly, to characterize maternal and family
demographics, the depressed and nondepressed groups were
comparable in terms of maternal age, t(112) ¼0.25, p¼
.80, marital status of never married, x2(1) ¼2.28, p¼.13,
years of education, t(112) ¼1.59, p¼.12, low socioeco-
nomic status status based on the Hollingshead scale, x2(1)
¼1.76, p¼.19, and current receipt of public assistance, x2
(1) ¼0.17, p¼.68. Mothers in the depressed and nonde-
pressed groups differed substantially on BDI-II scores, t
(102.3) ¼22.72, p,.001, consistent with respective group
recruitment criteria.
Procedures
As part of the larger investigation, mothers and their infants
participated in baseline assessments during laboratory- and
home-based research sessions. All assessments were conducted
by trained research assistants who were unaware of group con-
dition or study hypotheses. During laboratory sessions, DNA
samples were obtained from infants, as described below.
Table 1. Demographic characteristics
Depressed
Group
Nondepressed
Group
Child age (months), M(SD) 13.27 (1.09) 13.22 (0.96)
Gender (% female) 49.3 53.2
Child race (% African American) 58.9 61.0
Child ethnicity (% Latino) 28.8 22.0
Maternal age, M(SD) 24.85 (5.04) 24.63 (5.06)
Marital status (% never married) 80.8 68.3
Years of education, M(SD) 11.68 (1.70) 12.24 (1.97)
Current public assistance 98.6 97.6
BDI-II score, M(SD) 31.23 (8.89) 4.63 (3.48)
Note: All contrasts were nonsignificant for demographic variables. BDI-II,
Beck Depression Inventory—II. BDI-II scores: p,.001.
D. Cicchetti et al.2
http://dx.doi.org/10.1017/S0954579416000912
Downloaded from http:/www.cambridge.org/core. University of Rochester, on 11 Oct 2016 at 19:55:30, subject to the Cambridge Core terms of use, available at http:/www.cambridge.org/core/terms.
Maternal measures
CES-D. The CES-D (Radloff, 1977) is a frequently used,
well-validated 20-item scale to screen for depression. Scores
.16 predict a high likelihood of MDD.
DIS-IV. The DIS-IV (Robins et al., 1995) is a structured inter-
view designed to assess diagnostic criteria for Axis I disorders,
as well as for antisocial personality disorder, as outlined in the
Diagnostic and Statistical Manual of Mental Disorders Fourth
Edition (DSM-IV; American Psychiatric Association, 1994).
The DIS-IV ascertains diagnoses present in the past year, the
past 6 months, and those that are current or remitted. The
DIS has been shown to be reliable and valid for use in psychi-
atric epidemiological field studies (Robins, Helzer, Croughan,
&Ratcliff,1981; Robins, Helzer, Ratcliff, & Seyfried, 1982).
Robins et al. (1981) compared DSM diagnoses made using the
DIS to those made by psychiatrists and reported mean k¼
0.69, sensitivity of 75%, and specificity of 94%. Given the
forced choice structured format of the DIS, interviewers do
not need to be trained clinicians. All interviewers were trained
to criterion reliability in the administration of the DIS and com-
puter-generated diagnoses were utilized.
BDI-II. The BDI-II (Beck et al., 1996) is the most widely used
self-report instrument for measuring the severity of depression.
It includes 21 questions in a multiple-choice format, and scores
of 17 or above indicate levels of depression with clinical signif-
icance. Previous studies report that the BDI-II demonstrates
good internal consistency (coefficient a¼0.91) and validity
(Dozois, Dobson, & Ahnberg 1998; Storch, Roberti, & Roth,
2004). In the current study, the average internal consistency
of the BDI-II based on the three assessments was a¼0.94.
DNA sampling and methylation
Buccal swab samples were collected from infants during base-
line laboratory sessions using the BuccalAmpTM DNA Extrac-
tion Kit (Epicentre, Item BQ0901). After collection, the swabs
were processed into the provided QuickExtract solution and
stored at –80 8C. The entire sample of approximately 450 ml
was purified using a chloroform extraction in 1.5 ml MaXtract
High Density tubes (Qiagen, Item 129046). The aqueous
layer was recovered and DNA precipitated by adding 15 ml
of 3 M sodium acetate and 1 ml 100% ethanol and incubating
at –20 8C for 1 hr. The sample was then pelleted by centrifuga-
tion in an Allegra 25R (Beckman Coulter, Inc.) at 12,000g
for 20 min. The samples were then washed three times in
80% ethanol, dried, and resuspended in 50 ml 1X Tris-EDTA.
The diluted DNA samples were submitted to the BioMedical
Genomics Center at the University of Minnesota for quality
analysis in preparation for testing of whole-genome methylation
analysis using the HumanMethylation450 BeadChip (Illumina).
The samples were assayed for quality by determining the con-
centration by Quant-iT PicoGreen dsDNA Assay Kit (Invitro-
gen, Item P7589) and real-time polymerase chain reaction (Taq-
Man) quantification of human DNA concentration. DNA
samples were included based on the previously determined cri-
teria of greater than 40% of the total DNA in the sample to be
human (real-time polymerase chain reaction divided by Pico-
Green)andaminimumof40nghumanDNA.
For samples that passed quality-control testing, 40 ng of
each sample and three study samples at 60, 40 (replicated),
and 20 ng were subjected to bisulfite conversion using the
EZ-96 DNA Methylation Kit (Zymo Research, D5003), which
converts unmethylated cytosine bases to uracils. This method
utilizes the methyl group attached to a cytosine as a protecting
group to deamination and subsequent conversion to a uracil.
After bisulfite conversion, the total amount of DNA was in-
creased by methylation specific amplification using a whole-
genome amplification process, which copies the converted
uracils to thymine bases. The DNA was then enzymatically
fragmented in an end-point fragmentation process.
Microarray processing and analysis of the Illumina Infinium
HumanMethylation450 BeadChip then proceeded at the Uni-
versity of Minnesota’s BioMedical Genomics Center. This
BeadChip covers over 485,000 individual sites with single
nucleotide resolution of cytosine nucleotide–phosphate–guanine
nucleotide (CpG) sites both inside and outside CpG islands
and greater than 90% of the content in common with the
HumanMethylation27 BeachChip. The HumanMethylation450
BeadChip offers comprehensive genome-wide coverage in-
cluding 99% of RefSeq genes with high quality by using
more than 600 negative controls. Bisulfite converted samples
were then hybridized to these BeadChips followed by washing
and staining per protocols prescribed by Illumina. The microar-
ray bead chips were then imaged using a HiScan SQ system.
The fluorescence data was subsequently analyzed using the
Methylation Module v1.9.0 of the GenomeStudio software
package v2011.1 (Illumina). All data were background cor-
rected and negative control normalized producing average beta
values. This average beta value represents the relative quantity
of methylation at an individual site ranging from 0 to 1 (unme-
thylated to completely methylated). Tests that produced dif-
ferent results from technical replicates of the three control
DNA samples at 60, 40, and 20 ng human DNA were iden-
tified as poor and removed from subsequent analyses. This
was accomplished by using differential methylation analysis
of replicate sample average beta and the loci with a jDiffScorej
.13, which is equivalent to p,.01 as determined by com-
paring each sample individually at 40 ng to the 20, 40, and
60 ng quantities. These suspect loci (N¼75,512) and those
tests with pvalues of ..01 (N¼4,612) were excluded (N¼
77,018, 15.9%). Beta values were analyzed using principle
component analysis in Partek Genomics Suite, Partek Inc.Re-
view of the data distribution identified eight samples as outli-
ers that were subsequently removed from further analysis.
Methylation analysis approach
Differential methylation analyses were conducted for infants of
depressed and nondepressed mothers. These analyses were per-
DNA methylation in infants of mothers with MDD 3
http://dx.doi.org/10.1017/S0954579416000912
Downloaded from http:/www.cambridge.org/core. University of Rochester, on 11 Oct 2016 at 19:55:30, subject to the Cambridge Core terms of use, available at http:/www.cambridge.org/core/terms.
formed after subtracting background noise and normalizing to
array controls using GenomeStudio, Methylation Module,
and the Illumina Custom Model. The resulting measure of
this calculation set is delta beta, which represents the amount
of change to the average beta at a site, or relative percentage
methylation change between defined groups. Positive delta
beta values indicate an elevation in relative methylation and a
negative value indicates a reduction. Because the data set in-
cludes both male and female infants, the X and Y chromosome
data were removed from subsequent analyses. To correct for
multiple testing, the significance threshold to determine differ-
ential methylation was set to 5.010–7, which is consistent with
prior research (i.e., Yang et al., 2013) and recommendations by
Raykan, Down, Balding, and Beck (2011). To investigate the
association of maternal depression with known disease bio-
markers, the delta beta values of differentially methylated loci
(p,5.010–7) were then analyzed using GeneGo MetaCore
Software (Thomas-Reuters, MetaCore Version 6.23).
Results
Differential methylation analysis
Using the 5.0 10–7 pvalue, 2,119 loci were found to be sig-
nificantly different between infants of depressed and nonde-
pressed mothers. The delta beta information was binned to
10% increments based on the expected amount of percent methy-
lation from the infants of nondepressed mother group, or
expected average beta. The results indicated a pattern of greater
methylation from 0% to 20% and less methylation from 70%
to 100%. The data are also heavily weighted to the
70%2100% end on the continuum (see Figure 1 for graphical
representation). Data were further classified at low methylation
(0%229%), medium methylation (30%–69%), and high
methylation (70%2100%). Table 2 illustrates that infants of de-
pressed mothers had greater methylation atlow methylation sites
(0%229%) compared to infants of nondepressed mothers. At
high levels of methylation (70%2100%) the infants of de-
pressed mothers were predominantly hypomethylated. The
mean difference in methylation between the infants of depressed
and infants of nondepressed mothers was 5.23% with a range of
1%–68% for the differentially methylated ( p,5.010–7 ).
Disease by biomarker analysis
Loci that evidenced differential methylation between infants
of depressed and infants of nondepressed mothers were up-
loaded into the GeneGo MetaCore to examine the association
of infants of maternal depression with known disease bio-
markers. A disease biomarker network analysis was con-
ducted to examine differences between infants of depressed
mothers and infants of nondepressed mothers in multiple dis-
ease components. Table 3 lists the number of network objects
associated with each disease biomarker network and the num-
ber of objects that were differentially methylated for mal-
treated and nonmaltreated groups. The significance values
for differential methylation rates are lower than the adjusted
false discovery rate pvalues, indicating significant de-
pressed/nondepressed group differences. The results indi-
cated significant cancer-related differences in biomarker net-
works such as prostatic neoplasms, ovarian and breast
neoplasms, and colonic neoplasms. Next, a disease by bio-
marker analysis was conducted to identify a broader range
of individual components of potential diseases. Significant
differences between infants of depressed and infants of non-
depressed mothers were found for mental disorders, immune
system diseases, respiratory tract diseases, central nervous
system diseases, neurodegenerative diseases, and cardiovas-
cular diseases (see Table 4). Finally, a process networks
analysis was conducted to determine differences in general
biological processes among infants of depressed and nonde-
pressed mothers. The results indicated significant differences
in process networks associated with neuronal development
and central nervous system functioning, cardiac develop-
ment, as well as others (see Table 5).
Discussion
To our knowledge, this is the first study to examine methylation
differences between infants of mothers with MDD and infants
Figure 1. (Color online) Differencein methylation of the infants of depressed
mothers compared to the infants of nondepressed mothers.
Table 2. Genome-wide methylation differences among
infants of depressed mothers compared to expected
methylation (infants of nondepressed mothers)
Expected
Methylation
Range
N
Depressed
Greater
N
Depressed
Less
Total Loci
Differentially
Methylated
0.00–0.29 232 29 260
0.30–0.69 144 135 279
0.70–1.00 51 1528 1579
Total 427 1692 2119
D. Cicchetti et al.4
http://dx.doi.org/10.1017/S0954579416000912
Downloaded from http:/www.cambridge.org/core. University of Rochester, on 11 Oct 2016 at 19:55:30, subject to the Cambridge Core terms of use, available at http:/www.cambridge.org/core/terms.
of well mothers in a low-income sample. Moreover, we ob-
tained DNA samples and tested for methylation in the infants
at approximately 1 year of age, very early in development.
Mothers in the depressed group met diagnostic criteria for cur-
rent MDD rather than elevated depressive symptoms alone.
We found that there were significant differences in methy-
lation between infants of mothers with MDD and infants of
well mothers across the epigenome. Infants of depressed
mothers tended to have higher levels of methylation at CpG
sites where infants of well mothers evinced low levels of
methylation, and lower levels of methylation at CpG sites where
infants of well mothers evidenced higher levels of methylation
(see Table 2 and Figure 1). Specifically, between 0% and 70%
methylation, the infants of mothers with MDD showed a gen-
eralized increase in methylation, whereas for loci with 70% to
100% methylation in the well mothers group, the infants of de-
pressed mothers had decreased methylation. This suggests that
there are genes that should be turned on that are turned off and
genes that should be turned off that are turned on.
The pattern of methylation differences was related to dif-
ferential physical and mental health risk for infants of
mothers with MDD and infants of well mothers. Infants of de-
pressed mothers evinced differential methylation in genes as-
sociated with disease biomarkers for mental disorders, as well
as a range of physical diseases, biomarker network effects on
different forms of cancer, and process network risks for neu-
ronal development, central nervous system functioning, car-
diac development, transcription and transduction signaling,
among others. Thus, current epigenetic differences observed
in infants of mothers with MDD suggest future liabilities for
future health outcomes.
In future research, further probing of the nature of epige-
netic transmission should be conducted. Subsequent research
will need to investigate the extent to which these methylation
differences are experienced based, involving the rearing ex-
periences with a depressed mother in the first year, or initiated
in utero (Braithwaite, Kundakovic, Ramchandani, Murphy, &
Champagne, 2015; Oberlander et al., 2008), as over 90% of
the mothers with MDD were depressed prior to the infant’s
birth. In addition, methylation differences may have been in-
herited epigenetically from the mothers with depression. Dif-
ferentiating the source of these methylation differences will be
important.
Longitudinal research would be valuable to investigate
epigenetic changes over time and determine how they are re-
lated to the development of physical and mental health out-
Table 3. MetaCore analysis of isease biomarker network differences between infants of depressed and infants
of nondepressed mothers
Networks pFDR-Adj. p
No. of Signif.
Diff. Network
Objects
Total
Network
Objects
Prostatic neoplasms_regulation of
progression through cell cycle 9.0E-03 2.4E-01 14 70
Ovarian Nneoplasms (core network 2) 9.1E-03 2.4E-01 18 99
Breast neoplasm_transcription 9.8E-03 2.4E-01 11 50
Prostatic neoplasms_cell proliferation 1.4E-02 2.4E-01 9 39
Breast neoplasm_transcription regulation 1.4E-02 2.4E-01 24 150
Breast neoplasm_cell-cell signaling 2.1E-02 3.0E-01 17 100
Colonic neoplasms_cell cycle 3.6E-02 4.0E-01 11 60
Breast neoplasm_p53 3.7E-02 4.0E-01 10 53
Note: FDR, False discovery rate.
Table 4. MetaCore analysis of diseases by biomarker differences among infants
of depressed and infants of nondepressed mothers
Diseases pFDR-Adj. p
No. of Signif.
Diff. Network
Objects
Total
Network
Objects
Mental disorders 3.6E-14 2.1E-11 195 1610
Immune system 1.1E-13 4.2E-11 574 6257
Respiratory tract 8.1E-11 4.4E-09 1401 18398
Central nervous system 1.1E-10 5.5E-09 305 3060
Neurodegenerative 4.1E-07 6.7E-06 206 2087
Cardovascular 5.0E-07 8.2E-06 324 3565
Note: FDR, False discovery rate.
DNA methylation in infants of mothers with MDD 5
http://dx.doi.org/10.1017/S0954579416000912
Downloaded from http:/www.cambridge.org/core. University of Rochester, on 11 Oct 2016 at 19:55:30, subject to the Cambridge Core terms of use, available at http:/www.cambridge.org/core/terms.
comes. It will be important to investigate the potential for ad-
ditional methylation variation to occur as these infants de-
velop, particularly if mothers continue to be depressed over
time. This will contribute to developing a better understand-
ing of the role of epigenetics in the risk associated with hav-
ing a depressed mother. Linking methylation differences to
the cascade of developmental vulnerabilities observed in
the offspring of depressed mothers, (e.g., emotion regulation,
attachment organization, self development, and neurocogni-
tive abilities) will be important. Longitudinal mediational
analysis will be useful in establishing whether methylation
may be portrayed as a veridical mechanism of the risk of ma-
ternal depression on various developmental processes, and
subsequent mental and physical health outcomes.
If DNA methylation changes are driving human disease
and health problems, it may be possible to reverse (demethyl-
ate) maladaptive DNA methylation marks with pharmacolog-
ical or behavioral interventions (Szyf & Bick, 2013). As the
pathways that lead from specific to general experiences to
phenotypic DNA methylation changes become increasingly
understood, this should enable prevention scientists to design
interventions to decrease disease and increase health and
wellness (Szfy & Bick, 2013). Through early intervention
with depressed mothers and their young children, research
will be able to ascertain whether the observed patterns of
methylation may be altered, whether normalization of
methylation relative to comparisons may occur, and the role
of methylation in adaptive intervention outcomes.
Table 5. MetaCore analysis of process network differences among infants of depressed and infants of nondepressed
mothers
Networks pFDR-Adj. p
No. of Signif.
Diff. Network
Objects
Total
Network
Objects
Neuronal development
Development_neurogenesis_synaptogenesis 2.6E-05 4.1E-03 33 180
Development_neurogenesis_axonal guidance 2.7E-03 2.1E-01 33 230
Central nervous system functioning
Development_neuromuscular junction 2.9E-02 2.6E-01 20 147
Neurophysiological process_GABAergic
neurotransmission 2.9E-02 2.6E-01 19 138
Neurophysiological process_Transmission of nerve
impulse 4.5E-02 2.8E-01 26 212
Cardiac development
Cardiac development_FGF_ErbB signaling 2.1E-02 2.6E-01 18 124
Cardiac development_role of NADPH oxidase and
ROS 2.2E-02 2.6E-01 19 134
Cardiac development_BMP_TGF_beta_signaling 2.4E-02 2.6E-01 17 117
General transcription/transduction
Signal transduction_NOTCH signaling 7.3E-03 2.1E-01 32 236
Signal transduction_ESR1-membrane pathway 1.1E-02 2.1E-01 15 91
Signal transduction_ERBB-family signaling 1.2E-02 2.1E-01 13 75
Signal transduction_ESR1-nuclear pathway 1.2E-02 2.1E-01 29 216
Signal transduction_WNT signaling 1.9E-02 2.6E-01 24 177
Transcription_mRNA processing 3.6E-02 2.8E-01 21 160
Signal transduction_TGF-beta, GDF and activin
signaling 4.4E-02 2.8E-01 20 154
Other
Cell adhesion_synaptic contact 4.6E-03 2.1E-01 27 184
Cell adhesion_cell junctions 6.5E-03 2.1E-01 24 162
Cytoskeleton_regulation of cytoskeleton
rearrangement 8.2E-03 2.1E-01 26 183
Reproduction_gonadotropin regulation 2.3E-02 2.6E-01 26 199
Transport_calcium transport 2.6E-02 2.6E-01 25 192
Apoptosis_anti-apoptosis mediated by external
signals via NF-kB 3.0E-02 2.6E-01 16 111
Reproduction_FSH-beta signaling pathway 3.6E-02 2.8E-01 21 160
Cell adhesion_cadherins 3.9E-02 2.8E-01 23 180
Cytoskeleton_cytoplasmic microtubules 4.0E-02 2.8E-01 16 115
Cell cycle_G0-G1 4.1E-02 2.8E-01 11 71
Reproduction_Male sex differentiation 4.8E-02 2.9E-01 29 243
Cell adhesion_Attractive and repulsive receptors 4.9E-02 2.9E-01 22 175
Cell adhesion_Amyloid proteins 5.1E-02 2.9E-01 24 195
Note: FDR, False discovery rate.
D. Cicchetti et al.6
http://dx.doi.org/10.1017/S0954579416000912
Downloaded from http:/www.cambridge.org/core. University of Rochester, on 11 Oct 2016 at 19:55:30, subject to the Cambridge Core terms of use, available at http:/www.cambridge.org/core/terms.
References
American Psychiatric Association. (1994). Diagnostic and statistical manual
of mental disorders (4th ed.). Washington, DC: Author.
Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Manual for the Beck De-
pression Inventory—II. San Antonio, TX: Psychological Corporation.
Braithwaite, E. C., Kundakovic, M., Ramchandani, P. G., Murphy, S. E., &
Champagne, F. A. (2015). Maternal prenatal depressive symptoms predict
infant NR3C1 1F and BDNF IV DNA methylation. Epigenetics,10,
408–417.
Cicchetti, D., & Aber, J. L. (1986). Early precursors to later depression: An
organizational perspective. In L. Lipsitt & C. Rovee-Collier (Eds.), Ad-
vances in infancy (Vol. 4, pp. 87–137). Norwood, NJ: Ablex.
Cicchetti, D., Rogosch, F. A., Toth, S. L., & Spagnola, M. (1997). Affect,
cognition, and the emergence of self-knowledge in the toddler offspring
of depressed mothers. Journal of Experimental Child Psychology,67,
338–362.
Cicchetti, D., & Schneider-Rosen, K. (1986). An organizational approach to
childhood depression. In M. Rutter, C. Izard, & P. Read (Eds.), Depres-
sion in young people: Clinical and developmental perspectives (pp. 71–
134). New York: Guilford Press.
Cicchetti, D., & Toth, S. L. (1995). Developmental psychopathology and dis-
orders of affect. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psy-
chopathology: Risk, disorder, and adaptation (Vol. 2, pp. 369–420).
New York: Wiley.
Cicchetti, D., & Toth, S. L. (1998). The development of depression in chil-
dren and adolescents. American Psychologist,53, 221–241.
Cole, P. M., Luby, J., & Sullivan, M. W. (2008). Emotions and the develop-
ment of childhood depression: Bridging the gap. Child Development Per-
spectives,2, 141–148.
Cummings, E. M., & Cicchetti, D. (1990). Toward a transactional model
of relations between attachment and depression. In M. T. Greenberg,
D. Cicchetti, & E. M. Cummings (Eds.), Attachment in the preschool
years, (pp. 339–372). Chicago: University of Chicago Press.
Davidson, R. J., & Fox, N. A. (1982). Asymmetrical brain activity discrimi-
nates between positive versus affective stimuli in human infants. Science,
218, 1235–1237.
Dozois, D. J., Dobson, K. S., & Ahnberg, J. L. (1998). A psychometric evalu-
ation of the Beck Depression Inventory—II. Psychological Assessment,
10, 83–89.
Field, T., & Diego, M. (2008). Maternal depression effects of infant frontal
EEG asymmetry. International Journal of Neuroscience,118, 1081–
1108.
Goodman, S. H., & Gotlib, I. H. (1999). Risk for psychopathology in the chil-
dren of depressed mothers: A developmental model for understanding
mechanisms of transmission. Psychological Review,106, 458–490.
Oberlander, T. F., Weinberg, J., Papsdorf, M., Grunau, R., Misri, S., & Dev-
lin, A. M. (2008). Prenatal exposure to maternal depression, neonatal
methylation of human glucocorticoid receptor gene (NR3C1) and infant
cortisol stress responses. Epigenetics,3, 97–106.
Radke-Yarrow, M., Cummings, E. M., Kuczynski, L., & Chapman, M. (1985).
Patterns of attachment in two- and three-year-olds in normal families and
families with parental depression. Child Development,56, 884–893.
Radloff, L. (1977). The CES-D Scale: A self-report depression scale for
research in the general population. Applied Psychological Measurement,
1, 385–401.
Rakyan, V. K., Down, T. A., Balding, D. J., & Beck, S. (2011). Epigenome-
wide association studies for common human diseases. Nature Reviews.
Genetics,12, 529–541.
Robins, L., Cottler, L., Bucholz, K., & Compton, W. (1995). Diagnostic In-
terview Schedule for DSM-IV. St. Louis, MO: Washington University.
Robins, L., Helzer, J., Croughan, J., & Ratcliff, K. (1981). The NIMH Diag-
nostic Interview Schedule: Its history, characteristics, and validity. Ar-
chives of General Psychiatry,38, 381–389.
Robins, L. W., Helzer, J. E., Ratcliff, K. S., & Seyfried, W. (1982). Validity
of the Diagnostic Interview Schedule, Version II: DSM-III diagnoses.
Psychological Medicine,12, 855–865.
Storch, E. A., Roberti, J. W., & Roth, D. A. (2004). Factor structure, concur-
rent validity, and internal consistency of the Beck Depression Inven-
tory—Second Edition in a sample of college students. Depression and
Anxiety,19, 187–189.
Szyf, M., & Bick, J. (2013). DNA methylation: A mechanism for embedding
early life experiences in the genome. Child Development,84, 49–57.
Toth, S. L., Rogosch, F. A., Manly, J. T., & Cicchetti, D. (2006). The efficacy
of toddler–parent psychotherapy to reorganize attachment in the young
offspring of mothers with major depressive disorder. Journal of Consult-
ing & Clinical Psychology,74, 1006–1016.
Yang, B. Z. Y., Zhang, H., Ge, W., Weder, N., Douglas-Palumberi, H., Per-
epletchikova, F., et al. (2013). Child abuse and epigenetic mechanisms of
disease risk. American Journal of Preventive Medicine,44, 101–107.
DNA methylation in infants of mothers with MDD 7
http://dx.doi.org/10.1017/S0954579416000912
Downloaded from http:/www.cambridge.org/core. University of Rochester, on 11 Oct 2016 at 19:55:30, subject to the Cambridge Core terms of use, available at http:/www.cambridge.org/core/terms.
