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Maternal sensitivity and child internalizing and externalizing behavior: a mediating role for glucocorticoid receptor gene (NR3C1) methylation?

Published online by Cambridge University Press:  10 March 2023

Nicole Creasey*
Affiliation:
Preventive Youth Care, Research Institute of Child Development and Education, University of Amsterdam, the Netherlands
Roseriet Beijers
Affiliation:
Department of Social Development, Behavioral Science Institute, Radboud University, the Netherlands, and Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, the Netherlands
Kieran J. O’Donnell
Affiliation:
Ludmer Centre for Neuroinformatics and Mental Health, Douglas Hospital Research Centre, McGill University, QC, Canada; Canadian Institute for Advanced Research, Child and Brain Development Program, Canada; and Yale Child Study Center & Department of Obstetrics, Gynecology and Reproductive Sciences, Yale School of Medicine, USA
Carolina de Weerth
Affiliation:
Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, the Netherlands
Marieke S. Tollenaar
Affiliation:
Institute of Psychology and Leiden Institute for Brain and Cognition, Leiden University, the Netherlands
*
Corresponding author: Nicole Creasey, email: [email protected]
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Abstract

The early caregiving environment can have lasting effects on child mental health. Animal models suggest that glucocorticoid receptor gene (NR3C1) DNA methylation plays a mediating role in linking more responsive caregiving to improved behavioral outcomes by its impact on the stress regulatory system. In this longitudinal study, we examined whether children’s NR3C1 methylation levels mediate an effect of maternal sensitivity in infancy on levels of child internalizing and externalizing behavior in a community sample. Maternal sensitivity of 145 mothers was rated at infant age 5 weeks, 12 months, and 30 months by observing mother–infant interactions. Buccal DNA methylation was assessed in the same children at age 6 years and maternal-reported internalizing and externalizing behavior was assessed at age 6 and 10 years. Higher sensitivity at age 5 weeks significantly predicted lower DNA methylation levels at two NR3C1 CpG loci, although methylation levels at these loci did not mediate an effect of maternal sensitivity on levels of child internalizing and externalizing behavior. Overall, the study provides evidence that maternal sensitivity in early infancy is associated with DNA methylation levels at loci involved in stress regulation, but the significance of this finding for child mental health remains unclear.

Type
Regular Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press

Introduction

Mental health problems are one of the main causes of disability worldwide and typically emerge before adulthood (Global Burden of Disease Study 2013 Collaborators 2015; Solmi et al., Reference Solmi, Radua, Olivola, Croce, Soardo, Salazar de Pablo, Il Shin, Kirkbride, Jones, Kim, Kim, Carvalho, Seeman, Correll and Fusar-Poli2021; Whiteford et al., Reference Whiteford, Degenhardt, Rehm, Baxter, Ferrari, Erskine, Charlson, Norman, Flaxman, Johns, Burstein, Murray and Vos2013). As such, it is crucial that we improve our understanding of early life factors that modify children’s risk of developing mental health problems. One such factor is maternal sensitivity – the extent to which a mother is able to appropriately identify and respond to her infant’s physical and emotional needs and signals (Ainsworth et al., Reference Ainsworth, Bell, Stayton and Richards1974). Less sensitive caregiving during infancy is associated with higher levels of childhood internalizing behavior (i.e., anxiety, depression, and withdrawal; Kok et al., Reference Kok, Linting, Bakermans-Kranenburg, van Ijzendoorn, Jaddoe, Hofman, Verhulst and Tiemeier2013) and externalizing behavior (i.e., aggression, defiance, and impulsivity; Wang et al., Reference Wang, Christ, Mills-Koonce, Garrett-Peters and Cox2013; van der Voort et al., Reference van der Voort, Linting, Juffer, Bakermans-Kranenburg, Schoenmaker and van IJzendoorn2014). Child internalizing and externalizing behaviors are, in turn, major predictors of later life psychopathology (Mathyssek et al., Reference Mathyssek, Olino, Verhulst and van Oort2012; Reef et al., Reference Reef, Diamantopoulou, van Meurs, Verhulst and van der Ende2009). However, the pathways by which maternal sensitivity influences children’s levels of internalizing and externalizing behavior are not yet fully understood and warrant further investigation in order to inform preventive interventions (Deans, Reference Deans2020; Provenzi et al., Reference Provenzi, Brambilla, Scotto di Minico, Montirosso and Borgatti2019).

Maternal sensitivity may influence children’s levels of internalizing and externalizing behavior through its effects on the developing stress regulatory system in early infancy. Specifically, sensitive caregiving provides infants with the external support they need to cope with emotional and physiological stress, and thus a model for infants to learn how to independently regulate stress (Bell & Ainsworth, Reference Bell and Ainsworth1972; Bowlby, Reference Bowlby1980; Gianino & Tronick, Reference Gianino, Tronick, Field, McCabe and Schneiderman1988). On the other hand, insensitive caregiving – characterized by absent, noncontingent and/or intrusive responses to an infant’s signals and behaviors – not only fails to provide infants with external regulation but may act as a source of stress in itself (Smeekens et al., Reference Smeekens, Marianne Riksen-Walraven and van Bakel2007; Tronick, Reference Tronick1989). As such, infants that receive insensitive caregiving may be at risk for long-term stress dysregulation (Laurent et al., Reference Laurent, Harold, Leve, Shelton and Van Goozen2016), which could contribute to higher levels of internalizing behavior and externalizing behavior (Ruttle et al., Reference Ruttle, Shirtcliff, Serbin, Ben-Dat Fisher, Stack and Schwartzman2011). In this way, insensitive caregiving may act as a risk factor for later life psychopathology, while sensitive caregiving may act as a protective factor by ensuring that children are able to appropriately respond to the stressors that they will inevitably face in their daily environment. A potential biological pathway for this association is through epigenetic processes such as DNA methylation, a relatively stable modification to nuclear DNA that occurs most commonly at cytosine-guanine dinucleotide (CpG) sites and can functionally regulate gene expression (Aristizabal et al., Reference Aristizabal, Anreiter, Halldorsdottir, Odgers, McDade, Goldenberg, Mostafavi, Kobor, Binder, Sokolowski and O'Donnell2020). Epigenetic changes in response to sensitive caregiving may alter the function of the hypothalamic pituitary adrenal axis to enhance recovery from stress and reduce stress-related behaviors such as internalizing and externalizing behaviors (Berretta et al., Reference Berretta, Guida, Forni and Provenzi2021). The current study tested the feasibility of this pathway in children by examining whether differential DNA methylation levels at the glucocorticoid receptor (GR) gene (NR3C1), a key regulator of the HPA axis, mediate an association between maternal sensitivity in infancy and later levels of internalizing and externalizing behavior.

Research in rodents has implicated DNA methylation changes at NR3C1 as a mediator of the effects of maternal responsivity on levels of stress-related behaviors, such as internalizing-like and externalizing-like behaviors. More sensitive caregiving behavior by rat dams (i.e., licking, grooming and arch-backed nursing) during the first week of life has been found to lead to long-term hypomethylation at exon 17 of the NR3C1 promotor in the hippocampal tissues of their offspring (Weaver et al., Reference Weaver, Cervoni, Champagne, D’Alessio, Sharma, Seckl, Dymov, Szyf and Meaney2004). In turn, NR3C1 promotor hypomethylation is associated with increased hippocampal GR expression, and subsequently more modest HPA axis responses and less defensive, stress-related behaviors in adult rats (Weaver et al., Reference Weaver, Cervoni, Champagne, D’Alessio, Sharma, Seckl, Dymov, Szyf and Meaney2004, Reference Weaver, Champagne, Brown, Dymov, Sharma, Meaney and Szyf2005, Reference Weaver, Meaney and Szyf2006; van Hasselt et al., Reference van Hasselt, Cornelisse, Yuan Zhang, Meaney, Velzing, Krugers and Joëls2012). Given that higher maternal sensitivity has also been found to predict better HPA axis regulation in human infants (Albers et al., Reference Albers, Marianne Riksen-Walraven, Sweep and Weerth2008; Blair et al., Reference Blair, Granger, Willoughby and Kivlighan2006), it is possible that a similar epigenetic pathway may link more sensitive caregiving with lower levels of child internalizing and externalizing behavior in humans.

To date, human studies have predominately focused on the effects of severely disrupted caregiving (i.e., child maltreatment) on DNA methylation and provide some preliminary evidence that NR3C1 hypermethylation may link an adverse caregiving environment to later psychopathology (for a review see Wadji et al., Reference Wadji, Tandon, Ketcha Wanda, Wicky, Dentz, Hasler, Morina and Martin-Soelch2021). However, relatively little attention has been given to typical variation in caregiving within community samples. To our knowledge, only two human studies have investigated the link between maternal sensitivity and NR3C1 methylation, while no studies have considered the pathway from maternal sensitivity through NR3C1 to subsequent stress-related behaviors. In one of the aforementioned studies, maternal insensitivity was associated cross-sectionally with higher methylation at the NR3C1 1f region in buccal-derived DNA of 5-month-old infants, although results differed based on infant sex and maternal depressive symptoms (Conradt et al., Reference Conradt, Dylan Guerin, Marsit, Hawes and Tronick2016, Reference Conradt, Ostlund, Guerin, Armstrong, Marsit, Tronick, LaGasse and Lester2019). Notably, increased methylation at the 1f region – orthologous to the exon 17 in rodents – has been repeatedly linked to mental health problems in adult populations (for a review see Watkeys et al., Reference Watkeys, Kremerskothen, Quidé, Fullerton and Green2018). In contrast, no association was found between maternal sensitivity at age 3–4 years and NR3C1 methylation levels in whole blood DNA at age 6 in a prospective, longitudinal study (Dall’Aglio et al., Reference Dall’ Aglio, Rijlaarsdam, Mulder, Neumann, Felix, Kok, Bakermans-Kranenburg, van Ijzendoorn, Tiemeier and Cecil2020). The difference in findings between studies could be related to differences in methodology (e.g., rating scales for maternal sensitivity and methylation analysis method), but could also be related to a difference in the developmental timing of the measurement of maternal sensitivity (i.e., 5 months vs. 3–4 years). Both rodent and human studies support the likelihood that there is a sensitive period in early infancy (i.e., before three years of age) during which the caregiving environment may have a more significant impact on children’s DNA methylation (Curley & Champagne, Reference Curley and Champagne2016; Dunn et al., Reference Dunn, Soare, Zhu, Simpkin, Suderman, Klengel, Smith, Ressler and Relton2019). However, the timing of exposure to sensitive versus insensitive caregiving in relation to NR3C1 methylation has not been considered in prior human studies. Moreover, it remains unclear from existing studies whether associations between maternal sensitivity and NR3C1 methylation in early life persist into middle childhood and whether they mediate an effect of maternal sensitivity on children’s behaviors.

Prior research has established associations of NR3C1 methylation with child internalizing and externalizing behavior. A number of cross-sectional studies have demonstrated that higher parent-reported internalizing behavior associates with higher methylation levels at the NR3C1 1f exon in children aged 3–16 years (Dadds et al., Reference Dadds, Moul, Hawes, Mendoza Diaz and Brennan2015; Gardini et al., Reference Gardini, Schaub, Neuhauser, Ramseier, Villiger, Ehlert, Lanfranchi and Turecki2022; Parade et al., Reference Parade, Ridout, Seifer, Armstrong, Marsit, McWilliams and Tyrka2016), and at the NR3C1 1d exon in children aged 3–5 years (Parade et al., Reference Parade, Ridout, Seifer, Armstrong, Marsit, McWilliams and Tyrka2016). Furthermore, in a longitudinal study, higher NR3C1 promoter methylation in adolescents aged 15–16 years predicted higher internalizing symptoms three years later (van der Knaap et al., Reference van der Knaap, van Oort, Verhulst, Oldehinkel and Riese2015). Evidence for associations of NR3C1 methylation with externalizing behavior is less consistent. In a study of children aged 4–16 years, higher parent-reported externalizing behavior was cross-sectionally associated with higher salivary NR3C1 methylation levels at the 1f exon (Dadds et al., Reference Dadds, Moul, Hawes, Mendoza Diaz and Brennan2015). Likewise, positive associations were found between methylation levels at the 1f exon and parent-reported oppositional defiant problems in 3-year-olds (Gardini et al., Reference Gardini, Schaub, Neuhauser, Ramseier, Villiger, Ehlert, Lanfranchi and Turecki2022). In contrast, a cross-sectional study of children aged 3–5 years found no significant associations of parent-reported externalizing behavior with NR3C1 promoter methylation (Parade et al., Reference Parade, Ridout, Seifer, Armstrong, Marsit, McWilliams and Tyrka2016), whereas a longitudinal study reported that lifetime externalizing disorder – based on parent reports from ages 3 to 19 years – predicted lower NR3C1 1f exon methylation at age 19 years (Heinrich et al., Reference Heinrich, Buchmann, Zohsel, Dukal, Frank, Treutlein, Nieratschker, Witt, Brandeis, Schmidt, Esser, Banaschewski, Laucht and Rietschel2015). Together these findings lend some preliminary support for a pathway from NR3C1 methylation to child behavior. However, there is a paucity of longitudinal studies during childhood that test said pathway. Furthermore, most studies to date have been limited in scope to the 1f exon of the NR3C1 promoter and have relied solely on parental reports of child internalizing and externalizing behavior.

To address the gaps in prior research, the current study investigated whether NR3C1 methylation mediates an effect of early maternal sensitivity on levels of internalizing and externalizing behaviors in later childhood. First, we examined whether maternal sensitivity at three time points in early infancy (5 weeks, 12 months, and 30 months) predicted children’s NR3C1 methylation levels at age six. Second, we examined whether children’s NR3C1 methylation levels at age 6 mediated an association of maternal sensitivity with children’s levels of internalizing and externalizing behavior at ages 6 and 10 years. Based on earlier rodent models, we hypothesized that 1) more sensitive caregiving would be associated with lower levels of NR3C1 methylation at age 6, and 2) CpG loci with lower levels of NR3C1 methylation at age 6 would partially mediate a negative association of sensitive caregiving with children’s levels of internalizing and externalizing behavior at ages 6 and 10 years. For the sake of completeness, we also explored whether there were associations between NR3C1 methylation levels at age 6 on all 25 assessed CpG loci and child internalizing and externalizing behaviors at age 6 and 10 years.

Methods

Participant characteristics

Participants were mother–infant dyads recruited as part of an ongoing prospective study on the role of early environmental factors in infant and child development (BIBO project; Basal Influences on Child Development; see Beijers et al., Reference Beijers, Jansen, Riksen-Walraven and de Weerth2010, Reference Beijers, Jansen, Riksen-Walraven and de Weerth2011). Mothers were recruited during pregnancy in collaboration with midwife clinics located in or close to the cities of Nijmegen and Arnhem, The Netherlands. The project was approved by the Radboud University ethical committee of the social science faculty (ECG300107, SW2017-1303-49) and written informed consent was obtained from each participant on enrollment. The original maternal study sample reflected a healthy, nonclinical population of 193 mothers aged 21–42 years with the following inclusion criteria: a singleton uncomplicated pregnancy, no drug use, and no current physical or mental health problems. All infants had an uncomplicated birth and were born healthy with a 5-min APGAR score ≥7. From the original study sample, 148 children provided buccal epithelial cells at age six for genetic and DNA methylation analyses with their mother’s informed consent. All parents in the current study sample described their child’s ethnic background as Caucasian. Chi-square and Mann–Whitney U tests revealed no significant differences between dyads with and without child buccal samples in terms of child sex, child birthweight, maternal age at childbirth, maternal sensitivity, and child behavioral outcomes.

Design

Maternal caregiving was observed at three time points: infant age 5 weeks (at home), 12 months (in the laboratory), and 30 months (at home). Buccal cell samples were collected for (epi)genetic analysis from the same children using buccal swabs when they were 6 years old. Mothers reported on the internalizing and externalizing behavior of their child via questionnaire when the same children were 6 years old and 10 years old. Children also reported on their own internalizing and externalizing behavior via questionnaire at age 10 years.

Measures

Maternal sensitivity

When the infants were five weeks old, mother–infant dyads were visited at home and mothers were videotaped while bathing their infant as they would normally (as described by Jansen et al., Reference Jansen, Beijers, Riksen-Walraven and de Weerth2010, and Beijers et al., Reference Beijers, Hartman, Shalev, Hastings, Mattern, de Weerth and Belsky2020). Two trained independent coders rated videotapes of the whole bathing routine for sensitivity – that is, the extent to which the mother timeously and adequately responds to the infant’s needs and signals – on a 9-point rating scale using the Ainsworth Maternal Sensitivity Scale (Ainsworth et al., Reference Ainsworth, Blehar, Waters and Wall1978). Interrater reliability was excellent (Cohen’s kappa = .90). Higher scores represent mothers who displayed more appropriate responses to their child’s needs and signals, that is, higher maternal sensitivity. Of the mothers, 24.3% received a rating of three or lower, reflecting low to inadequate care (Helmerhorst et al., Reference Helmerhorst, Riksen-Walraven, Fukkink, Tavecchio and Gevers Deynoot-Schaub2017).

When the infants were 12 and 30 months old, mother–infant interactions were videotaped during a joint semi-structured play session (as described by Beijers et al., Reference Beijers, Hartman, Shalev, Hastings, Mattern, de Weerth and Belsky2020). Specifically, at infant age 12 months, mothers were asked to play with their infants using four toys (e.g., puzzle, books, and hand puppets) for 3 minutes each during a lab visit. At infant age 30 months, mothers were asked to play with their children using three toys (e.g., puzzle and blocks) for 4 minutes each during a home visit. The videotapes were rated by two independent observers using the Erickson scales (Erickson et al., Reference Erickson, Sroufe and Egeland1985). For each mother–infant dyad a composite score for maternal sensitivity was computed by taking the mean of the seven-point subscales for supportive presence and respect for autonomy (Kok et al., Reference Kok, Linting, Bakermans-Kranenburg, van Ijzendoorn, Jaddoe, Hofman, Verhulst and Tiemeier2013). Supportive presence refers to the extent a mother shows positive regard and emotional support to their infant, while respect for autonomy describes how far the mother refrains from interfering with the infant’s desires, interests, or behavior during the task. The two measures were highly and positively correlated at age 12 months (r = .62, p < .001), and moderately and positively correlated at age 30 months (r = .44, p < .001). Interrater reliability was excellent for supportive presence at 12 months (intraclass coefficient [IC] = .95) and 30 months (IC = .91), and moderate for respect for autonomy at 12 months (IC = .70) and 30 months (IC = .70). Higher composite scores represent higher maternal sensitivity. Of the mothers, 22.9% received averaged ratings of three or lower when their infants were 12 months old, reflecting low to inadequate care, while all mothers scored above three when their infants were 30 months old, reflecting at least adequate care (Helmerhorst et al., Reference Helmerhorst, Riksen-Walraven, Fukkink, Tavecchio and Gevers Deynoot-Schaub2017).

Internalizing and externalizing behavior

Child internalizing and externalizing behaviors were measured by maternal report at age six using the Dutch-version of the Child Behavior Checklist for ages 4–18 (CBCL/4-18; Achenbach, Reference Achenbach2007). The CBCL/4-18 has good reliability in Dutch samples and is predictive of adult mental problems (Dekker et al., Reference Dekker, Koot, van der Ende and Verhulst2002; Roza et al., Reference Roza, Hofstra, Van Der Ende and Verhulst2003). Items were rated from zero (not true as far as you know) to two (very true or often true), and included items such as, “Unhappy, sad, or depressed”. Ratings were used to form two broad-band scales: internalizing (anxiety-depression, somatic complaints, and withdrawal subscales) and externalizing (delinquent and aggressive subscales). Continuous raw scores, ranging 0–66 for both internalizing and externalizing, were used for each broad-band scale, with higher scores reflecting a higher frequency of child internalizing or externalizing behaviors.

Child internalizing and externalizing behaviors were also measured at age 10 years by child self-report with the Strengths and Difficulties questionnaire (SDQ; Mieloo et al., Reference Mieloo, Bevaart, Donker, van Oort, Raat and Jansen2014), to confirm if study outcomes were consistent across informants and symptom checklists. An externalizing score ranging 0–20 was formed from the sum of the conduct and hyperactivity subscales, while an internalizing score ranging 0–20 was formed from the sum of the emotional and peer problems subscale (Goodman & Goodman, Reference Goodman and Goodman2009).

NR3C1 DNA methylation

Genomic DNA was extracted from buccal epithelial cells with the QIAamp DNA Mini Kit (Qiagen, Germany) and quantified using a Nanodrop 2000 spectrometer (Thermo Fisher Scientific). The Zymo EZ DNA methylation kit (Zymo Research, Irvine, CA, USA) was then used to bisulfite convert 750 ng of gDNA, before genome-wide DNA methylation was described using the Infinium EPIC array (850k array; Illumina, San Diego CA, USA) in accordance with manufacturer’s guidelines. Preprocessing was performed with the meffil package in R (Min et al., Reference Min, Hemani, Davey Smith, Relton and Suderman2018). Probes failed quality control if for more than 10% of the samples they had either: a detection p-value >.01, and/or a bead count less than three. Moreover, samples were removed during quality control if either: the reported sex did not match the methylation-predicted sex, more than 10% of the sample’s probes had a detection p-value >.01, and/or more than 10% of sample’s probes had a bead count less than three. Three samples failed quality control leaving a study sample of 145 children for the main analyses. Additionally, functional normalization (FN; Fortin et al., Reference Fortin, Labbe, Lemire, Zanke, Hudson, Fertig, Greenwood and Hansen2014) was used to reduce non-biological differences between probes. Methylation was estimated based on the ratio of methylation signal to overall signal at each CpG and expressed as β-values ranging from 0 to 1. For our analyses, we extracted values for 25 CpG loci located within the CpG island in the 5’ untranslated region of the NR3C1 gene (GRCh37/hg19 chr5:142,782,071 to chr5:142,785,071; Palma-Gudiel et al., Reference Palma-Gudiel, Córdova-Palomera, Leza and Fañanás2015). Buccal epithelial cell content of the samples was estimated using the approach described by Smith and colleagues (Smith et al., Reference Smith, Kilaru, Klengel, Mercer, Bradley, Conneely, Ressler and Binder2015) and included as a covariate in the main analyses to adjust for cell heterogeneity (Ong et al., Reference Ong, Lin and Holbrook2014).

Genetic covariates

The same buccal samples were genotyped using the Infinium Global Screening Array (Illumina, Inc.). During quality control, two participants were excluded due to missing single nucleotide polymorphism (SNP) rates higher than 5%. A principal component analysis-based approach was used to account for population stratification, which can confound the results of methylation analysis (Barfield et al., Reference Barfield, Almli, Kilaru, Smith, Mercer, Duncan, Klengel, Mehta, Binder, Epstein, Ressler and Conneely2014). The first two genetic principal components (PC1 and PC2), which best described the population structure of the sample, were included as covariates in the main analyses.

Maternal mental health

Mothers’ scores on the State-Trait Anxiety Inventory (STAI; Spielberger et al., Reference Spielberger, Gorsuch, Lushene, Vagg and Jacobs1983) and Edinburgh Postnatal Depression Scale (EPDS; Pop et al., Reference Pop, Komproe and van Son1992) at 37 weeks gestational age, and at infant ages 3 months, 12 months, and 30 months, were used to control for maternal anxiety and depression in post hoc sensitivity analyses given potential confounding effects of maternal mental health on associations of maternal sensitivity with NR3C1 methylation and child behavior.

Data analysis

Analyses were performed in IBM SPSS version 24 and an alpha level of 0.05 was used to assess statistical significance unless otherwise specified. To handle outliers and overcome violation of normality, child internalizing and externalizing scores were log-transformed during data preparation; as CBCL scores range from zero and log0 is undefined, we added a value of one to all scores before the log transformation, that is, transformed score = log (original score + 1). The missing data, which are described in Table 1, were missing completely at random (Little’s test: χ2(214) = 219.93, p = .376) and thus handled using listwise deletion. Buccal cell count, genetic PC1 and PC2, child sex, child birthweight and maternal age at child birth (as a proxy for socioeconomic status) were selected a priori as covariates based on previous research and included in all statistical models (Barfield et al., Reference Barfield, Almli, Kilaru, Smith, Mercer, Duncan, Klengel, Mehta, Binder, Epstein, Ressler and Conneely2014; Liu et al., Reference Liu, Morgan, Hutchison and Calhoun2010; McDade et al., Reference McDade, Ryan, Jones, Hoke, Borja, Miller, Kuzawa and Kobor2019; Mulligan et al., Reference Mulligan, D’Errico, Stees and Hughes2012; Ong et al., Reference Ong, Lin and Holbrook2014; Yousefi et al., Reference Yousefi, Huen, Davé, Barcellos, Eskenazi and Holland2015). In the preliminary analysis, Pearson’s and biserial-point correlations were used to test associations between study variables (i.e., maternal sensitivity at three time points, internalizing and externalizing behavior at two time points, methylation at 25 CpG loci, and the preselected covariates).

Table 1. Descriptive statistics

Note. CBCL = Child Behavior Checklist.

In the first step of the main analyses, for each of the 25 CpG loci, a multiple regression analysis was performed to test maternal sensitivity scores at 5 weeks, 12 months, and 30 months as predictors of methylation levels. Scores for maternal sensitivity at each time point were included as separate predictors within each model, thus allowing us to test the individual effect of maternal sensitivity at each time point on children’s NR3C1 methylation. Multiple regression is a suitable method for testing the association of repeatedly measured predictors on an outcome variable when the predictors are not highly correlated, that is, when statistical assumptions are not violated due to multicollinearity, and when data are missing completely at random (Ha et al., Reference Ha, Mabuchi, Sigurdson, Freedman, Linet, Doody and Hauptmann2007; Lubin et al., Reference Lubin, Tomásek, Edling, Hornung, Howe, Kunz, Kusiak, Morrison, Radford, Samet, Tirmarche, Woodward and Yao1997; Sánchez et al., Reference Sánchez, Hu, Litman and Téllez-rojo2011). In our data, maternal sensitivity scores were not highly correlated between time points at the whole sample level (see Table 1 for Pearson’s correlation coefficients) nor were maternal sensitivity scores highly correlated within subjects over time (intraclass correlation = 0.07, based on an unconditional means model run in R version 4.0.3). After running the multiple regression analyses for each CpG loci, a false-discovery rate (FDR) correction (q = 0.05) was applied to control for multiple comparisons (Benjamini & Hochberg, Reference Benjamini and Hochberg1995). CpG loci whose methylation levels were significantly predicted by maternal caregiving at any timepoint after correction were selected for the mediation analyses.

In the next step of the main analyses, methylation levels at CpG loci selected in the first step were tested as mediators of a possible relationship between maternal sensitivity and child internalizing and externalizing behavior. We performed a separate parallel mediation analysis for each outcome variable (i.e., internalizing behavior at age 6, internalizing behavior at age 10, externalizing behavior at age 6, and externalizing behavior at age 10) using multiple regression and bootstrapping procedures described by Hayes (Reference Hayes2013). Each mediation analysis tested a total effect model of the relationship between maternal sensitivity scores and internalizing/externalizing behavior scores, and a direct effect model of the same relationship while additionally controlling for CpG loci methylation levels. Maternal sensitivity scores at all three time points and the preselected covariates were included as predictors in all models. Ninety-five percent bias-corrected confidence intervals and 1000 bootstrap resamples were then used to determine the significance of the indirect effect (i.e., the reduction in the effect of maternal sensitivity on internalizing/externalizing behavior when CpG loci methylation levels were included in the model). Confidence intervals that did not include zero were interpreted as statistically significant and indicative of partial mediation. As a sensitivity check, the mediation analyses were repeated with self-reported child internalizing and externalizing behavior scores at age 10 years as the dependent variable.

Additionally, Spearman’s rank partial correlations were conducted to explore associations between methylation levels at individual CpG loci and child internalizing and externalizing behavior at both 6 and 10 years of age while controlling for the preselected covariates. Again, a false-discovery rate (FDR) correction (q = 0.05) was applied to control for multiple comparisons.

Finally, we conducted two post hoc analyses. First, in case of confounding between maternal mental health and maternal sensitivity, we reran the main regression analyses including both maternal anxiety symptoms (i.e., STAI) and depression symptoms (i.e., EPDS) as covariates, repeating the models for each time point that maternal mental health was measured (i.e., prenatal, 3 months, 12 months, and 30 months). Second, given prior research showing sex-specific effects of associations of maternal sensitivity with NR3C1 1f methylation (Conradt et al., Reference Conradt, Ostlund, Guerin, Armstrong, Marsit, Tronick, LaGasse and Lester2019), we repeated the main regression analyses including an interaction term for maternal sensitivity at each time point by child sex in separate models. We probed significant interactions by inspecting the sex-specific slopes and applied FDR correction to deal with multiple testing for the main effects.

Results

Preliminary analysis

Descriptive statistics for the sample characteristics, maternal sensitivity scores, and CBCL scores are shown in Table 1 and associations between these variables are reported in Table 2. Notably, across all time points, there were no significant associations of maternal sensitivity with child internalizing or externalizing behavior. However, we continued with the planned mediation analyses given that the absence of a direct association between the independent and dependent variables does not rule out the possibility of an indirect effect via a mediator (Hayes, Reference Hayes2013).

Table 2. Correlation coefficients for associations between study variables

Note. Pearson’s correlation coefficients are shown, except for child sex where the biserial-point correlation coefficient is reported.

aM boys = 3689g, M girls = 3510g; *p <. 05, **p < .01

As for methylation levels, descriptive statistics are shown in Supplementary Table 1 and associations with the study covariates are reported in Supplementary Table 2. DNA methylation levels across the 25 CpG loci were consistent with hypomethylation of this promoter region (beta range: 0.01–0.12) with significant associations between methylation levels at several loci and the study covariates, with the exception of the two genetic PCs. Furthermore, methylation levels were significantly correlated between almost a third of CpG loci, as shown in Figure 1; these correlations were mostly positive, weak to moderate and did not show a pattern based on the spatial proximity of the loci.

Figure 1. Heat map of significant correlations in methylation levels between 25 CpG Loci at the NR3C1 promoter region. Note. The figure shows the significant (p < .05) Pearson’s correlation coefficients between methylation levels of the CpG loci at the NR3C1 promoter. The strength of the association is visualized on a color spectrum with red representing positive correlations and blue negative correlations as indicated in the key to the right of the heat map. The heat map includes, in chromosome location order, all CpG loci at the NR3C1 promoter region whose methylation levels are described by the EPIC array (GRCh37/hg19 chr5:142,782,071 to chr5:142,785,071).

Associations between maternal sensitivity and NR3C1 methylation

As shown in Table 3, maternal sensitivity at age five weeks was associated with methylation levels at two CpG loci after FDR correction for multiple testing. Specifically, higher maternal sensitivity scores were associated with significantly lower methylation levels at cg21702128 (b = −0.002, p = <.001) and cg04111177 (b = −0.001, p = <.001). In other words, each one unit increase in maternal sensitivity at age five weeks was associated with a 0.2% decrease in methylation levels at cg21702128 and a 0.1% decrease in methylation levels at cg04111177. In contrast, there were no significant associations of maternal sensitivity at either 12 months or 30 months with children’s methylation levels after correcting for multiple testing. As such, in the mediation analyses we tested possible indirect effects of maternal sensitivity at five weeks on child internalizing and externalizing behavior via methylation levels at cg21702128 and cg04111177.

Table 3. Standardized regression coefficients for associations of cpG methylation levels at age 6 with maternal sensitivity at 5 weeks, 12 months, and 30 months of age

Note. N = 139, β = standardized regression coefficients, covariates: buccal cell count, genetic PC1 and PC2, maternal age, child birthweight, child sex.

*Significant after FDR correction for multiple testing.

Indirect effects of maternal sensitivity on child behaviors via NR3C1 methylation

The results of the mediation analyses are presented in Table 4. Maternal sensitivity at five weeks did not significantly predict child internalizing or externalizing behavior at age 6 or 10 years in the total and direct models. Moreover, there were no significant indirect effects, indicating that cg21702128 and cg04111177 methylation levels did not mediate an effect of maternal sensitivity at age five weeks on child internalizing or externalizing behavior at either age 6 or 10 years. Likewise, there were no significant indirect effects when child self-reported internalizing and externalizing behavior scores at age 10 years were used in the mediation analyses instead of maternal reports.

Table 4. Regression and bootstrapping results for testing effects of maternal sensitivity on child internalizing/externalizing behavior at age 6 and 10 as mediated by Cg21702128 and Cg04111177 methylation at age 6

Note. N6 years = 134, N10 years = 127, B = unstandardized regression coefficients, CI = 95% bias-corrected confidence interval for the significance of the indirect effects; all CIs cross zero indicating no significant effects. Covariates: maternal sensitivity at age 12 months and 30 months, buccal cell count, genetic PC1 and PC2, maternal age, child birthweight, child sex.

aCompletely standardized indirect effects of maternal sensitivity at 5 weeks on the dependent variables.

*p < .05

Exploratory analyses: associations between NR3C1 methylation and child behaviors

Coefficients and uncorrected p-values for the associations of methylation levels at individual CpG loci with child internalizing and externalizing behavior at ages 6 and 10 years are shown in Table 5. Partial correlations revealed a positive association of cg01967637 methylation levels with internalizing behavior at age 6 years, a negative association of cg00629244 methylation levels with internalizing behavior at age 6 years, and a positive association of cg19135245 methylation levels with internalizing at age 10 years. However, these associations did not remain significant after correction for multiple testing. No significant associations were found between methylation levels at any of the 25 CpG loci and children’s externalizing behavior at ages six or 10 years. No significant associations were found after correction for multiple testing when including child self-reported internalizing and externalizing behavior scores at age 10 years either.

Table 5. Spearman’s rho coefficients and P-values for partial correlations of NR3C1 cpG loci methylation levels at age 6 with internalizing/externalizing behavior at age 6 and 10 years

Note. N 6 years = 134 , N 10 years = 127. covariates: buccal cell count, genetic PC1 and PC2, maternal age, child birthweight, and child sex.

Post hoc analyses

Maternal mental health

Pearson’s correlations revealed one significant association between maternal sensitivity and maternal mental health: specifically, a weak negative correlation between maternal sensitivity and maternal depression scores at infant age 30 weeks (r = .20, p = .006). Furthermore, there were no meaningful changes to the results for the associations of maternal sensitivity with NR3C1 methylation levels, or for the mediation analyses, when maternal anxiety and depression scores during pregnancy or at infant age 3 months, 12 months, or 30 months were included in the models.

Child sex

There were no moderating effects of child sex on the associations between maternal sensitivity at infant age 5 weeks or 12 months and NR3C1 methylation. However, child sex moderated the association between maternal sensitivity at age 30 months and cg21702128 methylation levels (interaction term: b = 0.01, SE = .003, p = <.001). Probing of the sex-specific slopes revealed a positive association between maternal sensitivity at 30 months and methylation levels cg21702128 in girls (b = 0.005, SE = .003, p = .044), whereas for boys the association was negative (b = −0.007, SE = .002, p = .006). However, neither association remained significant after FDR correction.

Discussion

The current study suggests that higher maternal sensitivity in the first weeks of infancy is associated with lower methylation levels at two loci at the NR3C1 promoter region in later childhood. However, the study also highlights that the timing of caregiving quality may be particularly important given that maternal sensitivity later in infancy (i.e., 12 and 30 months) was not associated with children’s NR3C1 methylation levels. Furthermore, contrary to our hypothesis, the study showed no associations between maternal sensitivity and child internalizing and externalizing behaviors at ages 6 or 10 years – neither directly nor indirectly via NR3C1 methylation.

In the current study, two CpG loci – cg21702128 and cg04111177 were significantly less methylated in 6-year-old children who had more sensitive mothers when they were 5 weeks old. These findings are in line with previous research that found significant associations of children’s methylation levels at these two loci with severely disrupted caregiving (Weder et al., Reference Weder, Zhang, Jensen, Yang, Simen, Jackowski, Lipschitz, Douglas-Palumberi, Ge, Perepletchikova, O’Loughlin, Hudziak, Gelernter and Kaufman2014). Furthermore, cg04111177 is located in the exon 1F region where methylation levels in 5-month-old infants were found to be cross-sectionally associated with maternal sensitivity in earlier studies using pyrosequencing (Conradt et al., Reference Conradt, Dylan Guerin, Marsit, Hawes and Tronick2016, Reference Conradt, Ostlund, Guerin, Armstrong, Marsit, Tronick, LaGasse and Lester2019). Thus, the current study builds on previous findings by suggesting that links between maternal sensitivity and NR3C1 methylation extend into childhood.

In relation to the functional relevance of cg21702128 and cg04111177, methylation at these sites has been linked to functioning of the HPA axis. Specifically, methylation at cg04111177 was found to predict morning cortisol values in school-aged children, although the direction of the effect was not reported (Weder et al., Reference Weder, Zhang, Jensen, Yang, Simen, Jackowski, Lipschitz, Douglas-Palumberi, Ge, Perepletchikova, O’Loughlin, Hudziak, Gelernter and Kaufman2014). Meanwhile, higher methylation at cg21702128 – located in the exon 1D region – was found in patients with endogenous Cushing’s syndromes, which is characterized by heightened cortisol levels (Glad et al., Reference Glad, Andersson-Assarsson, Berglund, Bergthorsdottir, Ragnarsson and Johannsson2017). Therefore, differential methylation at these two CpG loci may be related to regulation of the HPA axis. Yet, as in the current study, prior research has not established a link between methylation levels at either loci and internalizing or externalizing behavior (Cicchetti & Handley, Reference Cicchetti and Handley2017; Radtke et al., Reference Radtke, Schauer, Gunter, Ruf-Leuschner, Sill, Meyer and Elbert2015; Weder et al., Reference Weder, Zhang, Jensen, Yang, Simen, Jackowski, Lipschitz, Douglas-Palumberi, Ge, Perepletchikova, O’Loughlin, Hudziak, Gelernter and Kaufman2014).

As for the importance of developmental timing of sensitive caregiving, we found associations between children’s NR3C1 methylation levels at age 6 years and maternal sensitivity measured at age 5 weeks, but not at ages 12 and 30 months. These findings are partly in keeping with prior research and suggest a sensitive period for NR3C1 methylation in response to maternal sensitivity before age 12 months (Conradt et al., Reference Conradt, Dylan Guerin, Marsit, Hawes and Tronick2016, Reference Conradt, Ostlund, Guerin, Armstrong, Marsit, Tronick, LaGasse and Lester2019; Dall’ Aglio et al., Reference Dall’ Aglio, Rijlaarsdam, Mulder, Neumann, Felix, Kok, Bakermans-Kranenburg, van Ijzendoorn, Tiemeier and Cecil2020; Dunn et al., Reference Dunn, Soare, Zhu, Simpkin, Suderman, Klengel, Smith, Ressler and Relton2019). However, it should be noted that there was a difference in the measurement of maternal sensitivity at age 5 weeks versus 12 and 30 months, which matches methodological differences between previous studies in younger versus older infants. As well as the use of different observational coding systems, maternal sensitivity was observed during a mild stressor at age 5 weeks (i.e., a bathing session) compared to a play task at later ages. Earlier research has indicated that maternal sensitivity ratings can differ in situations of infant distress versus non-distress and differentially predict child outcomes (Leerkes et al., Reference Leerkes, Weaver and O'Brien2012). That said, both measures used in the current study have been found to detect improvements in sensitivity following a parenting intervention to increase sensitivity, which supports the likelihood that they are measuring the same construct (Mesman & Emmen, Reference Mesman and Emmen2013).

In terms of child behavioral outcomes, maternal sensitivity did not predict levels of child internalizing or externalizing behaviors at ages 6 or 10 years in the current sample, nor did we find indirect effects via NR3C1 promoter methylation levels. A possible reason might be the relatively long follow-up from the measurement of maternal sensitivity to child behavior, during which time other factors (e.g., parenting style, family support, and community social support) may have fostered resilience to internalizing and externalizing problems (Fritz et al., Reference Fritz, de Graaff, Caisley, van Harmelen and Wilkinson2018). Such an explanation could also account for mixed evidence regarding the influence of maternal sensitivity on internalizing and externalizing behaviors in other community samples (Campbell et al., Reference Campbell, Matestic, von Stauffenberg, Mohan and Kirchner2007; Kok et al., Reference Kok, Linting, Bakermans-Kranenburg, van Ijzendoorn, Jaddoe, Hofman, Verhulst and Tiemeier2013; Propper et al., Reference Propper, Willoughby, Halpern, Carbone and Cox2007). Moreover, most research that links higher NR3C1 methylation to increased psychopathology does so in the context of severe adversities (Palma-Gudiel et al., Reference Palma-Gudiel, Córdova-Palomera, Leza and Fañanás2015; Parade et al., Reference Parade, Ridout, Seifer, Armstrong, Marsit, McWilliams and Tyrka2016; Tyrka et al., Reference Tyrka, Ridout and Parade2016; Watkeys et al., Reference Watkeys, Kremerskothen, Quidé, Fullerton and Green2018). However, the current study sample comprised healthy mother–infant dyads of mainly higher socioeconomic status who were thus less likely to have been exposed to extreme stress (Turner & Avison, Reference Turner and Avison2003) and were at lower risk for psychopathology (van Oort et al., Reference van Oort, van der Ende, Wadsworth, Verhulst and Achenbach2011). This was reflected in low NR3C1 methylation levels and low child behavior scores across the current study sample; the lack of variation in the data hence potentially created difficulties for detecting associations. Future studies could recruit more heterogenous samples, for example including children with known risk factors for psychopathology, and consider the moderating effects of protective factors that may influence the potential pathway from caregiving to child behavior via DNA methylation. Also mentionable is that the small statistical effects of maternal sensitivity on children’s methylation levels may not necessarily impact gene expression, and thus subsequent child behavior, which highlights a need for future studies that include measures of GR gene expression and HPA axis functioning to better assess the biological relevance of associations between caregiving and NR3C1 methylation.

This study is not without limitations. For example, the study was correlational and methylation was not measured prior to exposure to caregiving, which means that we cannot conclude that higher sensitivity causes a reduction in methylation levels at the NR3C1 promoter region. Additionally, the relatively small sample offered little power to fully evaluate the effects of possible moderators. Moreover, methylation levels were measured from buccal cells and thus the relationship with DNA methylation in brain regions implicated in stress physiology is unknown (Jones et al., Reference Jones, Moore and Kobor2018); although DNA methylation levels in buccal and brain tissues have been found to be highly correlated at NR3C1 (r = .92; Braun et al., Reference Braun, Han, Hing, Nagahama, Gaul, Heinzman, Grossbach, Close, Dlouhy, Howard, Kawasaki, Potash and Shinozaki2019). On the other hand, in terms of strengths, the longitudinal design did allow us to measure mother–infant interactions by direct observation at multiple time points rather than relying on retrospective reports, as well as to assess longer-term associations of maternal sensitivity with children’s NR3C1 methylation levels and stress-related behaviors. Furthermore, children’s internalizing and externalizing behaviors at age 10 years were also measured by child self-report rather than relying solely on parental reports. The next step would be to use intervention studies whereby methylation and behavioral data are collected before and after parental sensitivity training, thus providing causal evidence for epigenetic mechanisms that link caregiving to child behavioral outcomes (Montirosso et al., Reference Montirosso, Rosa, Giorda, Fazzi, Orcesi, Cavallini and Provenzi2020; Overbeek et al., Reference Overbeek, Creasey, Wesarg, Huijzer-Engbrenghof and Spencer2020). Moreover, future studies could include other caregivers, such as fathers, whose sensitivity may also be important for child development and compensate when maternal sensitivity is low (Malmberg et al., Reference Malmberg, Lewis, West, Murray, Sylva and Stein2016).

To conclude, the current study aimed to improve our knowledge of the factors and mechanisms that protect children from the development of mental health problems in the context of universal prevention. In a community sample, we showed that typical variation in maternal sensitivity at infant age 5 weeks was associated with 6-year-old children’s methylation levels at NR3C1 loci implicated in HPA axis regulation. However, the same results did not apply for maternal sensitivity measured at infant ages 12 and 30 months, suggesting a sensitive period for caregiving effects on NR3C1 methylation within the first year of life. Moreover, we did not find evidence that differential NR3C1 methylation mediates a pathway from sensitive caregiving to lower levels of child internalizing or externalizing behavior; this is potentially related to the influence of other protective factors and the low risk for psychopathology in our community sample. In the future, studies using parenting interventions in vulnerable (high stress) populations could expand our understanding of the biological mechanisms linking the early caregiving environment to child mental health and provide the causal evidence needed to inform universal prevention approaches.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0954579423000226

Acknowledgements

This work was supported by the Dutch Research Council VENI grant 016.195.197 (RB), VIDI grant 575-25-009 (CdeW), and VICI grant 016.Vici.185.038 (CdeW), a Jacobs Foundation Advanced Research Fellowship (CdeW), and a Sara van Dam Project Grant of the Royal Netherlands Academy of Arts and Sciences (RB). KOD is a CIFAR Fellow in the Child and Brain Development Program and supported by the Brain and Behavior Research Foundation (Pfeil Fellow).

Conflict of Interest

None.

References

Achenbach, T. M. (2007). Manual for the ASEBA school-age forms & profiles an integrated system of multi-informant assessment. Research Center for Children, 82, 6090.Google Scholar
Ainsworth, M. D. S., Bell, S. M., & Stayton, D. F. (1974). Infant-mother attachment and social development: Socialization as a product of reciprocal responsiveness to signals. In Richards, M. P. M. (Eds.), The integration of a child into a social world (pp. 99135). Cambridge University Press.Google Scholar
Ainsworth, M. D. S., Blehar, M. C., Waters, E., & Wall, S. (1978). Patterns of attachment: A psychological study of the strange situation. Lawrence Erlbaum.Google Scholar
Albers, E. M., Marianne Riksen-Walraven, J., Sweep, F. C. G. J., & Weerth, C. De (2008). Maternal behavior predicts infant cortisol recovery from a mild everyday stressor. Journal of Child Psychology and Psychiatry, 49(1), 97103. https://doi.org/10.1111/j.1469-7610.2007.01818.x CrossRefGoogle ScholarPubMed
Aristizabal, M. J., Anreiter, I., Halldorsdottir, T., Odgers, C. L., McDade, T. W., Goldenberg, A., Mostafavi, S., Kobor, M. S., Binder, E. B., Sokolowski, M. B., O'Donnell, K. J. (2020). Biological embedding of experience: A primer on epigenetics. Proceedings of the National Academy of Sciences of the United States of America, 117(38), 2326123269. https://doi.org/10.1073/pnas.1820838116 CrossRefGoogle ScholarPubMed
Barfield, R. T., Almli, L. M., Kilaru, V., Smith, A. K., Mercer, K. B., Duncan, R., Klengel, T., Mehta, D., Binder, E. B., Epstein, M. P., Ressler, K. J., Conneely, K. N. (2014). Accounting for population stratification in DNA methylation studies. Genetic Epidemiology, 38(3), 231241. https://doi.org/10.1002/gepi.21789 CrossRefGoogle ScholarPubMed
Beijers, R., Hartman, S., Shalev, I., Hastings, W., Mattern, B. C., de Weerth, C., & Belsky, J. (2020). Testing three hypotheses about effects of sensitive-insensitive parenting on telomeres. Developmental Psychology, 56(2), 237250. https://doi.org/10.1037/dev0000879 CrossRefGoogle ScholarPubMed
Beijers, R., Jansen, J., Riksen-Walraven, M., & de Weerth, C. (2010). Maternal prenatal anxiety and stress predict infant illnesses and health complaints. Pediatrics, 126(2), e401e409. https://doi.org/10.1542/peds.2009-3226 CrossRefGoogle ScholarPubMed
Beijers, R., Jansen, J., Riksen-Walraven, M., & de Weerth, C. (2011). Nonparental care and infant health: Do number of hours and number of concurrent arrangements matter? Early Human Development, 87(1), 915. https://doi.org/10.1016/j.earlhumdev.2010.09.003 CrossRefGoogle ScholarPubMed
Bell, S. M., & Ainsworth, M. D. S. (1972). Infant crying and maternal responsiveness. Child Development, 43(4), 11711190. https://doi.org/10.2307/1127388 CrossRefGoogle ScholarPubMed
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x CrossRefGoogle Scholar
Berretta, E., Guida, E., Forni, D., & Provenzi, L. (2021). Glucocorticoid receptor gene (NR3C1) methylation during the first thousand days: Environmental exposures and developmental outcomes. Neuroscience and Biobehavioral Reviews, 125, 493502. https://doi.org/10.1016/j.neubiorev.2021.03.003 CrossRefGoogle ScholarPubMed
Blair, C., Granger, D., Willoughby, M., & Kivlighan, K. (2006). Maternal sensitivity is related to hypothalamic-pituitary-adrenal axis stress reactivity and regulation in response to emotion challenge in 6-month-old infants. Annals of the New York Academy of Sciences, 1094(1), 263267. https://doi.org/10.1196/annals.1376.031 CrossRefGoogle ScholarPubMed
Bowlby, J. (1980). Attachment and loss. Basic Books.Google Scholar
Braun, P. R., Han, S., Hing, B., Nagahama, Y., Gaul, L. N., Heinzman, J. T., Grossbach, A. J., Close, L., Dlouhy, B. J., Howard, M. A. 3rd, Kawasaki, H., Potash, J. B., & Shinozaki, G. (2019). Genome-wide DNA methylation comparison between live human brain and peripheral tissues within individuals. Translational Psychiatry, 9(1), 47, https://doi.org/10.1038/s41398-019-0376-y,CrossRefGoogle ScholarPubMed
Campbell, S. B., Matestic, P., von Stauffenberg, C., Mohan, R., & Kirchner, T. (2007). Trajectories of maternal depressive symptoms, maternal sensitivity, and children’s functioning at school entry. Developmental Psychology, 43(5), 12021215. https://doi.org/10.1037/0012-1649.43.5.1202 CrossRefGoogle ScholarPubMed
Cicchetti, D., & Handley, E. D. (2017). Methylation of the glucocorticoid receptor gene, nuclear receptor subfamily 3, group C, member 1 (NR3C1), in maltreated and nonmaltreated children: Associations with behavioral undercontrol, emotional lability/negativity, and externalizing and internalizing. Development and Psychopathology, 29(5), 17951806. https://doi.org/10.1017/S0954579417001407 CrossRefGoogle Scholar
Conradt, E., Dylan Guerin, D. A., Marsit, C. J., Hawes, K., & Tronick, E. (2016). The contributions of maternal sensitivity and maternal depressive symptoms to epigenetic processes and neuroendocrine functioning. Child Development, 87(1), 7385. https://doi.org/10.1111/cdev.12483 CrossRefGoogle ScholarPubMed
Conradt, E., Ostlund, B., Guerin, D., Armstrong, D. A., Marsit, C. J., Tronick, E., LaGasse, L., & Lester, B. M. (2019). DNA methylation of NR3c1 in infancy: Associations between maternal caregiving and infant sex. Infant Mental Health Journal, 40(4), 513522. https://doi.org/10.1002/imhj.21789 CrossRefGoogle ScholarPubMed
Curley, J. P., & Champagne, F. A. (2016). Influence of maternal care on the developing brain: Mechanisms, temporal dynamics and sensitive periods. Frontiers in Neuroendocrinology, 40, 5266. https://doi.org/10.1016/j.yfrne.2015.11.001 CrossRefGoogle ScholarPubMed
Dadds, M. R., Moul, C., Hawes, D. J., Mendoza Diaz, A., & Brennan, J. (2015). Individual differences in childhood behavior disorders associated with epigenetic modulation of the cortisol receptor gene. Child Development, 86(5), 13111320. https://doi.org/10.1111/cdev.12391 CrossRefGoogle ScholarPubMed
Dall’ Aglio, L., Rijlaarsdam, J., Mulder, R. H., Neumann, A., Felix, J. F., Kok, R., Bakermans-Kranenburg, M. J., van Ijzendoorn, M. H., Tiemeier, H., Cecil, C. A. M. (2020). Epigenome-wide associations between observed maternal sensitivity and offspring DNA methylation: A population-based prospective study in children. Psychological Medicine, 1-11(13), 24812491. https://doi.org/10.1017/S0033291720004353 Google Scholar
Deans, C. L. (2020). Maternal sensitivity, its relationship with child outcomes, and interventions that address it: A systematic literature review. Early Child Development and Care, 190(2), 252275. https://doi.org/10.1080/03004430.2018.1465415 CrossRefGoogle Scholar
Dekker, M. C., Koot, H. M., van der Ende, J., & Verhulst, F. C. (2002). Emotional and behavioral problems in children and adolescents with and without intellectual disability. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 43(8), 10871098. https://doi.org/10.1111/1469-7610.00235 CrossRefGoogle ScholarPubMed
Dunn, E. C., Soare, T. W., Zhu, Y., Simpkin, A. J., Suderman, M. J., Klengel, T., Smith, A. D. A. C., Ressler, K. J., & Relton, C. L. (2019). Sensitive periods for the effect of childhood adversity on DNA methylation: Results from a prospective, longitudinal study. Biological Psychiatry, 85(10), 838849. https://doi.org/10.1016/j.biopsych.2018.12.023 CrossRefGoogle ScholarPubMed
Erickson, M. F., Sroufe, L. A., & Egeland, B. (1985). The relationship between quality of attachment and behavior problems in preschool in a high-risk sample. Monographs of the Society for Research in Child Development, 50(1), 147166.CrossRefGoogle Scholar
Fortin, J. P., Labbe, A., Lemire, M., Zanke, B. W., Hudson, T. J., Fertig, E. J., Greenwood, C. M., & Hansen, K. D. (2014). Functional normalization of 450k methylation array data improves replication in large cancer studies. Genome Biology, 15(11), 503. https://doi.org/10.1186/s13059-014-0503-2 CrossRefGoogle ScholarPubMed
Fritz, J., de Graaff, A. M., Caisley, H., van Harmelen, A. L., & Wilkinson, P. O. (2018). A systematic review of amenable resilience factors that moderate and/or mediate the relationship between childhood adversity and mental health in young people. Frontiers in Psychiatry, 9, 230. https://doi.org/10.3389/fpsyt.2018.00230 CrossRefGoogle ScholarPubMed
Gardini, E. S., Schaub, S., Neuhauser, A., Ramseier, E., Villiger, A., Ehlert, U., Lanfranchi, A., & Turecki, G. (2022). Methylation of the glucocorticoid receptor promoter in children: Links with parents as teachers, early life stress, and behavior problems. Development and Psychopathology, 34(3), 810822. https://doi.org/10.1017/S0954579420001984 CrossRefGoogle ScholarPubMed
Gianino, A. F., & Tronick, E. Z. (1988). The mutual regulation model: The infant’s self and interactive regulation and coping and defensive capacities. In Field, T. M., McCabe, P. M., & Schneiderman, N. (Eds.), Stress and coping across development (pp. 4768). Lawrence Erlbaum Associates, Inc.Google Scholar
Glad, C. A. M., Andersson-Assarsson, J. C., Berglund, P., Bergthorsdottir, R., Ragnarsson, O., & Johannsson, G. (2017). Reduced DNA methylation and psychopathology following endogenous hypercortisolism – a genome-wide study. Scientific Reports, 7(1), 44445. https://doi.org/10.1038/srep44445 CrossRefGoogle ScholarPubMed
Global Burden of Disease Study 2013 Collaborators (2015). Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: A systematic analysis for the Global Burden of Disease Study 2013. The Lancet, 386(9995), 743800. https://doi.org/10.1016/S0140-6736(15)60692-4 CrossRefGoogle Scholar
Goodman, A., & Goodman, R. (2009). Strengths and difficulties questionnaire as a dimensional measure of child mental health. Journal of the American Academy of Child and Adolescent Psychiatry, 48(4), 400403. https://doi.org/10.1097/CHI.0b013e3181985068 CrossRefGoogle ScholarPubMed
Ha, M., Mabuchi, K., Sigurdson, A. J., Freedman, D. M., Linet, M. S., Doody, M. M., & Hauptmann, M. (2007). Smoking cigarettes before first childbirth and risk of breast cancer. American Journal of Epidemiology, 166(1), 5561. https://doi.org/10.1093/aje/kwm045 CrossRefGoogle ScholarPubMed
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press.Google Scholar
Heinrich, A., Buchmann, A. F., Zohsel, K., Dukal, H., Frank, J., Treutlein, J., Nieratschker, V., Witt, S. H., Brandeis, D., Schmidt, M. H., Esser, G., Banaschewski, T., Laucht, M., Rietschel, M. (2015). Alterations of glucocorticoid receptor gene methylation in externalizing disorders during childhood and adolescence. Behavior Genetics, 45(5), 529536. https://doi.org/10.1007/s10519-015-9721-y CrossRefGoogle ScholarPubMed
Helmerhorst, K., Riksen-Walraven, J., Fukkink, R. G., Tavecchio, L., & Gevers Deynoot-Schaub, M. (2017). Effects of the caregiver interaction profile training on caregiver-child interactions in Dutch child care centers: A randomized controlled trial. Child & Youth Care Forum, 46(3), 413436. https://doi.org/10.1007/s10566-016-9383-9 CrossRefGoogle ScholarPubMed
Jansen, J., Beijers, R., Riksen-Walraven, M., & de Weerth, C. (2010). Does maternal care-giving behavior modulate the cortisol response to an acute stressor in 5-week-old human infants? Stress-the International Journal on The Biology of Stress, 13(6), 491497. https://doi.org/10.3109/10253890.2010.483298 CrossRefGoogle Scholar
Jones, M., Moore, S., & Kobor, M. (2018). Principles and challenges of applying epigenetic epidemiology to psychology. Annual Review of Psychology, 69(459-485), 459485. https://doi.org/10.1146/annurev-psych-122414-033653 CrossRefGoogle ScholarPubMed
Kok, R., Linting, M., Bakermans-Kranenburg, M. J., van Ijzendoorn, M. H., Jaddoe, V. W. V., Hofman, A., Verhulst, F. C., & Tiemeier, H. (2013). Maternal sensitivity and internalizing problems: Evidence from two longitudinal studies in early childhood. Child Psychiatry and Human Development, 44(6), 751765. https://doi.org/10.1007/s10578-013-0369-7 CrossRefGoogle ScholarPubMed
Laurent, H. K., Harold, G. T., Leve, L., Shelton, K. H., & Van Goozen, S. H. M. (2016). Understanding the unfolding of stress regulation in infants. Development and Psychopathology, 28(4pt2), 14311440. https://doi.org/10.1017/S0954579416000171 CrossRefGoogle ScholarPubMed
Leerkes, E. M., Weaver, J. M., & O'Brien, M. (2012). Differentiating maternal sensitivity to infant distress and non-distress. Parenting, Science and Practice, 12(2-3), 175184. https://doi.org/10.1080/15295192.2012.683353 CrossRefGoogle ScholarPubMed
Liu, J., Morgan, M., Hutchison, K., & Calhoun, V. D. (2010). A study of the influence of sex on genome wide methylation. PLoS ONE, 5(4), e10028. https://doi.org/10.1371/journal.pone.0010028 CrossRefGoogle ScholarPubMed
Lubin, J. H., Tomásek, L., Edling, C., Hornung, R. W., Howe, G., Kunz, E., Kusiak, R. A., Morrison, H. I., Radford, E. P., Samet, J. M., Tirmarche, M., Woodward, A., Yao, S. X. (1997). Estimating lung cancer mortality from residential radon using data for low exposures of miners. Radiation Research, 147(2), 126134. https://doi.org/10.2307/3579412 CrossRefGoogle ScholarPubMed
Malmberg, L.-E., Lewis, S., West, A., Murray, E., Sylva, K., & Stein, A. (2016). The influence of mothers’ and fathers’ sensitivity in the first year of life on children’s cognitive outcomes at 18 and 36 months. Child: Care, Health and Development, 42(1), 17. https://doi.org/10.1111/cch.12294 CrossRefGoogle ScholarPubMed
Mathyssek, C. M., Olino, T. M., Verhulst, F. C., & van Oort, F. V. A. (2012). Childhood internalizing and externalizing problems predict the onset of clinical panic attacks over adolescence: The TRAILS study. PLoS ONE, 7(12), e51564. https://doi.org/10.1371/journal.pone.0051564 CrossRefGoogle ScholarPubMed
McDade, T. W., Ryan, C. P., Jones, M. J., Hoke, M. K., Borja, J., Miller, G. E., Kuzawa, C. W., & Kobor, M. S. (2019). Genome-wide analysis of DNA methylation in relation to socioeconomic status during development and early adulthood. American Journal of Physical Anthropology, 169(1), 311. https://doi.org/10.1002/ajpa.23800 CrossRefGoogle ScholarPubMed
Mesman, J., & Emmen, R. A. G. (2013). Mary Ainsworth’s legacy: A systematic review of observational instruments measuring parental sensitivity. Attachment and Human Development, 15(5-6), 485506. https://doi.org/10.1080/14616734.2013.820900 CrossRefGoogle ScholarPubMed
Mieloo, C. L., Bevaart, F., Donker, M. C., van Oort, F. V., Raat, H., & Jansen, W. (2014). Validation of the SDQ in a multi-ethnic population of young children. European Journal of Public Health, 24(1), 2632. https://doi.org/10.1093/eurpub/ckt100 CrossRefGoogle Scholar
Min, J. L., Hemani, G., Davey Smith, G., Relton, C., & Suderman, M. (2018). Meffil: Efficient normalization and analysis of very large DNA methylation datasets. Bioinformatics, 34(23), 39833989. https://doi.org/10.1093/bioinformatics/bty476 CrossRefGoogle ScholarPubMed
Montirosso, R., Rosa, E., Giorda, R., Fazzi, E., Orcesi, S., Cavallini, A., Provenzi, L., & Early Intervention Study Group (2020). Early Parenting Intervention - Biobehavioral Outcomes in infants with Neurodevelopmental Disabilities (EPI-BOND): Study protocol for an Italian multicentre randomised controlled trial. BMJ Open, 10(7), e035249, https://doi.org/10.1136/bmjopen-2019-035249,CrossRefGoogle ScholarPubMed
Mulligan, C. J., D’Errico, N. C., Stees, J., & Hughes, D. A. (2012). Methylation changes at NR3C1 in newborns associate with maternal prenatal stress exposure and newborn birth weight. Epigenetics, 7(8), 853857. https://doi.org/10.4161/epi.21180 CrossRefGoogle ScholarPubMed
Ong, M. L., Lin, X., & Holbrook, J. D. (2014). Measuring epigenetics as the mediator of gene/environment interactions in DOHaD. Journal of Developmental Origins of Health and Disease, 6(1), 1016. https://doi.org/10.1017/S2040174414000506 CrossRefGoogle ScholarPubMed
Overbeek, G., Creasey, N., Wesarg, C., Huijzer-Engbrenghof, M., & Spencer, H. (2020). When mummy and daddy get under your skin: A new look at how parenting affects children’s DNA methylation, stress reactivity, and disruptive behavior. New Directions for Child and Adolescent Development, 2020(172), 2538. https://doi.org/10.1002/cad.20362 CrossRefGoogle Scholar
Palma-Gudiel, H., Córdova-Palomera, A., Leza, J. C., & Fañanás, L. (2015). Glucocorticoid receptor gene (NR3C1) methylation processes as mediators of early adversity in stress-related disorders causality: A critical review. Neuroscience and Biobehavioral Reviews, 55, 520535. https://doi.org/10.1016/j.neubiorev.2015.05.016 CrossRefGoogle ScholarPubMed
Parade, S. H., Ridout, K. K., Seifer, R., Armstrong, D. A., Marsit, C. J., McWilliams, M. A., & Tyrka, A. R. (2016). Methylation of the glucocorticoid receptor gene promoter in preschoolers: Links with internalizing behavior problems. Child Development, 87(1), 8697. https://doi.org/10.1111/cdev.12484 CrossRefGoogle ScholarPubMed
Pop, V. J., Komproe, I. H., & van Son, M. J. (1992). Characteristics of the Edinburgh postnatal depression scale in The Netherlands. Journal of Affective Disorders, 26(2), 105110.CrossRefGoogle Scholar
Propper, C., Willoughby, M., Halpern, C. T., Carbone, M. A., & Cox, M. (2007). Parenting quality, DRD4, and the prediction of externalizing and internalizing behaviors in early childhood. Developmental Psychobiology, 49(6), 619632. https://doi.org/10.1002/dev.20249 CrossRefGoogle ScholarPubMed
Provenzi, L., Brambilla, M., Scotto di Minico, G., Montirosso, R., & Borgatti, R. (2019). Maternal caregiving and DNA methylation in human infants and children: Systematic review. Genes, Brain and Behavior, 19(3), 111. https://doi.org/10.1111/gbb.12616 September.Google ScholarPubMed
Radtke, K. M., Schauer, M., Gunter, H. M., Ruf-Leuschner, M., Sill, J., Meyer, A., & Elbert, T. (2015). Epigenetic modifications of the glucocorticoid receptor gene are associated with the vulnerability to psychopathology in childhood maltreatment. Translational Psychiatry, 5(5), e571e571. https://doi.org/10.1038/tp.2015.63 CrossRefGoogle ScholarPubMed
Reef, J., Diamantopoulou, S., van Meurs, I., Verhulst, F., & van der Ende, J. (2009). Child to adult continuities of psychopathology: A 24-year follow-up. Acta Psychiatrica Scandinavica, 120(3), 230238. https://doi.org/10.1111/j.1600-0447.2009.01422.x CrossRefGoogle ScholarPubMed
Roza, S. J., Hofstra, M. B., Van Der Ende, J., & Verhulst, F. C. (2003). Stable prediction of mood and anxiety disorders based on behavioral and emotional problems in childhood: A 14-year follow-up during childhood, adolescence, and young adulthood. American Journal of Psychiatry, 160(12), 21162121. https://doi.org/10.1176/appi.ajp.160.12.2116 CrossRefGoogle ScholarPubMed
Ruttle, P. L., Shirtcliff, E. A., Serbin, L. A., Ben-Dat Fisher, D., Stack, D. M., & Schwartzman, A. E. (2011). Disentangling psychobiological mechanisms underlying internalizing and externalizing behaviors in youth: Longitudinal and concurrent associations with cortisol. Hormones and Behavior, 59(1), 123132. https://doi.org/10.1016/j.yhbeh.2010.10.015 CrossRefGoogle ScholarPubMed
Sánchez, B. N., Hu, H., Litman, H. J., & Téllez-rojo, M. M. (2011). Statistical methods to study timing of vulnerability with sparsely sampled data on environmental toxicants. Environmental Health Perspectives, 119(3), 409415. https://doi.org/10.1289/ehp.1002453 CrossRefGoogle ScholarPubMed
Smeekens, S., Marianne Riksen-Walraven, J., & van Bakel, H. J. A. (2007). Cortisol reactions in five-year-olds to parent-child interaction: The moderating role of ego-resiliency. Journal of Child Psychology and Psychiatry, 48(7), 649656. https://doi.org/10.1111/j.1469-7610.2007.01753.x CrossRefGoogle ScholarPubMed
Smith, A. K., Kilaru, V., Klengel, T., Mercer, K. B., Bradley, B., Conneely, K. N., Ressler, K. J., & Binder, E. B. (2015). DNA extracted from saliva for methylation studies of psychiatric traits: Evidence tissue specificity and relatedness to brain. American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics, 168(1), 3644. https://doi.org/10.1002/ajmg.b.32278 CrossRefGoogle Scholar
Solmi, M., Radua, J., Olivola, M., Croce, E., Soardo, L., Salazar de Pablo, G., Il Shin, J., Kirkbride, J. B., Jones, P., Kim, J. H., Kim, J. Y., Carvalho, A. F., Seeman, M. V., Correll, C. U., Fusar-Poli, P. (2021). Age at onset of mental disorders worldwide: Large-scale meta-analysis of 192 epidemiological studies. Molecular Psychiatry, 27(1), 281295. https://doi.org/10.1038/s41380-021-01161-7 CrossRefGoogle ScholarPubMed
Spielberger, C. D., Gorsuch, R. L., Lushene, P. R., Vagg, P. R., & Jacobs, G. A. (1983). Manual for the state-trait anxiety inventory. Palo Alto, CA: Consulting Psychologists Press.Google Scholar
Tronick, E. Z. (1989). Emotions and emotional communication in infants. American Psychologist, 44(2), 112119. https://doi.org/10.1037/0003-066X.44.2.112 CrossRefGoogle ScholarPubMed
Turner, R. J., & Avison, W. R. (2003). Status variations in stress exposure: Implications for the interpretation of research on race. Socioeconomic Status, and Gender. Journal of Health and Social Behavior, 44(4), 488505. https://doi.org/10.2307/1519795 Google ScholarPubMed
Tyrka, A. R., Ridout, K. K., & Parade, S. H. (2016). Childhood adversity and epigenetic regulation of glucocorticoid signaling genes: Associations in children and adults. Development and Psychopathology, 28(4pt2), 13191331. https://doi.org/10.1017/S0954579416000870 CrossRefGoogle ScholarPubMed
van der Knaap, L. J., van Oort, F. V., Verhulst, F. C., Oldehinkel, A. J., & Riese, H. (2015). Methylation of NR3C1 and SLC6A4 and internalizing problems. The TRAILS Study. Journal of Affective Disorders, 180, 97103. https://doi.org/10.1016/j.jad.2015.03.056 CrossRefGoogle ScholarPubMed
van der Voort, A., Linting, M., Juffer, F., Bakermans-Kranenburg, M. J., Schoenmaker, C., & van IJzendoorn, M. H. (2014). The development of adolescents’ internalizing behavior: Longitudinal effects of maternal sensitivity and child inhibition. Journal of Youth and Adolescence, 43(4), 528540. https://doi.org/10.1007/s10964-013-9976-7 CrossRefGoogle ScholarPubMed
van Hasselt, F. N., Cornelisse, S., Yuan Zhang, T., Meaney, M. J., Velzing, E. H., Krugers, H. J., & Joëls, M. (2012). Adult hippocampal glucocorticoid receptor expression and dentate synaptic plasticity correlate with maternal care received by individuals early in life. Hippocampus, 22(2), 255266. https://doi.org/10.1002/hipo.20892 CrossRefGoogle ScholarPubMed
van Oort, F. V., van der Ende, J., Wadsworth, M. E., Verhulst, F. C., & Achenbach, T. M. (2011). Cross-national comparison of the link between socioeconomic status and emotional and behavioral problems in youths. Social Psychiatry and Psychiatric Epidemiology, 46(2), 167172. https://doi.org/10.1007/s00127-010-0191-5 CrossRefGoogle ScholarPubMed
Wadji, D. L., Tandon, T., Ketcha Wanda, G. J. M., Wicky, C., Dentz, A., Hasler, G., Morina, N., & Martin-Soelch, C. (2021). Child maltreatment and NR3C1 exon 1F methylation, link with deregulated hypothalamus-pituitary-adrenal axis and psychopathology: A systematic review. Child Abuse & Neglect, 122(September), 105304. https://doi.org/10.1016/j.chiabu.2021.105304 CrossRefGoogle ScholarPubMed
Wang, F., Christ, S. L., Mills-Koonce, W. R., Garrett-Peters, P., & Cox, M. J. (2013). Association between maternal sensitivity and externalizing behavior from preschool to preadolescence. Journal of Applied Developmental Psychology, 34(2), 89100. https://doi.org/10.1016/j.appdev.2012.11.003 CrossRefGoogle ScholarPubMed
Watkeys, O. J., Kremerskothen, K., Quidé, Y., Fullerton, J. M., & Green, M. J. (2018). Glucocorticoid receptor gene (NR3C1) DNA methylation in association with trauma, psychopathology, transcript expression, or genotypic variation: A systematic review. Neuroscience & Biobehavioral Reviews, 95(August), 85122. https://doi.org/10.1016/j.neubiorev.2018.08.017 CrossRefGoogle ScholarPubMed
Weaver, I. C. G., Cervoni, N., Champagne, F. A., D’Alessio, A. C., Sharma, S., Seckl, J. R., Dymov, S., Szyf, M., & Meaney, M. J. (2004). Epigenetic programming by maternal behavior. Nature Neuroscience, 7(8), 847854. https://doi.org/10.1038/nn1276 CrossRefGoogle ScholarPubMed
Weaver, I. C. G., Champagne, F. A., Brown, S. E., Dymov, S., Sharma, S., Meaney, M. J., & Szyf, M. (2005). Reversal of maternal programming of stress responses in adult offspring through methyl supplementation: Altering epigenetic marking later in life. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 25(47), 1104511054. https://doi.org/10.1523/JNEUROSCI.3652-05.2005 CrossRefGoogle ScholarPubMed
Weaver, I. C. G., Meaney, M. J., & Szyf, M. (2006). Maternal care effects on the hippocampal transcriptome and anxiety-mediated behaviors in the offspring that are reversible in adulthood. Proceedings of The National Academy of Sciences of The United States of America, 103(9), 34803485. https://doi.org/10.1073/pnas.0507526103 CrossRefGoogle ScholarPubMed
Weder, N., Zhang, H., Jensen, K., Yang, B. Z., Simen, A., Jackowski, A., Lipschitz, D., Douglas-Palumberi, H., Ge, M., Perepletchikova, F., O’Loughlin, K., Hudziak, J. J., Gelernter, J., Kaufman, J. (2014). Child abuse, depression, and methylation in genes involved with stress, neural plasticity, and brain circuitry. Journal of the American Academy of Child and Adolescent Psychiatry, 53(4), 417424.e5. https://doi.org/10.1016/j.jaac.2013.12.025 CrossRefGoogle ScholarPubMed
Whiteford, H. A., Degenhardt, L., Rehm, J., Baxter, A. J., Ferrari, A. J., Erskine, H. E., Charlson, F. J., Norman, R. E., Flaxman, A. D., Johns, N., Burstein, R., Murray, C. J., Vos, T. (2013). Global burden of disease attributable to mental and substance use disorders: Findings from the Global Burden of Disease Study 2010. The Lancet, 382(9904), 15751586. https://doi.org/10.1016/S0140-6736(13)61611-6 CrossRefGoogle ScholarPubMed
Yousefi, P., Huen, K., Davé, V., Barcellos, L., Eskenazi, B., & Holland, N. (2015). Sex differences in DNA methylation assessed by 450 K BeadChip in newborns. BMC Genomics, 16(1), 911. https://doi.org/10.1186/s12864-015-2034-y CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Descriptive statistics

Figure 1

Table 2. Correlation coefficients for associations between study variables

Figure 2

Figure 1. Heat map of significant correlations in methylation levels between 25 CpG Loci at the NR3C1 promoter region. Note. The figure shows the significant (p < .05) Pearson’s correlation coefficients between methylation levels of the CpG loci at the NR3C1 promoter. The strength of the association is visualized on a color spectrum with red representing positive correlations and blue negative correlations as indicated in the key to the right of the heat map. The heat map includes, in chromosome location order, all CpG loci at the NR3C1 promoter region whose methylation levels are described by the EPIC array (GRCh37/hg19 chr5:142,782,071 to chr5:142,785,071).

Figure 3

Table 3. Standardized regression coefficients for associations of cpG methylation levels at age 6 with maternal sensitivity at 5 weeks, 12 months, and 30 months of age

Figure 4

Table 4. Regression and bootstrapping results for testing effects of maternal sensitivity on child internalizing/externalizing behavior at age 6 and 10 as mediated by Cg21702128 and Cg04111177 methylation at age 6

Figure 5

Table 5. Spearman’s rho coefficients and P-values for partial correlations of NR3C1 cpG loci methylation levels at age 6 with internalizing/externalizing behavior at age 6 and 10 years

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