Childhood adversity increases methylation in the GRIN2B gene

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Journal of Psychiatric Research 132 (2021) 38–43

Available online 3 October 2020

Short communication

Childhood adversity increases methylation in the GRIN2B gene

Elin Engdahlâ^,^*^,¹, Ali Alavian-Ghavanini^b^,², Yvonne Forsell^c, Catharina Lavebratt^d^,ê, Joëlle Rüegg^f

aKarolinska Institutet, Institute of Environmental Medicine (IMM), Unit of Integrative Toxicology, Stockholm, Sweden

bSwetox, Karolinska Institutet, Unit of Toxicology Sciences, S¨odert¨alje, Sweden

cKarolinska Institutet, Department of Global Public Health, Stockholm, Sweden

dKarolinska Institutet, Department of Molecular Medicine and Surgery, Stockholm, Sweden

eCenter for Molecular Medicine (CMM), Karolinska University Hospital, Stockholm, Sweden

fUppsala University, Department of Organismal Biology, Uppsala, Sweden

A R T I C L E I N F O Keywords:

GRIN2B DNA methylation Childhood adversity Early life stress Depression Epigenetics

A B S T R A C T

Childhood adversity is an early life stressor associated with increased risk of several psychiatric disorders such as depression. Epigenetic changes, primarily DNA methylation, can be affected by early life stress, which in turn might contribute to altered disease susceptibility later in life. One plausible biomarker of early life stress is methylation of the ionotropic glutamate receptor NMDA type subunit 2B (GRIN2B) gene, which has been pre- viously shown to be epigenetically affected by prenatal environmental stressors. Here, we set out to investigate if stress-inducing adversity during childhood is associated with changes in methylation of GRIN2B in adulthood.

We studied 186 individuals from a Swedish naturalistic population-based cohort who had provided saliva samples (DNA) as well as information regarding both childhood adversity (CA) and depressive symptoms (dep) (nCA,dep =41, nCA,no-dep =56, nno-CA,dep =40, Nno-CA,no-dep =49). Methylation at four CpG sites in a regulatory region of GRIN2B was analysed using bisulfite pyrosequencing. Associations for methylation status to childhood adversity and to depression status were investigated using linear regression models. Our study shows that childhood adversity is associated with increased methylation levels of GRIN2B in adulthood, for three of the measured CpGs (p = 0.007, 0.006 and 5 × 10⁻¹⁴). This indicates that GRIN2B methylation is susceptible to early life stress, and that methylation at this gene is persistent over time. No association was found between GRIN2B methylation and depression status. Yet, this does not rule out a role for alterations in GRIN2B methylation for other neuropsychological outcomes not studied here.

1. Introduction

On top of the genetic information, environmental factors, especially early in life, shape an organism’s phenotype and disease susceptibility later in life (Gluckman and Hanson, 2004; Suzuki, 2018). During development, epigenetic processes play a crucial role in organising the functional genome (Champagne, 2013). Changes in epigenetic patterns, such as DNA methylation, induced during development can be stable throughout life and are thought to be one link between early life exposures and health outcomes later in life (Marsit, 2015; Provencal and Binder, 2015; Tran and Miyake, 2017; Burns et al., 2018; Goyal et al., 2019; Park et al., 2019).

Childhood adversity (CA), such as parental death, neglect, sexual, physical or emotional abuse, and friction within the family, is an early life stressor that has been associated with an increased risk of psychiatric disorders like depression (Collishaw et al., 2007; Widom et al., 2007;

Liu, 2017), psychosis (Varese et al., 2012) and schizophrenia (Wells et al., 2020), but also with cognitive impairments (Pechtel and Pizza- galli, 2011; Martins et al., 2019; Wells et al., 2020). On a molecular level, CA can induce long lasting changes in DNA methylation patterns (Provencal and Binder, 2015; Burns et al., 2018; Park et al., 2019).

Primarily, methylation of genes involved in glucocorticoid signalling (e.

g. NR3C1, FKBP5 (Tyrka et al., 2012; Klengel et al., 2013; Turecki and Meaney, 2016)) and cortisol stress reactivity (e.g. KITLG (Houtepen

* Corresponding author.

E-mail address: Elin.Engdahl@ebc.uu.se (E. Engdahl).

1 Present address: Uppsala University, Department of Organismal Biology, Uppsala, Sweden.

2 Present address: Departments of Physiology, University of Toronto, Canada.

Contents lists available at ScienceDirect

Journal of Psychiatric Research

journal homepage: www.elsevier.com/locate/jpsychires

https://doi.org/10.1016/j.jpsychires.2020.09.022

Received 31 January 2020; Received in revised form 14 September 2020; Accepted 25 September 2020

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et al., 2016)) has been reported to be affected by CA. Yet, methylation of genes with other cellular functions such as cellular/neuronal plasticity has also been reported to be affected by CA (Labonte et al., 2012; Yang et al., 2013; Checknita et al., 2018), indicating that several molecular mechanisms may underlie associations between CA and mental and cognitive health outcomes later in life.

One gene important for mental and cognitive development is GRIN2B, encoding the NR2B subunit of the N-methyl-D-aspartate re- ceptor (NMDAR). NMDARs are receptors for the excitatory neurotrans- mitter glutamate and are involved in synaptic plasticity (reviewed in (Liu and Zhao, 2013; Baez et al., 2018)). Mutations in GRIN2B have been associated with neurodevelopmental and neuropsychiatric disorders such as intellectual disability, developmental dyslexia, autism spectrum disorders and schizophrenia (Platzer and Lemke, 1993; Mascheretti et al., 2015; Guo et al., 2016; Hu et al., 2016; Myers et al., 2019). In addition, specific genetic variants in GRIN2B have also been associated with major depressive disorder (MDD), specifically treatment resistant depression (Zhang et al., 2014), and suicide attempts (Sokolowski et al., 2013). In post mortem brain samples from females, but not males, higher GRIN2B gene expression has been observed in MDD patients compared to controls, where GRIN2B expression was even higher in MDD-suicide patients (Gray et al., 2015). These reports indicate that GRIN2B may play a role in depression, possibly in a sex-dependent way.

We have previously shown that methylation in a GRIN2B regulatory region is affected by chemical exposure during development (Alavian-- Ghavanini et al., 2018), and others have shown that GRIN2B methylation is altered in schizophrenia patients (Fachim et al., 2019). In the present study we hypothesised that not only chemical exposure, but also the psychological stressor CA affects GRIN2B methylation in humans. In addition, we set out to investigate if GRIN2B methylation is associated with depressive disorders, which are commonly stress-induced and associated with impaired cognitive function (Airaksinen et al., 2004).

2. Material and method 2.1. PART cohort

The samples included in this work were derived from the PART study (Lundberg et al., 2005; Liu et al., 2015), a longitudinal population based study in Stockholm, Sweden, with the aim to identify risk and protective factors for mental health. The PART study was approved by the ethical review board at Karolinska Institutet and performed according to the latest version of the Helsinki Declaration. All study participants provided written informed consent after the study had been fully explained.

Swedish nationals aged 20–64 years were randomly selected to be invited to participate in the PART study. Information regarding demographics, childhood conditions, occupation and financial status, so- matic disorders, use of drugs and psychiatric symptoms was collected through self-reported questionnaires two times (waves) for each individual, first in 1998–2000 and then 3 years later (2001–2003). Saliva was collected 2006–2007, with a nested case-control design, of those participating in wave 1 and 2 using self-administered kits (Sjoholm et al., 2009; Melas et al., 2010), from which DNA was extracted using the Oragene Purifier (DNA Genotek Inc., Canada) (Liu et al., 2015).

In our study, CA is defined as, before the age of 18, having at least two of the following adverse events: a parental death, major or severe financial problems, major or severe disturbances within the family. In- dividuals without CA did not experience any of the above mentioned adversities.

Out of the self-reported questionnaires, depression status (including major depression, mixed anxiety depression and dysthymia) was assessed according to the DSM-IV criteria using the Major Depression Inventory (MDI (Bech et al., 2001; Forsell, 2005)), the Sheehan Patient-Related (Panic) Anxiety Scale (Sheehan, 1983) and a question on duration of depressive symptoms. Depression cases were those with a depression status in at least one of the two waves. The non-depressed

study participants (controls) did not show any pathological symptoms of depression, anxiety, obsessive compulsive disorder, agoraphobia, eating disorder or social disability due to a psychological problem. In addition, controls had never received health care for a psychiatric disorder or nervous discomfort.

Alcohol consumption was assessed using the Alcohol Use Disorders Identification Test (AUDIT) consisting of 10 questions on alcohol use (Saunders et al., 1993), and the average score between wave 1 and 2 was used. Smoking (never or stopped/sometimes/regularly), education (9y/12y/>12y), occupation (no/yes), and financial stability (ability to pay 14 000 Swedish Crowns within a week in case of an unexpected situation: No/No, probably not/Yes, probably/Yes, certainly) (H¨allstr¨om et al., 2003) were self-reported in wave 2.

In total, 3018 DNA samples were collected. Of these, all individuals with CA among the depression cases and the non-depressed controls were selected (ndep = 46, nnon-dep = 57). Additionally, participants without CA were included, trying to match for depression status, sex and smoking (n_dep=46, n_non-dep=56). Demographic characteristics for all selected participants is presented in Table S1.

2.2. DNA methylation of GRIN2B

Methylation status of 4 CpG sites in the GRIN2B regulatory region (figure S1) were assessed by targeted bisulfite pyrosequencing. First, genomic DNA obtained from saliva samples was bisulfite converted using the EZ-96 DNA Methylation-Gold MagPrep kit (Zymo Research Corporation). After that, a 119 base pair (bp) fragment was amplified using the PyroMark PCR kit (Qiagen) together with 0.2 μM forward primer 5^′-TGATTTAGGGGGGAGGAGAAATT-3^′and biotinylated reverse primer 5^′-AAACTACCTCCCCCAAAATCTTAACA-3^′ and with the addition of 1 μl MgCl2 (25 mM) per 25 μl reaction, according to manufacturer’s protocol. Pyrosequencing was performed on a PyroMark Q96 ID instrument (Qiagen) using PyroMark Gold Q96 reagents (Qiagen) and 0.4 μM sequencing primer 5^′-GGAAGATATTGTTTTTGTTTTTAG-3^′ according to the manufacturer’s protocol. Methylation level at the four sequenced CpG sites were obtained using the PyroMark Q96 software.

The first CpG site in this fragment (hereafter referred to as CpG1) is identical with the Illumina 450K probe ID cg10091102. The assay was validated using standard curves of commercial DNA with known methylation status.

Samples from 205 individuals (Table S1) were analysed for GRIN2B methylation. 18 samples did not pass pyrosequencing quality check (“ok”) at all analysed CpG sites and were excluded from the analysis. In addition, one individual was regarded as an outlier (CpG1 methylation

=76%) and was thus excluded.

2.3. Statistics

Differences in characteristics at sampling between those with CA and those without CA were assessed using either Mann-Whitney-Wilcoxon Test (age, AUDIT score) or chi-squared tests (sex, depression status, smoking, education, occupation, financial stability). Correlation between variables were measured with Spearman rank correlation (Table S2) and based on the results of these analyses, the variables that correlated significantly with any CpG methylation level were added as covariates in the linear regression models to be used. Residuals of reported linear regression models were confirmed to be normally distributed.

To assess if there were any associations between CA and GRIN2B methylation, linear regression models adjusted for age and sex were used. In addition, since the measured CpG sites were correlated (Table S2), a second model was used where all measured CpG sites (except the dependent CpG variable in the specific model) were added as covariates with the aim to pick up the effect of CA on solely one specific CpG site eliminating the influence of the nearby region. Since smoking habits, level of education, occupational status and financial stability

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differed between CA and non-CA individuals, additional analyses were performed where these variables were added as covariates to the models. The analyses were also stratified for sex based on our previous observation that bisphenol A (BPA) only associates with GRIN2B DNA methylation in females (Alavian-Ghavanini et al., 2018).

Association between GRIN2B methylation and age, sex, depression, alcohol use and smoking was also investigated using linear regression models adjusted for age, sex (when possible) and CA.

All statistics were calculated using R version 3.5.1 and 4.0.2. Sta- tistical significance was set at α =0.05 since methylation at the 4 CpG sites correlated with each other (p < 0.01).

3. Results

We set out to investigate if severe adversity during childhood was associated with methylation changes in GRIN2B, a gene involved in neurodevelopment. A case-control approach was used where CA cases were selected based on having experienced at least two of the following CAs: major financial problems, major conflicts within the family and/or parental death before the age of 18 years. At sampling, the study cohort had a mean age of 56 years and consisted of 65% women and 44%

depressed individuals (Table 1). Age, sex, depression status and alcohol consumption did not differ significantly between the CA and no CA group. On the other hand, smoking habits, level of education, occupational status and financial stability differed between the two groups (Table 1), where smoking, as well as lower level of education, occupation and financial stability, was more common among individuals who had experienced CA.

GRIN2B CpG1-4 methylation level distributions differed between

individuals who had experienced CA and those who had not (Fig. 1), where CA individuals displayed higher methylation levels. To statisti- cally investigate the association between CA and GRIN2B methylation levels, linear regression models on GRIN2B CpG methylation were used.

The models were adjusted for age and sex, which were identified as potential covariates as they correlated with CpG methylation in Spearman rank correlation tests (Table S2). CA before the age of 18 years inferred higher methylation at 3 CpG sites in the GRIN2B gene (CpG1 β = 0.95 p = 0.007; CpG2 β = 0.70 p = 0.006; CpG3 β = 2.12 p = 5 × 10⁻¹⁴; Table 2). These results did not notably change when smoking, level of education, occupational status and financial stability, which differed between CA and non-CA, were added as covariates to the model (Table S3). Since the methylation levels of the different CpG sites were correlated (Table S2), these CpG sites were added as covariates in a second regression model. In this model, CA was only significantly associated with CpG3 methylation (β = 1.7 p = 2 × 10⁻¹², Table 2), suggesting that CpG3 is the main driver for the association between GRIN2B methylation and CA.

Although sex was not significantly associated with GRIN2B methyl- ation in the linear regression models (p ≥ 0.2 for all CpG sites), the test for association between CA and methylation level was stratified for sex.

Association between CA and methylation at all 4 CpG sites was more pronounced (higher beta values) in females compared to males. In females, CpG1-3 methylation was significantly associated with CA, while only CpG3 methylation was significantly associated with CA in males (Table S4).

In line with the Spearman rank correlation results (Table S2), methylation at CpG3 and CpG4 increased significantly with age in adjusted linear regression models (CpG3 β = 0.03, p = 0.008, CpG4 β = 0.02, p = 0.03, Figure S2). Also in line with the Spearman rank correlation results, neither smoking nor alcohol intake was associated with GRIN2B methylation levels in adjusted linear regression models.

In addition to investigate what may influence GRIN2B methylation, we also investigated if GRIN2B methylation levels associated with depression. However, none of the analysed CpG sites were associated with depression status in the study cohort (Fig. 2).

4. Discussion

In the present study we report, for the first time, that methylation in a GRIN2B regulatory region is higher in individuals who experienced CA.

This was seen for 3 out of 4 CpG sites studied, in particular the CpG we refer to as CpG3. These findings confirm that methylation at this region of GRIN2B is sensitive to environmental exposures early in life. While previous studies have shown an effect of physical environmental factors (chemical exposure and diet) in utero on Grin2b methylation in rodents (Yan et al., 2017; Alavian-Ghavanini et al., 2018) and a human cohort (Alavian-Ghavanini et al., 2018), our results here suggest that GRIN2B methylation act as a more general environmental “sensor”, affected also by psychological stress in childhood. This finding can increase the un- derstanding of how early life stress may influence neural development on a molecular level, possibly being one underlying link between CA and psychiatric and/or cognitive adversities later in life.

The specific GRIN2B region analysed in the present study was chosen based on our previous experimental findings showing that in rat hippocampus, increased methylation in a well-conserved region of this specific GRIN2B sequence was correlated with lower Grin2b expression (Alavian-Ghavanini et al., 2018). This suggests that methylation in this region affects gene function, in the case of higher methylation resulting in decreased GRIN2B expression.

We could not find an association between GRIN2B methylation and depression, and therefore the association between CA and depression reported by us (Lavebratt et al., 2010; Melas et al., 2013) and others (Collishaw et al., 2007; Widom et al., 2007; Liu, 2017) is likely to be mediated through other pathways. This negative finding may not be surprising since genetic variations in GRIN2B have been more often Table 1

Demographics of the study groups.

No childhood

adversity (n = 89) Childhood

adversity (n = 97) p^f Characteristics at sampling

Mean age (SD) 55.0 (11.9) 57.7 (10.6) 0.13

Female sex 66% (59/89) 64% (62/97) 0.85

Depressed 45% (40/89) 42% (41/97) 0.83

Smokers^a 10% (9/87) 27% (26/95) < 0.01

Harmful alcohol

consumption^b 8% (7/88) 5% (5/96) 0.35

High school education

c 87% (77/89) 62% (60/96) < 0.01

Occupation^d 88% (78/89) 70% (68/96) < 0.01

Financial stability ^e 95% (84/89) 78% (76/96) < 0.01 Events during childhood (<18 years)

Major financial

problems 0% (0/89) 91% (88/97) < 0.01

Major conflicts within

the family 0% (0/89) 84% (81/97) < 0.01

Parental death 0% (0/89) 35% (34/97) < 0.01

Parents divorced 0% (0/89) 31% (30/97) < 0.01

All individuals included in the study analyses had passed the quality control (QC) for all four investigated CpG sites. Demographics for all individuals, including also the 19 who did not pass the QC, are presented in Table S1. Data was missing for smoking (n = 4), alcohol consumption (n = 2), education (n = 1), occupation (n = 1) and financial stability (n = 1).

a% individuals who reported regular cigarette smoking, compared to individuals who reported no, stopped or sometimes smoking.

b AUDIT score >8 (Saunders et al., 1993).

cAt least 12 years of education.

dHaving an occupation includes full time and part time employment, self- employment, studying and maternity/paternity leave.

eFinancial stability is here defined to be able to, or probably able to, obtain 14 000 Swedish Crowns within a week in case of an unforeseen and sudden situation.

fp-values calculated using either Mann-Whitney-Wilcoxon Test (age, AUDIT score) or chi-squared tests (sex, depression status, smoking, education, occupation, financial status and childhood events).

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associated with cognitive impairments like intellectual disability as well as language and learning disorders (Hu et al., 2016; Myers et al., 2019).

If the CA associated increase in GRIN2B methylation has a mediating function in the association between CA and impaired cognitive functioning reported by others (Gould et al., 2012; Petkus et al., 2018) will be subject of future investigation.

4.1. Limitations

Firstly, childhood adversity was retrospectively self-reported, hence recall as well as subjectivity might be a limitation in this study. Also, the PART study provides only data on selected CA events, not including physical and sexual abuse. In addition, information regarding other exposures, like chemical exposures, is lacking in this study. Secondly, information about the exact age at which the adversity took place is missing in our data. This may decrease sensitivity of the analyses as it has been shown that effects on DNA methylation are more pronounced if the adversity happens before the age of 3 compared to later in life (Dunn et al., 2019). Also, the age at sample collection range from 20 to 64 years, which introduces a variation in time interval between a CA event and sampling. Thirdly, our data is obtained in the surrogate tissue saliva, while GRIN2B methylation in brain would be of foremost interest considering its functions. Finally, information regarding age at depression onset is lacking in our data, and the depression status was deter- mined based on validated self-reported questionnaires.

5. Conclusion

In conclusion, our study shows for the first time that childhood adversity is associated with increased methylation levels at a regulatory region of GRIN2B, a gene important for neurodevelopment. This con- firms the notion that the investigated region is sensitive to environmental stressors (physical and psychological) in early life. No association was found between GRIN2B methylation at this region and depression status, which suggests that this GRIN2B methylation does not affect susceptibility to depressive disorders.

Fig. 1. Distribution of DNA methylation at four CpG sites in a regulatory region of the GRIN2B gene. CA = Persons who experienced childhood adversity, No CA = Persons without reported childhood adversity. The dashed lines indicate the median values of the two groups (red = CA, blue = No CA). Reported p-values represent the associations between CA and CpG methylation levels, obtained from linear regression models on GRIN2B methylation adjusted for age and sex. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Table 2

Association between childhood adversity (CA) and GRIN2B methylation.

Model 1 Model 2 Model 3

Unadjusted^a Age & sex^b Age, sex & CpGs ^c

beta (SE) p beta (SE) p beta (SE) p

CpG1 0.96

(0.35) 6.0E-

03 0.95

(0.35) 7.4E-

03 −0.14

(0.37) 0.72 CpG2 0.74

(0.25) 3.2E-

03 0.70

(0.25) 5.8E-

03 0.06 (0.27) 0.83 CpG3 2.20

(0.26) 8.3E-

15 2.12

(0.26) 4.6E-

14 1.71 (0.23) 2.1E- CpG4 0.35 12

(0.23) 0.13 0.28

(0.23) 0.22 −0.48

(0.24) 0.05 Results from three different linear regression models on GRIN2B CpG methyl- ation. Bold font indicates statistical significant (p < 0.05) association between CA and methylation level. Beta = unstandardized beta values, SE = std error of the unstandardized beta. N = 186.

aModel 1: Unadjusted.

b Model 2 Adjusted for age & sex.

cModel 3: Adjusted for age, sex & the methylation level of the 3 other CpG sites.

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Author statement

EE: Data curation, Formal analysis, Funding acquisition, Writing - original draft. AAG: Investigation, Writing - review & editing. YF:

Funding acquisition, Resources, Writing - review & editing. CL:

Conceptualization, Funding acquisition, Project administration (PART), Methodology, Resources, Writing - review & editing. JR: Conceptuali- zation, Resources, Writing - review & editing.

Funding statement

This work was supported by the Swedish Research Council [www.vr.

se; grant numbers 2009-5546, 2010-3631, 2014-10171], the Karolinska Institutet’s Faculty Funds and Research Foundation Grants [https://fon der.ki.se; grant number 2018-01508], the regional agreement on med- ical training and clinical research between Stockholm County Council and Karolinska Institutet [www.forskningsstod.sll.se; grant numbers SLL20170292, SLL20140484, SLL20110560, 20090281], the Swedish Brain Foundation [grant numbers FO2017-0129, FO2018-0141]. The funders had no role in study design, data collection and analysis, deci- sion to publish, or preparation of the manuscript.

Declaration of competing interest

The authors declare no conflict of interest.

Acknowledgement

We want to thank Mandy Tang for technical assistance on the bisulfite pyrosequencing.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.

org/10.1016/j.jpsychires.2020.09.022.

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Fig. 2. GRIN2B methylation levels in depressed and non-depressed individuals, with and without childhood adversity (CA). Each grey dot represents CpG methylation of one individual, and the overlying coloured box plots indicate median value and the interquartile range (IQR) plus whiskers up to the lowest/highest value < 1.5 x IQR. The association between CpG methylation and depression was investigated in linear regression models on depression status adjusted for age, sex and CA. ns = not significant (p > 0.05), No CA = Persons without reported childhood adversity, CA = Persons who experienced childhood adversity. (For inter- pretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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