Longitudinal Analysis of Estrogen Receptor Gene Methylation, Estradiol, and Depressive Symptoms during the Perinatal Period

Longitudinal Analysis of Estrogen Receptor Gene Methylation, Estradiol, and Depressive Symptoms during the Perinatal Period | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Longitudinal Analysis of Estrogen Receptor Gene Methylation, Estradiol, and Depressive Symptoms during the Perinatal Period Gianna Zorzini, Alexandra Johann, Jelena Dukic, Elena Gardini, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6578336/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Dec, 2025 Read the published version in Molecular Neurobiology → Version 1 posted 10 You are reading this latest preprint version Abstract Background: DNA methylation of estrogen receptor genes ( ESR1 , ESR2 , and GPER ) may affect expression of the estrogen receptors (ERs) alpha, beta, and G protein-coupled estrogen receptor (GPER). Altered receptor expression may in turn affect the receptors’ sensitivity to estrogen, thereby modulating vulnerability to depression during periods of estrogen fluctuation. The aim of this study was to investigate the association between methylation of ESR1 , ESR2 , and GPER , depressive symptoms, and estradiol during the perinatal period using a longitudinal design. Methods: A total of 159 women were followed longitudinally from 34-36 weeks of gestation to 8-12 weeks postpartum. Depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS). Salivary estradiol levels were quantified, and DNA methylation was analyzed using dried blood spots. Multivariate linear regressions and paired t-tests were used for analysis. Results: Depressive symptoms were negatively associated with the mean overall ESR1 methylation during pregnancy ( β =-0.41 , p =0.002 ) , but not during the postpartum period ( p ≥0.05). No associations emerged for ESR2 , GPER , or estradiol at either time point (all p ≥0.05). The mean overall methylation of ESR1 increased from pregnancy to postpartum (t=-2.59, p =0.012) and was positively associated with depressive symptom scores during pregnancy ( β =0.418, p =0.031). Conclusion: This work suggests that lower DNA methylation levels of ESR1 , which may reflect higher ER-alpha expression and thus greater sensitivity to estrogen, are associated with increased depressive symptoms during pregnancy. The findings highlight molecular pathways of estrogen sensitivity, particularly via ER-alpha, as a promising target for future biomarker research for perinatal depression. estrogen receptor epigenetics DNA methylation perinatal depression Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Women are particularly susceptible to depression during phases of pronounced sex steroid hormone fluctuations, such as the premenstrual, perinatal, and perimenopausal periods [ 1 – 3 ]. Moreover, the occurrence of depression during one of these reproductive transitions appears to be associated with an increased risk of depression during the respective other phases [ 4 – 6 ], leading to the suggestion of a reproductive subtype of depression [ 7 ]. There is growing evidence to support the existence of this subtype, particularly regarding perinatal depression, which refers to depression arising during pregnancy or up to one year postpartum [ 8 ]. Depression during this period seems to be characterized by distinct symptoms, severity, heritability patterns, and epigenetic marks compared to depression occurring outside reproductive transitions [ 9 – 11 ]. Moreover, with a reported prevalence of 17%, and presumably even higher rates of undetected cases, the perinatal period represents a time of high vulnerability to developing depression [ 12 , 13 ]. Perinatal depression is particularly concerning if left undetected and therefore untreated, as it is associated with far-reaching implications, not only for the woman but also for her offspring [ 14 – 16 ]. However, despite the well-documented prevalence, symptomatology, and consequences of perinatal depression, the biological underpinnings remain unclear, therefore impeding the identification of reliable biomarkers for early detection and thus treatment initiation [ 17 ]. Although each female reproductive transition is characterized by unique fluctuations in sex steroid hormones, these fluctuations are considered as important biological triggers for depression during reproductive transition phases [ 11 ]. Regarding the perinatal period, sex steroid hormones are found to increase strongly during pregnancy, followed by a sharp decrease after delivery [ 18 ]. However, only some women appear to be sensitive to these fluctuations and therefore vulnerable to depression during this period [ 19 – 21 ]. For instance, studies examining affective symptoms in multiparous women following a pharmacological simulation of the perinatal hormonal fluctuations have reported an increase in depressive symptoms in women with a history of perinatal depression but not in those without [ 22 , 23 ]. Research exploring this sensitivity at the molecular level has specifically highlighted the involvement of estrogen signaling pathways. In detail, women with perinatal depression were found to exhibit an enrichment of transcripts involved in estrogen signaling compared to healthy controls, indicating an increased sensitivity to estrogen in affected women [ 24 ]. As such, sensitivity to estrogen has been suggested as a key pathway in mediating susceptibility to perinatal depression [ 21 , 24 , 25 ]. The physiological response to fluctuating estrogen levels depends on the capacity of estrogen receptors (ERs) [ 26 ]. The ERs, encompassing ER-α, ER-β, and the G protein-coupled ER (GPER), mediate the biological effects of estrogen through genomic and non-genomic pathways after binding to the hormone [ 27 ]. Given the widespread distribution of ERs throughout the body, the biological effects of estrogen are manifold [ 28 ]. In the brain, ERs are predominantly expressed in limbic regions, where estrogen has been found to modulate neurotransmitters such as gamma-aminobutyric acid (GABA), serotonin, dopamine, and glutamate, ultimately regulating emotional and cognitive functions [ 29 – 31 ]. However, the efficacy of the ERs in responding to fluctuating estrogen levels depends, at least in part, on their expression levels [ 32 , 33 ] DNA methylation (DNAm) of the ER genes ESR1 , ESR2 , and GPER , which encode ER-α, ER-β, and GPER, respectively, has the function of adjusting the expression levels of the receptors [ 34 ]. DNAm refers to the binding of methyl groups at cytosines in cytosine-guanine dinucleotides (CpGs), without changing the underlying DNA sequence itself [ 35 ]. This epigenetic modification can alter DNA accessibility, thereby affecting gene transcription and gene expression [ 36 – 38 ]. For instance, hypermethylation of the promoter regions of ER genes has been associated with reduced gene expression, while hypomethylation has been linked to increased ER levels [ 39 – 41 ]. Although several epigenome-wide association studies (EWAS) have identified associations between DNAm marks implicated in estrogen signaling and depression during the perinatal period, biomarkers for clinical use remain to be investigated [ 17 , 25 , 42 , 43 ]. While EWAS offer broad insights across the whole genome, they are often burdened by multiple testing correction, which reduces the statistical power and thus the ability to detect subtle but biologically meaningful associations [ 44 ]. However, studies using a targeted approach to investigat ER gene methylation in association with perinatal depression are lacking [ 45 ]. Moreover, DNAm has the ability to change over time, which has also been observed during the perinatal period [ 46 , 47 ]. Consequently, it is important to take this variability into consideration in order to identify reliable biomarkers [ 48 ]. While longitudinal courses of DNAm and potentially implicated factors remain understudied, findings from a cross-sectional study by our research group suggest that DNAm of ER genes may change over time [ 49 ]. In detail, differences in ESR1 DNAm levels emerged between pre- and postmenopausal women, and estradiol levels were found to be positively associated with ESR1 DNAm in both groups. Thus, in view of the pronounced estrogen fluctuations during the perinatal period and the observed effects of estrogen on DNAm at various CpGs [ 18 , 50 ], estrogen may play a crucial role in epigenetic regulation during the perinatal period. However, to date, no study has longitudinally examined DNAm of the ER genes, its relationship to estradiol, and its possible association with depressive symptoms during the perinatal period. This research gap limits the ability to form a comprehensive understanding and the identification of biomarkers for early detection. The aim of this study was to investigate the association between DNAm of promoter regions in ESR1 , ESR2 , and GPER , depressive symptoms, and estradiol levels during the perinatal period using a longitudinal design. Based on previous research and theoretical considerations, we hypothesized that depressive symptoms and estradiol levels would be associated with DNAm levels of promoter regions in ESR1, ESR2 , and GPER in pregnant and postpartum women. We further assumed that these DNAm marks would change during the transition from pregnancy to the postpartum period, and that this change would be associated with depressive symptoms and estradiol levels. Methods This study was part of a larger longitudinal research project on (epi-)genetic, biological, and psychological factors implicated in female mood disorders during the transition from pregnancy to postpartum. All participants provided informed consent prior to data collection, which took place between June 2019 and June 2021. The research project was carried out at the University of Zurich, Department of Clinical Psychology and Psychotherapy. The project was approved by the Ethics Committee of the Canton of Zurich (KEK-ZH-Nr. 2018-02357) and conducted in accordance with the principles of the Declaration of Helsinki. The present study investigated associations between DNAm of ER genes, depressive symptoms, and estradiol during the transition from pregnancy to postpartum. Participants Physically healthy women between aged between 20 and 45 years were recruited during their third trimester of pregnancy. The participants were followed from 34-36 weeks of gestation up to 8-12 weeks postpartum, encompassing a mean study duration of 17 weeks per participant. Detailed information on the participants, recruitment process, and eligibility criteria can be found elsewhere [51–53]. For epigenetic analyses, the original sample size (N=161) was reduced to n=159, as one participant did not provide written informed consent to use (epi-)genetic data, and one participant did not provide blood samples. Procedure Women interested in participating in the study were first screened for eligibility using an online questionnaire. Eligible participants were then invited to a telephone interview to confirm the inclusion and exclusion criteria. After successful inclusion, the first laboratory visit took place at around 34-36 weeks of gestation at the University of Zurich, Department of Clinical Psychology and Psychotherapy. During this visit, which started between 8 and 9 am, various psychological, biological, and (epi-)genetic parameters were assessed. Additionally, the participants were given instructions on carrying out the five home assessments, which encompassed the independent collection of saliva samples and several online questionnaires. After completion of the home assessments, the participants were invited for a second laboratory visit at approximately 8-12 weeks postpartum. During this visit, the same parameters as during the first visit were assessed, along with birth-related information. Assessment of perinatal mood The German version of the Edinburgh Postnatal Depression Scale (EPDS) was used to assess depressive symptoms [54, 55]. The EPDS is a validated self-report screening tool to assess depressive symptoms during pregnancy and the postpartum period, with 10 items rated on a 4-point Likert scale. The original validation of the German version of the EPDS showed good internal consistency, with Cronbach’s α = 0.81 [54]. Participants completed the EPDS at both laboratory visits, as well as on the first day of each home assessment time point. In the present study, we used the EPDS scores from both laboratory visits. Blood sampling The participants provided up to five drops of blood (about 50 µL per drop) during the laboratory visits at 34-36 weeks of gestation and 8-12 weeks postpartum. Blood samples were collected through finger prick using the dried blood spot (DBS) method with standardized filter paper (No. 903 Whatman, DBS Protein Saver Card). The samples were dried for 3-4 hours at room temperature before being stored at -20°C at the laboratory of the University of Zurich until further biochemical analysis. Saliva sampling Saliva samples were collected using the passive drool method with SaliCap sampling tubes (IBL International GMBH, Hamburg, Germany). The participants were instructed to collect a targeted total of 52 saliva samples. Samples were collected on two consecutive days at 34-36 weeks of gestation, 40 weeks of gestation, 4-8 weeks postpartum, and 8-12 weeks postpartum. Additionally, the participants provided samples on five consecutive days, starting within the first 48 hours after delivery. On each assessment day, four saliva samples were provided: three in the morning (immediately after awakening, 30 and 45 min after awakening) and one in the evening between 8 and 10 pm. The samples were stored in the participants’ home freezers until the second laboratory visit, whereupon they were stored at -20°C at the laboratory of the University of Zurich until further biochemical analysis. Estradiol Assessment As salivary assessment of steroid hormones is a reliable marker of serum steroid levels [56, 57], saliva samples were used to quantify estradiol (E2) levels. Salivary E2 (pg/mL) was determined using luminescence immunoassay with enzyme-linked immunosorbent assay (ELISA) kits (IBL International GmbH, Hamburg, Germany, catalog number RE62141/RE62149). Estradiol determinations were performed by Dresden LabService GmbH in Dresden, Germany. In accordance with the manufacturer’s instructions, the standard range for E2 was between 2-64 pg/ml and the highest cross-reactivity was with Estrone, at around 14%. The inter- and intraassay coefficients of variability were 9.5% and <6%, respectively. E2 values were only available for n=126 participants. Missing E2 values were imputed using predictive mean matching (pmm) from the mice package in R (version 4.3.2) [58], generating 50 imputation datasets to account for the uncertainty introduced by imputing missing values. In this study, mean estradiol values from the first day of the assessment at around 34-36 weeks of gestation and 8-12 weeks postpartum were used to account for inter-day variability. Methylation analysis Genomic DNA was extracted from DBS, and was reported to provide reliable results in the context of methylation analysis [59]. Three punches of 3.0 mm diameter DBS were used to extract DNA with the QIAamp DNA Investigator Kit (QIAGEN, Hilden, Germany), in accordance with the manufacturer’s instructions. Additionally, duplicates and negative controls (samples without DNA) were included for quality control. The extracted DNA and negative controls were eluted in a final volume of 30μL RNase-free water. DNA concentration was assessed using NanoDrop (Thermo Fischer Scientific, Waltham, MA, USA) and ranged from 9.04 to 86.67 ng. DNA extraction was performed by a trained biologist in our laboratory at the University of Zurich, Department of Clinical Psychology, while subsequent steps were carried out at the Genetic Diversity Centre (GDC), ETH Zurich. Genomic DNA was bisulfite-converted using the EZ-96 DNA Methylation-Lightning Kit D5032 (Zymo Research, Irvine, CA, USA) in accordance with the manufacturer’s instructions, which recommend using samples containing 0.5-2000 ng of DNA. An initial polymerase chain reaction (PCR) was performed on the bisulfite-treated DNA using the Kapa HiFi Uracil+ master mix (Kapa Biosystems, Wilmington, MA, USA). Primers included the universal oligonucleotides CS1/CS2 at the 5ʹ ends (Fluidigm, San Francisco, CA, USA), which are used for customized next-generation sequencing (NGS; see Table 1). The primers were designed to target the specific DNA sequence of the ESR1 shore of promoter C (hg 38; chr6:151805523-151805822, Figure 1A), the ESR2 promoter 0N (hg 38; chr14: 64,760,866- 64,761,269, Figure 1B), and the GPER promoter (hg 38; chr7:1087059-1087533, Figure 1C). The PCR conditions were set to an initial temperature of 95°C for 3 min, followed by 30x (98°C for 20s, annealing temperature for 15s, and 72°C for 15s), and a final elongation at 72°C for 40s. The annealing temperature varied for each sequence (see Table 1). Subsequently, a second PCR was performed with an initial temperature of 95°C for 3 min, then 20x (98°C for 20s, annealing temperature for 15s, 72°C for 15s), and a final elongation at 72°C for 40s. After the second PCR, amplicons were purified using KingFisher (Thermo Fisher Scientific, Waltham, MA, USA). Table 1 PCR primers used for amplification of DNA sequences in the ESR1 , ESR2 and GPER . Gene Forward Primer Reverse primer GRCh38 AT (°C) ESR1 ACACTGACGACATGGTTCTACA NNN GTTTTTTGTGAGTAGATAGTAAGTT TACGGTAGCAGAGACTTGGTCT NNN AAACCTACCCTACTAAATCAAAAAC chr6: 151,805,523-151,805,822 55 ESR2 ACACTGACGACATGGTTCTACA NNN TTATTATTTTTGTGGGTGGAT TACGGTAGCAGAGACTTGGTCT NNN CACCTCCTACAACTCAAACTC chr14: 64,760,866- 64,761,269 59 GPER ACACTGACGACATGGTTCTACA NNN AGTGAAAATTTAAATGGTTAGTA TACGGTAGCAGAGACTTGGTCT NNN ACAATCCAAACAATTCAAAATTTATTT chr7: 1,087,059- 1,087,533 57 Note: Universal primer CS1 = ACACTGACGACATGGTTCTACA, universal primer CS2 = TACGGTAGCAGAGACTTGGTCT. Abbreviations: PCR = polymerase chain reaction; ESR1 = estrogen receptor alpha gene; ESR2 = estrogen receptor beta gene; GPER = G protein-coupled estrogen receptor gene; GRCh38 = Genome Reference Consortium Human Build 38 Organism; AT = annealing temperature Purified amplicons were then indexed with customized single barcodes (Fluidigm, San Francisco, CA, USA) using a third PCR with the conditions set to 95°C for 3 min, then 10x (98°C for 20s, 58°C for 15s, 72°C for 15s), and a final elongation at 72°C for 40s. The indexed amplicons were eluted in 15μL RNase-free water and again purified using KingFisher (Thermo Fisher Scientific, Waltham, MA, USA). The purified indexed amplicons were quantified using Sparke Plate Reader (TECAN Spark, Tecan Group Ltd, Maennedorf, Switzerland), before normalization and pooling were conducted. After a final purification with AMPure XP beads, the pool was quantified using the Agilent 2200 Tape Station instrument and HS DNA 1000 reagents (Agilent Scientific Instruments, Santa Clara, CA, USA) and Quibit (Thermo Fischer Scientific, Waltham, MA, USA). The pool was then diluted to a final molarity of 4 nM. PhiX spike-in (15%) was added to the library to increase the diversity of base calling during sequencing. The final library was sequenced on the Illumina MiSeq using the V3, 600 cycles kit (300 PE; Illumina, San Diego, CA, USA). Low-quality products were removed using Trimmomatic v0.35 (http://www.usadellab.org/cms/index.php?page=trimmomatic; [60]. The remaining sequencing reads were aligned to the target regions. The Bismark program (v0.19.0) was used to extract the number of methylated (cytosine) and non-methylated (thymine) bases. A total of 33, 18, and 12 samples in ESR1 , ESR2 , and GPER , respectively, showed zero coverage (no aligned reads detected) and were thus missing. In accordance with [61], a minimum threshold of 100 reads was set. For ESR1 , ESR2 , and GPER , 80, 67, and 88 samples, respectively, did not reach this threshold and were thus excluded. For the remaining samples, coverage ranged from 109 to 325’599 for ESR1 , from 106 to 829’507 for ESR2 , and from 111 to 292’350 for GPER . Moreover, samples with a significant deviation (± 3 times the interquartile range (IQR)) were excluded. For ESR1 , ESR2, and GPER , 7, 16, and 8 samples, respectively, were below or above the IQR and thus excluded. After the exclusion of these outliers, the methylation levels reached normal distribution for all three sequences. Statistical analysis All analyses were performed using the overall mean DNAm levels of the 9, 30, and 22 CpGs in ESR1 , ESR2 , and GPER, respectively, and the DNAm levels of the individual CpGs in ESR1 . To examine the associations between depressive symptoms, E2 levels, age, and DNAm during pregnancy and the postpartum period, we performed Spearman or Pearson correlations, depending on normality of the data. Moreover, multivariate linear regression analyses were conducted to assess the effect of depressive symptoms and E2 levels on DNAm in pregnancy and the postpartum period, while controlling for maternal age and history of depression. Paired t-tests were used to investigate DNAm changes from pregnancy to postpartum. In case of significant DNAm changes, multivariate linear regressions were calculated with the corresponding DNAm delta scores, while controlling for the previously mentioned covariates. Two sets of predictors were used: depressive symptom scores and E2 levels obtained at 34-36 weeks of gestation, and delta scores of depressive symptoms and E2 levels. All statistical tests were two-sided, and the significance level was set at p ≤ 0.05. To correct for multiple testing, the Benjamini-Hochberg method [62] was used, with the significance threshold set at q ≤ 0.1. We found no issues with multicollinearity, which was assessed using the variance inflation factor (VIF; all VIFs were < 2). All statistical analyses were performed using R (version 4.3.2; R Project). Results Sample characteristics Sample sizes varied between variables due to the missing data. Descriptive statistics were therefore calculated for all available data points for each variable used in this study (see Table 2). Participant’s age ranged between 21 to 43 years, with a median of 33 years. Moreover, all participants (n=159) were of self-reported European ancestry, with the majority reporting being Swiss (71.7%). More information on sociodemographic characteristics can be found elsewhere [51, 53]. Table 2 Descriptive statistics of biological and psychological measures. Variable 34-36 weeks of gestation 8-12 weeks postpartum N M(SD) N M(SD) ESR1 CpGI shore methylation (%) 69 72.83(5.47) 134 74.06(5.77) CpG 1 methylation (%) 69 61.76(11.34) 134 62.57(13.78) CpG 2 methylation (%) 69 76.83(9.35) 134 77.02(11.05) CpG 3 methylation (%) 69 83.20(7.84) 134 84.35(8.36) CpG 4 methylation (%) 69 78.39(8.97) 134 80.22(9.66) CpG 5 methylation (%) 69 81.37(7.58) 134 81.35(10.28) CpG 6 methylation (%) 69 83.60(11.95) 134 84.73(10.15) CpG 7 methylation (%) 69 82.84(5.12) 134 83.16(8.68) CpG 8 methylation (%) 69 31.05(5.66) 134 31.55(6.5) CpG 9 methylation (%) 69 76.44(8.70) 134 80.18(9.09) ESR2 promoter 0N methylation (%) 92 0.75(0.32) 127 0.76(0.44) GPER promoter methylation (%) 70 13.65(3.43) 140 14.35(4.97) E2 (pg/mL) 126 43.00(7.82) 126 3.66(1.91) EPDS 159 4.78(4.31) 154 4.01(4.40) Note. E2 estradiol, EPDS Edinburgh Postnatal Depression Scale. DNA methylation, depressive symptoms, and estradiol Third trimester of pregnancy Correlation results are displayed in additional file 1, Table S1-2. Spearman’s rank-order correlations revealed a weak negative association between depressive symptom scores and both overall ESR1 DNAm (ρ=-0.29, p =0.013, n=69) and DNAm of the CpG 1 in ESR1 (ρ=-0.24, p =0.04, n=69). Additionally, a moderate negative association emerged between depressive symptom scores and DNAm of CpG 2 in ESR1 (ρ=-0.39, p =0.0007, n=69). Pearson’s correlations revealed a weak positive correlation between E2 levels and DNAm of CpG 5 in ESR1 (r=0.28, p =0.03, n=69). No further correlations were found between any of the investigated variables (all p >0.05). Results of the multivariate linear regressions during pregnancy are displayed in Table 3. Depressive symptoms were associated with the overall ESR1 DNAm, as well as the DNAm of four of its individual CpGs, all of which all remained significant after correction for multiple testing. In detail, increased depressive symptom scores were associated with lower DNAm levels (see Figure 2). E2 levels were not found to be associated with the overall ESR1 , ESR2 , and GPER DNAm or with the DNAm of any of the individual CpGs in ESR1 (all p >0.05). Table 3 Results of multivariate linear regressions during the third trimester of pregnancy. Methylation (%) EPDS E2 Age History of depression Adjusted β p Adjusted β p Adjusted β p Adjusted β p ESR1 -0.41 0.002* a 0.087 0.496 0.047 0.710 0.083 0.530 CpG 1 -0.365 0.006* a 0.092 0.465 0.028 0.824 0.214 0.105 CpG 2 -0.489 0.003* a 0.055 0.662 0.126 0.317 -0.026 0.843 CpG 3 -0.171 0.242 0.044 0.756 -0.061 0.666 0.085 0.564 CpG 4 -0.318 0.028* a 0.096 0.481 -0.014 0.917 -0.089 0.053 CpG 5 -0.288 0.035* a 0.257 0.050 0.121 0.352 0.094 0.485 CpG 6 -0.110 0.451 -0.189 0.184 0.040 0.776 0.031 0.830 CpG 7 -0.208 0.153 0.084 0.547 0.063 0.655 0.057 0.693 CpG 8 -0.255 0.071 0.217 0.109 -0.057 0.669 0.103 0.459 CpG 9 -0.222 0.129 0.073 0.601 0.003 0.981 0.047 0.745 ESR2 -0.026 0.833 0.165 0.166 -0.111 0.363 0.060 0.633 GPER 0.141 0.329 0.115 0.392 -0.214 0.117 -0.238 0.104 Note. *p ≤ 0.05, a significant after correction for multiple testing, EPDS Edinburgh Postnatal Depression Scale, E2 estradiol. Postpartum period Correlation results are displayed in Table S3-4. Spearman’s rank correlations revealed a weak significant positive correlation between E2 levels and both overall GPER DNAm (ρ=0.21, p =0.02, n=111) and depressive symptom scores (ρ=0.21, p =0.01, n=124). No further correlations emerged between any of the assessed variables (all p >0.05). Multivariate linear regressions revealed no associations of depressive symptoms and E2 levels with the overall ESR1 , ESR2 , and GPER DNAm or with the DNAm of any of the individual CpGs in ESR1 (all p >0.05, see Table S5). DNA methylation changes from pregnancy to postpartum Results of the paired t-tests regarding DNAm changes in ER genes during the transition from pregnancy to postpartum are displayed in Table 4. Significant changes were only found for the overall ESR1 DNAm, and for the DNAm of the individual CpG 9 in ESR1 , which were both found to increase (see Figure 3). Both of these DNAm changes remained significant after correction for multiple testing. Table 4 Results of the paired t-tests of the methylation changes from pregnancy to postpartum. Methylation (%) N 34-36 weeks of gestation 8-12 weeks postpartum t-statistics p Cohen’s d M SD M SD ESR1 60 72.62 5.67 74.52 6.12 2.590 0.012* a 0.334 CpG 1 60 61.48 11.31 62.24 16.93 0.311 0.756 0.040 CpG 2 60 76.10 9.39 76.82 12.74 0.430 0.668 0.055 CpG 3 60 83.66 7.08 84.94 9.18 0.918 0.361 0.118 CpG 4 60 78.08 9.46 79.73 9.53 1.041 0.302 0.134 CpG 5 60 81.04 7.87 81.19 11.78 0.096 0.923 0.012 CpG 6 60 83.24 12.73 84.85 7.46 0.962 0.339 0.124 CpG 7 60 82.76 5.35 83.21 10.81 0.339 0.735 0.043 CpG 8 60 31.31 5.60 31.49 7.49 0.156 0.876 0.020 CpG 9 60 75.87 9.12 80.79 9.57 3.151 0.002* a 0.406 ESR2 71 0.79 0.31 0.79 0.42 0.012 0.990 0.001 GPER 62 13.72 3.6 14.65 5.3 1.095 0.277 0.139 Note. * p ≤ .05, a significant after correction for multiple testing. Change scores from pregnancy to postpartum Change scores (delta values) were only calculated for the entire ESR1 DNAm and for the DNAm of the individual CpG 9 in ESR1 , as only these changed significantly during the transition from pregnancy to postpartum. Multivariate linear regression analysis did not reveal any significant associations when using delta scores of the predictors (all p >0.05, see Table S6). However, when using scores at 34-36 weeks of gestation for the predictors, a significant effect was found for delta scores of overall ESR1 DNAm (see Table S7). Specifically, depressive symptoms at 34-36 weeks of gestation showed a significant positive association with overall ESR1 delta DNAm ( β =0.311, p =0.036, see Figure 4). This finding remained significant after correction for multiple testing. Discussion This longitudinal study investigated the association between DNAm of ER genes ( ESR1 , ESR2 , and GPER ), estradiol, and depressive symptoms during the transition from pregnancy to the postpartum period. Mean DNAm levels varied across the genes analyzed, with ESR1 showing intermediate methylation, ESR2 almost absent methylation, and GPER low methylation during both pregnancy and the postpartum period. During pregnancy, depressive symptoms were found to be negatively associated with the overall DNAm of the CpGI shore of ESR1 and with four of its individual CpGs (CpG 1, CpG 2, CpG 4, and CpG 5). During the postpartum period, no associations were identified between depressive symptoms and DNAm of the three genes analyzed. Likewise, estradiol was not found to be associated with DNAm of any of the three genes at either time point. In addition, the overall DNAm of the CpGI shore of ESR1 and its individual CpG 9 increased from pregnancy to the postpartum period. Although changes in estradiol levels and depressive symptoms were not linked to these DNAm changes, higher depressive symptoms at 34–36 weeks of gestation were associated with a larger increase in the overall DNAm of the CpGI shore of ESR1 . Recently a systematic review by our research group described that sensitivity to estrogen signaling, in particular via ER-α, is associated with perinatal depression [ 63 ]. Markers of this sensitivity can help to identify women at risk. In this vein, the present study revealed that DNAm of the CpGI shore of ESR1 , encoding for ER-α, was associated with depressive symptoms during pregnancy, whereas no such association was found for ESR2 and GPER . These results support the assumption from other genetic studies that ER-α plays a more important role in mood regulation than do ER-β and GPER, which might be explained by its predominant expression in neuronal areas implicated in emotional functions, such as the amygdala and hypothalamus, compared to other ERs [ 64 , 65 ]. Interestingly, lower DNAm levels of the overall CpGI shore of ESR1 and its individual CpG 1, CpG 2, CpG 4, and CpG 5 were associated with increased depressive symptom scores during pregnancy. Notably, higher DNAm levels of the CpGI shore of ESR1 have been associated with lower mRNA expression of ER-α [ 66 ]. Moreover, DNAm of one of these individual CpGs, namely CpG 4, was previously found to be negatively correlated with ER-α expression [ 67 ]. Therefore, we suggest that lower DNAm levels of the CpGI shore of ESR1 , particularly at CpG4, may upregulate ER-α expression, thereby increasing sensitivity to estrogen and thus susceptibility to depressive symptoms during pregnancy, when estrogen levels are high. Previous cross-sectional findings by our research group indicated that mean DNAm levels of the CpGI shore of ESR1 are associated with estradiol levels within different menopausal groups [ 49 ]. In detail, estradiol was positively associated with ESR1 DNAm in pre- and postmenopausal women, while a negative association was found in perimenopausal women. Contrary to our expectation, in the present study, no associations were observed between estradiol levels and DNAm levels of any ER gene in either pregnant or postpartum women. Nevertheless, a trend emerged for the DNAm of CpG 5 of the CpGI shore of ESR1 , showing a positive association with estradiol in pregnant women and a negative association in postpartum women. Additionally, a trend towards a positive association between estradiol and GPER DNAm was observed in postpartum women. These findings may reflect a subtle but dynamic and context-dependent hormonal regulation of ER gene DNAm during the perinatal period. The lack of robust associations may be due to the specific period investigated, which encompasses pronounced hormonal fluctuations. Therefore, single time point measurements may not capture the dynamic interplay between fluctuating hormone levels and DNAm, limiting our ability to detect potential long-term exposures relevant to DNAm. In contrast to genetic variations, DNAm is an epigenetic modification that can change over time, a dynamic that has also been observed for various CpGs during the perinatal period [ 46 , 47 ]. Supporting this, the present longitudinal analysis revealed that overall DNAm of the CpGI shore of ESR1 and its individual CpG 9 increased from pregnancy to the postpartum period. Interestingly, DNAm of the CpG 9 has also been found to differ cross-sectionally between pre- and postmenopausal women [ 49 ]. As such, our findings support the assumption that DNAm patterns of ER genes, particularly at specific CpGs, may change over time and across reproductive transitions. Nevertheless, it is important to note that the increase in DNAm only showed a small effect size and that we did not assess gene expression levels to investigate corresponding changes at the receptor level. Moreover, the factors implicated in these changes still remain largely unclear. Emerging evidence from Guintivano et al. suggests that DNAm marks associated with a risk of postpartum depression overlap with estradiol-induced methylation changes [ 25 ]. Extending this finding, Mehta et al. employed a hormonal manipulation model using the gonadotropin-releasing hormone agonist (GnRHa) to examine hormone-induced mood changes in relation to a previously identified set of 116 genes enriched for estrogen receptor targets and associated with perinatal depression [ 68 ]. Notably, in women exposed to GnRHa, changes in DNAm over the course of the intervention were associated with changes in both estrogen levels and depressive symptoms. In the present study, contrary to expectation, we did not find an association of DNAm changes of ER genes with change scores either of estradiol or depressive symptoms. However, when using depression scores at 34–36 weeks of gestation as predictors, higher depressive symptom scores were associated with a higher increase in ESR1 DNAm, indicating sensitivity to epigenetic changes in vulnerable women. This is the first study to investigate DNAm levels of all three estrogen receptor genes and their association with estradiol and depressive symptoms during the perinatal period. A main strength of our study lies in its longitudinal design, which given the dynamic nature of DNAm, allowed us to examine the stability and change of ER gene methylation during the perinatal period. In view of the initial evidence from EWAS highlighting the role of estrogen signaling pathways in perinatal depression, the use of a targeted candidate gene approach overcomes the limitation of multiple testing correction [ 44 ]. A further strength of this study is the use of DBS, which is a minimally invasive method of blood sampling [ 69 , 70 ], and has been found to provide high-quality methylation results that are highly correlated with more invasive methods such as venous blood samples [ 71 ]. However, some limitations of the study should also be mentioned. The correlational nature of the study precludes any conclusions about the effects of underlying pathways such as gene expression levels. For instance, as we did not assess ER gene expression levels, it remains unclear whether DNAm levels and changes are associated with corresponding gene expression levels and changes. Moreover, due to the lack of assessment of cell type-specific methylation, it cannot be ruled out that the observed changes in methylation levels reflect differences in cell type composition rather than epigenetic variability [ 72 ]. Additionally, DNAm was only assessed in peripheral blood, which may not fully capture tissue-specific epigenetic patterns relevant to brain function, given the tissue specificity of DNAm. However, peripheral DNAm has been proposed as a promising target for identifying clinically relevant biomarkers [ 73 ]. Notably, blood was found to have the highest proportion of CpGs associated with brain tissue methylation compared to other peripheral tissues, although brain-blood correlations may vary between genes and CpGs [ 74 ]. Finally, although this study employed a longitudinal design, it only covered a limited period within the peripartum and did not include assessments of methylation prior to pregnancy. Consequently, we cannot infer changes across the entire perinatal period, and the relatively short window of observation may have been insufficient to capture long-term epigenetic changes or cumulative effects over time. In conclusion, the present findings indicate that lower DNAm levels of the CpGI shore of ESR1 , which may reflect higher ER-α expression and thus greater sensitivity to estrogen, are associated with increased depressive symptoms during pregnancy. Moreover, the results add to previous findings of perinatal DNAm changes by demonstrating that ER gene methylation changes during the transition from pregnancy to the postpartum period. Although current evidence is insufficient to establish these epigenetic signatures as biomarkers of perinatal depression, the findings highlight molecular pathways of estrogen sensitivity as a promising target for future research. Furthermore, our results emphasize the need to take into account the temporal variability of DNAm patterns in order to identify reliable biomarkers. Longitudinal studies including assessments prior to pregnancy and the investigation of corresponding gene expression dynamics are warranted. Addressing these research gaps is essential to improve our understanding and early detection of perinatal mood disorders. Abbreviations CpG: Cytosine-guanine dinucleotide; CpGI: Cytosine-guanine dinucleotide island; DBS: Dried blood spots; DNAm: DNA methylation; ELISA: Enzyme-linked immunosorbent assay; ER: Estrogen receptor; ER-α: Estrogen receptor alpha; ER-β: Estrogen receptor beta; ESR1 : Estrogen receptor gene 1; ESR2 : Estrogen receptor gene 2; EPDS: Edinburgh Postnatal Depression Scale; E2: Estradiol; EWAS: epigenome wide association studies; GABA: gamma-aminobutyric acid; GPER: G protein-coupled estrogen receptor; NGS: Next-generation sequencing; PCR: Polymerase chain reaction; pmm: predictive mean matching; VIF: variance inflation factor. Declarations Funding This work was supported by the Swiss National Science Foundation under Grant reference number: 100014_182120/1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests The authors declare that they have no competing interests. Authors' contributions Ulrike Ehlert contributed to the study conception. Alexandra Johann, Jelena Dukic, and Ulrike Ehlert contributed to the study design. Material preparation and data collection was performed by Alexandra Johann and Jelena Dukic. DNA methylation analysis was performed by Gianna Zorzini with the support of Elena Gardini. The first draft of the manuscript was written by Gianna Zorzini and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data Availability The datasets generated during and/or analyzed during the current study are not publicly available as patient-specific data could be used to identify patients with great effort, but are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study was performed in line with the principles of the Declaration of Helsinki. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6578336","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":464808051,"identity":"50f4d5de-4016-4682-8bbf-dc0cb8e6d174","order_by":0,"name":"Gianna Zorzini","email":"","orcid":"","institution":"University of Zurich","correspondingAuthor":false,"prefix":"","firstName":"Gianna","middleName":"","lastName":"Zorzini","suffix":""},{"id":464808052,"identity":"a0a41b15-abec-4f11-b10e-e7748a370c8d","order_by":1,"name":"Alexandra Johann","email":"","orcid":"","institution":"University of Zurich","correspondingAuthor":false,"prefix":"","firstName":"Alexandra","middleName":"","lastName":"Johann","suffix":""},{"id":464808053,"identity":"38c4dd18-4869-4484-bdba-6efbc47bb623","order_by":2,"name":"Jelena Dukic","email":"","orcid":"","institution":"University of Zurich","correspondingAuthor":false,"prefix":"","firstName":"Jelena","middleName":"","lastName":"Dukic","suffix":""},{"id":464808054,"identity":"0c5b1acd-58cd-476f-8de3-152468af33b4","order_by":3,"name":"Elena Gardini","email":"","orcid":"","institution":"University of Zurich","correspondingAuthor":false,"prefix":"","firstName":"Elena","middleName":"","lastName":"Gardini","suffix":""},{"id":464808055,"identity":"c049fe62-ce89-47b0-8491-0e9b069c5d76","order_by":4,"name":"Ulrike Ehlert","email":"data:image/png;base64,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","orcid":"","institution":"University of Zurich","correspondingAuthor":true,"prefix":"","firstName":"Ulrike","middleName":"","lastName":"Ehlert","suffix":""}],"badges":[],"createdAt":"2025-05-02 12:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6578336/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6578336/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12035-025-05556-3","type":"published","date":"2025-12-01T15:57:56+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83763376,"identity":"04310787-9e09-40bf-845d-9961d9834ad0","added_by":"auto","created_at":"2025-06-02 10:17:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":253311,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic figures of \u003cem\u003eESR1\u003c/em\u003e (a), \u003cem\u003eESR2\u003c/em\u003e (b), and \u003cem\u003eGPER\u003c/em\u003e (c) promoter regions.\u003cstrong\u003e a.\u003c/strong\u003e The DNA sequence of \u003cem\u003eESR1\u003c/em\u003e, chr6: 151805523–151805822, is located in a CpG island shore of promoter C. \u003cstrong\u003eb.\u003c/strong\u003e The DNA sequence of \u003cem\u003eESR2\u003c/em\u003e, chr14: 64,760,866- 64,761,269, is located in a CpG island of promoter 0N. \u003cstrong\u003ec.\u003c/strong\u003eThe DNA sequence of \u003cem\u003eGPER\u003c/em\u003e, chr7:1087059–1087533, is located in a CpG island across exons 1 and 2. White boxes represent exons or promoter regions. Bold “CG” correspond to the interrogated CpGs\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6578336/v1/be6c6a1aa416803941081009.png"},{"id":83763377,"identity":"9d4ae4e4-14fc-4b16-9ba1-cfa25748777f","added_by":"auto","created_at":"2025-06-02 10:17:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":70071,"visible":true,"origin":"","legend":"\u003cp\u003eScatterplot of EPDS scores and methylation levels of overall \u003cem\u003eESR1 \u003c/em\u003emethylation and its individual CpGs. \u003cstrong\u003ea.\u003c/strong\u003e Scatterplot of EPDS scores and overall \u003cem\u003eESR1 \u003c/em\u003emethylation. \u003cstrong\u003eb.\u003c/strong\u003e Scatterplot of EPDS scores and individual methylation of CpG 1 in \u003cem\u003eESR1\u003c/em\u003e. \u003cstrong\u003ec.\u003c/strong\u003e Scatterplot of EPDS scores and individual methylation of CpG 2 in \u003cem\u003eESR1\u003c/em\u003e. \u003cstrong\u003ed.\u003c/strong\u003e Scatterplot of EPDS scores and individual methylation of CpG 4 in \u003cem\u003eESR1\u003c/em\u003e. \u003cstrong\u003ee.\u003c/strong\u003e Scatterplot of EPDS scores and individual methylation of CpG 5 in \u003cem\u003eESR1\u003c/em\u003e. Regression lines represent the modeled relationship with 95% confidence intervals. Abbreviations: EPDS Edinburgh Postnatal Depression Scale\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6578336/v1/ad513b46b8abceb6216d6c14.png"},{"id":83763378,"identity":"06473fef-b6a0-4ce5-883a-fecfc74afde1","added_by":"auto","created_at":"2025-06-02 10:17:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":33914,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots of methylation levels at 34-36 weeks of gestation and 8-12 weeks postpartum. \u003cstrong\u003ea.\u003c/strong\u003eBoxplot of overall \u003cem\u003eESR1 \u003c/em\u003emethylation. \u003cstrong\u003eb.\u003c/strong\u003e Boxplot of the methylation of the individual CpG 9 in \u003cem\u003eESR1\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6578336/v1/9a36f4bba709ebf8a29e68f2.png"},{"id":83763148,"identity":"a9e0c73b-60be-44f0-a9e8-8178ed79c6b8","added_by":"auto","created_at":"2025-06-02 10:09:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":26928,"visible":true,"origin":"","legend":"\u003cp\u003eScatterplot of depressive symptom scores at 34-36 weeks of gestation and overall \u003cem\u003eESR1 \u003c/em\u003edelta methylation. Regression lines represent the modeled relationship with 95% confidence intervals. Abbreviations: EPDS Edinburgh postnatal depression scale\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6578336/v1/d5289d5aaa47710aa712e3ab.png"},{"id":97724057,"identity":"134eac25-1986-4a68-b139-0646cef5e540","added_by":"auto","created_at":"2025-12-08 16:11:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1480679,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6578336/v1/021be551-8c9d-4563-ad24-579e2eca7d0e.pdf"},{"id":83763143,"identity":"fb866dd1-ffb6-468c-beb9-607055891679","added_by":"auto","created_at":"2025-06-02 10:09:01","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":40064,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6578336/v1/551119568be0632c676c836c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Longitudinal Analysis of Estrogen Receptor Gene Methylation, Estradiol, and Depressive Symptoms during the Perinatal Period","fulltext":[{"header":"Background","content":"\u003cp\u003eWomen are particularly susceptible to depression during phases of pronounced sex steroid hormone fluctuations, such as the premenstrual, perinatal, and perimenopausal periods [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Moreover, the occurrence of depression during one of these reproductive transitions appears to be associated with an increased risk of depression during the respective other phases [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], leading to the suggestion of a reproductive subtype of depression [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. There is growing evidence to support the existence of this subtype, particularly regarding perinatal depression, which refers to depression arising during pregnancy or up to one year postpartum [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Depression during this period seems to be characterized by distinct symptoms, severity, heritability patterns, and epigenetic marks compared to depression occurring outside reproductive transitions [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Moreover, with a reported prevalence of 17%, and presumably even higher rates of undetected cases, the perinatal period represents a time of high vulnerability to developing depression [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Perinatal depression is particularly concerning if left undetected and therefore untreated, as it is associated with far-reaching implications, not only for the woman but also for her offspring [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, despite the well-documented prevalence, symptomatology, and consequences of perinatal depression, the biological underpinnings remain unclear, therefore impeding the identification of reliable biomarkers for early detection and thus treatment initiation [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough each female reproductive transition is characterized by unique fluctuations in sex steroid hormones, these fluctuations are considered as important biological triggers for depression during reproductive transition phases [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Regarding the perinatal period, sex steroid hormones are found to increase strongly during pregnancy, followed by a sharp decrease after delivery [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, only some women appear to be sensitive to these fluctuations and therefore vulnerable to depression during this period [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For instance, studies examining affective symptoms in multiparous women following a pharmacological simulation of the perinatal hormonal fluctuations have reported an increase in depressive symptoms in women with a history of perinatal depression but not in those without [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Research exploring this sensitivity at the molecular level has specifically highlighted the involvement of estrogen signaling pathways. In detail, women with perinatal depression were found to exhibit an enrichment of transcripts involved in estrogen signaling compared to healthy controls, indicating an increased sensitivity to estrogen in affected women [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. As such, sensitivity to estrogen has been suggested as a key pathway in mediating susceptibility to perinatal depression [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe physiological response to fluctuating estrogen levels depends on the capacity of estrogen receptors (ERs) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The ERs, encompassing ER-α, ER-β, and the G protein-coupled ER (GPER), mediate the biological effects of estrogen through genomic and non-genomic pathways after binding to the hormone [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Given the widespread distribution of ERs throughout the body, the biological effects of estrogen are manifold [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In the brain, ERs are predominantly expressed in limbic regions, where estrogen has been found to modulate neurotransmitters such as gamma-aminobutyric acid (GABA), serotonin, dopamine, and glutamate, ultimately regulating emotional and cognitive functions [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, the efficacy of the ERs in responding to fluctuating estrogen levels depends, at least in part, on their expression levels [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eDNA methylation (DNAm) of the ER genes \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2\u003c/em\u003e, and \u003cem\u003eGPER\u003c/em\u003e, which encode ER-α, ER-β, and GPER, respectively, has the function of adjusting the expression levels of the receptors [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. DNAm refers to the binding of methyl groups at cytosines in cytosine-guanine dinucleotides (CpGs), without changing the underlying DNA sequence itself [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This epigenetic modification can alter DNA accessibility, thereby affecting gene transcription and gene expression [\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. For instance, hypermethylation of the promoter regions of ER genes has been associated with reduced gene expression, while hypomethylation has been linked to increased ER levels [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough several epigenome-wide association studies (EWAS) have identified associations between DNAm marks implicated in estrogen signaling and depression during the perinatal period, biomarkers for clinical use remain to be investigated [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. While EWAS offer broad insights across the whole genome, they are often burdened by multiple testing correction, which reduces the statistical power and thus the ability to detect subtle but biologically meaningful associations [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. However, studies using a targeted approach to investigat ER gene methylation in association with perinatal depression are lacking [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Moreover, DNAm has the ability to change over time, which has also been observed during the perinatal period [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Consequently, it is important to take this variability into consideration in order to identify reliable biomarkers [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. While longitudinal courses of DNAm and potentially implicated factors remain understudied, findings from a cross-sectional study by our research group suggest that DNAm of ER genes may change over time [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In detail, differences in ESR1 DNAm levels emerged between pre- and postmenopausal women, and estradiol levels were found to be positively associated with \u003cem\u003eESR1\u003c/em\u003e DNAm in both groups. Thus, in view of the pronounced estrogen fluctuations during the perinatal period and the observed effects of estrogen on DNAm at various CpGs [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], estrogen may play a crucial role in epigenetic regulation during the perinatal period. However, to date, no study has longitudinally examined DNAm of the ER genes, its relationship to estradiol, and its possible association with depressive symptoms during the perinatal period. This research gap limits the ability to form a comprehensive understanding and the identification of biomarkers for early detection.\u003c/p\u003e \u003cp\u003eThe aim of this study was to investigate the association between DNAm of promoter regions in \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2\u003c/em\u003e, and \u003cem\u003eGPER\u003c/em\u003e, depressive symptoms, and estradiol levels during the perinatal period using a longitudinal design. Based on previous research and theoretical considerations, we hypothesized that depressive symptoms and estradiol levels would be associated with DNAm levels of promoter regions in \u003cem\u003eESR1, ESR2\u003c/em\u003e, and \u003cem\u003eGPER\u003c/em\u003e in pregnant and postpartum women. We further assumed that these DNAm marks would change during the transition from pregnancy to the postpartum period, and that this change would be associated with depressive symptoms and estradiol levels.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study was part of a larger longitudinal research project on (epi-)genetic, biological, and psychological factors implicated in female mood disorders during the transition from pregnancy to postpartum. All participants provided informed consent prior to data collection, which took place between June 2019 and June 2021. The research project was carried out at the University of Zurich, Department of Clinical Psychology and Psychotherapy. The project was approved by the Ethics Committee of the Canton of Zurich (KEK-ZH-Nr. 2018-02357) and conducted in accordance with the principles of the Declaration of Helsinki. The present study investigated associations between DNAm of ER genes, depressive symptoms, and estradiol during the transition from pregnancy to postpartum.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePhysically healthy women between aged between 20 and 45 years were recruited during their third trimester of pregnancy. The participants were followed from 34-36 weeks of gestation up to 8-12 weeks postpartum, encompassing a mean study duration of 17 weeks per participant. Detailed information on the participants, recruitment process, and eligibility criteria can be found elsewhere [51\u0026ndash;53]. For epigenetic analyses, the original sample size (N=161) was reduced to n=159, as one participant did not provide written informed consent to use (epi-)genetic data, and one participant did not provide blood samples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWomen interested in participating in the study were first screened for eligibility using an online questionnaire. Eligible participants were then invited to a telephone interview to confirm the inclusion and exclusion criteria. After successful inclusion, the first laboratory visit took place at around 34-36 weeks of gestation at the University of Zurich, Department of Clinical Psychology and Psychotherapy. During this visit, which started between 8 and 9 am, various psychological, biological, and (epi-)genetic parameters were assessed. Additionally, the participants were given instructions on carrying out the five home assessments, which encompassed the independent collection of saliva samples and several online questionnaires. After completion of the home assessments, the participants were invited for a second laboratory visit at approximately 8-12 weeks postpartum. During this visit, the same parameters as during the first visit were assessed, along with birth-related information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of perinatal mood\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe German version of the Edinburgh Postnatal Depression Scale (EPDS) was used to assess depressive symptoms [54, 55]. The EPDS is a validated self-report screening tool to assess depressive symptoms during pregnancy and the postpartum period, with 10 items rated on a 4-point Likert scale. The original validation of the German version of the EPDS showed good internal consistency, with Cronbach\u0026rsquo;s \u0026alpha; = 0.81 [54]. Participants completed the EPDS at both laboratory visits, as well as on the first day of each home assessment time point. In the present study, we used the EPDS scores from both laboratory visits.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBlood sampling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe participants provided up to five drops of blood (about 50 \u0026micro;L per drop) during the laboratory visits at 34-36 weeks of gestation and 8-12 weeks postpartum. Blood samples were collected through finger prick using the dried blood spot (DBS) method with standardized filter paper (No. 903 Whatman, DBS Protein Saver Card). The samples were dried for 3-4 hours at room temperature before being stored at -20\u0026deg;C at the laboratory of the University of Zurich until further biochemical analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSaliva sampling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSaliva samples were collected using the passive drool method with SaliCap sampling tubes (IBL International GMBH, Hamburg, Germany). The participants were instructed to collect a targeted total of 52 saliva samples. Samples were collected on two consecutive days at 34-36 weeks of gestation, 40 weeks of gestation, 4-8 weeks postpartum, and 8-12 weeks postpartum. Additionally, the participants provided samples on five consecutive days, starting within the first 48 hours after delivery. On each assessment day, four saliva samples were provided: three in the morning (immediately after awakening, 30 and 45 min after awakening) and one in the evening between 8 and 10 pm. The samples were stored in the participants\u0026rsquo; home freezers until the second laboratory visit, whereupon they were stored at -20\u0026deg;C at the laboratory of the University of Zurich until further biochemical analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstradiol Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs salivary assessment of steroid hormones is a reliable marker of serum steroid levels [56, 57], saliva samples were used to quantify estradiol (E2) levels. Salivary E2 (pg/mL) was determined using luminescence immunoassay with enzyme-linked immunosorbent assay (ELISA) kits (IBL International GmbH, Hamburg, Germany, catalog number RE62141/RE62149). Estradiol determinations were performed by Dresden LabService GmbH in Dresden, Germany. In accordance with the manufacturer\u0026rsquo;s instructions, the standard range for E2 was between 2-64 pg/ml and the highest cross-reactivity was with Estrone, at around 14%. The inter- and intraassay coefficients of variability were 9.5% and \u0026lt;6%, respectively. E2 values were only available for n=126 participants. Missing E2 values were imputed using predictive mean matching (pmm) from the mice package in R (version 4.3.2) [58], generating 50 imputation datasets to account for the uncertainty introduced by imputing missing values. In this study, mean estradiol values from the first day of the assessment at around 34-36 weeks of gestation and 8-12 weeks postpartum were used to account for inter-day variability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethylation analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenomic DNA was extracted from DBS, and was reported to provide reliable results in the context of methylation analysis [59]. Three punches of 3.0 mm diameter DBS were used to extract DNA with the QIAamp DNA Investigator Kit (QIAGEN, Hilden, Germany), in accordance with the manufacturer\u0026rsquo;s instructions. Additionally, duplicates and negative controls (samples without DNA) were included for quality control. The extracted DNA and negative controls were eluted in a final volume of 30\u0026mu;L RNase-free water. DNA concentration was assessed using NanoDrop (Thermo Fischer Scientific, Waltham, MA, USA) and ranged from 9.04 to 86.67 ng. DNA extraction was performed by a trained biologist in our laboratory at the University of Zurich, Department of Clinical Psychology, while subsequent steps were carried out at the Genetic Diversity Centre (GDC), ETH Zurich.\u003c/p\u003e\n\u003cp\u003eGenomic DNA was bisulfite-converted using the EZ-96 DNA Methylation-Lightning Kit D5032 (Zymo Research, Irvine, CA, USA) in accordance with the manufacturer\u0026rsquo;s instructions, which recommend using samples containing 0.5-2000 ng of DNA.\u003c/p\u003e\n\u003cp\u003eAn initial polymerase chain reaction (PCR) was performed on the bisulfite-treated DNA using the Kapa HiFi Uracil+ master mix (Kapa Biosystems, Wilmington, MA, USA). Primers included the universal oligonucleotides CS1/CS2 at the 5ʹ ends (Fluidigm, San Francisco, CA, USA), which are used for customized next-generation sequencing (NGS; see Table 1). The primers were designed to target the specific DNA sequence of the \u003cem\u003eESR1\u003c/em\u003e shore of promoter C (hg 38; chr6:151805523-151805822, Figure 1A), the \u003cem\u003eESR2\u003c/em\u003e promoter 0N (hg 38; chr14: 64,760,866- 64,761,269, Figure 1B), and the \u003cem\u003eGPER\u003c/em\u003e promoter (hg 38; chr7:1087059-1087533, Figure 1C). The PCR conditions were set to an initial temperature of 95\u0026deg;C for 3 min, followed by 30x (98\u0026deg;C for 20s, annealing temperature for 15s, and 72\u0026deg;C for 15s), and a final elongation at 72\u0026deg;C for 40s. The annealing temperature varied for each sequence (see Table 1). Subsequently, a second PCR was performed with an initial temperature of 95\u0026deg;C for 3 min, then 20x (98\u0026deg;C for 20s, annealing temperature for 15s, 72\u0026deg;C for 15s), and a final elongation at 72\u0026deg;C for 40s. After the second PCR, amplicons were purified using KingFisher (Thermo Fisher Scientific, Waltham, MA, USA).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003ePCR primers used for amplification of DNA sequences in the \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2\u003c/em\u003e and \u003cem\u003eGPER\u003c/em\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eForward Primer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReverse primer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGRCh38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAT (\u0026deg;C)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cem\u003eESR1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eACACTGACGACATGGTTCTACA NNN GTTTTTTGTGAGTAGATAGTAAGTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eTACGGTAGCAGAGACTTGGTCT NNN AAACCTACCCTACTAAATCAAAAAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003echr6:\u003c/p\u003e\n \u003cp\u003e151,805,523-151,805,822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cem\u003eESR2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eACACTGACGACATGGTTCTACA NNN TTATTATTTTTGTGGGTGGAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eTACGGTAGCAGAGACTTGGTCT NNN CACCTCCTACAACTCAAACTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003echr14:\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e64,760,866- 64,761,269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cem\u003eGPER\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eACACTGACGACATGGTTCTACA NNN AGTGAAAATTTAAATGGTTAGTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eTACGGTAGCAGAGACTTGGTCT NNN ACAATCCAAACAATTCAAAATTTATTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003echr7:\u003c/p\u003e\n \u003cp\u003e1,087,059-\u003c/p\u003e\n \u003cp\u003e1,087,533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003eNote: Universal primer CS1 = ACACTGACGACATGGTTCTACA, universal primer CS2 = TACGGTAGCAGAGACTTGGTCT. Abbreviations: PCR = polymerase chain reaction; \u003cem\u003eESR1\u003c/em\u003e = estrogen receptor alpha gene; \u003cem\u003eESR2\u003c/em\u003e = estrogen receptor beta gene; \u003cem\u003eGPER\u003c/em\u003e = G protein-coupled estrogen receptor gene; GRCh38 = Genome Reference Consortium Human Build 38 Organism; AT = annealing temperature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePurified amplicons were then indexed with customized single barcodes (Fluidigm, San Francisco, CA, USA) using a third PCR with the conditions set to 95\u0026deg;C for 3 min, then 10x (98\u0026deg;C for 20s, 58\u0026deg;C for 15s, 72\u0026deg;C for 15s), and a final elongation at 72\u0026deg;C for 40s. The indexed amplicons were eluted in 15\u0026mu;L RNase-free water and again purified using KingFisher (Thermo Fisher Scientific, Waltham, MA, USA).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe purified indexed amplicons were quantified using Sparke Plate Reader (TECAN Spark, Tecan Group Ltd, Maennedorf, Switzerland), before normalization and pooling were conducted. After a final purification with AMPure XP beads, the pool was quantified using the Agilent 2200 Tape Station instrument and HS DNA 1000 reagents (Agilent Scientific Instruments, Santa Clara, CA, USA) and Quibit (Thermo Fischer Scientific, Waltham, MA, USA). The pool was then diluted to a final molarity of 4 nM. PhiX spike-in (15%) was added to the library to increase the diversity of base calling during sequencing. The final library was sequenced on the Illumina MiSeq using the V3, 600 cycles kit (300 PE; Illumina, San Diego, CA, USA). Low-quality products were removed using Trimmomatic v0.35 (http://www.usadellab.org/cms/index.php?page=trimmomatic; [60]. The remaining sequencing reads were aligned to the target regions. The Bismark program (v0.19.0) was used to extract the number of methylated (cytosine) and non-methylated (thymine) bases.\u003c/p\u003e\n\u003cp\u003eA total of 33, 18, and 12 samples in \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2\u003c/em\u003e, and \u003cem\u003eGPER\u003c/em\u003e, respectively, showed zero coverage (no aligned reads detected) and were thus missing. In accordance with [61], a minimum threshold of 100 reads was set. For \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2\u003c/em\u003e, and \u003cem\u003eGPER\u003c/em\u003e, 80, 67, and 88 samples, respectively, did not reach this threshold and were thus excluded. For the remaining samples, coverage ranged from 109 to 325\u0026rsquo;599 for \u003cem\u003eESR1\u003c/em\u003e, from 106 to 829\u0026rsquo;507 for \u003cem\u003eESR2\u003c/em\u003e, and from 111 to 292\u0026rsquo;350 for \u003cem\u003eGPER\u003c/em\u003e. Moreover, samples with a significant deviation (\u0026plusmn; 3 times the interquartile range (IQR)) were excluded. For \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2,\u003c/em\u003e and \u003cem\u003eGPER\u003c/em\u003e, 7, 16, and 8 samples, respectively, were below or above the IQR and thus excluded. After the exclusion of these outliers, the methylation levels reached normal distribution for all three sequences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll analyses were performed using the overall mean DNAm levels of the 9, 30, and 22 CpGs in \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2\u003c/em\u003e, and GPER, respectively, and the DNAm levels of the individual CpGs in \u003cem\u003eESR1\u003c/em\u003e. To examine the associations between depressive symptoms, E2 levels, age, and DNAm during pregnancy and the postpartum period, we performed Spearman or Pearson correlations, depending on normality of the data. Moreover, multivariate linear regression analyses were conducted to assess the effect of depressive symptoms and E2 levels on DNAm in pregnancy and the postpartum period, while controlling for maternal age and history of depression. Paired t-tests were used to investigate DNAm changes from pregnancy to postpartum.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eIn case of\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003esignificant DNAm changes, multivariate linear regressions were calculated with the corresponding DNAm delta scores, while controlling for the previously mentioned covariates. Two sets of predictors were used: depressive symptom scores and E2 levels obtained at 34-36 weeks of gestation, and delta scores of depressive symptoms and E2 levels. All statistical tests were two-sided, and the significance level was set at \u003cem\u003ep\u003c/em\u003e \u0026le; 0.05. To correct for multiple testing, the Benjamini-Hochberg method [62] was used, with the significance threshold set at q \u0026le; 0.1. We found no issues with multicollinearity, which was assessed using the variance inflation factor (VIF; all VIFs were \u0026lt; 2). All statistical analyses were performed using R (version 4.3.2; R Project).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSample characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSample sizes varied between variables due to the missing data. Descriptive statistics were therefore calculated for all available data points for each variable used in this study (see Table 2). Participant\u0026rsquo;s age ranged between 21 to 43 years, with a median of 33 years. Moreover, all participants (n=159) were of self-reported European ancestry, with the majority reporting being Swiss (71.7%). More information on sociodemographic characteristics can be found elsewhere [51, 53].\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 606px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003eDescriptive statistics of biological and psychological measures.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e34-36 weeks of gestation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e8-12 weeks postpartum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eM(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eM(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cem\u003eESR1\u0026nbsp;\u003c/em\u003eCpGI shore methylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e72.83(5.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e74.06(5.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 1 methylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e61.76(11.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e62.57(13.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 2 methylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e76.83(9.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e77.02(11.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 3 methylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e83.20(7.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e84.35(8.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 4 methylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e78.39(8.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e80.22(9.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 5 methylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e81.37(7.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e81.35(10.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 6 methylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e83.60(11.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e84.73(10.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 7 methylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e82.84(5.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e83.16(8.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 8 methylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e31.05(5.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e31.55(6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 9 methylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e76.44(8.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e80.18(9.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cem\u003eESR2\u0026nbsp;\u003c/em\u003epromoter 0N methylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e0.75(0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.76(0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cem\u003eGPER\u0026nbsp;\u003c/em\u003epromoter\u003cem\u003e\u0026nbsp;\u003c/em\u003emethylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e13.65(3.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e14.35(4.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003eE2 (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e43.00(7.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3.66(1.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003eEPDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e4.78(4.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e4.01(4.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 606px;\"\u003e\n \u003cp\u003eNote. E2 estradiol, EPDS Edinburgh Postnatal Depression Scale.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eDNA methylation, depressive symptoms, and estradiol\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eThird trimester of pregnancy\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrelation results are displayed in additional file 1, Table S1-2. Spearman\u0026rsquo;s rank-order correlations revealed a weak negative association between depressive symptom scores and both overall \u003cem\u003eESR1\u0026nbsp;\u003c/em\u003eDNAm (\u0026rho;=-0.29, \u003cem\u003ep\u003c/em\u003e=0.013, n=69) and DNAm of the CpG 1 in \u003cem\u003eESR1\u003c/em\u003e (\u0026rho;=-0.24, \u003cem\u003ep\u003c/em\u003e=0.04, n=69). Additionally, a moderate negative association emerged between depressive symptom scores and DNAm of CpG 2 in \u003cem\u003eESR1\u003c/em\u003e (\u0026rho;=-0.39, \u003cem\u003ep\u003c/em\u003e=0.0007, n=69). Pearson\u0026rsquo;s correlations revealed a weak positive correlation between E2 levels and DNAm of CpG 5 in \u003cem\u003eESR1\u003c/em\u003e (r=0.28, \u003cem\u003ep\u003c/em\u003e=0.03, n=69). No further correlations were found between any of the investigated variables (all \u003cem\u003ep\u003c/em\u003e\u0026gt;0.05).\u003c/p\u003e\n\u003cp\u003eResults of the multivariate linear regressions during pregnancy are displayed in Table 3. Depressive symptoms were associated with the overall \u003cem\u003eESR1\u003c/em\u003e DNAm, as well as the DNAm of four of its individual CpGs, all of which all remained significant after correction for multiple testing. In detail, increased depressive symptom scores were associated with lower DNAm levels (see Figure 2). E2 levels were not found to be associated with the overall \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2\u003c/em\u003e, and \u003cem\u003eGPER\u003c/em\u003e DNAm or with the DNAm of any of the individual CpGs in \u003cem\u003eESR1\u003c/em\u003e (all \u003cem\u003ep\u003c/em\u003e\u0026gt;0.05).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eResults of multivariate linear regressions during the third trimester of pregnancy.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eMethylation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eEPDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eHistory of depression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eAdjusted \u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eAdjusted \u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eAdjusted \u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eAdjusted \u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cem\u003eESR1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.002*\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.530\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.006*\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.489\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.003*\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e-0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e-0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.028*\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e-0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e-0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.035*\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.830\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e-0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.669\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.459\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cem\u003eESR2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e-0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cem\u003eGPER\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e-0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e-0.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 605px;\"\u003e\n \u003cp\u003eNote. \u003cem\u003e*p\u0026nbsp;\u003c/em\u003e\u0026le; 0.05, \u003csup\u003ea\u0026nbsp;\u003c/sup\u003esignificant after correction for multiple testing, EPDS Edinburgh Postnatal Depression Scale, E2 estradiol.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePostpartum period\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrelation results are displayed in Table S3-4. Spearman\u0026rsquo;s rank correlations revealed a weak significant positive correlation between E2 levels and both overall \u003cem\u003eGPER\u003c/em\u003e DNAm (\u0026rho;=0.21, \u003cem\u003ep\u003c/em\u003e=0.02, n=111) and depressive symptom scores (\u0026rho;=0.21, \u003cem\u003ep\u003c/em\u003e=0.01, n=124). No further correlations emerged between any of the assessed variables (all \u003cem\u003ep\u003c/em\u003e\u0026gt;0.05). Multivariate linear regressions revealed no associations of depressive symptoms and E2 levels with the overall \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2\u003c/em\u003e, and \u003cem\u003eGPER\u003c/em\u003e DNAm or with the DNAm of any of the individual CpGs in \u003cem\u003eESR1\u003c/em\u003e (all \u003cem\u003ep\u003c/em\u003e\u0026gt;0.05, see Table S5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA methylation changes from pregnancy to postpartum\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults of the paired t-tests regarding DNAm changes in ER genes during the transition from pregnancy to postpartum are displayed in Table 4. Significant changes were only found for the overall \u003cem\u003eESR1\u003c/em\u003e DNAm,\u003cem\u003e\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;\u003c/em\u003efor the DNAm of the individual CpG 9 in \u003cem\u003eESR1\u003c/em\u003e, which were both found to increase (see Figure 3). Both of these DNAm changes remained significant after correction for multiple testing.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eResults of the paired t-tests of the methylation changes from pregnancy to postpartum.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003eMethylation (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e34-36 weeks of gestation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e8-12 weeks postpartum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003et-statistics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eCohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cem\u003eESR1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e72.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e5.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e74.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e6.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2.590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.012*\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e61.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e11.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e62.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e16.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e76.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e9.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e76.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e12.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e83.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e7.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e84.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e9.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e78.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e9.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e79.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e9.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e81.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e7.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e81.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e11.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e83.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e12.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e84.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e7.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e82.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e5.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e83.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e10.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e31.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e5.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e31.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e7.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; CpG 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e75.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e9.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e80.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e9.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e3.151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.002*\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.406\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cem\u003eESR2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cem\u003eGPER\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e13.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e14.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote. * p \u0026le; .05, \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e\u003c/em\u003esignificant after correction for multiple testing.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eChange scores from pregnancy to postpartum\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChange scores (delta values) were only calculated for the entire \u003cem\u003eESR1\u003c/em\u003e DNAm and for the DNAm of the individual CpG 9 in \u003cem\u003eESR1\u003c/em\u003e, as only these changed significantly during the transition from pregnancy to postpartum. Multivariate linear regression analysis did not reveal any significant associations when using delta scores of the predictors (all \u003cem\u003ep\u003c/em\u003e\u0026gt;0.05, see Table S6). However, when using scores at 34-36 weeks of gestation for the predictors, a significant effect was found for delta scores of overall \u003cem\u003eESR1\u003c/em\u003e DNAm (see Table S7). Specifically, depressive symptoms at 34-36 weeks of gestation showed a significant positive association with overall \u003cem\u003eESR1\u003c/em\u003e delta DNAm (\u003cem\u003e\u0026beta;\u003c/em\u003e=0.311, \u003cem\u003ep\u003c/em\u003e=0.036, see Figure 4). This finding remained significant after correction for multiple testing.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis longitudinal study investigated the association between DNAm of ER genes (\u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2\u003c/em\u003e, and \u003cem\u003eGPER\u003c/em\u003e), estradiol, and depressive symptoms during the transition from pregnancy to the postpartum period. Mean DNAm levels varied across the genes analyzed, with \u003cem\u003eESR1\u003c/em\u003e showing intermediate methylation, \u003cem\u003eESR2\u003c/em\u003e almost absent methylation, and \u003cem\u003eGPER\u003c/em\u003e low methylation during both pregnancy and the postpartum period. During pregnancy, depressive symptoms were found to be negatively associated with the overall DNAm of the CpGI shore of \u003cem\u003eESR1\u003c/em\u003e and with four of its individual CpGs (CpG 1, CpG 2, CpG 4, and CpG 5). During the postpartum period, no associations were identified between depressive symptoms and DNAm of the three genes analyzed. Likewise, estradiol was not found to be associated with DNAm of any of the three genes at either time point. In addition, the overall DNAm of the CpGI shore of \u003cem\u003eESR1\u003c/em\u003e and its individual CpG 9 increased from pregnancy to the postpartum period. Although changes in estradiol levels and depressive symptoms were not linked to these DNAm changes, higher depressive symptoms at 34\u0026ndash;36 weeks of gestation were associated with a larger increase in the overall DNAm of the CpGI shore of \u003cem\u003eESR1\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eRecently a systematic review by our research group described that sensitivity to estrogen signaling, in particular via ER-α, is associated with perinatal depression [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Markers of this sensitivity can help to identify women at risk. In this vein, the present study revealed that DNAm of the CpGI shore of \u003cem\u003eESR1\u003c/em\u003e, encoding for ER-α, was associated with depressive symptoms during pregnancy, whereas no such association was found for \u003cem\u003eESR2\u003c/em\u003e and \u003cem\u003eGPER\u003c/em\u003e. These results support the assumption from other genetic studies that ER-α plays a more important role in mood regulation than do ER-β and GPER, which might be explained by its predominant expression in neuronal areas implicated in emotional functions, such as the amygdala and hypothalamus, compared to other ERs [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Interestingly, lower DNAm levels of the overall CpGI shore of \u003cem\u003eESR1\u003c/em\u003e and its individual CpG 1, CpG 2, CpG 4, and CpG 5 were associated with increased depressive symptom scores during pregnancy. Notably, higher DNAm levels of the CpGI shore of \u003cem\u003eESR1\u003c/em\u003e have been associated with lower mRNA expression of ER-α [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Moreover, DNAm of one of these individual CpGs, namely CpG 4, was previously found to be negatively correlated with ER-α expression [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Therefore, we suggest that lower DNAm levels of the CpGI shore of \u003cem\u003eESR1\u003c/em\u003e, particularly at CpG4, may upregulate ER-α expression, thereby increasing sensitivity to estrogen and thus susceptibility to depressive symptoms during pregnancy, when estrogen levels are high.\u003c/p\u003e \u003cp\u003ePrevious cross-sectional findings by our research group indicated that mean DNAm levels of the CpGI shore of \u003cem\u003eESR1\u003c/em\u003e are associated with estradiol levels within different menopausal groups [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In detail, estradiol was positively associated with ESR1 DNAm in pre- and postmenopausal women, while a negative association was found in perimenopausal women. Contrary to our expectation, in the present study, no associations were observed between estradiol levels and DNAm levels of any ER gene in either pregnant or postpartum women. Nevertheless, a trend emerged for the DNAm of CpG 5 of the CpGI shore of \u003cem\u003eESR1\u003c/em\u003e, showing a positive association with estradiol in pregnant women and a negative association in postpartum women. Additionally, a trend towards a positive association between estradiol and \u003cem\u003eGPER\u003c/em\u003e DNAm was observed in postpartum women. These findings may reflect a subtle but dynamic and context-dependent hormonal regulation of ER gene DNAm during the perinatal period. The lack of robust associations may be due to the specific period investigated, which encompasses pronounced hormonal fluctuations. Therefore, single time point measurements may not capture the dynamic interplay between fluctuating hormone levels and DNAm, limiting our ability to detect potential long-term exposures relevant to DNAm.\u003c/p\u003e \u003cp\u003eIn contrast to genetic variations, DNAm is an epigenetic modification that can change over time, a dynamic that has also been observed for various CpGs during the perinatal period [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Supporting this, the present longitudinal analysis revealed that overall DNAm of the CpGI shore of \u003cem\u003eESR1\u003c/em\u003e and its individual CpG 9 increased from pregnancy to the postpartum period. Interestingly, DNAm of the CpG 9 has also been found to differ cross-sectionally between pre- and postmenopausal women [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. As such, our findings support the assumption that DNAm patterns of ER genes, particularly at specific CpGs, may change over time and across reproductive transitions. Nevertheless, it is important to note that the increase in DNAm only showed a small effect size and that we did not assess gene expression levels to investigate corresponding changes at the receptor level. Moreover, the factors implicated in these changes still remain largely unclear. Emerging evidence from Guintivano et al. suggests that DNAm marks associated with a risk of postpartum depression overlap with estradiol-induced methylation changes [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Extending this finding, Mehta et al. employed a hormonal manipulation model using the gonadotropin-releasing hormone agonist (GnRHa) to examine hormone-induced mood changes in relation to a previously identified set of 116 genes enriched for estrogen receptor targets and associated with perinatal depression [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Notably, in women exposed to GnRHa, changes in DNAm over the course of the intervention were associated with changes in both estrogen levels and depressive symptoms. In the present study, contrary to expectation, we did not find an association of DNAm changes of ER genes with change scores either of estradiol or depressive symptoms. However, when using depression scores at 34\u0026ndash;36 weeks of gestation as predictors, higher depressive symptom scores were associated with a higher increase in \u003cem\u003eESR1\u003c/em\u003e DNAm, indicating sensitivity to epigenetic changes in vulnerable women.\u003c/p\u003e \u003cp\u003eThis is the first study to investigate DNAm levels of all three estrogen receptor genes and their association with estradiol and depressive symptoms during the perinatal period. A main strength of our study lies in its longitudinal design, which given the dynamic nature of DNAm, allowed us to examine the stability and change of ER gene methylation during the perinatal period. In view of the initial evidence from EWAS highlighting the role of estrogen signaling pathways in perinatal depression, the use of a targeted candidate gene approach overcomes the limitation of multiple testing correction [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. A further strength of this study is the use of DBS, which is a minimally invasive method of blood sampling [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e], and has been found to provide high-quality methylation results that are highly correlated with more invasive methods such as venous blood samples [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, some limitations of the study should also be mentioned. The correlational nature of the study precludes any conclusions about the effects of underlying pathways such as gene expression levels. For instance, as we did not assess ER gene expression levels, it remains unclear whether DNAm levels and changes are associated with corresponding gene expression levels and changes. Moreover, due to the lack of assessment of cell type-specific methylation, it cannot be ruled out that the observed changes in methylation levels reflect differences in cell type composition rather than epigenetic variability [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Additionally, DNAm was only assessed in peripheral blood, which may not fully capture tissue-specific epigenetic patterns relevant to brain function, given the tissue specificity of DNAm. However, peripheral DNAm has been proposed as a promising target for identifying clinically relevant biomarkers [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. Notably, blood was found to have the highest proportion of CpGs associated with brain tissue methylation compared to other peripheral tissues, although brain-blood correlations may vary between genes and CpGs [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Finally, although this study employed a longitudinal design, it only covered a limited period within the peripartum and did not include assessments of methylation prior to pregnancy. Consequently, we cannot infer changes across the entire perinatal period, and the relatively short window of observation may have been insufficient to capture long-term epigenetic changes or cumulative effects over time.\u003c/p\u003e \u003cp\u003eIn conclusion, the present findings indicate that lower DNAm levels of the CpGI shore of \u003cem\u003eESR1\u003c/em\u003e, which may reflect higher ER-α expression and thus greater sensitivity to estrogen, are associated with increased depressive symptoms during pregnancy. Moreover, the results add to previous findings of perinatal DNAm changes by demonstrating that ER gene methylation changes during the transition from pregnancy to the postpartum period. Although current evidence is insufficient to establish these epigenetic signatures as biomarkers of perinatal depression, the findings highlight molecular pathways of estrogen sensitivity as a promising target for future research. Furthermore, our results emphasize the need to take into account the temporal variability of DNAm patterns in order to identify reliable biomarkers. Longitudinal studies including assessments prior to pregnancy and the investigation of corresponding gene expression dynamics are warranted. Addressing these research gaps is essential to improve our understanding and early detection of perinatal mood disorders.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCpG: Cytosine-guanine dinucleotide; CpGI: Cytosine-guanine dinucleotide island; DBS: Dried blood spots; DNAm: DNA methylation; ELISA: Enzyme-linked immunosorbent assay; ER: Estrogen receptor; ER-\u0026alpha;: Estrogen receptor alpha; ER-\u0026beta;: Estrogen receptor beta; \u003cem\u003eESR1\u003c/em\u003e: Estrogen receptor gene 1; \u003cem\u003eESR2\u003c/em\u003e: Estrogen receptor gene 2; EPDS: Edinburgh Postnatal Depression Scale; E2: Estradiol; EWAS: epigenome wide association studies; GABA: gamma-aminobutyric acid; GPER: G protein-coupled estrogen receptor; NGS: Next-generation sequencing; PCR: Polymerase chain reaction; pmm: predictive mean matching; VIF: variance inflation factor.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Swiss National Science Foundation under Grant reference number: 100014_182120/1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUlrike Ehlert contributed to the study conception. Alexandra Johann, Jelena Dukic, and Ulrike Ehlert contributed to the study design. Material preparation and data collection was performed by Alexandra Johann and Jelena Dukic. \u0026nbsp;DNA methylation analysis was performed by Gianna Zorzini with the support of Elena Gardini. The first draft of the manuscript was written by Gianna Zorzini and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are not publicly available as patient-specific data could be used to identify patients with great effort, but are available from the corresponding author on reasonable request.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Committee of the Canton of Zurich (06.02.2019/ KEK-ZH-Nr. 2018-02357).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLokuge S, Frey BN, Foster JA, Soares CN, Steiner M. Depression in women: windows of vulnerability and new insights into the link between estrogen and serotonin. J Clin Psychiatry. 2011;72:e1563-9. doi:10.4088/JCP.11com07089.\u003c/li\u003e\n\u003cli\u003eKuehner C. Why is depression more common among women than among men? Lancet Psychiatry. 2017;4:146\u0026ndash;58. doi:10.1016/S2215-0366(16)30263-2.\u003c/li\u003e\n\u003cli\u003eKundakovic M, Rocks D. Sex hormone fluctuation and increased female risk for depression and anxiety disorders: From clinical evidence to molecular mechanisms. 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Transl Psychiatry. 2019;9:47. doi:10.1038/s41398-019-0376-y.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"molecular-neurobiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"moln","sideBox":"Learn more about [Molecular Neurobiology](https://www.springer.com/journal/12035)","snPcode":"12035","submissionUrl":"https://submission.nature.com/new-submission/12035/3","title":"Molecular Neurobiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"estrogen receptor, epigenetics, DNA methylation, perinatal depression","lastPublishedDoi":"10.21203/rs.3.rs-6578336/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6578336/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eDNA methylation of estrogen receptor genes (\u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2\u003c/em\u003e, and \u003cem\u003eGPER\u003c/em\u003e) may affect expression of the estrogen receptors (ERs) alpha, beta, and G protein-coupled estrogen receptor (GPER). Altered receptor expression may in turn affect the receptors’ sensitivity to estrogen, thereby modulating vulnerability to depression during periods of estrogen fluctuation. The aim of this study was to investigate the association between methylation of \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eESR2\u003c/em\u003e, and \u003cem\u003eGPER\u003c/em\u003e, depressive symptoms, and estradiol during the perinatal period using a longitudinal design.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A total of 159 women were followed longitudinally from 34-36 weeks of gestation to 8-12 weeks postpartum. Depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS). Salivary estradiol levels were quantified, and DNA methylation was analyzed using dried blood spots. Multivariate linear regressions and paired t-tests were used for analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eDepressive symptoms were negatively associated with the mean overall \u003cem\u003eESR1\u003c/em\u003e methylation during pregnancy (\u003cem\u003eβ\u003c/em\u003e=-0.41\u003cem\u003e, p\u003c/em\u003e=0.002\u003cem\u003e)\u003c/em\u003e, but not during the postpartum period (\u003cem\u003ep\u003c/em\u003e≥0.05). No associations emerged for \u003cem\u003eESR2\u003c/em\u003e, \u003cem\u003eGPER\u003c/em\u003e, or estradiol at either time point (all \u003cem\u003ep\u003c/em\u003e≥0.05). The mean overall methylation of \u003cem\u003eESR1\u003c/em\u003e increased from pregnancy to postpartum (t=-2.59, \u003cem\u003ep\u003c/em\u003e=0.012)\u003cem\u003e \u003c/em\u003eand was\u003cem\u003e \u003c/em\u003epositively associated with depressive symptom scores during pregnancy (\u003cem\u003eβ\u003c/em\u003e=0.418, \u003cem\u003ep\u003c/em\u003e=0.031).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003eThis work suggests that lower DNA methylation levels of \u003cem\u003eESR1\u003c/em\u003e, which may reflect higher ER-alpha expression and thus greater sensitivity to estrogen, are associated with increased depressive symptoms during pregnancy. The findings highlight molecular pathways of estrogen sensitivity, particularly via ER-alpha, as a promising target for future biomarker research for perinatal depression.\u003c/p\u003e","manuscriptTitle":"Longitudinal Analysis of Estrogen Receptor Gene Methylation, Estradiol, and Depressive Symptoms during the Perinatal Period","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-02 10:08:56","doi":"10.21203/rs.3.rs-6578336/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-27T20:36:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-27T18:42:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"14882015253479263639800456294137265507","date":"2025-08-12T21:57:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"288158092189591590141978071085378431055","date":"2025-07-16T13:48:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-03T21:02:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"99608130097571212899444424365692239774","date":"2025-06-03T14:51:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-29T09:32:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-12T06:14:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-12T06:09:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Neurobiology","date":"2025-05-02T12:08:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-neurobiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"moln","sideBox":"Learn more about [Molecular Neurobiology](https://www.springer.com/journal/12035)","snPcode":"12035","submissionUrl":"https://submission.nature.com/new-submission/12035/3","title":"Molecular Neurobiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3fb23429-ea5b-4116-b2d8-63af30239eb0","owner":[],"postedDate":"June 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T16:06:31+00:00","versionOfRecord":{"articleIdentity":"rs-6578336","link":"https://doi.org/10.1007/s12035-025-05556-3","journal":{"identity":"molecular-neurobiology","isVorOnly":false,"title":"Molecular Neurobiology"},"publishedOn":"2025-12-01 15:57:56","publishedOnDateReadable":"December 1st, 2025"},"versionCreatedAt":"2025-06-02 10:08:56","video":"","vorDoi":"10.1007/s12035-025-05556-3","vorDoiUrl":"https://doi.org/10.1007/s12035-025-05556-3","workflowStages":[]},"version":"v1","identity":"rs-6578336","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6578336","identity":"rs-6578336","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}