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Methylation analysis for postpartum depression: a case control study.

ABSTRACT: BACKGROUND:Postpartum depression (PPD) is a major depressive disorder that occurs after childbirth. Objective diagnostic and predictive methods for PPD are important for early detection and appropriate intervention. DNA methylation has been recognized as a potential biomarker for major depressive disorder. In this study, we used methylation analysis and peripheral blood to search for biomarkers that could to lead to the development a predictive method for PPD. METHODS:Study participants included 36 pregnant women (18 cases and 18 controls determined after childbirth). Genome-wide DNA methylation profiles were obtained by analysis with an Infinium Human Methylation 450BeadChip. The association of DNA methylation status at each DNA methylation site with PPD was assessed using linear regression analysis. We also conducted functional enrichment analysis of PPD using The Database for Annotation, Visualization and Integrated Discovery 6.8 to explore enriched functional-related gene groups for PPD. RESULTS:In the analysis with postpartum depressed state as an independent variable, the difference in methylation frequency between the postpartum non-depressed group and the postpartum depressed group was small, and sites with genome-wide significant differences were not confirmed. After analysis by The Database for Annotation, Visualization and Integrated Discovery 6.8, we revealed four gene ontology terms, including axon guidance, related to postpartum depression. CONCLUSIONS:These findings may help with the development of an objective predictive method for PPD.

SUBMITTER: Nakamura Y

PROVIDER: S-EPMC6585089 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Methylation analysis for postpartum depression: a case control study.

Nakamura Yukako Y Nakatochi Masahiro M Kunimoto Shohko S Okada Takashi T Aleksic Branko B Toyama Miho M Shiino Tomoko T Morikawa Mako M Yamauchi Aya A Yoshimi Akira A Furukawa-Hibi Yoko Y Nagai Taku T Ohara Masako M Kubota Chika C Yamada Kiyofumi K Ando Masahiko M Ozaki Norio N

BMC psychiatry 20190620 1

<h4>Background</h4>Postpartum depression (PPD) is a major depressive disorder that occurs after childbirth. Objective diagnostic and predictive methods for PPD are important for early detection and appropriate intervention. DNA methylation has been recognized as a potential biomarker for major depressive disorder. In this study, we used methylation analysis and peripheral blood to search for biomarkers that could to lead to the development a predictive method for PPD.<h4>Methods</h4>Study partic ...[more]

PMID: 31221108

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Project description:IntroductionPostpartum depression (PPD) is a severe psychiatric disorder that negatively affects postnatal mothers worldwide. The aim of the study is to investigate the association between postpartum pain sensitivity and PPD as well as to identify the other potential risk factors for PPD and their interconnections.MethodsThe current study was a prospective observational clinical study that enrolled 210 singleton pregnant women in a tertiary referral hospital from January to December 2020. Postpartum pain sensitivity was assessed by the Mandarin Chinese version of the Pain Sensitivity Questionnaire (PSQ), and PSQ-C-total and PSQ-C-minor scores were collected. PPD was screened by self-reporting Edinburgh Postnatal Depression Scale (EPDS), and EPDS total score was recorded. The association between postpartum pain sensitivity and PPD, as well as the risk factors and their interconnections, was analyzed by using a combination of stratified, bivariate, correlation, receiver-operating characteristic (ROC) curve, multivariate logistic regression, and path analysis.ResultsOverall, 87 of 210 mothers (41.4%) screened positive for PPD. A positive correlation between PSQ-C-total (r = 0.67) or PSQ-C-minor (r = 0.62) and EPDS scores was identified. PSQ-C-total [area under curve (AUC) 0.89, 95% CI 0.84-0.93; P < 0.0001] showed significantly higher diagnostic accuracy compared with PSQ-C-minor (AUC 0.85, 95% CI 0.80-0.90; P < 0.0001) in predicting EPDS scores ≥ 10 points. Multivariate logistic regression indicated that a high PSQ-C-total score [adjusted odds ratio (OR) 1.12, 95% CI 1.08-1.51; P < 0.001] and gestational diabetes (adjusted OR 2.68, 95% CI 0.96-7.47; P = 0.045) were independent risk factors, while breastfeeding (adjusted OR: 0.34, 95% CI 0.15-0.78; P = 0.007) and normal birth weight (adjusted OR 0.17, 95% CI 0.05-0.61; P = 0.0047) were independently associated with decreasing adjusted ORs for EPDS scores ≥ 10 points. The path analysis model indicated that PSQ-C-total scores and gestational diabetes showed bidirectional effects, while birth weight and breastfeeding only had a direct impact on EPDS scores ≥ 10 points.ConclusionIncreased postpartum pain sensitivity was closely associated with EPDS scores ≥ 10 points, and PSQ-C scores could be a reliable predictor. Moreover, gestational diabetes, low occurrence of breastfeeding, and low birth weight were the risk factors for EPDS scores ≥ 10 points.Trial registrationChiCTR.org.cn identifier, ChiCTR-2000033091.

Dataset Information

Methylation analysis for postpartum depression: a case control study.

Publications

Methylation analysis for postpartum depression: a case control study.

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