Evaluating Stochastic Epigenetic Mutations as Potential Mechanism Translating Psychosocial Stressors into Risk for Postpartum Depression Restricted; Files Only

Todd, Julianne (Fall 2022)

Permanent URL: https://etd.library.emory.edu/concern/etds/jh343t679?locale=pt-BR%2A
Published

Abstract

Psychosocial stress has previously been shown to associate with poor health outcomes and is consistently correlated with risk for postpartum depressive symptoms. While some epigenetic mechanisms have been investigated as potential sources conferring risk or generating interindividual variation in the experience of negative outcomes, the role of stochastic epigenetic mutations (SEMs) has never been investigated. SEMs are random extreme high or low methylation outliers that are unremitting and have the potential to cause more severe cellular dysfunction when compared to less extreme methylation values.

This secondary analysis sought to determine whether an association exists between the experience of psychosocial stress in childhood or pregnancy associated with the number of SEMs in peripheral blood mononuclear cells (PBMCs) taken during routine prenatal visits. Furthermore, this study also investigated whether the number of SEMs in prenatal blood samples was correlated to the presence and severity of postpartum depressive symptoms. Data for this study was derived from existing study records collected from approximately 350 pregnant African America individuals who enrolled in longitudinal research during their first trimester at prenatal care clinics at Emory Midtown and Grady hospitals. Many of these individuals continued enrollment throughout pregnancy and the postpartum period.

Linear and logistic regression models were used to determine whether associations exist between various measures of psychosocial stress and adversity, SEMs, and postpartum depressive symptoms. Findings from these models suggest that there is no significant association between these variables in this sample, but further efforts should be made to determine whether this lack of association is inherent to the variables’ relationships or due to a methodological limitation that require further investigation.

Table of Contents

Introduction 1

Study 1a: Exposure to Early Childhood Stressors and Stochastic Epigenetic Mutations: Findings from a Cohort of African American Expectant Mothers 13

Study 1b: Stress and Trauma in Pregnancy: Exploring the Relationship between Presence of Perinatal Stressors and the number of Stochastic Epigenetic Mutations in Expectant Mothers 27

Study 2: Relationship between Stochastic Epigenetic Mutations and Maternal Mental Health: Utilization of a Novel Epigenetic Analysis to Understand Potential Mechanisms of Risk for Postpartum Depression 42

Evaluating Stochastic Epigenetic Mutations as Potential Mechanism Translating Psychosocial Stressors into Risk for Postpartum Depression: Results, Lessons Learned, and Future Directions 55

Tables and Figures

Tables and Figures Relevant to Study 1a: Exposure to Early Childhood Stressors and Stochastic Epigenetic Mutations

Table 1: Participant demographics and study variable descriptions 62

Figures 1a-b: Density plots of SEM values and natural log transformed SEM values 63

Table 2: Blood cell type descriptive statistics and correlations with SEM values 64

Appendix Table 1: Association between SEM values and other potential covariates associated with poor maternal outcomes 65

Appendix Table 2a-b: Descriptive statistics of CTQ and ACE scores & Comparison of covariates across groups dichotomized by severity of stress on CTQ 66

Table 3: Cronbach’s α of the Childhood Trauma Questionnaire (CTQ) subscales 67

Table 4: Unadjusted and adjusted linear models comparing SEM values to continuous CTQ total score, CTQ subscale scores, and ACE total score 68

Table 5: Unadjusted and adjusted linear models comparing SEM values to dichotomized CTQ total score, CTQ subscale scores, and ACE total score 69

Appendix Table 3: ANOVAs comparing initial model of covariates to models containing stress measures as predictors 70

Tables and Figures Relevant to Study 1b: Stress and Trauma in Pregnancy

Table 6: Participant demographics and study variable descriptions 71

Figures 2a-b: Density Plots of SEM values and natural log transformed SEM values 72

Table 7: Descriptive statistics of PSS and SLEI scores 73

Table 8: Blood cell type descriptive statistics and correlations with SEM values 74

Appendix Table 4: Association between SEM values and other potential covariates associated with poor maternal outcomes 75

Table 9: Unadjusted and adjusted linear models comparing SEM values to continuous PSS total score, PSS subscale scores, and SLEI total score 76

Figure 3: Natural log of SEM values by perceived stress level 77

Table 10: Comparisons of SEM Values across perceived stress levels 78

Table 11: Significance of interaction term in moderation analysis 79

Tables and Figures Relevant to Study 2: Relationship between Stochastic Epigenetic Mutations and Maternal Mental Health

Table 12: Participant demographics and study variable descriptions 80

Figures 4a-b: Density plots of SEM values and natural log transformed SEM values 82

Tables 13a-b: Unadjusted associations between blood cell estimates and highest postpartum EPDS score & Unadjusted and adjusted associations between potential covariates and highest postpartum EPDS score 83

Appendix Table 5: Blood cell type descriptive statistics and correlations with SEM values 84

Appendix Table 6: Associations between potential covariates and SEM values (predictor) 85

Figures 5a-b: Scatterplot of highest EPDS total score during postpartum period versus natural log of SEM values calculated from blood drawn at 2nd trimester prenatal visit & Scatterplot of EPDS total score during 2nd trimester prenatal visit versus natural log of SEM values calculated from blood drawn at same visit 86

Tables and Figures Relevant to Concluding Chapter

Figures 6a-b: Expected methylation distribution and suspected SNP distribution 87

Table 14: CpG sites with highest SEM occurrence 87

References 88

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