Examining Genetically Regulated Gene Expression As A Potential Biomarker For Postpartum Depression Screening
Date of Award
Master of Public Health (MPH)
School of Public Health
Background: PPD is one of most common complications of pregnancy but is underdiagnosed and undertreated with less than 10% of women with PPD receiving adequate treatment. Currently, the most well-validated screening questionnaire for perinatal depression, the EPDS, produces a high false positive rate and results in a large number of unnecessary referrals. Objective: The principal emphasis of this investigation will center upon the estrogen sensitivity, which hypothesizes that individuals with a history of PPD will have differences in estrogen receptor gene (ESR1 and ESR2) mediated responses to estradiol and thus, are likely to be more sensitive to the abrupt drop in estrogen in the postpartum period that results in PPD development. And determine if genetically regulated gene expression can predict dynamically regulated pregnancy and PPD symptoms. Methods: PrediXcan was utilized to impute predicted brain tissue and whole blood gene expression and determine genetic association to measured EPDS scores at four time points in the MAWS cohort (T1: n = 678, T2: N = 594, T3: N = 563, T4: N = 551). Additionally, PCA analysis was performed to reduce dimensionality and identify the main axes of variance in the final list of genetically regulated gene expression in each tissue. Results: There was no significant association between genetically regulated gene expression and EPDS scores at all time points. OGFR, was shown to be somewhat predictive at three timepoints. Conclusion: Further studies are needed to elucidate genomic contributions to PPD and the role of estrogen in PPD pathogenesis. Current focus should be on PPD interventions that target known risk factors.
Zhu, Eileen, "Examining Genetically Regulated Gene Expression As A Potential Biomarker For Postpartum Depression Screening" (2023). Public Health Theses. 2369.
This thesis is restricted to Yale network users only. It will be made publicly available on 05/10/2025