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Through a recent cross species translational experiment, researchers have identified a set of epigenetic marks capable of predicting postpartum depression with greater than 85% accuracy. The researchers are looking to identify a group of women from both the general population and those with a history of mood disorders who are at risk for postpartum depression and obtain brain imaging data at a postpartum time period prior to the onset of depressive symptoms and compare it with those obtained during depressive episodes. The researchers will also evaluate the efficacy of postpartum depression biomarker prediction.
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Postpartum depression (PPD) occurs in approximately 10-18% of women from the general population, affecting ~400,000 to 800,000 women each year. PPD results in significant morbidity to both mother and child, with offspring risks including low self-esteem, low intellectual skills, child abuse, and infanticide. PPD occurs within four weeks following parturition according to Diagnostic and Statistical Manual (DSM)-IV criteria and follows a dramatic drop in the circulating levels of estradiol (E2) and progesterone (P4). While PPD risk is not predicted by serum levels of gonadal hormones in humans, numerous studies suggest that risk to PPD is mediated by hormonal sensitivity. Recently, the investigators demonstrated that women at risk to PPD demonstrate an increased sensitivity to E2 mediated DNA methylation reprogramming at hippocampally relevant genes and identified two biomarkers, Tetratricopeptide repeat protein 9B (TTC9B) and heterochromatin protein 1 binding protein 3 (HP1BP3) that appeared functionally related to modulating neuroplasticity and which were predictive of PPD with 82-96% accuracy. Given that peripherally measurable epigenetic marks in genes implicated in hormone related neuroplastic changes may underlie risk to PPD, it is logical to next investigate neuroconnectivity alterations occurring longitudinally in the postpartum population at risk for PPD. The study is divided into two waves; in wave 1, the researchers will draw a tube of blood to be used as a biomarker screening to identify those at risk for PPD and matched controls, who will be asked to enter wave 2 of the study. In wave 2, women will undergo neuroimaging at weeks 2 and 6 postpartum in hopes to gather a neural signature of PPD prior to the onset of symptoms and while experiencing the symptoms. Additionally, data on a variety of candidate moderators of depression during or after pregnancy will be collected at each visit. This includes history of premenstrual symptoms, use of oral contraceptives, use of hormonal treatments to promote pregnancy and psychiatric history during previous pregnancies and the postpartum. Several measures of mood symptoms and anxiety symptoms will be administered including: Edinburgh Postnatal Depression Rating Scale (EPDS) which measures depressive symptoms in pregnant and postpartum mothers, the Young Mania Rating Scale, which rates manic and hypomanic symptoms, and the State Trait Anxiety Inventory, Perinatal Anxiety Scale, and the Penn State Worry questionnaire which measure anxiety symptoms. The Pittsburgh Sleep Quality Index scale will be administered at every visit to assess the role of sleep in the relapse of depression in the mothers. Two scales designed to measure stress will be administered to allow examination of its potential role in Major Depressive Disorder (MDD) relapse. The Recent Life Changes Scale, which measures stressful life events, will be administered at the Screening, 3rd trimester and 6 week visits. The Perceived Stress Scale which provides a subjective rating of the stress of will be administered at every visit. The investigators will also administer measures of childhood trauma, and note demographic information, medication usage, clinical history (e.g. number of hospitalizations, medication trials, etc.) and birth outcomes. These measures will be used in future exploratory analyses of potential moderators of epigenetic changes seen during and after pregnancy.
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80 participants in 4 patient groups
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Data sourced from clinicaltrials.gov
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