Search

Objective: To investigate the relationship between preeclampsia and SARS-CoV-2 infection during pregnancy. Methods: This was a retrospective cohort study of pregnant women between March and October 2020. Pregnant patients admitted to 14 obstetrical centers in Michigan, USA formed the study population. Of the N = 1458 participants, 369 had SARS-CoV-2 infection (cases). Controls were uninfected pregnancies that were delivered in the same obstetric unit within 30 days of the index case. Robust Poisson regression was used to estimate relative risk (RR) of preterm and term preeclampsia and preeclampsia involving placental lesions. The analysis included adjustment for relevant clinical and demographic risk factors.Results: SARS-CoV-2 infection during pregnancy increased the risk of preeclampsia [adjusted aRR = 1.69 (1.26–2.26)], preeclampsia involving placental lesions [aRR = 1.97(1.14–3.4)] and preterm preeclampsia 2.48(1.48–4.17). Although the highest rate of preeclampsia was observed in patients infected with SARS-CoV-2 who were symptomatic (18.4%), there was increased risk even in asymptomatic SARS-CoV-2 infected patients (14.2%) relative to non-infected controls (8.7%) (p < 0.05). This association with symptomatology was also noted with preterm preeclampsia for which the rate doubled from 2.7% in controls to 5.2% in asymptomatic cases and reached 11.8% among symptomatic cases (p < 0.05). The rate of preterm preeclampsia among cases of pregnant people self-identified as Black reached 10.1% and was almost double the rate of the reminder of the group of infected pregnancies (5.3%), although the rate among uninfected was almost the same (2.7%) for both Black and non-Black groups (interaction p = 0.05).Conclusions: Infection with SARS-CoV-2 increases the risk of preeclampsia even in the absence of symptoms, although symptomatic persons are at even higher risk. Racial disparities in the development of preterm preeclampsia after SARS-CoV-2 infection may explain discrepancies in prematurity between different populations. [ABSTRACT FROM AUTHOR]

Introduction: Preeclampsia (PreE) remains a major source of maternal and newborn complications. Prenatal prediction of these complications could significantly improve pregnancy management. Objectives: Using metabolomic analysis we investigated the prenatal prediction of maternal and newborn complications in early and late PreE and investigated the pathogenesis of such complications. Methods: Serum samples from 76 cases of PreE (36 early-onset and 40 late-onset), and 40 unaffected controls were collected. Direct Injection Liquid Chromatography–Mass Spectrometry combined with Nuclear Magnetic Resonance (NMR) spectroscopy was performed. Logistic regression analysis was used to generate models for prediction of adverse maternal and neonatal outcomes in patients with PreE. Metabolite set enrichment analysis (MSEA) was used to identify the most dysregulated metabolites and pathways in PreE. Results: Forty-three metabolites were significantly altered (p < 0.05) in PreE cases with maternal complications and 162 metabolites were altered in PreE cases with newborn adverse outcomes. The top metabolite prediction model achieved an area under the receiver operating characteristic curve (AUC) = 0.806 (0.660–0.952) for predicting adverse maternal outcomes in early-onset PreE, while the AUC for late-onset PreE was 0.843 (0.712–0.974). For the prediction of adverse newborn outcomes, regression models achieved an AUC = 0.828 (0.674–0.982) in early-onset PreE and 0.911 (0.828–0.994) in late-onset PreE. Profound alterations of lipid metabolism were associated with adverse outcomes. Conclusion: Prenatal metabolomic markers achieved robust prediction, superior to conventional markers for the prediction of adverse maternal and newborn outcomes in patients with PreE. We report for the first-time the prediction and metabolomic basis of adverse maternal and newborn outcomes in patients with PreE. [ABSTRACT FROM AUTHOR]

The outbreak of the SARS-CoV-2 elicited a surge in publications. Obstetric reports were with few exceptions characterized by small sample sizes with potentially limited generalizability. In this review, evidence suggests increased susceptibility to COVID-19 in pregnancy; common pregnancy comorbidities may help explain worse outcomes. While the risk of death is low, pregnancy may be associated with increased need for ventilation. Prematurity rates seem to be increased but may be accounted for in part by higher cesarean rates, to a large degree accounted for by elective decision to shorten the course of the labor. Though fetal/neonatal complication rates may be higher in the presence of COVID-19 infection, survival rates seem unaffected and vertical transmission is rare. As the outbreak continues in the USA with resurgence in many other western countries that achieved initial success in suppressing the virus, much remains to be learned. For example, the question related to the degree to pregnancy modifying symptomatology remains open. Currently, routine polymerase chain reaction testing remains limited by supply shortages possibly delaying diagnosis until later in the course of the disorder and thus altering the symptom complex at presentation. To add to the knowledge base, we initiated a regional COVID-19 in pregnancy collaborative observational study with a coordinating center, standardized data collection and a shared database. This was facilitated by a longstanding tradition of collaboration among regional obstetric services. Over an anticipated two-year study duration, we expect to study 400 documented and suspected COVID-19 pregnancies with time and site of services controls for cohort effect and high power to detect several adverse maternal/infant outcomes. We include a complete listing of variables in our database, which, along with our experience in setting up our regional collaborative, we hope and believe will be of use in other settings. [ABSTRACT FROM AUTHOR]

COVID-19 has been reported to increase the risk of prematurity, however, due to the frequent absence of unaffected controls as well as inadequate accounting for confounders in many studies, the question requires further investigation. We sought to determine the impact of COVID-19 disease on preterm birth (PTB) overall, as well as related subcategories such as early prematurity, spontaneous, medically indicated preterm birth, and preterm labor (PTL). We assessed the impact of confounders such as COVID-19 risk factors, a-priori risk factors for PTB, symptomatology, and disease severity on rates of prematurity. This was a retrospective cohort study of pregnant women from March 2020 till October 1st, 2020. The study included patients from 14 obstetric centers in Michigan, USA. Cases were defined as women diagnosed with COVID-19 at any point during their pregnancy. Cases were matched with uninfected women who delivered in the same unit, within 30 d of the delivery of the index case. Outcomes of interest were frequencies of prematurity overall and subcategories of preterm birth (early, spontaneous/medically indicated, preterm labor, and premature preterm rupture of membranes) in cases compared to controls. The impact of modifiers of these outcomes was documented with extensive control for potential confounders. A p value <.05 was used to infer significance. The rate of prematurity was 8.9% in controls, 9.4% in asymptomatic cases, 26.5% in symptomatic COVID-19 cases, and 58.8% among cases admitted to the ICU. Gestational age at delivery was noted to decrease with disease severity. Cases were at an increased risk of prematurity overall [adjusted relative risk (aRR) = 1.62 (1.2–2.18)] and of early prematurity (<34 weeks) [aRR = 1.8 (1.02–3.16)] when compared to controls. Medically indicated prematurity related to preeclampsia [aRR = 2.46 (1.47–4.12)] or other indications [aRR = 2.32 (1.12–4.79)], were the primary drivers of overall prematurity risk. Symptomatic cases were at an increased risk of preterm labor [aRR = 1.74 (1.04–2.8)] and spontaneous preterm birth due to premature preterm rupture of membranes [aRR = 2.2(1.05–4.55)] when compared to controls and asymptomatic cases combined. The gestational age at delivery followed a dose-response relation with disease severity, as more severe cases tended to deliver earlier (Wilcoxon p <.05). COVID-19 is an independent risk factor for preterm birth. The increased preterm birth rate in COVID-19 was primarily driven by medically indicated delivery, with preeclampsia as the principal risk factor. Symptomatic status and disease severity were significant drivers of preterm birth. [ABSTRACT FROM AUTHOR]

Opioid abuse during pregnancy can result in Neonatal Opioid Withdrawal Syndrome (NOWS). We investigated genome-wide methylation analyses of 96 placental tissue samples, including 32 prenatally opioid-exposed infants with NOWS who needed therapy (+Opioids/+NOWS), 32 prenatally opioid-exposed infants with NOWS who did not require treatment (+Opioids/-NOWS), and 32 prenatally unexposed controls (-Opioids/-NOWS, control). Statistics, bioinformatics, Artificial Intelligence (AI), including Deep Learning (DL), and Ingenuity Pathway Analyses (IPA) were performed. We identified 17 dysregulated pathways thought to be important in the pathophysiology of NOWS and reported accurate AI prediction of NOWS diagnoses. The DL had an AUC (95% CI) =0.98 (0.95–1.0) with a sensitivity and specificity of 100% for distinguishing NOWS from the +Opioids/-NOWS group and AUCs (95% CI) =1.00 (1.0–1.0) with a sensitivity and specificity of 100% for distinguishing NOWS versus control and + Opioids/-NOWS group versus controls. This study provides strong evidence of methylation dysregulation of placental tissue in NOWS development. • Epigenetic mechanisms in the placenta related to in-utero opioid-exposed infants with Neonatal Opioid Withdrawal Syndrome (NOWS) was described • Significant epigenetic changes were observed in multiple genes belonging to 17 molecular pathways. • Many of the neuronal and brain pathways showing epigenetic dysregulation are involved in opioid use disorder and NOWS. • There are detectable epigenetic changes in placenta that predict drug withdrawal signs. • These results provide a foundation for future large-scale epigenomic studies of NOWS in diverse patient populations. [ABSTRACT FROM AUTHOR]