An immune clock of human pregnancy

Association between inflammatory biomarkers before pregnancy and risk of perinatal depression: A prospective cohort study of 4483 women in Sweden

AIM

Perinatal depression (PND) is a global health concern, affecting millions of childbearing women. Emerging data suggest that inflammation may play a role in the development of PND. Peripheral blood inflammatory biomarkers before pregnancy are widely tested in clinical practice at minimum cost, yet their potential role in PND risk remains unknown.

METHODS

We conducted a prospective cohort study of 4483 birthing women during 2009-2021 within the LifeGene study with linkage to Swedish registers. Peripheral blood inflammatory biomarkers were profiled at baseline. Cases of PND were identified using validated tools or clinical diagnosis from subsequent pregnancies and postpartum periods. Logistic regression models were employed to assess the associations of each inflammatory biomarker (z scored) with PND.

RESULTS

We identified 495 (11.0 %) PND cases with an average age of 29.2 years. Pre-pregnancy platelet-to-lymphocyte ratio (PLR) was positively associated [OR, 95 % CI:1.14(1.01,1.27)], while lymphocyte count was inversely associated [OR, 95 % CI: 0.89(0.80,0.98)] with PND. A dose-response relationship was indicated for both PLR and lymphocytes when analyzed in categories based on tertile distribution. These associations appeared more pronounced for postpartum depression than antepartum depression and were independent of psychiatric comorbidities.

CONCLUSION

With implications for future mechanistic research, these findings suggest that blood levels of lymphocytes and PLR before pregnancy are associated with subsequent risk of PND in a dose-response manner.

Immune changes in pregnancy: associations with pre-existing conditions and obstetrical complications at the 20th gestational week-a prospective cohort study

BACKGROUND

Pregnancy is a complex biological process and serious complications can arise when the delicate balance between the maternal and semi-allogeneic fetal immune systems is disrupted or challenged. Gestational diabetes mellitus (GDM), pre-eclampsia, preterm birth, and low birth weight pose serious threats to maternal and fetal health. Identification of early biomarkers through an in-depth understanding of molecular mechanisms is critical for early intervention.

METHODS

We analyzed the associations between 47 proteins involved in inflammation, chemotaxis, angiogenesis, and immune system regulation, maternal and neonatal health outcomes, and the baseline characteristics and pre-existing conditions of the mother in a prospective cohort of 1049 pregnant women around the 20th gestational week. We used Bayesian linear regression models to examine the impact of risk factors on biomarker levels and Bayesian cause-specific parametric proportional hazards models to analyze the effect of biomarkers on maternal and neonatal outcomes. We evaluated the predictive value of baseline characteristics and 47 proteins using machine-learning models and identified the most predictive biomarkers using Shapley additive explanation scores.

RESULTS

Associations were identified between specific inflammatory markers and several conditions, including maternal age and pre-pregnancy body mass index, chronic diseases, complications from prior pregnancies, and COVID-19 exposure. Smoking during pregnancy affected GM-CSF and 9 other biomarkers. Distinct biomarker patterns were observed for different ethnicities. Within obstetric complications, IL-6 inversely correlated with pre-eclampsia risk, while birth weight to gestational age ratio was linked to markers including VEGF and PlGF. GDM was associated with IL-1RA, IL-17D, and eotaxin-3. Severe postpartum hemorrhage correlated with CRP, IL-13, and proteins of the IL-17 family. Predictive modeling yielded area under the receiver operating characteristic curve values of 0.708 and 0.672 for GDM and pre-eclampsia, respectively. Significant predictive biomarkers for GDM included IL-1RA and eotaxin-3, while pre-eclampsia prediction yielded the highest predictions when including MIP-1β, IL-1RA, and IL-12p70.

CONCLUSIONS

Our study provides novel insights into the interplay between preexisting conditions and immune dysregulation in pregnancy. These findings contribute to our understanding of the pathophysiology of obstetric complications and the identification of novel biomarkers for early intervention(s) to improve maternal and fetal health.

Engineered exosome as a biological nanoplatform for drug delivery of Rosmarinic acid to improve implantation in mice with induced endometritis

Endometritis is an inflammatory and histopathologic disease in uterine tissues that interferes with the proper decidualization and implantation of the embryo. In this study, rosmarinic acid (RA) is used as an anti-inflammatory agent that encapsulates in exosomes and is used to attenuate lipopolysaccharide (LPS)-induced endometritis and improve implantation. For this purpose, exosomes were loaded with RA and then administrated into the animal groups, including RA, exosome, RA plus exosome (RA + Exo), and RA-loaded exosomes (RALExo) groups. The concentrations of RA or exosomes used in this study were 10 mg/kg, and the compounds were injected into the uterine horn 24 h following the induction of endometritis. Upon the presence of inflammation detected by the histopathological method, the most proper groups were mated with male mice. The effect of the treatment group on the implantation rate, progesterone levels, and gene expressions were assessed by Chicago Blue staining, enzyme-linked immunosorbent assay (ELISA), and Quantitative PCR (qPCR), respectively. Results showed RALExo10 and RA10 + Exo10 groups improved pathological alterations, enhanced progesterone levels, increased implantation rate, as well as heightened expression levels of Leukemia inhibitory factor (LIF) and Mucin-16 (MUC-16) genes. Besides, the expression levels of inflammatory cytokines, including Transforming growth factor-β (TGF-β), Interlukine-10 (IL-10), Interlukine-15 (IL-15), and Interlukine-18 (IL-18), were regulated. Our findings indicated that the expression of LIF, Muc-16 genes as well as IL-18, were significantly correlated with serum progesterone concentrations and the implantation rate in the treatment groups. The RALExo10 and RA10 + Exo10 groups showed ameliorated implantation rates in experimental groups.

Placenta a potential gateway of prenatal SARS-CoV-2 infection: A review

SARS-CoV-2, the causative agent of COVID-19, can infect various tissues in the body apart from the lungs. Although placental infection remains controversial, COVID-19-associated placental abnormalities have been reported worldwide. Therefore, COVID-19 poses a significant risk for fetal distress as well. Scientists are currently debating whether such distress results from direct viral induced assault or placental damage caused by the mother's immune response. The placenta develops different histopathological lesions in response to maternal SARS-CoV-2 infection. While some studies support both theories, the transmission rate through the placenta remains low. Therefore, a more in-depth study is necessary to determine the primary cause of maternal SARS-CoV-2-induced fetal distress. This comprehensive review is aimed to shed light on the possible reasons towards fetal distress among mothers with COVID-19. This review describes the various mechanisms of viral entry along with the mechanisms by which the virus could affect the placenta. Reported cases of placental abnormalities and fetal distress symptoms have been collated to provide an overview of the current state of knowledge on vertical transmission of COVID-19.

Characterization of COVID-19 infected pregnant women with ICU admission and the risk of preterm: A cluster analysis

BACKGROUND

The unique physiological changes during pregnancy present challenges in understanding the full scope and effects of COVID-19 on pregnant women, adding complexity to their medical management. Given the significant changes in the immune, circulatory, respiratory, and hormonal systems during the progression of the pregnancy, and the specific factors with higher risk of COVID-19, like metabolic, vascular, and endothelial factors, typically also associated with maternal and neonatal unfavorable outcomes, the full understanding of how COVID-19 affects pregnant women is not clarified yet.

METHODS

In this study, anonymous data from medical records of pregnant women with lab-confirmed COVID-19 in Astana, Kazakhstan from May 1, 2021, to July 14, 2021, were collected retrospectively. A multivariate regression model was built to identify factors associated with the risk of ICU admission. Cluster analysis was performed to identify distinct groups among women admitted to the ICU based on their blood parameters, coagulation profiles, and oxygenation saturation levels.

RESULTS

10.7 % of pregnant women were admitted to ICU. Among them, 4.36 % were in the 2nd trimester and 13.58 % in the 3rd trimester. No women in the 1st trimester were admitted to ICU. A multivariate regression model demonstrates that gestational diabetes, leukocytes, CRP, and saturation were the factors significantly associated with a higher risk of ICU admission. Three clusters of pregnant women were segmented, and preterm birth was frequent in clusters 1 (serious systemic conditions affecting multiple organs) and 3 (women with hypertension and preeclampsia), whereas cluster 2 represents women who can also be characterized as suffering from infections with a possible autoimmune component. Neutrophil to lymphocyte ratio was frequent in clusters 1 and 3.

CONCLUSION

In this study, multivariable analysis identified factors with a risk of ICU admission, and clustering analysis helped to identify groups of COVID-19-infected pregnant women admitted to ICU with similar risk profiles. Differences in clusters can help to explain discrepancies in COVID-19 outcomes and suggest biochemical and molecular mechanisms involved in COVID-19 and outline a more personalized approach to understanding, diagnosing, and treating women.

Single-cell profiling of the peripheral blood immune landscape during mid- and late-stage pregnancy

We aimed to determine the peripheral blood mononuclear cell (PBMC) immune profiles of mid- and late-stage pregnant women to establish a foundation for studying pregnancy-related diseases. Peripheral blood samples were collected from three women each during mid- and late-stage pregnancy, and PBMCs were extracted for single-cell RNA sequencing (scRNA-seq). Peripheral blood samples were also collected for flow cytometry analysis to validate the analytical results. HOPX+ CD4+ T cells, ZNF683+CD8+ T cells, and KLRB1+CD8+ T cells significantly differed in quantitative ratio and gene transcript level between women at mid- and late-stage pregnancy. In late pregnancy, cell-to-cell communication was enhanced and effector CD8+ T cells highly expressed infection-related pathways. A rare T cell subtype, "XIST+ T cells," exhibited high XIST expression, a gene that may be involved in the regulation of immune-related gene transcription and translation, and insulin signaling pathway, during pregnancy. Monocytes exhibited significant proinflammatory and metabolic properties in mid- and late-stage pregnancy, respectively. Natural killer (NK) cells were mainly involved in T- and B-cell-mediated signaling pathways, and in T cell differentiation, in mid-pregnancy. Enhanced innate immunity of NK cells was observed. Moreover, NK cells expressed genes associated with diabetes-related pathways in late-stage pregnancy. To conclude, we present detailed changes in the immune response occurring in pregnant women from mid- to late-stage gestation, revealing significant differences in PBMC subtypes and molecular properties. These findings provide insights into the physiopathological mechanisms of chronic hepatitis B infection, systemic lupus erythematosus, and gestational diabetes mellitus underlying systemic immune responses during mid- and late-stage pregnancy.NEW & NOTEWORTHY There are significant differences in three subtypes of memory/effector T cells (HOPX+ CD4+ T cells, ZNF683+CD8+ T cells, and KLRB1+CD8+ T cells) between mid- and late pregnancy. In late pregnancy, intercellular interaction was enhanced and effector CD8+ T cells highly expressed infection-related pathways. A rare T cell subtype, "XIST+ T cells," may be involved in the regulation of immune-related gene transcription and translation with a strong female bias.

Prediction of risk for early or very early preterm births using high-resolution urinary metabolomic profiling

BACKGROUND

Preterm birth (PTB) is a serious health problem. PTB complications is the main cause of death in infants under five years of age worldwide. The ability to accurately predict risk for PTB during early pregnancy would allow early monitoring and interventions to provide personalized care, and hence improve outcomes for the mother and infant.

OBJECTIVE

This study aims to predict the risks of early preterm (< 35 weeks of gestation) or very early preterm (≤ 26 weeks of gestation) deliveries by using high-resolution maternal urinary metabolomic profiling in early pregnancy.

DESIGN

A retrospective cohort study was conducted by two independent preterm and term cohorts using high-density weekly urine sampling. Maternal urine was collected serially at gestational weeks 8 to 24. Global metabolomics approaches were used to profile urine samples with high-resolution mass spectrometry. The significant features associated with preterm outcomes were selected by Gini Importance. Metabolite biomarker identification was performed by liquid chromatography tandem mass spectrometry (LCMS-MS). XGBoost models were developed to predict early or very early preterm delivery risk.

SETTING AND PARTICIPANTS

The urine samples included 329 samples from 30 subjects at Stanford University, CA for model development, and 156 samples from 24 subjects at the University of Alabama, Birmingham, AL for validation.

RESULTS

12 metabolites associated with PTB were selected and identified for modelling among 7,913 metabolic features in serial-collected urine samples of pregnant women. The model to predict early PTB was developed using a set of 12 metabolites that resulted in the area under the receiver operating characteristic (AUROCs) of 0.995 (95% CI: [0.992, 0.995]) and 0.964 (95% CI: [0.937, 0.964]), and sensitivities of 100% and 97.4% during development and validation testing, respectively. Using the same metabolites, the very early PTB prediction model achieved AUROCs of 0.950 (95% CI: [0.878, 0.950]) and 0.830 (95% CI: [0.687, 0.826]), and sensitivities of 95.0% and 60.0% during development and validation, respectively.

CONCLUSION

Models for predicting risk of early or very early preterm deliveries were developed and tested using metabolic profiling during the 1st and 2nd trimesters of pregnancy. With patient validation studies, risk prediction models may be used to identify at-risk pregnancies prompting alterations in clinical care, and to gain biological insights of preterm birth.

Towards a new taxonomy of preterm birth

Disease categories traditionally reflect a historical clustering of clinical phenotypes based on biologic and nonbiologic features. Multiomics approaches have striven to identify signatures to develop individualized categorizations through tests and/or therapies for 'personalized' medicine. Precision health classifies clinical syndromes into endotype clusters based on novel technological advancements, which can reveal insights into the etiologies of phenotypical syndromes. A new taxonomy of preterm birth should be considered in this context, as not all preterm infants of similar gestational ages are the same because most have different biologic vulnerabilities and hence different health trajectories. Even the choice of interventions may affect observed clinical conditions. Thus, a new taxonomy of prematurity would help to advance the field of neonatology, but also obstetrics and perinatology by adopting anticipatory and more targeted approaches to the care of preterm infants with the intent of preventing and treating some of the most common newborn pathologic conditions.

Inflammatory signalling during the perinatal period: Implications for short- and long-term disease risk

During pregnancy and the postpartum, there are dynamic fluctuations in steroid and peptide hormone levels as well as inflammatory signalling. These changes are required for a healthy pregnancy and can persist well beyond the postpartum. Many of the same hormone and inflammatory signalling changes observed during the perinatal period also play a role in symptoms related to autoimmune disorders, psychiatric disorders, and perhaps neurodegenerative disease later in life. In this review, we outline hormonal and immunological shifts linked to pregnancy and the postpartum and discuss the possible role of these shifts in increasing psychiatric, neurodegenerative disease risk and autoimmune symptoms during and following pregnancy. Furthermore, we discuss how key variables such as the number of births (parity) and sex of the fetus can influence inflammatory signalling, and possibly future disease risk, but are not often studied. We conclude by discussing the importance of studying female experiences such as pregnancy and parenting on physiology and disease.

Regulators of placental antibody transfer through a modeling lens

Infants are vulnerable to infections owing to a limited ability to mount a humoral immune response and their tolerogenic immune phenotype, which has impeded the success of newborn vaccination. Transplacental transfer of IgG from mother to fetus provides crucial protection in the first weeks of life, and maternal immunization has recently been implemented as a public health strategy to protect newborns against serious infections. Despite their early success, current maternal vaccines do not provide comparable protection across pregnancies with varying gestational lengths and placental and maternal immune features, and they do not account for the dynamic interplay between the maternal immune response and placental transfer. Moreover, progress toward the rational design of maternal vaccines has been hindered by inadequacies of existing experimental models and safety challenges of investigating longitudinal dynamics of IgG transfer in pregnant humans. Alternatively, in silico mechanistic models are a logical framework to disentangle the processes regulating placental antibody transfer. This Review synthesizes current literature through a mechanistic modeling lens to identify placental and maternal regulators of antibody transfer, their clinical covariates, and knowledge gaps to guide future research. We also describe opportunities to use integrated modeling and experimental approaches toward the rational design of vaccines against existing and emerging neonatal pathogen threats.

Distinct maternofetal immune signatures delineate preterm birth onset following urinary tract infection

Preterm birth is the leading cause of infant mortality resulting in over one million neonatal deaths annually. Maternal urinary tract infection (UTI) during pregnancy increases risk for preterm birth; however, biological processes mediating UTI-associated preterm birth are not well-described. We established a murine maternal UTI model in which challenge with uropathogenic E. coli resulted in preterm birth in about half of dams. Dams experiencing preterm birth displayed excessive bladder inflammation and altered uteroplacental T cell polarization compared to non-laboring infected dams, with no differences in bacterial burdens. Additional factors associated with preterm birth included higher proportions of male fetuses and lower maternal serum IL-10. Furthermore, exogenous maternal IL-10 treatment absolved UTI-associated preterm birth but contributed to fetal growth restriction in this model. Using urine samples from a cohort of human pregnancies with or without UTI, we correlated urinary cytokines with birth outcomes and urine culture status. These analyses yielded a non-invasive, highly predictive three-model system for evaluating preterm birth risk implicating cytokines IL-10, IL-15, IL-1β, and IL-1RA. Our unique bimodal murine model coupled with patient samples provides a platform to investigate immunological and microbial factors governing UTI-associated preterm birth, revealing novel therapeutic opportunities to predict or prevent preterm birth.

Discrimination of primary and chronic cytomegalovirus infection based on humoral immune profiles in pregnancy

BACKGROUNDMost humans have been infected with cytomegalovirus (CMV) by midlife without clinical signs of disease. However, in settings in which the immune system is undeveloped or compromised, the virus is not adequately controlled and consequently presents a major infectious cause of both congenital disease during pregnancy as well as opportunistic infection in children and adults. With clear evidence that risk to the fetus varies with gestational age at the time of primary maternal infection, further research on humoral responses to primary CMV infection during pregnancy is needed.METHODSHere, systems serology tools were applied to characterize antibody responses to CMV infection in pregnant and nonpregnant women experiencing either primary or chronic infection.RESULTSWhereas strikingly different antibody profiles were observed depending on infection status, limited differences were associated with pregnancy status. Beyond known differences in IgM responses used clinically for identification of primary infection, distinctions observed in IgA and FcγR-binding antibodies and among antigen specificities accurately predicted infection status. Machine learning was used to define the transition from primary to chronic states and predict time since infection with high accuracy. Humoral responses diverged over time in an antigen-specific manner, with IgG3 responses toward tegument decreasing over time as typical of viral infections, while those directed to pentamer and glycoprotein B were lower during acute and greatest during chronic infection.CONCLUSIONIn sum, this work provides insights into the antibody response associated with CMV infection status in the context of pregnancy, revealing aspects of humoral immunity that have the potential to improve CMV diagnostics.FUNDINGCYMAF consortium and NIH NIAID.

Solubilized β-Glucan Supplementation in C57BL/6J Mice Dams Augments Neurodevelopment and Cognition in the Offspring Driven by Gut Microbiome Remodeling

A maternal diet rich in dietary fiber, such as β-glucan, plays a crucial role in the offspring's acquisition of gut microbiota and the subsequent shaping of its microbiome profile and metabolome. This in turn has been shown to aid in neurodevelopmental processes, including early microglial maturation and immunomodulation via metabolites like short chain fatty acids (SCFAs). This study aimed to investigate the effects of oat β-glucan supplementation, solubilized by citric acid hydrolysis, from gestation to adulthood. Female C57BL/6J mice were orally supplemented with soluble oat β-glucan (ObG) or carboxymethyl cellulose (CMC) via drinking water at 200 mg/kg body weight during breeding while the control group received 50 mg/kg body weight of carboxymethyl cellulose. ObG supplementation increased butyrate production in the guts of both dams and 4-week-old pups, attributing to alterations in the gut microbiota profile. One-week-old pups from the ObG group showed increased neurodevelopmental markers similar to four-week-old pups that also exhibited alterations in serum markers of metabolism and anti-inflammatory cytokines. Notably, at 8 weeks, ObG-supplemented pups exhibited the highest levels of spatial memory and cognition compared to the control and CMC groups. These findings suggest a potential enhancement of neonatal neurodevelopment via shaping of early-life gut microbiome profile, and the subsequent increased later-life cognitive function.

Temporal Dynamics of Oxidative Stress and Inflammation in Bronchopulmonary Dysplasia

Bronchopulmonary dysplasia (BPD) is the most common lung complication of prematurity. Despite extensive research, our understanding of its pathophysiology remains limited, as reflected by the stable prevalence of BPD. Prematurity is the primary risk factor for BPD, with oxidative stress (OS) and inflammation playing significant roles and being closely linked to premature birth. Understanding the interplay and temporal relationship between OS and inflammation is crucial for developing new treatments for BPD. Animal studies suggest that OS and inflammation can exacerbate each other. Clinical trials focusing solely on antioxidants or anti-inflammatory therapies have been unsuccessful. In contrast, vitamin A and caffeine, with antioxidant and anti-inflammatory properties, have shown some efficacy, reducing BPD by about 10%. However, more than one-third of very preterm infants still suffer from BPD. New therapeutic agents are needed. A novel tripeptide, N-acetyl-lysyltyrosylcysteine amide (KYC), is a reversible myeloperoxidase inhibitor and a systems pharmacology agent. It reduces BPD severity by inhibiting MPO, enhancing antioxidative proteins, and alleviating endoplasmic reticulum stress and cellular senescence in a hyperoxia rat model. KYC represents a promising new approach to BPD treatment.

Conditional Similarity Triplets Enable Covariate-Informed Representations of Single-Cell Data

Single-cell technologies enable comprehensive profiling of diverse immune cell-types through the measurement of multiple genes or proteins per cell. In order to translate data from immune profiling assays into powerful diagnostics, machine learning approaches are used to compute per-sample immunological summaries, or featurizations that can be used as inputs to models for outcomes of interest. Current supervised learning approaches for computing per-sample representations are optimized based only on the outcome variable to be predicted and do not take into account clinically-relevant covariates that are likely to also be measured. Here we expand the optimization problem to also take into account such additional patient covariates to directly inform the learned per-sample representations. To do this, we introduce CytoCoSet, a set-based encoding method, which formulates a loss function with an additional triplet term penalizing samples with similar covariates from having disparate embedding results in per-sample representations. Overall, incorporating clinical covariates leads to improved prediction of clinical phenotypes.

Maternal immunity shapes biomarkers of germinal center development in HIV-exposed uninfected infants

Introduction

HIV-exposed uninfected (HEU) infants exhibit elevated pro-inflammatory biomarkers that persist after birth. However, comprehensive assessments of bioprofiles associated with immune regulation and development in pregnant women with HIV (PWH) and HEU infants has not been performed. Maternal immunity in PWH may be imprinted on their HEU newborns, altering immune bioprofiles during early immune development.

Methods

Cryopreserved paired plasma samples from 46 HEU infants and their mothers enrolled in PACTG 316, a clinical trial to prevent perinatal HIV-1 transmission were analyzed. PWH received antiretrovirals (ARV) and had either fully suppressed or unsuppressed viral replication. Maternal blood samples obtained during labor and infant samples at birth and 6 months were measured for 21 biomarkers associated with germinal centers (GC), macrophage activation, T-cell activation, interferon gamma (IFN-γ)-inducible chemokines, and immune regulatory cytokines using Mesoscale assays. Pregnant women without HIV (PWOH) and their HIV unexposed uninfected (HUU) newborns and non-pregnant women without HIV (NPWOH) served as reference groups. Linear regression analysis fitted for comparison among groups and adjusted for covariant(s) along with principal component analysis performed to assess differences among groups.

Results

Compared with NPWOH, PWOH displayed higher levels of GC, macrophage, and regulatory biomarkers. PWH compared to PWOH displayed elevated GC, T cell activation, and IFN-γ-inducible chemokines biomarkers at delivery. Similar to their mothers, HEU infants had elevated GC, macrophage, and IFN-γ-inducible chemokines, as well as elevated anti-inflammatory cytokines, IL-10 and IL-1RA. Across all mother/newborn dyads, multiple biomarkers positively correlated, providing further evidence that maternal inflammation imprints on newborn bioprofiles. By 6 months, many HEU biomarkers normalized to levels similar to HUU infants, but some GC and inflammatory biomarkers remained perturbed. Bioprofiles in PWH and HEU infants were similar regardless of the extent of maternal viral suppression by ARV.

Conclusions

GC immune pathways are perturbed in HEU newborns, but immune regulatory responses down regulate inflammation during early infancy, indicating a transient inflammatory effect. However, several GC biomarkers that may alter immune development remain perturbed.

COVID-19 vaccination before or during pregnancy results in high, sustained maternal neutralizing activity to SARS-CoV-2 wild-type and Delta/Omicron variants of concern, particularly following a booster dose or infection

OBJECTIVES

To investigate multi-dose and timings of COVID-19 vaccines in preventing antenatal infection.

DESIGN

Prospective observational study investigating primary vaccinations, boosters, antenatal COVID-19 infections, neutralizing antibody (Nab) durability, and cross-reactivity to Delta and Omicron variants of concern (VOCs).

RESULTS

Ninety-eight patients completed primary vaccination prepregnancy (29.6%) and antenatally (63.3%), 24.2% of whom had antenatal COVID-19, while 7.1% were unvaccinated (28.6% had antenatal COVID-19). None had severe COVID-19. Prepregnancy vaccination resulted in vaccination-to-infection delay of 23.3 weeks, which extended to 45.2 weeks with a booster, compared to 16.9 weeks following antenatal vaccination (P < 0.001). Infections occurred at 26.2 weeks gestation in women vaccinated prepregnancy compared to 36.2 weeks gestation in those vaccinated during pregnancy (P < 0.007). The risk of COVID-19 infection was higher without antenatal vaccination (hazard ratio [HR] 14.6, P = 0.05) and after prepregnancy vaccination without a booster (HR 10.4, P = 0.002). Antenatal vaccinations initially led to high Nab levels, with mild waning but subsequent rebound. Significant Nab enhancement occurred with a third-trimester booster. Maternal-neonatal Nab transfer was efficient (transfer ratio >1), and cross-reactivity to VOCs was observed.

CONCLUSION

Completing vaccination during any trimester delays COVID-19 infection and maintains effective neutralizing activity throughout pregnancy, with robust cross-reactivity to VOCs and efficient maternal-neonatal transfer.

Evaluation of the maternal systemic immune system during frozen euploid embryo transfer according to cycle outcome

Infertility affects 15 % of couples in the US, and many turn to assisted reproductive technologies, including in vitro fertilization and subsequent frozen embryo transfer (FET) to become pregnant. This study aimed to perform a broad assessment of the maternal immune system to determine if there are systemic differences on the day of FET in cycles that result in a live birth compared to those that do not. Women undergoing FET of euploid embryos were recruited and blood was collected on the day of FET as well as at early timepoints in pregnancy. Sixty immune and angiogenic proteins were measured in plasma, and gene expression of 92 immune-response related genes were evaluated in peripheral blood mononuclear cells (PBMCs). We found plasma concentrations of interleukin-13 (IL-13) and macrophage derived chemokine (MDC) were significantly lower on the day of FET in cycles that resulted in a live birth. We also found genes encoding C-C chemokine receptor type 5 (CCR5), CD8 subunit alpha (CD8A) and SMAD family member 3 (SMAD3) were upregulated in PBMCs on the day of FET in cycles that resulted in live birth. Measurements of immune mediators from maternal blood could serve as prognostic markers during FET to guide clinical decision making and further our understanding of implantation failure.

Chemokine and cytokine profiles in preterm and term labor, in preterm prelabor rupture of the membranes, and in normal pregnancy

The objective of this study was to investigate the immune mechanisms involved in preterm labor (PTL), preterm prelabor rupture of the membranes (PPROM), and normal pregnancies. The second objective was to explore immune profiles in PTL for association with early ( < 34 gestational weeks (gw)) or instant ( < 48 h) delivery. This prospective observational multi-center study included women with singleton pregnancies with PTL (n = 80) or PPROM (n = 40) before 34 gw, women with normal pregnancies scheduled for antenatal visits (n = 44), and women with normal pregnancies in active labor at term (n = 40). Plasma samples obtained at admission were analyzed for cytokine and chemokine quantification using a multiplex bead assay in order to compare the immune profiles between PTL, PPROM, and normal pregnancies. In PTL, CXCL1 and CCL17 were significantly higher compared to gestational age-matched women at antenatal visits, whereas for PPROM, CXCL1 and IL-6 were increased. Women in term labor had a more pronounced inflammatory pattern with higher levels of CXCL1, CXCL8, and IL-6 compared with PTL (p = 0.007, 0.003, and 0.013, respectively), as well as higher levels of CCL17, CXCL1 and IL-6 (all p < 0.001) compared with the women at antenatal visits. In PTL, CXCL8 was higher in women with delivery before 34 gw, whereas CXCL8, GM-CSF, and IL-6 were significantly higher in women with delivery within 48 h. To conclude, PTL and PPROM were associated with a complex pattern of inflammation, both involving Th17 (CXCL1) responses. Although further studies are needed, CXCL8, GM-CSF, and IL-6 may be potential candidates for predicting preterm birth in PTL.

Early prediction of spontaneous preterm birth before 34 gestational weeks based on a combination of inflammation-associated plasma proteins

Background

In order to identify and possibly offer prophylactic treatment to women at risk for preterm birth (PTB), novel prediction models for PTB are needed. Our objective was to utilize high-sensitive plasma protein profiling to investigate whether early prediction of spontaneous PTB (sPTB) before 34 gestational weeks (gw) was possible in a low-risk population.

Methods

A case-control study was conducted on 46 women with sPTB before 34 gw and 46 women with normal pregnancies and term deliveries. Prospectively collected plasma sampled at gw 11 (range 7-16) and gw 25 (range 23-30) was analyzed with a high-sensitivity Proximity Extension Assay for levels of 177 inflammation-associated proteins, and statistically processed with multivariate logistic regression analysis.

Results

In the first trimester, higher levels of hepatocyte growth factor (HGF) were associated with sPTB <34 gw (OR 1.49 (1.03-2.15)). In the second trimester, higher levels of interleukin (IL)-10 (OR 2.15 (1.18-3.92)), IL-6 (OR 2.59 (1.34-4.99)), and the receptor activator of nuclear factor κB (RANK) (OR 2.18 (1.26-3.77)) were associated with sPTB <34 gw. The area under the curve for the prediction models including these proteins was 0.653 (0.534-0.759) in the first trimester and 0.854 (0.754-0.925) in the second trimester.

Conclusion

A combination of inflammation-associated plasma proteins from the second trimester of pregnancy showed a good predictive ability regarding sPTB before 34 gw, suggesting it could be a valuable supplement for the assessment of the clinical risk of sPTB. However, although a high number (n=177) of plasma proteins were analyzed with a high-sensitivity method, the prediction of sPTB in the first trimester remains elusive.

Impact of previous pregnancy and BMI on cellular and serum immune activity from early to late pregnancy

Immunological adaptions during pregnancy play a crucial role in healthy fetal development. Aberrant immune modifications however contribute to adverse pregnancy outcomes, which may be driven by maternal factors such as previous pregnancies and BMI. This secondary analysis of the MicrobeMom2 RCT investigates the changes to maternal inflammatory biomarkers derived from serum and stimulated peripheral blood mononuclear cells (PBMCs) during pregnancy, and the effects of previous pregnancies (parity) and BMI on maternal immune responses. Changes in immune and metabolic biomarkers from early (11-15 weeks' gestation) to late (28-32 weeks' gestation) pregnancy were compared using paired t-tests. Participants were then split by parity (nulliparous, parous) and BMI (BMI < 25, BMI > = 25), and the relationship between parity and BMI with immune biomarker levels was examined using independent t-tests, paired t-tests, ANCOVA, and linear regression. Equivalent non-parametric tests were used for skewed data. Recruited women (n = 72) were on average 31.17 (SD ± 4.53) years of age and 25.11 (SD ± 3.82) BMI (kg/m2). Of these, 51 (70.8%) had a previous term pregnancy. Throughout gestation, PBMC cytokines displayed contrasting trends to serum, with a dampening of immune responses noted in PBMCs, and enhanced production of cytokines observed in the serum. Significant decreases in PBMC derived TNF-α, IL-10 and IFN-γ were seen from early to late pregnancy. Serum C3, IL-17A, IL-6, TNF-α, CD163, GDF-15 and leptin increased throughout gestation. First pregnancy was associated with higher levels of leptin in late pregnancy, while parous women showed significant decreases in PBMC derived TNF-α, IL10, and IFN-γ with gestation. Differences in levels of C3, IL-17A, TNF-α, GDF-15 and leptin were observed across BMI groups. Overall, serum-derived cytokines exhibit contrasting levels to those derived from stimulated PBMCs. Maternal immune responses undergo significant changes from early to late pregnancy, which are influenced by parity and BMI. These differences aid our understanding as to why first-time mothers are at greater risk of placental disease such as pre-eclampsia and fetal growth restriction.

Prenatal maternal Inflammation, childhood cognition and adolescent depressive symptoms

BACKGROUND

Accumulating evidence indicates that higher prenatal maternal inflammation is associated with increased depression risk in adolescent and adult-aged offspring. Prenatal maternal inflammation (PNMI) may increase the likelihood for offspring to have lower cognitive performance, which, in turn, may heighten risk for depression onset. Therefore, this study explored the potential mediating role of childhood cognitive performance in the relationship between PNMI and adolescent depressive symptoms in offspring.

METHODS

Participants included 696 mother-offspring dyads from the Child Health and Development Studies (CHDS) cohort. Biomarkers of maternal inflammation [interleukin (IL)-6, IL-8, IL-1 receptor antagonist (IL-1RA) and soluble TNF receptor-II (sTNF-RII)] were assayed from first (T1) and second trimester (T2) sera. Childhood (ages 9-11) cognitive performance was assessed via standardized Peabody Picture Vocabulary Test (PPVT), a measure of receptive vocabulary correlated with general intelligence. Adolescent (ages 15-17) depressive symptoms were assessed via self-report.

RESULTS

There were no significant associations between T1 biomarkers and childhood PPVT or adolescent depressive symptoms. Higher T2 IL1-RA was directly associated with lower childhood PPVT (b = -0.21, SE = 0.08, t = -2.55, p = 0.01), but not with adolescent depressive symptoms. T2 IL-6 was not directly associated with childhood PPVT, but higher T2 IL-6 was directly associated at borderline significance with greater depressive symptoms in adolescence (b = 0.05, SE = 0.03, t = 1.96, p = 0.05). Lower childhood PPVT predicted significantly higher adolescent depressive symptoms (b = -0.07, SE = 0.02, t = -2.99, p < 0.01). There was a significant indirect effect of T2 IL-1RA on adolescent depressive symptoms via childhood PPVT (b = 0.03, 95 % CI = 0.002-0.03) indicating a partially mediated effect. No significant associations were found with T2 sTNF-RII nor IL-8.

CONCLUSIONS

Lower childhood cognitive performance, such as that indicated by a lower PPVT score, represents a potential mechanism through which prenatal maternal inflammation contributes to adolescent depression risk in offspring.

Protective role of macrophages from maternal-fetal interface in unvaccinated coronavirus disease 2019 pregnant women

Pregnant women represent a high-risk population for Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection. The presence of SARS-CoV-2 has been reported in placenta from infected pregnant women, but whether the virus influences placenta immune response remains unclear. We investigated the properties of maternal-fetal interface macrophages (MFMs) in a cohort of unvaccinated women who contracted coronavirus disease 2019 (COVID-19) during their pregnancy. We reported an infiltration of CD163+ macrophages in placenta from COVID-19 women 19 whereas lymphoid compartment was not affected. Isolated MFMs exhibited nonpolarized activated signature (NOS2, IDO1, IFNG, TNF, TGFB) mainly in women infected during the second trimester of pregnancy. COVID-19 during pregnancy primed MFM to produce type I and III interferon response to SARS-CoV-2 (Wuhan and δ strains), that were unable to elicit this in MFMs from healthy pregnant women. COVID-19 also primed SARS-CoV-2 internalization by MFM in an angiotensin-converting enzyme 2-dependent manner. Activation and recall responses of MFMs were influenced by fetal sex. Collectively, these findings support a role for MFMs in the local immune response to SARS-CoV-2 infection, provide a basis for protective placental immunity in COVID-19, and highlight the interest of vaccination in pregnant women.

Stress and Its Consequences-Biological Strain

Understanding the role of stress in pregnancy and its consequences is important, particularly given documented associations between maternal stress and preterm birth and other pathological outcomes. Physical and psychological stressors can elicit the same biological responses, known as biological strain. Chronic stressors, like poverty and racism (race-based discriminatory treatment), may create a legacy or trajectory of biological strain that no amount of coping can relieve in the absence of larger-scale socio-behavioral or societal changes. An integrative approach that takes into consideration simultaneously social and biological determinants of stress may provide the best insights into the risk of preterm birth. The most successful computational approaches and the most predictive machine-learning models are likely to be those that combine information about the stressors and the biological strain (for example, as measured by different omics) experienced during pregnancy.

Adapting the SMART tube technology for flow cytometry in feline full blood samples

Flow cytometry of blood samples is a very valuable clinical and research tool to monitor the immune response in human patients. Furthermore, it has been successfully applied in cats, such as for infections with feline immune deficiency virus (FIV). However, if cells are not isolated and frozen, analysis of anticoagulated blood samples requires mostly prompt processing following blood collection, making later analysis of stored full blood samples obtained in clinical studies often impossible. The SMART Tube system (SMART TUBE Inc., California, United States; SMT) allows fixation and long-term preservation of whole blood samples at -80°C. However, this system has so far only been applied to human biological samples. In the present study, a new flow cytometry SMART Tube protocol adapted for feline whole blood samples was successfully established allowing quantification of T-helper cells, cytotoxic T-cells, B-cells, monocytes, and neutrophils up to 2 years post sampling. Results obtained from frozen stabilized and fresh blood samples were compared for validation purposes and correlated to differential blood counts from a conventional hematology analyzer. Clinical applicability of the new technique was verified by using samples from a treatment study for feline infectious peritonitis (FIP). Using the new SMT protocol on retained samples, it could be demonstrated that long-term storage of these SMT tubes is also possible. In summary, the newly adapted SMT protocol proved suitable for performing flow cytometry analysis on stored feline whole blood samples, thus opening up new avenues for veterinary research on a variety of aspects of clinical interest.

The vaginal immunoproteome for the prediction of spontaneous preterm birth: A retrospective longitudinal study

Background

Preterm birth is the leading cause of neonatal morbidity and mortality worldwide. Most cases of preterm birth occur spontaneously and result from preterm labor with intact (spontaneous preterm labor [sPTL]) or ruptured (preterm prelabor rupture of membranes [PPROM]) membranes. The prediction of spontaneous preterm birth (sPTB) remains underpowered due to its syndromic nature and the dearth of independent analyses of the vaginal host immune response. Thus, we conducted the largest longitudinal investigation targeting vaginal immune mediators, referred to herein as the immunoproteome, in a population at high risk for sPTB.

Methods

Vaginal swabs were collected across gestation from pregnant women who ultimately underwent term birth, sPTL, or PPROM. Cytokines, chemokines, growth factors, and antimicrobial peptides in the samples were quantified via specific and sensitive immunoassays. Predictive models were constructed from immune mediator concentrations.

Results

Throughout uncomplicated gestation, the vaginal immunoproteome harbors a cytokine network with a homeostatic profile. Yet, the vaginal immunoproteome is skewed toward a pro-inflammatory state in pregnant women who ultimately experience sPTL and PPROM. Such an inflammatory profile includes increased monocyte chemoattractants, cytokines indicative of macrophage and T-cell activation, and reduced antimicrobial proteins/peptides. The vaginal immunoproteome has improved predictive value over maternal characteristics alone for identifying women at risk for early (<34 weeks) sPTB.

Conclusions

The vaginal immunoproteome undergoes homeostatic changes throughout gestation and deviations from this shift are associated with sPTB. Furthermore, the vaginal immunoproteome can be leveraged as a potential biomarker for early sPTB, a subset of sPTB associated with extremely adverse neonatal outcomes.

Funding

This research was conducted by the Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services (NICHD/NIH/DHHS) under contract HHSN275201300006C. ALT, KRT, and NGL were supported by the Wayne State University Perinatal Initiative in Maternal, Perinatal and Child Health.

Inflammatory markers in pregnancy - surprisingly stable. Mapping trajectories and drivers in four large cohorts

Adaptations of the immune system throughout gestation have been proposed as important mechanisms regulating successful pregnancy. Dysregulation of the maternal immune system has been associated with adverse maternal and fetal outcomes. To translate findings from mechanistic preclinical studies to human pregnancies, studies of serum immune markers are the mainstay. The design and interpretation of human biomarker studies require additional insights in the trajectories and drivers of peripheral immune markers. The current study mapped maternal inflammatory markers (C-reactive protein (CRP), interleukin (IL)-1β, IL-6, IL-17A, IL-23, interferon- γ ) during pregnancy and investigated the impact of demographic, environmental and genetic drivers on maternal inflammatory marker levels in four multi-ethnic and socio-economically diverse population-based cohorts with more than 12,000 pregnant participants. Additionally, pregnancy inflammatory markers were compared to pre-pregnancy levels. Cytokines showed a high correlation with each other, but not with CRP. Inflammatory marker levels showed high variability between individuals, yet high concordance within an individual over time during and pre-pregnancy. Pre-pregnancy body mass index (BMI) explained more than 9.6% of the variance in CRP, but less than 1% of the variance in cytokines. The polygenic score of CRP was the best predictor of variance in CRP (>14.1%). Gestational age and previously identified inflammation drivers, including tobacco use and parity, explained less than 1% of variance in both cytokines and CRP. Our findings corroborate differential underlying regulatory mechanisms of CRP and cytokines and are suggestive of an individual inflammatory marker baseline which is, in part, genetically driven. While prior research has mainly focused on immune marker changes throughout pregnancy, our study suggests that this field could benefit from a focus on intra-individual factors, including metabolic and genetic components.

Characteristics of COVID-19 comorbidities and severity profiles among pregnant women from a single-center cross-sectional study

The study aimed to determine the characteristics of comorbidities, association between comorbidities and coronavirus disease 2019 (COVID-19), as well as characteristics of COVID-19 severity among pregnant women at a tertiary hospital in Bandung. We conducted a cross-sectional study by taking secondary data between January 2020 and December 2021 involving 278 pregnant women aged 16 to 45 years that confirmedly diagnosed with COVID-19 via RT-PCR. We collected information from the medical record on severity and comorbidities. The admission C-reactive protein (CRP) profiles were compared between the severe and nonsevere COVID-19 patients. This study employed bivariate analysis, t test, and multivariate analysis with logistic regression models. Of the 278 data included in this study, 120 cases had comorbidities. Most patients were asymptomatic (82%). Obesity was the most common comorbid proportion. Only hypertension as comorbid showed a significant association with symptomatic or asymptomatic COVID-19 (<0.05). Pregnant women with hypertension were 6 times more likely to show symptoms than those without hypertension (OR = 6.092; 95% CI 3.103-11.962). Pregnant women with comorbidities were at higher risk of cesarean sections and stillbirth. The CRP levels which were found to have statistically significant association with COVID-19 severity (<0.05). The domination of asymptomatic COVID-19 in pregnant women was found in this study. Hypertension comorbid has a significant association with COVID-19 symptoms. Maternal and neonatal outcomes appear to be influenced by maternal comorbidities. Moreover, the CRP levels were found to be significant risk factors for COVID-19 severity in pregnant women that might have association with comorbidities.

Converging cytokine and metabolite networks shape asymmetric T cell fate at the term human maternal-fetal interface

Placentation presents immune conflict between mother and fetus, yet in normal pregnancy maternal immunity against infection is maintained without expense to fetal tolerance. This is believed to result from adaptations at the maternal-fetal interface (MFI) which affect T cell programming, but the identities (i.e., memory subsets and antigenic specificities) of T cells and the signals that mediate T cell fates and functions at the MFI remain poorly understood. We found intact recruitment programs as well as pro-inflammatory cytokine networks that can act on maternal T cells in an antigen-independent manner. These inflammatory signals elicit T cell expression of co-stimulatory receptors necessary for tissue retention, which can be engaged by local macrophages. Although pro-inflammatory molecules elicit T cell effector functions, we show that additional cytokine (TGF-β1) and metabolite (kynurenine) networks may converge to tune T cell function to those of sentinels. Together, we demonstrate an additional facet of fetal tolerance, wherein T cells are broadly recruited and restrained in an antigen-independent, cytokine/metabolite-dependent manner. These mechanisms provide insight into antigen-nonspecific T cell regulation, especially in tissue microenvironments where they are enriched.

Solving the Puzzle of Preterm Birth

Solving the puzzle of preterm birth has been challenging and will require novel integrative solutions as preterm birth likely arises from many etiologies. It has been demonstrated that many sociodemographic and psychological determinants of preterm birth relate to its complex biology. It is this understanding that has enabled the development of a novel preventative strategy, which integrates the omics profile (genome, epigenome, transcriptome, proteome, metabolome, microbiome) with sociodemographic, environmental, and psychological determinants of individual pregnant people to solve the puzzle of preterm birth.

Predicting Spontaneous Preterm Birth Using the Immunome

Throughout pregnancy, the maternal peripheral circulation contains valuable information reflecting pregnancy progression, detectable as tightly regulated immune dynamics. Local immune processes at the maternal-fetal interface and other reproductive and non-reproductive tissues are likely to be the pacemakers for this peripheral immune "clock." This cellular immune status of pregnancy can be leveraged for the early risk assessment and prediction of spontaneous preterm birth (sPTB). Systems immunology approaches to sPTB subtypes and cross-tissue (local and peripheral) interactions, as well as integration of multiple biological data modalities promise to improve our understanding of preterm birth pathobiology and identify potential clinically actionable biomarkers.

Computational Approaches for Connecting Maternal Stress to Preterm Birth

Multiple studies have hinted at a complex connection between maternal stress and preterm birth (PTB). This article describes the potential of computational methods to provide new insights into this relationship. For this, we outline existing approaches for stress assessments and various data modalities available for profiling stress responses, and review studies that sought either to establish a connection between stress and PTB or to predict PTB based on stress-related factors. Finally, we summarize the challenges of computational methods, highlighting potential future research directions within this field.

Computational Approaches for Predicting Preterm Birth and Newborn Outcomes

Preterm birth (PTB) and its associated morbidities are a leading cause of infant mortality and morbidity. Accurate predictive models and a better biological understanding of PTB-associated morbidities are critical in reducing their adverse effects. Increasing availability of multimodal high-dimensional data sets with concurrent advances in artificial intelligence (AI) have created a rich opportunity to gain novel insights into PTB, a clinically complex and multifactorial disease. Here, the authors review the use of AI to analyze 3 modes of data: electronic health records, biological omics, and social determinants of health metrics.

Predicting Preterm Birth Using Proteomics

The complexity of preterm birth (PTB), both spontaneous and medically indicated, and its various etiologies and associated risk factors pose a significant challenge for developing tools to accurately predict risk. This review focuses on the discovery of proteomics signatures that might be useful for predicting spontaneous PTB or preeclampsia, which often results in PTB. We describe methods for proteomics analyses, proteomics biomarker candidates that have so far been identified, obstacles for discovering biomarkers that are sufficiently accurate for clinical use, and the derivation of composite signatures including clinical parameters to increase predictive power.

A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development

BACKGROUND

Most previous research on the environmental epidemiology of childhood atopic eczema, rhinitis and wheeze is limited in the scope of risk factors studied. Our study adopted a machine learning approach to explore the role of the exposome starting already in the preconception phase.

METHODS

We performed a combined analysis of two multi-ethnic Asian birth cohorts, the Growing Up in Singapore Towards healthy Outcomes (GUSTO) and the Singapore PREconception Study of long Term maternal and child Outcomes (S-PRESTO) cohorts. Interviewer-administered questionnaires were used to collect information on demography, lifestyle and childhood atopic eczema, rhinitis and wheeze development. Data training was performed using XGBoost, genetic algorithm and logistic regression models, and the top variables with the highest importance were identified. Additive explanation values were identified and inputted into a final multiple logistic regression model. Generalised structural equation modelling with maternal and child blood micronutrients, metabolites and cytokines was performed to explain possible mechanisms.

RESULTS

The final study population included 1151 mother-child pairs. Our findings suggest that these childhood diseases are likely programmed in utero by the preconception and pregnancy exposomes through inflammatory pathways. We identified preconception alcohol consumption and maternal depressive symptoms during pregnancy as key modifiable maternal environmental exposures that increased eczema and rhinitis risk. Our mechanistic model suggested that higher maternal blood neopterin and child blood dimethylglycine protected against early childhood wheeze. After birth, early infection was a key driver of atopic eczema and rhinitis development.

CONCLUSION

Preconception and antenatal exposomes can programme atopic eczema, rhinitis and wheeze development in utero. Reducing maternal alcohol consumption during preconception and supporting maternal mental health during pregnancy may prevent atopic eczema and rhinitis by promoting an optimal antenatal environment. Our findings suggest a need to include preconception environmental exposures in future research to counter the earliest precursors of disease development in children.

Maternal-driven immune education in offspring

Maternal environmental exposures, particularly during gestation and lactation, significantly influence the immunological development and long-term immunity of offspring. Mammalian immune systems develop through crucial inputs from the environment, beginning in utero and continuing after birth. These critical developmental windows are essential for proper immune system development and, once closed, may not be reopened. This review focuses on the mechanisms by which maternal exposures, particularly to pathogens, diet, and microbiota, impact offspring immunity. Mechanisms driving maternal-offspring immune crosstalk include transfer of maternal antibodies, changes in the maternal microbiome and microbiota-derived metabolites, and transfer of immune cells and cytokines via the placenta and breastfeeding. We further discuss the role of transient maternal infections, which are common during pregnancy, in providing tissue-specific immune education to offspring. We propose a "maternal-driven immune education" hypothesis, which suggests that offspring can use maternal encounters that occur during a critical developmental window to develop optimal immune fitness against infection and inflammation.

Increased miR-3074-5p expression promotes M1 polarization and pyroptosis of macrophages via ERα/NLRP3 pathway and induces adverse pregnancy outcomes in mice

Decidual macrophages (dMϕs) play critical roles in regulation of immune-microhomeostasis at maternal-fetal interface during pregnancy, but the underlying molecular mechanisms are still unclear. In this study, it was found that litter size and fetal weight were significantly reduced, whereas the rate of embryo resorption was increased in miR-3074-5p knock-in (3074-KI) pregnant mice, compared to that of wild-type (WT) pregnant mice. Plasma levels of pro-inflammatory cytokines in 3074-KI pregnant mice were also significantly elevated compared to WT pregnant mice at GD7.5. The quantity of M1-Mϕs in uterine tissues of 3074-KI pregnant mice was significantly increased compared to WT pregnant mice at GD13.5. Estrogen receptor-α (ERα) was validated to be a target of miR-3074-5p. Either miR-3074-5p overexpression or ERα knockdown promoted transcriptional activity of NF-κB/p65, induced M1-polarization and pyroptosis of THP1-derived Mϕs, accompanied with increased intracellular levels of cleaved Caspase-1, cleaved IL-1β, NLRP3, cleaved GSDMD and ASC aggregation. Furthermore, ERα could not only bind to NLRP3 or ASC directly, but also inhibit the interaction between NLRP3 and ASC. The endometrial miR-3074-5p expression level at the middle secretory stage of repeated implantation failure (RIF) patients was significantly decreased compared to that of control fertile women. These data indicated that miR-3074-5p could promote M1 polarization and pyroptosis of Mϕs via activation of NLRP3 inflammasome by targeting ERα, and the dysregulation of miR-3074-5p expression in dMϕs might damage the embryo implantation and placentation by interfering with inflammatory microenvironment at the maternal-fetal interface during early pregnancy.

Proteomic studies of VEGFR2 in human placentas reveal protein associations with preeclampsia, diabetes, gravidity, and labor

VEGFR2 (Vascular endothelial growth factor receptor 2) is a central regulator of placental angiogenesis. The study of the VEGFR2 proteome of chorionic villi at term revealed its partners MDMX (Double minute 4 protein) and PICALM (Phosphatidylinositol-binding clathrin assembly protein). Subsequently, the oxytocin receptor (OT-R) and vasopressin V1aR receptor were detected in MDMX and PICALM immunoprecipitations. Immunogold electron microscopy showed VEGFR2 on endothelial cell (EC) nuclei, mitochondria, and Hofbauer cells (HC), tissue-resident macrophages of the placenta. MDMX, PICALM, and V1aR were located on EC plasma membranes, nuclei, and HC nuclei. Unexpectedly, PICALM and OT-R were detected on EC projections into the fetal lumen and OT-R on 20-150 nm clusters therein, prompting the hypothesis that placental exosomes transport OT-R to the fetus and across the blood-brain barrier. Insights on gestational complications were gained by univariable and multivariable regression analyses associating preeclampsia with lower MDMX protein levels in membrane extracts of chorionic villi, and lower MDMX, PICALM, OT-R, and V1aR with spontaneous vaginal deliveries compared to cesarean deliveries before the onset of labor. We found select associations between higher MDMX, PICALM, OT-R protein levels and either gravidity, diabetes, BMI, maternal age, or neonatal weight, and correlations only between PICALM-OT-R (p < 2.7 × 10-8), PICALM-V1aR (p < 0.006), and OT-R-V1aR (p < 0.001). These results offer for exploration new partnerships in metabolic networks, tissue-resident immunity, and labor, notably for HC that predominantly express MDMX.

Longitudinal Cervical Length Measurements and Spontaneous Preterm Birth in Singleton and Twin Pregnancies

Importance

Changes in cervical length in twin pregnancies exhibit various patterns, but it is unclear whether the mechanism underlying spontaneous preterm birth (sPTB) is consistent. The existence of detailed phenomena in singleton pregnancies is also unclear.

Objectives

To explore the different patterns in cervical length trajectories in singleton and twin pregnancies and to analyze whether the immunological mechanisms of sPTB are consistent among these cervical length patterns.

Design, Setting, and Participants

This cohort study recruited pregnant individuals who received antenatal care and delivered at Peking University Third Hospital in Beijing, China, between January 1, 2014, and December 31, 2022. Individuals with singleton and twin pregnancies were included.

Exposures

Cervical length measurements and white blood cell (WBC) indicators.

Main Outcomes and Measures

The primary outcome was sPTB. Longitudinal trajectory cluster analysis was used to identify patterns of changes in cervical length in singleton and twin pregnancies. A random-effects model with cubic spline was used to fit and compare the longitudinal trajectory of WBC indicators among early preterm birth, moderate to late preterm birth, and term birth.

Results

A total of 43 559 pregnant individuals were included; of these, 41 706 had singleton pregnancies (mean [SD)] maternal age, 33.0 [4.0] years) and 1853 had twin pregnancies (mean [SD] maternal age, 33.3 [3.6] years). Two distinct patterns of cervical length changes were observed in both singleton and twin pregnancies: shortened (21 366 singletons and 546 twins) and stable (20 340 singletons and 1307 twins). In singleton pregnancies, WBC count was associated with early sPTB in individuals with both shortened cervix (odds ratio [OR], 1.35; 95% CI, 1.00-1.82) and stable cervix (OR, 1.64; 95% CI, 1.07-2.50). However, for twin pregnancies, the association of WBC count (OR, 3.13; 95% CI, 1.58-6.18) with the risk of early sPTB was observed only in individuals with a shortened cervix.

Conclusions and Relevance

This study identified 2 distinct cervical length patterns: shortened and stable. These patterns revealed 2 preterm birth mechanisms in twin pregnancies, with the immunopathogenesis of sPTB found only in the shortened cervix pattern; in singleton pregnancies, maternal immune response was associated with a higher risk of sPTB regardless of a shortened or stable cervix.

Predictive models of recurrent implantation failure in patients receiving ART treatment based on clinical features and routine laboratory data

STUDY QUESTION

The objective was to construct a model for predicting the probability of recurrent implantation failure (RIF) after assisted reproductive technology (ART) treatment based on the clinical characteristics and routine laboratory test data of infertile patients. A model was developed to predict RIF. The model showed high calibration in external validation, helped to identify risk factors for RIF, and improved the efficacy of ART therapy.

WHAT IS KNOWN ALREADY

Research on the influencing factors of RIF has focused mainly on embryonic factors, endometrial receptivity, and immune factors. However, there are many kinds of examinations regarding these aspects, and comprehensive screening is difficult because of the limited time and economic conditions. Therefore, we should try our best to analyse the results of routine infertility screenings to make general predictions regarding the occurrence of RIF.

STUDY DESIGN, SIZE, DURATION

A retrospective study was conducted with 5212 patients at the Reproductive Center of the First Affiliated Hospital of USTC from January 2018 to June 2022.

PARTICIPANTS/MATERIALS, SETTING, METHODS

This study included 462 patients in the RIF group and 4750 patients in the control group. The patients' basic characteristics, clinical treatment data, and laboratory test indices were compared. Logistic regression was used to analyse RIF-related risk factors, and the prediction model was evaluated by receiver operating characteristic (ROC) curves and the corresponding areas under the curve (AUCs). Further analysis of the influencing factors of live births in the first cycle of subsequent assisted reproduction treatment in RIF patients was performed, including the live birth subgroup (n = 116) and the no live birth subgroup (n = 200).

MAIN RESULTS AND THE ROLE OF CHANCE

(1) An increased duration of infertility (1.978; 95% CI, 1.264-3.097), uterine cavity abnormalities (2.267; 95% CI, 1.185-4.336), low AMH levels (0.504; 95% CI, 0.275-0.922), insulin resistance (3.548; 95% CI, 1.931-6.519), antinuclear antibody (ANA)-positive status (3.249; 95% CI, 1.20-8.797) and anti-β2-glycoprotein I antibody (A-β2-GPI Ab)-positive status (5.515; 95% CI, 1.481-20.536) were associated with an increased risk of RIF. The area under the curve of the logistic regression model was 0.900 (95% CI, 0.870-0.929) for the training cohort and 0.895 (95% CI, 0.865-0.925) for the testing cohort. (2) Advanced age (1.069; 95% CI, 1.015-1.126) was a risk factor associated with no live births after the first cycle of subsequent assisted reproduction treatment in patients with RIF. Blastocyst transfer (0.365; 95% CI = 0.181-0.736) increased the probability of live birth in subsequent cycles in patients with RIF. The area under the curve of the logistic regression model was 0.673 (95% CI, 0.597-0.748).

LIMITATIONS, REASONS FOR CAUTION

This was a single-centre regression study, for which the results need to be evaluated and verified by prospective large-scale randomized controlled studies. The small sample size for the analysis of factors influencing pregnancy outcomes in subsequent assisted reproduction cycles for RIF patients resulted in the inclusion of fewer covariates, and future studies with larger samples and the inclusion of more factors are needed for assessment and validation.

WIDER IMPLICATIONS OF THE FINDINGS

Prediction of embryo implantation prior to transfer will facilitate the clinical management of patients and disease prediction and further improve ART treatment outcomes.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the General Project of the National Natural Science Foundation of China (Nos. 82,201,792, 82,301,871, 81,971,446, and 82,374,212) and the Natural Science Foundation of Anhui Province (No. 2208085MH206). There are no conflicts of interest to declare.

TRIAL REGISTRATION NUMBER

This study was registered with the Chinese Clinical Trial Register (Clinical Trial Number: ChiCTR1800018298 ).

The effect of SARS-CoV-2 infection and vaccination on Th17 and regulatory T cells in a pregnancy cohort in NYC

Disturbances in T-cells, specifically the Th17/Treg balance, have been implicated in adverse pregnancy outcomes. We investigated these two T-cell populations following pre-pregnancy and pregnancy SARS-CoV-2 infection and COVID-19 vaccination in 351 participants from a pregnancy cohort in New York City (Generation C; 2020-2022). SARS-CoV-2 infection status was determined via laboratory or medical diagnosis and COVID-19 vaccination status via survey and electronic medical records data. Peripheral blood mononuclear cells (PBMCs) were collected at routine prenatal visits throughout gestation (median 108 days; IQR 67-191 days) with repeated measures for 104 participants (29.6%). T-cell populations CD4+/CD3+, Th17/CD4+, Treg/CD4+ and the Th17/Treg ratio were quantified using flow cytometry. Results showed that inter-individual differences are a main influencing factor in Th17 and Treg variance, however total variance explained remained small (R2 = 15-39%). Overall, Th17 and Treg populations were not significantly affected by SARS-CoV-2 infection during pregnancy in adjusted linear mixed models (p>0.05), however comparison of repeated measures among SARS-CoV-2 infected participants and non-infected controls suggests a relative increase of the Th17/Treg ratio following infection. In addition, the Th17/Treg ratio was significantly higher after SARS-CoV-2 infection prior to pregnancy (10-138 weeks) compared to controls (β=0.48, p=0.003). COVID-19 vaccination was not associated with Th17 and Treg cells. Our findings suggest an impact of SARS-CoV-2 infection on the Th17/Treg ratio, likely depending on severity of infection, yet the observed trends and their potential consequences for pregnancy outcomes require further investigation. Our study contributes to growing evidence that COVID-19 vaccination during pregnancy does not lead to an exacerbated immune response.

Analysis of Vaginal Microbiota Variations in the Third Trimester of Pregnancy and Their Correlation with Preterm Birth: A Case-Control Study

This study conducted a detailed analysis of the vaginal microbiota in pregnant women to explore its correlation with preterm birth (PTB) outcomes. The primary objective was to identify microbial variations associated with increased PTB risk. Secondary objectives included investigating how changes in microbial composition relate to the local immune environment and PTB. Utilizing a retrospective case-control design, the study involved pregnant women with liveborn infants between 2019 and 2023. In total, 89 women who delivered preterm and 106 term deliveries were included. Data collection focused on third-trimester vaginal cultures. Statistically significant differences were observed between the preterm and full-term groups in several areas. The median white blood cell count (10.2 × 103/mm3 vs. 7.6 × 103/mm3, p = 0.009) and neutrophil count (7.2 × 103/mm3 vs. 5.1 × 103/mm3, p < 0.001) were higher in the preterm group. Vaginal pH was also elevated in preterm births (5.6 vs. 4.4, p < 0.001), with a higher prevalence of bacterial vaginosis (29.2% vs. 12.3%, p = 0.001) as indicated by the Nugent Score. The study noted a significant association of PTB with the presence of Candida spp. (OR = 1.84, p = 0.018), Gardnerella vaginalis (OR = 2.29, p = 0.003), Mycoplasma hominis (OR = 1.97, p = 0.007), and Ureaplasma urealyticum (OR = 2.43, p = 0.001). Conversely, a reduction in Lactobacillus spp. correlated with a decreased PTB risk (OR = 0.46, p = 0.001). The study provides compelling evidence that specific vaginal microbiota components, particularly certain pathogenic bacteria and an altered Lactobacillus profile, are significantly associated with PTB risk. These findings highlight the potential of targeting microbial factors in strategies aimed at reducing PTB rates. Further research is necessary to fully understand the complex interplay between microbial dynamics, host immunity, and PTB outcomes.

Prenatal mood and anxiety disorders and associated cytokine changes

BACKGROUND

We examined whether women with prenatal mood and anxiety disorders would exhibit differential pro- and anti-inflammatory marker trajectories during the prenatal and postpartum periods compared to women without these disorders.

METHODS

Approximately 179 pregnant women participated in a longitudinal study conducted in two urban areas. Blood samples for inflammatory markers were collected at six study visits. The Structured Clinical Interview for the DSM-IV (SCID) was administered to participants scoring above cutoffs on anxiety and depression. Pregnant women with SCID Axis I diagnoses of mood and/or anxiety disorders were compared to other participants on inflammatory markers. Multilevel modeling tested associations between SCID diagnoses and within-person interleukin (IL)6 and IL10 trajectories.

RESULTS

Prenatal SCID diagnoses were associated with linear, quadratic and cubic change in IL6 from prenatal to postpartum timepoints. Women with a prenatal SCID diagnosis had steeper decreases and increases in IL6 during prenatal and postpartum periods. SCID diagnoses were associated with lower IL10 in mid-pregnancy to postpartum (b = -0.078, SE = 0.019; p = .015).

LIMITATIONS

Future studies would benefit from a larger sample size and a larger number of participants with SCID diagnoses. Future research should also examine whether different prenatal Axis 1 diagnoses are associated with different patterns of immune response in pregnancy.

CONCLUSIONS

Pregnant women with prenatal mood and anxiety disorders had greater fluctuations in IL6 across prenatal and postpartum periods and lower IL10 through pregnancy and postpartum. They may have different proinflammatory states that remain after birth without a reciprocal anti-inflammatory response.

Multimodal machine learning for modeling infant head circumference, mothers' milk composition, and their shared environment

Links between human milk (HM) and infant development are poorly understood and often focus on individual HM components. Here we apply multi-modal predictive machine learning to study HM and head circumference (a proxy for brain development) among 1022 mother-infant dyads of the CHILD Cohort. We integrated HM data (19 oligosaccharides, 28 fatty acids, 3 hormones, 28 chemokines) with maternal and infant demographic, health, dietary and home environment data. Head circumference was significantly predictable at 3 and 12 months. Two of the most associated features were HM n3-polyunsaturated fatty acid C22:6n3 (docosahexaenoic acid, DHA; p = 9.6e-05) and maternal intake of fish (p = 4.1e-03), a key dietary source of DHA with established relationships to brain function. Thus, using a systems biology approach, we identified meaningful relationships between HM and brain development, which validates our statistical approach, gives credence to the novel associations we observed, and sets the foundation for further research with additional cohorts and HM analytes.

Design of a targeted blood transcriptional panel for monitoring immunological changes accompanying pregnancy

Background

Immunomodulatory processes exert steering functions throughout pregnancy. Detecting diversions from this physiologic immune clock may help identify pregnant women at risk for pregnancy-associated complications. We present results from a data-driven selection process to develop a targeted panel of mRNAs that may prove effective in detecting pregnancies diverting from the norm.

Methods

Based on a de novo dataset from a resource-constrained setting and a dataset from a resource-rich area readily available in the public domain, whole blood gene expression profiles of uneventful pregnancies were captured at multiple time points during pregnancy. BloodGen3, a fixed blood transcriptional module repertoire, was employed to analyze and visualize gene expression patterns in the two datasets. Differentially expressed genes were identified by comparing their abundance to non-pregnant postpartum controls. The selection process for a targeted gene panel considered (i) transcript abundance in whole blood; (ii) degree of correlation with the BloodGen3 module; and (iii) pregnancy biology.

Results

We identified 176 transcripts that were complemented with eight housekeeping genes. Changes in transcript abundance were seen in the early stages of pregnancy and similar patterns were observed in both datasets. Functional gene annotation suggested significant changes in the lymphoid, prostaglandin and inflammation-associated compartments, when compared to the postpartum controls.

Conclusion

The gene panel presented here holds promise for the development of predictive, targeted, transcriptional profiling assays. Such assays might become useful for monitoring of pregnant women, specifically to detect potential adverse events early. Prospective validation of this targeted assay, in-depth investigation of functional annotations of differentially expressed genes, and assessment of common pregnancy-associated complications with the aim to identify these early in pregnancy to improve pregnancy outcomes are the next steps.

Cellograph: a semi-supervised approach to analyzing multi-condition single-cell RNA-sequencing data using graph neural networks

With the growing number of single-cell datasets collected under more complex experimental conditions, there is an opportunity to leverage single-cell variability to reveal deeper insights into how cells respond to perturbations. Many existing approaches rely on discretizing the data into clusters for differential gene expression (DGE), effectively ironing out any information unveiled by the single-cell variability across cell-types. In addition, DGE often assumes a statistical distribution that, if erroneous, can lead to false positive differentially expressed genes. Here, we present Cellograph: a semi-supervised framework that uses graph neural networks to quantify the effects of perturbations at single-cell granularity. Cellograph not only measures how prototypical cells are of each condition but also learns a latent space that is amenable to interpretable data visualization and clustering. The learned gene weight matrix from training reveals pertinent genes driving the differences between conditions. We demonstrate the utility of our approach on publicly-available datasets including cancer drug therapy, stem cell reprogramming, and organoid differentiation. Cellograph outperforms existing methods for quantifying the effects of experimental perturbations and offers a novel framework to analyze single-cell data using deep learning.

Deciphering maternal-fetal cross-talk in the human placenta during parturition using single-cell RNA sequencing

Labor is a complex physiological process requiring a well-orchestrated dialogue between the mother and fetus. However, the cellular contributions and communications that facilitate maternal-fetal cross-talk in labor have not been fully elucidated. Here, single-cell RNA sequencing (scRNA-seq) was applied to decipher maternal-fetal signaling in the human placenta during term labor. First, a single-cell atlas of the human placenta was established, demonstrating that maternal and fetal cell types underwent changes in transcriptomic activity during labor. Cell types most affected by labor were fetal stromal and maternal decidual cells in the chorioamniotic membranes (CAMs) and maternal and fetal myeloid cells in the placenta. Cell-cell interaction analyses showed that CAM and placental cell types participated in labor-driven maternal and fetal signaling, including the collagen, C-X-C motif ligand (CXCL), tumor necrosis factor (TNF), galectin, and interleukin-6 (IL-6) pathways. Integration of scRNA-seq data with publicly available bulk transcriptomic data showed that placenta-derived scRNA-seq signatures could be monitored in the maternal circulation throughout gestation and in labor. Moreover, comparative analysis revealed that placenta-derived signatures in term labor were mirrored by those in spontaneous preterm labor and birth. Furthermore, we demonstrated that early in gestation, labor-specific, placenta-derived signatures could be detected in the circulation of women destined to undergo spontaneous preterm birth, with either intact or prelabor ruptured membranes. Collectively, our findings provide insight into the maternal-fetal cross-talk of human parturition and suggest that placenta-derived single-cell signatures can aid in the development of noninvasive biomarkers for the prediction of preterm birth.

Characterizing immune variation and diagnostic indicators of preeclampsia by single-cell RNA sequencing and machine learning

Preeclampsia is a multifactorial and heterogeneous complication of pregnancy. Here, we utilize single-cell RNA sequencing to dissect the involvement of circulating immune cells in preeclampsia. Our findings reveal downregulation of immune response in lymphocyte subsets in preeclampsia, such as reduction in natural killer cells and cytotoxic genes expression, and expansion of regulatory T cells. But the activation of naïve T cell and monocyte subsets, as well as increased MHC-II-mediated pathway in antigen-presenting cells were still observed in preeclampsia. Notably, we identified key monocyte subsets in preeclampsia, with significantly increased expression of angiogenesis pathways and pro-inflammatory S100 family genes in VCAN+ monocytes and IFN+ non-classical monocytes. Furthermore, four cell-type-specific machine-learning models have been developed to identify potential diagnostic indicators of preeclampsia. Collectively, our study demonstrates transcriptomic alternations of circulating immune cells and identifies immune components that could be involved in pathophysiology of preeclampsia.

Trophoblast-derived miR-410-5p induces M2 macrophage polarization and mediates immunotolerance at the fetal-maternal interface by targeting the STAT1 signaling pathway

BACKGROUND

Macrophages phenotypic deviation and immune imbalance play vital roles in pregnancy-associated diseases such as spontaneous miscarriage. Trophoblasts regulate phenotypic changes in macrophages, however, their underlying mechanism during pregnancy remains unclear. Therefore, this study aimed to elucidate the potential function of trophoblast-derived miRNAs (miR-410-5p) in macrophage polarization during pregnancy.

METHODS

Patient decidual macrophage tissue samples in spontaneous abortion group and normal pregnancy group (those who had induced abortion for non-medical reasons) were collected at the Reproductive Medicine Center of Renmin Hospital of Wuhan University from April to December 2021. Furthermore, placental villi and decidua tissue samples were collected from patients who had experienced a spontaneous miscarriage and normal pregnant women for validation and subsequent experiments at the Shenzhen Zhongshan Obstetrics & Gynecology Hospital (formerly Shenzhen Zhongshan Urology Hospital), from March 2021 to September 2022. As an animal model, 36 female mice were randomly divided into six groups as follows: naive-control, lipopolysaccharide-model, agomir-negative control prevention, agomir-410-5p prevention, agomir-negative control treatment, and agomir-410-5p treatment groups. We analyzed the miR-410-5p expression in abortion tissue and plasma samples; and supplemented miR-410-5p to evaluate embryonic absorption in vivo. The main source of miR-410-5p at the maternal-fetal interface was analyzed, and the possible target gene, signal transducer and activator of transcription (STAT) 1, of miR-410-5p was predicted. The effect of miR-410-5p and STAT1 regulation on macrophage phenotype, oxidative metabolism, and mitochondrial membrane potential was analyzed in vitro.

RESULTS

MiR-410-5p levels were lower in the spontaneous abortion group compared with the normal pregnancy group, and plasma miR-410-5p levels could predict pregnancy and spontaneous abortion. Prophylactic supplementation of miR-410-5p in pregnant mice reduced lipopolysaccharide-mediated embryonic absorption and downregulated the decidual macrophage pro-inflammatory phenotype. MiR-410-5p were mainly distributed in villi, and trophoblasts secreted exosomes-miR-410-5p at the maternal-fetal interface. After macrophages captured exosomes, the cells shifted to the tolerance phenotype. STAT1 was a potential target gene of miR-410-5p. MiR-410-5p bound to STAT1 mRNA, and inhibited the expression of STAT1 protein. STAT1 can drive macrophages to mature to a pro-inflammatory phenotype. MiR-410-5p competitive silencing of STAT1 can avoid macrophage immune disorders.

CONCLUSION

MiR-410-5p promotes M2 macrophage polarization by inhibiting STAT1, thus ensuring a healthy pregnancy. These findings are of great significance for diagnosing and preventing spontaneous miscarriage, providing a new perspective for further research in this field.

A Comparative Analysis of NT-proBNP Levels in Pregnant Women and the Impact of SARS-CoV-2 Infection: Influence on Birth Outcome

BACKGROUND

The cardiac biomarker NT-proBNP is released by the ventricles in response to increased cardiac wall tension, showing cardiac activity in heart failure. The primary objective of this comparative study was to analyze the variations of NT-proBNP levels among pregnant patients and to determine the potential influence of SARS-CoV-2 infection on these values. Secondly, the study focused on NT-proBNP levels and their influence on the type of birth.

METHODS

Blood samples were taken from 160 pregnant mothers in order to determine, through the solid-phase enzyme-linked immunosorbent assay (ELISA) method, the NT-proBNP concentrations from the plasma. The cohort was separated into two distinct groups based on SARS-CoV-2 diagnostic results: negative to the infection, and positive to the infection.

RESULTS

The SARS-CoV-2-positive group of patients presented with higher levels of NT-proBNP and had higher rates of cesarean sections. (4) Conclusions: Our research highlights the crucial relationship between elevated NT-proBNP values and the mode of giving birth, natural delivery or cesarean section, and also the influence of SARS-CoV-2 viral infection and this biomarker.