Commentary on a combined approach to the problem of developing biomarkers for the prediction of spontaneous preterm labor that leads to preterm birth

Neonatal Outcomes after Maternal Biomarker-Guided Preterm Birth Intervention: The AVERT PRETERM Trial

The AVERT PRETERM trial (NCT03151330) evaluated whether screening clinically low-risk pregnancies with a validated maternal blood biomarker test for spontaneous preterm birth (sPTB) risk, followed by preventive treatments for those screening positive, would improve neonatal outcomes compared to a clinically low-risk historical population that had received the usual care. Prospective arm participants with singleton non-anomalous pregnancies and no PTB history were tested for sPTB risk at 191/7-206/7 weeks' gestation and followed up with after neonatal discharge. Screen-positive individuals (≥16% sPTB risk) were offered vaginal progesterone (200 mg) and aspirin (81 mg) daily, with twice-weekly nurse phone calls. Co-primary outcomes were neonatal morbidity and mortality, measured using a validated composite index (NMI), and neonatal hospital length of stay (NNLOS). Endpoints were assessed using survival analysis and logistic regression in a modified intent-to-treat population comprising screen-negative individuals and screen-positive individuals accepting treatment. Of 1460 eligible participants, 34.7% screened positive; of these, 56.4% accepted interventions and 43.6% declined. Compared to historical controls, prospective arm neonates comprising mothers accepting treatment had lower NMI scores (odds ratio 0.81, 95% CI, 0.67-0.98, p = 0.03) and an 18% reduction in severe morbidity. NNLOS was shorter (hazard ratio 0.73, 95% CI, 0.58-0.92, p = 0.01), with a 21% mean stay decrease among neonates having the longest stays. Sensitivity analyses in the entire intent-to-treat population supported these findings. These results suggest that biomarker sPTB risk stratification and preventive interventions can ameliorate PTB complications in singleton, often nulliparous, pregnancies historically deemed low risk.

Exploring research hotspots and future directions in neural tube defects field by bibliometric and bioinformatics analysis

Background

Neural tube defects (NTDs) is the most common birth defect of the central nervous system (CNS) which causes the death of almost 88,000 people every year around the world. Much efforts have been made to investigate the reasons that contribute to NTD and explore new ways to for prevention. We trawl the past decade (2013-2022) published records in order to get a worldwide view about NTDs research field.

Methods

7,437 records about NTDs were retrieved from the Web of Science (WOS) database. Tools such as shell scripts, VOSviewer, SCImago Graphica, CiteSpace and PubTator were used for data analysis and visualization.

Results

Over the past decade, the number of publications has maintained an upward trend, except for 2022. The United States is the country with the highest number of publications and also with the closest collaboration with other countries. Baylor College of Medicine has the closest collaboration with other institutions worldwide and also was the most prolific institution. In the field of NTDs, research focuses on molecular mechanisms such as genes and signaling pathways related to folate metabolism, neurogenic diseases caused by neural tube closure disorders such as myelomeningocele and spina bifida, and prevention and treatment such as folate supplementation and surgical procedures. Most NTDs related genes are related to development, cell projection parts, and molecular binding. These genes are mainly concentrated in cancer, Wnt, MAPK, PI3K-Akt and other signaling pathways. The distribution of NTDs related SNPs on chromosomes 1, 3, 5, 11, 14, and 17 are relatively concentrated, which may be associated with high-risk of NTDs.

Conclusion

Bibliometric analysis of the literature on NTDs field provided the current status, hotspots and future directions to some extant. Further bioinformatics analysis expanded our understanding of NTDs-related genes function and revealed some important SNP clusters and loci. This study provided some guidance for further studies. More extensive cooperation and further research are needed to overcome the ongoing challenge in pathogenesis, prevention and treatment of NTDs.

Host-microbiome interactions in distinct subsets of preterm labor and birth

Preterm birth, the leading cause of perinatal morbidity, often follows premature labor, a syndrome whose prevention remains a challenge. To better understand the relationship between premature labor and host-microbiome interactions, we conducted a mechanistic investigation using three preterm birth models. We report that intra-amniotic delivery of LPS triggers inflammatory responses in the amniotic cavity and cervico-vaginal microenvironment, causing vaginal microbiome changes and signs of active labor. Intra-amniotic IL-1α delivery causes a moderate inflammatory response in the amniotic cavity but increasing inflammation in the cervico-vaginal space, leading to vaginal microbiome disruption and signs of active labor. Conversely, progesterone action blockade by RU-486 triggers local immune responses accompanying signs of active labor without altering the vaginal microbiome. Preterm labor facilitates ascension of cervico-vaginal bacteria into the amniotic cavity, regardless of stimulus. This study provides compelling mechanistic insights into the dynamic host-microbiome interactions within the cervico-vaginal microenvironment that accompany premature labor and birth.

mRNA and Protein Expression in Human Fetal Membrane Cells: Potential Biomarkers for Preterm Prelabor Rupture of the Fetal Membranes?

Clinically, unique markers in fetal membrane cells may contribute to the search for biomarkers for preterm prelabor rupture of the fetal membranes (pPROM) in maternal blood. pPROM is associated with overwhelming inflammation and premature cellular senescence causing "biological microfractures" of the fetal membranes. We hypothesize that these pathological processes are associated with the shedding of fetal membrane cells into the maternal circulation. The aim of this study was to identify markers expressed exclusively in fetal membrane cells to facilitate their isolation, characterization, and determination of biomarker potential in maternal blood. We have (1), by their transcriptomic profile, identified markers that are upregulated in amnion and chorion tissue compared to maternal white blood cells, and (2), by immunohistochemistry, confirmed the localization of the differentially expressed proteins in fetal membranes, placenta, and the placental bed of the uterus. RNA sequencing revealed 31 transcripts in the amnion and 42 transcripts in the chorion that were upregulated. Among these, 22 proteins were evaluated by immunohistochemistry. All but two transcripts were expressed both on mRNA and protein level in at least one fetal membrane cell type. Among these remaining 20 proteins, 9 proteins were not significantly expressed in the villous and extravillous trophoblasts of the placenta.

Advances in mass spectrometry technologies to characterize cervicovaginal microbiome functions that impact spontaneous preterm birth

Preterm birth (PTB) is a leading cause of morbidity and mortality in young children. Infection is a major cause of this adverse outcome, particularly in PTBs characterised by spontaneous rupture of membranes, referred to as spontaneous (s)PTB. However, the aetiology of sPTB is not well defined and specific bacteria associated with sPTB differ between studies and at the individual level. This may be due to many factors including a lack of understanding of strain-level differences in bacteria that influence how they function and interact with each other and the host. Metaproteomics and metabolomics are mass spectrometry-based methods that enable the collection of detailed microbial and host functional information. Technological advances in this field have dramatically increased the resolution of these approaches, enabling the simultaneous detection of thousands of proteins or metabolites. These data can be used for taxonomic analysis of vaginal bacteria and other microbes, to understand microbiome-host interactions, and identify diagnostic biomarkers or therapeutic targets. Although these methods have been used to assess host proteins and metabolites, few have characterized the microbial compartment in the context of pregnancy. The utilisation of metaproteomic and metabolomic-based approaches has the potential to vastly improve our understanding of the mechanisms leading to sPTB.

Cervicovaginal Cytokines to Predict the Onset of Normal and Preterm Labor: a Pseudo-longitudinal Study

Inflammatory processes associated with human parturition are still not completely understood, not only because the gap between inflammation and the onset of labor has been difficult to study but also because of the limited knowledge about the role of cervicovaginal fluid (CVF) cytokines during the sequence of labor. We aimed to determine whether CVF cytokines could predict the onset of normal and preterm labor. Chemokines and proinflammatory and anti-inflammatory cytokines in CVF were measured in a pseudo-longitudinal manner in healthy women between 12 and 41 weeks gestation with intact fetal membranes before and during the first stage of labor. Women were grouped into five stages, from the absence of uterine activity and cervical changes to regular uterine contractions with cervix dilation > 3 cm (active phase of labor). Of 144 women with spontaneous labor, 96 gave birth at term, 48 gave birth preterm, and both groups displayed similar cytokine concentrations. We found positive correlations between proinflammatory cytokines and the initial sequence of labor, using individual cytokines and score-based data by principal component analysis (IFN-γ, TNF-α, IL-1β, IL-6) as dependent variables. The risk of labor onset increased as the concentrations of IL-6 increased (hazard ratio = 202.09, 95% confidence interval = 24.57-1662.49, P < 0.001). The IL-6 concentration predicted the onset of labor within 12 days of sampling (area under the time-dependent ROC curve = 0.785, 95% confidence interval = 0.693-0.877). Here, we showed that regardless of gestational age, the onset of labor could be predicted by the IL-6 concentration in the CVF, since the initial sequence of spontaneous labor displayed an inflammatory response expressed by the increase in proinflammatory cytokines.

Natural copper isotopic abnormity in maternal serum at early pregnancy associated to risk of spontaneous preterm birth

Spontaneous preterm birth (SPB) has drawn public attention due to its increasing incidence and adverse effects on fetal growth. Effect of copper (Cu) imbalance in maternal bodies on the risk of SPB remains a subject of debate, and the related mechanisms are still unraveled. Here we applied natural stable copper isotopes to explore the underlying association and mechanism of copper imbalance with SPB using a nested case-control study. We collected maternal sera at the early pregnancy stage and then measured their copper isotopic ratio (⁶⁵Cu/⁶³Cu, expressed as δ⁶⁵Cu) as well as physiological and biochemical indexes from women with and without delivering SPB. We found that SPB cases had no significant difference in serum copper level from their controls, but their serum copper was significantly isotopically heavier than the controls (δ⁶⁵Cu value = 0.15 ± 0.34 ‰ versus -0.15 ± 0.17 ‰, P = 0.0149). Compared with the controls with lower δ⁶⁵Cu values, the crude odds ratio (OR) associated with SPB risk increased to 4.00 (95 % confidence interval (CI): 1.37-11.70) and the adjusted OR reached up to 11.35 (95 % CI: 1.35-95.60). Furthermore, via the copper isotopic fractionation, we revealed that dietary intake and blood ceruloplasmin may play more important roles than blood lipids and mother-to-child transmission in the copper imbalance associated with SPB. Further studies will be needed to understand the mechanisms of isotope fractionation related to reproductive health.

Developing and validating a risk prediction model for preterm birth at Felege Hiwot Comprehensive Specialized Hospital, North-West Ethiopia: a retrospective follow-up study

OBJECTIVE

To develop and validate a risk prediction model for the prediction of preterm birth using maternal characteristics.

DESIGN

This was a retrospective follow-up study. Data were coded and entered into EpiData, V.3.02, and were analysed using R statistical programming language V.4.0.4 for further processing and analysis. Bivariable logistic regression was used to identify the relationship between each predictor and preterm birth. Variables with p≤0.25 from the bivariable analysis were entered into a backward stepwise multivariable logistic regression model, and significant variables (p<0.05) were retained in the multivariable model. Model accuracy and goodness of fit were assessed by computing the area under the receiver operating characteristic curve (discrimination) and calibration plot (calibration), respectively.

SETTING AND PARTICIPANTS

This retrospective study was conducted among 1260 pregnant women who did prenatal care and finally delivered at Felege Hiwot Comprehensive Specialised Hospital, Bahir Dar city, north-west Ethiopia, from 30 January 2019 to 30 January 2021.

RESULTS

Residence, gravidity, haemoglobin <11 mg/dL, early rupture of membranes, antepartum haemorrhage and pregnancy-induced hypertension remained in the final multivariable prediction model. The area under the curve of the model was 0.816 (95% CI 0.779 to 0.856).

CONCLUSION

This study showed the possibility of predicting preterm birth using maternal characteristics during pregnancy. Thus, use of this model could help identify pregnant women at a higher risk of having a preterm birth to be linked to a centre.

Predicting preterm birth through vaginal microbiota, cervical length, and WBC using a machine learning model

An association between the vaginal microbiome and preterm birth has been reported. However, in practice, it is difficult to predict premature birth using the microbiome because the vaginal microbial community varies highly among samples depending on the individual, and the prediction rate is very low. The purpose of this study was to select markers that improve predictive power through machine learning among various vaginal microbiota and develop a prediction algorithm with better predictive power that combines clinical information. As a multicenter case–control study with 150 Korean pregnant women with 54 preterm delivery group and 96 full-term delivery group, cervicovaginal fluid was collected from pregnant women during mid-pregnancy. Their demographic profiles (age, BMI, education level, and PTB history), white blood cell count, and cervical length were recorded, and the microbiome profiles of the cervicovaginal fluid were analyzed. The subjects were randomly divided into a training (n = 101) and a test set (n = 49) in a two-to-one ratio. When training ML models using selected markers, five-fold cross-validation was performed on the training set. A univariate analysis was performed to select markers using seven statistical tests, including the Wilcoxon rank-sum test. Using the selected markers, including Lactobacillus spp., Gardnerella vaginalis, Ureaplasma parvum, Atopobium vaginae, Prevotella timonensis, and Peptoniphilus grossensis, machine learning models (logistic regression, random forest, extreme gradient boosting, support vector machine, and GUIDE) were used to build prediction models. The test area under the curve of the logistic regression model was 0.72 when it was trained with the 17 selected markers. When analyzed by combining white blood cell count and cervical length with the seven vaginal microbiome markers, the random forest model showed the highest test area under the curve of 0.84. The GUIDE, the single tree model, provided a more reasonable biological interpretation, using the 10 selected markers (A. vaginae, G. vaginalis, Lactobacillus crispatus, Lactobacillus fornicalis, Lactobacillus gasseri, Lactobacillus iners, Lactobacillus jensenii, Peptoniphilus grossensis, P. timonensis, and U. parvum), and the covariates produced a tree with a test area under the curve of 0.77. It was confirmed that the association with preterm birth increased when P. timonensis and U. parvum increased (AUC = 0.77), which could also be explained by the fact that as the number of Peptoniphilus lacrimalis increased, the association with preterm birth was high (AUC = 0.77). Our study demonstrates that several candidate bacteria could be used as potential predictors for preterm birth, and that the predictive rate can be increased through a machine learning model employing a combination of cervical length and white blood cell count information.

Circulating trophoblast numbers as a potential marker for pregnancy complications

OBJECTIVE

To explore the potential of circulating trophoblasts (TBs) as a non-invasive tool to assess placental health and predict obstetric complications.

METHODS

We retrospectively reviewed maternal characteristics and pregnancy outcomes of 369 women who enrolled in our original cell-based NIPT (cbNIPT) study. The number of circulating TBs recovered from the maternal blood samples was recorded and expressed as fetal cell concentration (FCC). We evaluated if FCC can be used to predict pregnancy outcomes such as hypertensive disorders of pregnancy (HDP), fetal growth restriction, placental abruption, preterm labor, and pregnancy loss.

RESULTS

Receiver operating characteristic (ROC) analysis was performed to find the best cut off value to classify FCC into a low and high FCC group, and this cut-off point was calculated as 11.1 cells per 100 ml of blood. The adjusted odds ratio (aOR) for the composite morbidity was significantly increased for the high FCC group at an aOR of 1.6.

CONCLUSION

Circulating TB have the potential of predicting obstetrical complications such as HDP. Future studies, with larger sample sizes, should focus on the study of these cells as a biomarker for placental health and a possible screening or diagnostic tool for fetal genetic conditions.

Interferon epsilon and preterm birth subtypes; a new piece of the type I interferon puzzle during pregnancy?

PROBLEM

Interferon epsilon (IFNε) is a unique type I IFN that is expressed in response to sex steroids. Studies suggest that type I IFNs regulate inflammation-induced preterm birth (PTB), but no study has examined the role of IFNε in human pregnancy.

METHOD OF STUDY

We used stored vaginal swabs between 8 and 26 weeks of gestation from the Global Alliance to Prevent Prematurity and Stillbirth (GAPPS) biobank and measured IFNε by enzyme-linked immunosorbent assay (ELISA). A total of 29 women with spontaneous preterm births, 34 women with medically indicated preterm births, and 134 women with term births were included. Secondary outcomes included a preterm birth with chorioamnionitis and preeclampsia with a preterm birth. Logistic regression calculated odds ratios (OR) and 95% confidence intervals (CI) adjusting for maternal age, race, body mass index, prior pregnancy complications, lower genital tract infections, chronic health conditions, and gestational age at blood draw.

RESULTS AND CONCLUSIONS

There was no significant association between IFNε and spontaneous preterm birth (OR_adj 1.0, 0.8-1.3) or chorioamnionitis (OR_adj 1.6, 0.7-3.5). A trend toward increased odds of medically indicated preterm birth (OR_adj . 1.3, 1.0-1.8) was observed. This was likely due to elevated IFNε among women with preterm preeclampsia (OR_adj . 2.0, 95% CI 1.3-3.2). While exploratory, our novel findings suggest that larger longitudinal studies of IFNε across human pregnancy may be warranted.

Preterm birth update in Australasia: A report of the international symposium of Preterm Birth International Collaborative-Australasia branch

Preterm birth (PTB) is one of the most important problems that pose dilemmas for both the obstetrician and neonatologist, placing a heavy burden psychologically and financially on the families involved, and triggering high socio-economic costs to the public healthcare. The rate of PTB in Asian countries has been ranked at top globally. To reduce the PTB rate, to promote the prevention and intervention for PTB, and to better understand the pathophysiology underlying PTB, the Preterm Birth International Collaborative Australia branch (PREBIC-AA) was launched in 2017. A series scientific activities including organizing annual research symposiums has been planned and organized among Australasian countries. Here we briefly updated the current progress in clinical management and translational research on PTB in Australasian countries that have been participated in PREBIC-AA.

Development of a mouse model of ascending infection and preterm birth

BACKGROUND

Microbial invasion of the intraamniotic cavity and intraamniotic inflammation are factors associated with spontaneous preterm birth. Understanding the route and kinetics of infection, sites of colonization, and mechanisms of host inflammatory response is critical to reducing preterm birth risk.

OBJECTIVES

This study developed an animal model of ascending infection and preterm birth with live bacteria (E. coli) in pregnant CD-1 mice with the goal of better understanding the process of microbial invasion of the intraamniotic cavity and intraamniotic inflammation.

STUDY DESIGN

Multiple experiments were conducted in this study. To determine the dose of E. coli required to induce preterm birth, CD-1 mice were injected vaginally with four different doses of E. coli (103, 106, 1010, or 1011 colony forming units [CFU]) in 40 μL of nutrient broth or broth alone (control) on an embryonic day (E)15. Preterm birth (defined as delivery before E18.5) was monitored using live video. E. coli ascent kinetics were measured by staining the E. coli with lipophilic tracer DiD for visualization through intact tissue with an in vivo imaging system (IVIS) after inoculation. The E. coli were also directly visualized in reproductive tissues by staining the bacteria with carboxyfluorescein succinimidyl ester (CFSE) prior to administration and via immunohistochemistry (IHC) by staining tissues with anti-E. coli antibody. Each pup's amniotic fluid was cultured separately to determine the extent of microbial invasion of the intraamniotic cavity at different time points. Intraamniotic inflammation resulting from E. coli invasion was assessed with IHC for inflammatory markers (TLR-4, P-NF-κB) and neutrophil marker (Ly-6G) for chorioamnionitis at 6- and 24-h post-inoculation.

RESULTS

Vaginally administered E. coli resulted in preterm birth in a dose-dependent manner with higher doses causing earlier births. In ex vivo imaging and IHC detected uterine horns proximal to the cervix had increased E. coli compared to the distal uterine horns. E. coli were detected in the uterus, fetal membranes (FM), and placenta in a time-dependent manner with 6 hr having increased intensity of E. coli positive signals in pups near the cervix and in all pups at 24 hr. Similarly, E. coli grew from the cultures of amniotic fluid collected nearest to the cervix, but not from the more distal samples at 6 hr post-inoculation. At 24 hr, all amniotic fluid cultures regardless of distance from the cervix, were positive for E. coli. TLR-4 and P-NF-κB signals were more intense in the tissues where E. coli was present (placenta, FM and uterus), displaying a similar trend toward increased signal in proximal gestational sacs compared to distal at 6 hr. Ly-6G+ cells, used to confirm chorioamnionitis, were increased at 24 hr compared to 6 hr post-inoculation and control.

CONCLUSION

We report the development of mouse model of ascending infection and the associated inflammation of preterm birth. Clinically, these models can help to understand mechanisms of infection associated preterm birth, determine targets for intervention, or identify potential biomarkers that can predict a high-risk pregnancy status early in pregnancy.

The Role of Innate Immune System in the Human Amniotic Membrane and Human Amniotic Fluid in Protection Against Intra-Amniotic Infections and Inflammation

Intra-amniotic infection and inflammation (IAI) affect fetal development and are highly associated with preterm labor and premature rupture of membranes, which often lead to adverse neonatal outcomes. Human amniotic membrane (hAM), the inner part of the amnio-chorionic membrane, protects the embryo/fetus from environmental dangers, including microbial infection. However, weakened amnio-chorionic membrane may be breached or pathogens may enter through a different route, leading to IAI. The hAM and human amniotic fluid (hAF) respond by activation of all components of the innate immune system. This includes changes in 1) hAM structure, 2) presence of immune cells, 3) pattern recognition receptors, 4) cytokines, 5) antimicrobial peptides, 6) lipid derivatives, and 7) complement system. Herein we provide a comprehensive and integrative review of the current understanding of the innate immune response in the hAM and hAF, which will aid in design of novel studies that may lead to breakthroughs in how we perceive the IAI.

Overview and recent developments in cell-based noninvasive prenatal testing

Investigators have long been interested in the natural phenomenon of fetal and placental cell trafficking into the maternal circulation. The scarcity of these circulating cells makes their detection and isolation technically challenging. However, as a DNA source of fetal origin not mixed with maternal DNA, they have the potential of considerable benefit over circulating cell-free DNA-based noninvasive prenatal genetic testing (NIPT). Endocervical trophoblasts, which are less rare but more challenging to recover are also being investigated as an approach for cell-based NIPT. We review published studies from around the world describing both forms of cell-based NIPT and highlight the different approaches' advantages and drawbacks. We also offer guidance for developing a sound cell-based NIPT protocol.

Prevention of preterm birth: Proactive and reactive clinical practice-are we on the right track?

Preterm birth remains the major cause of death and disability among children under the age of five. In developing countries antenatal preterm birth prevention clinics are set up to provide cervical length surveillance and/or treatment modalities such as cerclage or progesterone for those women with identified risk factors such as previous cervical treatment or preterm birth. However, 85% of women have no risk factors for PTB and currently there is no biomarker to screen women early in pregnancy. Women will present unexpectedly in threatened preterm labour and we have no choice but to adopt a re-active approach to their care by using predication and preparation strategies such as fetal fibronectin, tocolytic therapy and steroids. Despite these strategies approximately 15-20% of these women will give birth preterm before 34 weeks. There is a urgent need to re-design primary, secondary and tertiary prevention strategies for spontaneous preterm labour (sPTL) in singleton pregnancies aimed at identifying and addressing key gaps in clinical practice and research.