Development and validation of a spontaneous preterm delivery predictor in asymptomatic women

Association between maternal gestation weight gain and preterm birth according to pre-pregnancy body mass index and HbA1c

BACKGROUND

To investigate the association between gestational weight gain (GWG) and preterm birth (PTB) according to pre-pregnancy body mass index (pp-BMI) and glycated haemoglobin (HbA1c) within the normal range.

METHODS

We conducted a population-based retrospective cohort study between July 2017 and January 2020 at Women's Hospital, Zhejiang University School of Medicine. Women were classified into three groups (inadequate GWG, appropriate GWG, and excessive GWG). In addition, women were divided into different subgroups according to pp-BMI and HbA1c. We estimated the odds ratios (OR) with 95% confidence intervals (CI) to assess the associations between GWG and the risk of PTB. Meanwhile, we adjusted for possible confounding factors, including maternal age, infant sex, family history of diabetes, education, pregnancy mode, delivery mode, parity, and gravidity.

RESULTS

The study involved 23,699 pregnant women, of which 1124 (4.70%) were PTB. Women who had inadequate GWG were found to have a significantly higher risk of PTB compared to women with appropriate GWG. In contrast, women with excessive GWG had a reduced risk of PTB. Similarly, GWG and PTB had similar risk associations in the HbA1c and pp-BMI subgroups. Among women with pp-BMI <18.5 kg/m2, women with inadequate GWG had a significantly increased risk of PTB compared with women in the control group (HbA1c 4.6-5.0%, appropriate GWG), and the risk increased with increasing HbA1c levels. Similar results were observed in women with normal pp-BMI.

CONCLUSIONS

There was a significant association between GWG and the risk of PTB, but the risk varied by pp-BMI and HbA1c levels. Reasonable weight gain during pregnancy is essential to prevent PTB. Furthermore, while HbA1c is within the normal range, the higher levels should be noticed.

Validating the ratio of insulin like growth factor binding protein 4 to sex hormone binding globulin as a prognostic predictor of preterm birth in Viet Nam: a case-cohort study

OBJECTIVE

To validate a serum biomarker developed in the USA for preterm birth (PTB) risk stratification in Viet Nam.

METHODS

Women with singleton pregnancies (n = 5000) were recruited between 19+0-23+6 weeks' gestation at Tu Du Hospital, Ho Chi Minh City. Maternal serum was collected from 19+0-22+6 weeks' gestation and participants followed to neonatal discharge. Relative insulin-like growth factor binding protein 4 (IGFBP4) and sex hormone binding globulin (SHBG) abundances were measured by mass spectrometry and their ratio compared between PTB cases and term controls. Discrimination (area under the receiver operating characteristic curve, AUC) and calibration for PTB <37 and <34 weeks' gestation were tested, with model tuning using clinical factors. Measured outcomes included all PTBs (any birth ≤37 weeks' gestation) and spontaneous PTBs (birth ≤37 weeks' gestation with clinical signs of initiation of parturition).

RESULTS

Complete data were available for 4984 (99.7%) individuals. The cohort PTB rate was 6.7% (n = 335). We observed an inverse association between the IGFBP4/SHBG ratio and gestational age at birth (p = 0.017; AUC 0.60 [95% CI, 0.53-0.68]). Including previous PTB (for multiparous women) or prior miscarriage (for primiparous women) improved performance (AUC 0.65 and 0.70, respectively, for PTB <37 and <34 weeks' gestation). Optimal performance (AUC 0.74) was seen within 19-20 weeks' gestation, for BMI >21 kg/m2 and age 20-35 years.

CONCLUSION

We have validated a novel serum biomarker for PTB risk stratification in a very different setting to the original study. Further research is required to determine appropriate ratio thresholds based on the prevalence of risk factors and the availability of resources and preventative therapies.

Development of a spontaneous preterm birth predictive model using a panel of serum protein biomarkers for early pregnant women: A nested case-control study

OBJECTIVE

To develop a model based on maternal serum liquid chromatography tandem mass spectrometry (LC-MS/MS) proteins to predict spontaneous preterm birth (sPTB).

METHODS

This nested case-control study used the data from a cohort of 2053 women in China from July 1, 2018, to January 31, 2019. In total, 110 singleton pregnancies at 11-13+6 weeks of pregnancy were used for model development and internal validation. A total of 72 pregnancies at 20-32 weeks from an additional cohort of 2167 women were used to evaluate the scalability of the model. Maternal serum samples were analyzed by LC-MS/MS, and a predictive model was developed using machine learning algorithms.

RESULTS

A novel predictive panel with four proteins, including soluble fms-like tyrosine kinase-1, matrix metalloproteinase 8, ceruloplasmin, and sex-hormone-binding globulin, was developed. The optimal model of logistic regression had an AUC of 0.934, with additional prediction of sPTB in second and third trimester (AUC = 0.868).

CONCLUSION

First-trimester modeling based on maternal serum LC-MS/MS identifies pregnant women at risk of sPTB, which may provide utility in identifying women at risk at an early stage of pregnancy before clinical presentation to allow for earlier intervention.

Assessment of current biomarkers and interventions to identify and treat women at risk of preterm birth

Preterm birth remains an important global problem, and an important contributor to under-5 mortality. Reducing spontaneous preterm birth rates at the global level will require the early identification of patients at risk of preterm delivery in order to allow the initiation of appropriate prophylactic management strategies. Ideally these strategies target the underlying pathophysiologic causes of preterm labor. Prevention, however, becomes problematic as the causes of preterm birth are multifactorial and vary by gestational age, ethnicity, and social context. Unfortunately, current screening and diagnostic tests are non-specific, with only moderate clinical risk prediction, relying on the detection of downstream markers of the common end-stage pathway rather than identifying upstream pathway-specific pathophysiology that would help the provider initiate targeted interventions. As a result, the available management options (including cervical cerclage and vaginal progesterone) are used empirically with, at best, ambiguous results in clinical trials. Furthermore, the available screening tests have only modest clinical risk prediction, and fail to identify most patients who will have a preterm birth. Clearly defining preterm birth phenotypes and the biologic pathways leading to preterm birth is key to providing targeted, biomolecular pathway-specific interventions, ideally initiated in early pregnancy Pathway specific biomarker discovery, together with management strategies based on early, mid-, and-late trimester specific markers is integral to this process, which must be addressed in a systematic way through rigorously planned biomarker trials.

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.

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.

The utility of combined utero-cervical ındex in predicting preterm delivery in pregnant women with preterm uterine contractions

PURPOSE

To evaluate the utility of a novel ultrasound index "combined utero-cervical index (CUCI)" in the prediction of preterm delivery.

METHODS

The present prospective cohort study was conducted in Ankara Bilkent City Hospital Perinatology Clinic between January 1, 2023, and March 31, 2023. Pregnant women with uterine contractions between 24 and 36th gestational weeks but did not have dilatation or effacement were included. CUCI was calculated as: (utero-cervical angle)/(anterior cervical lip thickness + fundal thickness + lower uterine segment thickness + cervical length). In the presence of cervical funneling, one point was added to the final result. A ROC analysis was conducted to determine the potential of CUCI in predicting delivery <37 weeks of gestation, <34 weeks of gestation, and <4 weeks after the first admission to the hospital for uterine contractions, respectively.

RESULTS

Optimal cut-off values of CUCI were found to be 1.4 (67.1% sensitivity, 67.2% specificity) for predicting delivery at <37th weeks, 1.7 (72.7% sensitivity, 65.7% specificity) for predicting delivery at <34th weeks, and 1.4 (62.5% sensitivity, 61.7% specificity) for predicting delivery at <4 weeks.

CONCLUSION

CUCI may be used in the prediction of preterm delivery for pregnant women admitted to hospital with preterm uterine contractions.

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.

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.

Evaluating the Efficacy of Cervical Tactile Ultrasound Technique as a Predictive Tool for Spontaneous Preterm Birth

Background

Premature cervical softening and shortening may be considered an early mechanical failure that predispose to preterm birth.

Purpose

This study aims to explore the applicability of an innovative cervical tactile ultrasound approach for predicting spontaneous preterm birth (sPTB).

Materials and Methods

Eligible participants were women with low-risk singleton pregnancies in their second trimester, enrolled in this prospective observational study. A Cervix Monitor (CM) device was designed with a vaginal probe comprising four tactile sensors and a single ultrasound transducer operating at 5 MHz. The probe enabled the application of controllable pressure to the external cervical surface, facilitating the acquisition of stress-strain data from both anterior and posterior cervical sectors. Gestational age at delivery was recorded and compared against cervical elasticity.

Results

CM examination data were analyzed for 127 women at 240/7 - 286/7 gestational weeks. sPTB was observed in 6.3% of the cases. The preterm group exhibited a lower average cervical stress-to-strain ratio (elasticity) of 0.70 ± 0.26 kPa/mm compared to the term group's 1.63 ± 0.65 kPa/mm with a p-value of 1.1 × 10-4. Diagnostic accuracy for predicting spontaneous preterm birth based solely on cervical elasticity data was found to be 95.0% (95% CI, 88.5 - 100.0).

Conclusion

These findings suggest that measuring cervical elasticity with the designed tactile ultrasound probe has the potential to predict spontaneous preterm birth in a cost-effective manner.

Applicability of selected reaction monitoring for precise screening tests

INTRODUCTION

The proactive identification of diseases through screening tests has long been endorsed as a means to preempt symptomatic onset. However, such screening endeavors are fraught with complications, such as diagnostic inaccuracies, procedural risks, and patient unease during examinations. These challenges are amplified when screenings for multiple diseases are administered concurrently. Selected Reaction Monitoring (SRM) offers a unique advantage, allowing for the high-throughput quantification of hundreds of analytes with minimal interferences.

AREAS COVERED

Our research posits that SRM-based assays, traditionally tailored for single-disease biomarker profiling, can be repurposed for multi-disease screening. This innovative approach has the potential to substantially alleviate time, labor, and cost demands on healthcare systems and patients alike. Nonetheless, there are formidable methodological hurdles to overcome. These include difficulties in detecting low-abundance proteins and the risk of model overfitting due to the multiple functionalities of single proteins across different disease spectrums - issues especially pertinent in blood-based assays where detection sensitivity is constrained. As we move forward, technological strides in sample preparation, online extraction, throughput, and automation are expected to ameliorate these limitations.

EXPERT OPINION

The maturation of mass spectrometry's integration into clinical laboratories appears imminent, positioning it as an invaluable asset for delivering highly sensitive, reproducible, and precise diagnostic results.

Development and validation of a simplified risk prediction model for preterm birth: a prospective cohort study in rural Ethiopia

Preterm birth is one of the most common obstetric complications in low- and middle-income countries, where access to advanced diagnostic tests and imaging is limited. Therefore, we developed and validated a simplified risk prediction tool to predict preterm birth based on easily applicable and routinely collected characteristics of pregnant women in the primary care setting. We used a logistic regression model to develop a model based on the data collected from 481 pregnant women. Model accuracy was evaluated through discrimination (measured by the area under the Receiver Operating Characteristic curve; AUC) and calibration (via calibration graphs and the Hosmer-Lemeshow goodness of fit test). Internal validation was performed using a bootstrapping technique. A simplified risk score was developed, and the cut-off point was determined using the "Youden index" to classify pregnant women into high or low risk for preterm birth. The incidence of preterm birth was 19.5% (95% CI:16.2, 23.3) of pregnancies. The final prediction model incorporated mid-upper arm circumference, gravidity, history of abortion, antenatal care, comorbidity, intimate partner violence, and anemia as predictors of preeclampsia. The AUC of the model was 0.687 (95% CI: 0.62, 0.75). The calibration plot demonstrated a good calibration with a p-value of 0.713 for the Hosmer-Lemeshow goodness of fit test. The model can identify pregnant women at high risk of preterm birth. It is applicable in daily clinical practice and could contribute to the improvement of the health of women and newborns in primary care settings with limited resources. Healthcare providers in rural areas could use this prediction model to improve clinical decision-making and reduce obstetrics complications.

Molecular epidemiology of pregnancy using omics data: advances, success stories, and challenges

Multi-omics approaches have been successfully applied to investigate pregnancy and health outcomes at a molecular and genetic level in several studies. As omics technologies advance, research areas are open to study further. Here we discuss overall trends and examples of successfully using omics technologies and techniques (e.g., genomics, proteomics, metabolomics, and metagenomics) to investigate the molecular epidemiology of pregnancy. In addition, we outline omics applications and study characteristics of pregnancy for understanding fundamental biology, causal health, and physiological relationships, risk and prediction modeling, diagnostics, and correlations.

Preterm Birth: Screening and Prediction

Preterm birth (PTB) affects approximately 10% of births globally each year and is the most significant direct cause of neonatal death and of long-term disability worldwide. Early identification of women at high risk of PTB is important, given the availability of evidence-based, effective screening modalities, which facilitate decision-making on preventative strategies, particularly transvaginal sonographic cervical length (CL) measurement. There is growing evidence that combining CL with quantitative fetal fibronectin (qfFN) and maternal risk factors in the extensively peer-reviewed and validated QUanititative Innovation in Predicting Preterm birth (QUiPP) application can aid both the triage of patients who present as emergencies with symptoms of preterm labor and high-risk asymptomatic women attending PTB surveillance clinics. The QUiPP app risk of delivery thus supports shared decision-making with patients on the need for increased outpatient surveillance, in-patient treatment for preterm labor or simply reassurance for those unlikely to deliver preterm. Effective triage of patients at preterm gestations is an obstetric clinical priority as correctly timed administration of antenatal corticosteroids will maximise their neonatal benefits. This review explores the predictive capacity of existing predictive tests for PTB in both singleton and multiple pregnancies, including the QUiPP app v.2. and discusses promising new research areas, which aim to predict PTB through cervical stiffness and elastography measurements, metabolomics, extracellular vesicles and artificial intelligence.

Identification of biochemical biomarkers associated with premature cervical shortening in high-risk, asymptomatic pregnant women: a retrospective data analysis

Reliably predicting spontaneous preterm birth remains challenging, therefore it persists as a major contributor to perinatal morbidity and mortality. The use of biomarkers to predict premature cervical shortening, a recognised risk factor for spontaneous preterm birth, is yet to be fully explored in current literature. This study evaluates seven cervicovaginal biochemical biomarkers as possible predictors of premature cervical shortening. Asymptomatic, high-risk women (n = 131) presenting to a specialised preterm birth prevention clinic were analysed through a retrospective data analysis. Cervicovaginal biochemical biomarker concentrations were obtained, and the shortest cervical length measurement, up to 28 weeks' gestation, was recorded. Associations between biomarker concentration and cervical length were then analysed. Of the seven biochemical biomarkers, Interleukin-1 Receptor Antagonist and Extracellular Matrix Protein-1 had statistically significant relationships with cervical shortening below 25 mm. Further investigation is required to validate these findings and any downstream clinical utility, with intentions to improve perinatal outcomes.IMPACT STATEMENTWhat is already known on this subject? Preterm birth is a major cause of perinatal morbidity and mortality. A woman's risk of delivering preterm is currently stratified using historical risk factors, mid-gestation cervical length, and biochemical biomarkers such as foetal fibronectin.What do the results of this study add? In a cohort of high-risk, asymptomatic pregnant women, two cervicovaginal biochemical biomarkers, Interleukin-1 Receptor Antagonist and Extracellular Matrix Protein-1, displayed associations with premature cervical shortening.What are the implications of these findings for clinical practice and/or further research? Further investigation into the possible clinical utility of these biochemical biomarkers is warranted, with a view to improving preterm birth prediction and antenatal resource utilisation, thereby reducing the burden of preterm birth and its sequelae in a cost-effective manner.

A dual-binding magnetic immunoassay to predict spontaneous preterm birth

Complications posed by preterm birth (delivery before 37 weeks of pregnancy) are a leading cause of newborn morbidity and mortality. The previous discovery and validation of an algorithm that includes maternal serum protein biomarkers, sex hormone-binding globulin (SHBG), and insulin-like growth factor-binding protein 4 (IBP4), with clinical factors to predict preterm birth represents an opportunity for the development of a widely accessible point-of-care assay to guide clinical management. Toward this end, we developed SHBG and IBP4 quantification assays for maternal serum using giant magnetoresistive (GMR) sensors and a self-normalizing dual-binding magnetic immunoassay. The assays have a picomolar limit of detections (LOD) with a relatively broad dynamic range that covers the physiological level of the analytes as they change throughout gestation. Measurement of serum from pregnant donors using the GMR assays was highly concordant with those obtained using a clinical mass spectrometry (MS)-based assay for the same protein markers. The MS assay requires capitally intense equipment and highly trained operators with a few days turnaround time, whereas the GMR assays can be performed in minutes on small, inexpensive instruments with minimal personnel training and microfluidic automation. The potential for high sensitivity, accuracy, and speed of the GMR assays, along with low equipment and personnel requirements, make them good candidates for developing point-of-care tests. Rapid turnaround risk assessment for preterm birth would enable patient testing and counseling at the same clinic visit, thereby increasing the timeliness of recommended interventions.

Prediction and Prevention of Preterm Birth: Secondary Analysis of a Randomized Intervention Trial

Our objective was to evaluate whether pregnancy is prolonged by the use of a proteomics-based maternal serum screening test followed by treatment interventions. This is a secondary analysis of the PREVENT-PTB randomized trial comparing screening with the PreTRM test versus no screening. The primary trial analysis found no significant between-group difference in the preterm birth rate. Rather than considering a dichotomous outcome (preterm versus term), we treated gestational age at birth as a continuous variable using survival analysis. We also evaluated between-group difference in NICU length of stay and duration of respiratory support. Results indicated that pregnancy was significantly prolonged in subjects screened with the PreTRM test compared to controls (adjusted hazard ratio 0.53, 95% confidence interval 0.36-0.78, p < 0.01). Newborns of screened subjects had significantly shorter NICU stays but no significant decrease in duration of respiratory support. In the PreTRM screen-positive group, interventions that were associated with pregnancy prolongation included care management and low-dose aspirin but not 17-hydroxyprogesterone caproate. We conclude that screening with the PreTRM test followed by interventions for screen-positive pregnancies may prolong pregnancy and reduce NICU LOS, but these observations need to be confirmed by additional research.

Risk Scoring Systems for Preterm Birth and Their Performance: A Systematic Review

Introduction: Nowadays, the risk stratification of preterm birth (PTB) and its prediction remain a challenge. Many risk factors associated with PTB have been identified, and risk scoring systems (RSSs) have been developed to face this challenge. The objectives of this systematic review were to identify RSSs for PTB, the variables they consist of, and their performance. Materials and methods: Two databases were searched, and two authors independently performed the screening and eligibility phases. Records studying an RSS, based on specified variables, with an evaluation of the predictive value for PTB, were considered eligible. Reference lists of eligible studies and review articles were also searched. Data from the included studies were extracted. Results: A total of 56 studies were included in this review. The most frequently incorporated variables in the RSS included in this review were maternal age, weight, history of smoking, history of previous PTB, and cervical length. The performance measures varied widely among the studies, with sensitivity ranging between 4.2% and 92.0% and area under the curve (AUC) between 0.59 and 0.95. Conclusions: Despite the recent technological and scientifical evolution with a better understanding of variables related to PTB and the definition of new ultrasonographic parameters and biomarkers associated with PTB, the RSS's ability to predict PTB remains poor in most situations, thus compromising the integration of a single RSS in clinical practice. The development of new RSSs, the identification of new variables associated with PTB, and the elaboration of a large reference dataset might be a step forward to tackle the problem of PTB.

Further Evidence that an Episode of Premature Labor Is a Pathologic State: Involvement of the Insulin-Like Growth Factor System

INTRODUCTION

Approximately 47% of women with an episode of preterm labor deliver at term; however, their infants are at greater risk of being small for gestational age and for neurodevelopmental disorders. In these cases, a pathologic insult may disrupt the homeostatic responses sustaining pregnancy. We tested the hypothesis of an involvement of components of the insulin-like growth factor (IGF) system.

METHODS

This is a cross-sectional study in which maternal plasma concentrations of pregnancy-associated plasma protease (PAPP)-A, PAPP-A2, insulin-like growth factor-binding protein 1 (IGFBP-1), and IGFBP-4 were determined in the following groups of women: (1) no episodes of preterm labor, term delivery (controls, n = 100); (2) episode of preterm labor, term delivery (n = 50); (3) episode of preterm labor, preterm delivery (n = 100); (4) pregnant women at term not in labor (n = 61); and (5) pregnant women at term in labor (n = 61). Pairwise differences in maternal plasma concentrations of PAPP-A, PAPP-A2, IGFBP-1, and IGFBP-4 among study groups were assessed by fitting linear models on log-transformed data and included adjustment for relevant covariates. Significance of the group coefficient in the linear models was assessed via t-scores, with p < 0.05 deemed a significant result.

RESULTS

Compared to controls, (1) women with an episode of premature labor, regardless of a preterm or a term delivery, had higher mean plasma concentrations of PAPP-A2 and IGFBP-1 (each p < 0.05); (2) women with an episode of premature labor who delivered at term also had a higher mean concentration of PAPP-A (p < 0.05); and (3) acute histologic chorioamnionitis and spontaneous labor at term were not associated with significant changes in these analytes.

CONCLUSION

An episode of preterm labor involves the IGF system, supporting the view that the premature activation of parturition is a pathologic state, even in those women who delivered at term.

Should case management be considered a component of obstetrical interventions for pregnancies at risk of preterm birth?

Preterm birth remains the leading cause of morbidity and mortality among nonanomalous neonates in the United States. Unfortunately, preterm birth rates remain high despite current medical interventions such as progestogen supplementation and cerclage placement. Case management, which encompasses coordinated care aimed at providing a more comprehensive and supportive environment, is a key component in improving health and reducing costs in other areas of medicine. However, it has not made its way into the general lexicon and practice of obstetrical care. Case management intended for decreasing prematurity or ameliorating its consequences may include specialty clinics, social services, coordination of specialty services such as nutrition counseling, home visits or frequent phone calls by specially trained personnel, and other elements described herein. It is not currently included in nor is it advocated for as a recommended prematurity prevention approach in the American College of Obstetricians and Gynecologists or Society for Maternal-Fetal Medicine guidelines for medically indicated or spontaneous preterm birth prevention. Our review of existing evidence finds consistent reductions or trends toward reductions in preterm birth with case management, particularly among individuals with high a priori risk of preterm birth across systematic reviews, metaanalyses, and randomized controlled studies. These findings suggest that case management has substantial potential to improve the environmental, behavioral, social, and psychological factors with patients at risk of preterm birth.

Biomarkers for Preterm Delivery

Preterm birth occurring before the thirty-seventh gestational week complicates 4.5%-18% of pregnancies worldwide. The pathogenesis of spontaneous preterm delivery is not fully understood. Among the factors held to be responsible for its pathogenesis, the most emphasized is the inflammatory process. Studies in terms of the prediction of preterm delivery are basically divided into 3 categories: 1) Prediction in pregnant women who are asymptomatic and without risk factors, 2) Prediction in pregnant women who are asymptomatic and have risk factors, 3) Prediction in symptomatic pregnant women who have threatened preterm labour. In this chapter, the topic of biomarkers in relation to preterm delivery is discussed. The most commonly used markers in published studies are fetal fibronectin, cervical pIGFBP-1 and cervical length measurement by transvaginal ultrasound. For prediction in symptomatic pregnant women applying to the hospital with threatened preterm labour, the markers used are fetal fibronection, insulin-like growth factors (IGFs) and inflammatory markers. Preterm labour prediction with markers checked in the first and second trimesters are fetal fibronection, insulin-like growth factors (IGFs), micro RNAs, progesterone, circulating microparticles (CMPs), inflammatory markers, matrix metalloproteinases, aneuploidy syndrome screening test parameters and other hormones.

Prediction and prevention of preterm birth in pregnant women living with HIV on antiretroviral therapy

INTRODUCTION

The rate of spontaneous preterm-birth among pregnant women living with HIV on antiretroviral therapy (ART) is 3- to 4-fold higher when compared to HIV-negative women. The pathophysiology of preterm-birth related to HIV or ART remains unknown, especially as women living with HIV are often excluded from preterm birth studies.

AREAS COVERED

This review discusses the currently available evidence on the prediction and prevention of preterm-birth in pregnant women living with HIV. A review of the literature was conducted of primary articles between 2005 and 2021 measuring the association or lack thereof between combination ART and preterm birth, as well as of other predisposing factors to preterm birth in women living with HIV, including cervical length, vaginal microbiome, and cervico-vaginal biomarkers.

EXPERT OPINION

Further research into the effect of ART exposure on preterm-birth risk is critical, and development of preterm-birth predictive tools in this population should be a priority. Vaginal progesterone supplementation deserves further investigation as a therapeutic option to prevent recurrent preterm birth in pregnant women living with HIV. The ProSPAR study, a multicenter randomized controlled trial studying progesterone supplementation in pregnant women on protease inhibitor-based regimens, has been designed but is not yet recruiting patients.

Evaluation of a Maternal Plasma RNA Panel Predicting Spontaneous Preterm Birth and Its Expansion to the Prediction of Preeclampsia

Preterm birth is the principal contributor to neonatal death and morbidity worldwide. We previously described a plasma cell-free RNA panel that between 16 and 20 weeks of pregnancy had potential to predict spontaneous preterm birth (sPTB) ≤ 32 weeks caused by preterm labor (PTL) or preterm premature rupture of membranes (PPROM). The present study had three objectives: (1) estimate the RNA panel prognostic accuracy for PTL/PPROM ≤ 32 weeks in a larger series; (2) improve accuracy by adding clinical characteristics to the predictive model; and (3) examine the association of the RNA panel with preeclampsia. We studied 289 women from Memphis TN prospectively sampled 16.0-20.7 weeks and found: (1) PSME2 and Hsa-Let 7g were differentially expressed in cases of PTL/PPROM ≤ 32 weeks and together provided fair predictive accuracy with AUC of 0.76; (2) combining the two RNAs with clinical characteristics improved good predictive accuracy for PTL/PPROM ≤ 32 weeks (AUC 0.83); (3) NAMPT and APOA1 were differentially expressed in women with 'early-onset preeclampsia' (EOP) and together provided good predictive accuracy with AUC of 0.89; and (4) combining the two RNAs with clinical characteristics provided excellent predictive accuracy (AUC 0.96). Our findings suggest an underlying common pathophysiological relationship between PTL/PPROM ≤ 32 weeks and EOP and open inroads for the prognostication of high-risk pregnancies.

Better Estimation of Spontaneous Preterm Birth Prediction Performance through Improved Gestational Age Dating

The clinical management of pregnancy and spontaneous preterm birth (sPTB) relies on estimates of gestational age (GA). Our objective was to evaluate the effect of GA dating uncertainty on the observed performance of a validated proteomic biomarker risk predictor, and then to test the generalizability of that effect in a broader range of GA at blood draw. In a secondary analysis of a prospective clinical trial (PAPR; NCT01371019), we compared two GA dating categories: both ultrasound and dating by last menstrual period (LMP) (all subjects) and excluding dating by LMP (excluding LMP). The risk predictor's performance was observed at the validated risk predictor threshold both in weeks 191/7-206/7 and extended to weeks 180/7-206/7. Strict blinding and independent statistical analyses were employed. The validated biomarker risk predictor showed greater observed sensitivity of 88% at 75% specificity (increases of 17% and 1%) in more reliably dated (excluding-LMP) subjects, relative to all subjects. Excluding dating by LMP significantly improved the sensitivity in weeks 191/7-206/7. In the broader blood draw window, the previously validated risk predictor threshold significantly stratified higher and lower risk of sPTB, and the risk predictor again showed significantly greater observed sensitivity in excluding-LMP subjects. These findings have implications for testing the performance of models aimed at predicting PTB.

Human placental proteomics and exon variant studies link AAT/SERPINA1 with spontaneous preterm birth

BACKGROUND

Preterm birth is defined as live birth before 37 completed weeks of pregnancy, and it is a major problem worldwide. The molecular mechanisms that lead to onset of spontaneous preterm birth are incompletely understood. Prediction and evaluation of the risk of preterm birth is challenging as there is a lack of accurate biomarkers. In this study, our aim was to identify placental proteins that associate with spontaneous preterm birth.

METHODS

We analyzed the proteomes from placentas to identify proteins that associate with both gestational age and spontaneous labor. Next, rare and potentially damaging gene variants of the identified protein candidates were sought for from our whole exome sequencing data. Further experiments we performed on placental samples and placenta-associated cells to explore the location and function of the spontaneous preterm labor-associated proteins in placentas.

RESULTS

Exome sequencing data revealed rare damaging variants in SERPINA1 in families with recurrent spontaneous preterm deliveries. Protein and mRNA levels of alpha-1 antitrypsin/SERPINA1 from the maternal side of the placenta were downregulated in spontaneous preterm births. Alpha-1 antitrypsin was expressed by villous trophoblasts in the placenta, and immunoelectron microscopy showed localization in decidual fibrinoid deposits in association with specific extracellular proteins. siRNA knockdown in trophoblast-derived HTR8/SVneo cells revealed that SERPINA1 had a marked effect on regulation of the actin cytoskeleton pathway, Slit-Robo signaling, and extracellular matrix organization.

CONCLUSIONS

Alpha-1 antitrypsin is a protease inhibitor. We propose that loss of the protease inhibition effects of alpha-1 antitrypsin renders structures critical to maintaining pregnancy susceptible to proteases and inflammatory activation. This may lead to spontaneous premature birth.

Predictive RNA profiles for early and very early spontaneous preterm birth

BACKGROUND

Spontaneous preterm birth remains the main driver of childhood morbidity and mortality. Because of an incomplete understanding of the molecular pathways that result in spontaneous preterm birth, accurate predictive markers and target therapeutics remain elusive.

OBJECTIVE

This study sought to determine if a cell-free RNA profile could reveal a molecular signature in maternal blood months before the onset of spontaneous preterm birth.

STUDY DESIGN

Maternal samples (n=242) were obtained from a prospective cohort of individuals with a singleton pregnancy across 4 clinical sites at 12-24 weeks (nested case-control; n=46 spontaneous preterm birth <35 weeks and n=194 term controls). Plasma was processed via a next-generation sequencing pipeline for cell-free RNA using the Mirvie RNA platform. Transcripts that were differentially expressed in next-generation sequencing cases and controls were identified. Enriched pathways were identified in the Reactome database using overrepresentation analysis.

RESULTS

Twenty five transcripts associated with an increased risk of spontaneous preterm birth were identified. A logistic regression model was developed using these transcripts to predict spontaneous preterm birth with an area under the curve =0.80 (95% confidence interval, 0.72-0.87) (sensitivity=0.76, specificity=0.72). The gene discovery and model were validated through leave-one-out cross-validation. A unique set of 39 genes was identified from cases of very early spontaneous preterm birth (<25 weeks, n=14 cases with time to delivery of 2.5±1.8 weeks); a logistic regression classifier on the basis of these genes yielded an area under the curve=0.76 (95% confidence interval, 0.63-0.87) in leave-one-out cross validation. Pathway analysis for the transcripts associated with spontaneous preterm birth revealed enrichment of genes related to collagen or the extracellular matrix in those who ultimately had a spontaneous preterm birth at <35 weeks. Enrichment for genes in insulin-like growth factor transport and amino acid metabolism pathways were associated with spontaneous preterm birth at <25 weeks.

CONCLUSION

Second trimester cell-free RNA profiles in maternal blood provide a noninvasive window to future occurrence of spontaneous preterm birth. The systemic finding of changes in collagen and extracellular matrix pathways may serve to identify individuals at risk for premature cervical remodeling, with growth factor and metabolic pathways implicated more often in very early spontaneous preterm birth. The use of cell-free RNA profiles has the potential to accurately identify those at risk for spontaneous preterm birth by revealing the underlying pathophysiology, creating an opportunity for more targeted therapeutics and effective interventions.

Is there a maternal blood biomarker that can predict spontaneous preterm birth prior to labour onset? A systematic review

INTRODUCTION

The ability to predict spontaneous preterm birth (sPTB) prior to labour onset is a challenge, and it is currently unclear which biomarker(s), may be potentially predictive of sPTB, and whether their predictive power has any utility. A systematic review was conducted to identify maternal blood biomarkers of sPTB.

METHODS

This study was conducted according to PRISMA protocol for systematic reviews. Four databases (MEDLINE, EMBASE, CINAHL, Scopus) were searched up to September 2021 using search terms: "preterm labor", "biomarker" and "blood OR serum OR plasma". Studies assessing blood biomarkers prior to labour onset against the outcome sPTB were eligible for inclusion. Risk of bias was assessed based on the Newcastle Ottawa scale. Increased odds of sPTB associated with maternal blood biomarkers, as reported by odds ratios (OR), or predictive scores were synthesized. This review was not prospectively registered.

RESULTS

Seventy-seven primary research articles met the inclusion criteria, reporting 278 unique markers significantly associated with and/or predictive of sPTB in at least one study. The most frequently investigated biomarkers were those measured during maternal serum screen tests for aneuploidy, or inflammatory cytokines, though no single biomarker was clearly predictive of sPTB based on the synthesized evidence. Immune and signaling pathways were enriched within the set of biomarkers and both at the level of protein and gene expression.

CONCLUSION

There is currently no known predictive biomarker for sPTB. Inflammatory and immune biomarkers show promise, but positive reporting bias limits the utility of results. The biomarkers identified may be more predictive in multi-marker models instead of as single predictors. Omics-style studies provide promising avenues for the identification of novel (and multiple) biomarkers. This will require larger studies with adequate power, with consideration of gestational age and the heterogeneity of sPTB to identify a set of biomarkers predictive of sPTB.

Evaluating the diagnosis and treatment of Chlamydia trachomatis and Neisseria gonorrhoeae in pregnant women to prevent adverse neonatal consequences in Gaborone, Botswana: protocol for the Maduo study

BACKGROUND

Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) are extremely common sexually transmitted infections (STIs) that are associated with adverse birth and neonatal outcomes, and the risk of vertical transmission of CT and NG during delivery is high. The majority of CT and NG infections are asymptomatic and missed by the standard of care in most countries (treatment based on symptoms). Thus, it is likely that missed maternal CT and NG infections contribute to preventable adverse health outcomes among women and children globally. This study aims to assess the effectiveness of CT and NG testing for asymptomatic pregnant women to prevent adverse neonatal outcomes, understand the inflammatory response linking CT and NG infections to adverse neonatal outcomes, and conduct an economic analysis of the CT and NG testing intervention.

METHODS

The Maduo ("results" in Setswana) is a prospective, cluster-controlled trial in Gaborone, Botswana to compare a near point-of-care CT and NG testing and treatment intervention implemented in "study clinics" with standard antenatal care (World Health Organization-endorsed "syndromic management" strategy based on signs and symptoms without laboratory confirmation) implemented in "standard of care clinics" among asymptomatic pregnant women. The primary outcome is vertical transmission of CT/NG infection. Secondary outcomes include preterm birth (delivery < 37 completed weeks of gestation) and/or low birth weight (< 2500 g). The trial will also evaluate immunological and inflammatory markers of adverse neonatal outcomes, as well as the costs and cost-effectiveness of the intervention compared with standard care.

DISCUSSION

The Maduo study will improve our understanding of the effectiveness and cost-effectiveness of CT and NG testing among asymptomatic pregnant women. It will also increase knowledge about the CT/NG-related immune responses that might drive adverse neonatal outcomes. Further, results from this study could encourage expansion of STI testing during antenatal care in low resource settings and improve maternal and neonatal health globally.

TRIAL REGISTRATION

This trial is registered with ClinicalTrials.gov (Identifier NCT04955717, First posted: July 9, 2021)).

Clinical and economic evaluation of a proteomic biomarker preterm birth risk predictor: cost-effectiveness modeling of prenatal interventions applied to predicted higher-risk pregnancies within a large and diverse cohort

OBJECTIVES

Preterm birth occurs in more than 10% of U.S. births and is the leading cause of U.S. neonatal deaths, with estimated annual costs exceeding $25 billion USD. Using real-world data, we modeled the potential clinical and economic utility of a prematurity-reduction program comprising screening in a racially and ethnically diverse population with a validated proteomic biomarker risk predictor, followed by case management with or without pharmacological treatment.

METHODS

The ACCORDANT microsimulation model used individual patient data from a prespecified, randomly selected sub-cohort (N = 847) of a multicenter, observational study of U.S. subjects receiving standard obstetric care with masked risk predictor assessment (TREETOP; NCT02787213). All subjects were included in three arms across 500 simulated trials: standard of care (SoC, control); risk predictor/case management comprising increased outreach, education and specialist care (RP-CM, active); and multimodal management (risk predictor/case management with pharmacological treatment) (RP-MM, active). In the active arms, only subjects stratified as higher risk by the predictor were modeled as receiving the intervention, whereas lower-risk subjects received standard care. Higher-risk subjects' gestational ages at birth were shifted based on published efficacies, and dependent outcomes, calibrated using national datasets, were changed accordingly. Subjects otherwise retained their original TREETOP outcomes. Arms were compared using survival analysis for neonatal and maternal hospital length of stay, bootstrap intervals for neonatal cost, and Fisher's exact test for neonatal morbidity/mortality (significance, p < .05).

RESULTS

The model predicted improvements for all outcomes. RP-CM decreased neonatal and maternal hospital stay by 19% (p = .029) and 8.5% (p = .001), respectively; neonatal costs' point estimate by 16% (p = .098); and moderate-to-severe neonatal morbidity/mortality by 29% (p = .025). RP-MM strengthened observed reductions and significance. Point estimates of benefit did not differ by race/ethnicity.

CONCLUSIONS

Modeled evaluation of a biomarker-based test-and-treat strategy in a diverse population predicts clinically and economically meaningful improvements in neonatal and maternal outcomes.

AI aided analysis on saliva crystallization of pregnant women for accurate estimation of delivery date and fetal status

Saliva contains similar molecular components to serum. Analysis of saliva can provide important diagnostic information about the body. Here we report an artificial intelligence (AI) aided home-based method that can let pregnant women perform daily monitoring on their pregnant status and accurate prediction on their delivery date by the pattern analysis of their salivary crystals. The method was developed based on the information obtained from our investigation on the saliva samples of 170 pregnant women about the correlation of the salivary crystal pattern with pregnant age and fetal status. It demonstrated that the patterns of salivary crystallization could act as indicators of the pregnant age, fetal state, and some medical conditions of pregnant women. On this basis, with the aid of AI recognition and analysis of the fractal dimension and some characteristic crystals in the salivary crystallization, we performed estimation on the delivery date in both quantitative and qualitative manners. The accuracy of the prediction on 15 pregnant women was satisfactory: 100 % delivering in the predicted week, 93.3 % within the estimated three days, and 86.7 % on the day as the prediction. We also developed a simple smartphone-based AI-aided salivary crystal imaging and analysis device as an auxiliary means to let pregnant women monitor their fetal status daily at home and predict their delivery date with adequate accuracy.

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.

Performance of a validated spontaneous preterm delivery predictor in South Asian and Sub-Saharan African women: a nested case control study

OBJECTIVES

To address the disproportionate burden of preterm birth (PTB) in low- and middle-income countries, this study aimed to (1) verify the performance of the United States-validated spontaneous PTB (sPTB) predictor, comprised of the IBP4/SHBG protein ratio, in subjects from Bangladesh, Pakistan and Tanzania enrolled in the Alliance for Maternal and Newborn Health Improvement (AMANHI) biorepository study, and (2) discover biomarkers that improve performance of IBP4/SHBG in the AMANHI cohort.

STUDY DESIGN

The performance of the IBP4/SHBG biomarker was first evaluated in a nested case control validation study, then utilized in a follow-on discovery study performed on the same samples. Levels of serum proteins were measured by targeted mass spectrometry. Differences between the AMANHI and U.S. cohorts were adjusted using body mass index (BMI) and gestational age (GA) at blood draw as covariates. Prediction of sPTB < 37 weeks and < 34 weeks was assessed by area under the receiver operator curve (AUC). In the discovery phase, an artificial intelligence method selected additional protein biomarkers complementary to IBP4/SHBG in the AMANHI cohort.

RESULTS

The IBP4/SHBG biomarker significantly predicted sPTB < 37 weeks (n = 88 vs. 171 terms ≥ 37 weeks) after adjusting for BMI and GA at blood draw (AUC= 0.64, 95% CI: 0.57-0.71, p < .001). Performance was similar for sPTB < 34 weeks (n = 17 vs. 184 ≥ 34 weeks): AUC = 0.66, 95% CI: 0.51-0.82, p = .012. The discovery phase of the study showed that the addition of endoglin, prolactin, and tetranectin to the above model resulted in the prediction of sPTB < 37 with an AUC= 0.72 (95% CI: 0.66-0.79, p-value < .001) and prediction of sPTB < 34 with an AUC of 0.78 (95% CI: 0.67-0.90, p < .001).

CONCLUSION

A protein biomarker pair developed in the U.S. may have broader application in diverse non-U.S. populations.

Clinical Validation of a Proteomic Biomarker Threshold for Increased Risk of Spontaneous Preterm Birth and Associated Clinical Outcomes: A Replication Study

Preterm births are the leading cause of neonatal death in the United States. Previously, a spontaneous preterm birth (sPTB) predictor based on the ratio of two proteins, IBP4/SHBG, was validated as a predictor of sPTB in the Proteomic Assessment of Preterm Risk (PAPR) study. In particular, a proteomic biomarker threshold of -1.37, corresponding to a ~two-fold increase or ~15% risk of sPTB, significantly stratified earlier deliveries. Guidelines for molecular tests advise replication in a second independent study. Here we tested whether the significant association between proteomic biomarker scores above the threshold and sPTB, and associated adverse outcomes, was replicated in a second independent study, the Multicenter Assessment of a Spontaneous Preterm Birth Risk Predictor (TREETOP). The threshold significantly stratified subjects in PAPR and TREETOP for sPTB (p = 0.041, p = 0.041, respectively). Application of the threshold in a Kaplan-Meier analysis demonstrated significant stratification in each study, respectively, for gestational age at birth (p < 001, p = 0.0016) and rate of hospital discharge for both neonate (p < 0.001, p = 0.005) and mother (p < 0.001, p < 0.001). Above the threshold, severe neonatal morbidity/mortality and mortality alone were 2.2 (p = 0.0083,) and 7.4-fold higher (p = 0.018), respectively, in both studies combined. Thus, higher predictor scores were associated with multiple adverse pregnancy outcomes.

Proteomic identification of novel plasma biomarkers associated with spontaneous preterm birth in women with preterm labor without infection/inflammation

Objective

We sought to identify plasma biomarkers associated with spontaneous preterm birth (SPTB, delivery within 21 days of sampling) in women with preterm labor (PTL) without intra-amniotic infection/inflammation (IAI) using label-free quantitative proteomic analysis, as well as to elucidate specific protein pathways involved in these cases.

Methods

This was a retrospective cohort study comprising 104 singleton pregnant women with PTL (24–32 weeks) who underwent amniocentesis and demonstrated no evidence of IAI. Analysis of pooled plasma samples collected from SPTB cases and term birth (TB) controls (n = 10 for each group) was performed using label-free quantitative mass spectrometry for proteome profiling in a nested case-control study design. Eight candidate proteins of interest were validated by ELISA-based assay and a clot-based assay in the total cohort.

Results

Ninety-one proteins were differentially expressed (P < 0.05) in plasma samples obtained from SPTB cases, of which 53 (58.2%) were upregulated and 38 (41.8%) were downregulated when compared to TD controls. A validation study confirmed that plasma from women who delivered spontaneously within 21 days of sampling contained significantly higher levels of coagulation factor Ⅴ and lower levels of S100 calcium binding protein A9 (S100A9), especially the former which was independent of baseline variables. The top-ranked pathways related to the 91 differentially expressed proteins were liver-X-receptor/retinoid X receptor (RXR) activation, acute phase response signaling, farnesoid X receptor/RXR activation, coagulation system, and complement system.

Conclusions

Proteomic analyses in this study identified potential novel biomarkers (i.e., coagulation factor V and S100A9) and potential protein pathways in plasma associated with SPTB in the absence of IAI in women with PTL. The present findings provide novel insights into the molecular pathogenesis and therapeutic targets specific for idiopathic SPTB.

Cost-Effectiveness of a Proteomic Test for Preterm Birth Prediction

Background

Preterm birth (PTB) carries increased risk of short- and long-term health problems as well as higher healthcare costs. Current strategies using clinically accepted maternal risk factors (prior PTB, short cervix) can only identify a minority of singleton PTBs.

Objective

We modeled the cost-effectiveness of a risk-screening-and-treat strategy versus usual care for commercially insured pregnant US women without clinically accepted PTB risk factors. The risk-screening-and-treat strategy included use of a novel PTB prognostic blood test (PreTRM^®) in the 19th–20th week of pregnancy, followed by treatment with a combined regimen of multi-component high-intensity-case-management and pharmacologic interventions for the remainder of the pregnancy for women assessed as higher-risk by the test, and usual care in women without higher risk.

Methods

We built a cost-effectiveness model using a combined decision-tree/Markov approach and a US payer perspective. We modeled 1-week cycles of pregnancy from week 19 to birth (preterm or term) and assessed costs throughout the pregnancy, and further to 12-months post-delivery in mothers and 30-months in infants. PTB rates and costs were based on >40,000 mothers and infants from the HealthCore Integrated Research Database^® with birth events in 2016. Estimates of test performance, treatment effectiveness, and other model inputs were derived from published literature.

Results

In the base case, the risk-screening-and-treat strategy dominated usual care with an estimated 870 fewer PTBs (20% reduction) and $54 million less in total cost ($863 net savings per pregnant woman). Reductions were projected for neonatal intensive care admissions (10%), overall length-of-stay (7%), and births <32 weeks (33%). Treatment effectiveness had the strongest influence on cost-effectiveness estimates. The risk-screening-and-treat strategy remained dominant in the majority of probabilistic sensitivity analysis simulations and model scenarios.

Conclusion

Use of a novel prognostic test during pregnancy to identify women at risk of PTB combined with evidence-based treatment is estimated to reduce total costs while preventing PTBs and their consequences.

Using principal component analysis to examine associations of early pregnancy inflammatory biomarker profiles and adverse birth outcomes

OBJECTIVE

Inflammation as a risk factor for preterm birth is well-established. The primary objective of this analysis was to examine whether individual cytokines versus a composite indicator of mid-pregnancy inflammation are significantly associated with risk for adverse birth outcomes.

STUDY DESIGN

A multi-site prospective study was conducted in a socio-demographically diverse cohort of 610 pregnant participants. At a study visit between 12 and 20 6/7 weeks' gestation, low-grade inflammation was measured via log-transformed serum concentrations of the biomarkers IFN-γ, IL-10, IL-13, IL-6, IL-8, TNF-α, and CRP. Principal component analysis (PCA) was used to identify underlying dimensions of inflammatory activity from the seven biomarkers measured. Gestational age and birth weight at delivery were obtained from medical chart review. The associations between inflammatory profiles and birth outcomes were assessed via linear and logistic regression models. Results were compared with those from individual inflammatory biomarkers, and model fit was assessed using Akaike's Information Criterion (AIC).

RESULTS

Principal component analysis analysis yielded a two-factor solution, with the first factor (IF1) composed of IL-8, IL-10, IL-13, IFN-ɣ, and TNF-α, and the second factor (IF2) containing IL-6 and CRP. When adjusted for race, education, BMI, smoking status, gestational age at time of blood draw, and study site, a one standard deviation (SD) increase in IF1 remained significantly associated with a decrease in standardized gestational age (β = -.13, 95% CI: -.21, -.05) and an increase in odds of preterm delivery (OR = 1.46, 95% CI: 1.13, 1.88) (Table 3). A one SD increase in IF2 was similarly associated with a decrease in standardized gestational age at delivery (β = -.13, 95% CI: -.23, -.04) and an increase in odds of preterm delivery (OR: 1.46, 95% CI: 1.04, 2.05). Neither IF1 nor IF2 was associated with measures of fetal growth. AIC identified that IL-6 was a slightly better fit for length of gestation compared to either composite measure, though all performed similarly.

CONCLUSION

Independent of known sociodemographic risk factors, an elevated mid-pregnancy inflammatory profile was associated with a nearly 50% increase in odds of preterm delivery. The composite performed similarly to IL-6. These results suggest that maternal low-grade inflammation is a risk factor for preterm delivery, and that mid-pregnancy inflammatory biomarkers may be useful in predicting risk for preterm delivery.

Prediction and Prevention of Preterm Birth: A Prospective, Randomized Intervention Trial

OBJECTIVE

 The study aimed to determine if a program of mid-trimester serum proteomics screening of women at low risk for spontaneous preterm birth (sPTB) and the use of a PTB risk-reduction protocol in those whose results indicated an increased risk of sPTB would reduce the likelihood of sPTB and its sequelae.

STUDY DESIGN

 Prospective comparison of birth outcomes in singleton pregnancies with mid-trimester cervical length ≥2.5 cm and at otherwise low risk for sPTB randomized to undergo or not undergo mid-trimester serum proteomics screening for increased risk of sPTB (NCT03530332). Screen-positive women were offered a group of interventions aimed at reducing the risk of spontaneous PTB. The primary outcome was the rate of sPTB <37 weeks, and secondary outcomes were gestational age at delivery, total length of neonatal stay, and NICU length of stay (LOS). Unscreened and screen-negative women received standard care. The adaptive study design targeted a sample size of 3,000 to 10,000 women to detect a reduction in sPTB from 6.4 to 4.7%. Due to limited resources, the trial was stopped early prior to data unblinding.

RESULTS

 A total of 1,191 women were randomized. Screened and unscreened women were demographically similar. sPTB <37 weeks occurred in 2.7% of screened women and 3.5% of controls (p = 0.41). In the screened compared with the unscreened group, there were no between-group differences in the gestational age at delivery, total length of neonatal stay, and NICU LOS. However, the NICU LOS among infants admitted for sPTB was significantly shorter (median = 6.8 days, interquartile range [IQR]: 1.8-8.0 vs. 45.5 days, IQR: 34.6-79.0; p = 0.005).

CONCLUSION

 Mid-trimester serum proteomics screening of women at low risk for sPTB and the use of a sPTB risk-reduction protocol in screen-positive patients did not significantly reduce the rate of sPTB compared with women not screened, though the trial was underpowered thus limiting the interpretation of negative findings. Infants in the screened group had a significantly shorter NICU LOS, a difference likely due to a reduced number of infants in the screened group that delivered <35 weeks.

KEY POINTS

· Mid-trimester serum proteomics screening of women at low risk for sPTB and the use of a sPTB risk-reduction protocol in screen-positive patients did not significantly reduce the rate of sPTB, though the trial was underpowered.. · NICU LOS following sPTB was significantly shortened among women who underwent screening and risk-reduction management.. · The use of serum biomarkers may contribute to a practical strategy to reduce sPTB sequelae..

Prediction and Prevention of Spontaneous Preterm Birth: ACOG Practice Bulletin, Number 234

Preterm birth is among the most complex and important challenges in obstetrics. Despite decades of research and clinical advancement, approximately 1 in 10 newborns in the United States is born prematurely. These newborns account for approximately three-quarters of perinatal mortality and more than one half of long-term neonatal morbidity, at significant social and economic cost (1-3). Because preterm birth is the common endpoint for multiple pathophysiologic processes, detailed classification schemes for preterm birth phenotype and etiology have been proposed (4, 5). In general, approximately one half of preterm births follow spontaneous preterm labor, about a quarter follow preterm prelabor rupture of membranes (PPROM), and the remaining quarter of preterm births are intentional, medically indicated by maternal or fetal complications. There are pronounced racial disparities in the preterm birth rate in the United States. The purpose of this document is to describe the risk factors, screening methods, and treatments for preventing spontaneous preterm birth, and to review the evidence supporting their roles in clinical practice. This Practice Bulletin has been updated to include information on increasing rates of preterm birth in the United States, disparities in preterm birth rates, and approaches to screening and prevention strategies for patients at risk for spontaneous preterm birth.

Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset

Estimating the time of delivery is of high clinical importance because pre- and postterm deviations are associated with complications for the mother and her offspring. However, current estimations are inaccurate. As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is key to understanding these physiological transitions and identifying predictive biomarkers of delivery. Here, a longitudinal study was conducted in 63 women who went into labor spontaneously. More than 7000 plasma analytes and peripheral immune cell responses were analyzed using untargeted mass spectrometry, aptamer-based proteomic technology, and single-cell mass cytometry in serial blood samples collected during the last 100 days of pregnancy. The high-dimensional dataset was integrated into a multiomic model that predicted the time to spontaneous labor [R = 0.85, 95% confidence interval (CI) [0.79 to 0.89], P = 1.2 × 10^-40, N = 53, training set; R = 0.81, 95% CI [0.61 to 0.91], P = 3.9 × 10^-7, N = 10, independent test set]. Coordinated alterations in maternal metabolome, proteome, and immunome marked a molecular shift from pregnancy maintenance to prelabor biology 2 to 4 weeks before delivery. A surge in steroid hormone metabolites and interleukin-1 receptor type 4 that preceded labor coincided with a switch from immune activation to regulation of inflammatory responses. Our study lays the groundwork for developing blood-based methods for predicting the day of labor, anchored in mechanisms shared in preterm and term pregnancies.

AACC Guidance Document on Laboratory Testing for the Assessment of Preterm Delivery

Identifying women with preterm labor who will go on to deliver prematurely is crucial to improving outcomes for mother and baby and for saving healthcare resources. Even among those with symptoms, the number of women who deliver preterm is low, and thus the low positive predictive value (PPV) and high negative predictive value (NPV) associated with available biomarkers does not substantially reduce the uncertainty of the clinical diagnosis. While there is some promise in the use of fetal fibronectin (fFN), interleukin 6 (IL-6), or placental alpha microglobulin 1 (PAMG-1) for predicting preterm birth (PTB), their use is unlikely to provide considerable clinical value in populations with a low prevalence. To provide real clinical benefit, a biomarker must demonstrate a high PPV to allow identification of the minority of symptomatic women who will deliver prematurely. As none of the currently available biomarkers exhibit this performance characteristic, we do not recommend their routine clinical use in populations with a pre-test probability of PTB of <5%. Limiting biomarker testing to only high-risk women identified on the basis of cervical length or other characteristics will increase the pre-testprobability in the tested population, thereby improving PPV. PAMG-1 is associated with a higher PPV than fFN and may show clinical utility in populations with a higher pre-test probability, but further work is required to conclusively demonstrate improved outcomes in this patient group.

Proteomic identification of biomarkers in maternal plasma that predict the outcome of rescue cerclage for cervical insufficiency

Objective

We sought to identify plasma protein biomarkers that are predictive of the outcome of rescue cerclage in patients with cervical insufficiency.

Methods

This retrospective cohort study included 39 singleton pregnant women undergoing rescue cerclage for cervical insufficiency (17–25 weeks) who gave plasma samples. Three sets of pooled plasma samples from controls (cerclage success, n = 10) and cases (cerclage failure, n = 10, defined as spontaneous preterm delivery at <33 weeks) were labeled with 6-plex tandem mass tag (TMT) reagents and analyzed by liquid chromatography-tandem mass spectrometry. Differentially expressed proteins between the two groups were selected from the TMT-based quantitative analysis. Multiple reaction monitoring-mass spectrometry (MRM-MS) analysis was further used to verify the candidate proteins of interest in patients with cervical insufficiency in the final cohort (n = 39).

Results

From MRM-MS analysis of the 40 proteins showing statistically significant changes (P < 0.05) from the TMT-based quantitative analysis, plasma IGFBP-2, PSG4, and PGLYRP2 levels were found to be significantly increased, whereas plasma MET and LXN levels were significantly decreased in women with cerclage failure. Of these, IGFBP-2, PSG4, and LXN levels in plasma were independent of cervical dilatation. A multiple-biomarker panel was developed for the prediction of cerclage failure, using a stepwise regression procedure, which included the plasma IGFBP-2, PSG4, and LXN (area under the curve [AUC] = 0.916). The AUC for this multiple-biomarker panel was significantly greater than the AUC for any single biomarker included in the multi-biomarker model.

Conclusions

Proteomic analysis identified useful and independent plasma biomarkers (IGFBP-2, PSG4, and LXN; verified by MRM) that predict poor pregnancy outcome following rescue cerclage. Their combined analysis in a multi-biomarker panel significantly improved predictability.

Prediction of neonatal morbidity and very preterm delivery using maternal steroid biomarkers in early gestation

Background

Preterm delivery is a common pregnancy complication that can result in significant neonatal morbidity and mortality. Limited tools exist to predict preterm birth, and none to predict neonatal morbidity, from early in pregnancy. The objective of this study was to determine if the progesterone metabolites 11-deoxycorticosterone (DOC) and 16-alpha hydroxyprogesterone (16α-OHP), when combined with patient demographic and obstetric history known during the pregnancy, are predictive of preterm delivery-associated neonatal morbidity, neonatal length of stay, and risk for spontaneous preterm delivery prior to 32 weeks’ gestation.

Methods and findings

We conducted a cohort study of pregnant women with plasma samples collected as part of Building Blocks of Pregnancy Biobank at the Indiana University School of Medicine. The progesterone metabolites, DOC and 16α-OHP, were quantified by mass spectroscopy from the plasma of 58 pregnant women collected in the late first trimester/early second trimester. Steroid levels were combined with patient demographic and obstetric history data in multivariable logistic regression models. The primary outcome was composite neonatal morbidity as measured by the Hassan scale. Secondary outcomes included neonatal length of stay and spontaneous preterm delivery prior to 32 weeks’ gestation. The final neonatal morbidity model, which incorporated antenatal corticosteroid exposure and fetal sex, was able to predict high morbidity (Hassan score ≥ 2) with an area under the ROC curve (AUROC) of 0.975 (95% CI 0.932, 1.00), while the model without corticosteroid and fetal sex predictors demonstrated an AUROC of 0.927 (95% CI 0.824, 1.00). The Hassan score was highly correlated with neonatal length of stay (p<0.001), allowing the neonatal morbidity model to also predict increased neonatal length of stay (53 [IQR 22, 76] days vs. 4.5 [2, 31] days, above and below the model cut point, respectively; p = 0.0017). Spontaneous preterm delivery prior to 32 weeks’ gestation was also predicted with an AUROC of 0.94 (95% CI 0.869, 1.00).

Conclusions

Plasma levels of DOC and 16α-OHP in early gestation can be combined with patient demographic and clinical data to predict significant neonatal morbidity, neonatal length of stay, and risk for very preterm delivery, though validation studies are needed to verify these findings. Early identification of pregnancies at risk for preterm delivery and neonatal morbidity allows for timely implementation of multidisciplinary care to improve perinatal outcomes.

Maternal metabolic profiling to assess fetal gestational age and predict preterm delivery: a two-centre retrospective cohort study in the US

OBJECTIVES

The aim of this study was to develop a single blood test that could determine gestational age and estimate the risk of preterm birth by measuring serum metabolites. We hypothesised that serial metabolic modelling of serum analytes throughout pregnancy could be used to describe fetal gestational age and project preterm birth with a high degree of precision.

STUDY DESIGN

A retrospective cohort study.

SETTING

Two medical centres from the USA.

PARTICIPANTS

Thirty-six patients (20 full-term, 16 preterm) enrolled at Stanford University were used to develop gestational age and preterm birth risk algorithms, 22 patients (9 full-term, 13 preterm) enrolled at the University of Alabama were used to validate the algorithms.

OUTCOME MEASURES

Maternal blood was collected serially throughout pregnancy. Metabolic datasets were generated using mass spectrometry.

RESULTS

A model to determine gestational age was developed (R²=0.98) and validated (R²=0.81). 66.7% of the estimates fell within ±1 week of ultrasound results during model validation. Significant disruptions from full-term pregnancy metabolic patterns were observed in preterm pregnancies (R²=-0.68). A separate algorithm to predict preterm birth was developed using a set of 10 metabolic pathways that resulted in an area under the curve of 0.96 and 0.92, a sensitivity of 0.88 and 0.86, and a specificity of 0.96 and 0.92 during development and validation testing, respectively.

CONCLUSIONS

In this study, metabolic profiling was used to develop and test a model for determining gestational age during full-term pregnancy progression, and to determine risk of preterm birth. With additional patient validation studies, these algorithms may be used to identify at-risk pregnancies prompting alterations in clinical care, and to gain biological insights into the pathophysiology of preterm birth. Metabolic pathway-based pregnancy modelling is a novel modality for investigation and clinical application development.

Identifying potential biomarkers related to pre-term delivery by proteomic analysis of amniotic fluid

We sought to identify biomarkers in the amniotic fluid (AF) and specific signaling pathways related to spontaneous preterm delivery (SPTD, < 34 weeks) in women with preterm labor (PTL) without intra-uterine infection/inflammation (IUI). This was a retrospective cohort study of a total of 139 PTL women with singleton gestation (24 + 0 to 32 + 6 weeks) who underwent amniocentesis and who displayed no evidence of IUI. A nested case-control was conducted using pooled AF samples (n = 20) analyzed via label-free liquid chromatography-tandem mass spectrometry. In the total cohort, an ELISA validation study was performed for seven candidate proteins of interest. Proteomic analysis identified 77 differentially expressed proteins (DEPs, P < 0.05) in the AF from SPTD cases compared to term delivery controls. ELISA validation confirmed that women who had an SPTD before 34 weeks had significantly independently lower levels of VEGFR-1 and higher levels of lipocalin-2 and the Fc fragment of IgG binding protein in the AF. Five principle pathways associated with the 77 DEPs were identified, including glycolysis, gluconeogenesis, and iron homeostasis. The proteomic analysis data of AFs from women with PTL identified several novel biomarkers and specific protein pathways related to SPTD in the absence of IUI.