Abstract

Approximately 1 in 4 pregnant women in the United States undergo labor induction. The onset and establishment of labor, particularly induced labor, is a complex and dynamic process influenced by multiple endocrine, inflammatory, and mechanical factors as well as obstetric and pharmacological interventions. The duration from labor induction to the onset of active labor remains unpredictable. Moreover, prolonged labor is associated with severe complications for the mother and her offspring, most importantly chorioamnionitis, uterine atony, and postpartum hemorrhage. While maternal immune system adaptations that are critical for the maintenance of a healthy pregnancy have been previously characterized, the role of the immune system during the establishment of labor is poorly understood. Understanding maternal immune adaptations during labor initiation can have important ramifications for predicting successful labor induction and labor complications in both induced and spontaneous types of labor. The aim of this study was to characterize labor-associated maternal immune system dynamics from labor induction to the start of active labor. Serial blood samples from fifteen participants were collected immediately prior to labor induction (baseline) and during the latent phase until the start of active labor. Using high-dimensional mass cytometry, a total of 1,059 single-cell immune features were extracted from each sample. A multivariate machine-learning method was employed to characterize the dynamic changes of the maternal immune system after labor induction until the establishment of active labor. A cross-validated linear sparse regression model (least absolute shrinkage and selection operator, LASSO) predicted the minutes since induction of labor with high accuracy (R = 0.86, p = 6.7e-15, RMSE = 277 min). Immune features most informative for the model included STAT5 signaling in central memory CD8+ T cells and pro-inflammatory STAT3 signaling responses across multiple adaptive and innate immune cell subsets. Our study reports a peripheral immune signature of labor induction, and provides important insights into biological mechanisms that may ultimately predict labor induction success as well as complications, thereby facilitating clinical decision-making to improve maternal and fetal well-being.

Highlights

  • Induction of labor is the pharmacological initiation of cervical change and uterine contractions before their spontaneous onset in the presence or absence of ruptured membranes [1]

  • Using a 46-parameter mass cytometry assay (Supplementary Table 1), a total of 1,059 single-cell immune features were extracted from each sample including the frequencies of 46 immune cell subsets representing major innate and adaptive populations, endogenous intracellular activities of 11 signaling proteins, and capacities of each cell subset to respond to a receptor-specific immune challenge [lipopolysaccharide (LPS)] (Figure 1B)

  • The results suggest that the clinical transitions between labor induction, latent labor and active labor are echoed by peripheral immune responses that can be detected in the maternal blood

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Summary

Introduction

Induction of labor is the pharmacological initiation of cervical change and uterine contractions before their spontaneous onset in the presence or absence of ruptured membranes [1]. The time interval between labor induction, the establishment of latent labor (defined as regular contractions leading to cervical changes from 0 to 6 cm) and the onset of active labor (defined as cervical dilatation ≥ 6 cm with regular uterine contractions ≤ 3 min apart) remains unpredictable. Induction complications associated with failure of successful labor initiation, prolonged labor progression, subsequent labor arrest, development of chorioamnionitis or failed induction resulting in cesarean delivery [7,8,9], are difficult to predict. A better understanding of the biological events temporally associated with the progression from labor induction until the establishment of active labor is much needed to identify predictive biomarkers of successful labor induction and prevent clinical complications resulting from failed induction

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